Frequent PIK3CA Mutations in Colorectal and Endometrial Tumors With 2 or More Somatic Mutations in Mismatch Repair Genes.

BACKGROUND & AIMS: Some colorectal and endometrial tumors with microsatellite instability not attributable to MLH1 hypermethylation or germline mutations contain 2 or more somatic mutations in genes encoding mismatch repair (MMR) proteins. We sought to define the molecular phenotype of this newly recognized tumor subtype. METHODS: From 2 prospective studies of the efficacy of screening for Lynch syndrome, we identified patients with colorectal and endometrial tumors who had 2 or more somatic (but not germline) mutations in genes encoding MMR proteins (double somatic). We determined the frequencies of tumor mutations in PIK3CA, BRAF, KRAS, NRAS, and PTEN by targeted next-generation sequencing and used logistic-regression models to compare them with those from patients with Lynch syndrome, MLH1-hypermethylated, or microsatellite-stable tumors. We validated our findings using independent data sets from The Cancer Genome Atlas. RESULTS: Among colorectal cancer cases, we found that 14 of 21 (67%) patients with double somatic tumors also had PIK3CA mutations, compared with 4 of 18 (22%) tumors from patients with Lynch syndrome, 2 of 10 (20%) tumors with MLH1 hypermethylation, and 12 of 78 (15%) tumors with microsatellite stability (P < .0001 for patients with double somatic tumors vs other subgroups). Mutations in PIK3CA were detected in all 13 patients with double somatic endometrial cancers (P = .04 compared with other subgroups). We did not detect BRAF mutations in patients with double somatic colorectal tumors or Lynch syndrome. We found highly similar results in a validation cohort from The Cancer Genome Atlas (113 patients with colorectal tumors, 178 endometrial tumors); 100% of double somatic cases had a somatic mutation in PIK3CA (P < .0001 compared with other subgroups). CONCLUSIONS: Most patients with colorectal or endometrial tumors with 2 or more somatic (but not germline) mutations in MMR proteins also have mutations in PIK3CA; mutations in PIK3CA are detected at substantially higher frequencies in these double somatic tumors than in other microsatellite-instability subgroups. PIK3CA mutation status might be used to identify a specific group of colorectal tumors, and to select treatment or determine prognosis.

CADD score has limited clinical validity for the identification of pathogenic variants in noncoding regions in a hereditary cancer panel.

PURPOSE: Several in silico tools have been shown to have reasonable research sensitivity and specificity for classifying sequence variants in coding regions. The recently developed combined annotation-dependent depletion (CADD) method generates predictive scores for single-nucleotide variants (SNVs) in all areas of the genome, including noncoding regions. We sought for non-coding variants to determine the clinical validity of common CADD scores. METHODS: We evaluated 12,391 unique SNVs in 624 patient samples submitted for germ-line mutation testing in a cancer-related gene panel. Stratifying by genomic region, we compared the distributions of CADD scores of rare SNVs, SNVs common in our patient population, and the null distribution of all possible SNVs. RESULTS: The median CADD scores of intronic and nonsynonymous variants were significantly different between rare and common SNVs (P < 0.0001). Despite these different distributions, no individual variants could be identified as plausibly causative among the rare intronic variants with the highest scores. The receiver-operating characteristics (ROC) area under the curve (AUC) for noncoding variants is modest, and the positive predictive value of CADD for intronic variants in panel testing was found to be 0.088. CONCLUSION: Focused in silico scoring systems with much higher predictive value will be necessary for clinical genomic applications.Genet Med 18 12, 1269-1275.

Applying Ancestry and Sex Computation as a Quality Control Tool in Targeted Next-Generation Sequencing.

OBJECTIVES: To apply techniques for ancestry and sex computation from next-generation sequencing (NGS) data as an approach to confirm sample identity and detect sample processing errors. METHODS: We combined a principal component analysis method with k-nearest neighbors classification to compute the ancestry of patients undergoing NGS testing. By combining this calculation with X chromosome copy number data, we determined the sex and ancestry of patients for comparison with self-report. We also modeled the sensitivity of this technique in detecting sample processing errors. RESULTS: We applied this technique to 859 patient samples with reliable self-report data. Our k-nearest neighbors ancestry screen had an accuracy of 98.7% for patients reporting a single ancestry. Visual inspection of principal component plots was consistent with self-report in 99.6% of single-ancestry and mixed-ancestry patients. Our model demonstrates that approximately two-thirds of potential sample swaps could be detected in our patient population using this technique. CONCLUSIONS: Patient ancestry can be estimated from NGS data incidentally sequenced in targeted panels, enabling an inexpensive quality control method when coupled with patient self-report.

Improving performance of multigene panels for genomic analysis of cancer predisposition.

