Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma.
Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma.
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DOI：
10.1016/j.xcrm.2023.100938
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发表时间：
2023-02-21
影响因子：
14.3
通讯作者：
Hassan, Raffit
中科院分区：
文献类型：
--
作者：
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
恶性间皮瘤是一种侵袭性癌症，治疗选择有限，预后差。更好地了解间皮瘤基因组学和转录组学可以推进治疗。在这里，我们提出了一个间皮瘤队列的122例患者沿着与他们的生殖细胞和肿瘤全外显子组和肿瘤RNA测序数据，以及表型和药物反应的信息。我们确定了一个48基因的预后标志，是高度预测间皮瘤患者的生存，包括CCNB1，其表达是高度预测患者的生存本身。此外，我们分析转录组学数据来研究肿瘤免疫微环境，并识别可预测治疗反应的基于合成致死率的特征。来自同一患者的这种种系和体细胞全外显子组测序以及转录组学数据是解决重要生物学问题的宝贵资源，包括间皮瘤治疗反应的预后生物标志物和决定因素。一个122例间皮瘤患者队列，具有基因组学、转录组学和表型数据，48个基因签名高度预测患者生存率。提出了一个122例胸膜和腹膜间皮瘤患者队列与基因组学，转录组学和表型数据。他们确定了一个基于48个基因转录组学的签名，高度预测间皮瘤患者的生存率，包括CCNB1基因。进行转录组学分析以研究肿瘤免疫微环境并预测患者的药物反应。
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. A 122-patient mesothelioma cohort with genomics, transcriptomics, and phenotypic data 48-gene signature highly predictive of patient survival Evaluated tumor immune microenvironment using transcriptomics Transcriptomic analysis to predict response to therapy Nair et al. present a 122-patient pleural and peritoneal mesothelioma cohort with genomics, transcriptomics, and phenotypic data. They identify a 48-gene transcriptomics-based signature that is highly predictive of mesothelioma patient survival, including the CCNB1 gene. Transcriptomics analysis is done to study the tumor immune microenvironment and predict drug response in patients.
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影响因子：
--
作者：
Gordon CA;Gong X;Ganesh D;Brooks JD
通讯作者：
Brooks JD
影响因子：
28.2
作者：
Carbone M;Harbour JW;Brugarolas J;Bononi A;Pagano I;Dey A;Krausz T;Pass HI;Yang H;Gaudino G
通讯作者：
Gaudino G
影响因子：
28.2
作者：
Hmeljak J;Sanchez-Vega F;Hoadley KA;Shih J;Stewart C;Heiman D;Tarpey P;Danilova L;Drill E;Gibb EA;Bowlby R;Kanchi R;Osmanbeyoglu HU;Sekido Y;Takeshita J;Newton Y;Graim K;Gupta M;Gay CM;Diao L;Gibbs DL;Thorsson V;Iype L;Kantheti H;Severson DT;Ravegnini G;Desmeules P;Jungbluth AA;Travis WD;Dacic S;Chirieac LR;Galateau-Sallé F;Fujimoto J;Husain AN;Silveira HC;Rusch VW;Rintoul RC;Pass H;Kindler H;Zauderer MG;Kwiatkowski DJ;Bueno R;Tsao AS;Creaney J;Lichtenberg T;Leraas K;Bowen J;TCGA Research Network;Felau I;Zenklusen JC;Akbani R;Cherniack AD;Byers LA;Noble MS;Fletcher JA;Robertson AG;Shen R;Aburatani H;Robinson BW;Campbell P;Ladanyi M
通讯作者：
Ladanyi M
影响因子：
46.9
作者：
Doench JG;Fusi N;Sullender M;Hegde M;Vaimberg EW;Donovan KF;Smith I;Tothova Z;Wilen C;Orchard R;Virgin HW;Listgarten J;Root DE
通讯作者：
Root DE
影响因子：
14.9
作者：
Han H;Cho JW;Lee S;Yun A;Kim H;Bae D;Yang S;Kim CY;Lee M;Kim E;Lee S;Kang B;Jeong D;Kim Y;Jeon HN;Jung H;Nam S;Chung M;Kim JH;Lee I
通讯作者：
Lee I