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

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

doi:10.3389/fgene.2023.906346

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

Front Genet. 2023 Jun 16:14:906346. doi: 10.3389/fgene.2023.906346. eCollection 2023.

Authors

Yongfeng Wang^{1

2

3

4}, Dongzhi Zhang^{1

2

3

4}, Yuxi Li¹, Yue Wu¹, Haizhong Ma^{3

4}, Xianglai Jiang^{2

3}, Liangyin Fu², Guangming Zhang¹, Haolan Wang², Xingguang Liu¹, Hui Cai^{1

2

3

4}

Affiliations

¹ The First Clinical Medical College of Lanzhou University, Lanzhou, Gansu, China.
² General Surgery Clinical Medical Center, Gansu Provincial Hospital, Lanzhou, Gansu, China.
³ Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province, Gansu Provincial Hospital, Gansu, China.
⁴ NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China.

Abstract

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.

Keywords: colon cancer; immune landscape; m6A-related lncRNAs; prognostic signatures; tumor immune microenvironment.

Grants and funding

This work was funded by The 2021 Central-Guided Local Science and Technology Development Fund (ZYYDDFFZZJ-1), Natural Science Foundation of Gansu Province, China (No. 18JR3RA052), Lanzhou Talent Innovation and Entrepreneurship Project Task Contract (No. 2016-RC-56), Gansu Da Vinci robot high-end diagnosis and treatment team construction project, Excellent master/doctoral program of Gansu Provincial People's Hospital (22GSSYD-1), National Key Research and Development Program (No. 2018YFC1311500), COVID-19 prevention and control technology research project (2020-XG-1), Gansu Province Excellent Doctor Fund Project (23JRRA1320), and National Key Research and Development Program (No. 2018YFC1311500).