Background Extracellular microRNAs (miRNAs) embedded in circulating exosomes may serves as prognostic biomarkers in cancer. Objective To identify and evaluate plasma exosomal miRNAs for prognosis in castration-resistant prostate cancer (CRPC). Design, setting, and participants RNA sequencing was performed to identify candidate exosomal miRNAs associated with overall survival in a screening cohort of 23 CRPC patients. Candidate miRNAs were further evaluated for prognosis using quantitative real-time polymerase chain reaction in a follow-up cohort of 100 CRPC patients. Outcome measurements and statistical analysis Cox regression and Kaplan-Meier survival analyses were used to evaluate survival association using candidate miRNAs along with clinical prognostic factors. Results and limitations RNA sequencing in screening cohort generated approximately 6.80 million mappable reads per patient. Of those with normalized read counts ≥5, 43% were mapped to miRNAs for a total of 375 known and 57 novel miRNAs. Cox regression analysis identified an association of miR-1290, -1246, and -375 with overall survival (false discover rate <0.05). Of those, higher levels of miR-1290 and -375 were significantly associated with poor overall survival (p < 0.004) in the follow-up cohort. Incorporation of miR-1290/-375 into putative clinical prognostic factors-based models in CRPC stage significantly improved predictive performance with a time-dependent area under the curve increase from 0.66 to 0.73 (p = 6.57 × 10−6). Conclusions Plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients. Prospective validation is needed for further development of these candidate miRNAs. Patient summary In this study, we evaluated whether small RNAs circulating in blood could be used to predict clinical outcomes in late-stage prostate cancer patients. We identified two blood-based small RNAs whose levels showed significant association with survival. Our results warrant further investigation because the noninvasive blood-based test has great potential in the management of late-stage prostate cancer.

BACKGROUND-Primary biliary cirrhosis is a chronic granulomatous cholangitis, characteristically associated with antimitochondrial antibodies. Twin and family aggregation data suggest that there is a significant genetic predisposition to primary biliary cirrhosis, but the susceptibility loci are unknown.

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A genome-wide association screen for primary biliary cirrhosis risk alleles was performed in an Italian cohort. The results from the Italian cohort replicated IL12A and IL12RB associations, and a combined meta-analysis using a Canadian dataset identified newly associated loci at SPIB (P = 7.9 × 10–11, odds ratio (OR) = 1.46), IRF5-TNPO3 (P = 2.8 × 10–10, OR = 1.63) and 17q12-21 (P = 1.7 × 10–10, OR = 1.38).

BackgroundLung cancer is the leading cause of cancer-related death in the United States. Nearly 50% of patients with stages I and II non-small cell lung cancer (NSCLC) will die from recurrent disease despite surgical resection. No reliable clinical or molecular predictors are currently available for identifying those at high risk for developing recurrent disease. As a consequence, it is not possible to select those high-risk patients for more aggressive therapies and assign less aggressive treatments to patients at low risk for recurrence.Methods and FindingsIn this study, we applied a meta-analysis of datasets from seven different microarray studies on NSCLC for differentially expressed genes related to survival time (under 2 y and over 5 y). A consensus set of 4,905 genes from these studies was selected, and systematic bias adjustment in the datasets was performed by distance-weighted discrimination (DWD). We identified a gene expression signature consisting of 64 genes that is highly predictive of which stage I lung cancer patients may benefit from more aggressive therapy. Kaplan-Meier analysis of the overall survival of stage I NSCLC patients with the 64-gene expression signature demonstrated that the high- and low-risk groups are significantly different in their overall survival. Of the 64 genes, 11 are related to cancer metastasis (APC, CDH8, IL8RB, LY6D, PCDHGA12, DSP, NID, ENPP2, CCR2, CASP8, and CASP10) and eight are involved in apoptosis (CASP8, CASP10, PIK3R1, BCL2, SON, INHA, PSEN1, and BIK).ConclusionsOur results indicate that gene expression signatures from several datasets can be reconciled. The resulting signature is useful in predicting survival of stage I NSCLC and might be useful in informing treatment decisions.