4.8 Article

The prognostic significance of human ovarian aging-related signature in breast cancer after surgery: A multicohort study

Journal

FRONTIERS IN IMMUNOLOGY
Volume 14, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2023.1139797

Keywords

ovarian ageing; breast cancer; prognosis; drug sensitivity; immune infiltration

Categories

Ask authors/readers for more resources

This study investigated the prognostic value and biological features of ovarian aging in breast cancer through genetic analysis. An eight-gene signature based on ovarian aging was established and validated, and it accurately predicted clinical outcomes and drug sensitivity of breast cancer patients.
BackgroundRecent studies have shown that ovarian aging is strongly associated with the risk of breast cancer, however, its prognostic impact on breast cancer is not yet fully understood. In this study, we performed a multicohort genetic analysis to explore its prognostic value and biological features in breast cancer. MethodsThe gene expression and clinicopathological data of 3366 patients from the The Cancer Genome Atlas (TCGA) cohort, the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort and the GSE86166 cohort were analyzed. A total of 290 ovarian aging-related genes (OARGs) were included in the establishment of the prognostic model. Furthermore, functional mechanisms analysis, drug sensitivity, and immune cell infiltration were investigated using bioinformatic methods. ResultsAn eight OARG-based signature was established and validated using independent cohorts. Two risk subgroups of patients with distinct survival outcomes were identified by the OARG-based signature. A nomogram with good predictive performance was developed by integrating the OARG risk score with clinicopathological factors. Moreover, the OARG-based signature was correlated with DNA damage repair, immune cell signaling pathways, and immunomodulatory functions. The patients in the low-risk subgroup were found to be sensitive to traditional chemotherapeutic, endocrine, and targeted agents (doxorubicin, tamoxifen, lapatinib, etc.) and some novel targeted drugs (sunitinib, pazopanib, etc.). Moreover, patients in the low-risk subgroup may be more susceptible to immune escape and therefore respond less effectively to immunotherapy. ConclusionsIn this study, we proposed a comprehensive analytical method for breast cancer assessment based on OARG expression patterns, which could precisely predict clinical outcomes and drug sensitivity of breast cancer patients.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available