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Developing an m5C regulator-mediated RNA methylation modification signature to predict prognosis and immunotherapy
Rixin Zhang1, Wenqiang Gan1, Jinbao Zong2,3
1State 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.
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.
Insights
A new risk model based on 5-methylcytosine (m5C) RNA modification regulators can predict colorectal cancer patient prognosis and response to immunotherapy, aiding personalized treatment strategies.
Area of Science:
- Oncology
- Molecular Biology
- Immunotherapy
Background:
- Limited patient response to immune checkpoint inhibitors (ICIs) in colorectal cancer (CRC) necessitates novel predictive biomarkers.
- Aberrant 5-methylcytosine (m5C) RNA modification is implicated in cancer development.
- Investigating m5C regulators may reveal predictive signatures for ICI treatment responsiveness.
Purpose of the Study:
- To develop a predictive signature based on m5C regulator-related genes for rectal adenocarcinoma (READ).
- To characterize immune landscapes and predict prognosis and therapy response in READ patients.
- To correlate the signature with tumor microenvironment, immunotherapy efficiency, and drug susceptibility.
Main Methods:
- Utilized The Cancer Genome Atlas (TCGA) cohort for training and GEO datasets for validation.
- Employed real-time quantitative PCR (RT-qPCR) and immunohistochemistry (IHC) for further validation.
- Constructed a three-gene signature using LASSO-Cox regression and unsupervised consensus clustering.
Main Results:
- The m5C methylation-based signature independently predicted prognosis.
- Low-risk patients exhibited enhanced immunoreactivity and better ICI response.
- High-risk patients showed immune suppression and enrichment of cancer hallmark pathways, indicating poor immunotherapy response.
Conclusions:
- A reliable m5C regulator-based risk model was developed for predicting prognosis and immune microenvironment status in rectal cancer.
- The model identifies patients likely to benefit from immunotherapy or chemotherapy.
- This study offers guidance for improved prognostic stratification and personalized therapeutic strategies in rectal cancer.
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