Pancancer analysis of CDCP1 reveals its carcinogenic mechanisms and prognostic value as a survival-related target

Pancancer analysis of CDCP1 reveals its carcinogenic mechanisms and prognostic value as a survival-related target | 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 Research Article Pancancer analysis of CDCP1 reveals its carcinogenic mechanisms and prognostic value as a survival-related target Shuchun Xie, Yan Tang, Qiuxia Zhao, Jianhui Ding, Xian Li, Yue Wu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9158731/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Although a growing body of evidence indicates that CDCP1 plays a crucial role in cancer initiation and progression, there remains a lack of systematic analysis regarding CDCP1 in cancer. Here, we conducted a comprehensive study of CDCP1 based on the Cancer Genome Atlas (TCGA) and the Clinical Proteomics Oncology Analysis Consortium (CATPAC) databases, aiming to explore its potential role and detailed mechanisms in 33 human tumors. The results showed that CDCP1 was highly expressed in many cancers, and the expression of CDCP1 was significantly correlated with the prognosis of cancer patients. DNA methylation levels of CDCP1 tended to decrease in most cancers and were inversely correlated with CDCP1 expression, which in addition significantly correlated with the level of infiltrating cells. In summary, the pancancer study described the relationship between CDCP1 expression and clinicopathological features in multiple cancer types, further showing its potential regulatory role in human cancer. This study is a systematic analysis of the function and role of CDCP1, which is a relatively comprehensive understanding of the oncogenic role of CDCP1 in different tumors. CDCP1 pancancer analysis prognosis tumorigenesis DNA methylation immune infiltration biomarker Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Cancer is the leading cause of morbidity and mortality worldwide, poses a major health and economic burden on society, and is a serious impediment to increasing global life expectancy [ 1 ]. After more than a hundred years of development, cancer treatment strategies have evolved from surgery, radiotherapy, and chemotherapy to today's precision targeted therapies and immunotherapy, which have become the mainstream and most effective cancer treatment strategy [ 2 , 3 ]. However, the relative concentration of targets for drug development can easily lead to drug resistance problems, thus limiting the therapeutic efficacy of drugs and ultimately affecting the curability and prognosis of patients [ 4 ]. Therefore, there is an urgent need to find new cancer therapeutic targets and develop sensitive tumor biomarkers with potential therapeutic capabilities for better cancer diagnosis and treatment [ 5 ]. Pancancer analysis is an approach that enables systematic analysis of multiple cancer gene profiles, identifying commonalities and differences in key biological processes that are dysregulated in cancer cells from different lineages. This approach can be used to study the relationship between genes or molecules and cancer progression and is a promising tool for systematic analysis [ 6 – 8 ]. Through this systematic research approach, we can provide a solid theoretical foundation for the discovery of innovative therapeutic targets, the development of tumor-targeted drugs, and the further expansion of the population for targeted therapies. CUB Domain Containing Protein1 (CDCP1) is a type I single-channel transmembrane glycoprotein, also known as CD318, SIMA135, gp140, or TRASK. This gene was first identified in colon cancer tissue by Scherl-Mostageer, and its expression was significantly upregulated compared to normal tissue. The CDCP1 gene was mapped to chromosome 3p21-p23 by fluorescence in situ hybridization [ 9 ]. Northern blot analysis, was utilized by John, showed that CDCP1 mRNA expression was low in normal human tissues, with the highest levels in skeletal muscle and colon. Immunohistochemical analysis showed that CDCP1 was expressed only in colonic epithelial cells of normal colonic mucosa. In colon tumors, CDCP1 expression was abnormal, showing extensive cell surface and cytoplasmic expression [ 10 , 11 ]. Studies have shown that CDCP1 is involved in key tumor metastatic signaling cascades, including SRC/PKCδ, PI3K/AKT, WNT, and RAS/ERK axes, the oxidized pentose phosphate pathway, and fatty acid oxidation, which are important for tumor cell proliferation, metastasis, and treatment resistance. In addition, elevated CDCP1 levels were also significantly associated with disease progression and poorer survival [ 12 – 14 ]. The multifaceted functions of CDCP1 suggest that its study may contribute to insights into the potential role of CDCP1 in malignant tumors. However, systematic evaluation of the role of CDCP1 in human cancers is still lacking. Considering the critical role of CDCP1 in cancer progression, we will combine multiple databases, including TCGA, GTEx, and CPTAC, to perform a systematic paradigm cancer analysis of CDCP1 in various human cancers. This comprehensive study aims to elucidate the potential functions and regulatory mechanisms of CDCP1 in the pathogenesis and clinical prognosis of a variety of cancer types, and to further substantiate its promising role as a diagnostic biomarker and therapeutic target for cancer therapy. This study may also broaden the application of CDCP1 in the development of immunotherapy and targeted therapy drugs. 2. Results 2.1 Assessment of CDCP1 expression in different cancers and normal tissues We first retrieved the interaction relationship of the CDCP1 gene with related genes at the subcellular level and protein level from the HPA database. The results showed that both at the subcellular level and protein level, CDCP1 interacts strongly with PRKCD, SRC, and SDCBP, with the weakest interaction with YES1 (Supplementary Fig. 1A). Next, we used the HPA database to retrieve the expression levels of CDCP1 in normal tissues and immune cells, and in general, CDCP1 showed low RNA specificity in various tissues and immune cells (Supplementary Fig. 1B-C). In addition, we constructed a map of CDCP1 expression landscape in different human cancers based on the TCGA database. Figure 1 A shows the significant variability in CDCP1 transcript levels between 15 tumor tissues and adjacent normal tissues. Compared to normal tissue, the expression of CDCP1 was significantly increased in Bladder Urothelial Carcinoma (BLCA), Breast invasive carcinoma (BRCA), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), Cholangio carcinoma (CHOL), Esophageal carcinoma (ESCA), Glioblastoma multiforme (GBM), Head and Neck squamous cell carcinoma (HNSC), Kidney Chromophobe (KICH), Lung adenocarcinoma (LUAD), Lung squamous cell carcinoma (LUSC), Stomach adenocarcinoma (STAD), Thyroid carcinoma (THCA) and Uterine Corpus Endometrial Carcinoma (UCEC). In contrast, CDCP1 expression was significantly downregulated in Colon adenocarcinoma (COAD) and Prostate adenocarcinoma (PRAD) tissues compared to normal tissues. We also incorporated the GTEx database to supplement the number of normal tissues used as controls in the TCGA program. The results in Fig. 1 B show that, compared to normal tissue, CDCP1 expression was significantly upregulated in BRCA, LUAD, LUSC, BLCA, Rectum adenocarcinoma (READ), UCEC, CESC, CHOL, Colon adenocarcinoma (COAD), GBM, Pancreatic adenocarcinoma (PAAD), Testicular Germ Cell Tumors (TGCT), KICH, Ovarian serous cystadenocarcinoma (OV), and STAD. However, in Acute Myeloid Leukemia (LAML) and Skin Cutaneous Melanoma (SKCM) tissues, the expression of CDCP1 was significantly lower than that in normal tissues (all p -values < 0.05). Moreover, we used the CPTAC dataset to detect differences in CDCP1 protein levels between tumor tissues and corresponding normal tissues. The results showed that expression of CDCP1 protein in Breast cancer, Colon cancer, Ovarian cancer, Clear cell renal cell carcinoma, UCEC, was significantly upregulated in Lung cancer and PAAD (Fig. 1 C). Furthermore, we retrieved immunohistochemical staining images of CDCP1 protein in different tumor tissues and corresponding normal tissues (Supplementary Fig. 2). 2.2 Analysis of the relationship between CDCP1 expression and clinicopathological features To investigate the relationship between CDCP1 expression levels and clinicopathological features, we analyzed CDCP1 expression in normal tissues and stage I, II, III, and IV tumor tissues using the UALCAN database. Our results showed that CDCP1 gene expression was significantly upregulated during disease progression from normal tissues to different stages of malignant tumors, including ESCA, HNSC, STAD, CESC, BLCA, BRCA, KICH, CHOL, UCEC, THCA, LUSC, LUAD, LIHC, and KIRC. However, the expression of CDCP1 was significantly upregulated in tumors, including COAD and READ. CDCP1 expression did not change significantly during disease progression (Fig. 2 ). In addition, expression of CDCP1 protein was found to be significantly associated with disease progression in multiple cancers, including breast cancer, colon cancer, ccRCC, LUAD, PAAD, and UCEC (supplemental Fig S3). 2.3 Survival analysis of pancancer analyzing CDCP1 To further assess the correlation between CDCP1 expression and the prognosis of human cancer patients, we investigated the correlation between CDCP1 expression and the prognosis of patients with different tumors using the TCGA database. The results showed that enhanced CDCP1 expression was significantly associated with higher overall survival (OS) in COAD (p = 0.03) and SKCM (p = 0.0051). While in HNSC (p = 0.033), LAML (p = 0.00021), Brain Lower Grade Glioma (LGG, p = 8.2×10 − 5 ), and LUAD (p = 0.011), decreased CDCP1 expression was significantly associated with higher OS. The significance of LGG was most significant in all tumor types (Fig. 3 A). Disease-free survival (DFS) analysis data showed that low CDCP1 expression significantly improved DFS in GBM (p = 0.011), LGG (p = 3.2×10 − 5), and PAAD (p = 0.03). The significance of LGG was the most significant among all tumor types (Fig. 3 B). In addition, reduced CDCP1 expression significantly improved Distant Metastasis Free Survival (DMFS) in breast cancer (p = 0.024) and poorer Progression Free Survival (PFS) in ovarian cancer patients (p = 0.018), as well as improved pancreatic cancer patients’ Disease Free Survival (DFS) (p = 0.0196), which were significantly associated (Supplementary Fig. 4). In addition, we conducted systematic subgroup analyses of breast, colorectal, lung, gastric, and ovarian cancers to explore the relationship between CDCP1 expression and prognosis in patients with different treatment groups (Supplementary Tables S1-S5). Next, we utilized the Kaplan-Meier plotter to assess the prognostic impact of CDCP1 on patients with different types of