Abstract

Tumor-associated stroma is comprised of fibroblasts, tumor-infiltrating lymphocytes (TIL), macrophages, endothelial cells, and other cells that interactively influence tumor progression through inflammation and wound repair. Although gene-expression signatures reflecting wound repair predict breast cancer survival, it is unclear whether combined density of tumor-associated stromal cells, a morphologic proxy for inflammation and wound repair signatures on routine hematoxylin and eosin (H&E)-stained sections, is of prognostic relevance. By applying machine learning to digitized H&E-stained sections for 2,084 breast cancer patients from China (n = 596; 24-55 years), Poland (n = 810; 31-75 years), and the United States (n = 678; 55-78 years), we characterized tumor-associated stromal cellular density (SCD) as the percentage of tumor-stroma that is occupied by nucleated cells. Hazard ratios (HR) and 95% confidence intervals (CI) for associations between SCD and clinical outcomes [recurrence (China) and mortality (Poland and the United States)] were estimated using Cox proportional hazard regression, adjusted for clinical variables. SCD was independently predictive of poor clinical outcomes in hormone receptor-positive (luminal) tumors from China [multivariable HR (95% CI)fourth(Q4) vs. first(Q1) quartile = 1.86 (1.06-3.26); P trend = 0.03], Poland [HR (95% CI)Q4 vs. Q1 = 1.80 (1.12-2.89); P trend = 0.01], and the United States [HR (95% CI)Q4 vs. Q1 = 2.42 (1.33-4.42); P trend = 0.002]. In general, SCD provided more prognostic information than most classic clinicopathologic factors, including grade, size, PR, HER2, IHC4, and TILs, predicting clinical outcomes irrespective of menopausal or lymph nodal status. SCD was not predictive of outcomes in hormone receptor-negative tumors. Our findings support the independent prognostic value of tumor-associated SCD among ethnically diverse luminal breast cancer patients. Assessment of tumor-associated SCD on standard H&E could help refine prognostic assessment and therapeutic decision making in luminal breast cancer.

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