Data sets of colorectal cancer (CRC) were obtained from The Cancer Genome Atlas (TCGA), three N6‐methyladenosine (m6A) subtypes were identified using 21 m6A‐related long noncoding RNAs (lncRNAs) and differential m6A… Click to show full abstract
Data sets of colorectal cancer (CRC) were obtained from The Cancer Genome Atlas (TCGA), three N6‐methyladenosine (m6A) subtypes were identified using 21 m6A‐related long noncoding RNAs (lncRNAs) and differential m6A subtypes of different CRC tumors were determined in this study to evaluate the m6A expression and the prognosis of patients with CRC. Subsequently, eight key lncRNAs were identified based on co‐expression with 21 m6A‐related genes in CRC tumors using the single‐factor Cox and least absolute shrinkage and selection operator. Finally, an m6A‐related lncRNA risk score model of CRC tumor was established using multifactor Cox regression based on the eight important lncRNAs and found to have a better performance in evaluating the prognosis of patients in the TCGA‐CRC data set. TCGA‐CRC tumor samples were divided based on the risk scores: high and low. Then, the clinical characteristics, tumor mutation load, and tumor immune cell infiltration difference between the high‐ and low‐risk‐score groups were explored, and the predictive ability of the risk score was assessed for immunotherapeutic benefits. We found that the risk score model can determine the overall survival, be a relatively independent prognostic indicator, and better evaluate the immunotherapeutic benefits for patients with CRC. This study provides data support for accurate immunotherapy in CRC.
               
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