BRCA1/2 somatic mutation detection in formalin-fixed paraffin embedded tissue by next-generation sequencing in Korean ovarian cancer patients.

INTRODUCTION: The detection of BRCA1/2 mutations is important because PARP1 inhibitors are approved for germline and/or somatic BRCA-mutated advanced ovarian cancer. Next-generation sequencing (NGS) is increasingly used in clinical practice for BRCA1/2 mutations. The purpose of this study was to consider several conditions of NGS BRCA1/2 assay applicable to clinical laboratory tests, in particular for using formalin fixed paraffin embedded (FFPE) ovarian tissues. MATERIALS AND METHODS: We selected 64 ovarian cancer patients and performed Oncomine™ BRCA assay using FFPE tissue. Effect of FFPE sample quality was analyzed by NGS quality parameters including deamination metric. Somatic variants were selected by removing germline variants of peripheral blood and interpreted as pathogenic, variants of unknown significance, and false positive. RESULTS: We found a positive relationship between the number of variants over the deamination metric and FFPE age (P < 0.001) with a cutoff values of approximately 0.7 and 60 months, respectively. When comparing NGS results with Sanger sequencing, NGS misreported 3 of 15 variants using default parameters which were corrected after changing parameters. We detected somatic variants in eight patients and classified them into pathogenic (n = 3), VUS (n = 3) and false positive (n = 2). CONCLUSIONS: This study is important for improving BRCA1/2 mutation detection capabilities of NGS analytical pipelines and strategy to overcome their limitations using FFPE tissue in ovarian cancer patients.

Profiling molecular regulators of recurrence in chemorefractory triple-negative breast cancers.

BACKGROUND: Approximately two thirds of patients with localized triple-negative breast cancer (TNBC) harbor residual disease (RD) after neoadjuvant chemotherapy (NAC) and have a high risk-of-recurrence. Targeted therapeutic development for TNBC is of primary significance as no targeted therapies are clinically indicated for this aggressive subset. In view of this, we conducted a comprehensive molecular analysis and correlated molecular features of chemorefractory RD tumors with recurrence for the purpose of guiding downstream therapeutic development. METHODS: We assembled DNA and RNA sequencing data from RD tumors as well as pre-operative biopsies, lymphocytic infiltrate, and survival data as part of a molecular correlative to a phase II post-neoadjuvant clinical trial. Matched somatic mutation, gene expression, and lymphocytic infiltrate were assessed before and after chemotherapy to understand how tumors evolve during chemotherapy. Kaplan-Meier survival analyses were conducted categorizing cancers with TP53 mutations by the degree of loss as well as by the copy number of a locus of 18q corresponding to the SMAD2, SMAD4, and SMAD7 genes. RESULTS: Analysis of matched somatic genomes pre-/post-NAC revealed chaotic acquisition of copy gains and losses including amplification of prominent oncogenes. In contrast, significant gains in deleterious point mutations and insertion/deletions were not observed. No trends between clonal evolution and recurrence were identified. Gene expression data from paired biopsies revealed enrichment of actionable regulators of stem cell-like behavior and depletion of immune signaling, which was corroborated by total lymphocytic infiltrate, but was not associated with recurrence. Novel characterization of TP53 mutation revealed prognostically relevant subgroups, which were linked to MYC-driven transcriptional amplification. Finally, somatic gains in 18q were associated with poor prognosis, likely driven by putative upregulation of TGFß signaling through the signal transducer SMAD2. CONCLUSIONS: We conclude TNBCs are dynamic during chemotherapy, demonstrating complex plasticity in subclonal diversity, stem-like qualities, and immune depletion, but somatic alterations of TP53/MYC and TGFß signaling in RD samples are prominent drivers of recurrence, representing high-yield targets for additional interrogation.

Next-generation sequencing of circulating tumor DNA to predict recurrence in triple-negative breast cancer patients with residual disease after neoadjuvant chemotherapy.

