11. |
- Li, Yafang, et al.
(author)
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Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk
- 2022
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In: Human Molecular Genetics. - : Oxford University Press. - 0964-6906 .- 1460-2083. ; 31:16, s. 2831-2843
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Journal article (peer-reviewed)abstract
- Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.
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12. |
- Li, Yafang, et al.
(author)
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Lung cancer in ever- and never-smokers : findings from multi-population GWAS studies
- 2024
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In: Cancer Epidemiology, Biomarkers and Prevention. - : American Association For Cancer Research (AACR). - 1055-9965 .- 1538-7755. ; 33:3, s. 389-399
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Journal article (peer-reviewed)abstract
- BACKGROUND: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer.METHODS: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer.RESULTS: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior.CONCLUSIONS: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. IMPACT: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.
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13. |
- Lindström, Sara, et al.
(author)
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Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions
- 2023
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In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 115:6, s. 712-732
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Journal article (peer-reviewed)abstract
- BACKGROUND: The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci.METHODS: We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci.RESULTS: We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci.CONCLUSIONS: Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.
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14. |
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15. |
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16. |
- Zhao, Xiaoyu, et al.
(author)
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Identification of genetically predicted DNA methylation markers associated with non–small cell lung cancer risk among 34,964 cases and 448,579 controls
- 2024
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In: Cancer. - : John Wiley & Sons. - 0008-543X .- 1097-0142. ; 130:6, s. 913-926
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Journal article (peer-reviewed)abstract
- Background: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non–small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated.Methods: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways.Results: Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10−6) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10−3), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified.Conclusions: Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby.Plain Language Summary: The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non–small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.
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18. |
- Bosse, Yohan, et al.
(author)
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Transcriptome-wide association study reveals candidate causal genes for lung cancer
- 2020
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In: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 146:7, s. 1862-1878
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Journal article (peer-reviewed)abstract
- We have recently completed the largest GWAS on lung cancer including 29,266 cases and 56,450 controls of European descent. The goal of our study has been to integrate the complete GWAS results with a large‐scale expression quantitative trait loci (eQTL) mapping study in human lung tissues (n = 1,038) to identify candidate causal genes for lung cancer. We performed transcriptome‐wide association study (TWAS) for lung cancer overall, by histology (adenocarcinoma, squamous cell carcinoma and small cell lung cancer) and smoking subgroups (never‐ and ever‐smokers). We performed replication analysis using lung data from the Genotype‐Tissue Expression (GTEx) project. DNA damage assays were performed in human lung fibroblasts for selected TWAS genes. As expected, the main TWAS signal for all histological subtypes and ever‐smokers was on chromosome 15q25. The gene most strongly associated with lung cancer at this locus using the TWAS approach was IREB2 (pTWAS = 1.09E−99), where lower predicted expression increased lung cancer risk. A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (pTWAS = 3.72E−6). Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3‐adenocarcinoma on 9p13.3 was replicated using GTEx (pTWAS = 6.55E−5). Consistent with the effect of risk alleles on gene expression levels, IREB2 knockdown and AQP3 overproduction promote endogenous DNA damage. These findings indicate genes whose expression in lung tissue directly influences lung cancer risk.
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19. |
- Byun, Jinyoung, et al.
(author)
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Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer
- 2022
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In: Nature Genetics. - : Nature Research. - 1061-4036 .- 1546-1718. ; 54:8, s. 1167-1177
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Journal article (peer-reviewed)abstract
- To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.
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20. |
- Dai, Juncheng, et al.
(author)
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Genome-wide association study of INDELs identified four novel susceptibility loci associated with lung cancer risk
- 2020
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In: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 146:10, s. 2855-2864
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have identified 45 susceptibility loci associated with lung ncer. Only less than SNPs, small insertions and deletions (INDELs) are the second most abundant netic polymorphisms in the human genome. INDELs are highly associated with multiple human seases, including lung cancer. However, limited studies with large-scale samples have been available to stematically evaluate the effects of INDELs on lung cancer risk. Here, we performed a large-scale meta- alysis to evaluate INDELs and their risk for lung cancer in 23,202 cases and 19,048 controls. Functional notations were performed to further explore the potential function of lung cancer risk INDELs. nditional analysis was used to clarify the relationship between INDELs and SNPs. Four new risk loci re identified in genome-wide INDEL analysis (1p13.2: rs5777156, Insertion, OR = 0.92, p = 9.10 x 10(- ; 4q28.2: rs58404727, Deletion, OR = 1.19, p = 5.25 x 10(-7); 12p13.31: rs71450133, Deletion, OR = 09, p = 8.83 x 10(-7); and 14q22.3: rs34057993, Deletion, OR = 0.90, p = 7.64 x 10(-8)). The eQTL alysis and functional annotation suggested that INDELs might affect lung cancer susceptibility by gulating the expression of target genes. After conducting conditional analysis on potential causal SNPs, e INDELs in the new loci were still nominally significant. Our findings indicate that INDELs could be tentially functional genetic variants for lung cancer risk. Further functional experiments are needed to tter understand INDEL mechanisms in carcinogenesis.
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