The Inhibitor of DNA Binding Family Regulates the Prognosis of Ovarian Cancer

The Inhibitor of DNA Binding Family Regulates the Prognosis of Ovarian Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Primary research The Inhibitor of DNA Binding Family Regulates the Prognosis of Ovarian Cancer Quan Zhou, Ye-dong Mei Mei, Yang Huai-jie, Tao Ya-ling This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-38061/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 May, 2021 Read the published version in Future Oncology → Version 1 posted You are reading this latest preprint version Abstract Background: The inhibitor of DNA binding or differentiation ( ID ) protein family contributes to the carcinogenesis and progression of various cancers. However, its mechanistic role in tumor initiation and progression of ovarian cancer (OC) has remained unclear. Methods: We used the Oncomine, GEPIA, Kaplan-Meier plotter, cBioPortal, SurvExpress, PROGgene V2 server, TIMERdatabase, and FunRich to evaluate the expression and predictive prognostic value of individual IDs members’ mRNA in patients with OC. Results: Our results revealed that the mRNA transcripts of all ID family members were markedly downregulated in OC compared to normal tissue. Aberrant expression of ID 1/3/4 correlated with cancer aggressiveness and clinical in OC patients. The prognostic value of ID members was also explored within the subtypes, pathological stages, clinical stages, and TP53 mutational status. The group with a low risk IDs showed a relatively good overall survival (OS) in comparison to the high-risk group. In contrast, the expression level of IDs was significantly associated with the levels of infiltrating B cells and macrophages. Finally, enrichment analysis showed that ID co-expressed genes were involved in ID- , c-MYC , TNF- , and Wnt signaling pathways. Conclusion: These results indicate that ID1/3/4 may be exploited as promising prognostic biomarkers and therapeutic targets in OC patients. Obstetrics & Gynecology ID gene family ovarian cancer prognostic value bioinformatics analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Key among the genes that encode helix-loop-helix (HLH) family of transcription factors is the inhibitor of DNA binding or differentiation (ID ), abundant in stem and progenitor cells ( 1 ). To date, ID proteins are encoded by four ID genes in the ID family in vertebrates: ID1-4 , all of which encode the corresponding ( 1 , 2 ). As negative regulators of basic HLH proteins, ID proteins are potent suppressors of typical HLH proteins, and this is achieved via the formation of non-functional heterodimers ( 3 ). Recently, numerous studies have reported aberrant expression of ID proteins in different human malignancies. It has also been associated with advanced tumor metastasis and development of multiple carcinomas ( 1 , 2 , 4 ). In addition, ID proteins are involved in virtually all tumor-associated processes, including cell differentiation, cycle regulation, angiogenesis, stemness, epithelial-mesenchymal transition, chemoresistance, and immunomodulation ( 1 – 3 , 5 ). More importantly, findings from prior studies reveal the regulation of ID proteins expression and function via ID -specific antisense oligonucleotides, small interfering RNAs, or nanocomplexes, which in turn affect micro-angiogenesis and apoptosis in various types of tumor cells ( 4 , 6 , 7 ). Taken together, ID proteins may be promising and effective predictive biomarkers and anti-angiogenic or anti-apoptotic agents for cancer management. The incidence of OC has been on the rise; in 2018, it was estimated that 184,799 million deaths and 295,414 new cases of OC were recorded worldwide ( 8 ). This situation is expected to worsen globally. Although standard tumor reduction surgery combined with chemotherapy, and recent application of targeted therapies have significantly improved the survival chances of OC patients, this condition still shows a 5-year survival rate below 40% ( 9 ). The poor prognosis and high mortality rate are largely a result of less sensitive and suboptimal tools for early diagnosis, high recurrence following surgery resection, distant metastasis, and resistance to systemic chemotherapy and molecular drugs ( 10 , 11 ). Therefore, effective prognostic markers and promising molecular therapeutic strategies for OC patients are highly desirable. Recently, it was reported that several ID proteins are aberrantly expressed in OC samples in comparison with normal tissues, and the level of ID is closely related to poor differentiation, advanced stage, enhanced malignant potential, and worse clinical pathological features of OC ( 12 – 14 ) ( 15 ). Elevated expression levels of ID1 and ID3 were found to be a strong predicator of shorter survival in OC ( 14 , 15 ). These reports show that ID could be a promoter of OC progression and tumorigenesis. More importantly, animal experiments showed that partial loss function or knockdown of ID1 and ID3 decreased proliferation, anchorage-independent growth, increased apoptosis, and reduced survival in various human cancer cells ( 16 , 17 ). There is reason to believe that IDs may be novel therapeutic genes and potentially versatile therapeutic targets for OC. Regrettably, the distinct roles of the individual ID proteins in OC are not fully known. In our study, we comprehensively analyzed the relationships between the four ID subtypes and OC based on several large databases such as cBioPortal, Kaplan-Meier plotter (KM plotter), Gene Expression Profiling Interactive Analysis (GEPIA), SurvExpress, TIMER, and FunRich, to determine the expression patterns, genetic alterations, immune infiltrations, molecular function, and prognostic signature of ID proteins in OC. Materials And Methods Ethics statement All protocols and experiments in this study conformed to the Declaration of Helsinki and were approved by the Academic Committee of the First People’s Hospital of Yichang. The data used in this study were obtained from published reports. Oncomine analysis The Oncomine ( www.oncomine.org ) contains massive cancer-related microarray datasets of DNA or RNA sequences. It is frequently used in genome-wide expression studies ( 18 ). Herein, it was employed to reveal the transcriptional profile of ID family members in patient specimens from different cancer types and healthy controls. Moreover, the Student’s t-test was used to compare the expression levels between the two groups. Significant expressions were those with fold-change = 1.5; P -value = 0.001. GEPIA dataset analysis GEPIA ( http://gepia.cancer-pku.cn ) provides a platform for analyzing RNA sequencing dataset covering on 9,736 tumors and 8,587 normal specimens in the Genotype-tissue Expression dataset (GTEx) and the Cancer Genome Atlas (TCGA) projects. GEPIA is highly interactive and enables users to adjust various functions, such as dimensionality reduction analysis, correlation analysis, survival analysis, tumor/normal differential expression analysis, similar gene detection, and profiling plotting based on the pathological stage or type of cancer ( 19 ). TCGA and cBioPortal analysis TCGA ( http://cancergenome.nih.gov/ ) comprises pathological and sequencing datasets for 30 types of cancers ( 20 ). On the other hand, cBioPortal is a freely-accessible cancer genomic web platform ( http://www.cbioportal.org/ ), which may be used for integrative analysis and multi-functional visualization for clinical profiles and data of cancer genomics ( 21 ). In this study, the dataset “Ovarian Serous Cystadenocarcinoma (TCGA, Provisional)” was used. The frequency of ID family gene alterations, copy number variance, and mRNA expression z-scores (RNA Seq V2 RSEM) were assessed using cBioPortal in line with the guidelines provided on the cBioPortal webpage. Functional enrichment analysis FunRich is an open access gene interaction network analysis tool and enables comprehensive functional annotation of various biological processes ( 22 ). In the present study, processes and pathways enrichment analyses of ID family proteins were performed using FunRich to identify genes associated with ID expression. In addition, the Gene Ontology (GO) terms for cellular component (CC), molecular function (MF), and biological process (BP) categories, as well as the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of the 50 closely related genes significantly associated with ID expression were performed through FunRich. Kaplan–Meier plotter analysis KM plotter ( www.kmplot.com ) platform to estimate the prognostic performance of ID mRNA expression. This database constitutes the survival information and gene expression datasets of 1,816 patients with OC ( 23 ). We then subcategorized patients into low and high expression groups on the basis of the median expression value, and assessed the progression-free survival (PFS), and overall survival (OS) of OC patients employed the Kaplan-Meier survival plot, with log-rank p-value, a hazard ratio (HR) with 95% confidence intervals (CI). Further sub-classification was performed; TP53 mutation status, histological subtypes and pathological subtypes, foe subgroup analysis. SurvExpress analysis The SurvExpress ( http://bioinformatica.mty.itesm.mx/SurvExpress ), a web-based resource, is commonly used for risk assessment and survival multivariate analysis using gene expression data ( 24 ). This database was employed herein for risk assessment and survival analysis to identify key ID gene signatures in OC. A prognostic index established was utilized to group patient samples into high or low-risk groups in reference to the median value of the index by employing the maximized risk algorithm. The log-rank p- value, log-rank test with HR with 95% CI was utilized for statistical analysis of the equality of survival curves. PROGgeneV2 analysis The PROGgeneV2 is a web based tool available at www. compbio.iupui.edu/proggene. It contains data from 134 cohorts from 21 cancer types based on the Gene Expression Omnibus (GEO), the European Bioinformatics Institute (EBI) and TCGA. In the present study, PROGgeneV2 was used to validate the relationship between the expression of IDs and prognostic outcomes in OC. The HRs and the corresponding 95% CIs were used to assess the prognostic efficiency of IDs on OC. HRs and 95% CIs for OS were directly obtained from PROGgeneV2. Different data sets were meta-synthesized using STATE 14.0 software (State Corporation, College Station, TX, USA). The heterogeneity among studies was estimated with the v2-based Q-test and Higgins’ I 2 statistic. A p-value 30% indicated significant heterogeneity, and the random-effects model was used; otherwise, the fixed-effects model was used. TIMER analysis The extent of immune infiltration among various types is often estimated using the TIMER ( https://cistrome.shinyapps.io/timer platform) ( 25 ). This tool was therefore utilized to assess the correlation of IDs expression with six immune infiltrates (DCs, macrophages, neutrophils, CD4 + T cells, B cells, and CD8 + T cells) in OC using Spearman’s correlation analysis. On the basis of this correlation module, we established scatter plots between a pair of user-defined genes for each type of cancer, and the expression of each gene was presented with log2 RSEM. Results Mapping the mRNA expression profile to IDs in OC samples The human genome contains genes encoding four ID family members. The Oncomine database was employed to compare the expression pattern of ID genes in cancer samples and normal tissue samples, and the results are presented in Fig. 1 and Table 1 . Notably, cancer samples displayed the lowest expression of ID1 mRNA among the three datasets ( 26 , 27 ). It was reported that ID1 is decreased in ovarian serous adenocarcinoma when compared to normal samples in the Yoshihara datasets ( 27 ) and Hendrix ( 26 ). In the TCGA dataset also, ID1 also downregulated in ovarian serous cystadenocarcinoma in comparison to normal samples, with a fold change of -2.901. Similarly, the transcriptional level of ID2 was significantly downregulated in patients with OC in the three datasets ( 26 – 28 ). In the Hendrix ( 26 ) and Yoshihara dataset ( 27 ), ID2 was significantly downregulated with fold changes of -1.523 and − 6.008, respectively, in ovarian serous adenocarcinoma while it was downregulated in ovarian serous surface papillary carcinoma with a fold change of -11.999 in the Welsh dataset ( 28 ). A similar trend was also found for ID3 . The ID3 mRNA expression was markedly lower in multiple types of ovarian cancer compared to that in normal tissues in the Welsh ( 28 ), Yoshihara ( 27 ), and Hendrix ( 26 ) datasets. The mRNA level of ID4 was significantly lower in ovarian carcinoma and ovarian serous cystadenocarcinoma than that in the normal samples in the Bonome ( 29 ) and TCGA datasets. Table 1 The mRNA levels of IDs in between ovarian normal tissues and different types of OC (ONCOMINE). ID family Types of Ovarian cancer vs. Norma t-test Fold change P value Ref PMID ID1 Ovarian Serous Adenocarcinoma vs. Normal -9.123 -1.531 7.32E-10 Hendrix Ovarian 16452189 Ovarian Serous Cystadenocarcinoma vs. Normal -6.753 -2.901 6.20E-05 TCGA Ovarian - Ovarian Serous Adenocarcinoma vs. Normal -6.084 -4.067 9.16E-8 Yoshihara Ovarian 19486012 ID2 Ovarian Serous Adenocarcinoma vs. Normal -13.880 -1.523 1.11E-16 Hendrix Ovarian 16452189 Ovarian Serous Surface Papillary Carcinoma vs. Normal -8.342 -11.999 7.84E-09 Welsh Ovarian 11158614 Ovarian Serous Adenocarcinoma vs. Normal -10.929 -6.008 3.25E-15 Yoshihara Ovarian 19486012 ID3 Ovarian Serous Surface Papillary Carcinoma vs. Normal -7.992 -6.756 1.46E-07 Welsh Ovarian 11158614 Ovarian Serous Adenocarcinoma vs. Normal -11.731 -9.796 6.38E-15 Yoshihara Ovarian 19486012 Ovarian Clear Cell Adenocarcinoma vs. Normal -8.933 -1.946 4.14E-06 Hendrix Ovarian 16452189 Ovarian Serous Adenocarcinoma vs. Normal -9.049 -1.785 8.25E-06 Hendrix Ovarian 16452189 ID4 Ovarian Carcinoma vs. Normal -15.628 -7.350 2.44E-11 Bonome Ovarian 18593951 Ovarian Serous Cystadenocarcinoma vs. Normal -6.289 -3.362 1.22E-04 TCGA Ovarian - We also investigated the mRNA expression levels of IDs in OC compared to that in normal tissue using the GEPIA dataset. As shown in Fig. 2 A - D , ID1-ID3 mRNA transcripts were relatively low in OC tissues compared to normal ovarian tissues, however, only the levels of ID2 and ID3 showed marked differences between OC and normal tissues. In addition, analysis of the GEPIA dataset indicated that the mRNA level of ID was not related to the different stages of OC (Fig. 2 E - H). Genetic alteration rate of IDs and co-expressed genes in OC patient samples Gene variations of IDs in OC were examined on the cBioPortal. As shown in Figure. 3, a total of 594 patients and 606 samples from the TCGA provisional dataset of ovarian serous carcinoma were analyzed. The genetic alteration rates of ID1 , ID2 , ID3 , and ID4 were 10, 6, 3, and 15%, respectively (Fig. 3 A). We further explored the impact of IDs genetic alterations on the prognosis of OC. Notably, no significant association between the prognosis of OC with ID gene alteration or without alteration based on the TCGA provisional dataset ( p values, 0.404 and 0.759, Fig. 3 B, C). Functional enrichment analysis of IDs and co-expressed genes in patients with OC We subsequently compiled a list of the expressed IDs and the 50 closest co-expressed genes predicted by analyzing GO and KEGG in Funrich. As shown in Fig. 4 , the BP of IDs and their co-expressed genes were dramatically concentrated in processes related to regulation of nucleic acid metabolism, nucleobase, nucleoside nucleotide and regulation of gene expression, peptidolysis, proteolysis, organogenesis, and regulation of immune response (Fig. 4 A). The MF of these genes were mainly transcription regulator activity, protease inhibitor activity, protein binding, antigen binding, and protein serine/threonine phosphatase activity (Fig. 4 B). For the CC, the genes were correlated with nuclear membrane, protein kinase, CK2 complex, nucleus, junctional sarcoplasmic reticulum membrane, and connexon complex (Fig. 4 C). Additionally, the KEGG analysis revealed significant enrichment of genes in ID-, c-MYC-, TNF- , and Wnt signaling pathways (Fig. 4 D). Prognostic value of IDs in OC samples We subsequently assessed the correlation of individual IDs with different clinical pathology parameters such as pathological grade, clinical stage, and TP53 mutation status of OC. The results presented in Fig. 5 and Table 2 indicates that high mRNA expression of ID1 and ID3 predicted worse PFS and OS in serous OC patients. In contrast, the mRNA level of ID4 predicted favorable OS. In endometrioid OC, the expression of ID1 and ID3 showed a strong correlation with good PFS. As shown in Table 3 , in OC patients with pathological grade III, elevated ID1 and ID3 correlated with poor PFS and OS. In patients with pathological grade II, ID3 correlated with poor PFS and OS. In addition, upregulated ID1 was linked to poor OS and upregulated ID2 correlated with poor OS in pathological grade I patients. As shown in Table 4 , in clinical stage III patients, increased expression of ID1 and ID3 was associated with worse OS, and elevated ID2 was associated with poor PFS. In clinical stage IV OC patients, elevated ID1 was associated with worse OS and high ID3 expression was related to poor OS and PFS in this subgroup. As shown in Table 5 , Moreover, high expression of ID1 and ID3 was related was associated with worse PFS and OS in OC patients carrying mutated TP53, and high ID1 , ID2 , and ID3 expression was associated with worse OS in OC patients with wild-type TP53. Table 2 Correlation of the mRNA expression level of IDs with overall or different pathological histology OC prognosis (Kaplan-Meier plotter). ID family Affymetrix ID Pathological histology OS PFS Cases HR 95% CI p -value Cases HR 95% CI p -value ID1 208937_s_at Overall 1656 1.23 1.08–1.41 0.0023 1453 1.09 0.96–1.24 0.1700 Serous 1207 1.23 1.04–1.46 0.0170 1104 1.29 1.12–1.49 0.0005 Endometrioid 37 0 0-inf 0.0180 51 0.18 0.07–0.48 0.0001 ID2 213931_at Overall 1656 0.87 0.75–1.01 0.0590 1435 1.18 1.04–1.34 0.0110 Serous 1207 1.13 0.97–1.33 0.1100 1104 1.18 1.02–1.36 0.0300 Endometrioid 37 0 0-inf 0.1300 51 0.46 0.18–1.18 0.0990 ID3 207826_s_at Overall 1656 1.35 1.16–1.56 0.0001 1435 1.19 1.05–1.35 0.0076 Serous 1207 1.42 1.19–1.69 0.0001 1104 1.34 1.14–1.57 0.0004 Endometrioid 37 0 0-inf 0.0710 51 0.21 0.07–0.59 0.0011 ID4 209291_at Overall 1656 0.82 0.71–0.95 0.0071 1435 1.09 0.96–1.23 0.1900 Serous 1207 0.84 0.72–0.98 0.0240 1104 0.89 0.76–1.04 0.1300 Endometrioid 37 0 0-inf 0.0920 51 4.28 0.97–18.93 0.0380 Table 3 Correlation of the mRNA expression level of IDs with different pathological grade OC prognosis (Kaplan-Meier plotter). ID family Affymetrix ID Pathological grades OS PFS Cases HR 95% CI p -value Cases HR 95% CI p -value ID1 208937_s_at Ⅰ 56 1.78 0.65–4.83 0.2500 37 1.74 0.48–6.32 0.4000 Ⅱ 324 1.5 1.06–2.12 0.0200 256 1.2 0.89–1.61 0.2200 Ⅲ 1015 1.23 1.04–1.45 0.0140 837 1.25 1.06–1.48 0.0078 Ⅳ 20 2.05 0.76–5.53 0.1500 19 - - - ID2 213931_at Ⅰ 56 3.38 1.18–9.72 0.0170 37 2.48 0.76–8.08 0.1200 Ⅱ 324 1.12 0.81–1.55 0.4800 256 1.36 1.02–1.82 0.0380 Ⅲ 1015 0.93 0.78–1.1 0.3700 837 1.09 0.93–1.29 0.2900 Ⅳ 20 0.35 0.1–1.23 0.0880 19 - - - ID3 207826_s_at Ⅰ 56 1.6 0.53–4.79 0.4000 37 3.7 0.48–28.49 0.1800 Ⅱ 324 1.5 1.11–2.04 0.0087 256 1.42 1.02-2.00 0.0390 Ⅲ 1015 1.3 1.08–1.57 0.0063 837 1.33 1.11–1.61 0.0023 Ⅳ 20 1.69 0.64–4.44 0.2800 19 - - - ID4 209291_at Ⅰ 56 0.62 0.24–1.59 0.3200 37 0.35 0.11–1.08 0.0570 Ⅱ 324 1.16 0.85–1.58 0.3400 256 1.26 0.93–1.71 0.3100 Ⅲ 1015 0.85 0.75-1 0.0480 837 0.91 0.75–1.09 0.3000 Ⅳ 20 3.06 0.91–10.34 0.0610 19 - - - Table 4 Correlation of the mRNA expression level of IDs with different clinical stage OC prognosis (Kaplan-Meier plotter). ID family Affymetrix ID clinical stage OS PFS Cases HR 95% CI p -value Cases HR 95% CI p -value ID1 208937_s_at Ⅰ 74 2.9 0.93–9.09 0.0550 96 2.21 0.62–7.92 0.2100 Ⅱ 61 1.89 0.58–6.2 0.2800 67 0.45 0.18–1.09 0.0700 Ⅲ 1044 1.45 1.23–1.7 0.0000 919 1.24 1.07–1.45 0.0056 Ⅳ 176 0.78 0.52–1.16 0.2100 162 1.91 1.30–2.80 0.0007 ID2 213931_at Ⅰ 74 0.46 0.14–1.52 0.1900 96 0.44 0.15–1.32 0.1300 Ⅱ 61 2.76 0.92–8.28 0.0590 67 2.29 1.1–4.76 0.0220 Ⅲ 1044 0.87 0.73–1.02 0.0840 919 1.19 1.01–1.41 0.0380 Ⅳ 176 0.71 0.48–1.05 0.0880 162 0.71 0.48–1.05 0.0810 ID3 207826_s_at Ⅰ 74 3.78 0.49–29.37 0.1700 96 0.51 0.17–1.53 0.2200 Ⅱ 61 0.54 0.17–1.73 0.2900 67 0.45 0.18–1.08 0.0670 Ⅲ 1044 1.48 1.23–1.78 0.0000 919 1.26 1.08–1.47 0.0031 Ⅳ 176 1.67 1.12–2.49 0.0110 162 1.62 1.10–2.38 0.0140 ID4 209291_at Ⅰ 74 2.3 0.5–10.5 0.2700 96 0.52 0.18–1.48 0.2100 Ⅱ 61 2.32 0.52–10.42 0.2600 67 2.23 0.99–4.99 0.0470 Ⅲ 1044 0.83 0.69–1.01 0.0560 919 0.91 0.77–1.08 0.2800 Ⅳ 176 1.47 0.94–2.31 0.0920 162 1.53 0.96–2.43 0.0690 Table 5 Correlation of the mRNA expression level of IDs with different TP53 mutation status OC prognosis (Kaplan-Meier plotter). ID family Affymetrix ID TP53 mutation OS PFS Cases HR 95% CI p-value Cases HR 95% CI p-value ID1 208937_s_at mutated 506 1.38 1.1–1.74 0.0052 483 1.47 1.17–1.84 0.0007 wild type 94 1.74 1.01-3 0.0450 84 0.68 0.39–1.2 0.1900 ID2 213931_at mutated 506 1.21 0.96–1.52 0.0990 483 0.85 0.68–1.06 0.1500 wild type 94 2.12 1.13–3.97 0.0170 84 1.34 0.76–2.37 0.3200 ID3 207826_s_at mutated 506 1.51 1.17–1.94 0.0012 483 1.37 1.07–1.76 0.0120 wild type 94 1.99 1.13–3.51 0.0160 84 1.72 0.98–3.02 0.0560 ID4 209291_at mutated 506 0.83 0.66–1.04 0.1000 483 1.32 1.04–1.68 0.0240 wild type 94 0.56 0.3–1.03 0.0570 84 1.47 0.84–2.6 0.1800 Prognostic value of ID signatures in patients with OC The SurvExpress platform was used to establish a prognostic index based on ID expression. A total of 1,609 patients from three ovarian cancer datasets with large sample sizes were analyzed using the SurvExpress platform. High/low risk groups were categorized by prognostic risk algorithm in each dataset. The survival analysis and Kaplan–Meier plotter between high risk (red) and low risk (green) groups and the heat map of the expression of IDs in each dataset are shown in Fig. 6 . The results showed that the expression of each ID member was distributed between high and low risk groups. More importantly, the low risk group displayed a significantly good OS in comparison with the high risk group in the ovarian Meta-base: 6 cohorts with 22 K genes (HR = 1.44, 95% CI = 1.19–1.75), ovarian serous cystadenocarcinoma TCGA (HR = 1.28, 95% CI = 1.02–1.60) and OV – TCGA - ovarian serous cystadenocarcinoma June 2016 (HR = 1.40, 95% CI = 1.01–1.95) datasets, respectively. Validate the prognostic value of IDs in patients with OC in different data sets We applied PROGgeneV2 to validate the he prognostic value of IDs in patients with OC in different data sets. The results showed that seventeen data sets with 2,585 subjects reported the data of relationship between ID1 and OS in patients with OC. The pooled result showed that increased ID1 expression was significantly correlated with worse OS (HR: 1.08, 95% CI: 1.01–1.14, p = 0.017), with significant heterogeneity (I 2 : 36.5%, Ph = 0.065) (Fig. 7 A). In addition, the same 17 data sets reported data on the association between ID2 and OS in patients with OC. Meta-analysis of these 17 sets showed that there was no significant correlation between the expression of ID2 and the OS of OC patients (HR: 1.02, 95% CI: 0.96–1.09, p = 0. 0.617), and with no significant heterogeneity (I 2 : 10.3%, Ph = 0.334) (Fig. 7 B). Simultaneously, there were 18 data sets containing 2,663 OC patients the prognostic value of ID3 and ID4 in OS. As shown in Fig. 7 C, the elevated ID3 expression was significantly associated with unfavorable OS (HR: 1.10, 95% CI: 1.04–1.16, p < 0.001) and no significant heterogeneity was observed (I 2 : 11.5%, Ph = 0.317). At last, the results presented in Fig. 7 D indicates that increased ID4 expression was positively correlated with better OS (HR: 0.90, 95% CI: 0.84–0.97, p < 0.001), with extreme heterogeneity (I 2 : 55.0%, Ph = 0.003). Immune infiltration analysis of IDs in patients with OC We explored the correlation between ID expression and immune infiltration levels in OC using correlation modules in TIMER. As shown in Fig. 8 , ID1 expression level showed a significant negative correlation with infiltrating levels of B cells ( r = -0.252, p = 2.07e-08) and DCs ( r = -0.113, p = 1.30e-02). In contrast, it showed a positive correlation with infiltrating levels of macrophages ( r = 0.15, p = 9.95e-04). ID2 level showed a negative correlation with infiltrating levels of B cells ( r = -0.110, p = 1.55e-02), and positive correlation with infiltrating levels of macrophages ( r = 0.150, p = 9.95e-04) and neutrophils ( r = 0.097, p = 3.39e-02) in OC. For ID3 , there was a significant correlation with infiltrating levels of B cells ( r = -0.184, p = 5.18e-5) and macrophages ( r = 0.217, p = 1.68e-06). In addition, there was a negative correlation with infiltrating levels of macrophages ( r = -0.098, p = 3.10e-02) and neutrophils ( r = -0.14, p = 2.15e-03) in OC. Discussion Key among the genes that encode the helix-loop-helix (HLH) family of transcription factors is the ID , abundant in stem and progenitor cells ( 1 ). To date, it is known that ID proteins are encoded by four ID genes in the ID family in vertebrates: ID1-4 , all of which encode the corresponding four ID family members ( 1 , 2 ). These genes are located in different chromosomes and show inconsistent expression profiles and functions ( 30 ). Emerging evidence suggests that ID proteins play vital roles in tumorigenesis in several types of malignancies mediated by their ability to regulate cell-cycle, cell differentiation, epithelial-mesenchymal transition, chemoresistance, and immunomodulation ( 1 – 3 , 5 ). Yet, the specific roles of the four ID members in OC are obscure. This study evaluated the prognostic value and expression of ID family genes by investigating various large databases. Our study presents the first silico and bioinformatics analysis of the ID family. ID1 is the most widely characterized component of the HLH transcription factor family ( 31 ). Studies show that the molecular functions of ID-1 included induction of cell proliferation, increasing DNA synthesis, and interaction with various oncogenes ( 32 ). Aberrant expression of the ID1 protein has not only been detected in multiple types of human cancers, but is also correlated with tumor stages and clinical outcome ( 33 , 34 ). Furthermore, ectopic expression of ID1 in human cancer cells increases serum-independent cell growth, enhances primary tumor G1/S phase formation and metastatic potential, and protects tumor cells against apoptosis. Conversely, inhibition or inhibition of ID1 in human cancer cells has been shown to suppress cell proliferation, induce cellular senescence, induce G2/M cell-cycle arrest, reduce tumor colony formation or multiplicity, and increase lifespan ( 35 , 36 ). In OC, Schindl et. al. found that ID1 expression correlates with the malignant potential of OC and is correlated with aggressive behavior, differentiation of tumor cells, and clinical prognosis ( 12 ). Several studies have found that increased ID1 may promote cancer cell proliferation and enhance endothelial progenitor cell angiogenesis through regulation or facilitation