p27 Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer

p27 Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article p27 Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer Mengna Zhu, Si Sun, Lin Huang, Lingling Gao, Mengqing Chen, Jing Cai, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3195821/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose The biological function of p27 Kip1 largely depends on its subcellular localization and phosphorylation status. Different subcellular localization and phosphorylation status of p27 Kip1 may represent distinct clinical values, which are not entirely clear in ovarian cancer. This study aimed to elucidate different subcellular localizations of p27 Kip1 and pSer10p27 in predicting prognosis and chemotherapy response in ovarian cancer. Methods Meta-analyses were executed to evaluate the association of p27 Kip1 and phosphorylated p27 Kip1 with the prognosis of ovarian cancer patients. The expression levels and patterns of p27 Kip1 and pSer10p27 were evaluated by immunohistochemistry (IHC). The correlations between different p27 Kip1 states and clinicopathological features as well as prognosis were analyzed. p27 Kip1 and pSer10p27 expression level in cisplatin-sensitive and cisplatin-resistant ovarian cancer cell lines were detected using WB. KEGG analysis and WB were performed to evaluate the involved pathways of p27 Kip1 . Results Meta-analyses showed that p27 Kip1 was associated with significantly better overall survival (OS) in ovarian cancer (HR = 2.14; 95% CI [1.71 - 2.68]) and pSer10p27 was associated with significantly poor OS in mixed solid tumors (HR = 2.56; 95% CI [1.76 - 3.73]) In our cohort of ovarian cancer patients, low total p27 Kip1 remained independent risk factors for OS (HR = 2.097; 95% CI [1.121 - 3.922], P = 0.021) and PFS (HR = 2.483; 95% CI [1.364 - 4.518], P = 0.003), while low cytoplasmic pSer10p27 had independent protective effects in terms of OS (HR = 0.472; 95% CI [0.248 - 0.898], P = 0.022) and PFS (HR = 0.488; 95% CI [0.261 - 0.910], P = 0.024). Patients with low total p27 Kip1 /pSer10p27 and low nuclear p27 Kip1 had worse chemotherapy response while patients with low cytoplasmic pSer10p27 expression had better chemotherapy response. The protein levels of p27 Kip1 and pSer10p27 were significantly reduced in cisplatin resistant cell lines SKOV3-cDDP and A2780-cDDP and the level of p27 Kip1 /pSer10p27 was subjective to Akt activation. Conclusion The present study demonstrates that p27 Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer. Ovarian cancer Prognosis Chemotherapy response p27Kip1 Phosphorylation Overall survival Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Ovarian cancer is one of the most lethal malignancy of the female reproductive system worldwide (Duan et al. 2023 ). Due to the lack of early diagnosis methods, more than 70% of patients reach advanced stages at the time of diagnosis (Dochez et al. 2019 ). Although ovarian cancer patients can benefit from a combination of tumor reduction and platinum-based adjuvant chemotherapy after diagnosis, the relapse occurs in 70% − 80% of patients with International Federation of Gynecology and Obstetrics stage III to IV disease (FIGO III - IV) within 5 years. Due to the emergence of platinum resistance, adjuvant treatment options including PARP inhibitor Olaparib have been greatly limited (Pignata et al. 2019 ). Enriching platinum-based chemotherapy associated biomarkers may provide evidence for developing novel treatment strategy through identification of novel patient selection markers and therapeutic targets. p27 Kip1 protein, a cyclin-dependent kinase inhibitor, has long been known as a tumor suppressor (Polyak 2006 ; Bury et al. 2021 ). However, in recent years, it has been found that p27 Kip1 plays a pivotal dual role in tumorigenesis (Yoon et al. 2019 ). The p27 Kip1 protein structure has a CDK-binding domain, which allows it to bind and inhibit CDK or CDK-cyclin complex in the nucleus, arresting the cell cycle (Blain et al. 2003 ; Oboshi et al. 2020 ). p27 Kip1 can be functionally disrupted in cancer through excessive proteolysis, reduced translation or C-terminal phosphorylation (Chu et al. 2008 ; Larrea et al. 2009 ). However, different from previous findings, some studies have shown that p27 Kip1 is not completely localized in the nucleus hence different functions (Lian et al. 2019 ). Phosphorylation of p27 Kip1 promotes its nuclear-cytoplasmic trans-localization, which deprives the nuclear function of p27 Kip1 as a CDK inhibitor. Miscellaneous phosphorylation sites of p27 Kip1 have been reported and Ser10, Thr157, Thr187 and Thr198 were the most extensively studied (Ishida et al. 2000 ; Abbastabar et al. 2018 ; Bencivenga et al. 2021 ). Among these phosphorylation sites, Ser10 phosphorylation of p27 Kip1 determines protein stability and subcellular localization (Ishida et al. 2000 ; Xiao et al. 2023 ). However, whether the different localization of p27 Kip1 and pSer10p27 are associated with the prognosis and response to chemotherapy in ovarian cancer needs to be further explored. In the present study, we investigated the correlation of different localization of p27 Kip1 and pSer10p27 with chemotherapy response and prognosis in ovarian cancer. We found that total p27 Kip1 and cytoplasmic pSer10p27 could better predict chemotherapy response and were independent prognostic factors in ovarian cancer. These results provide a new basis for the prediction of chemotherapy response and prognosis in ovarian cancer. Materials and methods Public data gathering and mining The association of CDKN1B with overall survival (OS) and progression-free survival (PFS) in ovarian cancer was validated at the transcriptome level using the Kaplan-Meier (KM) plotter with JetSet probe set. KM curves, P -values and hazard ratios (HRs) with 95% confidence intervals (CIs) were generated by log-rank test and univariate cox proportional hazards regression. The GEPIA database was used to analyze the expression distribution of CDKN1B in ovarian serous cystadenocarcinoma (OV) and normal tissues. The genomic alterations of CDKN1B including copy number variations (CNVs ) and mutations were detected in 585 ovarian cancer samples from TCGA's Pan-Cancer Atlas project and the association between genomic alterations in CDKN1B and survival of ovarian cancer patients was provided through the cBioPortal database (Cerami1 et al. 2012 ). The “clusterProfiler” package in R 4.2.3 software was used to perform the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes between the CDKN1B high group and the CDKN1B low group from the TCGA-OV database. Meta-analysis Electronic search of PubMed, Embase and Web of Science from January 1990 to May 2021 was conducted with the following key words: 'ovarian cancer', 'ovarian carcinoma' or 'ovarian neoplasm' and 'p27 Kip1 ' or 'phosphorylation of p27 Kip1 '. The search strategies were supplemented by reviewing similar articles and checking references of the retrieved literatures. In addition, we searched the reference lists of all selected publications. Data were extracted in the access database, which was independently reviewed by two authors to determine which studies met the following criteria: 1) assessed the relevance of p27 Kip1 protein levels or phosphorylated p27 Kip1 protein levels to patients’ prognosis by IHC staining; 2) published as full text in English. We excluded reviews, non-original articles and studies on ovarian cancer cell lines or on animal models. In survival prognostic analysis, we assessed the prognostic impact of p27 Kip1 protein levels or phosphorylated p27 Kip1 protein levels by HR. HRs and 95% CIs were extracted. If these parameters were not available in the study, we used Engauge Digitizer 4.1 software to extract specific survival according to the Kaplan-Meier curves and calculated HRs by the method described by Tierney et al (Tierney et al. 2007 ). Upon cohort overlapping, only the largest cohort was included in the analysis. The meta-analysis was performed using R 4.2.3 software. Considering possible heterogeneities among studies, we calculated the overall HR, I 2 and P -value using a random effects model. Cell culture and drugs Ovarian cancer cell lines SKOV3 (adenocarcinoma) was purchased from the American Type Culture Collection (ATCC, USA) and A2780 (adenocarcinoma) was purchased from BLUEFBIO company. Parental cells were treated with increasing concentrations of cisplatin for 12 cycles to obtain cisplatin-resistant cell lines SKOV3-cDDP and A2780-cDDP (Sun et al. 2018 ). All cells were cultured in DMEM/F12 medium supplemented with 10% fetal bovine serum. Cisplatin-resistant cell lines were given 0.5 µg/ml cisplatin to maintain resistance. All cells were grown in a humidified incubator at 37°C 5% CO 2 . Cisplatin was purchased from the Department of Pharmacy, Wuhan Union Hospital. MK2206 was purchased from Selleck (S1078, USA). Cell viability assay The cellular viability was assessed via MTT assays. MTT reagents were purchased from Aladdin, Shanghai, China. Ovarian cancer cells were seeded into 96-well plates at a density of 5 × 10 3 cells per well and incubated until the next day. Then cisplatin at different concentrations (0.005 µM, 0.05 µM, 0.5 µM, 5 µM, 10 µM, 20 µM, 40 µM or 80 µM) were given to the cells for 72 hours. Subsequently, 20 µL of MTT solution (5 mg/mL) was added to each well and incubated at 37℃ for 4 hours. Subsequently, 150 µL dimethyl sulfoxide was added to each well and the plate was shaken in the dark until the crystals were completely dissolved. Finally, the absorbance at 570 nm was measured using a microplate reader (SpectraMax, Sunnyvale, CA, USA). The IC 50 values of drugs in different cell lines were analyzed with GraphPad Prism 9.4 (USA) software. Western blotting analysis Western blot (WB) was performed to detect p27 Kip1 , pSer10p27, Akt, p-Akt and β-actin protein levels in ovarian cancer cell lines. Total protein extraction process and WB were performed as previously described (Wen et al. 2021 ). The primary antibodies used were anti-p27 Kip1 antibody (Proteintech; 25614-1-AP; 1:1000 dilution), anti-pSer10p27 antibody (Abcam; ab62364; 1:1000 dilution), anti-Akt (CST; 2920S; 1:1000 dilution), anti-p-Akt (Ser473) antibody (CST; 4060S; 1:1000 dilution) and anti-β-actin antibody (ABclonal; AC026; 1:10000 dilution). The experiments were performed in three biological replicates. RNA extraction and quantitative Real-Time PCR (qRT-PCR) qRT-PCR was used to detect CDKN1B mRNA levels in ovarian cancer cell lines. Briefly, total RNA from ovarian cancer cells was extracted using TRIzol reagent (Takara, Japan), followed by reverse transcription. qRT-PCR was performed on a Step-One Plus Real-Time PCR system using SYBR Green PCR Master Mix (Vazyme, China). The relative expression of each mRNA was normalized using 2 −∆∆Ct method. The primers used in this study were GAPDH (Forward): 5’- TCCCATCACCATCTTCCAG-3’, GAPDH (Reverse): 5’-ATGAGTCCTTCCACGATACC-3’, CDKN1B (Forward): 5’-AACGTGCGAGTGTCTAACGG-3’, CDKN1B (Reverse): 5’- CCCTCTAGGGGTTTGTGATTCT-3’. The experiments were performed in three biological replicates. Clinical samples and clinical characteristics collection The clinical tissue microarrays consisted of 51 ovarian