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Record W4414493011 · doi:10.1158/2326-6074.cimm25-a016

Abstract A016: KRASG12D inhibition enhances tumor cell sensitivity to natural killer cell-mediated cytotoxicity

2025· article· en· W4414493011 on OpenAlexaboutno aff
Hong‐Yuan Chen, Tuo Hu, Xu Chao, Liangjie Chi, Fangqin Xue, Chunbo He

Bibliographic record

VenueCancer Immunology Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topic14-3-3 protein interactions
Canadian institutionsnot available
Fundersnot available
KeywordsTumor microenvironmentImmunotherapyImmune systemNatural killer cellCancer immunotherapyLymphokine-activated killer cellCancerImmunosuppressionFlow cytometryCytotoxicity

Abstract

fetched live from OpenAlex

Abstract Introduction: KRAS^G12D mutations represent a significant oncogenic driver, prevalent in highly aggressive malignancies such as pancreatic ductal adenocarcinoma (PDAC) and colorectal cancer (CRC). The recent development of direct KRAS^G12D inhibitors has ushered in a new era of targeted therapy, offering unprecedented opportunities to address these previously intractable cancers. This study aimed to explore and optimize therapeutic strategies by thoroughly evaluating the efficacy of MRTX1133, a novel selective non-covalent KRAS^G12D inhibitor, in conjunction with various immunotherapeutic modalities, particularly those involving natural killer (NK) cells. Methods: We utilized patient-derived xenograft and syngeneic murine cancer models to systematically characterize alterations of immune landscapes within tumor microenvironment (TME) upon KRAS^G12D inhibition. Comprehensive and in-depth assessment of immune cell function and single-cell level transcriptional activity was performed using flow cytometry and single-cell RNA sequencing analysis. Results: Our findings reveal that MRTX1133 not only suppresses tumor progression but also profoundly enhances the activation of infiltrated natural killer (NK) cells within the tumor microenvironment. Functional depletion of NK cells partially, yet significantly, attenuated the anti-tumor activity of MRTX1133, underscoring the contribution of NK cells to the observed therapeutic benefit. Notably, KRAS^G12D inhibition led to a reduction in tumor-infiltrating Gr-1^+ myeloid-derived suppressor cells (MDSCs) and increased the proportion of effector NK cells. Furthermore, MRTX1133 facilitated greater intratumoral accumulation of adoptively transferred NK cells and counteracted tumor-induced systemic immunosuppression on NK cells. Combined treatment with MRTX1133 and NK cell immunotherapies produced synergistic anti-tumor effects and significantly extended survival in preclinical models. Mechanistically, ex vivo analyses demonstrated that MRTX1133 upregulates NK cell-activating ligands, including MICA/B and ULBPs, and suppresses the production of cytokines such as IL-6 and GM-CSF by cancer cells, thereby enhancing tumor cell susceptibility to NK cell-mediated cytotoxicity and reducing MDSC proliferation. Conclusion: Collectively, our results illuminate the interplay between KRAS^G12D inhibition and immuno-microenvironmental remodeling, highlighting rational combinations of targeted and NK cell-based immunotherapies as promising strategies to potentiate therapeutic responses in KRAS^G12D-driven cancers, potentially improving clinical outcomes for patients. Citation Format: Hongyuan Chen, Tuo Hu, Chao Xu; Liangjie Chi, Fangqin Xue, Chunbo He. KRASG12D inhibition enhances tumor cell sensitivity to natural killer cell-mediated cytotoxicity [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr A016.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.350
Teacher spread0.331 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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