Next-generation sequencing to detect circulating tumor DNA is a minimally invasive method for tumor genotyping and monitoring therapeutic response. The majority of studies have focused on detecting circulating tumor DNA from patients with metastatic disease. Herein, we tested whether circulating tumor DNA could be used as a biomarker to predict relapse in triple-negative breast cancer patients with residual disease after neoadjuvant chemotherapy. In this study, we analyzed samples from 38 early-stage triple-negative breast cancer patients with matched tumor, blood, and plasma. Extracted DNA underwent library preparation and amplification using the Oncomine Research Panel consisting of 134 cancer genes, followed by high-coverage sequencing and bioinformatics. We detected high-quality somatic mutations from primary tumors in 33 of 38 patients. TP53 mutations were the most prevalent (82%) followed by PIK3CA (16%). Of the 33 patients who had a mutation identified in their primary tumor, we were able to detect circulating tumor DNA mutations in the plasma of four patients (three TP53 mutations, one AKT1 mutation, one CDKN2A mutation). All four patients had recurrence of their disease (100% specificity), but sensitivity was limited to detecting only 4 of 13 patients who clinically relapsed (31% sensitivity). Notably, all four patients had a rapid recurrence (0.3, 4.0, 5.3, and 8.9 months). Patients with detectable circulating tumor DNA had an inferior disease free survival (p < 0.0001; median disease-free survival: 4.6 mos. vs. not reached; hazard ratio = 12.6, 95% confidence interval: 3.06-52.2). Our study shows that next-generation circulating tumor DNA sequencing of triple-negative breast cancer patients with residual disease after neoadjuvant chemotherapy can predict recurrence with high specificity, but moderate sensitivity. For those patients where circulating tumor DNA is detected, recurrence is rapid.

Genetic association between the PRKCH gene encoding protein kinase Ceta isozyme and rheumatoid arthritis in the Japanese population.

OBJECTIVE: Analyses of families with rheumatoid arthritis (RA) have suggested the presence of a putative susceptibility locus on chromosome 14q21-23. This large population-based genetic association study was undertaken to examine this region. METHODS: A 2-stage case-control association study of 950 unrelated Japanese patients with RA and 950 healthy controls was performed using >400 gene-based common single-nucleotide polymorphisms (SNPs). RESULTS: Multiple SNPs in the PRKCH gene encoding the eta isozyme of protein kinase C (PKCeta) showed significant single-locus disease associations, the most significant being SNP c.427+8134C>T (odds ratio 0.72, 95% confidence interval 0.62-0.83, P = 5.9 x 10(-5)). Each RA-associated SNP was consistently mapped to 3 distinct regions of strong linkage disequilibrium (i.e., linkage disequilibrium or haplotype blocks) in the PRKCH gene locus, suggesting that multiple causal variants influence disease susceptibility. Significant SNPs included a novel common missense polymorphism of the PRKCH gene, V374I (rs2230500), which lies within the ATP-binding site that is highly conserved among PKC superfamily members. In circulating lymphocytes, PRKCH messenger RNA was expressed at higher levels in resting T cells (CD4(+) or CD8(+)) than in B cells (CD19(+)) or monocytes (CD14(+)) and was significantly down-regulated through immune responses. CONCLUSION: Our results provide evidence of the involvement of PRKCH as a susceptibility gene for RA in the Japanese population. Dysregulation of PKCeta signal transduction pathway(s) may confer increased risk of RA through aberrant T cell-mediated autoimmune responses.

A tool for selecting SNPs for association studies based on observed linkage disequilibrium patterns.