of EGFR and TGFβ1 expression, and activation NF-κB/MMP-2 and PI3K/Akt signaling pathways in OC cells ( 6 , 37 – 39 ). In addition, the study by Li ZD et al demonstrated that apigenin can suppress the expression of ID1 , resulting in inhibition of tumorigenesis in human OC A2780 cells ( 40 ). Thus, ID1 represents a promising therapeutic target for OC. In our study, the Oncomine and GEPIA datasets indicated that the expression of ID1 was suppressed in human OC. The Kaplan–Meier plotter and PROGgeneV2 analysis revealed a high mRNA expression of ID1 , and this was correlated with poor OS in all OC patients. These data reflect the heterogeneity of ID1 expression in mRNA and protein levels, and point to the oncogenic function of ID1 . ID2 belongs to the HLH transcription factor family, which promotes proliferation and invasive growth in multiple solid cancers, e.g., hepatocellular cancer, breast cancer, thyroid cancer, pancreatic cancer, and OC ( 1 , 41 ). Like ID1 , several studies have shown that ID2 promotes the proliferation of human cancer cells by inhibiting cell apoptosis, enhancing cancer stemness of pre-malignant cells, or mediating m6A modifications ( 42 – 44 ). Conversely, reduced ID2 expression increases apoptosis, reduces cell proliferation, and decreases tumor initiation in human cancer cells ( 16 , 45 ). However, currently there are very few reports on ID2 and OC development in the literature. An earlier study showed the ID2 gene as a candidate for inherited predisposition to breast and ovarian cancer in Jewish women ( 46 ). Moreover, the study by Meng et. al. reported that elevated ID2 expression in ERα-positive epithelial tumor cells promoted the invasiveness of cells via a non-canonical pathway independent forming dimers with basic helix-loop-helix factors ( 47 ). In this study, ID2 mRNA expression was found to be lower in OC samples than in normal ones, and elevated ID2 expression was strongly related to poor PFS in all patients with OC. Prognostic analysis in patients with OC in different data sets, however, overall effect did not show any significant correlation between ID2 expression and OS. The oncogenic effects, predictive value, and potential molecular targets of ID2 in OC remain to be investigated further. ID3 , associated with HLH transcription factors, has been recognized as a key regulator of cell development, senescence, differentiation, proliferation, stemness, and migration ( 1 , 48 ). It has been confirmed that ID3 and ID1 can compensate for each other and have similar biological functions ( 5 ). Previous studies have demonstrated that aberrant expression of ID3 is associated with advanced tumor stage and poor prognosis in many types of human cancers. In animal experiments, although Id1+/-Id3-/- or Id1-/-Id3+/- mice grow to adulthood, they are unsuitable to implanted tumor xenografts because these mice lack the capacity to recruit hematopoietic precursors and endothelial ( 48 , 49 ). Furthermore, double knockdown of ID1 and ID3 has been shown to decrease proliferation and anchorage-independent growth, increase apoptosis, and reduce survival in various human cancer cells ( 16 , 17 ). More importantly, ID3 knockdown improved the survival duration of animals in a seeding model of medulloblastoma. It also compromised the progression of leptomeningeal seeding and the growth of primary tumors ( 50 ). Elsewhere, it was recognized that BMP4 signaling is active in ovarian cancer cells where it maintains ID3 expression. This was confirmed by the use of BMP4 blocker Noggin, which decreased endogenous ID3 expression ( 51 ). In this study, we also demonstrated that the expression of ID3 in OC tissues was lower than that in normal tissues, and ID3 overexpression was associated with reduced OS and PFS in OC patients. Because ID3 undergoes epigenetic inhibition in multiple cancers, it is therefore thought to be a tumor suppressor. In comparison with the other ID proteins, ID4 possesses a polyproline domain at its C terminus and a polyalanine domain at its N terminus. Although it harbors the HLH domain, ID4 does not display similar expression and function with D protein ( 5 ). Numerous studies have shown that the phenotypic changes and molecular pathways regulated by ID4 are, in general, not like those regulated by ID1 , ID2 , and ID3 . Interestingly, ID4 seems to function as a tumor suppressor in multiple cancers and as a tumor promoter in a small subset of cancers ( 30 , 52 , 53 ). The proposed tumor-suppressing effects of ID4 draw on observations that ID4 undergoes epigenetic silencing in several solid cancers such as esophageal, gastric, pancreatic, colorectal, cholangiocarcinoma and lung cancer. However, ID4 has been reported to be elevated in some small cancers, such as OC, prompting researchers to re-classify it as a tumor promoter ( 4 , 52 , 54 , 55 ). Mice deficient in ID4 develop some types of cancers in their lifetime, and the lack of ID4 results in follicular dysplasia and increased atretic follicles due to decreased estrogen biosynthesis ( 30 ). It is worth noting that a recent study showed that administration to mice harboring an ovarian tumor with an ID4 -specific tumor-penetrating nanocomplex was capable of suppressing the growth of established tumors and significantly improved survival ( 7 ). In the current study, unlike ID1, ID2 , and ID3 , the expression of ID4 was higher in OC tissues than that in normal tissues, and high ID4 expression was significantly correlated with better OS in OC patients, thereby indicating its tumor promoter role in OC. We also attempted to examine the mechanisms and roles of members of the ID family, we also used the cBioPortal database to explore the mutations in the ID family. The results showed that the genetic alteration rate of the ID family members varied from 3% to 15% for individual genes based on the TCGA provisional dataset, however, there was no significant association between the prognosis of OC with ID gene alteration or without alteration. We then constructed a network of ID family members and 50 of the closest co-expressed genes. The results of the functional analysis indicated that these genes were mainly enriched in tumor-related pathways, including the ID -, c-MYC -, TNF -, and Wnt signaling pathways. In addition, two major highlights of this study were the ID signature and immune infiltration analysis. In the ID signature analysis, the prognostic values of ID signature in patients with OC were evaluated in three datasets based on the SurvExpress platform. The method overcomes the problem single gene with the expression optimal cutoff for prognostic analysis cannot fully reflect the optimal differentiation of survival benefits and performance of potential biomarkers. In the immune infiltration analysis, we explored the correlation between IDs expression with six immune infiltration levels in OC via correlation modules in TIMER. Our results showed that ID expression showed a strong correlation with infiltrating levels of B cells and macrophages, which further confirmed that the biological role of ID may be associated with immune regulation. However, the underlying molecular mechanisms and regulation steps remain largely unexplored. Conclusions This study reveals that IDs exhibited diverse expression profiles between OC and normal samples. Aberrant expression of ID1/3/4 was correlated with cancer aggressiveness and prognosis in OC patients. The group with low risk ID signature presented a markedly good OS relative to the high-risk group. In contrast, the expression levels of IDs were significantly correlated with the levels of infiltrating B cells and macrophages. Finally, enrichment analysis showed that ID co-expressed genes were involved in ID- , c-MYC-, TNF- , and Wnt signaling pathways. These results indicate that ID1/3/4 may be exploited as promising prognostic biomarkers and therapeutic targets in OC patients. Abbreviations: ID, inhibitor of differentiation/DNA-binding; OC,ovarian cancer; HLH ,helix-loop-helix; GTEx, the Genotype-tissue Expression dataset; TCGA, the Cancer Genome Atlas; EBI, European Bioinformatics Institute; GO, Gene Ontology; CC, cellular component; MF, molecular function; BP, biological process; KEGG, Kyoto Encyclopedia of Genes and Genomes ; PFS, progression-free survival ; OS, overall survival; HR,hazard ratio ; CI, confidence intervals; GEPIA, Gene Expression Profiling Interactive Analysis. Declarations Acknowledgments We thank the Oncomine, GEPIA, Kaplan-Meier plotter, cBioPortal, SurvExpress, and TIMER for sharing the large amounts of data. Author contribution Q.Z., YD. M. and HJ. Y. designed the study. YD. M., HJ. Y. and YL.T.collected and performed data analysis and validation. Q.Z. and YL.T.wrote and edited the manuscript. Funding This study was supported by project grants from the Yichang Medical and Health Research Project (No.A17-301-12). 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Donzelli S, Milano E, Pruszko M, Sacconi A, Masciarelli S, Iosue I, et al. Expression of ID4 protein in breast cancer cells induces reprogramming of tumour-associated macrophages. Breast Cancer Res. 2018;20(1):59. Amaral LHP, Bufalo NE, Peres KC, Barreto IS, Campos A, Ward LS. ID Proteins May Reduce Aggressiveness of Thyroid Tumors. Endocr Pathol. 2019;30(1):24–30. Zhou JD, Zhang TJ, Li XX, Ma JC, Guo H, Wen XM, et al. Epigenetic dysregulation of ID4 predicts disease progression and treatment outcome in myeloid malignancies. J Cell Mol Med. 2017;21(8):1468–81. Supplementary Files ID.xlsx TableS1.docx Cite Share Download PDF Status: Published Journal Publication published 01 May, 2021 Read the published version in Future Oncology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-38061","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Primary research","associatedPublications":[],"authors":[{"id":726368,"identity":"c514d588-a164-449a-a29b-5b53a25b62f4","order_by":0,"name":"Quan Zhou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYDACCSjNL3+w8cEHAxs74rVIzmBuNpxRkJZMvBaDG+xt0jwfDjE2ENIhP7v5mMTbNrs8ydmNbdI2BgeYGdgPH92ATwvjnGNpknPbkov5ZQ42W+cY3OFj4ElLu4FPC7NEjpk0bxtz4syGxMbbOQbPmBkkeMzwamGDaKlP3HAgsUHawuAwYwMhLTwQLYcTN9xIbJJmIEaLhERasuWcc8cTZ/YcbDbsMUhLZiPkF/kZyQdvvCmrTuxnb3/44McfGzt+9sPH8GqBuA7FdwSVY2gZBaNgFIyCUYAOAHCASrftgyTyAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-6941-9887","institution":"First People's Hospital of Yichang","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Quan","middleName":"","lastName":"Zhou","suffix":""},{"id":726369,"identity":"67005435-c5af-408c-88ee-e118f2411c24","order_by":1,"name":"Ye-dong Mei Mei","email":"","orcid":"","institution":"the people's hospital of Wufeng county","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ye-dong","middleName":"Mei","lastName":"Mei","suffix":""},{"id":726370,"identity":"9aa295e1-20c3-4d65-a33b-29058f18c6f9","order_by":2,"name":"Yang Huai-jie","email":"","orcid":"","institution":"First People's Hospital of Yichang","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Huai-jie","suffix":""},{"id":726371,"identity":"d94d4f33-94be-4dba-aa8a-ecb55d7f28ab","order_by":3,"name":"Tao Ya-ling","email":"","orcid":"","institution":"First People's Hospital of Yichang","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Ya-ling","suffix":""}],"badges":[],"createdAt":"2020-06-26 18:23:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-38061/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-38061/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.2217/fon-2020-1006","type":"published","date":"2021-05-01T21:05:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":1444338,"identity":"134a5230-7733-4cbe-b052-02c507d4ebdb","added_by":"auto","created_at":"2020-06-29 13:47:03","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":573352,"visible":true,"origin":"","legend":"The mRNA levels of IDs in different types of cancers and OC (ONCOMINE). Note:The thresholds were restricted as follows: P value = 0.001; fold-change = 1.5; and data type, mRNA, respectively. (A) The mRNA levels of ID family members in different types of cancers. The graphic demonstrated the numbers of datasets with statistically significant mRNA over-expression (red) or down-expression (blue) of the target gene. (B)- (E) The mRNA levels of ID1-4 in human OC and normal tissue in four datasets, such as Hendrix Ovarian, Hendrix Ovarian, Welsh Ovarian, Bonome Ovarian, respectively.","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/Fig1.jpg"},{"id":1444339,"identity":"25494939-6d30-49be-9a60-7ce035538c86","added_by":"auto","created_at":"2020-06-29 13:47:04","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":342701,"visible":true,"origin":"","legend":"The mRNA expression levels of IDs in overall or subgroups of different stage OC patients (GEPIA database). Note: Box plots derived from gene expression data in GEPIA comparing expression of a specific ID family member in OC tissue and normal tissues, the p value was set up at 0.05. (A)- (D) The distribution of ID1-ID4 gene mRNA expression between OC tissue and normal tissues, respectively. (E)-(H) Boxplot showing relative expression of ID1-ID4 in OC patients in stages, 2, 3 or 4 using GEPIA, respectively. (*, P\u003c 0.05; **, P\u003c 0.01; ***, P \u003c 0.001).","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/Fig2.jpg"},{"id":1444340,"identity":"de296826-5369-41f6-9ac1-59ed62d92773","added_by":"auto","created_at":"2020-06-29 13:47:04","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1350718,"visible":true,"origin":"","legend":"Alteration frequency and prognostic value of IDs in OC (TCGA and cBioPortal). (A) OncoPrint visual summary of alteration on a query of ID family