cancer. We observed that dysregulated CDCP1 expression significantly affected OS in seven types of cancer. When CDCP1 expression is down-regulated, HNSC (p = 0.0011), KIRC (p = 0.00074), PAAD (p = 0.00025), LIHC (p = 0.032), LUAD (p = 0.00011), LUSC (p = 0.0061), and Thymoma (THYM) (p = 0.00042) had a favorable prognosis (Supplementary Fig. 5A). Supplementary Fig. 5B shows that high CDCP1 expression predicted better recurrence-free survival (RFS) in Esophageal squamous cell carcinoma (ESCC, p = 0.0067). However, enhanced CDCP1 expression predicted poorer RFS in LUAD (p = 0.016), PAAD (p = 0.0013), and TGCT (p = 0.0051) (Supplementary Fig. 5B). In conclusion, these results suggest that CDCP1 expression can predict the prognostic survival of patients with different types of cancer, and the specific relationship between the expression level of CDCP1 and the prognosis of cancer patients depends on the tumor type. 2.4 Pancancer analysis of DNA methylation levels of CDCP1 DNA methylation is a chemical modification that plays an important role in the regulation of gene expression [ 15 , 16 ]. Studies have shown that abnormal changes in DNA methylation can promote the occurrence and development of cancer [ 17 ]. Based on the TCGA database, we used UALCAN to explore the potential relationship between the DNA methylation level of CDCP1 and tumorigenesis. Compared with normal tissue, BLCA, BRCA, COAD, CESC, UCEC, Pheochromocytoma and Paraganglioma (PCPG), PRAD, and CDCP1 methylation was significantly downregulated in READ and Testicular Germ Cell Tumors (TGCT). In addition, methylation levels of CDCP1 were significantly upregulated in KIRP, KIRC, and PAAD compared with normal tissues (Fig. 4 ). 2.5 Data from genetic alteration analysis of CDCP1 We observed the genetic alteration status of CDCP1 in different tumor samples from the TCGA database. The results showed that SKCM patients with “mutation” as the predominant type had the highest frequency of mutations in CDCP1 (> 7%). Amplified variants accounted for a significant proportion of the alterations in OV, KICH, ESCA, and PCPG (Fig. 5 A). The types, loci, and number of cases of CDCP1 gene alterations are shown in Fig. 5 B. We found that missense mutations in CDCP1 were the main type of gene alteration. The study of the types and sites of CDCP1 gene alterations confirmed the R726*/Q shifted code insertion mutation in one case of LUSC, one case of uterine papillary serous carcinoma (UPSC), and one case of SKCM. The above results suggest that this is a hot spot mutation site in cancer (Fig. 5 B). We further examined the potential relationship between CDCP1 genetic alterations and the prognosis of patients with different types of cancer. The analysis results showed that genetic alterations in CDCP1 did not present significant differences with survival-related indices DFS, disease-specific survival (DSS), OS, and PFS in cancer patients (Fig. 5 C). In addition, we analyzed the effects of TP53, BRAF, and KRAS gene mutations on CDCP1 expression in tumor tissues (Supplementary Fig. 6). 2.6 Correlation analysis of CDCP1 expression and immune infiltration of MDSCs Studies have shown that the tumor microenvironment (TME) contains many immune-infiltrating cells. The interaction between immune cells and tumor cells is closely related to cancer development, progression, or metastasis [ 18 , 19 ]. We investigated different levels of immune cell infiltration for different cancer types in the TIMER database. As shown in Supplementary Table S6, the expression level of CDCP1 was significantly correlated with MDSC infiltration in BLCA, LGG, LIHC, LUAD, LUSC, OV, PAAD, PCPG, SKCM, and STAD. However, there was no generalized significant correlation between CDCP1 expression and infiltration of other subgroups of immune cells, including B cells, CD4 + T cells, CD8 + T cells, Treg cells, Tfh cells, γδ T cells, monocytes, macrophages, neutrophils, and DC cells. Therefore, we focused on MDSC in TME. As shown in Fig. 6 , the heatmap and scatterplot showed the relationship between infiltration estimates and CDCP1 gene expression. The results showed that CDCP1 expression showed a significant positive correlation with MDSC infiltration level in most cancer types. 2.7 Analysis of CDCP1 gene correlation in pancancer analysis We obtained the top 100 genes associated with CDCP1 expression in 33 human cancers based on GEPIA2. The top 5 related genes were ANXA2 (R = 0.58), FAM83H (R = 0.55), ZDHHC5 (R = 0.55), TUBA1C (R = 0.56), and ARNTL2 (R = 0.57) (all p -values < 0.01) (Fig. 7 A). In addition, we collected the top 20 CDCP1-interacting proteins using the STRING database, and these identifications were supported by experimental evidence. The PPI network of these 20 proteins is shown in Fig. 7 B. In addition, Venn diagram cross-analysis of the 20 genes that interacted with CDCP1 and the 100 genes related to CDCP1 finally revealed that the one common gene was EPHA2 (Fig. 7 C). These results emphasize that there may be a close connection between CDCP1 and EPHA2, and the upstream and downstream regulatory roles between them can be further investigated experimentally. 2.8 Interacting chemicals and genes in CDCP1 Comparative Toxicogenomics Database (CTD) data showed that CDCP1 was associated with 40 chemicals, of which 31 upregulated CDCP1 and 10 downregulated CDCP1. In addition, one chemical, Arensic, affected CDCP1 expression, but the exact role is unclear (Table 1 ). Furthermore, we showed the relationship between CDCP1 and 22 other genes by chemical association. The results show that CDCP1 was highly correlated with Transmembrane protein 158 (TMEM158), Laminin subunit gamma 2 (LAMC2), Exophilin 5 (EXPH5), Glutamine fructose 6 phosphate transaminase 2 (GFPT2), and Leucine-rich repeat and Ig domain containing 1 (LINGO1) (Table 2 ). Table 1 Interacting chemicals of CDCP1 from CTD Chemical name Chemical ID Interaction actions 1,4-bis(2-(3,5-dichloropyridyloxy)) benzene C028474 Decreases expression 1-Butanol D020001 Increases expression 2,4,5,2',4',5'-hexachlorobiphenyl C014024 Increases expression 2-amino-2-methyl-1-propanol C006551 Decreases expression 3,4-dichloroaniline C014464 Increases expression 4-(4-((5-(4,5-dimethyl-2-nitrophenyl)-2-furanyl) methylene) -4,5-dihydro-3-methyl-5-0xo-1H-pyrazol-1-yl) benzoic acid C584509 Increases expression 4-(5-benzo (1, 3) dioxol-5-yl-4-pyridin-2-yl-1H- imidazol-2-yl) benzamide C459179 Increases expression 7,8-Dihydro-7,8-dihydroxybenzo(a)pyrene 9,10-oxide D015123 Decreases expression Abrine C496492 Decreases expression Acetamide C030686 Increases expression Acetaminophen D000082 Increases expression Acrylamide D020106 Increases expression Aflatoxin B1 D016604 Increases expression Air Pollutants D000393 Increases expression Aldehydes D000447 Increases expression Antirheumatic Agents D018501 Decreases expression Aristolochic acid l C000228 Increases expression Arsenic D001151 Affects expression Asbestos, Crocidolite D017638 Increases expression Asbestos, Serpentine D017632 Increases expression Benzene D001554 Increases expression Benzo(a)pyrene D001564 Increases expression BisphenolA C006780 Increases expression Decreases expression Bisphenol F C000611646 Increases expression Bisphenol S C543008 Increases expression Butyraldehyde C018475 Increases expression Cadmium Chloride D019256 Decreases expression Calcitriol D002117 Increases expression Carbon Tetrachloride D002251 Increases expression Decamethrin C017180 Increases expression Dibenzofurans D000072318 Increases expression Dichlorodiphenyl Dichloroethylene D003633 Decreases expression Diethylhexyl Phthalate D004051 Increases expression Diethylstilbestrol D004054 Increases expression Diuron D004237 Increases expression Dorsomorphin C516138 Increases expression Doxorubicin D004317 Decreases expression Increases expression Entinostat C118739 Increases expression Epoxiconazole C109476 Decreases expression Erucylphospho-N, N, N-trimethylpropylammonium C472787 Increases expression Table 2 Relationship of CDCP1 with genes via chemical interaction, based on the CTD database Gene Gene ID Similarity index Common interacting chemicals TMEM158 25907 0.368055556 53 LAMC2 3918 0.338383838 67 EXPH5 23086 0.333333333 42 GFPT2 9945 0.318181818 49 LINGO1 84894 0.317460317 40 AFAP1L1 134265 0.314516129 39 C15ORF48 84419 0.314049587 38 EBl3 10148 0.312056738 44 KCNK5 8645 0.310344828 45 BHLHE41 79365 0.309090909 51 LRATD2 157638 0.307692308 40 RNF182 221687 0.307017544 35 TMC6 11322 0.304964539 43 CRISPLD2 83716 0.303867403 55 CYRIA 81553 0.303278689 37 RNFT2 84900 0.303278689 37 SLC43A2 124935 0.302816901 43 REEP1 65055 0.302158273 42 PNPT1 87178 0.30075188 40 CYB561 1534 0.3 42 NPTX1 4884 0.3 48 OASL 8638 0.3 45 3. Discussion CDCP1, as a cell surface glycoprotein, has an important regulatory role in the normal biological functions of cells. It was initially found to be highly expressed in colon cancer tissues [ 9 ]. With an in-depth study of this protein, it has been found that CDCP1 exhibits significant up-regulation in a variety of malignant tumors, including triple-negative breast cancer, lung adenocarcinoma, ovarian cancer, renal clear cell carcinoma, and acute myeloid leukemia, and it has emerged as a potential biomarker and therapeutic target for a range of cancers [ 20 – 22 ]. In human tumors, elevated CDCP1 expression is critical for tumor survival, growth, metastasis, and treatment resistance [ 11 , 23 , 24 ]. Through a literature search, we failed to retrieve any articles on the pan-cancer analysis of CDCP1 from the perspective of the tumor as a whole. Therefore, it is necessary to conduct a systematic paradigm cancer analysis of CDCP1 in various tumors. In this study, based on the data from TCGA, CPTAC and GEO databases, as well as the molecular features of gene expression, gene mutation, DNA methylation, etc., we conducted a systematic analysis of CDCP1 genes in 33 different tumors to explore in depth the effects of CDCP1 mutations on tumors, the relationship between CDCP1 and the tumor immune microenvironment, the prognostic value of CDCP1 expression in different types of cancers on the survival index of cancer patients, and the gene interaction network regulated by CDCP1, aiming to better understand the potential properties and role of CDCP1 in human cancers. Our study found that of the 33 tumor tissues evaluated, significant abnormal expression of the CDCP1 gene was present in 15 tumor tissues compared to normal tissues, and 13 of them showed significant overexpression of CDCP1, accounting for 86.67% (13/15). Comprehensive comparison of these data with the CPTAC database revealed that both gene and protein expression levels of CDCP1 were significantly higher in BRCA, lung cancer, and UCEC. With disease progression, there was a consistent trend of up-regulation of the CDCP1 gene and protein expression in BRCA, KIRC, LUAD, PAAD, and UCEC. These results suggest