Recurrent mutations of BRCA1, BRCA2 and PALB2 in the population of breast and ovarian cancer patients in Southern Poland

Background Mutations in the BRCA1, BRCA2 and PALB2 genes are well-established risk factors for the development of breast and/or ovarian cancer. The frequency and spectrum of mutations in these genes has not yet been examined in the population of Southern Poland. Methods We examined the entire coding sequences of the BRCA1 and BRCA2 genes and genotyped a recurrent mutation of the PALB2 gene (c.509_510delGA) in 121 women with familial and/or early-onset breast or ovarian cancer from Southern Poland. Results A BRCA1 mutation was identified in 11 of 121 patients (9.1 %) and a BRCA2 mutation was identified in 10 of 121 patients (8.3 %). Two founder mutations of BRCA1 accounted for 91 % of all BRCA1 mutation carriers (c.5266dupC was identified in six patients and c.181 T > G was identified in four patients). Three of the seven different BRCA2 mutations were detected in two patients each (c.9371A > T, c.9403delC and c.1310_1313delAAGA). Three mutations have not been previously reported in the Polish population (BRCA1 c.3531delT, BRCA2 c.1310_1313delAAGA and BRCA2 c.9027delT). The recurrent PALB2 mutation c.509_510delGA was identified in two patients (1.7 %). Conclusions The standard panel of BRCA1 founder mutations is sufficiently sensitive for the identification of BRCA1 mutation carriers in Southern Poland. The BRCA2 mutations c.9371A > T and c.9403delC as well as the PALB2 mutation c.509_510delGA should be included in the testing panel for this population

Targeted RNAseq assay incorporating unique molecular identifiers for improved quantification of gene expression signatures and transcribed mutation fraction in fixed tumor samples.

BACKGROUND: Our objective was to assess whether modifications to a customized targeted RNA sequencing (RNAseq) assay to include unique molecular identifiers (UMIs) that collapse read counts to their source mRNA counts would improve quantification of transcripts from formalin-fixed paraffin-embedded (FFPE) tumor tissue samples. The assay (SET4) includes signatures that measure hormone receptor and PI3-kinase related transcriptional activity (SET METHODS: Modifications included steps to introduce eight nucleotides-long UMIs during reverse transcription (RT) in bulk solution, followed by polymerase chain reaction (PCR) of labeled cDNA in droplets, with optimization of the polymerase enzyme and reaction conditions. We used Lin\u27s concordance correlation coefficient (CCC) to measure concordance, including precision (Rho) and accuracy (Bias), and nonparametric tests (Wilcoxon, Levene\u27s) to compare the modified (NEW) SET4 assay to the original (OLD) SET4 assay and to whole transcriptome RNAseq using RNA from matched fresh frozen (FF) and FFPE samples from 12 primary breast cancers. RESULTS: The modified (NEW) SET4 assay measured single transcripts (p\u3c 0.001) and SET CONCLUSIONS: Modifications to the targeted RNAseq protocol for SET4 assay significantly increased the precision of UMI-based and reads-based measurements of individual transcripts, multi-gene signatures, and mutant transcript fraction, particularly with FFPE samples

A feature selection method for classification within functional genomics experiments based on the proportional overlapping score

Background: Microarray technology, as well as other functional genomics experiments, allow simultaneous measurements of thousands of genes within each sample. Both the prediction accuracy and interpretability of a classifier could be enhanced by performing the classification based only on selected discriminative genes. We propose a statistical method for selecting genes based on overlapping analysis of expression data across classes. This method results in a novel measure, called proportional overlapping score (POS), of a feature's relevance to a classification task.Results: We apply POS, along-with four widely used gene selection methods, to several benchmark gene expression datasets. The experimental results of classification error rates computed using the Random Forest, k Nearest Neighbor and Support Vector Machine classifiers show that POS achieves a better performance.Conclusions: A novel gene selection method, POS, is proposed. POS analyzes the expressions overlap across classes taking into account the proportions of overlapping samples. It robustly defines a mask for each gene that allows it to minimize the effect of expression outliers. The constructed masks along-with a novel gene score are exploited to produce the selected subset of genes

Re-Arrest Among Juvenile Justice-Involved Youth: An Examination Of The Static And Dynamic Risk Factors

The purpose of this study is to investigate the static and dynamic risk factors for re-arrest among detained youth by examining gender, race/ethnicity, age, special education and mental health variables (i.e., anger/irritability, depression/anxiety, somatic complaints, suicide ideation, thought disturbances, and traumatic experiences). The demographic profiles of detained youth with one admit were also compared with those with multiple admits to the juvenile detention center. With regards to static risk factors, older, white, and special education were significantly at risk of re-arrest. Concerning dynamic risk factors, only anger/irritability predicted re-arrest. Practice implications are also discussed