Prognostic Immunity and Therapeutic Sensitivity Analyses Based on Differential Genomic Instability-Associated LncRNAs in Left- and Right-Sided Colon Adenocarcinoma - Guo, Jun-Nan; Xia, Tian-Yi; Deng, Shen-Hui; Xue, Wei-Nan; Cui, Bin-Bin; Liu, Yan-Long (Frontiers in Molecular Biosciences, 2021)
Background: The purpose of our study was to develop a prognostic risk model based on differential genomic instability-associated (DGIA) Long non-coding RNAs (lncRNAs) of LCCs and RCCs, therefore the prognostic key lncRNAs could be identified. Methods: We adopted two independent gene data-sets, corresponding somatic mutation and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Identification of differential DGIA lncRNAs from LCCs and RCCs were conducted with appliance of "Limma" analysis. Then, we screened out key lncRNAs based on univariate and multivariate Cox proportional hazard regression analysis. Meanwhile, DGIA lncRNAs related prognostic model (DRPM) was established. We employed the DRPM in the model group and internal verification group from TCGA for the purpose of risk grouping and accuracy verification of PRSM. We also verified the accuracy of key lncRNAs with GEO data. Finally, the differences of immune infiltration, functional pathways and therapeutic sensitivities were analyzed within different risk groups. Results: A total of 123 DGIA lncRNAs were screened out by differential expression analysis. We obtained 6 DGIA lncRNAs by the construction of DRPM, including AC004009.1, AP003555.2, BOLA3-AS1, NKILA, LINC00543 and UCA1. After the risk grouping by these DGIA lncRNAs, we found the prognosis of high-risk group (HRG) was significantly worse than that in low-risk group (LRG) (all p < 0.05). In all TCGA samples and model group, the expression of CD8+ T cells in HRG was lower than that in LRG (all p < 0.05). The functional analysis indicated that there was significant up-regulation with regard of pathways related to both genetic instability and immunity in LRG, including cytosolic DNA sensing pathway, response to dsRNA, RIG-Ⅰ like receptor signaling pathway and Toll-like receptor signaling pathway. Finally, we analyzed the difference and significance of key DGIA lncRNAs and risk groups in multiple therapeutic sensitivities. Conclusion: Through the analysis of the DGIA lncRNAs between LCCs and RCCs, we identified 6 key DGIA lncRNAs. They can not only predict the prognostic risk of patients, but also serve as biomarkers for evaluating the differences of genetic instability, immune infiltration and therapeutic sensitivity.