that CDCP1 may have a role in promoting cancer progression and may serve as a promising diagnostic marker for the progression of these cancers and as a potential target for drug development. For example, Khan et al. showed that CDCP1 expression is elevated in most tumors and low in normal tissues using a comprehensive analysis of multiple normal and tumor tissues as well as tumor cell lines. It has been evaluated as an ideal therapeutic target for antibody drug Conjugate (ADC) development [ 22 , 25 ]. Whether CDCP1 can play a role in the pathogenesis of different tumors through certain common molecular mechanisms remains to be further investigated. Representative images from immunohistochemical analysis showed that CDCP1 protein expression was up-regulated in most tumor tissues compared to normal tissues, showing significant cytoplasmic and cell membrane localization. In conclusion, these findings confirm the upregulation of CDCP1 expression in a wide range of cancers, suggesting a promising future for CDCP1 in cancer diagnosis and treatment. In addition, we tried to evaluate the predictive role of CDCP1 for the survival of patients with different tumors; therefore, we used the GEPIA2 database to analyze the prognostic relationship between CDCP1 and patients with different types of tumors. These results demonstrated the good prognostic value of CDCP1 for various types of tumors. Among them, low expression of CDCP1 significantly improved OS and DFS in LGG patients, while high expression of CDCP1 significantly improved PFS and PPS in OV patients. These results illustrate that CDCP1 is a good biomarker for predicting prognostic survival in LGG and OV patients. Based on these observations, we can hypothesize the critical role of CDCP1 in the progression of LGG and OV, and the mechanism of CDCP1’s role in the progression of LGG and OV can be further investigated by experiments in the future. DNA methylation is one of the most important epigenetic mechanisms regulating gene expression, and aberrant DNA methylation is strongly associated with diseases, including cancer [ 26 ]. Therefore, we further explored the level of DNA methylation changes of CDCP1 in various types of tumors. We found that the DNA methylation level of CDCP1 was significantly down-regulated in most types of tumors (BLCA, BRCA, COAD, CESC, UCEC, PCPG, PRAD, READ, and TGCT), which was consistent with the up-regulation of CDCP1 in the majority of tumor tissues, showing an important role of CDCP1 in tumor tissues. Tumorigenesis is a complex process accompanied by abnormal cell proliferation, inhibition of apoptosis, the role of TME, enhanced angiogenesis, and evasion of immunity. Among them, TME plays a key role. TME consists of cellular components and extracellular matrix, and the cellular components include stromal fibroblasts, infiltrating immune cells, blood and lymphatic vascular networks, etc [ 27 ]. Studies have shown that the interaction of cancer cells with various components of TME can lead to immune escape effects of tumor cells. Therefore, it is necessary to explore the characteristics of multiple immune cells and the mechanisms of their interaction with tumors. Our results showed that CDCP1 expression was significantly correlated with the infiltration levels of multiple immune cells, including B cells, CD4 + T cells, CD8 + T cells, Tregs, Tfh, γδT, Monocytes, Macrophage, Neutrophil, DC, and MDSC, in various types of tumors. By understanding the relationship between CDCP1 gene expression and the level of tumor immune cell infiltration, we can find that in most cancer types, CDCP1 expression is positively correlated with the level of MDSC infiltration. Finally, we analyzed the database to obtain the 100 genes most associated with CDCP1, and we cross-analyzed the 100 genes and the 20 genes in the network of interactions with CDCP1 to obtain the only shared gene, EPHA2. Targeted therapy is a promising therapeutic approach involving characteristic drugs that target cells or proteins that induce tumor progression. Targeted therapy uses a certain drug to inhibit key biomarkers that sustain the growth and proliferation of cancer cells, thereby inhibiting tumor progression, so the development of tumor-targeted drugs is a current research hotspot [ 28 , 29 ]. We identified 40 chemical substances that may regulate CDCP1 expression using CTD and analyzed the 20 genes most closely related to CDCP1 by chemical association. Future studies can further explore the mechanism of action of chemicals regulating CDCP1 genes, and can apply chemicals to CDCP1-expressing tumor cells to assess the effects of chemicals on tumor cells, to enable the development of innovative targeted drugs. 4 Materials and methods 4.1 Gene expression analysis Differences in expression between normal and tumor tissues in the TCGA database were assessed using TIMER 2.0 ( http://timer.cistrome.org/ ) based on the TCGA database [ 30 ]. Combining normal tissue data in the GTEx database with TCGA data, we used GEPIA2 ( http://gepia2.cancer-pku.cn/ ) to study the expression of CDCP1 between different types of cancer and normal tissues [ 31 ]. Download the expression data of the CDCP1 gene in different tissues and immune cells, as well as immunohistochemical expression images in different types of tumor tissues and normal tissues from the HPA database. Sample sources are provided at HPA ( https://www.proteinatlas.org/ ) [ 32 ]. In addition, we used the UALCAN database ( http://ualcan.path.uab.edu/analysis-prot.html ) to visualize the CPTAC dataset, and we obtained differences in the expression level of total CDCP1 protein between tumor tissues [ 33 ]. 4.2 Survival Prognosis Analysis Kaplan-Meier plot ( http://kmplot.com/analysis/ ) was used to analyze the effects of different types of cancer on survival prognosis (DMFS, PPS, FP, PFS, and DFS) in the GEO database [ 34 ]. Tumor patients were divided into two groups, Kaplan-Meier survival curves were obtained, and log-rank p-values and HRs were calculated. We used the GEPIA2 tool ( http://gepia2.cancer-pku.cn/ ) to analyze the effect of CDCP1 on the survival of cancer patients. We entered the CDCP1 gene into the "Survival analysis" module, selected custom cancer types, and the high and low expression cohorts were divided by high (50%) and low (50%) cutoff values, and performed OS and DFS analyses using the log-rank test. 4.3 DNA methylation analysis and genetic alteration analysis We used the UALCAN tool to explore the differences in CDCP1 DNA methylation levels between different types of tumor tissues and normal tissues. In addition, we utilized the cBioPortal web ( https://www.cbioportal.org/ ) to analyze the genetic variation, Alteration frequency, mutation site, and survival data of CDCP1 [ 35 ]. 4.4 Analysis of immune infiltration We used TIMER2.0 ( http://timer.cistrome.org/ ) to perform a systematic analysis of immune infiltration across cancer types [ 36 ]. We obtained data on the correlation between CDCP1 expression and the level of immune infiltration in different types of cancer. We analyzed some important immune infiltrating cells, including B cells, CD4 + T cells, CD8 + T cells, Tregs, Tfh cells, γδT cells, monocytes, macrophages, neutrophils, DC, and MDSCs. 4.5 Interaction of CDCP1 with chemicals and genes The Comparative Toxicogenomics Database (CTD, http://ctdbase.org/ ) is an innovative digital ecological public database that links toxicological information on chemicals, genes, phenotypes, diseases, and exposures and can be used to study new connections between chemicals and the molecular mechanisms underlying their biological effects [ 37 ]. We used this database to query for chemicals that interact with CDCP1 and to explore genes that interact with related chemicals and are highly similar to CDCP1. 4.6 Gene enrichment analysis To explore the regulatory network of CDCP1 in cancer, the top 20 CDCP1-interacting genes were downloaded using the STRING tool ( https://cn.string-db.org/ ) , and the PPI network was visualized using Cytoscape [ 38 , 39 ]. In addition, we obtained the top 100 CDCP1-related genes through GEPIA2. In the "Correlation analysis" module of GEPIA2, the top five genes associated with CDCP1 were tested for Pearson correlation to obtain p-values, dot plots, and correlation coefficients. Declarations Acknowledgements Not applicable. Funding No funding was received. Availability of data and materials All data generated or analysed during this study are included in this published article and its supplementary information files. Authors’ contributions statement SX, YT and QZ prepared the original manuscript draft. JD and XL participated in conceptualization. YW, YX and ZL participated in guiding the preparation and design of this manuscript. RP reviewed and edited the paper. Data authentication is not applicable. All authors read and approved the final manuscript. Ethics approval and consent to participate Not applicable. Patient consent for publication Not applicable. 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Br J Cancer. 2025;133(9):1265–77. 10.1038/s41416-025-03163-6 . Epub 2025/09/05. Wong SC, Yeh CC, Zhang XY, Hsieh CY, Lo CC, Kuo TT, et al. Inhibition of Cdcp1 by 8-Isopentenylnaringenin Synergizes with Egfr Inhibitors in Lung Cancer Treatment. Mol Oncol. 2023;17(8):1648–65. 10.1002/1878-0261.13429 . Epub 2023/04/05. Khan T, Lyons NJ, Gough M, Kwah KKX, Cuda TJ, Snell CE, et al. Cub Domain-Containing Protein 1 (Cdcp1) Is a Rational Target for the Development of Imaging Tracers and Antibody-Drug Conjugates for Cancer Detection and Therapy. Theranostics. 2022;12(16):6915–30. 10.7150/thno.78171 . Epub 2022/10/25. Hsieh KL, Huang KH, Chang CP, Tsai HW, Chang YH, Zheng YR, et al. Cub Domain-Containing Protein 1 Signaling Dysregulates Gemcitabine Metabolism Contributing to Therapeutic Resistance in T24 Cells. PLoS ONE. 2025;20(9):e0331289. 10.1371/journal.pone.0331289 . Epub 2025/09/02 22. Gough M, Kwah KKX, Khan T, Ghosh S, Sun B, Lee CYJ, et al. Receptor Cdcp1 Is a Potential Target for Personalized Imaging and Treatment of Poor Outcome Her2+, Triple-Negative, and Metastatic Er+/Her2- Breast Cancers. Clin Cancer Res. 2025;31(8):1504–19. 10.1158/1078-0432.CCR-24-2865 . Epub 2025/01/27. Um YJ, Noh HD, Cho JG, Ko HJ, Wi TM, Kim JO, et al. Cdcp1-Targeting Adc Outperforms Standard Therapies in Ras-Mutant Pancreatic Cancer. Mol Ther Oncol. 2025;33(3):201024. 10.1016/j.omton.2025.201024 . Epub 2025/08/13. Wu BK, Mei SC, Chen EH, Zheng Y, Pan D. Yap Induces an Oncogenic Transcriptional Program through Tet1-Mediated Epigenetic Remodeling in Liver Growth and Tumorigenesis. Nat Genet. 2022;54(8):1202–13. 10.1038/s41588-022-01119-7 . Epub 2022/07/15. Lo Cicero A, La Monica F, Lo Buglio G, Campora S, Gangemi F, Cina P, et al. A Vascularized Three-Dimensional Model Integrating Primary Breast Tumor Cells and Microvascular Fragments: Mimicking the Tumor Microenvironment Involved in Chemoresistance. Cancer Cell Int. 2026;26(1):74. 