A novel six-biomarker panel identified from male breast cancer-associated fibroblasts demonstrates prognostic power for prostate tumors.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: BC and prostate cancer to reveal specific protumorigenic mechanisms and identify novel therapeutic targets for both malignancies
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSIONS] We identified a novel gene signature with strong prognostic value in prostate cancer and potential relevance to male BC. This gene signature represents a complementary tool to standard clinical parameters for improving patient stratification and management.
[BACKGROUND] Male breast cancer (BC) is rare, accounting for only approximately 1% of all cases of BC, and poorly characterized.
APA
Talia M, Scordamaglia D, et al. (2025). A novel six-biomarker panel identified from male breast cancer-associated fibroblasts demonstrates prognostic power for prostate tumors.. Journal of translational medicine, 23(1), 1090. https://doi.org/10.1186/s12967-025-07196-6
MLA
Talia M, et al.. "A novel six-biomarker panel identified from male breast cancer-associated fibroblasts demonstrates prognostic power for prostate tumors.." Journal of translational medicine, vol. 23, no. 1, 2025, pp. 1090.
PMID
41088372 ↗
Abstract 한글 요약
[BACKGROUND] Male breast cancer (BC) is rare, accounting for only approximately 1% of all cases of BC, and poorly characterized. In contrast, prostate cancer is the most prevalent cancer in men and serves as a model for understanding male-specific tumor biology. The advent of high-throughput technologies has enabled the development of gene expression signatures for both breast and prostate tumors that could inform prognosis and guide treatment. In this respect, the role of the tumor microenvironment, particularly cancer-associated fibroblasts (CAFs), remains largely underexplored. Here, we sought to identify a CAF-related gene signature in male patients with BC and prostate cancer to reveal specific protumorigenic mechanisms and identify novel therapeutic targets for both malignancies.
[METHODS] RNA sequencing was performed to analyze and compare the transcriptomes of CAFs isolated from female and male BC patients. Differentially expressed genes (DEGs) between female and male breast CAFs were identified and subjected to enrichment analyses. Using a set of candidate upregulated genes in male breast CAFs, K-means clustering of prostate cancer patients was performed using multiple datasets to define a prognostic gene signature. Kaplan‒Meier curves and log-rank tests were conducted to assess differences in patient outcomes and other clinical variables between groups of patients with high or low prognostic gene expression. The clustering results were then validated using decision tree analysis, and boosted calculations were employed to increase the classifier performance.
[RESULTS] Transcriptomic profiling revealed 775 DEGs between female and male breast CAFs. Owing to the limited transcriptomic data from male BC patients, we leveraged large prostate cancer cohorts to investigate the relevance of the genes expressed by male breast CAFs. A six-gene signature (ASPN, COL4A1, COL4A2, COL5A3, COMP and FN1) that could predict patient outcomes in multiple independent cohorts of prostate cancer patients was identified.
[CONCLUSIONS] We identified a novel gene signature with strong prognostic value in prostate cancer and potential relevance to male BC. This gene signature represents a complementary tool to standard clinical parameters for improving patient stratification and management.
[METHODS] RNA sequencing was performed to analyze and compare the transcriptomes of CAFs isolated from female and male BC patients. Differentially expressed genes (DEGs) between female and male breast CAFs were identified and subjected to enrichment analyses. Using a set of candidate upregulated genes in male breast CAFs, K-means clustering of prostate cancer patients was performed using multiple datasets to define a prognostic gene signature. Kaplan‒Meier curves and log-rank tests were conducted to assess differences in patient outcomes and other clinical variables between groups of patients with high or low prognostic gene expression. The clustering results were then validated using decision tree analysis, and boosted calculations were employed to increase the classifier performance.
[RESULTS] Transcriptomic profiling revealed 775 DEGs between female and male breast CAFs. Owing to the limited transcriptomic data from male BC patients, we leveraged large prostate cancer cohorts to investigate the relevance of the genes expressed by male breast CAFs. A six-gene signature (ASPN, COL4A1, COL4A2, COL5A3, COMP and FN1) that could predict patient outcomes in multiple independent cohorts of prostate cancer patients was identified.
[CONCLUSIONS] We identified a novel gene signature with strong prognostic value in prostate cancer and potential relevance to male BC. This gene signature represents a complementary tool to standard clinical parameters for improving patient stratification and management.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
- Humans
- Male
- Prognosis
- Prostatic Neoplasms
- Cancer-Associated Fibroblasts
- Biomarkers
- Tumor
- Gene Expression Regulation
- Neoplastic
- Breast Neoplasms
- Female
- Gene Expression Profiling
- Cluster Analysis
- Transcriptome
- Aged
- Middle Aged
- Cancer-associated fibroblasts (CAFs)
- Gene signature
- K-means
- Male breast cancer
- Prostate cancer
- RNA-sequencing
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