cancer patients’ tissue samples from Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. All patients underwent surgery and received standard platinum-based chemotherapy. Clinical and pathological data were collected retrospectively. Basic patient characteristics included age, histological type, International Federation of Gynecology and Obstetrics (FIGO) stage, treatment regimen, chemotherapy response, and follow-up information. Chemotherapy resistance was defined by relapse within six months after completing chemotherapy or progression during the primary chemotherapy. Relapses were diagnosed on clinical symptoms, radiological evidence and biochemical abnormalities such as elevated CA125. OS was defined as from diagnosis to death or date of last follow-up, PFS was defined as from surgery to relapse or date of last follow-up. Diagnoses of all patients were confirmed pathologically. This study was approved by Independence Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (20210567). Immunohistochemistry (IHC) and its evaluation IHC staining of tissue microarrays were performed according to the previously described protocol (Li et al. 2021 ). Primary antibodies were anti-p27 Kip1 antibody (Proteintech; 25614-1-AP; 1:50 dilution) and anti-pSer10p27 antibody (Abcam; ab62364; 1:100 dilution). IHC staining scores for p27 Kip1 and pSer10p27 was evaluated according to total expression (total positive staining was evaluated without considering localization), nuclear expression (only nuclear staining was evaluated) and cytoplasmic expression (only cytoplasmic staining was evaluated), respectively. Total and cytoplasmic IHC scores were assessed according to the following formula: staining intensity (0, negative; 1, weak; 2, mild; 3, strong) and staining area (0, 0%; 1, 75%). Nuclear IHC score was assessed according to the following formula: percentage of positive tumor cells (0, 0%; 1, 75%) and staining intensity (0, negative; 1, weak; 2, mild; 3, strong). Statistical analysis Data was analyzed using GraphPad Prism 9.4 and SPSS 27.0 software. The χ 2 test and Fisher’s exact were used to analyze the relationship between IHC scores of p27 Kip1 and pSer10p27 and clinicopathological characteristics in ovarian cancer. The Spearman’s correlation test was used to analyze the correlation between p27 Kip1 and pSer10p27, and the Mann Whitney test was used to compare the difference between the two groups. Receiver operating characteristic (ROC) curve were plotted to analyze the value of total, nuclear and cytoplasmic p27 Kip1 and pSer10p27 in predicting chemotherapeutic efficacy. Logistic and cox regression were used to analyze the risk of chemotherapy response and survival. Chemotherapeutic efficacy was evaluated using odd ratio (OR). Survival curves were plotted and analyzed using the Kaplan-Meier method and log-rank test. Differences were considered statistically significant at P < 0.05. Results Meta-analysis of the correlation between p27 Kip1 /pSer10p27 and prognosis in ovarian cancer patients The correlation of p27 Kip1 protein with progression-free survival (PFS) and overall survival (OS) in ovarian cancer patients was first evaluated. A total of 650 studies were identified through literature search after duplicates-removal (N = 12) and study-exclusion after initial review of titles and abstracts (N = 589). After data-check, 9 studies with 805 patients were included in the meta-analysis. Low p27 Kip1 protein level was associated with poor OS (HR = 2.14; 95% CI [1.71–2.68]) and PFS (HR = 1.61; 95% CI [0.93–2.78]) in ovarian cancer. (Fig. 1 A and Supplementary Fig. 1A). In addition, CDKN1B (encoding p27 Kip1 protein) mRNA levels were negatively correlated with OS (HR = 1.23; 95% CI [1.07–1.41]) and PFS (HR = 1.28; 95% CI [1.12–1.45]) in ovarian cancer using the KM-Plotter database analysis (Supplementary Fig. 2A, B). According to the expression analysis from GEPIA database, CDKN1B was significantly reduced in ovarian cancer tissues compared to paired normal tissues (Supplementary Fig. 2C). According to the genomic alterations of CDKN1B including CNVs and mutations in 585 ovarian cancer samples from the cBioportal database (Supplementary Fig. 2D), CDKN1B was relatively conserved and had rare frequency of alteration (5%), which did not show statistically significant associations with PFS and OS in the cohort (Supplementary Fig. 2E, F). Therefore, we assumed that the correlation between p27 Kip1 and prognosis of ovarian cancer patients might mainly be due to the change of protein levels and status of phosphorylation. Furthermore, we performed another meta-analysis including 5 studies with 428 patients to analyze the prognostic effects of phosphorylation modifications of p27 Kip1 that might affect their protein level changes in tumors and found that high Ser10 phosphorylation modification of p27 Kip1 was associated with poor OS (HR = 2.56; 95% CI [1.76–3.73]) in ovarian cancer (Fig. 1 B). Level of total p27 Kip1 and total pSer10p27 in ovarian cancer correlated with chemotherapy response and prognosis. To further validate the results of meta-analysis and bioinformatics analysis, we used immunohistochemistry (IHC) to assess the total positive staining of p27 Kip1 and pSer10p27 in the nuclear and cytoplasm in ovarian cancer tissue microarrays (Fig. 2 A, B). Both total p27 Kip1 (46/51) and total pSer10p27 (34/51) can be robustly detected in most specimens and total pSer10p27 positively correlated with total p27 Kip1 as expected (Spearman r = 0.323, P = 0.021) (Fig. 2 C). The clinical significances of total p27 Kip1 and total pSer10p27 in ovarian cancer were subsequently analyzed. Total p27 Kip1 expression level was significantly correlated with chemotherapy response ( P < 0.001) and total pSer10p27 expression level was correlated with chemotherapy response ( P = 0.001) (Fig. 2 D and Table 1 ). Univariate cox regression analysis and Kaplan-Meier survival analysis showed that low total p27 Kip1 expression was associated with poor OS (HR = 2.323; 95% CI [1.269–4.255], P = 0.006) and PFS (HR = 2.654; 95% CI [1.472–4.784], P = 0.001) (Fig. 2 E, F and Table 2 ). These results suggest that total p27 Kip1 expression correlates with chemotherapy response and prognosis. Table 1 Association between total of p27 Kip1 and pSer10p27 to clinical pathological features in ovarian cancer by IHC-score stratification a Clinicopathological features N p27 Kip1 (Total b ) N pSer10p27 (Total) Low High P Low High P Age (years) c 0.572 0.470 < 50 20 10 10 20 4 16 ≥ 50 31 13 18 31 9 22 Histology 0.965 0.417 High grade serous 42 19 23 42 12 30 Others 9 4 5 9 1 8 FIGO stage d 0.037 0.309 I-II 14 3 11 14 5 9 III-IV 37 20 17 37 8 29 Chemo response < 0.001 0.027 Sensitive 37 11 26 37 6 31 Resistant 14 12 2 14 7 7 a The median IHC score was chosen as the cut-offs for total p27 Kip1 and total pSer10p27 b total positive staining was evaluated without considering localization c Age at surgery d International Federation of Gynecology and Obstetrics Table 2 Univariate Cox regression survival analysis PFS OS HR 95% CI P HR 95% CI P Age (< 50 vs ≥ 50y) 1.738 0.969–3.116 0.064 1.281 0.705–2.329 0.416 Histology (high grade serous vs others) 0.503 0.239–1.062 0.072 0.386 0.179–0.830 0.015 FIGO stage (I-II vs III-IV) 0.470 0.237–0.932 0.031 0.594 0.291–1.214 0.153 p27 Kip1 (Total) expression (low vs high) 2.654 1.472–4.784 0.001 2.323 1.269–4.255 0.006 p27 Kip1 (Nuc a ) expression (low vs high) 1.563 0.881–2.772 0.127 1.933 1.063–3.515 0.031 p27 Kip1 (Cyt b ) expression (low vs high) 1.129 0.632–2.017 0.682 1.252 0.686–2.285 0.464 pSer10p27 (Total) expression (low vs high) 0.838 0.407–1.728 0.633 0.787 0.375–1.649 0.525 pSer10p27 (Nuc) expression (low vs high) 1.507 0.829–2.739 0.179 1.533 0.819–2.869 0.182 pSer10p27 (Nuc) expression (low vs high) 0.509 0.286–0.904 0.021 0.473 0.258–0.865 0.015 a only nuclear staining was evaluated b only cytoplasmic staining was evaluated Different expression patterns of p27 Kip1 and pSer10p27 predict chemotherapy response and prognosis of ovarian cancer. Since previous studies that reported correlation between p27 Kip1 and patients’ prognosis did not specify the subcellular location of p27 Kip1 , we analyzed different subcellular locations of p27 Kip1 and pSer10p27 as well as their underlying clinical values. Four expression patterns of p27 Kip1 and pSer10p27 were identified: nuclear and cytoplasmic dominant (NCD), nuclear dominant (ND), cytoplasmic dominant (CD) and nuclear and cytoplasmic weak-to-none (NCWN) (Fig. 3 A, B). We also analyzed the compositional proportion of the four expression patterns of p27 Kip1 and pSer10p27 (Fig. 3 C). The patients with NCD, ND, CD and NCWN expression pattern of p27 Kip1 and pSer10p27 accounted for 33.33%, 13.73%, 43.14%, 9.80% and 13.73%, 17.65%, 35.29%, 33.33% respectively. Around 1/3 to 1/2 of patients presented CD pattern of p27 Kip1 or pSer10p27. 47.06% of p27 Kip1 positive patients were accompanied with positive pSer10p27 staining. The inexistence of pSer10p27 positive/p27 Kip1 negative pattern suggested the robustness of the staining. We then explored the correlation of nuclear and cytoplasmic p27 Kip1 /pSer10p27 with clinical features. Nuclear p27 Kip1 ( P = 0.020), nuclear pSer10p27 ( P = 0.010) and cytoplasmic pSer10p27 ( P < 0.001) were significantly correlated with chemotherapy response (Fig. 3 D, E and Table 3 ). Logistic regression analysis revealed that patients with low expression of total p27 Kip1 (OR = 14.182; 95% CI [2.711–74.188], P = 0.002), nuclear p27 Kip1 (OR = 4.615; 95% CI [1.207–17.656], P = 0.025) total pSer10p27 (OR = 5.167; 95% CI [1.320–20.220], P = 0.018) and nuclear pSer10p27 (OR = 11.050; 95% CI [1.308–93.380], P = 0.027) had worse chemotherapy response, while patients with low cytoplasmic pSer10p27 expression (OR = 0.047; 95% CI [0.006–0.398], P = 0.005) had better chemotherapy response (Table 4 ). The ROC curves showed that the area under the curve (AUC) for total p27 Kip1 and cytoplasmic pSer10p27 were 0.780 and 0.775 respectively (Fig. 3 F). Univariate cox regression analysis and Kaplan-Meier survival analysis showed that low cytoplasmic pSer10p27 expression was associated with better OS (HR = 0.473; 95% CI [0.258–0.865], P = 0.015) and PFS (HR = 0.509; 95% CI [0.286–0.904], P = 0.021) (Fig. 3 G, H and Table 2 ). Multivariate cox regression analyses showed that low total p27 Kip1 remained independent risk factors for OS (HR = 2.097; 95% CI [1.121–3.922], P = 0.021) and PFS (HR = 2.483; 95% CI [1.364–4.518], P = 0.003), while high cytoplasmic pSer10p27 had independent protective effects in terms of OS (HR = 0.472; 95% CI [0.248–0.898], P = 0.022) and PFS (HR = 0.488; 95% CI [0.261–0.910], P = 0.024) (Table 5 ). These results suggested that total p27 Kip1 and cytoplasmic pSer10p27 had promising predictive values for chemotherapy response and prognosis. Table 3 Association between p27 Kip1 and pSer10p27 to clinical pathological features in the nuclear and cytoplasm of ovarian cancer by IHC-score stratification Clinicopathological features N p27 Kip1 (Nuc) p27 Kip1 (Cyt) pSer10p27 (Nuc) pSer10p27 (Cyt) Low High P Low High P Low High P Low High P Age (years) 0.557 0.108 0.311 0.050 < 50 20 8 12 7 13 5 15 6 14 ≥ 50 31 15 16 18 13 12 19 18 13 Histology 0.159 0.726 0.699 0.718 High grade