PURPOSE: Screening multiple genes for inherited cancer predisposition expands opportunities for cancer prevention; however, reports of variants of uncertain significance (VUS) may limit clinical usefulness. We used an expert-driven approach, exploiting all available information, to evaluate multigene panels for inherited cancer predisposition in a clinical series that included multiple cancer types and complex family histories. METHODS: For 1,462 sequential patients referred for testing by BROCA or ColoSeq multigene panels, genomic DNA was sequenced and variants were interpreted by multiple experts using International Agency for Research on Cancer guidelines and incorporating evolutionary conservation, known and predicted variant consequences, and personal and family cancer history. Diagnostic yield was evaluated for various presenting conditions and family-history profiles. RESULTS: Of 1,462 patients, 12% carried damaging mutations in established cancer genes. Diagnostic yield varied by clinical presentation. Actionable results were identified for 13% of breast and colorectal cancer patients and for 4% of cancer-free subjects, based on their family histories of cancer. Incidental findings explaining cancer in neither the patient nor the family were present in 1.7% of subjects. Less than 1% of patients carried VUS in BRCA1 or BRCA2. For all genes combined, initial reports contained VUS for 10.5% of patients, which declined to 7.5% of patients after reclassification based on additional information. CONCLUSIONS: Individualized interpretation of gene panels is a complex medical activity. Interpretation by multiple experts in the context of personal and family histories maximizes actionable results and minimizes reports of VUS.Genet Med 18 10, 974-981.

MSIplus for Integrated Colorectal Cancer Molecular Testing by Next-Generation Sequencing.

Molecular analysis of colon cancers currently requires multiphasic testing that uses various assays with different performance characteristics, adding cost and time to patient care. We have developed a single, next-generation sequencing assay to simultaneously evaluate colorectal cancers for mutations in relevant cancer genes (KRAS, NRAS, and BRAF) and for tumor microsatellite instability (MSI). In a sample set of 61 cases, the assay demonstrated overall sensitivity of 100% and specificity of 100% for identifying cancer-associated mutations, with a practical limit of detection at 2% mutant allele fraction. MSIplus was 97% sensitive (34 of 35 MSI-positive cases) and 100% specific (42 of 42 MSI-negative cases) for ascertaining MSI phenotype in a cohort of 78 tumor specimens. These performance characteristics were slightly better than for conventional multiplex PCR MSI testing (97% sensitivity and 95% specificity), which is based on comparison of microsatellite loci amplified from tumor and matched normal material, applied to the same specimen cohort. Because the assay uses an amplicon sequencing approach, it is rapid and appropriate for specimens with limited available material or fragmented DNA. This integrated testing strategy offers several advantages over existing methods, including a lack of need for matched normal material, sensitive and unbiased detection of variants in target genes, and an automated analysis pipeline enabling principled and reproducible identification of cancer-associated mutations and MSI status simultaneously.

Microsatellite instability detection by next generation sequencing.

BACKGROUND: Microsatellite instability (MSI) is a useful phenotype in cancer diagnosis and prognosis. Nevertheless, methods to detect MSI status from next generation DNA sequencing (NGS) data are underdeveloped. METHODS: We developed an approach to detect the MSI phenotype using NGS (mSINGS). The method was used to evaluate mononucleotide microsatellite loci that were incidentally sequenced after targeted gene enrichment and could be applied to gene or exome capture panels designed for other purposes. For each microsatellite locus, the number of differently sized repeats in experimental samples were quantified and compared to a population of normal controls. Loci were considered unstable if the experimental number of repeats was statistically greater than in the control population. MSI status was determined by the fraction of unstable microsatellite loci. RESULTS: We examined data from 324 samples generated using targeted gene capture assays of 3 different sizes, ranging from a 0.85-Mb to a 44-Mb exome design and incorporating from 15 to 2957 microsatellite markers. When we compared mSING results to MSI-PCR as a gold standard for 108 cases, we found the approach to be both diagnostically sensitive (range of 96.4% to 100% across 3 panels) and specific (range of 97.2% to 100%) for determining MSI status. The fraction of unstable microsatellite markers calculated from sequencing data correlated with the number of unstable loci detected by conventional MSI-PCR testing. CONCLUSIONS: NGS data can enable highly accurate detection of MSI, even from limited capture designs. This novel approach offers several advantages over existing PCR-based methods.

Validation and implementation of targeted capture and sequencing for the detection of actionable mutation, copy number variation, and gene rearrangement in clinical cancer specimens.