The design of genetic association studies using single-nucleotide polymorphisms (SNPs) requires the selection of subsets of the variants providing high statistical power at a reasonable cost. SNPs must be selected to maximize the probability that a causative mutation is in linkage disequilibrium (LD) with at least one marker genotyped in the study. The HapMap project performed a genome-wide survey of genetic variation with about a million SNPs typed in four populations, providing a rich resource to inform the design of association studies. A number of strategies have been proposed for the selection of SNPs based on observed LD, including construction of metric LD maps and the selection of haplotype tagging SNPs. Power calculations are important at the study design stage to ensure successful results. Integrating these methods and annotations can be challenging: the algorithms required to implement these methods are complex to deploy, and all the necessary data and annotations are deposited in disparate databases. Here, we present the SNPbrowser Software, a freely available tool to assist in the LD-based selection of markers for association studies. This stand-alone application provides fast query capabilities and swift visualization of SNPs, gene annotations, power, haplotype blocks, and LD map coordinates. Wizards implement several common SNP selection workflows including the selection of optimal subsets of SNPs (e.g. tagging SNPs). Selected SNPs are screened for their conversion potential to either TaqMan SNP Genotyping Assays or the SNPlex Genotyping System, two commercially available genotyping platforms, expediting the set-up of genetic studies with an increased probability of success.

Power and sample size calculations for genetic case/control studies using gene-centric SNP maps: application to human chromosomes 6, 21, and 22 in three populations.

Power and sample size calculations are critical parts of any research design for genetic association. We present a method that utilizes haplotype frequency information and average marker-marker linkage disequilibrium on SNPs typed in and around all genes on a chromosome. The test statistic used is the classic likelihood ratio test applied to haplotypes in case/control populations. Haplotype frequencies are computed through specification of genetic model parameters. Power is determined by computation of the test's non-centrality parameter. Power per gene is computed as a weighted average of the power assuming each haplotype is associated with the trait. We apply our method to genotype data from dense SNP maps across three entire chromosomes (6, 21, and 22) for three different human populations (African-American, Caucasian, Chinese), three different models of disease (additive, dominant, and multiplicative) and two trait allele frequencies (rare, common). We perform a regression analysis using these factors, average marker-marker disequilibrium, and the haplotype diversity across the gene region to determine which factors most significantly affect average power for a gene in our data. Also, as a 'proof of principle' calculation, we perform power and sample size calculations for all genes within 100 kb of the PSORS1 locus (chromosome 6) for a previously published association study of psoriasis. Results of our regression analysis indicate that four highly significant factors that determine average power to detect association are: disease model, average marker-marker disequilibrium, haplotype diversity, and the trait allele frequency. These findings may have important implications for the design of well-powered candidate gene association studies. Our power and sample size calculations for the PSORS1 gene appear consistent with published findings, namely that there is substantial power (>0.99) for most genes within 100 kb of the PSORS1 locus at the 0.01 significance level.

Association between single-nucleotide polymorphisms in the SEC8L1 gene, which encodes a subunit of the exocyst complex, and rheumatoid arthritis in a Japanese population.

OBJECTIVE: To identify rheumatoid arthritis (RA) susceptibility genes in a Japanese population by conducting a large-scale case-control association analysis and linkage disequilibrium (LD) mapping on chromosome 7q31-34, a candidate susceptibility locus identified in a preliminary genome-wide scan in 53 Japanese families, using single-nucleotide polymorphisms (SNPs). METHODS: We prepared 728 dense, evenly spaced SNPs with a minor allele frequency >0.15 in each gene locus on chromosome 7q31-34. Using these SNPs, a 2-stage case-control analysis was performed on 760 RA patients (157 men and 603 women) and 806 non-RA controls (189 men and 617 women). Haplotypes and LD mapping results were assessed based on SNP genotypes in 380 controls. RESULTS: Forty-eight SNPs showed allele associations (P < 0.05) in the first set of DNA samples (380 RA cases and 380 non-RA controls; first-stage analysis). For 4 of the SNPs in the SEC8L1 gene, the association was replicated (P < 0.05) in the second, independent set of DNA samples (an additional 380 RA cases and 380 non-RA controls; second-stage analysis). When data from the 2 groups were combined, the most significant allele association was observed with SNP 441, an intronic SNP of the SEC8L1 gene (P = 0.000059). The SEC8L1 SNPs with significant allele associations were all located in a single conserved LD block (block 4). Haplotype analysis revealed the disease-risk (P = 0.0015) and disease-protective (P = 0.0000062) haplotypes. Resequencing of coding exons within block 4 did not identify any nonsynonymous SNPs. Real-time quantitative polymerase chain reaction revealed that SEC8L1 was expressed ubiquitously in human tissues, including fibroblast-like synoviocytes from RA patients. CONCLUSION: Our locus-wide association and LD analyses identified intronic SNPs and haplotypes in the SEC8L1 gene that are strongly associated with RA. We propose that SEC8L1, which encodes a component of the exocyst complex, is a candidate susceptibility gene for RA in the Japanese population.