serous 42 21 21 20 22 15 27 19 23 Others 9 2 7 5 4 2 7 5 4 FIGO stage 0.145 0.072 1.000 0.375 I–II 14 4 10 4 10 5 9 8 6 III–IV 37 19 18 21 16 12 25 16 21 Chemo response 0.020 0.072 0.010 < 0.001 Sensitive 37 13 24 21 16 20 17 23 14 Resistant 14 10 4 4 10 13 1 1 13 Table 4 Association of different parameters and chemotherapy resistance in ovarian cancer Chemotherapy resistance OR 95% CI P Age (< 50 vs ≥ 50y) 2.778 0.786–9.819 0.113 Histology (high grade serous vs others) 0.710 0.151–3.334 0.664 FIGO stage (I-II vs III-IV) 0.142 0.017–1.211 0.074 p27 Kip1 (Total) expression (low vs high) 14.182 2.711–74.188 0.002 p27 Kip1 (Nuc) expression (low vs high) 4.615 1.207–17.656 0.025 p27 Kip1 (Cyt) expression (low vs high) 0.305 0.081–1.152 0.080 pSer10p27 (Total) expression (low vs high) 5.167 1.320–20.220 0.018 pSer10p27 (Nuc) expression (low vs high) 11.050 1.308–93.380 0.027 pSer10p27 (Cyt) expression (low vs high) 0.047 0.006–0.398 0.005 Table 5 Multivariate Hazard Cox regression survival analysis PFS OS HR 95% CI P HR 95% CI P Age (< 50 vs ≥ 50y) 1.350 0.699–2.609 0.372 0.916 0.455–1.845 0.806 Histology (high grade serous vs others) 0.339 0.151–0.760 0.009 0.280 0.124–0.634 0.002 FIGO stage (I-II vs III-IV) 0.645 0.306–1.359 0.249 0.844 0.372–1.913 0.685 p27 Kip1 (Total) expression (low vs high) 2.483 1.364–4.518 0.003 2.097 1.121–3.922 0.021 pSer10p27 (Cyt) expression (low vs high) 0.488 0.261–0.910 0.024 0.472 0.248–0.898 0.022 Low expression of p27 Kip1 and pSer10p27 are associated with cisplatin resistance in platinum-resistant ovarian cancer cell lines To further investigate the relationship between p27 Kip1 /pSer10p27 and platinum resistance in ovarian cancer, we constructed cisplatin-resistant ovarian cancer cell lines SKOV3-cDDP and A2780-cDDP. The SKOV3-cDDP (IC50 = 44.40 µM) and A2780-cDDP (IC50 = 16.93 µM) cell lines were more resistant to cisplatin compared to the parental SKOV3 (IC50 = 12.22 µM) and A2780 (IC50 = 3.04 µM) validated by MTT (Fig. 4 A, B). The protein levels of p27 Kip1 and pSer10p27 were significantly reduced in SKOV3-cDDP and A2780-cDDP (Fig. 4 C). Similarly, CDKN1B mRNA levels were also reduced in the cisplatin-resistant cell lines (Fig. 4 D). These results suggested that increased p27 Kip1 and pSer10p27 levels were associated with increased cisplatin sensitivity in ovarian cancer. KEGG enrichment analysis of differentially expressed genes between the CDKN1B high group and the CDKN1B low group from the TCGA-OV database was mainly associated with cell cycle, cellular senescence and PI3K-Akt signaling pathway (Fig. 4 E). Considering some studies suggest that p27 Kip1 is phosphorylated at Ser10 by Akt (Fujita et al. 2002 ; Liang et al. 2002 ), we further investigated whether the level of pSer10p27 was subjective to Akt activation. The level of pS473Akt1 in cisplatin resistant cell lines was generally higher than that in the parental cell lines (Fig. 4 F, G). Inhibition of pS473Akt1 by MK2206 was accompanied with evident increase of p27 Kip1 /pSer10p27 in SKOV3-cDDP but not in A2780-cDDP (Fig. 4 F, G). These results suggested that inhibition of pS473Akt1 by MK2206 could to some extent restore p27 Kip1 and pSer10p27 in certain cell lines. Discussion In this study, we first investigated the overall prognostic values of p27 Kip1 and pSer10p27 in ovarian cancer by meta-analysis and bioinformatic data analysis, then evaluated the expression pattern of p27 Kip1 /pSer10p27 and subsequently assessed the correlation of p27 Kip1 /pSer10p27 with different subcellular localizations to OS, PFS and chemotherapy response of ovarian cancer patients through IHC staining using tissue microarrays. Finally, the association of p27 Kip1 /pSer10p27 with cisplatin-resistance was further validated in two cisplatin-resistant ovarian cancer cell lines. These results suggest that not only the total levels of p27 Kip1 /pSer10p27 but also nuclear p27 Kip1 and cytoplasmic pSer10p27 may influence ovarian cancer progression and chemotherapy response. p27 Kip1 was originally identified as a 27 kD non-tyrosine protein, which bound to various cyclin-CDK complexes in non-proliferating cells and leads to CDK inhibition and G1 arrest (Polyak et al. 1994 ; Toyoshima and Hunter 1994 ). The canonical role of p27 Kip1 as a major cell cycle regulator had become even more conclusive when evidence mounted and the protein-coding gene of p27 Kip1 , CDKN1B , was therefore regarded as a representative putative tumor-suppressor. Conformably, the tissue sample based p27 Kip1 level in various types of cancer are concordantly correlated with patients’ prognosis (Porter et al. 1997 ; Chiarle et al. 2000 ). Earlier findings suggested that in addition to anti-tumor effect, p27 Kip1 was also involved in regulation of embryonic stem cell differentiation (Li et al. 2012 ), cytokinesis (Serres et al. 2012 ) and actomyosin contractions (Godin et al. 2012 ). More recently, novel functions of p27 Kip1 were characterized including regulation of DNA damage response in P53 deficient cells (Cannell et al. 2015 ), transcriptional regulation and control of autophagic vesicle trafficking (Yoon et al. 2019 ). Since driver gene and tumor-suppressor mutation is one of the major theories of tumorigenesis, the mutational profile of CDKN1B is naturally studied. Multiple sets of data based on tissue specimens and cell lines all indicated that CDKN1B was rarely mutated in almost all tumor types (Kawamata et al. 1995 ; Shin et al. 2000 ), which suggested the importance of post-transcriptional modification on CDKN1B . The correlation between decreased p27 Kip1 protein level and poor prognosis of ovarian cancer patients was validated by our results together with several previous studies (Shigemasa et al. 2001 ; Schmider-Ross et al. 2006 ; Lu et al. 2011 ; Felix et al. 2015 ). In previous studies, cytoplasmic p27 Kip1 was observed but only nuclear p27 Kip1 was evaluated in ovarian cancer cohorts possibly due to the reason that only nuclear p27 Kip1 had access to CDKs. However, several recent studies suggested that in addition to nuclear p27 Kip1 , cytoplasmic p27 Kip1 also had prognostic effect in certain types of cancer such as nasopharyngeal carcinoma and osteosarcoma (Chen et al. 2020 ; Teng et al. 2020 ). According to our results, in accordance with previous studies low nuclear p27 Kip1 was associated with poor prognosis and higher risk of chemotherapy resistance. Although without statistical significance, patients with low cytoplasmic p27 Kip1 were apt to be chemotherapy-sensitive suggesting that a high nuclear and low cytoplasmic pattern might be most conducive to p27 Kip1 exerting its anti-cancer effect. Accumulating evidences reveal that cytoplasmic p27 Kip1 has distinct biological functions from nuclear ones (Serres et al. 2011 ; Li et al. 2016 ; Calvayrac et al. 2019 ). The translocation of p27 Kip1 from nuclear to cytoplasm could either resulted in degradation (Morishita et al. 2008 ), cytoplasmic sequestration (Kim et al. 2009 ), or even tumor promotion (Shin et al. 2002 ). The fate and function of cytoplasmic p27 Kip1 was tightly linked to p27 Kip1 phosphorylation. Up to date, around 10 sites of p27 Kip1 phosphorylation had been identified. Ser10 phosphorylation of p27 Kip1 represented nuclear export signal while Thr157 and Thr198 phosphorylation of p27 Kip1 blocked its nuclear entry and held for p27 Kip1 cytoplasmic retention (Lian et al. 2019 ). The dynamic process of nuclear-cytoplasmic p27 Kip1 translocation driven by different phosphorylation statuses might present as various p27 Kip1 subcellular expression pattern when evaluated cross-sectionally. Since pSer10p27 triggered p27 Kip1 export and blocked it from CDK, we further analyzed the relationship between different subcellular locations of pSer10p27 and clinical characteristics (e.g., age, histological type, FIGO stage, tumor type, response to chemotherapy and prognosis) in ovarian cancer patients. We found that patients with high cytoplasmic pSer10p27 state had higher risk of chemotherapy resistance and poor OS/PFS, which might suggest that cytoplasmic export of p27 Kip1 diminished the anti-cancer effect of p27 Kip1 . Quite a few studies reported the involvement of p27 Kip1 in cisplatin resistance recently (Huang et al. 2022 ; Li et al. 2022 ; Su et al. 2023 ). Cisplatin exerts anti-cancer effect by forming cisplatin-DNA adducts. Cells damaged by cisplatin usually go through G1 arrest and then apoptosis. Recent study showed that cells relied on p27 Kip1 for G1 arrest when P53 was deficient (La et al. 2023 ). As P53 mutation occurred in nearly 90% of high-grade serous ovarian cancer patients, the level of p27 Kip1 could be of noteworthy clinical significance. Here we found that p27 Kip1 and pSer10p27 were significantly decreased in cisplatin-resistant cell lines SKOV3-cDDP and A2780-cDDP. After inhibition of pS473Akt1 by MK2206, the levels of p27 Kip1 and pSer10p27 were restored in SKOV3-cDDP but not in A2780-cDDP. This was possibly due to natural deficiency of P53 in SKOV3 cells. In summary, our study provides evidence that different subcellular localizations of p27 Kip1 and pSer10p27 correlate with chemotherapy response and prognosis and can be used as potential biomarkers to assess chemotherapy response and prognosis in ovarian cancer. Declarations Acknowledgements We thanked Dr. Yujia Ma and Dr. Zheng Wei for providing valuable technical support. This work was funded by the National Natural Science Foundation of China (82002771, 82002766). Author contributions Mengna Zhu, Si Sun, Jing Cai, Zehua Wang and Minggang Peng contributed to the study conception and design. Material preparation, data collection and analysis were performed by Mengna Zhu, Si Sun and Lin Huang. Mengna Zhu and Si Sun wrote the manuscript and all authors analyzed and interpreted the data, read, revised and approved the final version of the manuscript. Funding This work was funded by the National Natural Science Foundation of China (grant number 82002771) and the National Natural Science Foundation of China (grant number 82002766). Data availability Public data sets of OV analyzed during the current study can be retrieved from TCGA database (https://portal.gdc.cancer.gov/), Kaplan-Meier Plotter (http://kmplot.com/analysis/index.php?p=service&cancer=ovar), GEPIA database (http://gepia.cancer-pku.cn/) and cBioPortal database (https://www.cbioportal.org/). Other data that support the findings of this study are available from the corresponding author on reasonable request. Competing interests The authors have no relevant financial or non-financial interests to disclose. Ethical approval This study was approved by Independence Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (20210567). Consent to publish Not applicable. 