Dual Prognostic Classification of Triple-Negative Breast Cancer by DNA Damage Immune Response and Homologous Recombination Deficiency.

PURPOSE: Triple-negative breast cancer (TNBC) is a heterogeneous disease. We previously showed that homologous recombination deficiency (HRD) and the DNA damage immune response (DDIR) signature are prognostic in TNBC. We hypothesized that these biomarkers reflect related but not completely interdependent biological processes, that their combined use would be prognostic, and that simultaneous assessment of the immunologic microenvironment and susceptibility to DNA damaging therapies might be able to identify subgroups with distinct therapeutic vulnerabilities. METHODS: We analyzed the dual DDIR/HRD classification in 341 patients with TNBC treated with adjuvant anthracycline-based chemotherapy on the SWOG S9313 trial and corroborated our findings in The Cancer Genome Atlas breast cancer data set. RESULTS: DDIR/HRD classification is highly prognostic in TNBC and identifies biologically and immunologically distinct subgroups. Immune-enriched DDIR+/HRD+ TNBCs have the most favorable prognosis, and DDIR+/HRD- and DDIR-/HRD+ TNBCs have favorable intermediate prognosis, despite the latter being immune-depleted. DDIR-/HRD- TNBCs have the worst prognosis and represent an internally heterogeneous group of immune-depleted chemoresistant tumors. CONCLUSION: Our findings propose DDIR/HRD classification as a potentially clinically relevant approach to categorize tumors on the basis of therapeutic vulnerabilities.

Identification of triple-negative breast cancer cell lines classified under the same molecular subtype using different molecular characterization techniques: Implications for translational research.

The original algorithm that classified triple-negative breast cancer (TNBC) into six subtypes has recently been revised. The revised algorithm (TNBCtype-IM) classifies TNBC into five subtypes and a modifier based on immunological (IM) signatures. The molecular signature may differ between cancer cells in vitro and their respective tumor xenografts. We identified cell lines with concordant molecular subtypes regardless of classification algorithm or analysis of cells in vitro or in vivo, to establish a panel of clinically relevant molecularly stable TNBC models for translational research. Gene expression data were used to classify TNBC cell lines using the original and the revised algorithms. Tumor xenografts were established from 17 cell lines and subjected to gene expression profiling with the original 2188-gene algorithm TNBCtype and the revised 101-gene algorithm TNBCtype-IM. A total of six cell lines (SUM149PT (BL2), HCC1806 (BL2), SUM149PT (BL2), BT549 (M), MDA-MB-453 (LAR), and HCC2157 (BL1)) maintained their subtype classification between in vitro and tumor xenograft analyses across both algorithms. For TNBC molecular classification-guided translational research, we recommend using these TNBC cell lines with stable molecular subtypes.

Expression of cytokeratins 17 and 5 identifies a group of breast carcinomas with poor clinical outcome.

While several prognostic factors have been identified in breast carcinoma, the clinical outcome remains hard to predict for individual patients. Better predictive markers are needed to help guide difficult treatment decisions. In a previous study of 78 breast carcinoma specimens, we noted an association between poor clinical outcome and the expression of cytokeratin 17 and/or cytokeratin 5 mRNAs. Here we describe the results of immunohistochemistry studies using monoclonal antibodies against these markers to analyze more than 600 paraffin-embedded breast tumors in tissue microarrays. We found that expression of cytokeratin 17 and/or cytokeratin 5/6 in tumor cells was associated with a poor clinical outcome. Moreover, multivariate analysis showed that in node-negative breast carcinoma, expression of these cytokeratins was a prognostic factor independent of tumor size and tumor grade.