Zeng Fanhong, Zhang Yue, Han Xu, Zeng Min, Gao Yi, Weng Jun
Department of Hepatobiliary Surgery II, Guangdong Provincial Research Center for Artificial Organ and Tissue Engineering, Guangzhou Clinical Research and Transformation Center for Artificial Liver, Institute of Regenerative Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.
State Key Laboratory of Organ Failure Research, Southern Medical University, Guangzhou, China.
Comput Struct Biotechnol J. 2021 Apr 21;19:2775-2789. doi: 10.1016/j.csbj.2021.03.033. eCollection 2021.
The hypoxic microenvironment was recognized as a major driving force of the malignant phenotype in hepatocellular carcinoma (HCC), which contributes to tumour immune microenvironment (TIM) remodeling and tumor progression. Dysregulated hypoxia-related genes (HRGs) result in treatment resistance and poor prognosis by reshaping tumor cellular activities and metabolism. Approaches to identify the relationship between hypoxia and tumor progression provided new sight for improving tumor treatment and prognosis. But, few practical tools, forecasting relationship between hypoxia, TIM, treatment sensitivity and prognosis in HCC were reported. Here, we pooled mRNA transcriptome and clinical pathology data from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), and later developed a hypoxia risk model including four HRGs (). The high-risk group displayed poor clinical characteristics, a malignant phenotype with carcinogenesis/proliferation pathways activation () and immunosuppressive TIM (decreased immune cell infiltrations and upregulated immunosuppressive cytokines). Meanwhile, activated B cells, effector memory CD8 T cells and deregulation were associated with patient's survival, which might be the core changes of HCC hypoxia. Finally, we validated the ability of the hypoxia risk model to predict treatment sensitivity and found high hypoxia risk patients had poor responses to HCC treatment, including surgical resection, Sorafenib, Transarterial Chemoembolization (TACE) and immunotherapy. In conclusion, based on 4 HRGs, we developed and validated a hypoxia risk model to reflect pathological features, evaluate TIM landscape, predict treatment sensitivity and compounds specific to hypoxia signatures in HCC patients.
缺氧微环境被认为是肝细胞癌（HCC）恶性表型的主要驱动力，它有助于肿瘤免疫微环境（TIM）重塑和肿瘤进展。缺氧相关基因（HRGs）失调通过重塑肿瘤细胞活动和代谢导致治疗耐药性和预后不良。识别缺氧与肿瘤进展之间关系的方法为改善肿瘤治疗和预后提供了新视角。但是，很少有实用工具能够预测HCC中缺氧、TIM、治疗敏感性和预后之间的关系。在此，我们汇总了来自国际癌症基因组联盟（ICGC）和癌症基因组图谱（TCGA）的mRNA转录组和临床病理数据，随后开发了一个包含四个HRGs的缺氧风险模型。高风险组表现出不良临床特征、具有致癌/增殖途径激活的恶性表型以及免疫抑制性TIM（免疫细胞浸润减少和免疫抑制细胞因子上调）。同时，活化B细胞、效应记忆CD8 T细胞和失调与患者生存相关，这可能是HCC缺氧的核心变化。最后，我们验证了缺氧风险模型预测治疗敏感性的能力，发现高缺氧风险患者对HCC治疗反应不佳，包括手术切除、索拉非尼、经动脉化疗栓塞（TACE）和免疫治疗。总之，基于4个HRGs，我们开发并验证了一个缺氧风险模型，以反映病理特征、评估TIM格局、预测治疗敏感性并确定HCC患者缺氧特征的特异性化合物。
