Germline Susceptibility to Renal Cell Carcinoma and Implications for Genetic Screening
Bibliographic record
Abstract
PURPOSE Genetic susceptibility to nonsyndromic renal cell carcinoma (RCC) remains poorly understood, especially for different histological subtypes, as does variations in genetic predisposition in different populations. The objectives of this study were to identify risk genes for RCC in the Canadian population, investigate their clinical significance, and evaluate variations in germline pathogenic variants (PVs) among patients with RCC across the globe. MATERIALS AND METHODS We conducted targeted sequencing of 19 RCC-related and 27 cancer predisposition genes for 960 patients with RCC from Canada and identified genes enriched in rare germline PVs in RCC compared with cancer-free controls. We combined our results with those reported for patients from Japan, the United Kingdom, and the United States to investigate PV variations in different populations. Furthermore, we evaluated the performance of referral criteria for genetic screening for including patients with rare PVs. RESULTS We identified 39 germline PVs in 56 patients (5.8%) from the Canadian cohort. Compared with cancer-free controls, PVs in CHEK2 (odds ratio [OR], 4.8 [95% CI, 2.7 to 7.9], P = 3.94 × 10−5) and ATM (OR, 4.5 [95% CI, 2.0 to 8.7], P = .016) were significantly enriched in patients with clear cell, whereas PVs in FH (OR, 215.1 [95% CI, 64.4 to 597.8], P = 6.14 × 10−9) were enriched in patients with non-clear cell RCCs. PVs in BRCA1, BRCA2, and ATM were associated with metastasis ( P = .003). Comparative analyses showed an enrichment of TP53 PVs in patients from Japan, of CHEK2 and ATM in patients from Canada, the United States and the United Kingdom, and of FH and BAP1 in the United States. CONCLUSION CHEK2, ATM, and FH are risk genes for RCC in the Canadian population, whereas PVs in BRCA1/ 2 and ATM are associated with risk of metastasis. Globally, clinical guidelines for genetic screening in RCC fail to include more than 70% of patients with rare germline PVs.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".