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17 citation(s) found for "Li, Yafang".

Abstract 4290: 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
Moiz, Bilal A., Middlebrooks, Candace D., Mandal, Diptasri , Gaba, Colette , Yang, Ping , Li, Yafang , Kupert, Elena, Anderson, Marshall W., Schwartz, Ann G. , Musolf, Anthony M. , Simpson, Claire L. , Andrade, Mariza de , You, Ming , Pinney, Susan M. , Amos, Christopher I. , Bailey‐Wilson, Joan E.

Mayo Clinic

Cancer Research | July 31, 2017 | Volume: 77 | Issue: 13_Supplement | Pages: 4290-4290

10.1158/1538-7445.am2017-4290 Get It

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
Familial Lung Cancer: A Brief History from the Earliest Work to the Most Recent Studies
Simpson, Claire L. , Andrade, Mariza de , Mandal, Diptasri , Gaba, Colette , Li, Yafang , You, Ming , Kupert, Elena, Anderson, Marshall W., Schwartz, Ann G. , Pinney, Susan M. , Bailey‐Wilson, Joan E. , de Andrade, Mariza, Musolf, Anthony M. , Yang, Ping , Amos, Christopher I. , de Andrade, Mariza , Wilson, Richard K , Pinney, Susan M

Mayo Clinic

Genes | January 18, 2017 | Volume: 8 | Issue: 1 | Pages: 36

10.3390/genes8010036 | PMID 28106732 Get It

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.
The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers
Wang, Zhaoming , Schumacher, Fredrick R. , Gayther, Simon A. , Casey, Graham , Sellers, Thomas A. , Gruber, Stephen B., Dunning, Alison M. , Michailidou, Kyriaki , Fachal, Laura , Doheny, Kimberly F. , Li, Yafang , Xiao, Xiangjun , Romm, Jane, Pugh, Elizabeth, Coetzee, Gerhard A. , Hazelett, Dennis J. , Bojesen, Stig E. , Caga-Anan, Charlisse , Haiman, Christopher A. , Kamal, Ahsan , Luccarini, Craig , Tessier, Daniel C., Vincent, Daniel , Bacot, François, Berg, David Van Den , Nelson, Stefanie A. , Demetriades, Stephen, Goldgar, David E., Forman, Judith L., Conti, David V. , Bickeböller, Heike , Risch, Angela , Waldenberger, Mélanie , Brüske‐Hohlfeld, Irene, Hicks, Belynda , McGuffog, Lesley, Kuchenbaecker, Karoline , Soucy, Penny, Manz, Judith, Cunningham, Julie M. , Butterbach, Katja, Kote‐Jarai, Zsofia , Kraft, Peter , Lindström, Sara , Adams, Marcia, McKay, James , Phelan, Catherine M., Benlloch, Sara, Kelemen, Linda E., Brennan, Paul , Riggan, Marjorie J. , O’Mara, Tracy A. , Shen, Hongbing , Shi, Yongyong , Thompson, Deborah J. , Goodman, Marc T. , Nielsen, Sune F. , LaBoissière, Sylvie, Schmit, Stephanie L. , Shelford, Tameka, Edlund, Christopher K., Taylor, Jack A. , Field, John K. , Park, Sue K. , Offit, Kenneth , Thomassen, Mads , Schmutzler, Rita K., Ottini, Laura , Hung, Rayjean J., Olama, Ali Amin Al , Peters, Ulrike , Eeles, Rosalind A. , Seldin, Michael F., Gillanders, Elizabeth M. , Seminara, Daniela, Antoniou, Antonis C. , Chenevix‐Trench, Georgia , Simard, Jacques , Easton, Douglas F. , Durocher, Francine , Hung, Rayjean J. , Amos, Christopher I. , Dennis, Joe , Byun, Jinyoung , Hunter, David J. , Spurdle, Amanda B. , Couch, Fergus J. , Giles, Graham G. , Ling, Hua , Lee, Andrew , FitzGerald, Liesel M. , Berchuck, Andrew , Marchini, Jonathan , Pharoah, Paul D.P. , Chanock, Stephen Jacob , Hazelett, Dennis J , Eeles, Rosalind A , Van Den Berg, David J , Hung, Rayjean J , Wang, Zhaoming , O'Mara, Tracy A , Field, John K , Dunning, Alison M , Michailidou, Kyriaki , Taylor, Jack A , Kraft, Peter , Simard, Jacques , Chenevix-Trench, Georgia , Ottini, Laura , Conti, David V , Bojesen, Stig E , Risch, Angela , Bickeböller, Heike , Shen, Hongbing , Goodman, Marc T , Fachal, Laura

