Alex Parker

Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing

As more clinically relevant cancer genes are identified, comprehensive diagnostic approaches are needed to match patients to therapies, raising the challenge of optimization and analytical validation of assays that interrogate millions of bases of cancer genomes altered by multiple mechanisms. Here we describe a test based on massively parallel DNA sequencing to characterize base substitutions, short insertions and deletions (indels), copy number alterations and selected fusions across 287 cancer-related genes from routine formalin-fixed and paraffin-embedded (FFPE) clinical specimens. We implemented a practical validation strategy with reference samples of pooled cell lines that model key determinants of accuracy, including mutant allele frequency, indel length and amplitude of copy change. Test sensitivity achieved was 95–99% across alteration types, with high specificity (positive predictive value >99%). We confirmed accuracy using 249 FFPE cancer specimens characterized by established assays. Application of the test to 2,221 clinical cases revealed clinically actionable alterations in 76% of tumors, three times the number of actionable alterations detected by current diagnostic tests.

Identification of new ALK and RET gene fusions from colorectal and lung cancer biopsies

Applying a next-generation sequencing assay targeting 145 cancer-relevant genes in 40 colorectal cancer and 24 non–small cell lung cancer formalin-fixed paraffin-embedded tissue specimens identified at least one clinically relevant genomic alteration in 59% of the samples and revealed two gene fusions, C2orf44-ALK in a colorectal cancer sample and KIF5B-RET in a lung adenocarcinoma. Further screening of 561 lung adenocarcinomas identified 11 additional tumors with KIF5B-RET gene fusions (2.0%; 95% CI 0.8–3.1%). Cells expressing oncogenic KIF5B-RET are sensitive to multi-kinase inhibitors that inhibit RET.

Two independent alleles at 6q23 associated with risk of rheumatoid arthritis

To identify susceptibility alleles associated with rheumatoid arthritis, we genotyped 397 individuals with rheumatoid arthritis for 116,204 SNPs and carried out an association analysis in comparison to publicly available genotype data for 1,211 related individuals from the Framingham Heart Study. After evaluating and adjusting for technical and population biases, we identified a SNP at 6q23 (rs10499194, ∼150 kb from TNFAIP3 and OLIG3) that was reproducibly associated with rheumatoid arthritis both in the genome-wide association (GWA) scan and in 5,541 additional case-control samples (P = 10−3, GWA scan; P < 10−6, replication; P = 10−9, combined). In a concurrent study, the Wellcome Trust Case Control Consortium (WTCCC) has reported strong association of rheumatoid arthritis susceptibility to a different SNP located 3.8 kb from rs10499194 (rs6920220; P = 5 × 10−6 in WTCCC). We show that these two SNP associations are statistically independent, are each reproducible in the comparison of our data and WTCCC data, and define risk and protective haplotypes for rheumatoid arthritis at 6q23.

Loci Related to Metabolic-Syndrome Pathways Including LEPR,HNF1A, IL6R, and GCKR Associate with Plasma C-Reactive Protein: The Women's Genome Health Study

Although elevated levels of C-reactive protein (CRP) independently predict increased risk of development of metabolic syndrome, diabetes, myocardial infarction, and stroke, comprehensive analysis of the influence of genetic variation on CRP is not available. To address this issue, we performed a genome-wide association study among 6345 apparently healthy women in which we evaluated 336,108 SNPs as potential determinants of plasma CRP concentration. Overall, seven loci that associate with plasma CRP at levels achieving genome-wide statistical significance were found (range of p values for lead SNPs within the seven loci: 1.9 x 10(-)(8) to 6.2 x 10(-)(28)). Two of these loci (GCKR and HNF1A) are suspected or known to be associated with maturity-onset diabetes of the young, one is a gene-desert region on 12q23.2, and the remaining four loci are in or near the leptin receptor protein gene, the apolipoprotein E gene, the interleukin-6 receptor protein gene, or the CRP gene itself. The protein products of six of these seven loci are directly involved in metabolic syndrome, insulin resistance, beta cell function, weight homeostasis, and/or premature atherothrombosis. Thus, common variation in several genes involved in metabolic and inflammatory regulation have significant effects on CRP levels, consistent with CRPs identification as a useful biomarker of risk for incident vascular disease and diabetes.

Forty-three loci associated with plasma lipoprotein size, concentration, and cholesterol content in genome-wide analysis.

