A brief overview of homologous recombination deficiency testing in cancers for the ‘Next-Generation’ Pathologist
Bibliographic record
Abstract
Genomic instability is one of the hallmarks of cancer, having a crucial role in cancer pathogenesis as well as tumor proliferation. This essential feature is secondary to dysregulation of DNA damage repair pathways. Homologous repair represents the most reliable double-strand break repair mechanism. Homologous recombination deficiency is responsible for generating and perpetuating DNA damage in cancer, posing an opportunity for targeting treatment with poly(ADP-ribose) polymerase inhibitors through ‘synthetic lethality’, as well as platinum-based agents. Comprehensive genomic analysis has made it possible to discover molecular biomarkers that assist in the identification of Homologous recombination deficient tumors, allowing for the expansion of such treatment strategies to various other malignancies. Leveraging the improvement of genomic analysis methods to be more efficient in identifying Homologous recombination deficiency is crucial in the advancement of cancer care. The current review highlights the current strategies for Homologous recombination deficiency detection, clinical implications, limitations, and applicability.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".