PDF(Pubmed)
Abstract：
Breast cancers (BRCA) exhibit substantial transcriptional heterogeneity, posing a significant clinical challenge. The global transcriptional changes in a disease context, however, are likely mediated by few key genes which reflect disease etiology better than the differentially expressed genes (DEGs). We apply our network-based tool PathExt to 1,059 BRCA tumors across 4 subtypes to identify key mediator genes in each subtype. Compared to conventional differential expression analysis, PathExt-identified genes exhibit greater concordance across tumors, revealing shared and subtype-specific biological processes; better recapitulate BRCA-associated genes in multiple benchmarks, and are more essential in BRCA subtype-specific cell lines. Single-cell transcriptomic analysis reveals a subtype-specific distribution of PathExt-identified genes in multiple cell types from the tumor microenvironment. Application of PathExt to a TNBC chemotherapy response dataset identified subtype-specific key genes and biological processes associated with resistance. We described putative drugs that target key genes potentially mediating drug resistance.
摘要：
乳腺癌（BRCA）表现出实质性的转录异质性，构成了重大的临床挑战。疾病背景下的全球转录变化，然而,可能是由少数关键基因介导的，这些关键基因比差异表达基因（DEGs）更好地反映疾病的病因。我们将基于网络的工具PathExt应用于4种亚型的1,059例BRCA肿瘤，以识别每种亚型中的关键介质基因。与常规差异表达分析相比，PathExt鉴定的基因在肿瘤中表现出更大的一致性，揭示共享和亚型特异性的生物过程；更好地在多个基准中概括BRCA相关基因，在BRCA亚型特异性细胞系中更重要。单细胞转录组分析揭示了来自肿瘤微环境的多种细胞类型中PathExt鉴定的基因的亚型特异性分布。将PathExt应用于TNBC化疗反应数据集鉴定了亚型特异性关键基因和与抗性相关的生物过程。我们描述了靶向潜在介导耐药性的关键基因的推定药物。