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Also discoverable on Platform About In Review Editorial Policies 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-3195821","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":221541857,"identity":"0b3d266e-cd25-4c81-a1f1-cb4879f97896","order_by":0,"name":"Mengna Zhu","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mengna","middleName":"","lastName":"Zhu","suffix":""},{"id":221541858,"identity":"948d215e-9075-42be-947c-d7d9dc31b930","order_by":1,"name":"Si Sun","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Si","middleName":"","lastName":"Sun","suffix":""},{"id":221541859,"identity":"72e854e0-aab9-4bff-b106-bc8a9d562cb3","order_by":2,"name":"Lin Huang","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Huang","suffix":""},{"id":221541860,"identity":"5eaa402f-3b63-418d-a147-33826751a711","order_by":3,"name":"Lingling Gao","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lingling","middleName":"","lastName":"Gao","suffix":""},{"id":221541861,"identity":"02b6ea99-8489-4b91-8fca-a52d2592e537","order_by":4,"name":"Mengqing Chen","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mengqing","middleName":"","lastName":"Chen","suffix":""},{"id":221541862,"identity":"42e5b315-8293-4800-bbf5-77da3da5b2b7","order_by":5,"name":"Jing Cai","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Cai","suffix":""},{"id":221541863,"identity":"255ebb1b-c3f1-4b41-a316-5a60044afb59","order_by":6,"name":"Zehua Wang","email":"","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zehua","middleName":"","lastName":"Wang","suffix":""},{"id":221541864,"identity":"74746278-d997-40f1-90be-1af3bda46a06","order_by":7,"name":"Minggang Peng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYBCDBAYJ5mNwNrFa2NKAtAFJWnjMiNOi27/24OOCX4fzDG73fHvM8+cPAz97jgHDzx24tZjdeJdsPLPvcLHBnbPbjXnbDBgke94YMPaewafljJk0b8/txA03crdJ8zYYMBjcyDFgZmzDq8X8N0RLzjNpnj8GDPYEtZzvMWPm+QHWwibNwwa0RYKgLXzJQPf8T5x5I81Mcm6bMY/EmWcFB3vx2nL24GeeP2mJfTeSn0m8+SMnx9+evPHBTzxaGCRyGBiQncEDIg7g0cDAwA8Kzj94lYyCUTAKRsFIBwAP6VdOK56H+gAAAABJRU5ErkJggg==","orcid":"","institution":"Wuhan Union Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Minggang","middleName":"","lastName":"Peng","suffix":""}],"badges":[],"createdAt":"2023-07-23 06:29:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3195821/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3195821/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":40834998,"identity":"b1616ebd-dd8c-42b4-8c66-bf9885319c9f","added_by":"auto","created_at":"2023-07-31 17:08:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":537531,"visible":true,"origin":"","legend":"\u003cp\u003eThe prognosis of p27\u003csup\u003eKip1\u003c/sup\u003e and phosphorylated p27\u003csup\u003eKip1 \u003c/sup\u003ein ovarian cancer. (A) Meta-analysis of p27\u003csup\u003eKip1\u003c/sup\u003e associated with overall survival in ovarian cancer. (B) Meta-analysis of phosphorylated p27\u003csup\u003eKip1\u003c/sup\u003e associated with overall survival in different cancers\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3195821/v1/5ca11c0b29b65ea2cb6d2ef0.png"},{"id":40834697,"identity":"699ec149-266e-4e2e-8219-4f341a5d9d46","added_by":"auto","created_at":"2023-07-31 17:00:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6220410,"visible":true,"origin":"","legend":"\u003cp\u003eThe chemotherapy response and prognosis of total p27\u003csup\u003eKip1\u003c/sup\u003e and total pSer10p27 in ovarian cancer. (A-B) Representative images of total p27\u003csup\u003eKip1\u003c/sup\u003e and total pSer10p27 staining in ovarian cancer tissues (200 × and 400 ×). (C) Positive correlation between the IHC score of total p27\u003csup\u003eKip1\u003c/sup\u003e and total pSer10p27 (Spearman’s correlation test). (D) Boxplots of semi-quantification of total p27\u003csup\u003eKip1\u003c/sup\u003e and total pSer10p27 expression levels in sensitive and resistant groups (Mann Whitney test). (E-F) Kaplan-Meier plots for progression-free survival and overall survival in ovarian cancer patients with total p27\u003csup\u003eKip1\u003c/sup\u003e level\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-3195821/v1/3987a0f42304c30320fa2c4b.png"},{"id":40834694,"identity":"69f828b0-da77-4542-a0f7-0fe408bdf16f","added_by":"auto","created_at":"2023-07-31 17:00:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":6319277,"visible":true,"origin":"","legend":"\u003cp\u003eDifferent subcellular localization of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 predicted chemotherapy response and prognosis for ovarian cancer. (A-B) Different expression patterns of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 staining such as nuclear and cytoplasmic dominant (NCD), nuclear dominant (ND), cytoplasmic dominant (CD) and nuclear and cytoplasmic weak-to-none (NCWN) in ovarian cancer tissues (400 ×). (C) Sankey diagram of the relationship between different expression patterns of p27Kip1 and pSer10p27. (D-E) Boxplots of semi-quantification of nuclear expression (Nuc) and cytoplasmic expression (Cyt) of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 in sensitive and resistant groups (Mann Whitney test). (F) ROC curves of different subcellular localization of p27Kip1 and pSer10p27 predicting chemotherapy response. (G-H) Kaplan-Meier plots for progression-free survival and overall survival in ovarian cancer patients with cytoplasmic pSer10p27 level\u003c/p\u003e","description":"","filename":"Fig.3.png","url":"https://assets-eu.researchsquare.com/files/rs-3195821/v1/ab4a678b59814ee3ddc759b0.png"},{"id":40834696,"identity":"2a7d39fb-980f-471d-9982-8c11707076b9","added_by":"auto","created_at":"2023-07-31 17:00:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1427596,"visible":true,"origin":"","legend":"\u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 associated with cisplatin resistance in ovarian cancer cells. (A-B) Cell viability analysis of parental and cisplatin-resistant cells under treatment with cisplatin at various concentrations for 72h. IC\u003csub\u003e50\u003c/sub\u003e of the indicated cells under treatment with cisplatin. Bars represent mean ± SD (n = 3). (C) Western blot for phosphorylated Ser10 and total p27\u003csup\u003eKip1\u003c/sup\u003e in the two paired parental and cisplatin-resistant cell lines. β-actin served as a loading control (n = 3). (D) The mRNA levels of \u003cem\u003eCDKN1B\u003c/em\u003e in parental and cisplatin-resistant cells. Bars represent mean ± SD (n = 3). (E) KEGG enrichment analysis of \u003cem\u003eCDKN1B\u003c/em\u003e-related upregulated genes. Fourteen representative pathways are displayed. (F-G) Western blot for phosphorylated and total p27\u003csup\u003eKip1\u003c/sup\u003e and phosphorylated and total Akt in the two paired parental and cisplatin-resistant cell lines after treated with DMSO and 5 µM MK2206 for 24h. β-actin served as a loading control (n = 3)\u003c/p\u003e","description":"","filename":"Fig.4.png","url":"https://assets-eu.researchsquare.com/files/rs-3195821/v1/3b85620e7a4613ae0e4830c4.png"},{"id":42968653,"identity":"5ab8e0ad-968a-446a-a55f-3c1abc8ea4a3","added_by":"auto","created_at":"2023-09-12 02:07:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2518981,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3195821/v1/1a5ecde9-29a9-4951-b0df-585c088bb10b.pdf"},{"id":40834698,"identity":"fdc795c1-f609-48c5-b7a4-0be6e37bcea6","added_by":"auto","created_at":"2023-07-31 17:00:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":636926,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3195821/v1/ce6eb3f202aef5813591e60b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"p27 Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOvarian cancer is one of the most lethal malignancy of the female reproductive system worldwide (Duan et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Due to the lack of early diagnosis methods, more than 70% of patients reach advanced stages at the time of diagnosis (Dochez et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Although ovarian cancer patients can benefit from a combination of tumor reduction and platinum-based adjuvant chemotherapy after diagnosis, the relapse occurs in 70% \u0026minus;\u0026thinsp;80% of patients with International Federation of Gynecology and Obstetrics stage III to IV disease (FIGO III - IV) within 5 years. Due to the emergence of platinum resistance, adjuvant treatment options including PARP inhibitor Olaparib have been greatly limited (Pignata et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Enriching platinum-based chemotherapy associated biomarkers may provide evidence for developing novel treatment strategy through identification of novel patient selection markers and therapeutic targets.\u003c/p\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e protein, a cyclin-dependent kinase inhibitor, has long been known as a tumor suppressor (Polyak \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Bury et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, in recent years, it has been found that p27\u003csup\u003eKip1\u003c/sup\u003e plays a pivotal dual role in tumorigenesis (Yoon et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The p27\u003csup\u003eKip1\u003c/sup\u003e protein structure has a CDK-binding domain, which allows it to bind and inhibit CDK or CDK-cyclin complex in the nucleus, arresting the cell cycle (Blain et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Oboshi et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). p27\u003csup\u003eKip1\u003c/sup\u003e can be functionally disrupted in cancer through excessive proteolysis, reduced translation or C-terminal phosphorylation (Chu et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Larrea et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, different from previous findings, some studies have shown that p27\u003csup\u003eKip1\u003c/sup\u003e is not completely localized in the nucleus hence different functions (Lian et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Phosphorylation of p27\u003csup\u003eKip1\u003c/sup\u003e promotes its nuclear-cytoplasmic trans-localization, which deprives the nuclear function of p27\u003csup\u003eKip1\u003c/sup\u003e as a CDK inhibitor. Miscellaneous phosphorylation sites of p27\u003csup\u003eKip1\u003c/sup\u003e have been reported and Ser10, Thr157, Thr187 and Thr198 were the most extensively studied (Ishida et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Abbastabar et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Bencivenga et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Among these phosphorylation sites, Ser10 phosphorylation of p27\u003csup\u003eKip1\u003c/sup\u003e determines protein stability and subcellular localization (Ishida et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Xiao et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, whether the different localization of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 are associated with the prognosis and response to chemotherapy in ovarian cancer needs to be further explored.\u003c/p\u003e \u003cp\u003eIn the present study, we investigated the correlation of different localization of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 with chemotherapy response and prognosis in ovarian cancer. We found that total p27\u003csup\u003eKip1\u003c/sup\u003e and cytoplasmic pSer10p27 could better predict chemotherapy response and were independent prognostic factors in ovarian cancer. These results provide a new basis for the prediction of chemotherapy response and prognosis in ovarian cancer.