Bailey‐Wilson, Joan E.

Abstract Lung cancer is the deadliest cancer in the United States, contributing approximately 25% of all cancer deaths. Lung cancer risk is well-documented to increase in response to environmental factors, particularly tobacco smoking. As one might expect for a complex trait, there is also a significant genetic risk component in lung cancer, though it is not very well studied. We obtained whole exome sequencing (WES) genotype data from Washington University on 204 subjects from 25 extended families. These individuals were recruited from families with a history of lung cancer and previous analyses showed these 25 families be informative. The purpose of this study is to identify potential risk variants for lung cancer by performing genetic linkage analysis. Quality control was performed on the sequence data, filtering on parameters such as depth (less than 10), genotype quality (less than 10), missingness, and Mendelian inconsistencies. Identity-by-descent (IBD) values were also calculated to verify correct familial relationships. Quality control procedures left approximately 500,000 SNVs and indels for analysis. We performed two-point parametric linkage analysis assuming an autosomal dominant mode of inheritance with a disease allele frequency of 1%, a 10% penetrance for carriers and a 1% penetrance for non-carriers. Two discrete sets of linkage analyses were performed. One was a variant-based analysis, which evaluated linkage between the phenotype and individual SNVs or indels. The second was gene-based analysis, which created a multi-allelic pseudomarker corresponding to a gene from haplotypes of rare variants (minor allele frequency <= 0.01) located within that particular gene. Two-point linkage analysis was then performed on the pseudomarkers. While the variant-based analysis did not identify any genome-wide significant results, several were identified by the gene-based analysis. The highest HLOD scores were both greater than the genome-wide significance level of HLOD = 3.3 and were located on two regions of chromosome 1q: 1q42.13-43 and 1q21.2-21.1. In both regions, the significant HLOD scores clustered around known cancer genes. At the 1q42.13-43 region, signals centered on the cancer-implicated genes OBSCN and RYR2 (also a known mesothelioma gene), while at 1q21.2-21.1 the signals centered on five genes in the neuroblastoma breakpoint family (NBPF) genes, a cluster of recently duplicated genes. NBPF genes have previously been implicated in a variety of different cancers including lung cancer. We are currently performing additional analyses to corroborate the significant results, as well as examining the individual families to determine which families are driving the significant signals. Citation Format: Anthony M. Musolf, Haiming Sun, Bilal A. Moiz, Diptasri Mandal, Mariza de Andrade, Colette Gaba, Ping Yang, Yafang Li, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson. Whole exome sequencing identifies significantly linked regions on multiple chromosomes in families with a history of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3276.

Abstract Lung cancer is the leading cancer-related cause of death in the United States. We had previously performed multipoint linkage analysis on families with a strong family history of lung cancer and found significant linkage to the 6q25 region. In order to find the source of that linkage signal, we performed targeted sequencing 6q23-6q27 on 75 individuals from the 9 most highly linked families. We performed two types of parametric linkage analysis, using an autosomal dominant mode of inheritance with 10% penetrance for carriers and a 1% phenocopy rate using a disease allele frequency of 1%. The first type was a two-point analysis using an Elston-Stewart algorithm. This approach did not lead to any genome-wide significant results but demonstrated significant heterogeneity throughout the nine families.In an effort to recover the power from the original multipoint analysis, we performed a regional linkage analysis using SEQLinkage and MERLIN. SEQLinkage built regional haplotypes that corresponded to a gene or an intergenic region - the regions were based on a customized map of our design. The regional markers were multiallelic which allowed for greater information content and were similar to the microsatellites that were used in the original multipoint analysis. The regional markers were then analyzed in a two-point linkage analysis via MERLIN. This allowed us to identify two genome-wide significant signals at PACRG-AS1 at 6q26 (HLOD = 3.4) and SAMD5 at 6q24 (3.3). The PACRG-AS1 is novel, though it is associated with the known lung cancer gene PARK2. SAMD5 may be involved in lung cancer cell proliferation. The heterogeneity of the two signals was particularly interesting. The PACRG-AS1 was driven primarily by two families. The SAMD5 marker was not being strongly driven by any of the families and appears to be a small cumulative effect across the nine families. In addition, several families have large, but non-significant LOD scores at other loci across the region. This further reinforces the locus heterogeneity within the region, and it is likely that our two significant signals here are not the only variants affecting the phenotype. We further attempted to localize the signals by running SEQLinkage using a custom map where genes are broken into exons and introns. Though this resulted in no significant markers, the highest signal was located in the intronic region of SAMD5 (HLOD = 3) and several other suggestive signals were localized to intronic regions of good candidate genes like SASH1 and ARID1B. Examination of predicted effects of the candidate regulatory variants using eQTL databases is ongoing. This is a region full of promising candidates, and it is likely that the two significant signals found here are just part of many that could be affecting lung cancer risk. We plan to do further analysis within the individual families to elucidate any more genes affecting this signal. Citation Format: Anthony M. Musolf, Claire L. Simpson, Bilal A. Moiz, Candace Middlebrooks, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Yafang Li, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson. A study in locus heterogeneity: Targeted sequencing analysis of 6q reveals multiple significant loci as the source of a previous linkage peak in familial lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4290. doi:10.1158/1538-7445.AM2017-4290

