Work

A prognostic gene model with psychological stress-related genes captures immune activation in breast cancer

Year: 2025

Type: article

Abstract: Background Chronic stress and depression play critical roles in modulating breast cancer oncogenesis. Psychological stress-related genes can regulate tumor behavior and serve as prognostic factors. Here, we constructed a signature with psychological stress-related tumor genes to predict breast cancer survival and sensitivity to immunotherapy. Methods 37 genes among the 374 psychological stress-related tumor genes were significantly associated with overall survival in The Cancer Genome Atlas (TCGA) and/or the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). The logistic least absolute shrinkage and selection operator (LASSO) regression was used to select genes to build the gene signature to predict overall survival. Area under the curve (AUC) and calibration curve were used to evaluate the performance of the prediction model. Pathway analysis and immune cell infiltration analysis were used to further understand the differences between tumors with high- and low-signature scores. Results 18 psychological stress-related tumor genes were selected to construct the final signature. The AUCs were 0.764 and 0.646 for predicting 5-year overall survival in METABRIC and TCGA, slightly lower than the 10-year AUCs of 0.772 and 0.703. The Hosmer-Lemeshow goodness-of-fit test p-value of the model was 1, showing a good calibration performance. Low 18-gene signature score was associated with better prognosis, activated immune pathways, immune-active tumor microenvironment (TME) characterized by higher proportions of CD8 + T cells and NK cells, and better response to immunotherapy. Conclusion The 18-gene signature of literature reported psychological stress-related genes establishes a model with consistent performance for predicting clinical outcomes and captures immune activation, which could improve prognostic precision and predict immunotherapy response.

Source: The Breast

DOI: 10.1016/j.breast.2025.104678

Authors: Tian Du, Jiayi Tang, Hanqi Zhang, Qianwen Liu, Yanan Kong

Institutions: Sun Yat-sen University, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China

Language: English

Topic: Breast Cancer Treatment Studies

Subfield: Cancer Research

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,200