Constructing a novel signature and predicting the immune landscape of colon cancer using N6-methylandenosine-related lncRNAs

oleh: Yongfeng Wang, Yongfeng Wang, Yongfeng Wang, Yongfeng Wang, Dongzhi Zhang, Dongzhi Zhang, Dongzhi Zhang, Dongzhi Zhang, Yuxi Li, Yue Wu, Haizhong Ma, Haizhong Ma, Xianglai Jiang, Xianglai Jiang, Liangyin Fu, Guangming Zhang, Haolan Wang, Xingguang Liu, Hui Cai, Hui Cai, Hui Cai, Hui Cai

Format: Article
Diterbitkan: Frontiers Media S.A. 2023-06-01

Deskripsi

Background: Colon cancer (CC) is a prevalent malignant tumor that affects people all around the world. In this study, N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) in 473 colon cancers and 41 adjacent tissues of CC patients from The Cancer Genome Atlas (TCGA) were investigated.Method: The Pearson correlation analysis was conducted to examine the m6A-related lncRNAs, and the univariate Cox regression analysis was performed to screen 38 prognostic m6A-related lncRNAs. The least absolute shrinkage and selection operator (LASSO) regression analysis were carried out on 38 prognostic lncRNAs to develop a 14 m6A-related lncRNAs prognostic signature (m6A-LPS) in CC. The availability of the m6A-LPS was evaluated using the Kaplan–Meier and Receiver Operating Characteristic (ROC) curves.Results: Three m6A modification patterns with significantly different N stages, survival time, and immune landscapes were identified. It has been discovered that the m6A-LPS, which is based on 14 m6A-related lncRNAs (TNFRSF10A-AS1, AC245041.1, AL513550.1, UTAT33, SNHG26, AC092944.1, ITGB1-DT, AL138921.1, AC099850.3, NCBP2-AS1, AL137782.1, AC073896.3, AP006621.2, AC147651.1), may represent a new, promising biomarker with great potential. It was re-evaluated in terms of survival rate, clinical features, tumor infiltration immune cells, biomarkers related to Immune Checkpoint Inhibitors (ICIs), and chemotherapeutic drug efficacy. The m6A-LPS has been revealed to be a novel potential and promising predictor for evaluating the prognosis of CC patients.Conclusion: This study revealed that the risk signature is a promising predictive indicator that may provide more accurate clinical applications in CC therapeutics and enable effective therapy strategies for clinicians.