members. (B) Kaplan-Meier plots comparing OS in cases with/without ID family members gene alterations. (C) Kaplan-Meier plots comparing disease free survival (DFS) in cases with/without E2F family members alterations. ","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/Fig3.jpg"},{"id":1444341,"identity":"faeebe1d-bd23-45e9-9cf1-32ce894ce3aa","added_by":"auto","created_at":"2020-06-29 13:47:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1677265,"visible":true,"origin":"","legend":"TheGene Ontology and KEGG enrichment analysis of IDs in OC (Funrich database). (A)-(D) The biological pathways and Gene Ontology (GO) terms for biological process (BP), molecular function (MF), cellular component (CC) categories and KEGG pathway enrichment analyses were performed through FunRich, respectively.","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/Fig4.jpg"},{"id":1444342,"identity":"7339419e-00ef-47f2-90ac-1ec2075652d3","added_by":"auto","created_at":"2020-06-29 13:47:05","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1055740,"visible":true,"origin":"","legend":"The prognostic value of the individual IDs (KM Plotter database). (A)- (D) The OS Kaplan-Meier survival curves of ID1-4 are plotted for OC patients by KM Plotter database; (E)- (H) The PFS Kaplan-Meier survival curves of ID1-4 are plotted for OC patients by KM Plotter database, respectively.","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/fig5.jpg"},{"id":1444343,"identity":"89990095-6f96-47b6-9d25-fc5cb65f616a","added_by":"auto","created_at":"2020-06-29 13:47:05","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2692876,"visible":true,"origin":"","legend":"The genes signature of IDs in OC (SurvExpress database). (A)-(B) The Kaplan-Meier survival curves and heat maps of ID1-4 were explored in high risk and low risk group for ovarian Meta-base: 6 cohorts 22K genes; (C)-(D)The Kaplan-Meier survival curves and heat maps of ID1-4 were explored in high risk and low risk group forovarian serous cystadenocarcinoma TCGA; and (E)-(F) The Kaplan-Meier survival curves and heat maps of ID1-4 were explored in high risk and low risk groupfor OV - TCGA-ovarian serous cystadenocarcinoma June 2016 datasets, respectively. ","description":"","filename":"Fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/Fig6.jpg"},{"id":1444344,"identity":"202adef8-068a-428a-9a4e-7498f117de97","added_by":"auto","created_at":"2020-06-29 13:47:05","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":819017,"visible":true,"origin":"","legend":"Validate the prognostic value of IDs in patients with OC in different data sets.\n(A)- (B) Validate the prognostic value of ID1-2 in patients with OC in 17 data setswith 2,585 patients, respectively. (C)- (D) Validate the prognostic value of ID1-2 in patients with OC in 18 data sets with 2,663 patients, respectively.","description":"","filename":"Fig7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/Fig7.jpg"},{"id":1444345,"identity":"ea7a03ae-92a2-40c2-ad04-68ec88ad8484","added_by":"auto","created_at":"2020-06-29 13:47:06","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1450541,"visible":true,"origin":"","legend":"Correlation of the expression levels of ID family members with immune infiltration level in OC (TIMER database). (A)- (D) Correlation of ID1-4 expression with immune infiltration level in OC, respectively. ","description":"","filename":"Fig8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/Fig8.jpg"},{"id":13547967,"identity":"4ec04931-6d8b-4c26-897f-43e884b330b8","added_by":"auto","created_at":"2021-09-17 02:15:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1802324,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/9143eb50-dc79-449b-ae55-eefafdd30023.pdf"},{"id":1444347,"identity":"86112b2f-5978-437c-9073-c30f1692e050","added_by":"auto","created_at":"2020-06-29 13:47:07","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22269,"visible":true,"origin":"","legend":"","description":"","filename":"ID.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/ID.xlsx"},{"id":1444348,"identity":"3206f553-39c2-4e6a-8312-fcb18e8fef1d","added_by":"auto","created_at":"2020-06-29 13:47:07","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17923,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-38061/v1/TableS1.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eThe Inhibitor of DNA Binding Family Regulates the Prognosis of Ovarian Cancer\u003c/p\u003e","fulltext":[{"header":"Introduction","content":" \u003cp\u003eKey among the genes that encode helix-loop-helix (HLH) family of transcription factors is the inhibitor of DNA binding or differentiation \u003cem\u003e(ID\u003c/em\u003e), abundant in stem and progenitor cells (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). To date, ID proteins are encoded by four \u003cem\u003eID\u003c/em\u003e genes in the \u003cem\u003eID\u003c/em\u003e family in vertebrates: \u003cem\u003eID1-4\u003c/em\u003e, all of which encode the corresponding (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). As negative regulators of basic HLH proteins, \u003cem\u003eID\u003c/em\u003e proteins are potent suppressors of typical HLH proteins, and this is achieved via the formation of non-functional heterodimers (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Recently, numerous studies have reported aberrant expression of \u003cem\u003eID\u003c/em\u003e proteins in different human malignancies. It has also been associated with advanced tumor metastasis and development of multiple carcinomas (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In addition, \u003cem\u003eID\u003c/em\u003e proteins are involved in virtually all tumor-associated processes, including cell differentiation, cycle regulation, angiogenesis, stemness, epithelial-mesenchymal transition, chemoresistance, and immunomodulation (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). More importantly, findings from prior studies reveal the regulation of \u003cem\u003eID\u003c/em\u003e proteins expression and function via \u003cem\u003eID\u003c/em\u003e-specific antisense oligonucleotides, small interfering RNAs, or nanocomplexes, which in turn affect micro-angiogenesis and apoptosis in various types of tumor cells (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Taken together, ID proteins may be promising and effective predictive biomarkers and anti-angiogenic or anti-apoptotic agents for cancer management.\u003c/p\u003e \u003cp\u003eThe incidence of OC has been on the rise; in 2018, it was estimated that 184,799\u0026nbsp;million deaths and 295,414 new cases of OC were recorded worldwide (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). This situation is expected to worsen globally. Although standard tumor reduction surgery combined with chemotherapy, and recent application of targeted therapies have significantly improved the survival chances of OC patients, this condition still shows a 5-year survival rate below 40% (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The poor prognosis and high mortality rate are largely a result of less sensitive and suboptimal tools for early diagnosis, high recurrence following surgery resection, distant metastasis, and resistance to systemic chemotherapy and molecular drugs (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Therefore, effective prognostic markers and promising molecular therapeutic strategies for OC patients are highly desirable.\u003c/p\u003e \u003cp\u003eRecently, it was reported that several \u003cem\u003eID\u003c/em\u003e proteins are aberrantly expressed in OC samples in comparison with normal tissues, and the level of \u003cem\u003eID\u003c/em\u003e is closely related to poor differentiation, advanced stage, enhanced malignant potential, and worse clinical pathological features of OC (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Elevated expression levels of \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e were found to be a strong predicator of shorter survival in OC (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These reports show that \u003cem\u003eID\u003c/em\u003e could be a promoter of OC progression and tumorigenesis. More importantly, animal experiments showed that partial loss function or knockdown of \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e decreased proliferation, anchorage-independent growth, increased apoptosis, and reduced survival in various human cancer cells (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). There is reason to believe that \u003cem\u003eIDs\u003c/em\u003e may be novel therapeutic genes and potentially versatile therapeutic targets for OC. Regrettably, the distinct roles of the individual \u003cem\u003eID\u003c/em\u003e proteins in OC are not fully known. In our study, we comprehensively analyzed the relationships between the four \u003cem\u003eID\u003c/em\u003e subtypes and OC based on several large databases such as cBioPortal, Kaplan-Meier plotter (KM plotter), Gene Expression Profiling Interactive Analysis (GEPIA), SurvExpress, TIMER, and FunRich, to determine the expression patterns, genetic alterations, immune infiltrations, molecular function, and prognostic signature of ID proteins in OC.\u003c/p\u003e "},{"header":"Materials And Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEthics statement\u003c/h2\u003e \u003cp\u003eAll protocols and experiments in this study conformed to the Declaration of Helsinki and were approved by the Academic Committee of the First People\u0026rsquo;s Hospital of Yichang. The data used in this study were obtained from published reports.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOncomine analysis\u003c/h2\u003e \u003cp\u003eThe Oncomine (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.oncomine.org\" target=\"_blank\"\u003ewww.oncomine.org\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e) contains massive cancer-related microarray datasets of DNA or RNA sequences. It is frequently used in genome-wide expression studies (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Herein, it was employed to reveal the transcriptional profile of \u003cem\u003eID\u003c/em\u003e family members in patient specimens from different cancer types and healthy controls. Moreover, the Student\u0026rsquo;s t-test was used to compare the expression levels between the two groups. Significant expressions were those with fold-change\u0026thinsp;=\u0026thinsp;1.5; \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;=\u0026thinsp;0.001.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGEPIA dataset analysis\u003c/h2\u003e \u003cp\u003eGEPIA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia.cancer-pku.cn\u003c/span\u003e\u003c/span\u003e) provides a platform for analyzing RNA sequencing dataset covering on 9,736 tumors and 8,587 normal specimens in the Genotype-tissue Expression dataset (GTEx) and the Cancer Genome Atlas (TCGA) projects. GEPIA is highly interactive and enables users to adjust various functions, such as dimensionality reduction analysis, correlation analysis, survival analysis, tumor/normal differential expression analysis, similar gene detection, and profiling plotting based on the pathological stage or type of cancer (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eTCGA and cBioPortal analysis\u003c/h2\u003e \u003cp\u003eTCGA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cancergenome.nih.gov/\u003c/span\u003e\u003c/span\u003e) comprises pathological and sequencing datasets for 30 types of cancers (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). On the other hand, cBioPortal is a freely-accessible cancer genomic web platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cbioportal.org/\u003c/span\u003e\u003c/span\u003e), which may be used for integrative analysis and multi-functional visualization for clinical profiles and data of cancer genomics (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In this study, the dataset \u0026ldquo;Ovarian Serous Cystadenocarcinoma (TCGA, Provisional)\u0026rdquo; was used. The frequency of ID family gene alterations, copy number variance, and mRNA expression z-scores (RNA Seq V2 RSEM) were assessed using cBioPortal in line with the guidelines provided on the cBioPortal webpage.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment analysis\u003c/h2\u003e \u003cp\u003eFunRich is an open access gene interaction network analysis tool and enables comprehensive functional annotation of various biological processes (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In the present study, processes and pathways enrichment analyses of ID family proteins were performed using FunRich to identify genes associated with ID expression. In addition, the Gene Ontology (GO) terms for cellular component (CC), molecular function (MF), and biological process (BP) categories, as well as the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of the 50 closely related genes significantly associated with ID expression were performed through FunRich.