10.1186/s12935-025-04154-6 . Epub 2026/01/09. Song D, Lian Y, Zhang L. The Potential of Activator Protein 1 (Ap-1) in Cancer Targeted Therapy. Front Immunol. 2023;14:1224892. 10.3389/fimmu.2023.1224892 . Epub 2023/07/24. Zheng L, Wang W, Sun Q. Targeted Drug Approvals in 2023: Breakthroughs by the Fda and Nmpa. Signal Transduct Target Ther. 2024;9(1):46. 10.1038/s41392-024-01770-y . Epub 2024/02/21. Li T, Fu J, Zeng Z, Cohen D, Li J, Chen Q, et al. Timer2.0 for Analysis of Tumor-Infiltrating Immune Cells. Nucleic Acids Res. 2020;48(W1):W509–14. 10.1093/nar/gkaa407 . Epub 2020/05/23. Magalhaes YT, Boell VK, Cardella GD, Forti FL. Downregulation of the Rho Gtpase Pathway Abrogates Resistance to Ionizing Radiation in Wild-Type P53 Glioblastoma by Suppressing DNA Repair Mechanisms. Cell Death Dis. 2023;14(4):283. 10.1038/s41419-023-05812-1 . Epub 2023/04/22. Xia L, Guo X, Lu D, Jiang Y, Liang X, Shen Y, et al. S100a13-Driven Interaction between Pancreatic Adenocarcinoma Cells and Cancer-Associated Fibroblasts Promotes Tumor Progression through Calcium Signaling. Cell Commun Signal. 2025;23(1):51. 10.1186/s12964-025-02049-7 . Epub 2025/01/28. Malik M, Maqbool M, Nisar T, Akhter T, Ujan JA, Algarni AS, et al. Deciphering Key Genes Involved in Cisplatin Resistance in Kidney Renal Clear Cell Carcinoma through a Combined in Silico and in Vitro Approach. Oncol Res. 2023;31(6):899–916. 10.32604/or.2023.030760 . Epub 2023/09/25. Kelly MR, Wisniewska K, Regner MJ, Lewis MW, Perreault AA, Davis ES, et al. A Multi-Omic Dissection of Super-Enhancer Driven Oncogenic Gene Expression Programs in Ovarian Cancer. Nat Commun. 2022;13(1):4247. 10.1038/s41467-022-31919-8 . Epub 2022/07/23. Zhang S, Guo A, Wang H, Liu J, Dong C, Ren J, et al. Oncogenic Morc2 in Cancer Development and Beyond. Genes Dis. 2024;11(2):861–73. 10.1016/j.gendis.2023.05.010 . Epub 2023/09/11. Duan WW, Yang LT, Liu J, Dai ZY, Wang ZY, Zhang H, et al. A Tgf-Beta Signaling-Related Lncrna Signature for Prediction of Glioma Prognosis, Immune Microenvironment, and Immunotherapy Response. CNS Neurosci Ther. 2024;30(4):e14489. 10.1111/cns.14489 . Epub 2023/10/18. Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ. Comparative Toxicogenomics Database (Ctd): Update 2023. Nucleic Acids Res. 2023;51(D1):D1257–62. 10.1093/nar/gkac833 . Epub 2022/09/29. Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The String Database in 2023: Protein-Protein Association Networks and Functional Enrichment Analyses for Any Sequenced Genome of Interest. Nucleic Acids Res. 2023;51(D1):D638–46. 10.1093/nar/gkac1000 . Epub 2022/11/13. Xiong T, Wang D, Yang H, Liu B, Li Y, Yu W, et al. Mir-194-3p Regulates Epithelial-Mesenchymal Transition in Embryonic Epicardial Cells Via P120/Beta-Catenin Signaling. Acta Biochim Biophys Sin (Shanghai). 2024;56(5):717–29. 10.3724/abbs.2024051 . Epub 2024/04/27. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 05 Apr, 2026 Editor invited by journal 27 Mar, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 26 Mar, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-9158731","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":617870100,"identity":"9ca5ad5f-1292-4190-8ffb-eaa12afe941f","order_by":0,"name":"Shuchun Xie","email":"","orcid":"","institution":"Ganzhou Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuchun","middleName":"","lastName":"Xie","suffix":""},{"id":617870101,"identity":"b8a19ce7-f8d2-4363-a41a-ad370b190113","order_by":1,"name":"Yan Tang","email":"","orcid":"","institution":"Xinghua People's Hospital Affiliated to Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Tang","suffix":""},{"id":617870102,"identity":"e4da5568-c919-4c32-9265-c6fdc3a480ad","order_by":2,"name":"Qiuxia Zhao","email":"","orcid":"","institution":"Xinghua People's Hospital Affiliated to Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Qiuxia","middleName":"","lastName":"Zhao","suffix":""},{"id":617870103,"identity":"68f2934a-ebc3-4059-8ab7-5786037284c1","order_by":3,"name":"Jianhui Ding","email":"","orcid":"","institution":"Hongze District People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jianhui","middleName":"","lastName":"Ding","suffix":""},{"id":617870104,"identity":"3ffd41d4-efbf-4891-a536-72ac639bc4c6","order_by":4,"name":"Xian Li","email":"","orcid":"","institution":"Xinghua People's Hospital Affiliated to Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xian","middleName":"","lastName":"Li","suffix":""},{"id":617870105,"identity":"d6ddb318-d0e1-4053-9ee6-48bfa4ea7861","order_by":5,"name":"Yue Wu","email":"","orcid":"","institution":"Xinghua People's Hospital Affiliated to Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Wu","suffix":""},{"id":617870106,"identity":"32ed9e01-53e8-4b0b-a5fc-279299f04d10","order_by":6,"name":"Yan Xu","email":"","orcid":"","institution":"Xinghua People's Hospital Affiliated to Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Xu","suffix":""},{"id":617870107,"identity":"7b2a2c72-f3e2-4a8e-aa7a-7e724271312b","order_by":7,"name":"Zixing Luo","email":"","orcid":"","institution":"Xinghua People's Hospital Affiliated to Yangzhou University","correspondingAuthor":false,"prefix":"","firstName":"Zixing","middleName":"","lastName":"Luo","suffix":""},{"id":617870108,"identity":"6dc13738-054d-4d5c-a4ea-7ab35735c536","order_by":8,"name":"Renjie Pan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYBADZjYGxoYDCRUScvIkaGFufPDgjIWxYQPxFrE3Gz5sq0hkOEBAnTn72QPMFRV32PnYG9skEudJJDA2MD98dAOPFsuevATGM2eeMbPxHARq2SaRx87AZmycg0eLwYEcA8bGtsPMbBKJYC3FjA08bNJ4tZx/A9TyD6hF/iFQyxyJxIYDhLTcANnSALKFsdkgsYEILZYzgLY0HANq4UlsfJBwTMLYsJmAX8z5gbY01BxOlm8//uDgj5o6OXn25oeP8ToMGB8/gHQyQogZj3KoFjCwI6BuFIyCUTAKRjIAANqRSZfjjArtAAAAAElFTkSuQmCC","orcid":"","institution":"Xinghua People's Hospital Affiliated to Yangzhou University","correspondingAuthor":true,"prefix":"","firstName":"Renjie","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2026-03-18 11:24:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9158731/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9158731/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106545350,"identity":"762d809b-41bb-4d3a-8721-ef927bc7541c","added_by":"auto","created_at":"2026-04-09 16:45:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3156839,"visible":true,"origin":"","legend":"\u003cp\u003eExpression status of NOL7 in the pancancer analysis. (A) Expression levels of NOL7 in tumor samples and paired normal tissues from different cancers in the TCGA database. (B) Combined with data from normal tissues in the GTEx database, Comparison of BRCA, LUAD, LUSC, BLCA, READ, UCEC, CESC, CHOL, COAD, GBM, PAAD, TGCT, KICH, OV, STAD, Box plots of CDCP1 expression levels for LAML and SKCM. (C) Based on the CPTAC dataset, comparison of breast cancer, Colon cancer, Ovarian cancer, Clear cell renal cell carcinoma, UCEC, CDCP1 protein expression levels in primary and normal tissues of Lung cancer and PAAD (* p \u0026lt; 0.05; * p \u0026lt; 0.001; *** p \u0026lt; 0.001)\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/6e0d5a69a0b1cbb9d774aac4.png"},{"id":106545353,"identity":"ee2d2386-1e98-4b5c-bba5-0401adf4ddb7","added_by":"auto","created_at":"2026-04-09 16:45:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":242744,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the relationship between CDCP1 expression and clinicopathological features.\u003cstrong\u003e \u003c/strong\u003eDetection of normal tissues, stages I, II, III, and IV ESCA using the TCGA dataset, HNSC, STAD, CESC, BLCA, BRCA, KICH, CHOL, UCEC, THCA, LUSC, LUAD, KICH, CHol, UCEC, THCA, LUSC, LUAD, Correlation between CDCP1 gene expression differences and major pathological stages in LIHC, KIRP, KIRC, COAD, READ, and PAAD tissues (* p \u0026lt; 0.05; ** p \u0026lt; 0.01; *** p \u0026lt; 0.001; ns No Significance)\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/2ec536a69dc90a0fb63f57af.png"},{"id":106545351,"identity":"63432fbf-7a91-4dbf-b26f-159676002e16","added_by":"auto","created_at":"2026-04-09 16:45:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1454117,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between CDCP1 gene expression and tumor survival prognosis in TCGA. We used the GEPIA2 tool to analyze the overall survival (A) and disease-free survival (B) of different tumors in the TCGA database by CDCP1 gene expression\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/9c1d3118a52af4499fa3787e.png"},{"id":106545357,"identity":"0a6696e8-0a3b-486e-a4d7-c446a5644dfc","added_by":"auto","created_at":"2026-04-09 16:45:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":883638,"visible":true,"origin":"","legend":"\u003cp\u003eDNA methylation levels of CDCP1 in multiple tumors (* p \u0026lt; 0.05; ** p \u0026lt; 0.01; *** p \u0026lt; 0.001)\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/3ecaa587fa6b20f6e7f59798.png"},{"id":106545354,"identity":"4d2da759-3102-44b9-9193-055d3556584b","added_by":"auto","created_at":"2026-04-09 16:45:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":973981,"visible":true,"origin":"","legend":"\u003cp\u003eMutational features of CDCP1 in different TCGA tumors. We analyzed the mutational features of CDCP1 in TCGA tumors using the cBioPortal tool, showing the mutation frequency of the CDCP1 gene (A) and the mutation types, loci, and number of cases in the CDCP1 gene (B). (C) Potential correlations between CDCP1 mutation status and DFS, DSS, OS, and PFS of cancer patients were analyzed using the cBioPortal tool\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/e4cf009819844fb36ba3d2cb.png"},{"id":106545355,"identity":"b56d5b39-8f32-4ea9-bb8a-bcc7fc1fd36d","added_by":"auto","created_at":"2026-04-09 16:45:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3229453,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between CDCP1 gene expression and MDSC infiltration. Heatmaps and scatterplots represent the relationship between MDSC infiltration and CDCP1 gene expression in different types of cancers in TCGA\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/718d5f9226b87804f8860778.png"},{"id":106545356,"identity":"f11032ff-1a9a-4d43-87ba-5f2fb930642e","added_by":"auto","created_at":"2026-04-09 16:45:25","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1336561,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of CDCP1 genes. (A) The top 100 genes associated with CDCP1 expression were obtained from the TCGA project, and the correlation of CDCP1 expression with selected target genes ANXA2, FAM83H, ZDHHC5, TUBA1C, and ARNTL2 was analyzed using GEPIA2. (B) A PPI network containing 20 experimentally validated CDCP1-interacting proteins. (C) Venn diagram cross-tabulation analysis of genes interacting with CDCP1 and genes associated with CDCP1 yielded 1 shared gene, EPH receptor A2 (EPHA2)\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/dd9f7538e88258c74d8bac98.png"},{"id":106726913,"identity":"07d105b7-4536-4e4d-a165-a298d6a32bbb","added_by":"auto","created_at":"2026-04-12 18:37:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13914736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/02552dec-2e1a-4cca-957d-160a156e2e5b.pdf"},{"id":106724973,"identity":"5304d5ba-38b2-4f45-a71a-ce259814f069","added_by":"auto","created_at":"2026-04-12 18:30:50","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":24717768,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9158731/v1/c052293633550a17e109aa25.