Next generation sequencing profiling identifies XXXX and miR-660-5p as potential novel prognostic markers for @entity0 .

@entity1 @entity0 @entity5 @entity48768 @entity1349
BACKGROUND: Prognostication of @entity0 ( @entity0 ) relies largely on traditional clinical factors and biomarkers such as hormone or growth factor receptors. Due to their suboptimal specificities, it is challenging to accurately identify the subset of @entity1 who are likely to undergo recurrence and there remains a major need for markers of higher utility to guide therapeutic decisions. MicroRNAs (miRNAs) are small non-coding RNAs that function as post-transcriptional regulators of gene expression and have shown promise as potential prognostic markers in several @entity5 types including @entity0 . RESULTS: In our study, we sequenced miRNAs from 104 @entity0 samples and 11 apparently healthy normal (reduction mammoplasty) breast tissues. We used Case-control (CC) and Case-only (CO) statistical paradigm to identify prognostic markers. Cox-proportional hazards regression model was employed and risk score analysis was performed to identify miRNA signature independent of potential confounders. Representative miRNAs were validated using qRT-PCR. Gene targets for prognostic miRNAs were identified using in silico predictions and in-house @entity0 transcriptome dataset. Gene ontology terms were identified using DAVID bioinformatics v6.7. A total of 1,423 miRNAs were captured. In the CC approach, 126 miRNAs were retained with predetermined criteria for good read counts, from which 80 miRNAs were differentially expressed. Of these, four and two miRNAs were significant for @entity1349 ( @entity1349 ) and @entity1349 ( @entity1349 ), respectively. In the CO approach, from 147 miRNAs retained after filtering, 11 and 4 miRNAs were significant for @entity1349 and @entity1349 , respectively. In both the approaches, the risk scores were significant after adjusting for potential confounders. The miRNAs associated with @entity1349 identified in our cohort were validated using an external dataset from The @entity5 (TCGA) project. Targets for the identified miRNAs were enriched for cell proliferation, invasion and migration. CONCLUSIONS: The study identified twelve non-redundant miRNAs associated with @entity1349 and/or @entity1349 . These signatures include those that were reported by others in @entity0 or other @entity5 . Importantly we report for the first time two new candidate miRNAs ( @entity48768 and miR-660-5p) as promising prognostic markers. Independent validation of signatures (for @entity1349 ) using an external dataset from TCGA further strengthened the study findings.
