Prognostic Value of Immune-Related Multi-IncRNA Signatures Associated With Tumor Microenvironment in Esophageal Cancer - Pang, Jingjing; Pan, He; Yang, Chunxiu; Meng, Pei; Xie, Wen; Li, Jiahao; Li, Yueying; Xiao, Shu-Yuan (Frontiers in Genetics, 2021)
Esophageal cancer is the eighth most common cancer and the sixth leading cause of cancer death worldwide. Hence, for better understanding of tumor microenvironment and seeking for novel molecular targets for esophageal cancer, we performed related researches on two histopathological subtypes of esophageal cancer: esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). Bioinformatic analyses were conducted based on the RNA-seq, genomic mutation, and clinical data from TCGA and GEO cohorts. We clustered patients into high immunity and low immunity groups through the ssGSEA results. The ESTIMATE algorithm was used to evaluate the tumor microenvironment. Patients with high immunity in both ESCC and EAC had lower tumor purity and poor survival. Subsequently, CIBERSORT was performed to learn about the detailed difference of tumor infiltrating lymphocytes (TILs) between high and low immunity patients. Specific increasing of M2 macrophages and decreasing of activated dendric cells can be observed in ESCC and EAC respectively. The most enriched functions and pathways of high immunity patients were immunoglobulin complex, MHC class II protein complex and allograft rejection according to the GO terms and KEGG. Two prognostic immune-related multi-lncRNA risk models were constructed and validated by ROC curve and PCA in ESCC and EAC. High-risk patients in both subtypes had poor survival, advanced clinical characteristics and higher drug susceptibility except cisplatin and sorafenib. In addition, the tumor mutation burden (TMB) was positively correlated with the risk level in the ESCC and EAC and showed distinct differences between the two subtypes. In summary, we comprehensively analyzed the tumor microenvironment for two subtypes of esophageal cancer, identified two multi-lncRNA signatures predictive for the prognosis and explored the possibility of the signatures to forecast drug susceptibility as well as TMB for the first time. The findings may serve as a conceptual basis for innovative strategy of individualized immunotherapy for esophageal cancer.