While conventional LDL-C, HDL-C, and triglyceride measurements reflect aggregate properties of plasma lipoprotein fractions, NMR-based measurements more accurately reflect lipoprotein particle concentrations according to class (LDL, HDL, and VLDL) and particle size (small, medium, and large). The concentrations of these lipoprotein sub-fractions may be related to risk of cardiovascular disease and related metabolic disorders. We performed a genome-wide association study of 17 lipoprotein measures determined by NMR together with LDL-C, HDL-C, triglycerides, ApoA1, and ApoB in 17,296 women from the Womens Genome Health Study (WGHS). Among 36 loci with genome-wide significance (P<5×10−8) in primary and secondary analysis, ten (PCCB/STAG1 (3q22.3), GMPR/MYLIP (6p22.3), BTNL2 (6p21.32), KLF14 (7q32.2), 8p23.1, JMJD1C (10q21.3), SBF2 (11p15.4), 12q23.2, CCDC92/DNAH10/ZNF664 (12q24.31.B), and WIPI1 (17q24.2)) have not been reported in prior genome-wide association studies for plasma lipid concentration. Associations with mean lipoprotein particle size but not cholesterol content were found for LDL at four loci (7q11.23, LPL (8p21.3), 12q24.31.B, and LIPG (18q21.1)) and for HDL at one locus (GCKR (2p23.3)). In addition, genetic determinants of total IDL and total VLDL concentration were found at many loci, most strongly at LIPC (15q22.1) and APOC-APOE complex (19q13.32), respectively. Associations at seven more loci previously known for effects on conventional plasma lipid measures reveal additional genetic influences on lipoprotein profiles and bring the total number of loci to 43. Thus, genome-wide associations identified novel loci involved with lipoprotein metabolism—including loci that affect the NMR-based measures of concentration or size of LDL, HDL, and VLDL particles—all characteristics of lipoprotein profiles that may impact disease risk but are not available by conventional assay.

Multiple genetic loci influence serum urate levels and their relationship with gout and cardiovascular disease risk factors

Background—Elevated serum urate levels can lead to gout and are associated with cardiovascular risk factors. We performed a genome-wide association study to search for genetic susceptibility loci for serum urate and gout and investigated the causal nature of the associations of serum urate with gout and selected cardiovascular risk factors and coronary heart disease (CHD). Methods and Results—Meta-analyses of genome-wide association studies (GWAS) were performed in 5 population-based cohorts of the Cohorts for Heart and Aging Research in Genome Epidemiology consortium for serum urate and gout in 28 283 white participants. The effect of the most significant single-nucleotide polymorphism at all genome-wide significant loci on serum urate was added to create a genetic urate score. Findings were replicated in the Womens Genome Health Study (n=22 054). Single-nucleotide polymorphisms at 8 genetic loci achieved genome-wide significance with serum urate levels (P=4×10−8 to 2×10−242 in SLC22A11, GCKR, R3HDM2-INHBC region, RREB1, PDZK1, SLC2A9, ABCG2, and SLC17A1). Only 2 loci (SLC2A9, ABCG2) showed genome-wide significant association with gout. The genetic urate score was strongly associated with serum urate and gout (odds ratio, 12.4 per 100 &mgr;mol/L; P=3×10−39) but not with blood pressure, glucose, estimated glomerular filtration rate, chronic kidney disease, or CHD. The lack of association between the genetic score and the latter phenotypes also was observed in the Womens Genome Health Study. Conclusions—The genetic urate score analysis suggested a causal relationship between serum urate and gout but did not provide evidence for one between serum urate and cardiovascular risk factors and CHD.

Genomewide Linkage Analysis of Stature in Multiple Populations Reveals Several Regions with Evidence of Linkage to Adult Height

Genomewide linkage analysis has been extremely successful at identification of the genetic variation underlying single-gene disorders. However, linkage analysis has been less successful for common human diseases and other complex traits in which multiple genetic and environmental factors interact to influence disease risk. We hypothesized that a highly heritable complex trait, in which the contribution of environmental factors was relatively limited, might be more amenable to linkage analysis. We therefore chose to study stature (adult height), for which heritability is approximately 75%-90% (Phillips and Matheny 1990; Carmichael and McGue 1995; Preece 1996; Silventoinen et al. 2000). We reanalyzed genomewide scans from four populations for which genotype and height data were available, using a variance-components method implemented in GENEHUNTER 2.0 (Pratt et al. 2000). The populations consisted of 408 individuals in 58 families from the Botnia region of Finland, 753 individuals in 183 families from other parts of Finland, 746 individuals in 179 families from Southern Sweden, and 420 individuals in 63 families from the Saguenay-Lac-St.-Jean region of Quebec. Four regions showed evidence of linkage to stature: 6q24-25, multipoint LOD score 3.85 at marker D6S1007 in Botnia (genomewide P<.06), 7q31.3-36 (LOD 3.40 at marker D7S2195 in Sweden, P<.02), 12p11.2-q14 (LOD 3.35 at markers D12S10990-D12S398 in Finland, P<.05) and 13q32-33 (LOD 3.56 at markers D13S779-D13S797 in Finland, P<.05). In a companion article (Perola et al. 2001 [in this issue]), strong supporting evidence is obtained for linkage to the region on chromosome 7. These studies suggest that highly heritable complex traits such as stature may be genetically tractable and provide insight into the genetic architecture of complex traits.