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Cancer Epidemiology, Biomarkers & Prevention | October 3, 2016 | Volume: 26 | Issue: 1 | Pages: 126-135

10.1158/1055-9965.epi-16-0106 | PMID 27697780 Get It

Abstract Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.
Abstract 4600: Target exome sequencing for disease-causing rare mutations in familial and sporadic lung cancer
Wheeler, David A. , Silverman, Edwin K. , Sanjay, Shete, Tsavachidis, Spiridon, Armstrong, Georgina , Kupert, Elena, Anderson, Marshall W., Li, Yafang , Pikielny, Claudio W. , You, Ming , Gaba, Colette , deAndrade, Mariza, Mandal, Diptasri , Spitz, Margaret R., Liu, Yanhong , Kheradmand, Farrah , Scheurer, Michael E. , Davis, Caleb , Armstrong, Georgina , Bailey‐Wilson, Joan E. , Simpson, Claire L. , Pinney, Susan M. , Amos, Christopher I.

Mayo Clinic

Cancer Research | August 5, 2015 | Volume: 75 | Issue: 15_Supplement | Pages: 4600-4600

10.1158/1538-7445.am2015-4600 Get It

Abstract Background: Recent genome-wide association studies (GWAS) have identified 28 susceptibility loci for Lung cancer (LC), 32 loci for smoking behavior, 10 loci for chronic obstructive pulmonary disease (COPD), 63 loci for pulmonary function and related phenotypes, totaling 107 GWAS susceptibility loci (as of November 2014). Given the common variants that have been found to be associated with LC in GWAS, targeted-region exome sequencing provides a cost-effective approach for further investigation of high-priority regions of the genome and has the great potential to identify rare causal variants in GWAS loci. Patients and Methods: Using an extreme phenotype approach, we selected 48 sporadic LC patients reporting heavy smoking histories with the presence of severe COPD in whom environmental factors are considered overwhelming, and 54 familial LC cases from families with at least three first-degree relatives with LC who are likely enriched for genomic signal, to search for the disease-causing rare mutations within the target 107 GWAS loci using exome sequencing data. Results: By focusing on exome profiles of these target 107 loci, we identified two disease-causing rare mutations on 6p21.32 TNXB p. Arg504His and 10q25.1 CCDC147 p.Arg696Cys. The homozygous Arg504His mutation presented in four familial and one sporadic LC cases. Notably, the minor allele frequency (MAF) of this variant in Caucasians from 1000 Genomes is very rare (<0.001). The heterozygous CCDC147 Arg696Cys variant were identified in two familial cases and one sporadic case. The MAF for this variant in the Caucasians from 1000 Genomes is 0.004. Both deleterious changes lead to truncation of the putative proteins, which disrupts the predicted domain and alters the cellular localization. We also observed several other suggestive rare mutations on G7C, TNS1, DBH1, and CHRNA5. Conclusion: Our target exome sequencing results demonstrate novel highly disruptive LC risk-conferring TNXB and CCDC147 mutations. Since the rare variants have appreciable effects on disease risk prediction, families and patients may warrant screening for mutations in TNXB and CCDC147 (if validated) to assess their potential LC risk. Citation Format: Yanhong Liu, Farrah Kheradmand, Michael Scheurer, Caleb Davis, David Wheeler, Edwin Silverman, Shete Sanjay, Spiridon Tsavachidis, Georgina Armstrong, Elena Kupert, Marshall Anderson, Yafang Li, Claudio Pikielny, Joan E. Bailey-Wilson, Ming You, Colette Gaba, Mariza DeAndrade, Diptasri Mandal, Claire Simpson, Susan Pinney, Christopher Amos, Margaret Spitz. Target exome sequencing for disease-causing rare mutations in familial and sporadic lung cancer. [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 4600. doi:10.1158/1538-7445.AM2015-4600
Ordered Subset Analysis Identifies Loci Influencing Lung Cancer Risk on Chromosomes 6q and 12q
Fang, Shenying , Pinney, Susan M. , Bailey‐Wilson, Joan E. , Andrade, Mariza A. de, Li, Yafang , Kupert, Elena, You, Ming, Schwartz, Ann G. , Anderson, Marshall W., Yang, Ping , Amos, Christopher I. , Wilson, Richard K , Pinney, Susan M

