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Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management
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 r...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539594/ https://www.ncbi.nlm.nih.gov/pubmed/37781709 http://dx.doi.org/10.3389/fphar.2023.1249145 |
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author | Yuan, Na Pan, Hai-Hua Liang, Yan-Shan Hu, Hui-Lin Zhai, Chang-Lin Wang, Bo |
author_facet | Yuan, Na Pan, Hai-Hua Liang, Yan-Shan Hu, Hui-Lin Zhai, Chang-Lin Wang, Bo |
author_sort | Yuan, Na |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10539594 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105395942023-09-30 Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management Yuan, Na Pan, Hai-Hua Liang, Yan-Shan Hu, Hui-Lin Zhai, Chang-Lin Wang, Bo Front Pharmacol Pharmacology 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. Frontiers Media S.A. 2023-09-14 /pmc/articles/PMC10539594/ /pubmed/37781709 http://dx.doi.org/10.3389/fphar.2023.1249145 Text en Copyright © 2023 Yuan, Pan, Liang, Hu, Zhai and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Yuan, Na Pan, Hai-Hua Liang, Yan-Shan Hu, Hui-Lin Zhai, Chang-Lin Wang, Bo Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management |
title | Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management |
title_full | Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management |
title_fullStr | Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management |
title_full_unstemmed | Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management |
title_short | Identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management |
title_sort | identification of prognostic and diagnostic signatures for cancer and acute myocardial infarction: multi-omics approaches for deciphering heterogeneity to enhance patient management |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10539594/ https://www.ncbi.nlm.nih.gov/pubmed/37781709 http://dx.doi.org/10.3389/fphar.2023.1249145 |
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