Introduction: African American women have a breast cancer mortality rate 40% higher than Caucasian women. Many contributing factors account for this racial disparity, such as socioeconomic status and the age when women give birth, but even after considering such factors, studies have found that the racial disparity persists, suggesting that genetic factors may play a crucial role in this breast cancer racial inequality.
Methods: This study utilizes the All of Us database, The Cancer Genome Atlas (TCGA), and an array of bioinformatics tools to integrate differential mutation and gene expression analyses, aiming to identify genes potentially associated with this racial disparity. Although previous studies have identified genes associated with this breast cancer racial disparity through mutation or gene expression analysis, no studies have considered both simultaneously. Ultimately, this study considers both mutation and gene expression to discover novel genes linked to this racial disparity.
Results: After mutation analysis, this study identified a gene involved in the destruction of oncogenic proteins, as being associated with this racial inequality. was the only gene that presented differences in both mutation frequency and gene expression between African Americans and Caucasians. The other four candidate genes, such as , whose upregulation plays a critical role in tumor progression, may also be linked to this racial inequality.
Conclusion: By combining both mutation and gene expression analysis, this research offers a unique perspective into this issue. Furthermore, the identification of provides insight into this racial disparity, which can contribute to the pursuit of more effective or personalized treatment for both Caucasian and African American breast cancer patients. Finally, the multi-level method presented could possibly apply to other racial disparities, providing a distinctive perspective that cannot be found with other methods.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496049 | PMC |
http://dx.doi.org/10.7759/cureus.69947 | DOI Listing |
Int J Urol
January 2025
Department of Urology, Dokkyo Medical University Saitama Medical Center, Saitama, Japan.
Background: C-reactive protein (CRP) is a prognostic biomarker for clear cell renal cell carcinoma (ccRCC). However, there may be potential racial heterogeneity in distribution and prognostic impact of CRP level. We investigated potential racial differences in distribution and prognostic impact of preoperative CRP among Asian (AS), African American (AA), and Caucasian (CAUC) patients with non-metastatic ccRCC (nmccRCC).
View Article and Find Full Text PDFSurg Obes Relat Dis
December 2024
Department of Surgery, Indiana University School of Medicine, Indianapolis, Indiana.
JMIR Ment Health
December 2024
Department of Psychiatry, Northwell Health, Zucker Hillside Hospital, Glen Oaks, NY, United States.
Background: Digital health technologies are increasingly being integrated into mental health care. However, the adoption of these technologies can be influenced by patients' digital literacy and attitudes, which may vary based on sociodemographic factors. This variability necessitates a better understanding of patient digital literacy and attitudes to prevent a digital divide, which can worsen existing health care disparities.
View Article and Find Full Text PDFPLoS One
January 2025
Division of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD, United States of America.
Background: Early initiation of treatment for lung cancer has been shown to improve patient survival. The present study investigates disparities in time to treatment initiation of invasive lung cancer within and between Black and White patients in Tennessee.
Methods: A population-based registry data of 42,970 individuals (Black = 4,480 and White = 38,490) diagnosed with invasive lung cancer obtained from the Tennessee Cancer Registry, 2005-2015, was analyzed.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!