Abstract 1203: Identification of 22 novel loci associated with susceptibility to testicular germ cell tumors
Bibliographic record
Abstract
Abstract Background: Testicular germ cell tumors (TGCT) are the most common cancers in young men of European ancestry aged 20 to 39 years. The incidence of TGCT has doubled over the past 20 years, yet no robust environmental risk factors for disease have been identified. Although TGCTs are treatable by surgery, radiation, and platinum-based chemotherapy, multiple long-term toxicities of treatment often occur impacting morbidity and mortality. Due to their high heritability and homogenous cell of origin, TGCTs are well suited to genome-wide association methods. The Testicular Cancer Consortium (TECAC) has brought together the largest genome-wise association study (GWAS) study of TGCT to date. Methods: We conducted a GWAS of 5,602 cases and 5,006 controls aggregated from 12 locations in the US and Europe. Logistic regression models adjusted for study center and genomic ancestry. Genotypes were imputed against the Human Haplotype Reference Consortium. Meta-analysis was performed to combine GWAS results with summary statistics from five previously published TGCT studies, UK Biobank, deCODE Genetics, and an independent set of cases and controls, for a total of 10,156 cases and 179,683 controls. Biologic function of loci was explored using PAINTOR annotated with ATAC-seq data of four TGCT cell lines, SPATIAL-seq data of the NTERA2 TGCT cell-line, and publicly available data from ENCODE. Polygenic risk scores (PRS) were computed using subject-level data from the 5,602 cases and 5,006 controls, and effect sizes of the novel hits derived from the meta-analysis. Results: 22 novel and 45 previously reported loci associated with TGCT surpassed genome-wide significance (p < 5e-08). We discovered additional markers in known susceptibility loci and identified novel regions associated with germ cell development and sex determination (e.g., BCL11, AR), immune function (e.g., TNXB, ITIH5), and for the first time identified genes associated with kinetochore activity (e.g., PPP2R5A, ANAPC2). All identified risk SNPs to date account for 42.3% of heritability. Men in the highest 1% of PRS had over a 15-fold increased risk of TGCT compared to those at the median PRS, and PRS overall had an AUC of 74.29%. Conclusions: Results from our TGCT meta-analysis continue to provide insights into biological pathways affecting germ cell specification, expression, and epigenetic reprogramming, and sex determination. Our results also uniquely place TGCT as the only cancer type in which inherited variants implicating kinetochore activity, critical for chromosomal segregation, have been identified. Citation Format: John Pluta, Louisa Pyle, Timothy Bishop, Javier Benitez, Victoria Cortessis, Alberto Ferlin, Jourik Gietema, Mark Greene, Thomas Grotmol, Ramneek Gupta, Robert Hamilton, Michelle Hildebrandt, Lambertus Kiemeney, Davor Lessel, Thorunn Rafnar, Lorenzo Richiardi, Rolf Skotheim, Clare Turnbull, Fredrik Wiklund, Tongzhang Zheng, Ewa Rajpert- De Meyts, Stephen Schwartz, Katherine McGlynn, Peter Kanetsky, Katherine Nathanson. Identification of 22 novel loci associated with susceptibility to testicular germ cell tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1203.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 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) | 0.007 | 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".