Homologous Recombination Defects and Mutations in DNA Damage Response (DDR) Genes Besides<i>BRCA1</i>and<i>BRCA2</i>as Breast Cancer Biomarkers for PARP Inhibitors and Other DDR Targeting Therapies
Bibliographic record
Abstract
Homologous recombination repair (HRR) is the cellular mechanism for error-free repair of double strand DNA (dsDNA) breaks. Cancer cells with mutations in both alleles of genes encoding for proteins involved in HRR, such as BRCA1 and BRCA2, have defects in the repair process. As a result, these cells repair dsDNA breaks with alternative mechanisms, such as non-homologous end joining. In breast cancers with germline mutations in BRCA1 and BRCA2 genes, HRR defects result in sensitivity to PARP inhibitors, drugs that interfere with the function of PARP enzyme and promote trapping of the enzyme on DNA and stalling of the process of repairing single strand breaks. HRR defects also lead to sensitivity to DNA damaging chemotherapy due to the inability of cells to repair chemotherapy induced DNA lesions. Besides germline mutations in BRCA1 and BRCA2, somatic mutations in these genes or germline and somatic mutations or other genetic and epigenetic alterations of other genes involved in homologous recombination (HR) may produce HRR defects leading to sensitivity to PARP inhibitors. However, studies are less conclusive, a fact that may relate to the common lack of bi-allelic loss of function in these cases, as opposed to cancers with germline BRCA1 or BRCA2 defects that usually acquire bi-allelic loss of function. In addition, there is heterogeneity between the different HRR genes and the severity of the resulting HRR defects, as measured by HR defect assays. This review article examines the landscape of HRR gene mutations in breast cancer and the possible therapeutic implications of HRR defects other than germline BRCA1 and BRCA2 mutations for targeted therapies. Identification of a wider range of breast cancers with HRR defects may expand the subset of patients that derive benefit from PARP inhibitors and other DDR-targeting drugs in the clinic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".