Division of General Medical Sciences-Oncology, Case Comprehensive Cancer Center.
Department of Genetics and genome Sciences.
Brief Bioinform. 2022 Jul 18;23(4). doi: 10.1093/bib/bbac280.
Current tailored-therapy efforts in cancer are largely focused on a small number of highly recurrently mutated driver genes but therapeutic targeting of these oncogenes remains challenging. However, the vast number of genes mutated infrequently across cancers has received less attention, in part, due to a lack of understanding of their biological significance. We present SYSMut, an extendable systems biology platform that can robustly infer the biologic consequences of somatic mutations by integrating routine multiomics profiles in primary tumors. We establish SYSMut's improved performance vis-à-vis state-of-the-art driver gene identification methodologies by recapitulating the functional impact of known driver genes, while additionally identifying novel functionally impactful mutated genes across 29 cancers. Subsequent application of SYSMut on low-frequency gene mutations in head and neck squamous cell (HNSC) cancers, followed by molecular and pharmacogenetic validation, revealed the lipidogenic network as a novel therapeutic vulnerability in aggressive HNSC cancers. SYSMut is thus a robust scalable framework that enables the discovery of new targetable avenues in cancer.
目前癌症的针对性治疗主要集中在少数高度反复突变的驱动基因上,但这些致癌基因的治疗靶向仍然具有挑战性。然而,由于对其生物学意义缺乏了解,癌症中频繁突变的大量基因受到的关注较少。我们提出了 SYSMut,这是一个可扩展的系统生物学平台,可以通过整合原发肿瘤的常规多组学谱,稳健地推断体细胞突变的生物学后果。我们通过重现已知驱动基因的功能影响,证明了 SYSMut 相对于最先进的驱动基因识别方法的改进性能,同时在 29 种癌症中确定了新的具有功能影响的突变基因。随后在头颈部鳞状细胞癌 (HNSC) 中的低频基因突变上应用 SYSMut,并进行分子和遗传药理学验证,揭示了脂质生成网络是侵袭性 HNSC 癌症的一个新的治疗弱点。因此,SYSMut 是一个强大的可扩展框架,能够在癌症中发现新的靶向途径。