Purpose: Accumulating evidence indicated that triple-negative breast cancer (TNBC) can stimulate stronger immune responses than other subtypes of breast cancer. We hypothesized that integrating immune-related genomic signatures with clinicopathologic factors may yield a predictive accuracy exceeding that of the currently available system. Methods: Ten signatures that reflect specific immunogenic or immune microenvironmental features of TNBC were identified and re-analyzed using bioinformatic methods. Then, clinically annotated TNBC (n = 711) with the corresponding expression profiles, which predicted a patient's probability of disease-free survival (DFS) and overall survival (OS), was pooled to evaluate their prognostic values and establish a clinicopathologic-genomic nomogram. Three and two immune features were, respectively, selected out of 10 immune features to construct nomogram for DFS and OS prediction based on multivariate backward stepwise Cox regression analyses. Results: By integrating the above immune expression signatures with prognostic clinicopathologic features, clinicopathologic-genomic nomograms were cautiously constructed, which showed reasonable prediction accuracies (DFS: HR, 1.79; 95% CI, 1.46-2.18, P < 0.001; AUC, 0.71; OS: HR, 1.96; 95% CI, 1.54-2.49; P < 0.001; AUC, 0.73). The nomogram showed low-risk subgroup had higher immune checkpoint molecules (PD-L1, PD-1, CTLA-4, LAG-3) expression and benefited from radiotherapy (HR, 0.2, 95% CI, 0.05-0.89; P = 0.034) rather than chemotherapy (HR, 1.26, 95% CI, 0.66-2.43; P = 0.485). Conclusions: These findings offer evidence that immune-related genomic data provide independent and complementary prognostic information for TNBC, and the nomogram might be a practical predictive tool to identify TNBC patients who would benefit from chemotherapy, radiotherapy, and upcoming popularity of immunotherapy.
- immune-related genomic signatures
- triple-negative breast
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Cancer Research