Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India.
Centre of Brain Research, Indian Institute of Sciences, Bangalore, Karnataka, India.
J Transl Med. 2023 Aug 20;21(1):558. doi: 10.1186/s12967-023-04435-6.
Tumor invasiveness reflects numerous biological changes, including tumorigenesis, progression, and metastasis. To decipher the role of transcriptional regulators (TR) involved in tumor invasiveness, we performed a systematic network-based pan-cancer assessment of master regulators of cancer invasiveness.
We stratified patients in The Cancer Genome Atlas (TCGA) into invasiveness high (INV-H) and low (INV-L) groups using consensus clustering based on an established robust 24-gene signature to determine the prognostic association of invasiveness with overall survival (OS) across 32 different cancers. We devise a network-based protocol to identify TRs as master regulators (MRs) unique to INV-H and INV-L phenotypes. We validated the activity of MRs coherently associated with INV-H phenotype and worse OS across cancers in TCGA on a series of additional datasets in the Prediction of Clinical Outcomes from the Genomic Profiles (PRECOG) repository.
Based on the 24-gene signature, we defined the invasiveness score for each patient sample and stratified patients into INV-H and INV-L clusters. We observed that invasiveness was associated with worse survival outcomes in almost all cancers and had a significant association with OS in ten out of 32 cancers. Our network-based framework identified common invasiveness-associated MRs specific to INV-H and INV-L groups across the ten prognostic cancers, including COL1A1, which is also part of the 24-gene signature, thus acting as a positive control. Downstream pathway analysis of MRs specific to INV-H phenotype resulted in the identification of several enriched pathways, including Epithelial into Mesenchymal Transition, TGF-β signaling pathway, regulation of Toll-like receptors, cytokines, and inflammatory response, and selective expression of chemokine receptors during T-cell polarization. Most of these pathways have connotations of inflammatory immune response and feasibility for metastasis.
Our pan-cancer study provides a comprehensive master regulator analysis of tumor invasiveness and can suggest more precise therapeutic strategies by targeting the identified MRs and downstream enriched pathways for patients across multiple cancers.
肿瘤侵袭性反映了许多生物学变化,包括肿瘤发生、进展和转移。为了解析参与肿瘤侵袭性的转录调控因子(TR)的作用,我们对癌症侵袭性的主要调控因子进行了系统的基于网络的泛癌症评估。
我们使用基于已建立的稳健 24 基因特征的共识聚类,将癌症基因组图谱(TCGA)中的患者分为侵袭性高(INV-H)和低(INV-L)组,以确定侵袭性与 32 种不同癌症的总生存期(OS)之间的预后关联。我们设计了一种基于网络的方案,以确定作为 INV-H 和 INV-L 表型独特的主调控因子(MR)的 TR。我们在 TCGA 中来自基因组图谱预测临床结局(PRECOG)存储库的一系列附加数据集中验证了与 INV-H 表型和更差的 OS 一致相关的 MR 的活性。
基于 24 基因特征,我们为每个患者样本定义了侵袭性评分,并将患者分为 INV-H 和 INV-L 簇。我们观察到侵袭性与几乎所有癌症的生存结局较差相关,并且在 32 种癌症中有 10 种与 OS 有显著关联。我们的基于网络的框架在十个预后癌症中确定了 INV-H 和 INV-L 组中常见的侵袭性相关的 MR,包括 COL1A1,它也是 24 基因特征的一部分,因此作为阳性对照。INV-H 表型特异的 MR 的下游途径分析导致了几个富集途径的鉴定,包括上皮间质转化、TGF-β信号通路、Toll 样受体的调节、细胞因子和炎症反应,以及 T 细胞极化期间趋化因子受体的选择性表达。这些途径大多数都具有炎症免疫反应的含义和转移的可行性。
我们的泛癌症研究提供了肿瘤侵袭性的全面主调控因子分析,并通过针对多个癌症患者的鉴定的 MR 和下游富集途径,为更精确的治疗策略提供了依据。