Background: Colorectal cancer (CRC) has been the 3rd most commonly malignant tumor of the gastrointestinal tract in the world. 5-Methylcytosine (mC) and long noncoding RNAs (lncRNAs) have an essential role in predicting the prognosis and immune response for CRC patients. Therefore, we built a mC-related lncRNA (mCRlncRNA) model to investigate the prognosis and treatment methods for CRC patients.

Methods: Firstly, we secured the transcriptome and clinical data for CRC from The Cancer Genome Atlas (TCGA). Then, mCRlncRNAs were recognized by coexpression analysis. Then, univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were utilized to build mC-related prognostic characteristics. Besides, Kaplan-Meier analysis, ROC, PCA, -index, enrichment analysis, and nomogram were performed to investigate the model. Additionally, immunotherapy responses and antitumor medicines were explored for CRC patients.

Results: A total of 8 mC-related lncRNAs (AC093157.1, LINC00513, AC025171.4, AC090948.2, ZEB1-AS1, AC109449.1, AC009041.3, and LINC02516) were adopted to construct a risk model to investigate survival and prognosis for CRC patients. CRC samples were separated into low- and high-risk groups, with the latter having a worse prognosis. The mC-related lncRNA model helps us to better distinguish immunotherapy responses and IC50 of antitumor medicines in different groups of CRC patients.

Conclusion: The research may give new perspectives on tailored therapy approaches as well as novel theories for forecasting the prognosis of CRC patients.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116225PMC
http://dx.doi.org/10.1155/2023/6632205DOI Listing

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