AUTHOR=Liu Yang , Wang Yizhao , Li Chang , Feng Huijin , Liu Yanqing , Ma Lianjun 

TITLE=An effective prognostic model in colon adenocarcinoma composed of cuproptosis-related epigenetic regulators

JOURNAL=Frontiers in Pharmacology

VOLUME=14

YEAR=2023

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2023.1254918

DOI=10.3389/fphar.2023.1254918

ISSN=1663-9812

ABSTRACT=<p><bold>Background:</bold> Colorectal adenocarcinoma (COAD) is a common malignant tumor with little effective prognostic markers. Cuproptosis is a newly discovered mode of cell death that may be related to epigenetic regulators. This study aimed to explore the association between epigenetic regulators and cuproptosis, and to establish a prognostic prediction model for COAD based on epigenetic regulators associated with cuproptosis (EACs).</p><p><bold>Methods:</bold> RNA sequencing data and clinical data of 524 COAD patients were obtained from the TCGA-COAD database, cuproptosis-related genes were from the FerrDb database, and epigenetic-related genes were from databases such as GO and EpiFactors. LASSO regression analysis and other methods were used to screen out epigenetic regulators associated with cuproptosis and prognosis. The risk score of each patient was calculated and the patients were divided into high-risk group and low-risk group. Next, the survival difference, functional enrichment analyses, tumor mutation burden, chemotherapy drug sensitivity and other indicators between the two groups were compared and analyzed.</p><p><bold>Results:</bold> We found 716 epigenetic regulators closely related to cuproptosis, among which 35 genes were related to prognosis of COAD. We further screened out 7 EACs from the 35 EACs to construct a prognostic prediction model. We calculated the risk score of each patient based on these 7 genes, and divided the patients into high-risk group and low-risk group. We found that the overall survival rate and progression-free survival rate of the high-risk group were significantly lower than those of the low-risk group. This model showed good predictive ability in the training set, test set and overall data set. We also constructed a prognostic prediction model based on risk score and other clinical features, and drew the corresponding Nomogram. In addition, we found significant differences between the high-risk group and the low-risk group in tumor mutation burden, chemotherapy drug sensitivity and other clinical aspects.</p><p><bold>Conclusion:</bold> We established an effective predictive prediction model for COAD based on EACs, revealing the association between epigenetic regulators and cuproptosis in COAD. We hope that this model can not only facilitate the treatment decision of COAD patients, but also promote the research progress in the field of cuproptosis.</p>