Abstract 2019: Synergistic anticancer activity of the RAD51 inhibitor IBR2 with inhibitors of receptor tyrosine kinases and microtubule protein
Bibliographic record
Abstract
Abstract Although cancer cell genetic instability contributes to characteristics that mediate tumorigenicity, it also contributes to the selective toxicity that some chemotherapy drugs have for cancer cells. This "synthetic lethality" (Nature 434:913, ‘05) can be enhanced by agents that inhibit DNA repair (Mol Onc 8:1429, ‘14; Proc AACR 57:3718, ‘16). To exploit this potential "Achilles heel", we tested the ability of a small molecule inhibitor of RAD51 to potentiate the cytotoxicity of established chemotherapy drugs. 2-(benzylsulfonyl)-1-(1H-indol-3-yl)-1,2-dihydroisoquinoline (IBR2) was obtained from Drs. J-W Zhu and W-H Lee (Univ. California - Irvine). IBR2 inhibits RAD51-mediated double-strand DNA break repair, but also enhances induction of apoptosis by the ABL inhibitor imatinib against K562 cells (EMBO Mol Med 5:353, ‘13). There is potential value of such synergistic interaction among other tumor types and with other drugs. IBR2-drug combinations were therefore examined across a spectrum of cancer cell lines from various tissues (AML, CML, carcinoma of breast, colon, stomach, lung, and head) representing a range of oncogenic drivers (ABL, c-kit, Raf, Ras, ER, mutant p53). Cells were exposed to IBR2 simultaneously with inhibitors of various tyrosine kinase receptors, DNA-damaging agents, or inhibitors of microtubule function. Cells were cultured in 96-well plates, exposed to drugs alone and in combination, and cell density determined by viability staining (alamarBlue or neutral red) 4 days later. Inhibition of proliferation by drug combinations was normalized to that of IBR2 alone. Depending on the drug sensitivity of the cell line, IBR2, at concentrations that inhibited proliferation between 0% and 75% as a single agent, enhanced toxicity of imatinib by up to 80%. IBR2 also greatly enhanced antiproliferative activity of regorafenib (targets RAF, kit, others), EGFR inhibitors erlotinib, gefitinib, afatinib and osimertinib, and microtubule inhibitor vincristine (VCR). However, IBR2 was antagonistic with VP-16, cisplatin, irinotecan, melphalan, and olaparib. To determine a possible mechanism of the observed synergy, the interaction between IBR2 and imatinib or VCR was compared with that between verapamil, a P-glycoprotein inhibitor, and the latter 2 drugs. The VCR-resistant head and neck cell line HN-5a/V15e was not cross-resistant to imatinib, but IBR2 enhanced imatinib toxicity in this cell line, its HN-5a parent, and HT-29 by up to 60%, much better than verapamil (up to 40% at similar concentrations, P<0.05). IBR2 enhanced VCR toxicity in these 3 lines to degree similar to verapamil, decreasing the IC50 by up to 90%. IBR2 appears to enhance drug toxicities via mechanisms other than just inhibition of RAD51 and may potentially interfere with microtubule function. The results indicate that this agent may be useful as a clinical adjuvant to numerous cytotoxic drugs. Citation Format: Peter J. Ferguson, Mark D. Vincent, James Koropatnick. Synergistic anticancer activity of the RAD51 inhibitor IBR2 with inhibitors of receptor tyrosine kinases and microtubule protein [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2019. doi:10.1158/1538-7445.AM2017-2019
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".