Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine

Translating whole exome sequencing (WES) for prospective clinical use may impact the care of cancer patients; however, multiple innovations are necessary for clinical implementation. These include: (1) rapid and robust WES from formalin-fixed paraffin embedded (FFPE) tumor tissue, (2) analytical output similar to data from frozen samples, and (3) clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival FFPE tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a “long tail” of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15/16 patients. In one patient, previously undetected findings guided clinical trial enrollment leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine

Genetic Determinants of Lipid Traits in Diverse Populations from the Population Architecture using Genomics and Epidemiology (PAGE) Study

For the past five years, genome-wide association studies (GWAS) have identified hundreds of common variants associated with human diseases and traits, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) levels. Approximately 95 loci associated with lipid levels have been identified primarily among populations of European ancestry. The Population Architecture using Genomics and Epidemiology (PAGE) study was established in 2008 to characterize GWAS–identified variants in diverse population-based studies. We genotyped 49 GWAS–identified SNPs associated with one or more lipid traits in at least two PAGE studies and across six racial/ethnic groups. We performed a meta-analysis testing for SNP associations with fasting HDL-C, LDL-C, and ln(TG) levels in self-identified European American (∼20,000), African American (∼9,000), American Indian (∼6,000), Mexican American/Hispanic (∼2,500), Japanese/East Asian (∼690), and Pacific Islander/Native Hawaiian (∼175) adults, regardless of lipid-lowering medication use. We replicated 55 of 60 (92%) SNP associations tested in European Americans at p<0.05. Despite sufficient power, we were unable to replicate ABCA1 rs4149268 and rs1883025, CETP rs1864163, and TTC39B rs471364 previously associated with HDL-C and MAFB rs6102059 previously associated with LDL-C. Based on significance (p<0.05) and consistent direction of effect, a majority of replicated genotype-phentoype associations for HDL-C, LDL-C, and ln(TG) in European Americans generalized to African Americans (48%, 61%, and 57%), American Indians (45%, 64%, and 77%), and Mexican Americans/Hispanics (57%, 56%, and 86%). Overall, 16 associations generalized across all three populations. For the associations that did not generalize, differences in effect sizes, allele frequencies, and linkage disequilibrium offer clues to the next generation of association studies for these traits

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Association Between Chromosome 9p21 Variants and the Ankle-Brachial Index Identified by a Meta-Analysis of 21 Genome-Wide Association Studies

Genetic determinants of peripheral arterial disease (PAD) remain largely unknown. To identify genetic variants associated with the ankle-brachial index (ABI), a noninvasive measure of PAD, we conducted a meta-analysis of genome-wide association study data from 21 population-based cohorts

The Somatic Genomic Landscape of Glioblastoma

We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer

Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine

Translating whole-exome sequencing (WES) for prospective clinical use may have an impact on the care of patients with cancer; however, multiple innovations are necessary for clinical implementation. These include rapid and robust WES of DNA derived from formalin-fixed, paraffin-embedded tumor tissue, analytical output similar to data from frozen samples and clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival formalin-fixed, paraffin-embedded tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a &apos;long tail&apos; of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15 out of 16 patients. In one patient, previously undetected findings guided clinical trial enrollment, leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine. Massively parallel sequencing approaches such as WES have elucidated the landscape of genetic alterations in many tumor types and revealed biological insights relevant to clinical contexts 1 . The increased practical availability and decreased cost of tumor genomic profiling has generated opportunities to test the &apos;precision medicine&apos; hypothesis in clinical oncology 2 . In principle, knowledge of alterations in the coding regions of all genes may inform immediate treatment choices and further therapeutic discovery efforts 3 . Most prospective clinical genotyping efforts have used &apos;hotspot&apos; genotyping 4-6 or targeted sequencing panels of clinically relevant genes using either fresh frozen or formalin-fixed, paraffin-embedded (FFPE) tissue Here, we describe an approach to generate high-quality WES data from archival tumor material and validate WES data from FFPE tumor samples with corresponding WES data from frozen samples. We also present a heuristic algorithm that interprets the resulting data for clinical oncologists and establish the clinical applicability of this interpretation algorithm in a retrospective cohort of 511 cases. Prospective application of this platform in patients with a range of tumor types indicates that this approach can be used for both biological discovery and clinical trial enrollment. This approach may therefore facilitate widespread application of WES for precision cancer medicine studies. RESULTS WES of FFPE samples To produce WES data for clinical use, robust sequencing data must frequently be generated from small quantities of archival FFPE tissue. To test this, we extracted DNA from 99 FFPE samples using the FFP

Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine

Translating whole-exome sequencing (WES) for prospective clinical use may have an impact on the care of patients with cancer; however, multiple innovations are necessary for clinical implementation. These include rapid and robust WES of DNA derived from formalin-fixed, paraffin-embedded tumor tissue, analytical output similar to data from frozen samples and clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival formalin-fixed, paraffin-embedded tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a &apos;long tail&apos; of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15 out of 16 patients. In one patient, previously undetected findings guided clinical trial enrollment, leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine. Massively parallel sequencing approaches such as WES have elucidated the landscape of genetic alterations in many tumor types and revealed biological insights relevant to clinical contexts 1 . The increased practical availability and decreased cost of tumor genomic profiling has generated opportunities to test the &apos;precision medicine&apos; hypothesis in clinical oncology 2 . In principle, knowledge of alterations in the coding regions of all genes may inform immediate treatment choices and further therapeutic discovery efforts 3 . Most prospective clinical genotyping efforts have used &apos;hotspot&apos; genotyping 4-6 or targeted sequencing panels of clinically relevant genes using either fresh frozen or formalin-fixed, paraffin-embedded (FFPE) tissue Here, we describe an approach to generate high-quality WES data from archival tumor material and validate WES data from FFPE tumor samples with corresponding WES data from frozen samples. We also present a heuristic algorithm that interprets the resulting data for clinical oncologists and establish the clinical applicability of this interpretation algorithm in a retrospective cohort of 511 cases. Prospective application of this platform in patients with a range of tumor types indicates that this approach can be used for both biological discovery and clinical trial enrollment. This approach may therefore facilitate widespread application of WES for precision cancer medicine studies. RESULTS WES of FFPE samples To produce WES data for clinical use, robust sequencing data must frequently be generated from small quantities of archival FFPE tissue. To test this, we extracted DNA from 99 FFPE samples using the FFP

Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine Corresponding Authors

. &quot;Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine.&quot; Nature medicine 20 Disclosures: Dr. Garraway and Dr. Wagle are equity holders and consultants in Foundation Medicine. Dr. Garraway is a consultant to Novartis, Millenium/Takeda, and Boehringer Ingelheim, and a recipient of a grant from Novartis. Dr. Getz is a consultant to The Kew Group. Dr. Barbie is a consultant to N-of-1. NIH Public Acces

Transcript expression-aware annotation improves rare variant interpretation

The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the ‘proportion expressed across transcripts’, which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.publishedVersionPeer reviewe