Mesothelioma survival prediction based on a six-gene transcriptomic signature

Background: Mesothelioma is an aggressive, fatal cancer that is inextricably linked to asbestos exposure. Recent trials using a combination of the immune checkpoint inhibitors ipilimumab and nivolumab has significantly improved treatment outcomes, however durable treatment responses remain restricted to a subset of patients (15-20%), highlighting the need to identify strategies that better predict treatment response. Method: We performed RNAseq on a large tumor biobank (n=167) from genetically diverse mouse model, CC-MexTAg model to compare gene expression profiles of tumors from mice with different overall survival to develop a prognostic gene signature. Results: while the variation in gene expression data of tumors did not associate with 3-fold variation in overall survival of CC-MexTAg mice, we identified two distinct tumor clusters characterized with immune and non-immune phenotypes, in which immune cluster tumours showed the better potential of response to cancer therapies. We used 20 hub genes associated with this tumor phenotype to develop a 6-gene signature that could predict survival in four independent mesothelioma datasets (Bueno, NCI, TCGA and Creaney) and showed a potential to respond to cancer immunotherapy. Here, the shared data include R markdown files to perform Gene set enrichment analysis (GSEA), CIBERSORT and WGCNA on RNAseq data from CCMT mouse model (CCMT data analysis_part 1 and 2). Folder (Gene_signature_development_validation_part 3) include the R markdown file for developing and validating the 6-gene signature via interrogating five independent human mesothelioma datasets.

背景：恶性间皮瘤（Mesothelioma）是一种侵袭性强、致死率高的癌症，与石棉暴露存在密不可分的因果关联。当前采用免疫检查点抑制剂（immune checkpoint inhibitors）伊匹单抗（ipilimumab）联合纳武利尤单抗（nivolumab）的治疗方案，已显著改善了患者的治疗结局，但持久的治疗应答仅见于15%~20%的患者亚群，这凸显出开发更精准的治疗应答预测策略的必要性。方法：本研究针对遗传多样性小鼠模型CC-MexTAg（CC-MexTAg model）构建的大型肿瘤生物样本库（n=167）开展RNA测序（RNAseq），对比不同总生存期小鼠的肿瘤基因表达谱，以开发预后基因标签。结果：尽管肿瘤基因表达数据的差异并未与CC-MexTAg小鼠总生存期的3倍差异存在相关性，我们鉴定出两个分别具备免疫表型与非免疫表型的独特肿瘤簇，其中免疫型肿瘤簇展现出更优的癌症治疗应答潜力。我们选取与该肿瘤表型相关的20个枢纽基因（hub genes），构建了一套6基因标签，该标签可在Bueno、NCI、TCGA及Creaney四个独立的间皮瘤数据集中预测患者生存期，并具备预测癌症免疫治疗应答的潜力。本研究公开共享的数据包含用于对CCMT小鼠模型的RNA测序数据开展基因集富集分析（Gene Set Enrichment Analysis, GSEA）、CIBERSORT及加权基因共表达网络分析（Weighted Gene Co-expression Network Analysis, WGCNA）的R Markdown文件，对应文件分为CCMT数据分析_第1部分与第2部分。文件夹Gene_signature_development_validation_part 3 中包含用于通过分析五个独立的人类间皮瘤数据集以开发并验证该6基因标签的R Markdown文件。