Targeting FEN1/EXO1 to enhance efficacy of PARP inhibition in triple-negative breast cancer
Bibliographic record
Abstract
• FEN1/EXO1 inhibition enhances PARP inhibition (PARPi) efficacy in 7/10 TNBC cell lines. • PARPi and FEN1/EXO1 inhibition synergize in PARPi-resistant cell lines and organoids that are BRCA1/2 wild-type. • FEN1/EXO1 inhibition sensitizes cell lines with acquired resistance to PARPi. • Synergy is mediated by enhanced DNA damage and DNA replication fork speed. Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. The only targeted therapeutic approach that has emerged for early TNBC patients with BRCA-mutations (BRCA MUT ) are PARP inhibitors (PARPi). In combination, PARPi may benefit a larger cohort of TNBC patients. We used our previously identified 63-gene signature that was associated with PARPi response to identify candidate genes that could be therapeutic targets. We selected FEN1 for further investigation since its knockdown was associated with an increase in G2/M arrest, DNA damage, and apoptosis. We first tested LNT1, a FEN1/EXO1 inhibitor, in a panel of 10 TNBC cell lines. LNT1 sensitivity was identified predominantly in BRCA1 -mutant/deficient cell lines. However, the combination of PARPi and LNT1 demonstrated a synergistic or additive effect in 7/10 cell lines, mainly in BRCA1/2 wild-type (BRCA WT ) and BRCA2 -mutant cell lines, with intrinsic and acquired resistance to PARPi. The greatest synergy was observed in a BRCA2 -mutant cell line with acquired resistance to olaparib (HCC1395-OlaR), with a combination index value of 0.20. In the synergistic cell lines, BT549 (BRCA WT ) and HCC1395-OlaR, the combination was associated with a rapid progression in DNA replication fork speed, an early and sustained increase in DNA damage in comparison to each of the single-agents. However, in the additive BRCA1/2 wild-type cell lines, MDAMB231 and HCC1806, the combination demonstrated a high DNA damage response that was largely driven by either talazoparib or LNT1. Therefore, targeting FEN1/EXO1 with PARPi is a promising targeted combination approach, particularly in the context of PARPi-resistant and BRCA WT TNBC.
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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 | 0.000 | 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".