Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management

Frontiers in Pharmacology

Pharmacology

Bo Wang¹  Yan-Shan Liang²  Chang-Lin Zhai³  Hai-Hua Pan³  Na Yuan³  Hui-Lin Hu³ 

[1] 3, The Second Affiliated Hospital of Jiaxing University, Jiaxing, Zhejiang, China;Affiliated Dongguan Hospital, Southern Medical University, Dongguan, Guangdong, China;The First Hospital of Jiaxing Affiliated Hospitial of Jiaxing University, Jiaxing, Zhejiang, China;

关键词: signature;    AMI;    cancer;    machine learning;    prognosis;   

DOI  :  10.3389/fphar.2023.1249145

 received in 2023-06-28, accepted in 2023-09-04,  发布年份 2023

来源: Frontiers

【 摘 要 】

Patients diagnosed with cancer face an increased risk of cardiovascular events in the short term, while those experiencing acute myocardial infarction (AMI) have a higher incidence of cancer. Given limitations in clinical resources, identifying shared biomarkers offers a cost-effective approach to risk assessment by minimizing the need for multiple tests and screenings. Hence, it is crucial to identify common biomarkers for both cancer survival and AMI prediction. Our study suggests that monocyte-derived biomarkers, specifically WEE1, PYHIN1, SEC61A2, and HAL, hold potential as predictors for cancer prognosis and AMI. We employed a novel formula to analyze mRNA levels in clinical samples from patients with AMI and cancer, resulting in the development of a new risk score based on expression profiles. By categorizing patients into high-risk and low-risk groups based on the median risk score, we observed significantly poorer overall survival among high-risk patients in cancer cohorts using Kaplan-Meier analysis. Furthermore, calibration curves, decision curve analysis (DCA), and clinical impact curve analyses provided additional evidence supporting the robust diagnostic capacity of the risk score for AMI. Noteworthy is the shared activation of the Notch Signaling pathway, which may shed light on common high-risk factors underlying both AMI and cancer. Additionally, we validated the differential expression of these genes in cell lines and clinical samples, respectively, reinforcing their potential as meaningful biomarkers. In conclusion, our study demonstrates the promise of mRNA levels as biomarkers and emphasizes the significance of further research for validation and refinement.

【 授权许可】

Unknown   
Copyright © 2023 Yuan, Pan, Liang, Hu, Zhai and Wang.