| 21. |
- Qin, Na, et al.
(författare)
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Comprehensive functional annotation of susceptibility variants identifies genetic heterogeneity between lung adenocarcinoma and squamous cell carcinoma
- 2021
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Ingår i: Frontiers of Medicine. - : Springer-Verlag New York. - 2095-0217 .- 2095-0225. ; 15:2, s. 275-291
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Tidskriftsartikel (refereegranskat)abstract
- Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer (NSCLC) risk, biological mechanisms of these variants remain largely unknown. By integrating a large-scale genotype data of 15 581 lung adenocarcinoma (AD) cases, 8350 squamous cell carcinoma (SqCC) cases, and 27 355 controls, as well as multiple transcriptome and epigenomic databases, we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility variants. We identified 3064 credible risk variants for NSCLC, which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive sites. Transcription factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was SqCC-specific. Functional annotation and gene-based analysis implicated 894 target genes, including 274 specifics for AD and 123 for SqCC, which were overrepresented in somatic driver genes (ER = 1.95,P= 0.005). Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways, while SqCC genes were homologous recombination deficiency related. Our results illustrate the molecular basis of both well-studied and new susceptibility loci of NSCLC, providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.
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| 22. |
- Rosenberger, Albert, et al.
(författare)
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Gene–gene interaction of AhR with and within the Wnt cascade affects susceptibility to lung cancer
- 2022
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Ingår i: European Journal of Medical Research. - : BioMed Central (BMC). - 0949-2321 .- 2047-783X. ; 27:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Aberrant Wnt signalling, regulating cell development and stemness, influences the development of many cancer types. The Aryl hydrocarbon receptor (AhR) mediates tumorigenesis of environmental pollutants. Complex interaction patterns of genes assigned to AhR/Wnt-signalling were recently associated with lung cancer susceptibility.Aim: To assess the association and predictive ability of AhR/Wnt-genes with lung cancer in cases and controls of European descent.Methods: Odds ratios (OR) were estimated for genomic variants assigned to the Wnt agonist and the antagonistic genes DKK2, DKK3, DKK4, FRZB, SFRP4 and Axin2. Logistic regression models with variable selection were trained, validated and tested to predict lung cancer, at which other previously identified SNPs that have been robustly associated with lung cancer risk could also enter the model. Furthermore, decision trees were created to investigate variant × variant interaction. All analyses were performed for overall lung cancer and for subgroups.Results: No genome-wide significant association of AhR/Wnt-genes with overall lung cancer was observed, but within the subgroups of ever smokers (e.g., maker rs2722278 SFRP4; OR = 1.20; 95% CI 1.13–1.27; p = 5.6 × 10–10) and never smokers (e.g., maker rs1133683 Axin2; OR = 1.27; 95% CI 1.19–1.35; p = 1.0 × 10–12). Although predictability is poor, AhR/Wnt-variants are unexpectedly overrepresented in optimized prediction scores for overall lung cancer and for small cell lung cancer. Remarkably, the score for never-smokers contained solely two AhR/Wnt-variants. The optimal decision tree for never smokers consists of 7 AhR/Wnt-variants and only two lung cancer variants.Conclusions: The role of variants belonging to Wnt/AhR-pathways in lung cancer susceptibility may be underrated in main-effects association analysis. Complex interaction patterns in individuals of European descent have moderate predictive capacity for lung cancer or subgroups thereof, especially in never smokers.
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| 23. |
- Sun, Ryan, et al.
(författare)
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Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer
- 2021
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Ingår i: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 45:1, s. 99-114
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Tidskriftsartikel (refereegranskat)abstract
- Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1 beta pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-kappa B signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.
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| 24. |
- Wang, Tao, et al.
