Systemic and CNS-delimited inflammation triggers skeletal muscle catabolism in a manner dependent on glucocorticoid signaling.

Piwi-interacting RNAs (piRNAs), whose role in germline maintenance has been established, are now also being classified as post-transcriptional regulators of gene expression in somatic cells. PIWI proteins, central to piRNA biogenesis, have been identified as genetic and epigenetic regulators of gene expression. piRNAs/PIWIs have emerged as potential biomarkers for cancer but their relevance to breast cancer has not been comprehensively studied. piRNAs and mRNAs were profiled from normal and breast tumor tissues using next generation sequencing and Agilent platforms, respectively. Gene targets for differentially expressed piRNAs were identified from mRNA expression dataset. piRNAs and PIWI genes were independently assessed for their prognostic significance (outcomes: Overall Survival, OS and Recurrence Free Survival, RFS). We discovered eight piRNAs as novel independent prognostic markers and their association with OS was confirmed in an external dataset (The Cancer Genome Atlas). Further, PIWIL3 and PIWIL4 genes showed prognostic relevance. 306 gene targets exhibited reciprocal relationship with piRNA expression. Cancer cell pathways such as apoptosis and cell signaling were the key Gene Ontology terms associated with the regulated gene targets. Overall, we have captured the entire cascade of events in a dysregulated piRNA pathway and have identified novel markers for breast cancer prognostication.

BackgroundPrognostication of Breast Cancer (BC) 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 patients 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 cancer types including BC.ResultsIn our study, we sequenced miRNAs from 104 BC 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 BC 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 Overall Survival (OS) and Recurrence Free Survival (RFS), respectively. In the CO approach, from 147 miRNAs retained after filtering, 11 and 4 miRNAs were significant for OS and RFS, respectively. In both the approaches, the risk scores were significant after adjusting for potential confounders. The miRNAs associated with OS identified in our cohort were validated using an external dataset from The Cancer Genome Atlas (TCGA) project. Targets for the identified miRNAs were enriched for cell proliferation, invasion and migration.ConclusionsThe study identified twelve non-redundant miRNAs associated with OS and/or RFS. These signatures include those that were reported by others in BC or other cancers. Importantly we report for the first time two new candidate miRNAs (miR-574-3p and miR-660-5p) as promising prognostic markers. Independent validation of signatures (for OS) using an external dataset from TCGA further strengthened the study findings.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1899-0) contains supplementary material, which is available to authorized users.

Breast cancer is a heterogeneous disease characterized by diverse molecular signatures and a variable response to therapy. Clinical management of breast cancer is guided by the expression of estrogen and progesterone receptors and HER2 amplification. New prognostic and predictive markers, as well as additional targets for therapy, are needed for more effective management of this disease. Gene expression microarrays were probed with RNAs from 176 primary breast cancer samples and tissue microarrays immunostained with anti-DDX1 antibody, an antibody to DEAD box protein DDX1, a putative RNA-RNA and RNA-DNA unwinding protein normally found in the nucleus. Half of the patient cohort had experienced early relapse despite standard adjuvant therapy, but were otherwise matched for estrogen receptor and HER2 status, stage and duration of follow-up. Here, we identify DDX1 RNA overexpression as an independent prognostic marker for early recurrence in primary breast cancer, with a hazard ratio of 4.31 based on logrank analysis of Kaplan-Meier curves. Elevated levels of DDX1 protein in the cytoplasm also independently correlate with early recurrence with a hazard ratio of 1.90. In conclusion, our data indicate a strong and independent association between poor prognosis and deregulation of the DEAD box protein DDX1. We propose that elevated levels of DDX1 RNA or the presence of DDX1 in the cytoplasm could serve as an effective prognostic biomarker for early recurrence in primary breast cancer.