You, Ming

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 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

Abstract In order to select samples that are optimally informative for sequence analysis, studies for the Genetic Epidemiology Consortium, we implemented three strategies for analysis, taking into account the known family histories of lung cancer. Susceptibility for lung cancer arises from a complex interplay between largely unknown genetic factors and smoking behavior. In order to optimize our ability to identify genetic factors for lung cancer we have recruited individuals with extensive family histories of lung cancer and also collected information about their smoking behaviors. For this study, we have modeled family history to identify individuals to select for sequencing using three approaches. First, we used an expert opinion approach in which multiple investigators evaluated pedigree structures with family history to reach a consensus priority in selecting individuals. Second we developed an approximation that assumes a low penetrance among noncarriers and uses known cancer status in first degree relatives. Third, we used the cancer, smoking behaviors and family information along with a likelihood that models penetrance according to genetic susceptibility and an interaction with smoking to estimate the probabilities individuals carry susceptibility factors. In this analysis we compare results among these methods. We evaluate effectiveness of these methods using simulation-based approaches. Citation Format: Christopher Amos, Joan Bailey-Wilson, Susan Pinney, Maria de Andrada, Colette Gaba, Diptasri Mandal, Ming You, Margaret Spitz, Marshall Anderson. Optimal strategies for selecting samples for sequencing families with a common cancer: The Genetic Epidemiology of Lung Cancer Consortium. [abstract]. In: Proceedings of the Eleventh Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2012 Oct 16-19; Anaheim, CA. Philadelphia (PA): AACR; Cancer Prev Res 2012;5(11 Suppl):Abstract nr A106.

Abstract Recent genome-wide association studies have linked the chromosome 15q24-25.1 locus to nicotine addiction and lung cancer susceptibility. To refine the 15q24-25.1 locus, we performed a haplotype-based association analysis of 194 familial lung cases and 219 cancer-free controls from the Genetic Epidemiology of Lung Cancer Consortium (GELCC) collection, and used proliferation and apoptosis analyses to determine which gene(s) in the 15q24-25.1 locus mediates effects on lung cancer cell growth in vitro. We identified two distinct subregions, hapL (P = 3.20 × 10−6) and hapN (P = 1.51 × 10−6), which were significantly associated with familial lung cancer. hapL encompasses IREB2, LOC123688, and PSMA4, and hapN encompasses the three nicotinic acetylcholine receptor subunit genes CHRNA5, CHRNA3, and CHRNB4. Examination of the genes around hapL revealed that PSMA4 plays a role in promoting cancer cell proliferation. PSMA4 mRNA levels were increased in lung tumors compared with normal lung tissues. Down-regulation of PSMA4 expression decreased proteasome activity and induced apoptosis. Proteasome dysfunction leads to many diseases including cancer, and drugs that inhibit proteasome activity show promise as a form of cancer treatment. Genes around hapN were also investigated, but did not show any direct effect on lung cancer cell proliferation. We concluded that PSMA4 is a strong candidate mediator of lung cancer cell growth, and may directly affect lung cancer susceptibility through its modulation of cell proliferation and apoptosis. [Cancer Res 2009;69(19):7844–50]