Recent years have seen development and implementation of anticancer therapies targeted to particular gene mutations, but methods to assay clinical cancer specimens in a comprehensive way for the critical mutations remain underdeveloped. We have developed UW-OncoPlex, a clinical molecular diagnostic assay to provide simultaneous deep-sequencing information, based on >500× average coverage, for all classes of mutations in 194 clinically relevant genes. To validate UW-OncoPlex, we tested 98 previously characterized clinical tumor specimens from 10 different cancer types, including 41 formalin-fixed paraffin-embedded tissue samples. Mixing studies indicated reliable mutation detection in samples with ≥ 10% tumor cells. In clinical samples with ≥ 10% tumor cells, UW-OncoPlex correctly identified 129 of 130 known mutations [sensitivity 99.2%, (95% CI, 95.8%-99.9%)], including single nucleotide variants, small insertions and deletions, internal tandem duplications, gene copy number gains and amplifications, gene copy losses, chromosomal gains and losses, and actionable genomic rearrangements, including ALK-EML4, ROS1, PML-RARA, and BCR-ABL. In the same samples, the assay also identified actionable point mutations in genes not previously analyzed and novel gene rearrangements of MLL and GRIK4 in melanoma, and of ASXL1, PIK3R1, and SGCZ in acute myeloid leukemia. To best guide existing and emerging treatment regimens and facilitate integration of genomic testing with patient care, we developed a framework for data analysis, decision support, and reporting clinically actionable results.

Germline and somatic mutations in homologous recombination genes predict platinum response and survival in ovarian, fallopian tube, and peritoneal carcinomas.

PURPOSE: Hallmarks of germline BRCA1/2-associated ovarian carcinomas include chemosensitivity and improved survival. The therapeutic impact of somatic BRCA1/2 mutations and mutations in other homologous recombination DNA repair genes is uncertain. EXPERIMENTAL DESIGN: Using targeted capture and massively parallel genomic sequencing, we assessed 390 ovarian carcinomas for germline and somatic loss-of-function mutations in 30 genes, including BRCA1, BRCA2, and 11 other genes in the homologous recombination pathway. RESULTS: Thirty-one percent of ovarian carcinomas had a deleterious germline (24%) and/or somatic (9%) mutation in one or more of the 13 homologous recombination genes: BRCA1, BRCA2, ATM, BARD1, BRIP1, CHEK1, CHEK2, FAM175A, MRE11A, NBN, PALB2, RAD51C, and RAD51D. Nonserous ovarian carcinomas had similar rates of homologous recombination mutations to serous carcinomas (28% vs. 31%, P = 0.6), including clear cell, endometrioid, and carcinosarcoma. The presence of germline and somatic homologous recombination mutations was highly predictive of primary platinum sensitivity (P = 0.0002) and improved overall survival (P = 0.0006), with a median overall survival of 66 months in germline homologous recombination mutation carriers, 59 months in cases with a somatic homologous recombination mutation, and 41 months for cases without a homologous recombination mutation. CONCLUSIONS: Germline or somatic mutations in homologous recombination genes are present in almost one third of ovarian carcinomas, including both serous and nonserous histologies. Somatic BRCA1/2 mutations and mutations in other homologous recombination genes have a similar positive impact on overall survival and platinum responsiveness as germline BRCA1/2 mutations. The similar rate of homologous recombination mutations in nonserous carcinomas supports their inclusion in PARP inhibitor clinical trials.

Bioinformatics Resource Manager v2.3: an integrated software environment for systems biology with microRNA and cross-species analysis tools.

BACKGROUND: MicroRNAs (miRNAs) are noncoding RNAs that direct post-transcriptional regulation of protein coding genes. Recent studies have shown miRNAs are important for controlling many biological processes, including nervous system development, and are highly conserved across species. Given their importance, computational tools are necessary for analysis, interpretation and integration of high-throughput (HTP) miRNA data in an increasing number of model species. The Bioinformatics Resource Manager (BRM) v2.3 is a software environment for data management, mining, integration and functional annotation of HTP biological data. In this study, we report recent updates to BRM for miRNA data analysis and cross-species comparisons across datasets. RESULTS: BRM v2.3 has the capability to query predicted miRNA targets from multiple databases, retrieve potential regulatory miRNAs for known genes, integrate experimentally derived miRNA and mRNA datasets, perform ortholog mapping across species, and retrieve annotation and cross-reference identifiers for an expanded number of species. Here we use BRM to show that developmental exposure of zebrafish to 30 uM nicotine from 6-48 hours post fertilization (hpf) results in behavioral hyperactivity in larval zebrafish and alteration of putative miRNA gene targets in whole embryos at developmental stages that encompass early neurogenesis. We show typical workflows for using BRM to integrate experimental zebrafish miRNA and mRNA microarray datasets with example retrievals for zebrafish, including pathway annotation and mapping to human ortholog. Functional analysis of differentially regulated (p<0.05) gene targets in BRM indicates that nicotine exposure disrupts genes involved in neurogenesis, possibly through misregulation of nicotine-sensitive miRNAs. CONCLUSIONS: BRM provides the ability to mine complex data for identification of candidate miRNAs or pathways that drive phenotypic outcome and, therefore, is a useful hypothesis generation tool for systems biology. The miRNA workflow in BRM allows for efficient processing of multiple miRNA and mRNA datasets in a single software environment with the added capability to interact with public data sources and visual analytic tools for HTP data analysis at a systems level. BRM is developed using Java™ and other open-source technologies for free distribution (http://www.sysbio.org/dataresources/brm.stm).