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eKaplan\u0026ndash;Meier plotter analysis\u003c/h2\u003e \u003cp\u003eKM plotter (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.oncomine.org\" target=\"_blank\"\u003ewww.kmplot.com\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e) platform to estimate the prognostic performance of ID mRNA expression. This database constitutes the survival information and gene expression datasets of 1,816 patients with OC (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). We then subcategorized patients into low and high expression groups on the basis of the median expression value, and assessed the progression-free survival (PFS), and overall survival (OS) of OC patients employed the Kaplan-Meier survival plot, with log-rank p-value, a hazard ratio (HR) with 95% confidence intervals (CI). Further sub-classification was performed; TP53 mutation status, histological subtypes and pathological subtypes, foe subgroup analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSurvExpress analysis\u003c/h2\u003e \u003cp\u003eThe SurvExpress (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinformatica.mty.itesm.mx/SurvExpress\u003c/span\u003e\u003c/span\u003e), a web-based resource, is commonly used for risk assessment and survival multivariate analysis using gene expression data (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). This database was employed herein for risk assessment and survival analysis to identify key \u003cem\u003eID\u003c/em\u003e gene signatures in OC. A prognostic index established was utilized to group patient samples into high or low-risk groups in reference to the median value of the index by employing the maximized risk algorithm. The log-rank \u003cem\u003ep-\u003c/em\u003evalue, log-rank test with HR with 95% CI was utilized for statistical analysis of the equality of survival curves.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePROGgeneV2 analysis\u003c/h2\u003e \u003cp\u003eThe PROGgeneV2 is a web based tool available at www. compbio.iupui.edu/proggene. It contains data from 134 cohorts from 21 cancer types based on the Gene Expression Omnibus (GEO), the European Bioinformatics Institute (EBI) and TCGA. In the present study, PROGgeneV2 was used to validate the relationship between the expression of IDs and prognostic outcomes in OC. The HRs and the corresponding 95% CIs were used to assess the prognostic efficiency of IDs on OC. HRs and 95% CIs for OS were directly obtained from PROGgeneV2. Different data sets were meta-synthesized using STATE 14.0 software (State Corporation, College Station, TX, USA). The heterogeneity among studies was estimated with the v2-based Q-test and Higgins\u0026rsquo; I\u003csup\u003e2\u003c/sup\u003e statistic. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for the Q-test or I2\u0026thinsp;\u0026gt;\u0026thinsp;30% indicated significant heterogeneity, and the random-effects model was used; otherwise, the fixed-effects model was used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTIMER analysis\u003c/h2\u003e \u003cp\u003eThe extent of immune infiltration among various types is often estimated using the TIMER (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cistrome.shinyapps.io/timer\u003c/span\u003e\u003c/span\u003e platform) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This tool was therefore utilized to assess the correlation of \u003cem\u003eIDs\u003c/em\u003e expression with six immune infiltrates (DCs, macrophages, neutrophils, CD4\u0026thinsp;+\u0026thinsp;T cells, B cells, and CD8\u0026thinsp;+\u0026thinsp;T cells) in OC using Spearman\u0026rsquo;s correlation analysis. On the basis of this correlation module, we established scatter plots between a pair of user-defined genes for each type of cancer, and the expression of each gene was presented with log2 RSEM.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMapping the mRNA expression profile to IDs in OC samples\u003c/h2\u003e \u003cp\u003eThe human genome contains genes encoding four \u003cem\u003eID\u003c/em\u003e family members. The Oncomine database was employed to compare the expression pattern of \u003cem\u003eID\u003c/em\u003e genes in cancer samples and normal tissue samples, and the results are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Notably, cancer samples displayed the lowest expression of ID1 mRNA among the three datasets (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). It was reported that \u003cem\u003eID1\u003c/em\u003e is decreased in ovarian serous adenocarcinoma when compared to normal samples in the Yoshihara datasets (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) and Hendrix (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In the TCGA dataset also, \u003cem\u003eID1\u003c/em\u003e also downregulated in ovarian serous cystadenocarcinoma in comparison to normal samples, with a fold change of -2.901. Similarly, the transcriptional level of \u003cem\u003eID2\u003c/em\u003e was significantly downregulated in patients with OC in the three datasets (\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). In the Hendrix (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and Yoshihara dataset (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), \u003cem\u003eID2\u003c/em\u003e was significantly downregulated with fold changes of -1.523 and \u0026minus;\u0026thinsp;6.008, respectively, in ovarian serous adenocarcinoma while it was downregulated in ovarian serous surface papillary carcinoma with a fold change of -11.999 in the Welsh dataset (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). A similar trend was also found for \u003cem\u003eID3\u003c/em\u003e. The \u003cem\u003eID3\u003c/em\u003e mRNA expression was markedly lower in multiple types of ovarian cancer compared to that in normal tissues in the Welsh (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), Yoshihara (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), and Hendrix (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) datasets. The mRNA level of \u003cem\u003eID4\u003c/em\u003e was significantly lower in ovarian carcinoma and ovarian serous cystadenocarcinoma than that in the normal samples in the Bonome (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) and TCGA datasets.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe mRNA levels of IDs in between ovarian normal tissues and different types of OC (ONCOMINE).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID family\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTypes of Ovarian cancer vs. Norma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003et-test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFold change\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePMID\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Adenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e7.32E-10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHendrix Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16452189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Cystadenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-2.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e6.20E-05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTCGA Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Adenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-4.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9.16E-8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYoshihara Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19486012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Adenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-13.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.11E-16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHendrix Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16452189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Surface Papillary Carcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e7.84E-09\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWelsh Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11158614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Adenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-10.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.25E-15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYoshihara Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19486012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Surface Papillary Carcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.46E-07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWelsh Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11158614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Adenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e6.38E-15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYoshihara Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19486012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Clear Cell Adenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4.14E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHendrix Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16452189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Adenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-1.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e8.25E-06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHendrix Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16452189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Carcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-15.628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.44E-11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBonome Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18593951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOvarian Serous Cystadenocarcinoma vs. Normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-3.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.22E-04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTCGA Ovarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe also investigated the mRNA expression levels of \u003cem\u003eIDs\u003c/em\u003e in OC compared to that in normal tissue using the GEPIA dataset. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA \u003cb\u003e- D\u003c/b\u003e, \u003cem\u003eID1-ID3\u003c/em\u003e mRNA transcripts were relatively low in OC tissues compared to normal ovarian tissues, however, only the levels of \u003cem\u003eID2\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e showed marked differences between OC and normal tissues. In addition, analysis of the GEPIA dataset indicated that the mRNA level of \u003cem\u003eID\u003c/em\u003e was not related to the different stages of OC (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE - H).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGenetic alteration rate of IDs and co-expressed genes in OC patient samples\u003c/h2\u003e \u003cp\u003eGene variations of \u003cem\u003eIDs\u003c/em\u003e in OC were examined on the cBioPortal. As shown in Figure. 3, a total of 594 patients and 606 samples from the TCGA provisional dataset of ovarian serous carcinoma were analyzed. The genetic alteration rates of \u003cem\u003eID1\u003c/em\u003e, \u003cem\u003eID2\u003c/em\u003e, \u003cem\u003eID3\u003c/em\u003e, and \u003cem\u003eID4\u003c/em\u003e were 10, 6, 3, and 15%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). We further explored the impact of \u003cem\u003eIDs\u003c/em\u003e genetic alterations on the prognosis of OC. Notably, no significant association between the prognosis of OC with \u003cem\u003eID\u003c/em\u003e gene alteration or without alteration based on the TCGA provisional dataset (\u003cem\u003ep\u003c/em\u003e values, 0.404 and 0.759, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment analysis of IDs and co-expressed genes in patients with OC\u003c/h2\u003e \u003cp\u003eWe subsequently compiled a list of the expressed \u003cem\u003eIDs\u003c/em\u003e and the 50 closest co-expressed genes predicted by analyzing GO and KEGG in Funrich. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the BP of IDs and their co-expressed genes were dramatically concentrated in processes related to regulation of nucleic acid metabolism, nucleobase, nucleoside nucleotide and regulation of gene expression, peptidolysis, proteolysis, organogenesis, and regulation of immune response (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The MF of these genes were mainly transcription regulator activity, protease inhibitor activity, protein binding, antigen binding, and protein serine/threonine phosphatase activity (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). For the CC, the genes were correlated with nuclear membrane, protein kinase, CK2 complex, nucleus, junctional sarcoplasmic reticulum membrane, and connexon complex (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Additionally, the KEGG analysis revealed significant enrichment of genes in \u003cem\u003eID-, c-MYC-, TNF-\u003c/em\u003e, and Wnt signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic value of IDs in OC samples\u003c/h2\u003e \u003cp\u003eWe subsequently assessed the correlation of individual \u003cem\u003eIDs\u003c/em\u003e with different clinical pathology parameters such as pathological grade, clinical stage, and TP53 mutation status of OC. The results presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e indicates that high mRNA expression of \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e predicted worse PFS and OS in serous OC patients. In contrast, the mRNA level of \u003cem\u003eID4\u003c/em\u003e predicted favorable OS. In endometrioid OC, the expression of \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e showed a strong correlation with good PFS. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, in OC patients with pathological grade III, elevated \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e correlated with poor PFS and OS. In patients with pathological grade II, \u003cem\u003eID3\u003c/em\u003e correlated with poor PFS and OS. In addition, upregulated \u003cem\u003eID1\u003c/em\u003e was linked to poor OS and upregulated \u003cem\u003eID2\u003c/em\u003e correlated with poor OS in pathological grade I patients. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, in clinical stage III patients, increased expression of \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e was associated with worse OS, and elevated \u003cem\u003eID2\u003c/em\u003e was associated with poor PFS. In clinical stage IV OC patients, elevated ID1 was associated with worse OS and high \u003cem\u003eID3\u003c/em\u003e expression was related to poor OS and PFS in this subgroup. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Moreover, high expression of \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e was related was associated with worse PFS and OS in OC patients carrying mutated TP53, and high \u003cem\u003eID1\u003c/em\u003e, \u003cem\u003eID2\u003c/em\u003e, and \u003cem\u003eID3\u003c/em\u003e expression was associated with worse OS in OC patients with wild-type TP53.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of the mRNA expression level of IDs with overall or different pathological histology OC prognosis (Kaplan-Meier plotter).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID family\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAffymetrix ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePathological histology\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208937_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1656\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.08\u0026ndash;1.41\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.96\u0026ndash;1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1207\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.04\u0026ndash;1.46\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1104\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.12\u0026ndash;1.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEndometrioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0-inf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e51\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.07\u0026ndash;0.48\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213931_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1435\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.04\u0026ndash;1.34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0110\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.97\u0026ndash;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1104\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.02\u0026ndash;1.36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEndometrioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0-inf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.18\u0026ndash;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0990\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207826_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1656\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.16\u0026ndash;1.56\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1435\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.05\u0026ndash;1.35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0076\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1207\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.19\u0026ndash;1.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1104\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.14\u0026ndash;1.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEndometrioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0-inf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e51\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0.07\u0026ndash;0.59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209291_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1656\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.71\u0026ndash;0.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0071\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.96\u0026ndash;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSerous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1207\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.72\u0026ndash;0.98\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0240\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.76\u0026ndash;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEndometrioid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0-inf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.97\u0026ndash;18.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0380\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of the mRNA expression level of IDs with different pathological grade OC prognosis (Kaplan-Meier plotter).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID family\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAffymetrix ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePathological grades\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208937_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65\u0026ndash;4.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.48\u0026ndash;6.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e324\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.06\u0026ndash;2.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0200\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.89\u0026ndash;1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.2200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.04\u0026ndash;1.45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0140\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e837\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.06\u0026ndash;1.48\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0078\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.76\u0026ndash;5.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213931_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e56\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e3.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.18\u0026ndash;9.72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.76\u0026ndash;8.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.81\u0026ndash;1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e256\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.02\u0026ndash;1.82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0380\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.78\u0026ndash;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.93\u0026ndash;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.2900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1\u0026ndash;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207826_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.53\u0026ndash;4.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.4000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.48\u0026ndash;28.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.1800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e324\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.11\u0026ndash;2.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0087\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e256\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.02-2.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0390\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.08\u0026ndash;1.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0063\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e837\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.11\u0026ndash;1.61\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.64\u0026ndash;4.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209291_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.24\u0026ndash;1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.11\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0570\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.85\u0026ndash;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.3400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.93\u0026ndash;1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.3100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.85\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.75-1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0480\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.75\u0026ndash;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.3000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.91\u0026ndash;10.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0610\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of the mRNA expression level of IDs with different clinical stage OC prognosis (Kaplan-Meier plotter).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID family\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAffymetrix ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eclinical stage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003ep\u003c/span\u003e\u003cb\u003e-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208937_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.93\u0026ndash;9.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.62\u0026ndash;7.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.2100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.58\u0026ndash;6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.18\u0026ndash;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0700\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.23\u0026ndash;1.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e919\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.07\u0026ndash;1.45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0056\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.52\u0026ndash;1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e162\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.91\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.30\u0026ndash;2.80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213931_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.14\u0026ndash;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.15\u0026ndash;1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.92\u0026ndash;8.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.1\u0026ndash;4.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.73\u0026ndash;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e919\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.01\u0026ndash;1.41\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0380\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.48\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.48\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0810\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207826_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.49\u0026ndash;29.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.17\u0026ndash;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.2200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026ndash;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.18\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0670\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.48\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.23\u0026ndash;1.78\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e919\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.08\u0026ndash;1.47\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e176\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.67\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.12\u0026ndash;2.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0110\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e162\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.62\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.10\u0026ndash;2.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0140\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209291_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅠ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5\u0026ndash;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.18\u0026ndash;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.2100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅡ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.52\u0026ndash;10.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.2600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.99\u0026ndash;4.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0470\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅢ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.69\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.77\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.2800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eⅣ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.94\u0026ndash;2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.96\u0026ndash;2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0690\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of the mRNA expression level of IDs with different TP53 mutation status OC prognosis (Kaplan-Meier plotter).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID family\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAffymetrix ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTP53 mutation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eCases\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e95% CI\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eID1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208937_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emutated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e506\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.1\u0026ndash;1.74\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0052\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e483\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.47\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.17\u0026ndash;1.