Abstract Lung cancer (LC) is the leading cancer killer of Americans; an estimated 158,000 people will die in the U.S. from LC in 2016. While it is well-known that LC risk is affected by the environment, particularly tobacco smoking, there is a substantial genetic risk to LC also. We examined genotype data from Illumina HumanCore-12v1-0 array (297,000 SNPs) on 175 individuals in 25 extended families with a strong history of LC recruited by the Genetic Epidemiology of Lung Cancer Consortium. The purpose of this study is to determine which families are segregating a high-penetrance genetic risk haplotype so that the most informative families can be selected for DNA sequencing studies. Quality control was performed to remove SNPs and individuals with greater than 1% missingness as well as monomorphic SNPs. SNPs with Mendelian errors in more than one family were dropped. Identity-by-descent values were calculated to confirm correct familial relationships; 1 individual was dropped. After quality control we were left with approximately 245,000 SNPs for analysis. We performed three types of parametric linkage analyses using an autosomal dominant model with 40% penetrance in carriers and 1% penetrance in non-carriers. A disease allele frequency of 0.01 was used. Standard single variant two-point analysis between the disease and each marker was performed using TwoPointLods. Multipoint linkage analysis was performed using SimWalk2. We also performed regional-based linkage analyses using SEQLinkage and MERLIN. SEQLinkage builds a multiallelic regional marker (similar to a microsatellite) that corresponds to a gene or a portion of a gene. Two-point linkage analyses were then performed on the regional markers using MERLIN. We identified five loci that were genome-wide significant (HLOD score ≥ 3.3) from the regional-based linkage analyses on 18p11.23 (HLOD = 4.1), 2p22.2 (3.9), 14q13.1 (3.7), 16p13.1 (3.4), and 20q13.11 (3.4). It is particularly exciting that the scores centered on prospective cancer genes. Our highest score was centered on PTPRM, a protein tyrosine phosphatase on chromosome 18 that has been implicated as a LC oncogene. The signal on 20q13 also centered on another protein tyrosine phosphatase (PTPRT) that has been shown to be mutated in LC cells. The source of the signal on 16p13 was RNA binding protein RBFOX1, which has been shown to be deleted in LC cell lines and the source of the signal on 2p22 was LRP1B, a LDL receptor-related protein that is often inactivated in LC cells. The source of the final signal on 14q13 was NPAS3, a transcription factor that is a tumor suppressor in brain tumors. It should be noted that all previous evidence linking these genes to cancer was based on somatic mutations; this is the first time any of these genes has been shown to be significantly linked to germline disease risk in a family-based study. We plan to perform targeted sequencing on the linked regions to elucidate the exact causal variant. Citation Format: Joan E. Bailey-Wilson, Anthony M. Musolf, Claire L. Simpson, Mariza de Andrade, Diptasri Mandal, Colette G. Gaba, Ping Yang, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos. Familial lung cancer is significantly linked to cancer-associated genes on five chromosomes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4268. doi:10.1158/1538-7445.AM2017-4268

ABSTRACTNext‐generation sequencing technologies have afforded unprecedented characterization of low‐frequency and rare genetic variation. Due to low power for single‐variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel‐machine regression and adaptive testing methods for aggregative rare‐variant association testing have been demonstrated to be powerful approaches for pathway‐level analysis, although these methods tend to be computationally intensive at high‐variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare‐variant analysis using component gene‐level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family‐wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case‐control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open‐source R code for public use to facilitate easy application of our methods to existing rare‐variant analysis results.

Lung cancer is the deadliest cancer in the United States, killing roughly one of four cancer patients in 2016. While it is well-established that lung cancer is caused primarily by environmental effects (particularly tobacco smoking), there is evidence for genetic susceptibility. Lung cancer has been shown to aggregate in families, and segregation analyses have hypothesized a major susceptibility locus for the disease. Genetic association studies have provided strong evidence for common risk variants of small-to-moderate effect. Rare and highly penetrant alleles have been identified by linkage studies, including on 6q23–25. Though not common, some germline mutations have also been identified via sequencing studies. Ongoing genomics studies aim to identify additional high penetrance germline susceptibility alleles for this deadly disease.