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Cancer Epidemiology, Biomarkers & Prevention | December 14, 2010 | Volume: 19 | Issue: 12 | Pages: 3157-3166

10.1158/1055-9965.epi-10-0792 | PMID 21030603 Get It

Abstract Background: Genetic susceptibility for cancer can differ substantially among families. We use trait-related covariates to identify a genetically homogeneous subset of families with the best evidence for linkage in the presence of heterogeneity. Methods: We performed a genome-wide linkage screen in 93 families. Samples and data were collected by the familial lung cancer recruitment sites of the Genetic Epidemiology of Lung Cancer Consortium. We estimated linkage scores for each family by the Markov chain Monte Carlo procedure using SimWalk2 software. We used ordered subset analysis (OSA) to identify genetically homogenous families by ordering families based on a disease-associated covariate. We performed permutation tests to determine the relationship between the trait-related covariate and the evidence for linkage. Results: A genome-wide screen for lung cancer loci identified strong evidence for linkage to 6q23–25 and suggestive evidence for linkage to 12q24 using OSA, with peak logarithm of odds (LOD) scores of 4.19 and 2.79, respectively. We found other chromosomes also suggestive for linkages, including 5q31–q33, 14q11, and 16q24. Conclusions: Our OSA results support 6q as a lung cancer susceptibility locus and provide evidence for disease linkage on 12q24. This study further increased our understanding of the inheritability for lung cancer. Validation studies using larger sample size are needed to verify the presence of several other chromosomal regions suggestive of an increased risk for lung cancer and/or other cancers. Impact: OSA can reduce genetic heterogeneity in linkage study and may assist in revealing novel susceptibility loci. Cancer Epidemiol Biomarkers Prev; 19(12); 3157–66. ©2010 AACR.
A Susceptibility Locus on Chromosome 6q Greatly Increases Lung Cancer Risk among Light and Never Smokers
Pinney, Susan M. , Li, Yafang , Kupert, Elena, Lee, Juwon , Andrade, Mariza A. de, Schwartz, Ann G. , Fain, P., Gazdar, Adi F. , Wiest, Jonathan S., Zeng, Dong, Rothschild, Henry, Mandal, Diptasri , You, Ming, Coons, Teresa, Gaba, Colette , Bailey‐Wilson, Joan E. , Anderson, Marshall W., Amos, Christopher I. , Yang, Ping , Minna, John Dorrance , Zeng, Dong, Wilson, Richard K , Pinney, Susan M

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Cancer Research | March 9, 2010 | Volume: 70 | Issue: 6 | Pages: 2359-2367

10.1158/0008-5472.can-09-3096 | PMID 20215501 Get It

Abstract Cigarette smoking is the major cause for lung cancer, but genetic factors also affect susceptibility. We studied families that included multiple relatives affected by lung cancer. Results from linkage analysis showed strong evidence that a region of chromosome 6q affects lung cancer risk. To characterize the effects that this region of chromosome 6q region has on lung cancer risk, we identified a haplotype that segregated with lung cancer. We then performed Cox regression analysis to estimate the differential effects that smoking behaviors have on lung cancer risk according to whether each individual carried a risk-associated haplotype or could not be classified and was assigned unknown haplotypic status. We divided smoking exposures into never smokers, light smokers (<20 pack-years), moderate smokers (20 to <40 pack-years), and heavy smokers (≥40 pack-years). Comparing results according to smoking behavior stratified by carrier status, compared with never smokers, there was weakly increasing risk for increasing smoking behaviors, with the hazards ratios being 3.44, 4.91, and 5.18, respectively, for light, moderate, or heavy smokers, whereas among the individuals from families without the risk haplotype, the risks associated with smoking increased strongly with exposure, the hazards ratios being, respectively, 4.25, 9.17, and 11.89 for light, moderate, and heavy smokers. The never smoking carriers had a 4.71-fold higher risk than the never smoking individuals without known risk haplotypes. These results identify a region of chromosome 6q that increases risk for lung cancer and that confers particularly higher risks to never and light smokers. Cancer Res; 70(6); 2359–67