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ewild type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.74\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.01-3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0450\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.39\u0026ndash;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213931_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emutated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.96\u0026ndash;1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.68\u0026ndash;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ewild type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.13\u0026ndash;3.97\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.76\u0026ndash;2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.3200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207826_s_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emutated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e506\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.51\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.17\u0026ndash;1.94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e483\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1.37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1.07\u0026ndash;1.76\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e0.0120\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ewild type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.13\u0026ndash;3.51\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.0160\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.98\u0026ndash;3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209291_at\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emutated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66\u0026ndash;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.1000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.04\u0026ndash;1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.0240\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ewild type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.3\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.0570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.84\u0026ndash;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.1800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic value of ID signatures in patients with OC\u003c/h2\u003e \u003cp\u003eThe SurvExpress platform was used to establish a prognostic index based on \u003cem\u003eID\u003c/em\u003e expression. A total of 1,609 patients from three ovarian cancer datasets with large sample sizes were analyzed using the SurvExpress platform. High/low risk groups were categorized by prognostic risk algorithm in each dataset. The survival analysis and Kaplan\u0026ndash;Meier plotter between high risk (red) and low risk (green) groups and the heat map of the expression of \u003cem\u003eIDs\u003c/em\u003e in each dataset are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The results showed that the expression of each \u003cem\u003eID\u003c/em\u003e member was distributed between high and low risk groups. More importantly, the low risk group displayed a significantly good OS in comparison with the high risk group in the ovarian Meta-base: 6 cohorts with 22\u0026nbsp;K genes (HR\u0026thinsp;=\u0026thinsp;1.44, 95% CI\u0026thinsp;=\u0026thinsp;1.19\u0026ndash;1.75), ovarian serous cystadenocarcinoma TCGA (HR\u0026thinsp;=\u0026thinsp;1.28, 95% CI\u0026thinsp;=\u0026thinsp;1.02\u0026ndash;1.60) and OV \u0026ndash; TCGA - ovarian serous cystadenocarcinoma June 2016 (HR\u0026thinsp;=\u0026thinsp;1.40, 95% CI\u0026thinsp;=\u0026thinsp;1.01\u0026ndash;1.95) datasets, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003eValidate the prognostic value of IDs in patients with OC in different data sets\u003c/h2\u003e \u003cp\u003eWe applied PROGgeneV2 to validate the he prognostic value of \u003cem\u003eIDs\u003c/em\u003e in patients with OC in different data sets. The results showed that seventeen data sets with 2,585 subjects reported the data of relationship between \u003cem\u003eID1\u003c/em\u003e and OS in patients with OC. The pooled result showed that increased \u003cem\u003eID1\u003c/em\u003e expression was significantly correlated with worse OS (HR: 1.08, 95% CI: 1.01\u0026ndash;1.14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017), with significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e: 36.5%, \u003cem\u003ePh\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.065) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). In addition, the same 17 data sets reported data on the association between \u003cem\u003eID2\u003c/em\u003e and OS in patients with OC. Meta-analysis of these 17 sets showed that there was no significant correlation between the expression of \u003cem\u003eID2\u003c/em\u003e and the OS of OC patients (HR: 1.02, 95% CI: 0.96\u0026ndash;1.09, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0. 0.617), and with no significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e: 10.3%, \u003cem\u003ePh\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.334) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). Simultaneously, there were 18 data sets containing 2,663 OC patients the prognostic value of \u003cem\u003eID3\u003c/em\u003e and \u003cem\u003eID4\u003c/em\u003e in OS. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC, the elevated \u003cem\u003eID3\u003c/em\u003e expression was significantly associated with unfavorable OS (HR: 1.10, 95% CI: 1.04\u0026ndash;1.16, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and no significant heterogeneity was observed (I\u003csup\u003e2\u003c/sup\u003e: 11.5%, \u003cem\u003ePh\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.317). At last, the results presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD indicates that increased \u003cem\u003eID4\u003c/em\u003e expression was positively correlated with better OS (HR: 0.90, 95% CI: 0.84\u0026ndash;0.97, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with extreme heterogeneity (I\u003csup\u003e2\u003c/sup\u003e: 55.0%, \u003cem\u003ePh\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eImmune infiltration analysis of IDs in patients with OC\u003c/h2\u003e \u003cp\u003eWe explored the correlation between \u003cem\u003eID\u003c/em\u003e expression and immune infiltration levels in OC using correlation modules in TIMER. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, \u003cem\u003eID1\u003c/em\u003e expression level showed a significant negative correlation with infiltrating levels of B cells (\u003cem\u003er\u003c/em\u003e = -0.252, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.07e-08) and DCs (\u003cem\u003er\u003c/em\u003e = -0.113, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.30e-02). In contrast, it showed a positive correlation with infiltrating levels of macrophages (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.15, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.95e-04). \u003cem\u003eID2\u003c/em\u003e level showed a negative correlation with infiltrating levels of B cells (\u003cem\u003er\u003c/em\u003e = -0.110, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.55e-02), and positive correlation with infiltrating levels of macrophages (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.150, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.95e-04) and neutrophils (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.097, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.39e-02) in OC. For \u003cem\u003eID3\u003c/em\u003e, there was a significant correlation with infiltrating levels of B cells (\u003cem\u003er\u003c/em\u003e = -0.184, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.18e-5) and macrophages (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.217, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.68e-06). In addition, there was a negative correlation with infiltrating levels of macrophages (\u003cem\u003er\u003c/em\u003e = -0.098, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.10e-02) and neutrophils (\u003cem\u003er\u003c/em\u003e = -0.14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.15e-03) in OC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e "},{"header":"Discussion","content":" \u003cp\u003eKey among the genes that encode the helix-loop-helix (HLH) family of transcription factors is the \u003cem\u003eID\u003c/em\u003e, abundant in stem and progenitor cells (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). To date, it is known that ID proteins are encoded by four \u003cem\u003eID\u003c/em\u003e genes in the \u003cem\u003eID\u003c/em\u003e family in vertebrates: \u003cem\u003eID1-4\u003c/em\u003e, all of which encode the corresponding four \u003cem\u003eID\u003c/em\u003e family members (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). These genes are located in different chromosomes and show inconsistent expression profiles and functions (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Emerging evidence suggests that \u003cem\u003eID\u003c/em\u003e proteins play vital roles in tumorigenesis in several types of malignancies mediated by their ability to regulate cell-cycle, cell differentiation, epithelial-mesenchymal transition, chemoresistance, and immunomodulation (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Yet, the specific roles of the four \u003cem\u003eID\u003c/em\u003e members in OC are obscure. This study evaluated the prognostic value and expression of ID family genes by investigating various large databases. Our study presents the first silico and bioinformatics analysis of the ID family.\u003c/p\u003e \u003cp\u003eID1 is the most widely characterized component of the HLH transcription factor family (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Studies show that the molecular functions of \u003cem\u003eID-1\u003c/em\u003e included induction of cell proliferation, increasing DNA synthesis, and interaction with various oncogenes (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Aberrant expression of the \u003cem\u003eID1\u003c/em\u003e protein has not only been detected in multiple types of human cancers, but is also correlated with tumor stages and clinical outcome (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Furthermore, ectopic expression of \u003cem\u003eID1\u003c/em\u003e in human cancer cells increases serum-independent cell growth, enhances primary tumor G1/S phase formation and metastatic potential, and protects tumor cells against apoptosis. Conversely, inhibition or inhibition of \u003cem\u003eID1\u003c/em\u003e in human cancer cells has been shown to suppress cell proliferation, induce cellular senescence, induce G2/M cell-cycle arrest, reduce tumor colony formation or multiplicity, and increase lifespan (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). In OC, Schindl et. al. found that \u003cem\u003eID1\u003c/em\u003e expression correlates with the malignant potential of OC and is correlated with aggressive behavior, differentiation of tumor cells, and clinical prognosis (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Several studies have found that increased \u003cem\u003eID1\u003c/em\u003e may promote cancer cell proliferation and enhance endothelial progenitor cell angiogenesis through regulation or facilitation of EGFR and TGFβ1 expression, and activation NF-κB/MMP-2 and PI3K/Akt signaling pathways in OC cells (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). In addition, the study by Li ZD et al demonstrated that apigenin can suppress the expression of \u003cem\u003eID1\u003c/em\u003e, resulting in inhibition of tumorigenesis in human OC A2780 cells (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Thus, \u003cem\u003eID1\u003c/em\u003e represents a promising therapeutic target for OC. In our study, the Oncomine and GEPIA datasets indicated that the expression of \u003cem\u003eID1\u003c/em\u003e was suppressed in human OC. The Kaplan\u0026ndash;Meier plotter and PROGgeneV2 analysis revealed a high mRNA expression of \u003cem\u003eID1\u003c/em\u003e, and this was correlated with poor OS in all OC patients. These data reflect the heterogeneity of \u003cem\u003eID1\u003c/em\u003e expression in mRNA and protein levels, and point to the oncogenic function of \u003cem\u003eID1\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cem\u003eID2\u003c/em\u003e belongs to the HLH transcription factor family, which promotes proliferation and invasive growth in multiple solid cancers, e.g., hepatocellular cancer, breast cancer, thyroid cancer, pancreatic cancer, and OC (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Like \u003cem\u003eID1\u003c/em\u003e, several studies have shown that \u003cem\u003eID2\u003c/em\u003e promotes the proliferation of human cancer cells by inhibiting cell apoptosis, enhancing cancer stemness of pre-malignant cells, or mediating m6A modifications (\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Conversely, reduced \u003cem\u003eID2\u003c/em\u003e expression increases apoptosis, reduces cell proliferation, and decreases tumor initiation in human cancer cells (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). However, currently there are very few reports on \u003cem\u003eID2\u003c/em\u003e and OC development in the literature. An earlier study showed the \u003cem\u003eID2\u003c/em\u003e gene as a candidate for inherited predisposition to breast and ovarian cancer in Jewish women (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Moreover, the study by Meng et. al. reported that elevated \u003cem\u003eID2\u003c/em\u003e expression in ERα-positive epithelial tumor cells promoted the invasiveness of cells via a non-canonical pathway independent forming dimers with basic helix-loop-helix factors (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). In this study, \u003cem\u003eID2\u003c/em\u003e mRNA expression was found to be lower in OC samples than in normal ones, and elevated \u003cem\u003eID2\u003c/em\u003e expression was strongly related to poor PFS in all patients with OC. Prognostic analysis in patients with OC in different data sets, however, overall effect did not show any significant correlation between \u003cem\u003eID2\u003c/em\u003e expression and OS. The oncogenic effects, predictive value, and potential molecular targets of \u003cem\u003eID2\u003c/em\u003e in OC remain to be investigated further.