MicroRNA Expression Profiling of the Porcine Developing Brain

BACKGROUND: MicroRNAs are small, non-coding RNA molecules that regulate gene expression at the post-transcriptional level and play an important role in the control of developmental and physiological processes. In particular, the developing brain contains an impressive diversity of microRNAs. Most microRNA expression profiling studies have been performed in human or rodents and relatively limited knowledge exists in other mammalian species. The domestic pig is considered to be an excellent, alternate, large mammal model for human-related neurological studies, due to its similarity in both brain development and the growth curve when compared to humans. Considering these similarities, studies examining microRNA expression during porcine brain development could potentially be used to predict the expression profile and role of microRNAs in the human brain. METHODOLOGY/PRINCIPAL FINDINGS: MicroRNA expression profiling by use of microRNA microarrays and qPCR was performed on the porcine developing brain. Our results show that microRNA expression is regulated in a developmentally stage-specific, as well as a tissue-specific manner. Numerous developmental stage or tissue-specific microRNAs including, miR-17, miR-18a, miR-29c, miR-106a, miR-135a and b, miR-221 and miR-222 were found by microarray analysis. Expression profiles of selected candidates were confirmed by qPCR. CONCLUSIONS/SIGNIFICANCE: The differential expression of specific microRNAs in fetal versus postnatal samples suggests that they likely play an important role in the regulation of developmental and physiological processes during brain development. The data presented here supports the notion that microRNAs act as post-transcriptional switches which may regulate gene expression when required

High levels of microRNA-21 in the stroma of colorectal cancers predict short disease-free survival in stage II colon cancer patients

Approximately 25% of all patients with stage II colorectal cancer will experience recurrent disease and subsequently die within 5 years. MicroRNA-21 (miR-21) is upregulated in several cancer types and has been associated with survival in colon cancer. In the present study we developed a robust in situ hybridization assay using high-affinity Locked Nucleic Acid (LNA) probes that specifically detect miR-21 in formalin-fixed paraffin embedded (FFPE) tissue samples. The expression of miR-21 was analyzed by in situ hybridization on 130 stage II colon and 67 stage II rectal cancer specimens. The miR-21 signal was revealed as a blue chromogenic reaction, predominantly observed in fibroblast-like cells located in the stromal compartment of the tumors. The expression levels were measured using image analysis. The miR-21 signal was determined as the total blue area (TB), or the area fraction relative to the nuclear density (TBR) obtained using a red nuclear stain. High TBR (and TB) estimates of miR-21 expression correlated significantly with shorter disease-free survival (p = 0.004, HR = 1.28, 95% CI: 1.06–1.55) in the stage II colon cancer patient group, whereas no significant correlation with disease-free survival was observed in the stage II rectal cancer group. In multivariate analysis both TB and TBR estimates were independent of other clinical parameters (age, gender, total leukocyte count, K-RAS mutational status and MSI). We conclude that miR-21 is primarily a stromal microRNA, which when measured by image analysis identifies a subgroup of stage II colon cancer patients with short disease-free survival

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC