miRNA expression in triple negative tumors

Triple negative breast cancer (TNBC) represents a challenging tumor type due to their poor prognosis and limited treatment options. It is well recognize that clinical and molecular heterogeneity of TNBC is driven in part by post-transcriptional regulators such as miRNAs. To stratify TNBCs, we profiled 1050 miRNAs in 132 adjuvant TNBC tumors and 40 tumors from other immunophenotypes using an Affymetrix microarray platform. A NMF clustering analysis allowed us to identify 4 TNBC subtypes featuring unique miRNA expression patterns, disease free and overall survival rates and particular gene ontology enrichments (performed with GSEA algorithm). Our agglomerative approach was cross-validated by using two other clustering algorithms (k-means and consensus clustering). TNBC miRNAs subgroups were also correlated with the Lehmann intrinsic subtypes, finding a significant enrichment of immmnomodulartory and basal 1 subtypes in our high risk miRNA subgroups. 3 cell line models (MDA MB 468, MDA MB 231 and HS578T) were classified according to our miRNA signature, recapitulating two different miRNA subgroups. The TNBC tumors were compared against other phenotypes identifying differentially expressed miRNAs that together with the altered miRNAs within the subgroups allowed us to define interesting miRNAs for further functional analysis. Breast cancer tumors were collected from the archives of the Fundación Mexicana de Fomento para la Prevención Oportuna del Cáncer de Mama, A.C., (FUCAM) after a carefully histopathological review by two training pathologist, according to the following criteria: adjuvant therapy and collection of the surgical sample without any treatment. We obtain triple negative tumors (ER-, PR- and Her2-) and tumors from other immunophenotype (ER+, PR+ or/and Her2+) by microdissection of tumoral cells for RNA extraction and hybridization on Affymetrix miRNA microarrays.