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e \u003cb\u003ePublic data gathering and mining\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe association of \u003cem\u003eCDKN1B\u003c/em\u003e with overall survival (OS) and progression-free survival (PFS) in ovarian cancer was validated at the transcriptome level using the Kaplan-Meier (KM) plotter with JetSet probe set. KM curves, \u003cem\u003eP\u003c/em\u003e-values and hazard ratios (HRs) with 95% confidence intervals (CIs) were generated by log-rank test and univariate cox proportional hazards regression. The GEPIA database was used to analyze the expression distribution of \u003cem\u003eCDKN1B\u003c/em\u003e in ovarian serous cystadenocarcinoma (OV) and normal tissues. The genomic alterations of \u003cem\u003eCDKN1B\u003c/em\u003e including copy number variations (CNVs ) and mutations were detected in 585 ovarian cancer samples from TCGA's Pan-Cancer Atlas project and the association between genomic alterations in \u003cem\u003eCDKN1B\u003c/em\u003e and survival of ovarian cancer patients was provided through the cBioPortal database (Cerami1 et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The \u0026ldquo;clusterProfiler\u0026rdquo; package in R 4.2.3 software was used to perform the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes between the \u003cem\u003eCDKN1B\u003c/em\u003e\u003csup\u003ehigh\u003c/sup\u003e group and the \u003cem\u003eCDKN1B\u003c/em\u003e\u003csup\u003elow\u003c/sup\u003e group from the TCGA-OV database.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeta-analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eElectronic search of PubMed, Embase and Web of Science from January 1990 to May 2021 was conducted with the following key words: 'ovarian cancer', 'ovarian carcinoma' or 'ovarian neoplasm' and 'p27\u003csup\u003eKip1\u003c/sup\u003e' or 'phosphorylation of p27\u003csup\u003eKip1\u003c/sup\u003e'. The search strategies were supplemented by reviewing similar articles and checking references of the retrieved literatures. In addition, we searched the reference lists of all selected publications. Data were extracted in the access database, which was independently reviewed by two authors to determine which studies met the following criteria: 1) assessed the relevance of p27\u003csup\u003eKip1\u003c/sup\u003e protein levels or phosphorylated p27\u003csup\u003eKip1\u003c/sup\u003e protein levels to patients\u0026rsquo; prognosis by IHC staining; 2) published as full text in English. We excluded reviews, non-original articles and studies on ovarian cancer cell lines or on animal models. In survival prognostic analysis, we assessed the prognostic impact of p27\u003csup\u003eKip1\u003c/sup\u003e protein levels or phosphorylated p27\u003csup\u003eKip1\u003c/sup\u003e protein levels by HR. HRs and 95% CIs were extracted. If these parameters were not available in the study, we used Engauge Digitizer 4.1 software to extract specific survival according to the Kaplan-Meier curves and calculated HRs by the method described by Tierney et al (Tierney et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Upon cohort overlapping, only the largest cohort was included in the analysis. The meta-analysis was performed using R 4.2.3 software. Considering possible heterogeneities among studies, we calculated the overall HR, \u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e and \u003cem\u003eP\u003c/em\u003e-value using a random effects model.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCell culture and drugs\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOvarian cancer cell lines SKOV3 (adenocarcinoma) was purchased from the American Type Culture Collection (ATCC, USA) and A2780 (adenocarcinoma) was purchased from BLUEFBIO company. Parental cells were treated with increasing concentrations of cisplatin for 12 cycles to obtain cisplatin-resistant cell lines SKOV3-cDDP and A2780-cDDP (Sun et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). All cells were cultured in DMEM/F12 medium supplemented with 10% fetal bovine serum. Cisplatin-resistant cell lines were given 0.5 \u0026micro;g/ml cisplatin to maintain resistance. All cells were grown in a humidified incubator at 37\u0026deg;C 5% CO\u003csub\u003e2\u003c/sub\u003e. Cisplatin was purchased from the Department of Pharmacy, Wuhan Union Hospital. MK2206 was purchased from Selleck (S1078, USA).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCell viability assay\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe cellular viability was assessed via MTT assays. MTT reagents were purchased from Aladdin, Shanghai, China. Ovarian cancer cells were seeded into 96-well plates at a density of 5 \u0026times; 10\u003csup\u003e3\u003c/sup\u003e cells per well and incubated until the next day. Then cisplatin at different concentrations (0.005 \u0026micro;M, 0.05 \u0026micro;M, 0.5 \u0026micro;M, 5 \u0026micro;M, 10 \u0026micro;M, 20 \u0026micro;M, 40 \u0026micro;M or 80 \u0026micro;M) were given to the cells for 72 hours. Subsequently, 20 \u0026micro;L of MTT solution (5 mg/mL) was added to each well and incubated at 37℃ for 4 hours. Subsequently, 150 \u0026micro;L dimethyl sulfoxide was added to each well and the plate was shaken in the dark until the crystals were completely dissolved. Finally, the absorbance at 570 nm was measured using a microplate reader (SpectraMax, Sunnyvale, CA, USA). The IC\u003csub\u003e50\u003c/sub\u003e values of drugs in different cell lines were analyzed with GraphPad Prism 9.4 (USA) software.\u003c/p\u003e \u003cp\u003e \u003cb\u003eWestern blotting analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWestern blot (WB) was performed to detect p27\u003csup\u003eKip1\u003c/sup\u003e, pSer10p27, Akt, p-Akt and β-actin protein levels in ovarian cancer cell lines. Total protein extraction process and WB were performed as previously described (Wen et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The primary antibodies used were anti-p27\u003csup\u003eKip1\u003c/sup\u003e antibody (Proteintech; 25614-1-AP; 1:1000 dilution), anti-pSer10p27 antibody (Abcam; ab62364; 1:1000 dilution), anti-Akt (CST; 2920S; 1:1000 dilution), anti-p-Akt (Ser473) antibody (CST; 4060S; 1:1000 dilution) and anti-β-actin antibody (ABclonal; AC026; 1:10000 dilution). The experiments were performed in three biological replicates.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRNA extraction and quantitative Real-Time PCR (qRT-PCR)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eqRT-PCR was used to detect \u003cem\u003eCDKN1B\u003c/em\u003e mRNA levels in ovarian cancer cell lines. Briefly, total RNA from ovarian cancer cells was extracted using TRIzol reagent (Takara, Japan), followed by reverse transcription. qRT-PCR was performed on a Step-One Plus Real-Time PCR system using SYBR Green PCR Master Mix (Vazyme, China). The relative expression of each mRNA was normalized using 2\u003csup\u003e\u0026minus;∆∆Ct\u003c/sup\u003e method. The primers used in this study were GAPDH (Forward): 5\u0026rsquo;- TCCCATCACCATCTTCCAG-3\u0026rsquo;, GAPDH (Reverse): 5\u0026rsquo;-ATGAGTCCTTCCACGATACC-3\u0026rsquo;, CDKN1B (Forward): 5\u0026rsquo;-AACGTGCGAGTGTCTAACGG-3\u0026rsquo;, CDKN1B (Reverse): 5\u0026rsquo;- CCCTCTAGGGGTTTGTGATTCT-3\u0026rsquo;. The experiments were performed in three biological replicates.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinical samples and clinical characteristics collection\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe clinical tissue microarrays consisted of 51 ovarian cancer patients\u0026rsquo; tissue samples from Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. All patients underwent surgery and received standard platinum-based chemotherapy. Clinical and pathological data were collected retrospectively. Basic patient characteristics included age, histological type, International Federation of Gynecology and Obstetrics (FIGO) stage, treatment regimen, chemotherapy response, and follow-up information. Chemotherapy resistance was defined by relapse within six months after completing chemotherapy or progression during the primary chemotherapy. Relapses were diagnosed on clinical symptoms, radiological evidence and biochemical abnormalities such as elevated CA125. OS was defined as from diagnosis to death or date of last follow-up, PFS was defined as from surgery to relapse or date of last follow-up. Diagnoses of all patients were confirmed pathologically. This study was approved by Independence Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (20210567).\u003c/p\u003e \u003cp\u003e \u003cb\u003eImmunohistochemistry (IHC) and its evaluation\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIHC staining of tissue microarrays were performed according to the previously described protocol (Li et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Primary antibodies were anti-p27\u003csup\u003eKip1\u003c/sup\u003e antibody (Proteintech; 25614-1-AP; 1:50 dilution) and anti-pSer10p27 antibody (Abcam; ab62364; 1:100 dilution). IHC staining scores for p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 was evaluated according to total expression (total positive staining was evaluated without considering localization), nuclear expression (only nuclear staining was evaluated) and cytoplasmic expression (only cytoplasmic staining was evaluated), respectively. Total and cytoplasmic IHC scores were assessed according to the following formula: staining intensity (0, negative; 1, weak; 2, mild; 3, strong) and staining area (0, 0%; 1, \u0026lt; 25%; 2, 25% \u0026minus;\u0026thinsp;50%; 3, 50% \u0026minus;\u0026thinsp;75%; 4, \u0026gt; 75%). Nuclear IHC score was assessed according to the following formula: percentage of positive tumor cells (0, 0%; 1, \u0026lt; 25%; 2, 25% \u0026minus;\u0026thinsp;50%; 3, 50% \u0026minus;\u0026thinsp;75%; 4, \u0026gt; 75%) and staining intensity (0, negative; 1, weak; 2, mild; 3, strong).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData was analyzed using GraphPad Prism 9.4 and SPSS 27.0 software. The χ \u003csup\u003e2\u003c/sup\u003e test and Fisher\u0026rsquo;s exact were used to analyze the relationship between IHC scores of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 and clinicopathological characteristics in ovarian cancer. The Spearman\u0026rsquo;s correlation test was used to analyze the correlation between p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27, and the Mann Whitney test was used to compare the difference between the two groups. Receiver operating characteristic (ROC) curve were plotted to analyze the value of total, nuclear and cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 in predicting chemotherapeutic efficacy. Logistic and cox regression were used to analyze the risk of chemotherapy response and survival. Chemotherapeutic efficacy was evaluated using odd ratio (OR). Survival curves were plotted and analyzed using the Kaplan-Meier method and log-rank test. Differences were considered statistically significant at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eMeta-analysis of the correlation between p27\u003c/b\u003e \u003csup\u003e \u003cb\u003eKip1\u003c/b\u003e \u003c/sup\u003e \u003cb\u003e/pSer10p27 and prognosis in ovarian cancer patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe correlation of p27\u003csup\u003eKip1\u003c/sup\u003e protein with progression-free survival (PFS) and overall survival (OS) in ovarian cancer patients was first evaluated. A total of 650 studies were identified through literature search after duplicates-removal (N\u0026thinsp;=\u0026thinsp;12) and study-exclusion after initial review of titles and abstracts (N\u0026thinsp;=\u0026thinsp;589). After data-check, 9 studies with 805 patients were included in the meta-analysis. Low p27\u003csup\u003eKip1\u003c/sup\u003e protein level was associated with poor OS (HR\u0026thinsp;=\u0026thinsp;2.14; 95% CI [1.71\u0026ndash;2.68]) and PFS (HR\u0026thinsp;=\u0026thinsp;1.61; 95% CI [0.93\u0026ndash;2.78]) in ovarian cancer. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and Supplementary Fig.\u0026nbsp;1A). In addition, \u003cem\u003eCDKN1B\u003c/em\u003e (encoding p27\u003csup\u003eKip1\u003c/sup\u003e protein) mRNA levels were negatively correlated with OS (HR\u0026thinsp;=\u0026thinsp;1.23; 95% CI [1.07\u0026ndash;1.41]) and PFS (HR\u0026thinsp;=\u0026thinsp;1.28; 95% CI [1.12\u0026ndash;1.45]) in ovarian cancer using the KM-Plotter database analysis (Supplementary Fig.\u0026nbsp;2A, B). According to the expression analysis from GEPIA database, \u003cem\u003eCDKN1B\u003c/em\u003e was significantly reduced in ovarian cancer tissues compared to paired normal tissues (Supplementary Fig.\u0026nbsp;2C). According to the genomic alterations of \u003cem\u003eCDKN1B\u003c/em\u003e including CNVs and mutations in 585 ovarian cancer samples from the cBioportal database (Supplementary Fig.\u0026nbsp;2D), \u003cem\u003eCDKN1B\u003c/em\u003e was relatively conserved and had rare frequency of alteration (5%), which did not show statistically significant associations with PFS and OS in the cohort (Supplementary Fig.\u0026nbsp;2E, F). Therefore, we assumed that the correlation between p27\u003csup\u003eKip1\u003c/sup\u003e and prognosis of ovarian cancer patients might mainly be due to the change of protein levels and status of phosphorylation. Furthermore, we performed another meta-analysis including 5 studies with 428 patients to analyze the prognostic effects of phosphorylation modifications of p27\u003csup\u003eKip1\u003c/sup\u003e that might affect their protein level changes in tumors and found that high Ser10 phosphorylation modification of p27\u003csup\u003eKip1\u003c/sup\u003e was associated with poor OS (HR\u0026thinsp;=\u0026thinsp;2.56; 95% CI [1.76\u0026ndash;3.73]) in ovarian cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eLevel of total p27\u003c/b\u003e \u003csup\u003e \u003cb\u003eKip1\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eand total pSer10p27 in ovarian cancer correlated with chemotherapy response and prognosis.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further validate the results of meta-analysis and bioinformatics analysis, we used immunohistochemistry (IHC) to assess the total positive staining of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 in the nuclear and cytoplasm in ovarian cancer tissue microarrays (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, B). Both total p27\u003csup\u003eKip1\u003c/sup\u003e (46/51) and total pSer10p27 (34/51) can be robustly detected in most specimens and total pSer10p27 positively correlated with total p27\u003csup\u003eKip1\u003c/sup\u003e as expected (Spearman r\u0026thinsp;=\u0026thinsp;0.323, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The clinical significances of total p27\u003csup\u003eKip1\u003c/sup\u003e and total pSer10p27 in ovarian cancer were subsequently analyzed. Total p27\u003csup\u003eKip1\u003c/sup\u003e expression level was significantly correlated with chemotherapy response (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and total pSer10p27 expression level was correlated with chemotherapy response (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Univariate cox regression analysis and Kaplan-Meier survival analysis showed that low total p27\u003csup\u003eKip1\u003c/sup\u003e expression was associated with poor OS (HR\u0026thinsp;=\u0026thinsp;2.323; 95% CI [1.269\u0026ndash;4.255], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) and PFS (HR\u0026thinsp;=\u0026thinsp;2.654; 95% CI [1.472\u0026ndash;4.784], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, F and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results suggest that total p27\u003csup\u003eKip1\u003c/sup\u003e expression correlates with chemotherapy response and prognosis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between total of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 to clinical pathological features in ovarian cancer by IHC-score stratification\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClinicopathological\u003c/p\u003e \u003cp\u003efeatures\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Total\u003csup\u003eb\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003epSer10p27 (Total)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh grade serous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIGO stage\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemo response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eThe median IHC score was chosen as the cut-offs for total p27\u003csup\u003eKip1\u003c/sup\u003e and total pSer10p27\u003c/p\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e total positive staining was evaluated without considering localization\u003c/p\u003e \u003cp\u003e\u003csup\u003ec\u003c/sup\u003eAge at surgery\u003c/p\u003e \u003cp\u003e\u003csup\u003ed\u003c/sup\u003eInternational Federation of Gynecology and Obstetrics\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\u003eUnivariate Cox regression survival analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (\u0026lt;\u0026thinsp;50 vs\u0026thinsp;\u0026ge;\u0026thinsp;50y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.969\u0026ndash;3.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.705\u0026ndash;2.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology (high grade serous vs others)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.239\u0026ndash;1.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.179\u0026ndash;0.830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIGO stage (I-II vs III-IV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.237\u0026ndash;0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.291\u0026ndash;1.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Total) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.472\u0026ndash;4.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.269\u0026ndash;4.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Nuc\u003csup\u003ea\u003c/sup\u003e) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.881\u0026ndash;2.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.063\u0026ndash;3.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Cyt\u003csup\u003eb\u003c/sup\u003e) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.632\u0026ndash;2.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.686\u0026ndash;2.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epSer10p27 (Total) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.407\u0026ndash;1.728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.375\u0026ndash;1.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epSer10p27 (Nuc) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.829\u0026ndash;2.739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.819\u0026ndash;2.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epSer10p27 (Nuc) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.286\u0026ndash;0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.258\u0026ndash;0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eonly nuclear staining was evaluated\u003c/p\u003e \u003cp\u003e\u003csup\u003eb\u003c/sup\u003eonly cytoplasmic staining was evaluated\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 \u003cb\u003eDifferent expression patterns of p27\u003c/b\u003e \u003csup\u003e \u003cb\u003eKip1\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eand pSer10p27 predict chemotherapy response and prognosis of ovarian cancer.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSince previous studies that reported correlation between p27\u003csup\u003eKip1\u003c/sup\u003e and patients\u0026rsquo; prognosis did not specify the subcellular location of p27\u003csup\u003eKip1\u003c/sup\u003e, we analyzed different subcellular locations of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 as well as their underlying clinical values. Four expression patterns of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 were identified: nuclear and cytoplasmic dominant (NCD), nuclear dominant (ND), cytoplasmic dominant (CD) and nuclear and cytoplasmic weak-to-none (NCWN) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, B). We also analyzed the compositional proportion of the four expression patterns of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The patients with NCD, ND, CD and NCWN expression pattern of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 accounted for 33.33%, 13.73%, 43.14%, 9.80% and 13.73%, 17.65%, 35.29%, 33.33% respectively. Around 1/3 to 1/2 of patients presented CD pattern of p27\u003csup\u003eKip1\u003c/sup\u003e or pSer10p27. 47.06% of p27\u003csup\u003eKip1\u003c/sup\u003e positive patients were accompanied with positive pSer10p27 staining. The inexistence of pSer10p27 positive/p27\u003csup\u003eKip1\u003c/sup\u003e negative pattern suggested the robustness of the staining.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe then explored the correlation of nuclear and cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 with clinical features. Nuclear p27\u003csup\u003eKip1\u003c/sup\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.020), nuclear pSer10p27 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010) and cytoplasmic pSer10p27 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly correlated with chemotherapy response (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, E and Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Logistic regression analysis revealed that patients with low expression of total p27\u003csup\u003eKip1\u003c/sup\u003e (OR\u0026thinsp;=\u0026thinsp;14.182; 95% CI [2.711\u0026ndash;74.188], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), nuclear p27\u003csup\u003eKip1\u003c/sup\u003e (OR\u0026thinsp;=\u0026thinsp;4.615; 95% CI [1.207\u0026ndash;17.656], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025) total pSer10p27 (OR\u0026thinsp;=\u0026thinsp;5.167; 95% CI [1.320\u0026ndash;20.220], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.018) and nuclear pSer10p27 (OR\u0026thinsp;=\u0026thinsp;11.050; 95% CI [1.308\u0026ndash;93.380], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.027) had worse chemotherapy response, while patients with low cytoplasmic pSer10p27 expression (OR\u0026thinsp;=\u0026thinsp;0.047; 95% CI [0.006\u0026ndash;0.398], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) had better chemotherapy response (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The ROC curves showed that the area under the curve (AUC) for total p27\u003csup\u003eKip1\u003c/sup\u003e and cytoplasmic pSer10p27 were 0.780 