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pancancer analysis of CDCP1 reveals its carcinogenic mechanisms and prognostic value as a survival-related target","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCancer is the leading cause of morbidity and mortality worldwide, poses a major health and economic burden on society, and is a serious impediment to increasing global life expectancy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. After more than a hundred years of development, cancer treatment strategies have evolved from surgery, radiotherapy, and chemotherapy to today's precision targeted therapies and immunotherapy, which have become the mainstream and most effective cancer treatment strategy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, the relative concentration of targets for drug development can easily lead to drug resistance problems, thus limiting the therapeutic efficacy of drugs and ultimately affecting the curability and prognosis of patients [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Therefore, there is an urgent need to find new cancer therapeutic targets and develop sensitive tumor biomarkers with potential therapeutic capabilities for better cancer diagnosis and treatment [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Pancancer analysis is an approach that enables systematic analysis of multiple cancer gene profiles, identifying commonalities and differences in key biological processes that are dysregulated in cancer cells from different lineages. This approach can be used to study the relationship between genes or molecules and cancer progression and is a promising tool for systematic analysis [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Through this systematic research approach, we can provide a solid theoretical foundation for the discovery of innovative therapeutic targets, the development of tumor-targeted drugs, and the further expansion of the population for targeted therapies.\u003c/p\u003e \u003cp\u003eCUB Domain Containing Protein1 (CDCP1) is a type I single-channel transmembrane glycoprotein, also known as CD318, SIMA135, gp140, or TRASK. This gene was first identified in colon cancer tissue by Scherl-Mostageer, and its expression was significantly upregulated compared to normal tissue. The CDCP1 gene was mapped to chromosome 3p21-p23 by fluorescence in situ hybridization [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Northern blot analysis, was utilized by John, showed that CDCP1 mRNA expression was low in normal human tissues, with the highest levels in skeletal muscle and colon. Immunohistochemical analysis showed that CDCP1 was expressed only in colonic epithelial cells of normal colonic mucosa. In colon tumors, CDCP1 expression was abnormal, showing extensive cell surface and cytoplasmic expression [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Studies have shown that CDCP1 is involved in key tumor metastatic signaling cascades, including SRC/PKCδ, PI3K/AKT, WNT, and RAS/ERK axes, the oxidized pentose phosphate pathway, and fatty acid oxidation, which are important for tumor cell proliferation, metastasis, and treatment resistance. In addition, elevated CDCP1 levels were also significantly associated with disease progression and poorer survival [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The multifaceted functions of CDCP1 suggest that its study may contribute to insights into the potential role of CDCP1 in malignant tumors. However, systematic evaluation of the role of CDCP1 in human cancers is still lacking.\u003c/p\u003e \u003cp\u003eConsidering the critical role of CDCP1 in cancer progression, we will combine multiple databases, including TCGA, GTEx, and CPTAC, to perform a systematic paradigm cancer analysis of CDCP1 in various human cancers. This comprehensive study aims to elucidate the potential functions and regulatory mechanisms of CDCP1 in the pathogenesis and clinical prognosis of a variety of cancer types, and to further substantiate its promising role as a diagnostic biomarker and therapeutic target for cancer therapy. This study may also broaden the application of CDCP1 in the development of immunotherapy and targeted therapy drugs.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Assessment of CDCP1 expression in different cancers and normal tissues\u003c/h2\u003e \u003cp\u003eWe first retrieved the interaction relationship of the CDCP1 gene with related genes at the subcellular level and protein level from the HPA database. The results showed that both at the subcellular level and protein level, CDCP1 interacts strongly with PRKCD, SRC, and SDCBP, with the weakest interaction with YES1 (Supplementary Fig.\u0026nbsp;1A). Next, we used the HPA database to retrieve the expression levels of CDCP1 in normal tissues and immune cells, and in general, CDCP1 showed low RNA specificity in various tissues and immune cells (Supplementary Fig.\u0026nbsp;1B-C).\u003c/p\u003e \u003cp\u003eIn addition, we constructed a map of CDCP1 expression landscape in different human cancers based on the TCGA database. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA shows the significant variability in CDCP1 transcript levels between 15 tumor tissues and adjacent normal tissues. Compared to normal tissue, the expression of CDCP1 was significantly increased in Bladder Urothelial Carcinoma (BLCA), Breast invasive carcinoma (BRCA), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), Cholangio carcinoma (CHOL), Esophageal carcinoma (ESCA), Glioblastoma multiforme (GBM), Head and Neck squamous cell carcinoma (HNSC), Kidney Chromophobe (KICH), Lung adenocarcinoma (LUAD), Lung squamous cell carcinoma (LUSC), Stomach adenocarcinoma (STAD), Thyroid carcinoma (THCA) and Uterine Corpus Endometrial Carcinoma (UCEC). In contrast, CDCP1 expression was significantly downregulated in Colon adenocarcinoma (COAD) and Prostate adenocarcinoma (PRAD) tissues compared to normal tissues. We also incorporated the GTEx database to supplement the number of normal tissues used as controls in the TCGA program. The results in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB show that, compared to normal tissue, CDCP1 expression was significantly upregulated in BRCA, LUAD, LUSC, BLCA, Rectum adenocarcinoma (READ), UCEC, CESC, CHOL, Colon adenocarcinoma (COAD), GBM, Pancreatic adenocarcinoma (PAAD), Testicular Germ Cell Tumors (TGCT), KICH, Ovarian serous cystadenocarcinoma (OV), and STAD. However, in Acute Myeloid Leukemia (LAML) and Skin Cutaneous Melanoma (SKCM) tissues, the expression of CDCP1 was significantly lower than that in normal tissues (all \u003cem\u003ep\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Moreover, we used the CPTAC dataset to detect differences in CDCP1 protein levels between tumor tissues and corresponding normal tissues. The results showed that expression of CDCP1 protein in Breast cancer, Colon cancer, Ovarian cancer, Clear cell renal cell carcinoma, UCEC, was significantly upregulated in Lung cancer and PAAD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Furthermore, we retrieved immunohistochemical staining images of CDCP1 protein in different tumor tissues and corresponding normal tissues (Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Analysis of the relationship between CDCP1 expression and clinicopathological features\u003c/h2\u003e \u003cp\u003eTo investigate the relationship between CDCP1 expression levels and clinicopathological features, we analyzed CDCP1 expression in normal tissues and stage I, II, III, and IV tumor tissues using the UALCAN database. Our results showed that CDCP1 gene expression was significantly upregulated during disease progression from normal tissues to different stages of malignant tumors, including ESCA, HNSC, STAD, CESC, BLCA, BRCA, KICH, CHOL, UCEC, THCA, LUSC, LUAD, LIHC, and KIRC. However, the expression of CDCP1 was significantly upregulated in tumors, including COAD and READ. CDCP1 expression did not change significantly during disease progression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, expression of CDCP1 protein was found to be significantly associated with disease progression in multiple cancers, including breast cancer, colon cancer, ccRCC, LUAD, PAAD, and UCEC (supplemental Fig S3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Survival analysis of pancancer analyzing CDCP1\u003c/h2\u003e \u003cp\u003eTo further assess the correlation between CDCP1 expression and the prognosis of human cancer patients, we investigated the correlation between CDCP1 expression and the prognosis of patients with different tumors using the TCGA database. The results showed that enhanced CDCP1 expression was significantly associated with higher overall survival (OS) in COAD (p\u0026thinsp;=\u0026thinsp;0.03) and SKCM (p\u0026thinsp;=\u0026thinsp;0.0051). While in HNSC (p\u0026thinsp;=\u0026thinsp;0.033), LAML (p\u0026thinsp;=\u0026thinsp;0.00021), Brain Lower Grade Glioma (LGG, p\u0026thinsp;=\u0026thinsp;8.2\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e), and LUAD (p\u0026thinsp;=\u0026thinsp;0.011), decreased CDCP1 expression was significantly associated with higher OS. The significance of LGG was most significant in all tumor types (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Disease-free survival (DFS) analysis data showed that low CDCP1 expression significantly improved DFS in GBM (p\u0026thinsp;=\u0026thinsp;0.011), LGG (p\u0026thinsp;=\u0026thinsp;3.2\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;5), and PAAD (p\u0026thinsp;=\u0026thinsp;0.03). The significance of LGG was the most significant among all tumor types (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In addition, reduced CDCP1 expression significantly improved Distant Metastasis Free Survival (DMFS) in breast cancer (p\u0026thinsp;=\u0026thinsp;0.024) and poorer Progression Free Survival (PFS) in ovarian cancer patients (p\u0026thinsp;=\u0026thinsp;0.018), as well as improved pancreatic cancer patients\u0026rsquo; Disease Free Survival (DFS) (p\u0026thinsp;=\u0026thinsp;0.0196), which were significantly associated (Supplementary Fig.\u0026nbsp;4). In addition, we conducted systematic subgroup analyses of breast, colorectal, lung, gastric, and ovarian cancers to explore the relationship between CDCP1 expression and prognosis in patients with different treatment groups (Supplementary Tables S1-S5).