Zhang Baohui, Tang Bufu, Gao Jianyao, Li Jiatong, Kong Lingming, Qin Ling
Department of Physiology, School of Life Science, China Medical University, No. 77 Puhe Road, Shenyang North New AreaLiaoning Province, Shenyang, 110122, People's Republic of China.
Department of Radiology, School of Medicine, Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China.
J Transl Med. 2020 Sep 4;18(1):342. doi: 10.1186/s12967-020-02492-9.
Hypoxia plays an indispensable role in the development of hepatocellular carcinoma (HCC). However, there are few studies on the application of hypoxia molecules in the prognosis predicting of HCC. We aim to identify the hypoxia-related genes in HCC and construct reliable models for diagnosis, prognosis and recurrence of HCC patients as well as exploring the potential mechanism.
Differentially expressed genes (DEGs) analysis was performed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and four clusters were determined by a consistent clustering analysis. Three DEGs closely related to overall survival (OS) were identified using Cox regression and LASSO analysis. Then the hypoxia-related signature was developed and validated in TCGA and International Cancer Genome Consortium (ICGC) database. The Gene Set Enrichment Analysis (GSEA) was performed to explore signaling pathways regulated by the signature. CIBERSORT was used for estimating the fractions of immune cell types.
A total of 397 hypoxia-related DEGs in HCC were detected and three genes (PDSS1, CDCA8 and SLC7A11) among them were selected to construct a prognosis, recurrence and diagnosis model. Then patients were divided into high- and low-risk groups. Our hypoxia-related signature was significantly associated with worse prognosis and higher recurrence rate. The diagnostic model also accurately distinguished HCC from normal samples and nodules. Furthermore, the hypoxia-related signature could positively regulate immune response. Meanwhile, the high-risk group had higher fractions of macrophages, B memory cells and follicle-helper T cells, and exhibited higher expression of immunocheckpoints such as PD1and PDL1.
Altogether, our study showed that hypoxia-related signature is a potential biomarker for diagnosis, prognosis and recurrence of HCC, and it provided an immunological perspective for developing personalized therapies.
缺氧在肝细胞癌（HCC）的发展过程中起着不可或缺的作用。然而，关于缺氧分子在HCC预后预测中的应用研究较少。我们旨在识别HCC中与缺氧相关的基因，并构建用于HCC患者诊断、预后和复发的可靠模型，同时探索潜在机制。
使用癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）进行差异表达基因（DEG）分析，并通过一致性聚类分析确定四个聚类。使用Cox回归和LASSO分析鉴定出与总生存期（OS）密切相关的三个DEG。然后在TCGA和国际癌症基因组联盟（ICGC）数据库中开发并验证缺氧相关特征。进行基因集富集分析（GSEA）以探索该特征调控的信号通路。使用CIBERSORT估计免疫细胞类型的比例。
共检测到HCC中397个与缺氧相关的DEG，其中选择三个基因（PDSS1、CDCA8和SLC7A11）构建预后、复发和诊断模型。然后将患者分为高风险和低风险组。我们的缺氧相关特征与较差的预后和较高的复发率显著相关。诊断模型也能准确地区分HCC与正常样本和结节。此外，缺氧相关特征可正向调节免疫反应。同时，高风险组中巨噬细胞、B记忆细胞和滤泡辅助性T细胞的比例较高，且免疫检查点如PD1和PDL1的表达较高。
总之，我们的研究表明，缺氧相关特征是HCC诊断、预后和复发的潜在生物标志物，并为开发个性化治疗提供了免疫学视角。
