Abstract P87: Combined therapy with CRIF1/CDK2 interface inhibitor and Taxol against Triple-Negative Breast Cancer
Bibliographic record
Abstract
Abstract A chemotherapeutic agent, Paclitaxel (Taxol), remains the standard of care for the lethal triple-negative breast cancer (TNBC). However, over 50% of TNBC patients become resistant to chemotherapy typically after 6–10 months of treatment. To date, no solution is available. CR6-interacting factor 1 (CRIF1) is reported to act as a negative regulator of the cell cycle by interacting with cyclin-dependent kinase 2 (CDK2). In our study, two selective CRIF1–CDK2 interface inhibitors [4-(4-methylphenyl)-N-[3-(morpholin-4-yl)propyl]phthalazin-1-amine; bis(oxalic acid) and N-[2-(benzylsulfanyl)ethyl]-3-{1-[(3-nitrophenyl)methyl]-2,4-dioxo-1,2,3,4-tetrahydroquinazolin-3-yl}propanamide] were obtained by molecular modeling and docking and then used to investigate whether they could exert anti-proliferative activity on the TNBC cell lines. When combined with Taxol treatment, these two inhibitors are able to advance the cells from G0/G1 to S and G2/M phases, producing irreparable damage to the cells, which then undergo apoptosis. Moreover, they enhanced the reduction in cell proliferation induced by Taxol in TNBC cells, thereby improving sensitivity to Taxol in these cell lines. It is important that the inhibitors did not regulate the cell cycle in normal cells, indicating their high selectivity towards TNBC cells. The resistance to the anti-proliferative effects induced by Taxol can thus be significantly reduced by the combined treatment with selective CRIF1–CDK2 interface inhibitors, making a conceptual advance in the CDK-related cancer treatment. Animal assay will be carried out with improved interface inhibitors. Citation Format: Xiaoye Sang, Nassira Belmessabih, Ruixuan Wang, Preyesh Stephen & Sheng-Xiang Lin. Combined therapy with CRIF1/CDK2 interface inhibitor and Taxol against Triple-Negative Breast Cancer [abstract]. In: Proceedings of Frontiers in Cancer Science 2024; 2024 Nov 13-15; Singapore. Philadelphia (PA): AACR; Cancer Res 2025;85(15_Suppl):Abstract nr P87.
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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".