\u003c/p\u003e \u003cp\u003eNext, we utilized the Kaplan-Meier plotter to assess the prognostic impact of CDCP1 on patients with different types of cancer. We observed that dysregulated CDCP1 expression significantly affected OS in seven types of cancer. When CDCP1 expression is down-regulated, HNSC (p\u0026thinsp;=\u0026thinsp;0.0011), KIRC (p\u0026thinsp;=\u0026thinsp;0.00074), PAAD (p\u0026thinsp;=\u0026thinsp;0.00025), LIHC (p\u0026thinsp;=\u0026thinsp;0.032), LUAD (p\u0026thinsp;=\u0026thinsp;0.00011), LUSC (p\u0026thinsp;=\u0026thinsp;0.0061), and Thymoma (THYM) (p\u0026thinsp;=\u0026thinsp;0.00042) had a favorable prognosis (Supplementary Fig.\u0026nbsp;5A). Supplementary Fig.\u0026nbsp;5B shows that high CDCP1 expression predicted better recurrence-free survival (RFS) in Esophageal squamous cell carcinoma (ESCC, p\u0026thinsp;=\u0026thinsp;0.0067). However, enhanced CDCP1 expression predicted poorer RFS in LUAD (p\u0026thinsp;=\u0026thinsp;0.016), PAAD (p\u0026thinsp;=\u0026thinsp;0.0013), and TGCT (p\u0026thinsp;=\u0026thinsp;0.0051) (Supplementary Fig.\u0026nbsp;5B). In conclusion, these results suggest that CDCP1 expression can predict the prognostic survival of patients with different types of cancer, and the specific relationship between the expression level of CDCP1 and the prognosis of cancer patients depends on the tumor type.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Pancancer analysis of DNA methylation levels of CDCP1\u003c/h2\u003e \u003cp\u003eDNA methylation is a chemical modification that plays an important role in the regulation of gene expression [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Studies have shown that abnormal changes in DNA methylation can promote the occurrence and development of cancer [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Based on the TCGA database, we used UALCAN to explore the potential relationship between the DNA methylation level of CDCP1 and tumorigenesis. Compared with normal tissue, BLCA, BRCA, COAD, CESC, UCEC, Pheochromocytoma and Paraganglioma (PCPG), PRAD, and CDCP1 methylation was significantly downregulated in READ and Testicular Germ Cell Tumors (TGCT). In addition, methylation levels of CDCP1 were significantly upregulated in KIRP, KIRC, and PAAD compared with normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data from genetic alteration analysis of CDCP1\u003c/h2\u003e \u003cp\u003eWe observed the genetic alteration status of CDCP1 in different tumor samples from the TCGA database. The results showed that SKCM patients with \u0026ldquo;mutation\u0026rdquo; as the predominant type had the highest frequency of mutations in CDCP1 (\u0026gt;\u0026thinsp;7%). Amplified variants accounted for a significant proportion of the alterations in OV, KICH, ESCA, and PCPG (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The types, loci, and number of cases of CDCP1 gene alterations are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB. We found that missense mutations in CDCP1 were the main type of gene alteration. The study of the types and sites of CDCP1 gene alterations confirmed the R726*/Q shifted code insertion mutation in one case of LUSC, one case of uterine papillary serous carcinoma (UPSC), and one case of SKCM. The above results suggest that this is a hot spot mutation site in cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). We further examined the potential relationship between CDCP1 genetic alterations and the prognosis of patients with different types of cancer. The analysis results showed that genetic alterations in CDCP1 did not present significant differences with survival-related indices DFS, disease-specific survival (DSS), OS, and PFS in cancer patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). In addition, we analyzed the effects of TP53, BRAF, and KRAS gene mutations on CDCP1 expression in tumor tissues (Supplementary Fig.\u0026nbsp;6).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Correlation analysis of CDCP1 expression and immune infiltration of MDSCs\u003c/h2\u003e \u003cp\u003eStudies have shown that the tumor microenvironment (TME) contains many immune-infiltrating cells. The interaction between immune cells and tumor cells is closely related to cancer development, progression, or metastasis [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. We investigated different levels of immune cell infiltration for different cancer types in the TIMER database. As shown in Supplementary Table S6, the expression level of CDCP1 was significantly correlated with MDSC infiltration in BLCA, LGG, LIHC, LUAD, LUSC, OV, PAAD, PCPG, SKCM, and STAD. However, there was no generalized significant correlation between CDCP1 expression and infiltration of other subgroups of immune cells, including B cells, CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells, Treg cells, Tfh cells, γδ T cells, monocytes, macrophages, neutrophils, and DC cells. Therefore, we focused on MDSC in TME. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the heatmap and scatterplot showed the relationship between infiltration estimates and CDCP1 gene expression. The results showed that CDCP1 expression showed a significant positive correlation with MDSC infiltration level in most cancer types.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Analysis of CDCP1 gene correlation in pancancer analysis\u003c/h2\u003e \u003cp\u003eWe obtained the top 100 genes associated with CDCP1 expression in 33 human cancers based on GEPIA2. The top 5 related genes were ANXA2 (R\u0026thinsp;=\u0026thinsp;0.58), FAM83H (R\u0026thinsp;=\u0026thinsp;0.55), ZDHHC5 (R\u0026thinsp;=\u0026thinsp;0.55), TUBA1C (R\u0026thinsp;=\u0026thinsp;0.56), and ARNTL2 (R\u0026thinsp;=\u0026thinsp;0.57) (all \u003cem\u003ep\u003c/em\u003e-values\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). In addition, we collected the top 20 CDCP1-interacting proteins using the STRING database, and these identifications were supported by experimental evidence. The PPI network of these 20 proteins is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB. In addition, Venn diagram cross-analysis of the 20 genes that interacted with CDCP1 and the 100 genes related to CDCP1 finally revealed that the one common gene was EPHA2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). These results emphasize that there may be a close connection between CDCP1 and EPHA2, and the upstream and downstream regulatory roles between them can be further investigated experimentally.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Interacting chemicals and genes in CDCP1\u003c/h2\u003e \u003cp\u003eComparative Toxicogenomics Database (CTD) data showed that CDCP1 was associated with 40 chemicals, of which 31 upregulated CDCP1 and 10 downregulated CDCP1. In addition, one chemical, Arensic, affected CDCP1 expression, but the exact role is unclear (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, we showed the relationship between CDCP1 and 22 other genes by chemical association. The results show that CDCP1 was highly correlated with Transmembrane protein 158 (TMEM158), Laminin subunit gamma 2 (LAMC2), Exophilin 5 (EXPH5), Glutamine fructose 6 phosphate transaminase 2 (GFPT2), and Leucine-rich repeat and Ig domain containing 1 (LINGO1) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eInteracting chemicals of CDCP1 from CTD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemical name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChemical ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInteraction actions\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1,4-bis(2-(3,5-dichloropyridyloxy)) benzene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC028474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1-Butanol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD020001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2,4,5,2',4',5'-hexachlorobiphenyl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC014024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2-amino-2-methyl-1-propanol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC006551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3,4-dichloroaniline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC014464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4-(4-((5-(4,5-dimethyl-2-nitrophenyl)-2-furanyl) methylene) -4,5-dihydro-3-methyl-5-0xo-1H-pyrazol-1-yl) benzoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC584509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4-(5-benzo (1, 3) dioxol-5-yl-4-pyridin-2-yl-1H- imidazol-2-yl) benzamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC459179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7,8-Dihydro-7,8-dihydroxybenzo(a)pyrene 9,10-oxide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD015123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC496492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC030686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcetaminophen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD000082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcrylamide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD020106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAflatoxin B1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD016604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAir Pollutants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD000393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAldehydes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD000447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntirheumatic Agents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD018501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAristolochic acid l\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC000228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArsenic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD001151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAffects expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsbestos, Crocidolite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD017638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsbestos, Serpentine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD017632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD001554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(a)pyrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD001564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisphenolA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC006780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression Decreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisphenol F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC000611646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisphenol