TY - JOUR
T1 - Integrative Analysis of DNA Methylation and microRNA Reveals GNPDA1 and SLC25A16 Related to Biopsychosocial Factors Among Taiwanese Women with a Family History of Breast Cancer
AU - Khairi, Sabiah
AU - Wang, Chih Yang
AU - Anuraga, Gangga
AU - Prayugo, Fidelia Berenice
AU - Ansar, Muhamad
AU - Lesmana, Mohammad Hendra Setia
AU - Irham, Lalu Muhammad
AU - Shen, Chen Yang
AU - Chung, Min Huey
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/4
Y1 - 2025/4
N2 - Biopsychosocial factors, including family history, influence the development of breast cancer. Malignancies in women with a family history of breast cancer may be detectable based on DNA methylation and microRNA. Objectives: The present study extended an integrative analysis of DNA methylation and microRNA to identify genes associated with biopsychosocial factors. Methods: We identified 3060 healthy women from the Taiwan Biobank and included 32 blood plasma samples for analysis of biopsychosocial factors and epigenetic changes. GEO databases and bioinformatics approaches were used for the identification and validation of potential genes. Results: Our integrative analysis revealed GNPDA1 and SLC25A16 as potential genes. Age, a family history of cancer, and alcohol consumption were associated with GNPDA1 and SLC25A16 based on the current data set and the GEO data set. GNPDA1 and SLC25A16 exhibited significant expression in breast cancer tissues based on UALCAN analysis, where they were overexpressed and underexpressed, respectively. Through a MethSurv analysis, GNPDA1 hypomethylation and SLC25A16 hypermethylation were associated with poor prognoses in terms of overall survival in breast cancer. Moreover, through a MetaCore functional enrichment analysis, GNPDA1 and SLC25A16 were associated with the BRCA1, BRCA2, and pro-oncogenic actions of the androgen receptor in breast cancer. Further, GNPDA1 and SLC25A16 were enriched in known targets of approved cancer drugs as potential genes associated with breast cancer. Conclusions: These two genes might serve as biomarkers for the early detection of breast cancer, especially for women with a family history of breast cancer.
AB - Biopsychosocial factors, including family history, influence the development of breast cancer. Malignancies in women with a family history of breast cancer may be detectable based on DNA methylation and microRNA. Objectives: The present study extended an integrative analysis of DNA methylation and microRNA to identify genes associated with biopsychosocial factors. Methods: We identified 3060 healthy women from the Taiwan Biobank and included 32 blood plasma samples for analysis of biopsychosocial factors and epigenetic changes. GEO databases and bioinformatics approaches were used for the identification and validation of potential genes. Results: Our integrative analysis revealed GNPDA1 and SLC25A16 as potential genes. Age, a family history of cancer, and alcohol consumption were associated with GNPDA1 and SLC25A16 based on the current data set and the GEO data set. GNPDA1 and SLC25A16 exhibited significant expression in breast cancer tissues based on UALCAN analysis, where they were overexpressed and underexpressed, respectively. Through a MethSurv analysis, GNPDA1 hypomethylation and SLC25A16 hypermethylation were associated with poor prognoses in terms of overall survival in breast cancer. Moreover, through a MetaCore functional enrichment analysis, GNPDA1 and SLC25A16 were associated with the BRCA1, BRCA2, and pro-oncogenic actions of the androgen receptor in breast cancer. Further, GNPDA1 and SLC25A16 were enriched in known targets of approved cancer drugs as potential genes associated with breast cancer. Conclusions: These two genes might serve as biomarkers for the early detection of breast cancer, especially for women with a family history of breast cancer.
KW - biopsychosocial factors
KW - DNA methylation
KW - family history of breast cancer
KW - integrative analysis
KW - microRNA
KW - biopsychosocial factors
KW - DNA methylation
KW - family history of breast cancer
KW - integrative analysis
KW - microRNA
UR - https://www.scopus.com/pages/publications/105003495814
UR - https://www.scopus.com/pages/publications/105003495814#tab=citedBy
U2 - 10.3390/jpm15040134
DO - 10.3390/jpm15040134
M3 - Article
AN - SCOPUS:105003495814
SN - 2075-4426
VL - 15
JO - Journal of Personalized Medicine
JF - Journal of Personalized Medicine
IS - 4
M1 - 134
ER -