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Record W4408881986 · doi:10.1136/jitc-2024-010791

Oxaliplatin, ATR inhibitor and anti-PD-1 antibody combination therapy controls colon carcinoma growth, induces local and systemic changes in the immune compartment, and protects against tumor rechallenge in mice

2025· article· en· W4408881986 on OpenAlexaff
Alexandra Fauvre, Chiara Ursino, Véronique Garambois, Elodie Culerier, Louis-Antoine Milazzo, Nadia Vezzio-Vié, Laura Jeanson, Candice Marchive, Augusto Faria Andrade, Eve Combès, Salima Atis, Gérald Lossaint, François Quénet, Henri‐Alexandre Michaud, Lakhdar Khellaf, Iléana Corbeau, Diégo Tosi, Nadine Houédé, Nathalie Bonnefoy, Olivia Sgarbură, Céline Gongora, Julien Faget

Bibliographic record

VenueJournal for ImmunoTherapy of Cancer · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineOxaliplatinCancer researchColorectal cancerTumor microenvironmentImmune systemAntibodyCancerImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Background Colorectal cancer (CRC) is the third most common cancer type and one of the leading causes of cancer-related death worldwide. The treatment of advanced metastatic CRC relies on classical chemotherapy combinations (5-fluorouracil, oxaliplatin or irinotecan). However, their use is limited by the emergence of resistance mechanisms, including to oxaliplatin. In this context, we recently showed that the combination of oxaliplatin and ataxia telangiectasia and Rad3-related protein inhibition (VE-822) is synergistic and may have a potential therapeutic effect in metastatic CRC management. Methods In this study, we investigated the role of the VE-822+oxaliplatin (Vox) combination on the immune response and its potential synergy with an anti-programmed-cell Death receptor-1 (PD-1) antibody. We used cell lines and organoids from metastatic CRC to investigate in vitro Vox efficacy and orthotopic syngeneic mouse models of metastatic CRC to assess the efficacy of Vox+anti-PD-1 antibody and identify the involved immune cells. Results The Vox+anti-PD-1 antibody combination completely cured tumor-bearing mice and protected them from a rechallenge. Vox was associated with a reduction of tumor-infiltrated neutrophils, CD206 + macrophages and regulatory T cells. Vox also induced a deep depletion of blood neutrophils. The increased bone marrow granulopoiesis failed to compensate for the Vox-mediated mature neutrophil depletion. Neutrophil depletion using a mouse recombinant anti-Ly6G antibody partially mimicked the Vox effect on the tumor microenvironment, but to a lower extent compared with the Vox+anti-PD-1 antibody combination. Vox, but not neutrophil depletion, led to the emergence of an Ly6C + PD-1 + CD8 + T-cell population in the blood and spleen of tumor-harboring mice. These cells were proliferating, and expressed IFN-γ, CD62L, CXCR3 and Eomes. Moreover, the proportion of tumor antigen-specific T cells and of CD122 + BCL6 + T cells, which shared phenotypic characteristics with stem-like CD8 + T cells, was increased in treated mice. Conclusions Our work strongly suggests that the Vox+anti-PD-1 antibody combination might significantly improve survival in patients with metastatic and treatment-refractory CRC by acting both on cancer cells and CD8 + T cells.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.318
Teacher spread0.297 · 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

Citations8
Published2025
Admission routes1
Has abstractyes

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