Abstract LB-A06: A high-throughput functional screen discovered that endogenous DNA damage underlies mechanisms of selected gene susceptibility factors predisposing to lung cancer
Bibliographic record
Abstract
Abstract Genome and transcriptome-wide association studies (GWAS and TWAS) have been successful in identifying genetic variants and candidate causal genes associated with lung cancer. However, systematic identification and functional studies of these genes remains a major bottleneck to clinical translation. Endogenous DNA damage has been implicated in genome instability and carcinogenesis, and we have recently discovered large networks of DNA damage-up proteins that are mostly non-DNA repair proteins [Xia J et al., Cell 176 (2019): 127–143], with many more predicted. Here, we validated several lung cancer-associated genes from GWAS and TWAS as DNA damage-up genes, which can potentially explain the cause of gene susceptibility to lung cancer. We performed a comprehensive exome-wide association study and TWAS analysis of the GWAS-nominated loci using expression quantitative trait loci (eQTL) analysis, which revealed many new candidate causal genes for lung cancer. We further tested endogenous DNA damage levels for many of these candidates using high-throughput cell-based assays and discovered that an alteration of the expression levels of multiple genes elevates the endogenous DNA damage, which is an early biomarker for genome instability and cancer. In our recent comprehensive TWAS, we mapped seventeen candidate-causal genes among previously described lung cancer GWAS loci. These include a new susceptibility locus for lung adenocarcinoma with AQP3 as the underlying causal gene and a new susceptibility gene, NEXN, for lung cancer in never-smokers. Additionally, we discovered that IREB2 is the gene most strongly associated with lung cancer on chromosome 15q25. In a separate study, we found that KIAA0930 was overproduced across multiple cancer types, including lung cancer. We used high-throughput cell-based assays and showed that overproduction of AQP3 or KIAA0930 elevated endogenous DNA damage in the lung fibroblast cell line and in kidney epithelial cells, which suggests a pan-cancer phenotype. Additionally, knocking down IREB2 increases spontaneous DNA damage in the lung fibroblast cell line, but this was not observed by knocking down NEXN. We are also implementing unbiased pooled screenings for other functional readouts. We established a functional validation platform that measures endogenous DNA damage for lung cancer susceptibility genes, and more importantly, this functional pipeline can be generalized to other cancers or diseases. Our discovery will potentially annotate many GWAS and TWAS genes as DNA damage-up genes and assign their cancer-driving roles to genome instability. Citation Format: Jun Xia, Zhuoyi Song, Xuemei Ji, James Mckay, Yohan Bossé, Christopher I Amos. A high-throughput functional screen discovered that endogenous DNA damage underlies mechanisms of selected gene susceptibility factors predisposing to lung cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr LB-A06. doi:10.1158/1535-7163.TARG-19-LB-A06
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".