and 0.775 respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Univariate cox regression analysis and Kaplan-Meier survival analysis showed that low cytoplasmic pSer10p27 expression was associated with better OS (HR\u0026thinsp;=\u0026thinsp;0.473; 95% CI [0.258\u0026ndash;0.865], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015) and PFS (HR\u0026thinsp;=\u0026thinsp;0.509; 95% CI [0.286\u0026ndash;0.904], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG, H and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Multivariate cox regression analyses showed that low total p27\u003csup\u003eKip1\u003c/sup\u003e remained independent risk factors for OS (HR\u0026thinsp;=\u0026thinsp;2.097; 95% CI [1.121\u0026ndash;3.922], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021) and PFS (HR\u0026thinsp;=\u0026thinsp;2.483; 95% CI [1.364\u0026ndash;4.518], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), while high cytoplasmic pSer10p27 had independent protective effects in terms of OS (HR\u0026thinsp;=\u0026thinsp;0.472; 95% CI [0.248\u0026ndash;0.898], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022) and PFS (HR\u0026thinsp;=\u0026thinsp;0.488; 95% CI [0.261\u0026ndash;0.910], \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These results suggested that total p27\u003csup\u003eKip1\u003c/sup\u003e and cytoplasmic pSer10p27 had promising predictive values for chemotherapy response and prognosis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 to clinical pathological features in the nuclear and cytoplasm of ovarian cancer by IHC-score stratification\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClinicopathological\u003c/p\u003e \u003cp\u003efeatures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Nuc)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Cyt)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003epSer10p27 (Nuc)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003epSer10p27 (Cyt)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.718\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh grade serous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIGO stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u0026ndash;II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u0026ndash;IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChemo response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of different parameters and chemotherapy resistance in ovarian cancer\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eChemotherapy resistance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (\u0026lt;\u0026thinsp;50 vs\u0026thinsp;\u0026ge;\u0026thinsp;50y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.786\u0026ndash;9.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.113\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology (high grade serous vs others)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.151\u0026ndash;3.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIGO stage (I-II vs III-IV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.017\u0026ndash;1.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Total) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.711\u0026ndash;74.188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Nuc) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.207\u0026ndash;17.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Cyt) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.081\u0026ndash;1.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epSer10p27 (Total) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.320\u0026ndash;20.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epSer10p27 (Nuc) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.308\u0026ndash;93.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epSer10p27 (Cyt) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006\u0026ndash;0.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate Hazard Cox regression survival analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePFS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eOS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (\u0026lt;\u0026thinsp;50 vs\u0026thinsp;\u0026ge;\u0026thinsp;50y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.699\u0026ndash;2.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.455\u0026ndash;1.845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistology (high grade serous vs others)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.151\u0026ndash;0.760\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.124\u0026ndash;0.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFIGO stage (I-II vs III-IV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.306\u0026ndash;1.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.372\u0026ndash;1.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e (Total) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.364\u0026ndash;4.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.121\u0026ndash;3.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epSer10p27 (Cyt) expression (low vs high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.261\u0026ndash;0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.248\u0026ndash;0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.022\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 \u003cb\u003eLow expression of p27\u003c/b\u003e \u003csup\u003e \u003cb\u003eKip1\u003c/b\u003e \u003c/sup\u003e \u003cb\u003eand pSer10p27 are associated with cisplatin resistance in platinum-resistant ovarian cancer cell lines\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further investigate the relationship between p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 and platinum resistance in ovarian cancer, we constructed cisplatin-resistant ovarian cancer cell lines SKOV3-cDDP and A2780-cDDP. The SKOV3-cDDP (IC50\u0026thinsp;=\u0026thinsp;44.40 \u0026micro;M) and A2780-cDDP (IC50\u0026thinsp;=\u0026thinsp;16.93 \u0026micro;M) cell lines were more resistant to cisplatin compared to the parental SKOV3 (IC50\u0026thinsp;=\u0026thinsp;12.22 \u0026micro;M) and A2780 (IC50\u0026thinsp;=\u0026thinsp;3.04 \u0026micro;M) validated by MTT (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B). The protein levels of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 were significantly reduced in SKOV3-cDDP and A2780-cDDP (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Similarly, \u003cem\u003eCDKN1B\u003c/em\u003e mRNA levels were also reduced in the cisplatin-resistant cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). These results suggested that increased p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 levels were associated with increased cisplatin sensitivity in ovarian cancer. KEGG enrichment analysis of differentially expressed genes between the \u003cem\u003eCDKN1B\u003c/em\u003e\u003csup\u003ehigh\u003c/sup\u003e group and the \u003cem\u003eCDKN1B\u003c/em\u003e\u003csup\u003elow\u003c/sup\u003e group from the TCGA-OV database was mainly associated with cell cycle, cellular senescence and PI3K-Akt signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). Considering some studies suggest that p27\u003csup\u003eKip1\u003c/sup\u003e is phosphorylated at Ser10 by Akt (Fujita et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Liang et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), we further investigated whether the level of pSer10p27 was subjective to Akt activation. The level of pS473Akt1 in cisplatin resistant cell lines was generally higher than that in the parental cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF, G). Inhibition of pS473Akt1 by MK2206 was accompanied with evident increase of p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 in SKOV3-cDDP but not in A2780-cDDP (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF, G). These results suggested that inhibition of pS473Akt1 by MK2206 could to some extent restore p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 in certain cell lines.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we first investigated the overall prognostic values of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 in ovarian cancer by meta-analysis and bioinformatic data analysis, then evaluated the expression pattern of p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 and subsequently assessed the correlation of p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 with different subcellular localizations to OS, PFS and chemotherapy response of ovarian cancer patients through IHC staining using tissue microarrays. Finally, the association of p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 with cisplatin-resistance was further validated in two cisplatin-resistant ovarian cancer cell lines. These results suggest that not only the total levels of p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 but also nuclear p27\u003csup\u003eKip1\u003c/sup\u003e and cytoplasmic pSer10p27 may influence ovarian cancer progression and chemotherapy response.\u003c/p\u003e \u003cp\u003ep27\u003csup\u003eKip1\u003c/sup\u003e was originally identified as a 27 kD non-tyrosine protein, which bound to various cyclin-CDK complexes in non-proliferating cells and leads to CDK inhibition and G1 arrest (Polyak et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Toyoshima and Hunter \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1994\u003c/span\u003e). The canonical role of p27\u003csup\u003eKip1\u003c/sup\u003e as a major cell cycle regulator had become even more conclusive when evidence mounted and the protein-coding gene of p27\u003csup\u003eKip1\u003c/sup\u003e, \u003cem\u003eCDKN1B\u003c/em\u003e, was therefore regarded as a representative putative tumor-suppressor. Conformably, the tissue sample based p27\u003csup\u003eKip1\u003c/sup\u003e level in various types of cancer are concordantly correlated with patients\u0026rsquo; prognosis (Porter et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Chiarle et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Earlier findings suggested that in addition to anti-tumor effect, p27\u003csup\u003eKip1\u003c/sup\u003e was also involved in regulation of embryonic stem cell differentiation (Li et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), cytokinesis (Serres et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and actomyosin contractions (Godin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). More recently, novel functions of p27\u003csup\u003eKip1\u003c/sup\u003e were characterized including regulation of DNA damage response in P53 deficient cells (Cannell et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), transcriptional regulation and control of autophagic vesicle trafficking (Yoon et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSince driver gene and tumor-suppressor mutation is one of the major theories of tumorigenesis, the mutational profile of \u003cem\u003eCDKN1B\u003c/em\u003e is naturally studied. Multiple sets of data based on tissue specimens and cell lines all indicated that \u003cem\u003eCDKN1B\u003c/em\u003e was rarely mutated in almost all tumor types (Kawamata et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Shin