Exploration of the Associations of lncRNA Expression Patterns with Tumor Mutation Burden and Prognosis in Colon Cancer

BACKGROUND: Tumor mutation burden (TMB) is emerging as a new biomarker to monitor the response of cancer patients to immunotherapy. Long non-coding RNAs (lncRNAs) are critical in regulating gene expression and play a significant role in cancer-associated immune responses. However, the association between lncRNA expression patterns and TMB levels and survival outcomes remains unknown in colon cancer. METHODS: In colon cancer patients from The Cancer Genome Atlas Program (TCGA), a multi-lncRNAs based classifier for predicting TMB levels was established using the least absolute shrinkage and selection operator (LASSO) method. The association between classifier index and immune-related characteristics of patients was also investigated. Quantitative polymerase chain reaction (qPCR) was used to verify the expression levels of these lncRNAs in normal and CRC cell lines. RESULTS: The multi-lncRNAs based classifier had ability to predict TMB level of patients with accuracy (AUC= 0.70), and the general applicability of this classifier was proved in the validation set (AUC= 0.71) and the pooled set (AUC= 0.70). The classifier index was related to three immune checkpoints (PD1, PD-L1, and CTLA-4), the infiltration level of immune cells, and immune response-related score (IFN-γ score, gene expression profiles (GEP) score, cytolytic activity (CYT) score and MHC score). A nomogram, which integrates classifier and some common clinical information, was able to predict the overall survival of colon cancer patients accurately. CONCLUSION: LncRNA expression patterns are associated with TMB, which may serve as a classifier to predict the TMB in colon cancer patients. The nomogram could potentially evaluate survival outcomes and provide a reference to better manage colon cancer patients.