Comprehensive analysis of alternative splicing across multiple transcriptomic cohorts reveals prognostic signatures in prostate cancer
dc.contributor.author | Mou, Z | |
dc.contributor.author | Spencer, J | |
dc.contributor.author | McGrath, JS | |
dc.contributor.author | Harries, LW | |
dc.date.accessioned | 2023-11-06T14:38:35Z | |
dc.date.issued | 2023-11-03 | |
dc.date.updated | 2023-11-06T11:57:50Z | |
dc.description.abstract | Background Alternative splicing (AS) plays a crucial role in transcriptomic diversity and is a hallmark of cancer that profoundly influences the development and progression of prostate cancer (PCa), a prevalent and potentially life-limiting cancer among men. Accumulating evidence has highlighted the association between AS dysregulation and the onset and progression of PCa. However, a comprehensive and integrative analysis of AS profiles at the event level, utilising data from multiple high-throughput cohorts and evaluating the prognosis of PCa progression, remains lacking and calls for thorough exploration. Results We identified a differentially expressed retained intron event in ZWINT across three distinct cohorts, encompassing an original array-based dataset profiled by us previously and two RNA sequencing (RNA-seq) datasets. Subsequent in-depth analyses of these RNA-seq datasets revealed 141 altered events, of which 21 demonstrated a significant association with patients’ biochemical recurrence-free survival (BCRFS). We formulated an AS event-based prognostic signature, capturing six pivotal events in genes CYP4F12, NFATC4, PIGO, CYP3A5, ALS2CL, and FXYD3. This signature effectively differentiated high-risk patients diagnosed with PCa, who experienced shorter BCRFS, from their low-risk counterparts. Notably, the signature's predictive power surpassed traditional clinicopathological markers in forecasting 5-year BCRFS, demonstrating robust performance in both internal and external validation sets. Lastly, we constructed a novel nomogram that integrates patients’ Gleason scores with pathological tumour stages, demonstrating improved prognostication of BCRFS. Conclusions Prediction of clinical progression remains elusive in PCa. This research uncovers novel splicing events associated with BCRFS, augmenting existing prognostic tools, thus potentially refining clinical decision-making. | en_GB |
dc.identifier.citation | Vol. 17(1), article 97 | en_GB |
dc.identifier.doi | https://doi.org/10.1186/s40246-023-00545-w | |
dc.identifier.uri | http://hdl.handle.net/10871/134441 | |
dc.language.iso | en | en_GB |
dc.publisher | BMC | en_GB |
dc.relation.url | https://bioinformatics.mdanderson.org/TCGASpliceSeq/index.jsp | en_GB |
dc.relation.url | https://www.ebi.ac.uk/ena/browser/home | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/geo/ | en_GB |
dc.rights | © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the dats | en_GB |
dc.title | Comprehensive analysis of alternative splicing across multiple transcriptomic cohorts reveals prognostic signatures in prostate cancer | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2023-11-06T14:38:35Z | |
exeter.article-number | 97 | |
dc.description | This is the final version. Available on open access from BMC via the DOI in this record | en_GB |
dc.description | Availability of data and materials: The gene expression profiling procedure using the Affymetrix Clariom D Human Array for this study is detailed in our previous paper [22]. The corresponding raw CEL data have been submitted to the Gene Expression Omnibus (GEO) database, under accession number GSE246282. Percent-spliced-in (PSI) values of alternative splicing events for TCGA-PRAD cohort were available at TCGA SpliceSeq (https://bioinformatics.mdanderson.org/TCGASpliceSeq/index.jsp). Raw RNA-seq data for PRJEB2449 cohort were available at ENA (https://www.ebi.ac.uk/ena/browser/home). Raw CEL files of microarray data for GSE107299 cohort were available at GEO (https://www.ncbi.nlm.nih.gov/geo/). | en_GB |
dc.identifier.eissn | 1479-7364 | |
dc.identifier.journal | Human Genomics | en_GB |
dc.relation.ispartof | Human Genomics, 17(1) | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2023-10-20 | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-11-03 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2023-11-06T14:36:15Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2023-11-06T14:38:40Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2023-11-03 |
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licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecom mons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the dats