(författare)
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Pleiotropy of genetic variants on obesity and smoking phenotypes : Results from the Oncoarray Project of The International Lung Cancer Consortium
- 2017
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:9, s. 0185660-0185660
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Tidskriftsartikel (refereegranskat)abstract
- Obesity and cigarette smoking are correlated through complex relationships. Common genetic causes may contribute to these correlations. In this study, we selected 241 loci potentially associated with body mass index (BMI) based on the Genetic Investigation of ANthropometric Traits (GIANT) consortium data and calculated a BMI genetic risk score (BMI-GRS) for 17,037 individuals of European descent from the Oncoarray Project of the International Lung Cancer Consortium (ILCCO). Smokers had a significantly higher BMI-GRS than never-smokers (p = 0.016 and 0.010 before and after adjustment for BMI, respectively). The BMI-GRS was also positively correlated with pack-years of smoking (p<0.001) in smokers. Based on causal network inference analyses, seven and five of 241 SNPs were classified to pleiotropic models for BMI/smoking status and BMI/pack-years, respectively. Among them, three and four SNPs associated with smoking status and pack-years (p<0.05), respectively, were followed up in the ever-smoking data of the Tobacco, Alcohol and Genetics (TAG) consortium. Among these seven candidate SNPs, one SNP (rs11030104, BDNF) achieved statistical significance after Bonferroni correction for multiple testing, and three suggestive SNPs (rs13021737, TMEM18; rs11583200, ELAVL4; and rs6990042, SGCZ) achieved a nominal statistical significance. Our results suggest that there is a common genetic component between BMI and smoking, and pleiotropy analysis can be useful to identify novel genetic loci of complex phenotypes.
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| 25. |
- Wang, Xinan, et al.
(författare)
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Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification
- 2024
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Ingår i: Genome Medicine. - : BioMed Central (BMC). - 1756-994X .- 1756-994X. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.Methods: Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.Results: Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12–3.50, P-value = 4.13 × 10−15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99–2.49, P-value = 5.70 × 10−46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72–0.74). Conclusions: Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.
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| 26. |
- Wang, Yuzhuo, et al.
(författare)
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Association Analysis of Driver Gene-Related Genetic Variants Identified Novel Lung Cancer Susceptibility Loci with 20,871 Lung Cancer Cases and 15,971 Controls
- 2020
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 29:7, s. 1423-1429
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Tidskriftsartikel (refereegranskat)abstract
- Background: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated.Methods: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project.Results: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P < 0.001) and validation (P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 x 10(-6)). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 x 10(-3)).Conclusions: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. Impact: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.
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| 27. |
- Zhang, Ruyang, et al.
(författare)
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A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians
- 2022
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Ingår i: Journal of Thoracic Oncology. - : Elsevier. - 1556-0864 .- 1556-1380. ; 17:8, s. 974-990
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).Methods: Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.Results: With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10−13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10−13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10−13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10−13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10−4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.Conclusions: Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.
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| 28. |
- Zhao, Xiaoyu, et al.
(författare)
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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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Ingår i: Cancer. - : John Wiley & Sons. - 0008-543X .- 1097-0142. ; 130:6, s. 913-926
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Tidskriftsartikel (refereegranskat)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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| 29. |
- Zhou, Wen, et al.
(författare)
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Causal relationships between body mass index, smoking and lung cancer : Univariable and multivariable Mendelian randomization
- 2021
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Ingår i: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 148:5, s. 1077-1086
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Tidskriftsartikel (refereegranskat)abstract
- At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a positive causal effect for high BMI on occurrence of small-cell lung cancer (odds ratio (OR) = 1.60, 95% confidence interval (CI) = 1.24-2.06,P= 2.70 x 10(-4)). After adjustment of smoking behaviors using multivariable Mendelian randomization (MVMR), a direct causal effect on small cell lung cancer (ORMVMR= 1.28, 95% CI = 1.06-1.55,P-MVMR= .011), and an inverse effect on lung adenocarcinoma (ORMVMR= 0.86, 95% CI = 0.77-0.96,P-MVMR= .008) were observed. A weak increased risk of lung squamous cell carcinoma was observed for higher BMI in univariable Mendelian randomization (UVMR) analysis (ORUVMR= 1.19, 95% CI = 1.01-1.40,P-UVMR= .036), but this effect disappeared after adjustment of smoking (ORMVMR= 1.02, 95% CI = 0.90-1.16,P-MVMR= .746). These results highlight the histology-specific impact of BMI on lung carcinogenesis and imply mediator role of smoking behaviors in the association between BMI and lung cancer.
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