Gene expression analysis reveals a 5-gene signature for progression-free survival in prostate cancer
dc.contributor.author | Mou, Z | |
dc.contributor.author | Spencer, J | |
dc.contributor.author | Knight, B | |
dc.contributor.author | John, J | |
dc.contributor.author | McCullagh, P | |
dc.contributor.author | McGrath, JS | |
dc.contributor.author | Harries, LW | |
dc.date.accessioned | 2022-09-01T10:59:42Z | |
dc.date.issued | 2022-08-12 | |
dc.date.updated | 2022-09-01T09:53:27Z | |
dc.description.abstract | Prostate cancer (PCa) is the second most common male cancer worldwide, but effective biomarkers for the presence or progression risk of disease are currently elusive. In a series of nine matched histologically confirmed PCa and benign samples, we carried out an integrated transcriptome-wide gene expression analysis, including differential gene expression analysis and weighted gene co-expression network analysis (WGCNA), which identified a set of potential gene markers highly associated with tumour status (malignant vs. benign). We then used these genes to establish a minimal progression-free survival (PFS)-associated gene signature (GS) (PCBP1, PABPN1, PTPRF, DANCR, and MYC) using least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analyses from The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) dataset. Our signature was able to predict PFS over 1, 3, and 5 years in TCGA-PRAD dataset, with area under the curve (AUC) of 0.64–0.78, and our signature remained as a prognostic factor independent of age, Gleason score, and pathological T and N stages. A nomogram combining the signature and Gleason score demonstrated improved predictive capability for PFS (AUC: 0.71–0.85) and was superior to the Cambridge Prognostic Group (CPG) model alone and some conventionally used clinicopathological factors in predicting PFS. In conclusion, we have identified and validated a novel five-gene signature and established a nomogram that effectively predicted PFS in patients with PCa. Findings may improve current prognosis tools for PFS and contribute to clinical decision-making in PCa treatment. | en_GB |
dc.description.sponsorship | National Institute for Health Research (NIHR) | en_GB |
dc.format.extent | 914078- | |
dc.identifier.citation | Vol. 12, article 914078 | en_GB |
dc.identifier.doi | https://doi.org/10.3389/fonc.2022.914078 | |
dc.identifier.uri | http://hdl.handle.net/10871/130637 | |
dc.identifier | ORCID: 0000-0001-7791-8061 (Harries, Lorna W) | |
dc.identifier | ScopusID: 13805289700 (Harries, Lorna W) | |
dc.identifier | ResearcherID: D-2241-2014 | E-2369-2011 (Harries, Lorna W) | |
dc.language.iso | en | en_GB |
dc.publisher | Frontiers Media | en_GB |
dc.rights | © 2022 Mou, Spencer, Knight, John, McCullagh, McGrath and Harries. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | en_GB |
dc.subject | gene signature | en_GB |
dc.subject | prostate cancer | en_GB |
dc.subject | transcriptomics | en_GB |
dc.subject | prognosis | en_GB |
dc.subject | prediction model | en_GB |
dc.title | Gene expression analysis reveals a 5-gene signature for progression-free survival in prostate cancer | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2022-09-01T10:59:42Z | |
dc.identifier.issn | 2234-943X | |
dc.description | This is the final version. Available on open access from Frontiers Media via the DOI in this record | en_GB |
dc.identifier.eissn | 2234-943X | |
dc.identifier.journal | Frontiers in Oncology | en_GB |
dc.relation.ispartof | Frontiers in Oncology, 12 | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2022-07-14 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2022-08-12 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2022-09-01T10:58:09Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2022-09-01T10:59:50Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2022-08-12 |
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Except where otherwise noted, this item's licence is described as © 2022 Mou, Spencer, Knight, John, McCullagh, McGrath and Harries. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.