Background: The study assessed the epigenetic regulation and the role of microRNA (miR) expression in locally advanced triple negative breast cancers (TNBC) and comparison with the clinico-pathological variables and survival.
Methods: Fifty patients of locally advanced TNBC during the period 2011-2013 were included. Expression level of test microRNA (miR-182 and miR-18a) was determined using Taqman quantitative Real time polymerase chain reaction (qRT-PCR) from formalin fixed paraffin embedded biopsy blocks. Clinical and demographic information and survival data was retrieved from the Hospital medical records.
Results: An improved clinical complete response (cCR) was observed in patients with age ≥ 45 years (80%), premenopausal status (70%), tumor size < 6 cms (80%), nodal status N0-N1 (95%) and grade II-III tumor (80%). A statistically significant correlation was observed on comparison of cCR with menopausal status (p-value 0.020), T category (p-value 0.018) and the clinical nodal status (p-value 0.003). pCR also correlated with clinical nodal status (p-value 0.008). Epigenetically, miR-18a under expression (< 8.84) was most commonly associated with tumor size < 6 cms (76.7%), clinical nodal status N0-N1 (90%), cCR (60%) and pCR (53.3%). A similar trend was observed with miR-182. Statistical significance was observed with T category (p-values 0.003 and 0.004), clinical nodal status (p-values 0.001 and 0.001), clinical response (p-values 0.002 and 0.002) and pathological response (p-values 0.007 and 0.006) with respect to miR-18a and miR-182, respectively. Also, the menopausal status significantly correlated with the miR-182 expression (p-value 0.009). miR-182 overexpression (≥ 6.32) was not observed in any of the postmenopausal patients. A univariate cox proportional hazard regression model also showed statistical interactions (p-values <0.004).
Conclusion: miR-182 and miR-18a overexpression correlates with worse clinical and pathological tumor characteristics in locally advanced TNBC and hence could be used to predict the outcomes and prognosis in these patients.