The linkage disequilibrium maps of three human chromosomes across four populations reflect their demographic history and a common underlying recombination pattern.

The extent and patterns of linkage disequilibrium (LD) determine the feasibility of association studies to map genes that underlie complex traits. Here we present a comparison of the patterns of LD across four major human populations (African-American, Caucasian, Chinese, and Japanese) with a high-resolution single-nucleotide polymorphism (SNP) map covering almost the entire length of chromosomes 6, 21, and 22. We constructed metric LD maps formulated such that the units measure the extent of useful LD for association mapping. LD reaches almost twice as far in chromosome 6 as in chromosomes 21 or 22, in agreement with their differences in recombination rates. By all measures used, out-of-Africa populations showed over a third more LD than African-Americans, highlighting the role of the population's demography in shaping the patterns of LD. Despite those differences, the long-range contour of the LD maps is remarkably similar across the four populations, presumably reflecting common localization of recombination hot spots. Our results have practical implications for the rational design and selection of SNPs for disease association studies.

A high-density admixture map for disease gene discovery in african americans.

Admixture mapping (also known as "mapping by admixture linkage disequilibrium," or MALD) provides a way of localizing genes that cause disease, in admixed ethnic groups such as African Americans, with approximately 100 times fewer markers than are required for whole-genome haplotype scans. However, it has not been possible to perform powerful scans with admixture mapping because the method requires a dense map of validated markers known to have large frequency differences between Europeans and Africans. To create such a map, we screened through databases containing approximately 450000 single-nucleotide polymorphisms (SNPs) for which frequencies had been estimated in African and European population samples. We experimentally confirmed the frequencies of the most promising SNPs in a multiethnic panel of unrelated samples and identified 3011 as a MALD map (1.2 cM average spacing). We estimate that this map is approximately 70% informative in differentiating African versus European origins of chromosomal segments. This map provides a practical and powerful tool, which is freely available without restriction, for screening for disease genes in African American patient cohorts. The map is especially appropriate for those diseases that differ in incidence between the parental African and European populations.

Genome-wide analysis of the odorant-binding protein gene family in Drosophila melanogaster.

Olfaction is of considerable importance to many insects in behaviors critical for survival and reproduction, including location of food sources, selection of mates, recognition of colony con-specifics, and determination of oviposition sites. An ubiquitous, but poorly understood, component of the insect's olfactory system is a group of odorant-binding proteins (OBPs) that are present at high concentrations in the aqueous lymph surrounding the dendrites of olfactory receptor neurons. OBPs are believed to shuttle odorants from the environment to the underlying odorant receptors, for which they could potentially serve as odorant presenters. Here we show that the Drosophila genome carries 51 potential OBP genes, a number comparable to that of its odorant-receptor genes. We find that the majority (73%) of these OBP-like genes occur in clusters of as many as nine genes, in contrast to what has been observed for the Drosophila odorant-receptor genes. Two of the presumptive OBP gene clusters each carries an odorant-receptor gene. We also report an intriguing subfamily of 12 putative OBPs that share a unique C-terminal structure with three conserved cysteines and a conserved proline. Members of this subfamily have not previously been described for any insect. We have performed phylogenetic analyses of the OBP-related proteins in Drosophila as well as other insects, and we discuss the duplication and divergence of the genes for this large family. [The sequence data from this study have been submitted to FlyBase. Annotations for these sequences are available as supplementary material at http://www.genome.org.]