Combined Targeting of STAT3 and STAT5: A Novel Approach to Overcome Drug Resistance in Ph+ Cml
Bibliographic record
Abstract
Abstract Chronic myeloid leukemia (CML) is a stem cell disease characterized by BCR-ABL1. Most patients in chronic phase (CP) CML achieve long-lasting molecular responses when treated with BCR-ABL1 tyrosine kinase inhibitors (TKI). However, resistance against TKI occurs in a subset of patients. Several molecular mechanisms, including BCR-ABL1 mutations, contribute to TKI resistance. For imatinib-resistant patients, second- and third generation TKI, including nilotinib, dasatinib, bosutinib, and ponatinib, are available. Using these drugs, it is now possible to cover most of the known BCR-ABL1 mutations, including the multi-resistant mutation T315I. Ponatinib, a third generation TKI, induces growth-inhibitory effects in drug-resistant patients even if T315I is expressed. However, not all mutant forms of BCR-ABL1 are responsive to ponatinib. Moreover, it has been described that multiple secondary mutations in BCR-ABL1, especially T315I-involving compound mutations, confer resistance against ponatinib. Furthermore, resistance against TKI may develop independent of BCR-ABL1 mutations. Therefore, drug combinations covering a broad range of targets, are currently under investigation with the aim to overcome drug resistance in advanced CML. Bardoxolone methyl (CDDO-Me) is an oleanane triterpenoid that has been described to induce ROS generation and to suppress a number of survival-related molecules, including AKT, mTOR, and STAT3. The aim of the current project was to evaluate the anti-leukemic effects of CDDO-Me in TKI-resistant CML cells. As assessed by 3H-thymidine uptake experiments, CDDO-Me was found to inhibit growth of various CML cell lines, including K562, an imatinib resistant sub-clone of K562, KU812, and imatinib-resistant KCL22 cells (IC50: 0.1-0.5 µM). These effects were accompanied by induction of apoptosis as assessed by staining for AnnexinV and propidium iodide. Furthermore, CDDO-Me was found to block the growth of Ba/F3 cells harboring the BCR-ABL1 mutations T315I, E255K, G250E, H396P, or F359V as well as Ba/F3 cells expressing TKI-resistant compound mutations, such as T315I/E255V, T315I/F311L, T315I/F359V, or T315I/G250E (IC50: 0.1-0.25 µM). The anti-proliferative effects of CDDO-Me were also confirmed in primary CML cells isolated from 13 patients with chronic phase (CP) CML (4 TKI-resistant patients, 3 with BCR-ABL1 mutations), one in blast phase (BP), and one suffering from ponatinib-resistant Ph+ ALL harboring BCR-ABL1T315I/E255K. IC50 values were comparable between samples isolated from freshly diagnosed patients (IC50: 0.1-0.5 µM) and samples isolated from heavily pre-treated patients, (IC50: 0.1-0.5 µM) suggesting that BCR-ABL1 mutations do not influence responses to this drug. In consecutive experiments, CDDO-Me was found to produce synergistic growth-inhibitory effects when combined with second- or third-generation BCR-ABL1 TKI. The combination ´CDDO-Me+ponatinib´ was found to be effective in Ba/F3 cells expressing various BCR-ABL1 mutations, including T315I-involving compound mutations. We also found that the combination ´CDDO-Me+TKI´ leads to simultaneous dephosphorylation of STAT3 and STAT5. To clarify whether this drug action contributes to the synergistic drug-interactions observed, we performed experiments with shRNA directed against STAT3 or STAT5 and the specific STAT5-inhibitor AC-3-019. Knockdown of STAT3 was found to produce synergistic effects with TKI and with AC-3-019 in K562 and KCL22 cells, whereas STAT5-knockdown sensitized CML cells against CDDO-Me, pointing to a new effective concept of dual STAT3+STAT5 inhibition. However, CDDO-Me was also found to increase expression of heme-oxygenase-1 (HO-1), a heat-shock-protein known to trigger drug resistance and cell survival in CML cells. We therefore combined CDDO-Me with the HO-1 inhibitor SMA-ZnPP, which also resulted in synergistic growth-inhibitory effects in human CML cells and BCR-ABL1+Ba/F3 cells. Moreover, SMA-ZnPP was found to sensitize KU812 cells and Ba/F3 cells expressing BCR-ABL1T315I/F311L against the combination ´CDDO-Me+TKI´. Together, combined targeting of STAT3, STAT5, and HO-1 overcomes multiple forms of TKI resistance in highly resistant CML clones expressing BCR-ABL1T315I or T315I-containing compound mutations. Whether such drug combinations are effective in vivo in TKI-resistant patients remains to be elucidated. Disclosures Hoermann: Ariad: Honoraria; Gilead: Research Funding; Amgen: Honoraria; Novartis: Honoraria. Konopleva:Reata Pharmaceuticals: Equity Ownership; Abbvie: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; Stemline: Consultancy, Research Funding; Eli Lilly: Research Funding; Cellectis: Research Funding; Calithera: Research Funding. Deininger:Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Incyte: Consultancy, Membership on an entity's Board of Directors or advisory committees; CTI BioPharma Corp.: Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Research Funding; Gilead: Research Funding; Celgene: Research Funding; Bristol Myers Squibb: Consultancy, Research Funding; Ariad: Consultancy, Membership on an entity's Board of Directors or advisory committees. Lion:Amgen: Honoraria; Pfizer: Honoraria; Ariad: Honoraria; Novartis: Honoraria, Research Funding; BMS: Honoraria. Valent:Ariad: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Deciphera Pharmaceuticals: Research Funding; Amgen: Honoraria.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".