Abstract Several papers have implicated mutations in the AT-rich interactive domain containing protein 1B (ARID1B) in carcinoma formation in multiple tissue types, including the lung. The ARID1B protein functions as part of SWI/SNF, a multi-subunit chromatin remodeling complex that repositions nucleosomes and may act as a tumor suppressor in cancer. ARID1B is located in a region in 6q that was previously shown to have strong evidence of linkage with lung cancer risk. As it is one of the more promising candidates within the target region, this study presents the viability of ARID1B as a candidate gene for familial lung cancer. Here, we chose individuals from families in our previous linkage study that showed the strongest linkage signal on 6q. 75 individuals from 9 families were sequenced for 37Mb of chromosome 6 from 130Mb to 167Mb using Illumina technology and a custom Agilent kit. Genotypes were imported into GoldenHelix SVS 7 for quality control and dropped if read depth < 10, quality score < 10 or a quality score to read depth ratio < 0.5. Variants with more than 1 Mendelian error were dropped. Variants with a single Mendelian inconsistency were dropped only for that family. Two-point parametric linkage analysis at theta = 0 was performed using R and an implementation of the Elston-Stewart algorithm in the paramlink package using a penetrance model of 0.01/0.1/0.1 (dd/Dd/DD) and a disease allele (D) frequency of 0.01. Family 102 showed strong evidence for linkage near ARID1B. The highest LOD score (1.34) out of all sequenced variants was located near this gene in a known conserved intergenic region between ARID1B and NOX3. Four other LOD scores > 0.7 were found in the intergenic region between these two genes. Two are transcription factor binding sites; two are conserved genomic elements. We also observed two linked intronic variants of ARID1B in this family; an enhancer (LOD = 0.89) and a transcribed region (LOD = 0.73). Two other families (47 and 59) displayed evidence of linkage in ARID1B. Here, the interest is not the value of the LOD scores (top scores were 0.64 and 0.54), but the centering of the linked haplotype around the gene. Family 47 has 60 variants with LODs between 0.64 and 0.61; 45 located within ARID1B or known regulatory regions. Family 59 has 61 variants with LODs between 0.54 and 0.51; 29 located within ARID1B or known regulatory regions The variants appear to be spread evenly throughout ARID1B, suggesting the presence of linked haplotypes. Analyses are currently underway to reconstruct possible haplotypes in these families. The results of this study show that variants in the ARID1B gene at least partially account for the linkage signal on 6q in three of the nine most strongly linked families in our cohort and thus we believe that ARID1B is a plausible candidate gene for further studies involving familial lung cancer. Replication studies using 27 new extended families are currently underway to confirm this initial result. Citation Format: Anthony M. Musolf, Claire L. Simpson, Mariza de Andrade, Diptasri Mandal, Colette Gaba, Ping Yang, Ming You, Elena Y. Kupert, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson. Chromatin remodeling gene ARID1B is linked to familial lung cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2542.

ABSTRACTRare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single‐marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden‐type approaches attempt to identify aggregation of RVs across case‐control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large‐scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway‐level RV analysis results from a prostate cancer (PC) risk case‐control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Abstract African American Hereditary Prostate Cancer Study (AAHPC) was developed as a national collaboration to explore the role of genetics in the causation of hereditary prostate cancer (HPC) in African American (AA) men. AAHPC is in partnership with the International Consortium for Prostate Cancer Genetics (ICPCG), which conducts collaborative studies of HPC genetics in multiplex families. As part of an ICPCG sequencing study of 539 affected individuals from 366 HPC pedigrees, we performed whole exome sequencing in 21 ICPCG AA families, of which there were 14 AAHPC affected men from 11 pedigrees. The combined ICPCG AA cohort consisted of N=26 affected members. Post-variant calling quality control (QC) was implemented using Golden Helix SVS 8 software with filters set for removal of variants with Read Depth < 10, Quality Score < 20, Quality Score: Read Depth Ratio < 0.5, Call Rate < 0.75. Variants were additionally filtered by MAF based on the NHLBI ESP650051-V2 exomes variant frequencies for the AA population using a MAF threshold of 5%. Following QC, 176/299 SNVs and 20/39 INDELs remained for further analysis. In these analyses, we focused on 13 known cancer genes (MSR1, AR, BRCA1, BRCA2, BTNL2, EPHB2, CDH1, RNASEL, ELAC2, HOXB13, CHEK2, TP53 and NBN). Three sequenced families had > 1 affected members sequenced (2 or 3 per family) and the remaining 18 families had one member sequenced. Under the dominant model, our preliminary results show that no rare variants in the 13 candidate genes were found in 3/3 affecteds in two families. Rare SNVs in seven candidate genes (AR, CDH1, ELAC2, HOXB13, RNASEL, BRCA2 and EPHB2) were found in 2/3 affecteds for two families and 2/2 affecteds in one family. Several of the remaining 18 affected men (1 sequenced per pedigree) shared the same rare SNV in these candidate genes. For INDELs, rare variants in three candidate genes were found in pedigrees with ≥ 2 affecteds. Several of the remaining 18 affected men (one sequenced per pedigree) shared the same rare INDEL. Additional QC is underway to validate these variants and bioinformatic analyses are being used to predict effects of the variants in an effort to unravel the complex genetic heterogeneity of HPC in AA. Citation Format: Cheryl D. Cropp, Shannon K. McDonnell, Sumit Middha, Melissa DeRycke, Danielle M. Karyadi, Daniel Schaid, Stephen N. Thibodeau, William B. Isaacs, Elaine A. Ostrander, Janet Stanford, Kathleen A. Cooney, Joan E. Bailey-Wilson, John D. Carpten. Rare variant discovery in known cancer genes from whole-exome sequencingof African American hereditary prostate cancer families. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr B40.