S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC543008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eButyraldehyde\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC018475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCadmium Chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD019256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcitriol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD002117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbon Tetrachloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD002251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDecamethrin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC017180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDibenzofurans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD000072318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDichlorodiphenyl Dichloroethylene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD003633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiethylhexyl Phthalate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD004051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiethylstilbestrol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD004054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiuron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD004237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDorsomorphin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC516138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDoxorubicin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD004317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression Increases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntinostat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC118739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpoxiconazole\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC109476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDecreases expression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErucylphospho-N, N, N-trimethylpropylammonium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC472787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIncreases expression\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=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelationship of CDCP1 with genes via chemical interaction, based on the CTD database\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGene ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimilarity index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCommon interacting chemicals\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMEM158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.368055556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAMC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.338383838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEXPH5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.333333333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFPT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.318181818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLINGO1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.317460317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFAP1L1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e134265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.314516129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC15ORF48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.314049587\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEBl3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.312056738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKCNK5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.310344828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBHLHE41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.309090909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLRATD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e157638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.307692308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRNF182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e221687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.307017544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMC6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.304964539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRISPLD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e83716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.303867403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYRIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.303278689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRNFT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.303278689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLC43A2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.302816901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eREEP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.302158273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNPT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30075188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCYB561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNPTX1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOASL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\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"},{"header":"3. Discussion","content":"\u003cp\u003eCDCP1, as a cell surface glycoprotein, has an important regulatory role in the normal biological functions of cells. It was initially found to be highly expressed in colon cancer tissues [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. With an in-depth study of this protein, it has been found that CDCP1 exhibits significant up-regulation in a variety of malignant tumors, including triple-negative breast cancer, lung adenocarcinoma, ovarian cancer, renal clear cell carcinoma, and acute myeloid leukemia, and it has emerged as a potential biomarker and therapeutic target for a range of cancers [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In human tumors, elevated CDCP1 expression is critical for tumor survival, growth, metastasis, and treatment resistance [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Through a literature search, we failed to retrieve any articles on the pan-cancer analysis of CDCP1 from the perspective of the tumor as a whole. Therefore, it is necessary to conduct a systematic paradigm cancer analysis of CDCP1 in various tumors. In this study, based on the data from TCGA, CPTAC and GEO databases, as well as the molecular features of gene expression, gene mutation, DNA methylation, etc., we conducted a systematic analysis of CDCP1 genes in 33 different tumors to explore in depth the effects of CDCP1 mutations on tumors, the relationship between CDCP1 and the tumor immune microenvironment, the prognostic value of CDCP1 expression in different types of cancers on the survival index of cancer patients, and the gene interaction network regulated by CDCP1, aiming to better understand the potential properties and role of CDCP1 in human cancers.\u003c/p\u003e \u003cp\u003eOur study found that of the 33 tumor tissues evaluated, significant abnormal expression of the CDCP1 gene was present in 15 tumor tissues compared to normal tissues, and 13 of them showed significant overexpression of CDCP1, accounting for 86.67% (13/15). Comprehensive comparison of these data with the CPTAC database revealed that both gene and protein expression levels of CDCP1 were significantly higher in BRCA, lung cancer, and UCEC. With disease progression, there was a consistent trend of up-regulation of the CDCP1 gene and protein expression in BRCA, KIRC, LUAD, PAAD, and UCEC. These results suggest that CDCP1 may have a role in promoting cancer progression and may serve as a promising diagnostic marker for the progression of these cancers and as a potential target for drug development. For example, Khan et al. showed that CDCP1 expression is elevated in most tumors and low in normal tissues using a comprehensive analysis of multiple normal and tumor tissues as well as tumor cell lines. It has been evaluated as an ideal therapeutic target for antibody drug Conjugate (ADC) development [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Whether CDCP1 can play a role in the pathogenesis of different tumors through certain common molecular mechanisms remains to be further investigated. Representative images from immunohistochemical analysis showed that CDCP1 protein expression was up-regulated in most tumor tissues compared to normal tissues, showing significant cytoplasmic and cell membrane localization. In conclusion, these findings confirm the upregulation of CDCP1 expression in a wide range of cancers, suggesting a promising future for CDCP1 in cancer diagnosis and treatment.\u003c/p\u003e \u003cp\u003eIn addition, we tried to evaluate the predictive role of CDCP1 for the survival of patients with different tumors; therefore, we used the GEPIA2 database to analyze the prognostic relationship between CDCP1 and patients with different types of tumors. These results demonstrated the good prognostic value of CDCP1 for various types of tumors. Among them, low expression of CDCP1 significantly improved OS and DFS in LGG patients, while high expression of CDCP1 significantly improved PFS and PPS in OV patients. These results illustrate that CDCP1 is a good biomarker for predicting prognostic survival in LGG and OV patients. Based on these observations, we can hypothesize the critical role of CDCP1 in the progression of LGG and OV, and the mechanism of CDCP1\u0026rsquo;s role in the progression of LGG and OV can be further investigated by experiments in the future.\u003c/p\u003e \u003cp\u003eDNA methylation is one of the most important epigenetic mechanisms regulating gene expression, and aberrant DNA methylation is strongly associated with diseases, including cancer [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Therefore, we further explored the level of DNA methylation changes of CDCP1 in various types of tumors. We found that the DNA methylation level of CDCP1 was significantly down-regulated in most types of tumors (BLCA, BRCA, COAD, CESC, UCEC, PCPG, PRAD, READ, and TGCT), which was consistent with the up-regulation of CDCP1 in the majority of tumor tissues, showing an important role of CDCP1 in tumor tissues. Tumorigenesis is a complex process accompanied by abnormal cell proliferation, inhibition of apoptosis, the role of TME, enhanced angiogenesis, and evasion of immunity. Among them, TME plays a key role. TME consists of cellular components and extracellular matrix, and the cellular components include stromal fibroblasts, infiltrating immune cells, blood and lymphatic vascular networks, etc [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Studies have shown that the interaction of cancer cells with various components of TME can lead to immune escape effects of tumor cells. Therefore, it is necessary to explore the characteristics of multiple immune cells and the mechanisms of their interaction with tumors. Our results showed that CDCP1 expression was significantly correlated with the infiltration levels of multiple immune cells, including B cells, CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells, Tregs, Tfh, γδT, Monocytes, Macrophage, Neutrophil, DC, and MDSC, in various types of tumors. By understanding the relationship between CDCP1 gene expression and the level of tumor immune cell infiltration, we can find that in most cancer types, CDCP1 expression is positively correlated with the level of MDSC infiltration. Finally, we analyzed the database to obtain the 100 genes most associated with CDCP1, and we cross-analyzed the 100 genes and the 20 genes in the network of interactions with CDCP1 to obtain the only shared gene, EPHA2.