Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer

Rixin Zhang; Wenqiang Gan; Jinbao Zong; Yufang Hou; Mingxuan Zhou; Zheng Yan; Tiegang Li; Silin Lv; Zifan Zeng; Weiqi Wang; Fang Zhang; Min Yang

doi:10.3389/fimmu.2023.1054700

Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy efficacy in rectal cancer

Front Immunol. 2023 Feb 22:14:1054700. doi: 10.3389/fimmu.2023.1054700. eCollection 2023.

Authors

Rixin Zhang¹, Wenqiang Gan¹, Jinbao Zong^{2

3}, Yufang Hou¹, Mingxuan Zhou¹, Zheng Yan¹, Tiegang Li¹, Silin Lv¹, Zifan Zeng¹, Weiqi Wang¹, Fang Zhang¹, Min Yang¹

Affiliations

¹ State Key Laboratory of Bioactive Substances and Function of Natural Medicine, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
² Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao, China.
³ Qingdao Hospital of Traditional Chinese Medicine, The Affiliated Qingdao Hiser Hospital of Qingdao University, Qingdao, China.

Abstract

Background: Currently, a very small number of patients with colorectal cancer (CRC) respond to immune checkpoint inhibitor (ICI) treatment. Therefore, there is an urgent need to investigate effective biomarkers to determine the responsiveness to ICI treatment. Recently, aberrant 5-methylcytosine (m⁵C) RNA modification has emerged as a key player in the pathogenesis of cancer. Thus, we aimed to explore the predictive signature based on m⁵C regulator-related genes for characterizing the immune landscapes and predicting the prognosis and response to therapies.

Methods: The Cancer Genome Atlas (TCGA) cohort was used as the training set, while GEO data sets, real-time quantitative PCR (RT-qPCR) analysis from paired frozen tissues, and immunohistochemistry (IHC) data from tissue microarray (TMA) were used for validation. We constructed a novel signature based on three m⁵C regulator-related genes in patients with rectal adenocarcinoma (READ) using a least absolute shrinkage and selection operator (LASSO)-Cox regression and unsupervised consensus clustering analyses. Additionally, we correlated the three-gene signature risk model with the tumor immune microenvironment, immunotherapy efficiency, and potential applicable drugs.

Results: The m⁵C methylation-based signature was an independent prognostic factor, where low-risk patients showed a stronger immunoreactivity phenotype and a superior response to ICI therapy. Conversely, the high-risk patients had enriched pathways of cancer hallmarks and presented immune-suppressive state, which demonstrated that they are more insensitive to immunotherapy. Additionally, the signature markedly correlated with drug susceptibility.

Conclusions: We developed a reliable m⁵C regulator-based risk model to predict the prognosis, clarify the molecular and tumor microenvironment status, and identify patients who would benefit from immunotherapy or chemotherapy. Our study could provide vital guidance to improve prognostic stratification and optimize personalized therapeutic strategies for patients with rectal cancer.

Keywords: rectal cancer; immunotherapy; m5C RNA methylation regulator; prognosis; tumor immune microenvironment.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Humans
Immunotherapy*
Methylation
Prognosis
RNA
Rectal Neoplasms*
Tumor Microenvironment

Substances

RNA

Grants and funding

This work was supported by the grants from CAMS Innovation Fund for Medical Sciences (CIFMS) (No. 2021-I2M-1-028) and the Natural Science Foundation of China (NSFC) (No. 81773750).