et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), which suggested the importance of post-transcriptional modification on \u003cem\u003eCDKN1B\u003c/em\u003e. The correlation between decreased p27\u003csup\u003eKip1\u003c/sup\u003e protein level and poor prognosis of ovarian cancer patients was validated by our results together with several previous studies (Shigemasa et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Schmider-Ross et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Lu et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Felix et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In previous studies, cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e was observed but only nuclear p27\u003csup\u003eKip1\u003c/sup\u003e was evaluated in ovarian cancer cohorts possibly due to the reason that only nuclear p27\u003csup\u003eKip1\u003c/sup\u003e had access to CDKs. However, several recent studies suggested that in addition to nuclear p27\u003csup\u003eKip1\u003c/sup\u003e, cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e also had prognostic effect in certain types of cancer such as nasopharyngeal carcinoma and osteosarcoma (Chen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Teng et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). According to our results, in accordance with previous studies low nuclear p27\u003csup\u003eKip1\u003c/sup\u003e was associated with poor prognosis and higher risk of chemotherapy resistance. Although without statistical significance, patients with low cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e were apt to be chemotherapy-sensitive suggesting that a high nuclear and low cytoplasmic pattern might be most conducive to p27\u003csup\u003eKip1\u003c/sup\u003e exerting its anti-cancer effect.\u003c/p\u003e \u003cp\u003eAccumulating evidences reveal that cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e has distinct biological functions from nuclear ones (Serres et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Calvayrac et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The translocation of p27\u003csup\u003eKip1\u003c/sup\u003e from nuclear to cytoplasm could either resulted in degradation (Morishita et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), cytoplasmic sequestration (Kim et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), or even tumor promotion (Shin et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The fate and function of cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e was tightly linked to p27\u003csup\u003eKip1\u003c/sup\u003e phosphorylation. Up to date, around 10 sites of p27\u003csup\u003eKip1\u003c/sup\u003e phosphorylation had been identified. Ser10 phosphorylation of p27\u003csup\u003eKip1\u003c/sup\u003e represented nuclear export signal while Thr157 and Thr198 phosphorylation of p27\u003csup\u003eKip1\u003c/sup\u003e blocked its nuclear entry and held for p27\u003csup\u003eKip1\u003c/sup\u003e cytoplasmic retention (Lian et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The dynamic process of nuclear-cytoplasmic p27\u003csup\u003eKip1\u003c/sup\u003e translocation driven by different phosphorylation statuses might present as various p27\u003csup\u003eKip1\u003c/sup\u003e subcellular expression pattern when evaluated cross-sectionally. Since pSer10p27 triggered p27\u003csup\u003eKip1\u003c/sup\u003e export and blocked it from CDK, we further analyzed the relationship between different subcellular locations of pSer10p27 and clinical characteristics (e.g., age, histological type, FIGO stage, tumor type, response to chemotherapy and prognosis) in ovarian cancer patients. We found that patients with high cytoplasmic pSer10p27 state had higher risk of chemotherapy resistance and poor OS/PFS, which might suggest that cytoplasmic export of p27\u003csup\u003eKip1\u003c/sup\u003e diminished the anti-cancer effect of p27\u003csup\u003eKip1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eQuite a few studies reported the involvement of p27\u003csup\u003eKip1\u003c/sup\u003e in cisplatin resistance recently (Huang et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Su et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Cisplatin exerts anti-cancer effect by forming cisplatin-DNA adducts. Cells damaged by cisplatin usually go through G1 arrest and then apoptosis. Recent study showed that cells relied on p27\u003csup\u003eKip1\u003c/sup\u003e for G1 arrest when P53 was deficient (La et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). As P53 mutation occurred in nearly 90% of high-grade serous ovarian cancer patients, the level of p27\u003csup\u003eKip1\u003c/sup\u003e could be of noteworthy clinical significance. Here we found that p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 were significantly decreased in cisplatin-resistant cell lines SKOV3-cDDP and A2780-cDDP. After inhibition of pS473Akt1 by MK2206, the levels of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 were restored in SKOV3-cDDP but not in A2780-cDDP. This was possibly due to natural deficiency of P53 in SKOV3 cells.\u003c/p\u003e \u003cp\u003eIn summary, our study provides evidence that different subcellular localizations of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 correlate with chemotherapy response and prognosis and can be used as potential biomarkers to assess chemotherapy response and prognosis in ovarian cancer.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e We thanked Dr. Yujia Ma and Dr. Zheng Wei for providing valuable technical support. This work was funded by the National Natural Science Foundation of China (82002771, 82002766).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e Mengna Zhu, Si Sun, Jing Cai, Zehua Wang and Minggang Peng contributed to the study conception and design. Material preparation, data collection and analysis were performed by Mengna Zhu, Si Sun and Lin Huang. Mengna Zhu and Si Sun wrote the manuscript and all authors analyzed and interpreted the data, read, revised and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis work was funded by the National Natural Science Foundation of China (grant number 82002771) and the National Natural Science Foundation of China (grant number 82002766).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003ePublic data sets of OV analyzed during the current study can be retrieved from TCGA database (https://portal.gdc.cancer.gov/), Kaplan-Meier Plotter (http://kmplot.com/analysis/index.php?p=service\u0026amp;cancer=ovar), GEPIA database (http://gepia.cancer-pku.cn/) and cBioPortal database (https://www.cbioportal.org/). Other data that support the findings of this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003eThis study was approved by Independence Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (20210567).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eAbbastabar M, Kheyrollah M, Azizian K, et al (2018) Multiple functions of p27 in cell cycle, apoptosis, epigenetic modification and transcriptional regulation for the control of cell growth: A double-edged sword protein. 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Proc Natl Acad Sci U S A 116:7005\u0026ndash;7014. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1817415116\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ovarian cancer, Prognosis, Chemotherapy response, p27Kip1, Phosphorylation, Overall survival","lastPublishedDoi":"10.21203/rs.3.rs-3195821/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3195821/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose \u003c/strong\u003eThe biological function of p27\u003csup\u003eKip1\u003c/sup\u003e largely depends on its subcellular localization and phosphorylation status. Different subcellular localization and phosphorylation status of p27\u003csup\u003eKip1\u003c/sup\u003e may represent distinct clinical values, which are not entirely clear in ovarian cancer. This study aimed to elucidate different subcellular localizations of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 in predicting prognosis and chemotherapy response in ovarian cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e Meta-analyses were executed to evaluate the association of p27\u003csup\u003eKip1\u003c/sup\u003e and phosphorylated p27\u003csup\u003eKip1 \u003c/sup\u003ewith the prognosis of ovarian cancer patients. The expression levels and patterns of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 were evaluated by immunohistochemistry (IHC). The correlations between different p27\u003csup\u003eKip1\u003c/sup\u003e states and clinicopathological features as well as prognosis were analyzed. p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 expression level in cisplatin-sensitive and cisplatin-resistant ovarian cancer cell lines were detected using WB. KEGG analysis and WB were performed to evaluate the involved pathways of p27\u003csup\u003eKip1\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e Meta-analyses showed that p27\u003csup\u003eKip1\u003c/sup\u003e was associated with significantly better overall survival (OS) in ovarian cancer (HR = 2.14; 95% CI [1.71 - 2.68]) and pSer10p27 was associated with significantly poor OS in mixed solid tumors (HR = 2.56; 95% CI [1.76 - 3.73]) In our cohort of ovarian cancer patients, low total p27\u003csup\u003eKip1\u003c/sup\u003e remained independent risk factors for OS (HR = 2.097; 95% CI [1.121 - 3.922], \u003cem\u003eP\u003c/em\u003e = 0.021) and PFS (HR = 2.483; 95% CI [1.364 - 4.518], \u003cem\u003eP\u003c/em\u003e = 0.003), while low cytoplasmic pSer10p27 had independent protective effects in terms of OS (HR = 0.472; 95% CI [0.248 - 0.898], \u003cem\u003eP\u003c/em\u003e = 0.022) and PFS (HR = 0.488; 95% CI [0.261 - 0.910], \u003cem\u003eP\u003c/em\u003e = 0.024). Patients with low total p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 and low nuclear p27\u003csup\u003eKip1\u003c/sup\u003e had worse chemotherapy response while patients with low cytoplasmic pSer10p27 expression had better chemotherapy response. The protein levels of p27\u003csup\u003eKip1\u003c/sup\u003e and pSer10p27 were significantly reduced in cisplatin resistant cell lines SKOV3-cDDP and A2780-cDDP and the level of p27\u003csup\u003eKip1\u003c/sup\u003e/pSer10p27 was subjective to Akt activation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e The present study demonstrates that p27\u003csup\u003eKip1\u003c/sup\u003e and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer.\u003c/p\u003e","manuscriptTitle":"p27 Kip1 and cytoplasmic pSer10p27 are promising biomarkers for predicting prognosis and chemotherapy response in ovarian cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-31 17:00:26","doi":"10.21203/rs.3.rs-3195821/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0859538e-1ff7-457d-9c1d-b5e3695efd26","owner":[],"postedDate":"July 31st, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-09-12T01:59:08+00:00","versionOfRecord":[],"versionCreatedAt":"2023-07-31 17:00:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3195821","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3195821","identity":"rs-3195821","version":["v1"]},"buildId":"V5aR-dtovt5O2cv8Agveh","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}