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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...

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Autores principales: 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
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
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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.
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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
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