Development of a novel hypoxia-immune–related LncRNA risk signature for predicting the prognosis and immunotherapy response of colorectal cancer - Luan, Likun; Dai, Youguo; Shen, Tao; Yang, Changlong; Chen, Zhenpu; Liu, Shan; Jia, Junyi; Li, Zhenhui; Fang, Shaojun; Qiu, Hengqiong; Cheng, Xianshuo; Yang, Zhibin (Frontiers in Immunology, 2022)
Background: Colorectal cancer (CRC) is one of the most common digestive system tumors worldwide. Hypoxia and immunity are closely related in CRC, however, the role of hypoxia-immune-related lncRNAs in CRC prognosis is unknown. Methods: Data used in the current study were sourced from the Gene Expression Ominibus and The Cancer Genome Atlas (TCGA) databases. CRC patients were divided into low- and high-hypoxia groups using the single-sample gene set enrichment analysis (ssGSEA) algorithm and into low- and high-immune groups using the ESTIMATE algorithm. Differentially expressed lncRNAs (DElncRNAs) between low- and high-hypoxia groups, low- and high-immune groups, and tumor and control samples were identified using the limma package. Hypoxia-immune-related lncRNAs were obtained by intersecting these DElncRNAs. A hypoxia-immune-related lncRNA risk signature was developed using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. The tumor microenvironments in the low- and high-risk groups were evaluated using ssGSEA, ESTIMATE, and the expression of immune checkpoints. The therapeutic response in the two groups was assessed using TIDE, IPS, and IC50. A ceRNA network based on signature lncRNAs was constructed. Finally, we used RT-qPCR to verify the expression of hypoxia-immune-related lncRNA signatures in normal and cancer tissues. Results: Using differential expression analysis, and univariate Cox and LASSO regression analyses, ZNF667-AS1, LINC01354, LINC00996, DANCR, CECR7 and LINC01116 were selected to construct a hypoxia-immune-related lncRNA signature. The performance of the risk signature in predicting CRC prognosis was validated in internal and external datasets, as evidenced by receiver operating characteristic curves. In addition, we observed significant differences in the tumor microenvironment and immunotherapy response between low- and high-risk groups and constructed a CECR7-miRNA-mRNA regulatory network in CRC. Furthermore, RT-qPCR results confirmed that the expression patterns of the six lncRNA signatures were consistent with those in the TCGA-CRC cohort. Conclusion: Our study identified six hypoxia-immune-related lncRNAs for predicting CRC survival and sensitivity to immunotherapy. These findings may enrich our understanding of CRC and help improve CRC treatment. However, large-scale long-term follow-up studies are required for verification.