Massively Parallel Tumor Multigene Sequencing to Evaluate Response to Panitumumab in a Randomized Phase III Study of Metastatic Colorectal Cancer

Purpose: To investigate whether EGF receptor (EGFR) pathway mutations predicted response to monotherapy with panitumumab, an anti-EGFR monoclonal antibody, in a randomized phase III study of metastatic colorectal cancer. Experimental Design: Using massively parallel multigene sequencing, we analyzed 320 samples for 9 genes, with multigene sequence data from 288 (90%) samples. Results: Mutation rates were: KRAS (45%), NRAS (5%), BRAF (7%), PIK3CA (9%), PTEN (6%), TP53 (60%), EGFR (1%), AKT1 (<1%), and CTNNB1 (2%). In the randomized study and open-label extension, 22 of 138 (16%) wild-type KRAS (codons 12/13/61) patients versus 0 of 103 mutant KRAS (codons 12/13) patients had objective responses. Of 6 mutant KRAS (codon 61) patients, 1 with a Q61H mutation achieved partial response during the extension. Among wild-type KRAS (codons 12/13/61) patients, 0 of 9 patients with NRAS mutations, 0 of 13 with BRAF mutations, 2 of 10 with PIK3CA mutations, 1 of 9 with PTEN mutations, and 1 of 2 with CTNNB1 mutations responded to panitumumab. No patients responded to best supportive care alone. Panitumumab treatment was associated with longer progression-free survival (PFS) among wild-type KRAS (codons 12/13/61) patients [HR, 0.39; 95% confidence interval (CI), 0.28–0.56]. Among wild-type KRAS patients, a treatment effect for PFS favoring panitumumab occurred in patients with wild-type NRAS (HR, 0.39; 95% CI, 0.27–0.56) and wild-type BRAF (HR, 0.37; 95% CI, 0.24–0.55) but not mutant NRAS (HR, 1.94; 95% CI, 0.44–8.44). Conclusions: These results show the feasibility and potential clinical use of next-generation sequencing for evaluating predictive biomarkers. Clin Cancer Res; 19(7); 1902–12. ©2012 AACR.

Polymorphism in the CETP gene region, HDL cholesterol, and risk of future myocardial infarction: Genomewide analysis among 18 245 initially healthy women from the Women's Genome Health Study.

Background—Recent trial data have challenged the hypothesis that cholesteryl ester transfer protein (CETP) and high-density lipoprotein cholesterol (HDL-C) have causal roles in atherothrombosis. One method to evaluate this issue is to examine whether polymorphisms in the CETP gene that impact on HDL-C levels also impact on the future development of myocardial infarction. Methods and Results—In a prospective cohort of 18 245 initially healthy American women, we examined over 350 000 singe-nucleotide polymorphisms (SNPs) first to identify loci associated with HDL-C and then to evaluate whether significant SNPs within these loci also impact on rates of incident myocardial infarction during an average 10-year follow-up period. Nine loci on 9 chromosomes had 1 or more SNPs associated with HDL-C at genome-wide statistical significance (P<5×10−8). However, only SNPs near or in the CETP gene at 16q13 were associated with both HDL-C and risk of incident myocardial infarction (198 events). For example, SNP rs708272 in the CETP gene was associated with a per-allele increase in HDL-C levels of 3.1 mg/dL and a concordant 24% lower risk of future myocardial infarction (age-adjusted hazard ratio, 0.76; 95% CI, 0.62 to 0.94), consistent with recent meta-analysis. Independent and again concordant effects on HDL-C and incident myocardial infarction were also observed at the CETP locus for rs4329913 and rs7202364. Adjustment for HDL-C attenuated but did not eliminate these effects. Conclusion—In this prospective cohort of initially healthy women, SNPs at the CETP locus impact on future risk of myocardial infarction, supporting a causal role for CETP in atherothrombosis, possibly through an HDL-C mediated pathway.

Large scale association analysis for identification of genes underlying premature coronary heart disease: cumulative perspective from analysis of 111 candidate genes

Background: to date, only three groups have reported data from large scale genetic association studies of coronary heart disease using a case control design. Methods and results: to extend our initial report of 62 genes, we present data for 210 polymorphisms in 111 candidate genes genotyped in 352 white subjects with familial, premature coronary heart disease (onset age for men, 45; for women, 50) and a random sample of 418 population based whites. Multivariate logistic regression analysis was used to compare the distributions of genotypes between cases and the comparison group while controlling for age, sex, body mass, diabetes, and hypertension. Significant associations were found with polymorphisms in thrombospondin-4 (THBS4), thrombospondin-2 (THBS2) and plasminogen activator inhibitor-2 (PAI2), the strongest being with the A387P variant in THBS4 (p = 0.002). The THBS2 and THBS4 associations have since been replicated. We evaluated polymorphisms in 40 genes previously associated with coronary heart disease and found significant (p<0.05) associations with 10: ACE, APOE, F7, FGB, GP1BA, IL1RN, LRP1, MTHFR, SELP, and THPO. For five of these genes, the polymorphism associated in our study was different from that previously reported, suggesting linkage disequilibrium as an explanation for failure to replicate associations consistently across studies. We found strong linkage disequilibrium between polymorphisms within and between genes, especially on chromosome 1q22-q25, a region containing several candidate genes. Conclusions: despite known caveats of genetic association studies, they can be an effective means of hypothesis generation and complement classic linkage studies for understanding the genetic basis of coronary heart disease.