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Identification of candidate circulating cisplatin-resistant biomarkers from epithelial ovarian carcinoma cell secretomes.

ABSTRACT: BACKGROUND:The majority of patients diagnosed with advanced epithelial ovarian carcinoma (EOC) relapse with resistant disease, and there are no biomarkers that possess clinical utility to identify or monitor these patients. This study aimed to identify secreted proteins ('secretome') collected from human EOC cell lines that differ in their inherent platinum sensitivity. METHODS:Secreted proteins collected from conditioned medium from ovarian cancer cell lines that vary in their sensitivity to cisplatin were digested with trypsin and analysed by liquid chromatography-tandem mass spectrometry for peptide identification. RESULTS:Of the 1688 proteins identified, 16 possessed significant differential abundances (P<0.05) between the platinum-resistant and -sensitive cell lines. A number of these were verified by immunoblot, including COL11A1, which was also found to be associated with worse progression-free survival (PFS; N=723) and overall survival (OS; N=1183) as assessed from publicly available transcript expression data from ovarian cancer tumour specimens. CONCLUSION:Secretome proteomics of EOC cells resulted in the identification of a novel candidate biomarker, COL11A1. The expression level of COL11A1 correlates to worse PFS and OS, and is predicted to reside in peripheral circulation making this an attractive candidate for validation in sera as a biomarker of cisplatin resistance and poor outcome.

SUBMITTER: Teng PN

PROVIDER: S-EPMC3887292 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Identification of candidate circulating cisplatin-resistant biomarkers from epithelial ovarian carcinoma cell secretomes.

Teng P-N PN Wang G G Hood B L BL Conrads K A KA Hamilton C A CA Maxwell G L GL Darcy K M KM Conrads T P TP

British journal of cancer 20131031 1

<h4>Background</h4>The majority of patients diagnosed with advanced epithelial ovarian carcinoma (EOC) relapse with resistant disease, and there are no biomarkers that possess clinical utility to identify or monitor these patients. This study aimed to identify secreted proteins ('secretome') collected from human EOC cell lines that differ in their inherent platinum sensitivity.<h4>Methods</h4>Secreted proteins collected from conditioned medium from ovarian cancer cell lines that vary in their se ...[more]

PMID: 24178762

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Project description:PurposeTo investigate the role of prognostic genes related to cisplatin resistance in ovarian cancer during disease progression.MethodThe gene expression profile of the NCI-60 cell line was acquired through comprehensive analysis of the GEO database accession GSE116439. We performed a thorough analysis of gene expression differences in samples from seven individuals exposed to cisplatin concentrations of 0 nM compared to seven samples exposed to 15000 nM over a 24-h period. Key genes were initially identified through LASSO regression, followed by their enrichment through differential gene function analysis (GO) and pathway enrichment analysis (KEGG). Subsequently, a prognostic risk model was established for these key genes. The prognostic model's performance was assessed through K-M survival curves and ROC curves. To examine the variance in immune cell infiltration between the high and low-risk groups, CIBERSORTx analysis was employed. Finally, validation of prognostic gene expression in cisplatin-resistant ovarian cancer was carried out using clinical samples, employing RT-qPCR and Western Blot techniques.ResultsA total of 132 differential genes were found between cisplatin resistance and control group, and 8 key prognostic genes were selected by analysis, namely VPS13B, PLGRKT, CDKAL1, TBC1D22A, TAP1, PPP3CA, CUX1 and PPP1R15A. The efficacy of the risk assessment model derived from prognostic biomarkers, as indicated by favorable performance on both Kaplan-Meier survival curves and ROC curves. Significant variations in the abundance of Macrophages M1, T cells CD4 memory resting, T cells follicular helper, and T cells gamma delta were observed between the high and low-risk groups. To further validate our findings, RT-qPCR and Western Blot analyses were employed, confirming differential expression of the identified eight key genes between the two groups.ConclusionVPS13B, TBC1D22A, PPP3CA, CUX1 and PPP1R15A were identified as poor prognostic genes of cisplatin resistance in ovarian cancer, while PLGRKT, CDKAL1 and TAP1 were identified as good prognostic genes. This offers a novel perspective for future advancements in ovarian cancer treatment, suggesting potential avenues for the development of new therapeutic targets.

Dataset Information

Identification of candidate circulating cisplatin-resistant biomarkers from epithelial ovarian carcinoma cell secretomes.

Publications

Identification of candidate circulating cisplatin-resistant biomarkers from epithelial ovarian carcinoma cell secretomes.

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