\u003c/p\u003e \u003cp\u003eTargeted therapy is a promising therapeutic approach involving characteristic drugs that target cells or proteins that induce tumor progression. Targeted therapy uses a certain drug to inhibit key biomarkers that sustain the growth and proliferation of cancer cells, thereby inhibiting tumor progression, so the development of tumor-targeted drugs is a current research hotspot [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. We identified 40 chemical substances that may regulate CDCP1 expression using CTD and analyzed the 20 genes most closely related to CDCP1 by chemical association. Future studies can further explore the mechanism of action of chemicals regulating CDCP1 genes, and can apply chemicals to CDCP1-expressing tumor cells to assess the effects of chemicals on tumor cells, to enable the development of innovative targeted drugs.\u003c/p\u003e"},{"header":"4 Materials and methods","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Gene expression analysis\u003c/h2\u003e \u003cp\u003eDifferences in expression between normal and tumor tissues in the TCGA database were assessed using TIMER 2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://timer.cistrome.org/\u003c/span\u003e\u003cspan address=\"http://timer.cistrome.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) based on the TCGA database [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Combining normal tissue data in the GTEx database with TCGA data, we used GEPIA2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia2.cancer-pku.cn/\u003c/span\u003e\u003cspan address=\"http://gepia2.cancer-pku.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to study the expression of CDCP1 between different types of cancer and normal tissues [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Download the expression data of the CDCP1 gene in different tissues and immune cells, as well as immunohistochemical expression images in different types of tumor tissues and normal tissues from the HPA database. Sample sources are provided at HPA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.proteinatlas.org/\u003c/span\u003e\u003cspan address=\"https://www.proteinatlas.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In addition, we used the UALCAN database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ualcan.path.uab.edu/analysis-prot.html\u003c/span\u003e\u003cspan address=\"http://ualcan.path.uab.edu/analysis-prot.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e to visualize the CPTAC dataset, and we obtained differences in the expression level of total CDCP1 protein between tumor tissues [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Survival Prognosis Analysis\u003c/h2\u003e \u003cp\u003eKaplan-Meier plot (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"http://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e was used to analyze the effects of different types of cancer on survival prognosis (DMFS, PPS, FP, PFS, and DFS) in the GEO database [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Tumor patients were divided into two groups, Kaplan-Meier survival curves were obtained, and log-rank p-values and HRs were calculated. We used the GEPIA2 tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia2.cancer-pku.cn/\u003c/span\u003e\u003cspan address=\"http://gepia2.cancer-pku.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to analyze the effect of CDCP1 on the survival of cancer patients. We entered the CDCP1 gene into the \"Survival analysis\" module, selected custom cancer types, and the high and low expression cohorts were divided by high (50%) and low (50%) cutoff values, and performed OS and DFS analyses using the log-rank test.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.3 DNA methylation analysis and genetic alteration analysis\u003c/h2\u003e \u003cp\u003eWe used the UALCAN tool to explore the differences in CDCP1 DNA methylation levels between different types of tumor tissues and normal tissues. In addition, we utilized the cBioPortal web (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org/\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to analyze the genetic variation, Alteration frequency, mutation site, and survival data of CDCP1 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Analysis of immune infiltration\u003c/h2\u003e \u003cp\u003eWe used TIMER2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://timer.cistrome.org/\u003c/span\u003e\u003cspan address=\"http://timer.cistrome.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to perform a systematic analysis of immune infiltration across cancer types [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. We obtained data on the correlation between CDCP1 expression and the level of immune infiltration in different types of cancer. We analyzed some important immune infiltrating cells, including B cells, CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells, Tregs, Tfh cells, γδT cells, monocytes, macrophages, neutrophils, DC, and MDSCs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Interaction of CDCP1 with chemicals and genes\u003c/h2\u003e \u003cp\u003eThe Comparative Toxicogenomics Database (CTD, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ctdbase.org/\u003c/span\u003e\u003cspan address=\"http://ctdbase.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) is an innovative digital ecological public database that links toxicological information on chemicals, genes, phenotypes, diseases, and exposures and can be used to study new connections between chemicals and the molecular mechanisms underlying their biological effects [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. We used this database to query for chemicals that interact with CDCP1 and to explore genes that interact with related chemicals and are highly similar to CDCP1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Gene enrichment analysis\u003c/h2\u003e \u003cp\u003eTo explore the regulatory network of CDCP1 in cancer, the top 20 CDCP1-interacting genes were downloaded using the STRING tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cn.string-db.org/\u003c/span\u003e\u003cspan address=\"https://cn.string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e, and the PPI network was visualized using Cytoscape [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In addition, we obtained the top 100 CDCP1-related genes through GEPIA2. In the \"Correlation analysis\" module of GEPIA2, the top five genes associated with CDCP1 were tested for Pearson correlation to obtain p-values, dot plots, and correlation coefficients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSX, YT and QZ prepared the original manuscript draft. JD and XL participated in conceptualization. YW, YX and ZL participated in guiding the preparation and design of this manuscript. RP reviewed and edited the paper. Data authentication is not applicable. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkhmedullin R, Aimyshev T, Zhakhina G, Yerdessov S, Beyembetova A, Ablayeva A, et al. In-Depth Analysis and Trends of Cancer Mortality in Kazakhstan: A Joinpoint Analysis of Nationwide Healthcare Data 2014\u0026ndash;2022. 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Epub 2024/04/27.\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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CDCP1, pancancer analysis, prognosis, tumorigenesis, DNA methylation, immune infiltration, biomarker","lastPublishedDoi":"10.21203/rs.3.rs-9158731/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9158731/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlthough a growing body of evidence indicates that CDCP1 plays a crucial role in cancer initiation and progression, there remains a lack of systematic analysis regarding CDCP1 in cancer. Here, we conducted a comprehensive study of CDCP1 based on the Cancer Genome Atlas (TCGA) and the Clinical Proteomics Oncology Analysis Consortium (CATPAC) databases, aiming to explore its potential role and detailed mechanisms in 33 human tumors. The results showed that CDCP1 was highly expressed in many cancers, and the expression of CDCP1 was significantly correlated with the prognosis of cancer patients. DNA methylation levels of CDCP1 tended to decrease in most cancers and were inversely correlated with CDCP1 expression, which in addition significantly correlated with the level of infiltrating cells. In summary, the pancancer study described the relationship between CDCP1 expression and clinicopathological features in multiple cancer types, further showing its potential regulatory role in human cancer. This study is a systematic analysis of the function and role of CDCP1, which is a relatively comprehensive understanding of the oncogenic role of CDCP1 in different tumors.\u003c/p\u003e","manuscriptTitle":"Pancancer analysis of CDCP1 reveals its carcinogenic mechanisms and prognostic value as a survival-related target","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-09 16:45:19","doi":"10.21203/rs.3.rs-9158731/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-05T19:25:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-27T05:46:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-26T18:52:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-26T12:47:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2026-03-26T12:41:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"98ac9c91-7324-4b3d-b774-7ad5724e8407","owner":[],"postedDate":"April 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-09T16:45:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-09 16:45:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9158731","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9158731","identity":"rs-9158731","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}