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Record W4393071125 · doi:10.1158/1538-7445.am2024-3341

Abstract 3341: Targeting CXCR4 via the small molecule inhibitor NMX1 as a therapeutic strategy to treat high-risk malignancies

2024· article· en· W4393071125 on OpenAlexaff
Patrick Sipila, Son Tran, Chunfen Zhang, Laura G. Corral, Kyle Chan, Cathy A. Swindlehurst, Aru Narendran

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicChemokine receptors and signaling
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPharmacologyMedicineCXCR4ImmunologyChemokineInflammation

Abstract

fetched live from OpenAlex

Abstract Introduction: Cytokines are secreted by various cells of the immune system, endothelium, and stroma that play a critical role in cell survival. The activation of C-X-C chemokine receptor type 4 (CXCR4) by its ligand SDF-1 leads to signaling by the AKT and mTOR pathways. CXCR4 is highly expressed in several types of cancer and contributes to tumor growth, metastasis, and resistance to therapy. Interleukin 11 (IL-11) is a cytokine that often drives disease progression, as well as contributing to tumor immune evasion. NMX1 (NovoMedix) is a novel oral small molecule that inhibits mTOR signaling, CXCR4 expression, IL-11 secretion, and activates AMPK. In animal models of breast cancer, NMX1 effectively prevented tumor growth and metastasis, while also protecting from doxorubicin-induced cardiotoxicity. In this study, we investigated the anticancer activity of NMX1 in preclinical models of high-risk pediatric and adult malignancies. Methods: Cell viability assays using alamar blue were performed in a panel of pediatric and adult cancer cells, including leukemia, brain, breast, lung, neuroblastoma, and sarcoma. Cells were treated with increasing concentrations of NMX1 ranging from 250 nM to 16 µM for 96 hours, followed by determination of half maximal inhibitory concentrations (IC50). To validate target modulation, the level of IL-11 and CXCR4 was determined by ELISA and immunoblot, respectively. Protein kinase activity was assessed by phosphorylation levels. Induction of apoptosis was confirmed by caspase-mediated PARP cleavage. To identify effective drug combinations, NMX1-treated cells were screened with a comprehensive drug library. Synergy was evaluated in the top candidates by dose-response matrices and SynergyFinder. Safety and tolerability was tested in animal models. Results: NMX1 treatment induced cytotoxicity at micromolar concentrations in diverse types of cancer, with IC50 values ranging from 0.2-8.7 µM and 0.4-4.4 µM for leukemia and solid tumor cells, respectively. NMX1 induced cancer cell death by PARP cleavage and apoptosis. Mechanistically, CXCR4 expression, mTOR signaling, and IL-11 secretion were decreased upon treatment with NMX1, validating effective target modulation. The drug combination screen identified several candidates in a tumor type-dependent manner. Synergistic effects were observed using NMX1 combined with clinically relevant concentrations of rucaparib, linsitinib, and crizotinib, which target PARP, IGFR, and c-MET, respectively. Conclusions: Our study shows antitumor activity by NMX1 through inhibition of CXCR4, IL-11, and mTOR signaling, providing an effective therapeutic strategy for high-risk and refractory malignancies. Preclinical data on feasible drug combinations and biological correlates of activity support development of early phase clinical studies involving NMX1. Citation Format: Patrick Sipila, Son Tran, Chunfen Zhang, Laura G. Corral, Kyle W. Chan, Cathy A. Swindlehurst, Aru Narendran. Targeting CXCR4 via the small molecule inhibitor NMX1 as a therapeutic strategy to treat high-risk malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3341.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.063
GPT teacher head0.380
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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