\u003c/p\u003e \u003cp\u003e \u003cem\u003eID3\u003c/em\u003e, associated with HLH transcription factors, has been recognized as a key regulator of cell development, senescence, differentiation, proliferation, stemness, and migration (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). It has been confirmed that \u003cem\u003eID3\u003c/em\u003e and \u003cem\u003eID1\u003c/em\u003e can compensate for each other and have similar biological functions (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Previous studies have demonstrated that aberrant expression of \u003cem\u003eID3\u003c/em\u003e is associated with advanced tumor stage and poor prognosis in many types of human cancers. In animal experiments, although Id1+/-Id3-/- or Id1-/-Id3+/- mice grow to adulthood, they are unsuitable to implanted tumor xenografts because these mice lack the capacity to recruit hematopoietic precursors and endothelial (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Furthermore, double knockdown of \u003cem\u003eID1\u003c/em\u003e and \u003cem\u003eID3\u003c/em\u003e has been shown to decrease proliferation and anchorage-independent growth, increase apoptosis, and reduce survival in various human cancer cells (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). More importantly, \u003cem\u003eID3\u003c/em\u003e knockdown improved the survival duration of animals in a seeding model of medulloblastoma. It also compromised the progression of leptomeningeal seeding and the growth of primary tumors (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Elsewhere, it was recognized that BMP4 signaling is active in ovarian cancer cells where it maintains \u003cem\u003eID3\u003c/em\u003e expression. This was confirmed by the use of BMP4 blocker Noggin, which decreased endogenous \u003cem\u003eID3\u003c/em\u003e expression (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). In this study, we also demonstrated that the expression of \u003cem\u003eID3\u003c/em\u003e in OC tissues was lower than that in normal tissues, and \u003cem\u003eID3\u003c/em\u003e overexpression was associated with reduced OS and PFS in OC patients. Because \u003cem\u003eID3\u003c/em\u003e undergoes epigenetic inhibition in multiple cancers, it is therefore thought to be a tumor suppressor.\u003c/p\u003e \u003cp\u003eIn comparison with the other \u003cem\u003eID\u003c/em\u003e proteins, \u003cem\u003eID4\u003c/em\u003e possesses a polyproline domain at its C terminus and a polyalanine domain at its N terminus. Although it harbors the HLH domain, \u003cem\u003eID4\u003c/em\u003e does not display similar expression and function with D protein (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Numerous studies have shown that the phenotypic changes and molecular pathways regulated by \u003cem\u003eID4\u003c/em\u003e are, in general, not like those regulated by \u003cem\u003eID1\u003c/em\u003e, \u003cem\u003eID2\u003c/em\u003e, and \u003cem\u003eID3\u003c/em\u003e. Interestingly, \u003cem\u003eID4\u003c/em\u003e seems to function as a tumor suppressor in multiple cancers and as a tumor promoter in a small subset of cancers (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). The proposed tumor-suppressing effects of \u003cem\u003eID4\u003c/em\u003e draw on observations that ID4 undergoes epigenetic silencing in several solid cancers such as esophageal, gastric, pancreatic, colorectal, cholangiocarcinoma and lung cancer. However, ID4 has been reported to be elevated in some small cancers, such as OC, prompting researchers to re-classify it as a tumor promoter (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Mice deficient in \u003cem\u003eID4\u003c/em\u003e develop some types of cancers in their lifetime, and the lack of \u003cem\u003eID4\u003c/em\u003e results in follicular dysplasia and increased atretic follicles due to decreased estrogen biosynthesis (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). It is worth noting that a recent study showed that administration to mice harboring an ovarian tumor with an \u003cem\u003eID4\u003c/em\u003e-specific tumor-penetrating nanocomplex was capable of suppressing the growth of established tumors and significantly improved survival (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In the current study, unlike \u003cem\u003eID1, ID2\u003c/em\u003e, and \u003cem\u003eID3\u003c/em\u003e, the expression of \u003cem\u003eID4\u003c/em\u003e was higher in OC tissues than that in normal tissues, and high \u003cem\u003eID4\u003c/em\u003e expression was significantly correlated with better OS in OC patients, thereby indicating its tumor promoter role in OC.\u003c/p\u003e \u003cp\u003eWe also attempted to examine the mechanisms and roles of members of the \u003cem\u003eID\u003c/em\u003e family, we also used the cBioPortal database to explore the mutations in the \u003cem\u003eID\u003c/em\u003e family. The results showed that the genetic alteration rate of the \u003cem\u003eID\u003c/em\u003e family members varied from 3% to 15% for individual genes based on the TCGA provisional dataset, however, there was no significant association between the prognosis of OC with \u003cem\u003eID\u003c/em\u003e gene alteration or without alteration. We then constructed a network of \u003cem\u003eID\u003c/em\u003e family members and 50 of the closest co-expressed genes. The results of the functional analysis indicated that these genes were mainly enriched in tumor-related pathways, including the \u003cem\u003eID\u003c/em\u003e-, \u003cem\u003ec-MYC\u003c/em\u003e-, \u003cem\u003eTNF\u003c/em\u003e-, and Wnt signaling pathways. In addition, two major highlights of this study were the \u003cem\u003eID\u003c/em\u003e signature and immune infiltration analysis. In the \u003cem\u003eID\u003c/em\u003e signature analysis, the prognostic values of \u003cem\u003eID\u003c/em\u003e signature in patients with OC were evaluated in three datasets based on the SurvExpress platform. The method overcomes the problem single gene with the expression optimal cutoff for prognostic analysis cannot fully reflect the optimal differentiation of survival benefits and performance of potential biomarkers. In the immune infiltration analysis, we explored the correlation between \u003cem\u003eIDs\u003c/em\u003e expression with six immune infiltration levels in OC via correlation modules in TIMER. Our results showed that \u003cem\u003eID\u003c/em\u003e expression showed a strong correlation with infiltrating levels of B cells and macrophages, which further confirmed that the biological role of \u003cem\u003eID\u003c/em\u003e may be associated with immune regulation. However, the underlying molecular mechanisms and regulation steps remain largely unexplored.\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eThis study reveals that \u003cem\u003eIDs\u003c/em\u003e exhibited diverse expression profiles between OC and normal samples. Aberrant expression of \u003cem\u003eID1/3/4\u003c/em\u003e was correlated with cancer aggressiveness and prognosis in OC patients. The group with low risk \u003cem\u003eID\u003c/em\u003e signature presented a markedly good OS relative to the high-risk group. In contrast, the expression levels of \u003cem\u003eIDs\u003c/em\u003e were significantly correlated with the levels of infiltrating B cells and macrophages. Finally, enrichment analysis showed that ID co-expressed genes were involved in \u003cem\u003eID-\u003c/em\u003e, \u003cem\u003ec-MYC-, TNF-\u003c/em\u003e, and Wnt signaling pathways. These results indicate that \u003cem\u003eID1/3/4\u003c/em\u003e may be exploited as promising prognostic biomarkers and therapeutic targets in OC patients.\u003c/p\u003e"},{"header":"Abbreviations:","content":"\u003cp\u003eID, inhibitor of differentiation/DNA-binding; OC,ovarian cancer; HLH ,helix-loop-helix; GTEx, the Genotype-tissue Expression dataset; TCGA, the Cancer Genome Atlas; EBI, European Bioinformatics Institute; GO, Gene Ontology; CC, cellular component; MF, molecular function; BP, biological process; KEGG, Kyoto Encyclopedia of Genes and Genomes ; PFS, progression-free survival ; OS, overall survival; HR,hazard ratio ; CI, confidence intervals; GEPIA, Gene Expression Profiling Interactive Analysis.\u003c/p\u003e "},{"header":"Declarations","content":"Acknowledgments\n\nWe thank the Oncomine, GEPIA, Kaplan-Meier plotter, cBioPortal, SurvExpress, and TIMER for sharing the large amounts of data.\n\nAuthor contribution\n\nQ.Z., YD. M. and HJ. Y. designed the study. YD. M., HJ. Y. and YL.T.collected and performed data analysis and validation. Q.Z. and YL.T.wrote and edited the manuscript.\n\nFunding\n\nThis study was supported by project grants from the Yichang Medical and Health Research Project (No.A17-301-12).\n\nAvailability of data and materials\n\nAll data generated or analyzed during this study are included in this publishedarticle.\n\nEthics approval and consent to participate\n\nNot applicable.\n\nConsent for publication\n\nNot applicable.\n\nCompeting interests\n\nThe authors declare that they have no competing interests."},{"header":"References","content":"\u003col\u003e\u003cli\u003e \u003cspan\u003eNorton JD. ID helix-loop-helix proteins in cell growth, differentiation and tumorigenesis. J Cell Sci. 2000;113(Pt 22):3897\u0026ndash;905.\u003c/span\u003e \u003c/li\u003e \u003cli\u003e \u003cspan\u003eRoschger C, Cabrele C. The Id-protein family in developmental and cancer-associated pathways. 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J Cell Mol Med. 2017;21(8):1468\u0026ndash;81.\u003c/span\u003e \u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ID gene family, ovarian cancer, prognostic value, bioinformatics analysis","lastPublishedDoi":"10.21203/rs.3.rs-38061/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-38061/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThe inhibitor of DNA binding or differentiation (\u003cem\u003eID\u003c/em\u003e) protein family contributes to the carcinogenesis and progression of various cancers. However, its mechanistic role in tumor initiation and progression of ovarian cancer (OC) has remained unclear. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We used the Oncomine, GEPIA, Kaplan-Meier plotter, cBioPortal, SurvExpress, PROGgene V2 server, TIMERdatabase, and FunRich to evaluate the expression and predictive prognostic value of individual IDs members’ mRNA in patients with OC. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOur results revealed that the mRNA transcripts of all \u003cem\u003eID \u003c/em\u003efamily members were markedly downregulated in OC compared to normal tissue. Aberrant expression of \u003cem\u003eID 1/3/4\u003c/em\u003ecorrelated with cancer aggressiveness and clinical in OC patients. The prognostic value of \u003cem\u003eID \u003c/em\u003emembers was also explored within the subtypes, pathological stages, clinical stages, and TP53 mutational status. The group with a low risk \u003cem\u003eIDs\u003c/em\u003e showed a relatively good overall survival (OS) in comparison to the high-risk group. In contrast, the expression level of \u003cem\u003eIDs \u003c/em\u003ewas significantly associated with the levels of infiltrating B cells and macrophages. Finally, enrichment analysis showed that \u003cem\u003eID\u003c/em\u003e co-expressed genes were involved in \u003cem\u003eID-\u003c/em\u003e,\u003cem\u003e c-MYC\u003c/em\u003e,\u003cem\u003e TNF-\u003c/em\u003e, and Wnt signaling pathways. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThese results indicate that \u003cem\u003eID1/3/4\u003c/em\u003e may be exploited as promising prognostic biomarkers and therapeutic targets in OC patients.\u003c/p\u003e","manuscriptTitle":"The Inhibitor of DNA Binding Family Regulates the Prognosis of Ovarian Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-06-29 13:47:03","doi":"10.21203/rs.3.rs-38061/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f70f6ad6-ef20-4418-bc83-5afa26075c75","owner":[],"postedDate":"June 29th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":132392,"name":"Obstetrics \u0026 Gynecology"}],"tags":[],"updatedAt":"2021-07-27T21:05:08+00:00","versionOfRecord":{"articleIdentity":"rs-38061","link":"https://doi.org/10.2217/fon-2020-1006","journal":{"identity":"future-oncology","isVorOnly":true,"title":"Future Oncology"},"publishedOn":"2021-05-01 21:05:08","publishedOnDateReadable":"May 1st, 2021"},"versionCreatedAt":"2020-06-29 13:47:03","video":"","vorDoi":"10.2217/fon-2020-1006","vorDoiUrl":"https://doi.org/10.2217/fon-2020-1006","workflowStages":[]},"version":"v1","identity":"rs-38061","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-38061","identity":"rs-38061","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}