Cargando…
Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma
Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. A better understanding of mesothelioma genomics and transcriptomics could advance therapies. Here, we present a mesothelioma cohort of 122 patients along with their germline and tumor whole-exome and tu...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975319/ https://www.ncbi.nlm.nih.gov/pubmed/36773602 http://dx.doi.org/10.1016/j.xcrm.2023.100938 |
_version_ | 1784898850414133248 |
---|---|
author | Nair, Nishanth Ulhas Jiang, Qun Wei, Jun Stephen Misra, Vikram Alexander Morrow, Betsy Kesserwan, Chimene Hermida, Leandro C. Lee, Joo Sang Mian, Idrees Zhang, Jingli Lebensohn, Alexandra Miettinen, Markku Sengupta, Manjistha Khan, Javed Ruppin, Eytan Hassan, Raffit |
author_facet | Nair, Nishanth Ulhas Jiang, Qun Wei, Jun Stephen Misra, Vikram Alexander Morrow, Betsy Kesserwan, Chimene Hermida, Leandro C. Lee, Joo Sang Mian, Idrees Zhang, Jingli Lebensohn, Alexandra Miettinen, Markku Sengupta, Manjistha Khan, Javed Ruppin, Eytan Hassan, Raffit |
author_sort | Nair, Nishanth Ulhas |
collection | PubMed |
description | Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. A better understanding of mesothelioma genomics and transcriptomics could advance therapies. Here, we present a mesothelioma cohort of 122 patients along with their germline and tumor whole-exome and tumor RNA sequencing data as well as phenotypic and drug response information. We identify a 48-gene prognostic signature that is highly predictive of mesothelioma patient survival, including CCNB1, the expression of which is highly predictive of patient survival on its own. In addition, we analyze the transcriptomics data to study the tumor immune microenvironment and identify synthetic-lethality-based signatures predictive of response to therapy. This germline and somatic whole-exome sequencing as well as transcriptomics data from the same patient are a valuable resource to address important biological questions, including prognostic biomarkers and determinants of treatment response in mesothelioma. |
format | Online Article Text |
id | pubmed-9975319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99753192023-03-02 Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma Nair, Nishanth Ulhas Jiang, Qun Wei, Jun Stephen Misra, Vikram Alexander Morrow, Betsy Kesserwan, Chimene Hermida, Leandro C. Lee, Joo Sang Mian, Idrees Zhang, Jingli Lebensohn, Alexandra Miettinen, Markku Sengupta, Manjistha Khan, Javed Ruppin, Eytan Hassan, Raffit Cell Rep Med Article Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. A better understanding of mesothelioma genomics and transcriptomics could advance therapies. Here, we present a mesothelioma cohort of 122 patients along with their germline and tumor whole-exome and tumor RNA sequencing data as well as phenotypic and drug response information. We identify a 48-gene prognostic signature that is highly predictive of mesothelioma patient survival, including CCNB1, the expression of which is highly predictive of patient survival on its own. In addition, we analyze the transcriptomics data to study the tumor immune microenvironment and identify synthetic-lethality-based signatures predictive of response to therapy. This germline and somatic whole-exome sequencing as well as transcriptomics data from the same patient are a valuable resource to address important biological questions, including prognostic biomarkers and determinants of treatment response in mesothelioma. Elsevier 2023-02-10 /pmc/articles/PMC9975319/ /pubmed/36773602 http://dx.doi.org/10.1016/j.xcrm.2023.100938 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Nair, Nishanth Ulhas Jiang, Qun Wei, Jun Stephen Misra, Vikram Alexander Morrow, Betsy Kesserwan, Chimene Hermida, Leandro C. Lee, Joo Sang Mian, Idrees Zhang, Jingli Lebensohn, Alexandra Miettinen, Markku Sengupta, Manjistha Khan, Javed Ruppin, Eytan Hassan, Raffit Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma |
title | Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma |
title_full | Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma |
title_fullStr | Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma |
title_full_unstemmed | Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma |
title_short | Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma |
title_sort | genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9975319/ https://www.ncbi.nlm.nih.gov/pubmed/36773602 http://dx.doi.org/10.1016/j.xcrm.2023.100938 |
work_keys_str_mv | AT nairnishanthulhas genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT jiangqun genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT weijunstephen genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT misravikramalexander genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT morrowbetsy genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT kesserwanchimene genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT hermidaleandroc genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT leejoosang genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT mianidrees genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT zhangjingli genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT lebensohnalexandra genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT miettinenmarkku genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT senguptamanjistha genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT khanjaved genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT ruppineytan genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma AT hassanraffit genomicandtranscriptomicanalysesidentifyaprognosticgenesignatureandpredictresponsetotherapyinpleuralandperitonealmesothelioma |