Triple-negative breast cancer (TNBC) accounts for 15% to 20% of breast cancer cases and is characterized by the absence of estrogen, progesterone, and human epidermal growth factor 2 receptors. Though TNBC is a highly heterogenic and aggressive disease, TNBC patients have better response to neoadjuvant therapy compared to other breast cancer subtypes. Nevertheless, patients with residual disease have a very poor prognosis, with higher probability of relapse and lower overall survival in the first years after diagnosis. TNBC has 6 subtypes with distinct molecular signatures with different prognoses and probably different responses to therapy. The precise stratification of TNBC is therefore crucial for the development of potent standardized and targeted therapies. In spite of intensive research into finding new molecular biomarkers and designing personalized therapeutic approaches, BRCA mutational status is the only clinically validated biomarker for personalized therapy in TNBC. Recent studies have reported several promising biomarkers that are currently being validated through clinical trials. The objective of this review was to summarize the clinically relevant genetic markers for TNBC that could serve as diagnostic, prognostic, or predictive or could improve personalized therapeutic strategies.

Neither targeted therapies nor predictors for chemotherapy sensitivity are available for triple-negative breast cancer (TNBC). Our study included 187 patients with TNBC, 164 of whom were treated with anthracycline-based adjuvant chemotherapy. Eleven molecular biomarkers were analyzed. BCL2, epidermal growth factor receptor (EGFR), MYC, TOP2A, and Ki-67 protein expression was evaluated by immunohistochemistry. The status of the EGFR, MYC, and TOP2A genes and chromosomes 7, 8, and 17 was assessed using fluorescence in situ hybridization. High BCL2 expression predicted poor relapse-free survival (RFS) in patients treated with anthracycline-based adjuvant chemotherapy (p = 0.035), poor breast cancer-specific survival (BCSS) (p = 0.048), and a trend to poor overall survival (OS) (p = 0.085). High levels of BCL2 expression predicted poor OS in basal-like (BL) TNBC patients treated with adjuvant anthracycline-based regimens (log-rank p = 0.033, hazard ratio (HR) 3.04, 95 % confidence interval (CI) 1.04-8.91) and a trend to poor RFS (log-rank p = 0.079) and poor BCSS (log-rank p = 0.056). Multivariate analysis showed that BCL2 status, tumor size, and nodal status all had independent predictive significance for RFS (p = 0.005, p = 0.091, p = 0.003, respectively; likelihood ratio test for the whole model, p = 0.003), BCSS (p = 0.012, p = 0.077, p = 0.01, respectively; likelihood ratio test for the whole model, p = 0.016), and OS (p = 0.008, p = 0.004, p = 0.004, respectively; likelihood ratio test for the whole model, p = 0.0006). Similarly, multivariate analysis for BL TNBC showed BCL2, tumor size, and nodal status all had independent predictive significance for RFS (likelihood ratio test for the whole model, p = 0.00125), BCSS (p = 0.00035), and OS (p = 0.00063). High EGFR expression was associated with poor BCSS (p = 0.039) in patients treated with anthracycline-based adjuvant chemotherapy. Patients who underwent anthracycline-based adjuvant chemotherapy and exhibited CMYC amplification had a trend to worse BCSS (p = 0.066). In conclusion, high BCL2 expression is a significant independent predictor of poor outcome in TNBC patients treated with anthracycline-based adjuvant chemotherapy, and this is the first study showing the BCL2 prediction in BL TNBC. BCL2 expression analysis could facilitate decision making on adjuvant treatment in TNBC patients.

Background. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer that is the leading cause of cancer-related mortality worldwide. Several predictive markers have been found in NSCLC patients to date but only a few are currently used for tailored therapy. Methods and Results. PubMed and Web of Science online databases were used to search review and original articles on the most important predictive markers in NSCLC. Conclusion. EGFR activating mutations (exons 18 to 21) and EML4-ALK rearrangement are clinically important markers able to select NSCLC patients which benefit from EGFR or ALK tyrosine kinase inhibitors (gefitinib, erlotinib, crizotinib). Other markers, such as KRAS mutation, EGFR T790M mutation and C-MET amplification, are responsible for resistance to these inhibitors. Overcoming of this resistance as well as discovery of new potential markers and inhibitors is the main goal of ongoing research and clinical trials in NSCLC.