Abstract Several studies have identified common genetic factors that influence susceptibility to lung cancer but no large studies have systematically studied familial lung cancers. The Genetic Epidemiology of Lung Cancer Consortium completed a genome-wide association study (GWAS) using samples from 757 cases and 796 controls, all of European American ancestry, and frequency matched on age and sex. Genotyping was performed by the Center for Inherited Disease Research (CIDR) using an Illumina Human OmniExpressExome-8v1 array. The most significantly associated SNPs were identified in the cases as a whole, and were also stratified by histology (adenocarcinoma and squamous cell carcinoma) and family history (0-1 and 2-5 affected family members). Analysis of all cases and controls identified a large number of SNPs around the CFTR gene that are strongly associated with lung cancer risk. Upon imputation with European Ancestry 1000 genomes data, the most significant SNP in this region is rs43034 (p = 3.89E-07, OR = 0.657) in the promoter region. In addition, an exonic missense SNP, rs213950 (p = 6.32E-07, OR = 0.663), and an intronic SNP with a possible splicing effect, rs213935 (p = 5.20E-07, OR = 0.660) were also identified as possible protective alleles. Analysis by histological subtype identified several rare and exonic SNPs that were specific by histology. We highlight two SNPs, rs114719990 (p = 1.194E-04, OR = 336.8, SETD2, c.3229A>G, p.Thr1077Ala) and rs199710487 (p = 1.124E-04, OR = 366, NTN5, c.656G>A, p.Arg219Gln), that were identified as strongly associated SNPs in cases with histologically confirmed adenocarcinoma, and two SNPs, rs144465058 (p = 1.029E-04, OR = 484.6, ANK3, c.6555G>T, p.Gln2185His) and rs140216112 (p = 1.087E-04, OR = 476, GRIK4, c.1013C>G, p.Ala338Gly), that were identified as top SNPs in cases with histologically confirmed squamous cell carcinoma. The SETD2 gene is thought to be a tumor suppressor gene and variants in this gene have previously been associated with leukemia and glioma (Zhu X et al. 2014, Fontebasso AM et al. 2013), and may now have implications in lung cancer, specifically adenocarcinoma development. In conclusion, we identified SNPs in the CFTR gene that may have a protective effect on lung cancer and several rare and exonic variants that were specific to histology subtype. SNPChrPositionGeneGenomic/ Nucleotide/ Amino acid changeOdds Ratiop-valueCFTR Protective Allelesrs430347117108449CFTRg.117108449T>C; 2.4kb upstream0.6573.89×10−7rs2139507117199533CFTRc.1408G>A; p.Val470Met0.6636.32×10−7rs2139357117178208CFTRc.869+1481A>G0.6605.20×10−7 Citation Format: Diana M. Toledo, Susan M. Pinney, Diptasri Mandal, Mariza de Andrade, Elena Kupert, Jennifer Franks, Colette Gaba, Claire L. Simpson, Ming You, Marshall W. Anderson, Joan E. Bailey-Wilson, Christopher I. Amos, Ann Schwartz. Genetic Epidemiology of Lung Cancer Consortium: genome-wide association study of familial lung cancer cases. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr LB-189. doi:10.1158/1538-7445.AM2015-LB-189