Abstract 2569: A genome wide association study of lung cancer identifies 11 novel susceptibility loci
Bibliographic record
Abstract
Abstract Background Genome wide association studies (GWAS) of lung cancer have identified susceptibility loci at 15q25, 5p15, 6p21, 13q13 and 22q12 that contain relevant candidate genes such as CHRNA3/5, TERT, HLA, BRCA2 and CHEK2, respectively. Many of these alleles appear more relevant to a particularly histological type of lung cancer. With the aim of identifying novel lung cancer susceptibility loci, The Transdisciplinary Research in Cancer of the Lung (TRICL), the International Lung Cancer Consortium (ILCCO) and Lung Cancer Cohort Consortium (LC3) have undertaken a very large collaborative GWAS across 29 lung cancer studies, including analysis of the predominant lung cancer histological subtypes. Methods In collaboration with the Center for Disease Research (CIDR), TRICL, ILCCO and LC3 have genotyped 18,000 case-control pairs on the GAME-On Oncoarray. SNP imputation was undertaken using the 1,000 Genomes v3 reference panel, followed by logistic regression of each genetic variant with lung cancer and considering ancestry inferred by genetic profile to correct for cryptic population structure. The OncoArray and our previous GWAS results were combined using meta-analysis. This allowed for a GWAS of 10,155,682 SNPs for 25,655 lung cancer cases and 52,451 controls, as well as histology specific analysis of 6,629 squamous cell and 9,817 adenocarcinomas. Alternate genotyping techniques (Affymetrix, Taqman) were used to confirm the fidelity of the genotyping for variants of interest. Results We have identified common genetic variants exceeding genome wide significance (p<5×10-8) at eleven novel susceptibility loci. This included two associated with overall lung cancer (1p31, 19q13), eight with lung adenocarcinomas (3q28, 6p25, 8p12, 9p21, 10q25, 11q23, 15q21, 20q13) and one with squamous-cell lung carcinomas (10q24). These genetic variants are located near several intriguing candidate genes, such as telomere function genes (OBFC1, RTEL1), nicotine metabolism genes (CYP2A6), genes somatically mutated in lung cancer (NRG1) and genetic susceptibility loci linked to other cancers (IRF4, CDNK2A). In additional, we noted several borderline (p<10-6) associations with common variants located near nicotine addiction genes (CHRNB2, CHRNA2, CHRNA4, DBH) and other genes somatically translocated in lung cancer (ROS1). Integration of eQTL databases suggests that many of the associated genetic variants influence gene expression levels of these candidate genes. Conclusion We have identified eleven novel lung cancer susceptibility loci, doubling the number implicated by GWAS. These genetic variants were common (MAF 0.05-0.49) with modest to small genetic effects (OR's 1.10-1.17). Further expansion of GWAS efforts, particularly within histological subtypes of lung cancer, is likely to identify additional susceptibility loci and further increase our understanding of lung cancer aetiology. Citation Format: James Dowling Mckay, Yafang Li, Younghun Han, Xiangjun Xioa, John Field, Xuchen Zong, Heike Bickeböller, David C. Christiani, Paul Brennan, Maria-Teresa Landi, Rayjean Hung, Christopher I. Amos, on behalf of the OncoArray Lung Cancer Group. A genome wide association study of lung cancer identifies 11 novel susceptibility loci. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2569.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".