Evaluating Germline Testing Panels in Southern African Males With Advanced Prostate Cancer
Bibliographic record
Abstract
BACKGROUND: Germline testing for prostate cancer is on the increase, with clinical implications for risk assessment, treatment, and management. Regardless of family history, NCCN recommends germline testing for patients with metastatic, regional, very-high-risk localized, and high-risk localized prostate cancer. Although African ancestry is a significant risk factor for aggressive prostate cancer, due to a lack of available data no testing criteria have been established for ethnic minorities. PATIENTS AND METHODS: Through deep sequencing, we interrogated the 20 most common germline testing panel genes in 113 Black South African males presenting with largely advanced prostate cancer. Bioinformatic tools were then used to identify the pathogenicity of the variants. RESULTS: After we identified 39 predicted deleterious variants (16 genes), further computational annotation classified 17 variants as potentially oncogenic (12 genes; 17.7% of patients). Rare pathogenic variants included CHEK2 Arg95Ter, BRCA2 Trp31Arg, ATM Arg3047Ter (2 patients), and TP53 Arg282Trp. Notable oncogenic variants of unknown pathogenicity included novel BRCA2 Leu3038Ile in a patient with early-onset disease, whereas patients with FANCA Arg504Cys and RAD51C Arg260Gln reported a family history of prostate cancer. Overall, rare pathogenic and early-onset or familial-associated oncogenic variants were identified in 6.9% (5/72) and 9.2% (8/87) of patients presenting with a Gleason score ≥8 or ≥4 + 3 prostate cancer, respectively. CONCLUSIONS: In this first-of-its-kind study of southern African males, we provide support of African inclusion for advanced, early-onset, and familial prostate cancer genetic testing, indicating clinical value for 30% of current gene panels. Recognizing current panel limitations highlights an urgent need to establish testing guidelines for men of African ancestry. We provide a rationale for considering lowering the pathologic diagnostic inclusion criteria and call for further genome-wide interrogation to ensure the best possible African-relevant prostate cancer gene panel.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".