• Fine mapping of MHC region in lung cancer highlights independent susceptibility loci by ethnicity.

      Ferreiro-Iglesias, Aida; Lesseur, Corina; McKay, James; Hung, Rayjean J; Han, Younghun; Zong, Xuchen; Christiani, David; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; et al. (2018-09-25)
      Lung cancer has several genetic associations identified within the major histocompatibility complex (MHC); although the basis for these associations remains elusive. Here, we analyze MHC genetic variation among 26,044 lung cancer patients and 20,836 controls densely genotyped across the MHC, using the Illumina Illumina OncoArray or Illumina 660W SNP microarray. We impute sequence variation in classical HLA genes, fine-map MHC associations for lung cancer risk with major histologies and compare results between ethnicities. Independent and novel associations within HLA genes are identified in Europeans including amino acids in the HLA-B*0801 peptide binding groove and an independent HLA-DQB1*06 loci group. In Asians, associations are driven by two independent HLA allele sets that both increase risk in HLA-DQB1*0401 and HLA-DRB1*0701; the latter better represented by the amino acid Ala-104. These results implicate several HLA-tumor peptide interactions as the major MHC factor modulating lung cancer susceptibility.
    • Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development.

      Li, Yafang; Xiao, Xiangjun; Bossé, Yohan; Gorlova, Olga; Gorlov, Ivan; Han, Younghun; Byun, Jinyoung; Leighl, Natasha; Johansen, Jakob S; Barnett, Matt; et al. (2019-03-05)
      The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in
    • Genome-wide interaction study of smoking behavior and non-small cell lung cancer risk in Caucasian population

      Li, Yafang; Xiao, Xiangjun; Han, Younghun; Gorlova, Olga; Qian, David; Leighl, Natasha; Johansen, Jakob S; Barnett, Matt; Chen, Chu; Goodman, Gary; et al. (2018-03)
      Non-small cell lung cancer is the most common type of lung cancer. Both environmental and genetic risk factors contribute to lung carcinogenesis. We conducted a genome-wide interaction analysis between single nucleotide polymorphisms (SNPs) and smoking status (never- versus ever-smokers) in a European-descent population. We adopted a two-step analysis strategy in the discovery stage: we first conducted a case-only interaction analysis to assess the relationship between SNPs and smoking behavior using 13336 non-small cell lung cancer cases. Candidate SNPs with P-value <0.001 were further analyzed using a standard case-control interaction analysis including 13970 controls. The significant SNPs with P-value <3.5 × 10-5 (correcting for multiple tests) from the case-control analysis in the discovery stage were further validated using an independent replication dataset comprising 5377 controls and 3054 non-small cell lung cancer cases. We further stratified the analysis by histological subtypes. Two novel SNPs, rs6441286 and rs17723637, were identified for overall lung cancer risk. The interaction odds ratio and meta-analysis P-value for these two SNPs were 1.24 with 6.96 × 10-7 and 1.37 with 3.49 × 10-7, respectively. In addition, interaction of smoking with rs4751674 was identified in squamous cell lung carcinoma with an odds ratio of 0.58 and P-value of 8.12 × 10-7. This study is by far the largest genome-wide SNP-smoking interaction analysis reported for lung cancer. The three identified novel SNPs provide potential candidate biomarkers for lung cancer risk screening and intervention. The results from our study reinforce that gene-smoking interactions play important roles in the etiology of lung cancer and account for part of the missing heritability of this disease.
    • Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study.

      Carreras-Torres, Robert; Johansson, Mattias; Haycock, Philip C; Wade, Kaitlin H; Relton, Caroline L; Martin, Richard M; Davey Smith, George; Albanes, Demetrius; Aldrich, Melinda C; Andrew, Angeline; et al. (2017)
      Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer.