Abstract 1631: Combination of olverembatinib (HQP1351) with BCL-2 inhibitor lisaftoclax (APG-2575) overcomes resistance in gastrointestinal stromal tumors (GISTs)
Bibliographic record
Abstract
Abstract GISTs are common malignant mesenchymal tumors that occur in the GI tract, with an estimated incidence rate of 1% to 2%. About 75% to 80% of patients with GIST have mutations in the KIT gene, while 5% to 10% have mutations in the platelet-derived growth factor receptor α (PDGFRA) gene. Tyrosine kinase inhibitors (TKIs) offer patients an improved quality of life but increased pharmacological resistance to TKIs is often observed. BCL-2 is expressed in >80% of GISTs, and amplification of BCL-2 and BCL-xL are common features associated with disease progression. One approach to enhance GIST eradication is to concurrently inhibit oncogenic KIT signaling while actively engaging apoptotic pathways. Olverembatinib (HQP1351) is a new, third-generation TKI that targets BCR-ABL1, KIT and PDGFRA and is currently in development for relapsed or refractory chronic myeloid leukemia and GIST. Lisaftoclax (APG-2575) is a selective BCL-2 inhibitor under development for hematologic malignancies. The purpose of this study was to evaluate whether combining a BCL-2 inhibitor, lisaftoclax, with olverembatinib enhances treatment effect on imatinib-resistant GISTs. Compared to imatinib-sensitive GIST cell lines (GIST882 and GIST-T1), increased BCL-2 protein expression was observed in imatinib-resistant GIST cells, particularly in GIST430, GIST48, and GIST48B lines. Cell-based antiproliferation studies showed additive activity of olverembatinib and lisaftoclax in imatinib-resistant GIST cells. In vivo studies using imatinib-resistant GIST430 cell-derived xenograft models further revealed that coadministration of olverembatinib at 15 mg/kg (every other day for 3 weeks) with lisaftoclax at 50 mg/kg (daily for 3 weeks) resulted in enhanced antitumor effects compared to either agent alone. Tumor growth inhibition (TGI) rates for combined treatment with olverembatinib and lisaftoclax reached 76.8%, which was superior to the TGI rate of either agent alone: 57.6% and 31.2% for olverembatinib and lisaftoclax, respectively. Regarding putative mechanisms, olverembatinib treatment was shown to downregulate BCL-xL and MCL-1 protein expression, possibly via inhibition of KIT signal pathway and downstream signal transducer and activator of transcription 3 (STAT3). Lisaftoclax triggered apoptosis by disrupting the BCL-2:BIM complex. Therefore, selective inhibition of BCL-2, aided by TKI-mediated MCL-1 and BCL-XL inhibition, markedly augmented cleavage of caspase-3 and poly (ADP-ribose) polymerase 1 (PARP-1), thus triggering apoptosis and subsequently enhancing antitumor effects. Our results demonstrate that olverembatinib and BCL-2 inhibitor lisaftoclax have additive antitumor effects in imatinib-resistant GIST. This novel dual approach may have the potential for treating patients with GISTs whose disease has progressed after treatment with TKIs. Citation Format: Ping Min, Guangfeng Wang, Eric Liang, Bingxing Wu, Huidan Yu, Dajun Yang, Yifan Zhai. Combination of olverembatinib (HQP1351) with BCL-2 inhibitor lisaftoclax (APG-2575) overcomes resistance in gastrointestinal stromal tumors (GISTs) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1631.
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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) | 0.003 | 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".