BRCAness, SLFN11, and RB1 loss predict response to topoisomerase I inhibitors in triple-negative breast cancers
Bibliographic record
Abstract
Topoisomerase I (TOP1) inhibitors trap TOP1 cleavage complexes resulting in DNA double-strand breaks (DSBs) during replication, which are repaired by homologous recombination (HR). Triple-negative breast cancer (TNBC) could be eligible for TOP1 inhibitors given the considerable proportion of tumors with a defect in HR-mediated repair (BRCAness). The TOP1 inhibitor irinotecan was tested in 40 patient-derived xenografts (PDXs) of TNBC. BRCAness was determined with a single-nucleotide polymorphism (SNP) assay, and expression of Schlafen family member 11 (SLFN11) and retinoblastoma transcriptional corepressor 1 (RB1) was evaluated by real-time polymerase chain reaction (RT-PCR) and immunohistochemistry analyses. In addition, the combination of irinotecan and the ataxia telangiectasia and Rad3-related protein (ATR) inhibitor VE-822 was tested in SLFN11-negative PDXs, and two clinical non-camptothecin TOP1 inhibitors (LMP400 and LMP776) were tested. Thirty-eight percent of the TNBC models responded to irinotecan. BRCAness combined with high SLFN11 expression and RB1 loss identified highly sensitive tumors, consistent with the notion that deficiencies in cell cycle checkpoints and DNA repair result in high sensitivity to TOP1 inhibitors. Treatment by the ATR inhibitor VE-822 increased sensitivity to irinotecan in SLFN11-negative PDXs and abolished irinotecan-induced phosphorylation of checkpoint kinase 1 (CHK1). LMP400 (indotecan) and LMP776 (indimitecan) showed high antitumor activity in BRCA1-mutated or BRCAness-positive PDXs. Last, low SLFN11 expression was associated with poor survival in 250 patients with TNBC treated with anthracycline-based chemotherapy. In conclusion, a substantial proportion of TNBC respond to irinotecan. BRCAness, high SLFN11 expression, and RB1 loss are highly predictive of response to irinotecan and the clinical indenoisoquinoline TOP1 inhibitors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".