Transcript Chris Amos
Genetic predictors of lung cancer risk and progression Some results and new proposals Christopher Amos, Ph.D. Olga Gorlova, Ph.D. Ivan Gorlov, Ph.D. Konstantin Dragnev Scott Gerber, Ph.D. James Rigas, M.D. David Christiani, M.D, Sc.D. Genetic Associations and Mechanisms in Oncology (GAME-ON): Transdisciplinary Studies of Genetic Variation in Follow-up of Ovarian Cancer Colorectal Cancer Genetic Association and Interaction Studies (FOCI) Thomas Sellers (CORECT) Stephen Gruber Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE) Brian Henderson PHASE 1 DISCOVERY Transdisciplinary Research in Cancer of the Lung (TRICL) Chris Amos PHASE 2 FUNCTIONAL ANALYSIS Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) David Hunter PHASE 3 RISK ASSESMENT Manhattan plot of all lung cancers from 1000 Genomes Imputation CHRNA5 hTERT BRCA2 TP63 hMSH5 CHEK2 Associations of common mutations in BRCA2 with cancer in Iceland Comparison of AD and SQ LC Adenocarcinoma Squamous Carcinoma CHRNA5 (C) SQ hTERT TP63 CHRNA5 BRCA2 CHEK2 hMSH5 CLPTM1L CDKN2 RAD52 Squamous Lung Cancer BRCA2 BRCA2 CHEK2 CHEK2 GWAS-translation • Knockdown studies of CLPTM1L and TERT show loss of CLPTM1L expression is necessary for lung cancer development in a kRAS knockout mouse • Comprehensive promoter methylation studies of risk loci implicate epigenetic deregulation of most SNPassociated lung cancer loci including CHRNA3, CHRNB4 and TERT in lung cancer susceptibility • Genotype-methylation associations in lung tumor tissue for TERT and CHRNB4 • CHRNB4 promoter hypomethylation and CHRNA3 + TERT promoter hypermethylation as well as methylation-expression correlations in tumor tissue • CHRNB4 knockdown leads to reduced proliferation and propensity to form colonies Other Genetic Analysis Projects Custom Affymetrix Array • 9 studies concentrating on cohorts – 7,500 lung cancer cases – 7,500 controls Custom Array with 300,000 exome array markers 100,000 custom markers including markers derived from sequencing studies and pharmacogenetic variants Exome plus targeted regions sequencing • Sequencing of 1000 lung ca. cases and 1000 contols • Funded through a separate application to CIDR • Includes samples from the Custom Affymetrix Array Study to inform imputations • Selecting early onset cases, family history positive, cases with tumor samples and rare variant carriers GAME-ON OncoArray Common Content – 40K Fine-mapping of common cancer susceptibility loci (TERT, 8q24 (proximal and distal to MYC), HNF1B, TET2, RAD51B, 11q13, MERIT40, MDM4) Ancestry Informative Markers Cross-Site meta analysis Pharmacogenetic components eQTL (Height, Weight, BMI, WHR, Menarche, Menopause etc) Other cancers published GWAS variants Chromosome X and mitochondrial DNA variants GWAS Backbone 260K Illumina Core OncoChip 600K beadtypes Cancer Specific Variants Lung Colon Breast Prostate Ovarian (proportional allocation) Proposed Research Studies • Shared decision making and tumor analysis – Proposed application of 100 lung cancer cases with hotspot mutation versus exome sequencing • Collaboration between Karmanos Cancer Institute and Dartmouth • Reviewers liked Dartmouth component but not Karmanos – lack of electronic medical record at KCI, insufficient process details Predicting Risk for Recurrence • Proposed collaboration to Lungevity Foundation • Uses snap frozen samples from Harvard to perform integrated analysis – genomic mutations and proteomic alternations • 200 cases selected for recurrence or nonrecurrence • Could be extended in R01 to larger sample size • Extend to other lung cancer phenotypes U01 Grant On Integration of SNP Data in Lung Cancer Screening • In collaboration with Dr. Kimmel from Rice we are working on the proposal to integrate GWAS-detected risk and outcome SNP into lung cancer screening model. • As the first step we will estimate effects of SNPs on tumor growth and metastasizing rate. We will use NLST and TCGA data. • We will then incorporate SNPs into the model of natural history of lung cancer with the screening module superimposed onto it. • SNPs in the model will be incorporated based on their frequency and estimated effect size on tumor growth and metastasizing rates. • The goal is to estimate if targeted genotyping of the risk associated SNPs will improve screening efficacy. P01 Integrative Analysis of Lung Cancer Risk Project 1 Smoking Genetic Predictors Dependence Project 4: Application of Risk Models to Screening Populations Biostatistics and QC Core Project 2: Genomic and Epigenetic Predictors of Risk Project 3: Intermediate predictors of risk: miRNA, metabolomiic and ‘nutritional’ exposures Genomics and Genetics Genetic Mapping of DNA Methylation in EAGLE Lung Conducted methylation quantitative trait loci (QTL) analysis of EAGLE normal lung tissues in 210 samples, with 450K CpG probes, replicated in TCGA lung tissue (Additive model between each SNP and normalized methylation trait pair, adjusting for sex, age, plate, population stratification and methylation-based PCA scores) 34,304 cis-meQTL (mapping to 9,963 genes) cis region=500kb 585 trans-meQTLs trans region>500kb or different chromosomes Most meQTLs are not in gene promoters or CpG islands Shi et al., Nature Communications (In press) CHRNA5 CLPM1L TERT 15q25 6p21 5p15 12p13 9p21 CHRNA3 RAD52 CDKN2A MSH5 Inherited genetic variation may affect lung carcinogenesis by cis-meQTL in lung cancer GWAS loci regulating the human methylome