Clin Breast Cancer. 2024 Feb 21:S1526-8209(24)00053-3. doi: 10.1016/j.clbc.2024.02.015. Online ahead of print.
ABSTRACT
INTRODUCTION: Fibrillar collagens accumulate in the breast cancer stroma and appear as poorly defined spiculated masses in mammography imaging. The prognostic value of tissue type I collagen remains elusive in treatment-naïve and chemotherapy-treated breast cancer patients. Here, type I collagen mRNA and protein expression were analysed in 2 large independent breast cancer cohorts. Levels were related to clinicopathological parameters, prognostic biomarkers, and outcome.
METHOD: COL1A1 mRNA expression was analysed in 2509 patients with breast cancer obtained from the cBioPortal database. Type I collagen protein expression was studied by immunohistochemistry in 1395 women diagnosed with early invasive breast cancer.
RESULTS: Low COL1A1 mRNA and protein levels correlated with poor prognosis features, such as hormone receptor negativity, high histological grade, triple-negative subtype, node positivity, and tumour size. In unadjusted analysis, high stromal type I collagen protein expression was associated with improved overall survival (OS) (HR = 0.78, 95% CI = 0.61-0.99, p = .043) and trended towards improved breast cancer-specific survival (BCSS) (HR = 0.65, 95% CI = 0.42-1.01, P = 0.053), although these findings were lost after adjustment for other clinical variables. In unadjusted analysis, high expression of type I collagen was associated with better OS (HR = 0.70, 95% CI = 0.55-0.90, P = .006) and BCSS (HR = 0.55, 95% CI = 0.34-0.88, P = .014) among patients not receiving chemotherapy. Strikingly, the opposite was observed among patients receiving chemotherapy. There, high expression of type I collagen was instead associated with worse OS (HR = 1.83, 95% CI = 0.65-5.14, P = .25) and BCSS (HR = 1.72, 95% CI = 0.54-5.50, P = .357).
CONCLUSION: Low stromal type I collagen mRNA and protein expression are associated with unfavourable tumour characteristics in breast cancer. Stromal type I collagen might predict chemotherapy response.
PMID:38485557 | DOI:10.1016/j.clbc.2024.02.015
