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Record W4409625693 · doi:10.1158/1538-7445.am2025-2216

Abstract 2216: Modulating gut microbiota to enhance the efficacy of immunotherapy in triple negative breast cancer

2025· article· en· W4409625693 on OpenAlexaff
Samarpan Majumder, Fokhrul Hossain, Luis Del Ville, Lucio Miele, Justin C. Brown

Bibliographic record

VenueCancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsRogue Research (Canada)
Fundersnot available
KeywordsTriple-negative breast cancerMedicineBreast cancerCancerImmunotherapyGut floraCancer immunotherapyOncologyInternal medicineImmunology

Abstract

fetched live from OpenAlex

Abstract Background: Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer and is diagnosed more frequently in younger, premenopausal women. Obesity is a known risk factor for increased TNBC incidence. The association of gut dysbiosis with obesity is now established. Immune checkpoint blockade with anti-PD-1 is currently the standard of care for early TNBC. Evidence suggests modulating the gut microbiome enhances cancer immunotherapy efficacy in a few cancer types. However, there are no studies on early TNBC. Overarching Challenge: The number of patients with early TNBC who benefit from anti-PD-1 therapy remains suboptimal. Objective: Our study aims to enhance the efficacy of anti-PD-1 therapy by modulating the gut microbiota in a mouse model of obesity and TNBC. We hypothesize that a probiotic supplement will enhance the efficacy of anti-PD-1 therapy. Methods: We determined the efficacy and safety of two weeks of probiotic supplementation before anti-PD-1 therapy on objective response rates in an obese mouse model of triple-negative breast cancer. This was evaluated by measuring the objective response rate (tumor burden) after two weeks of anti-PD-1 treatment. FVB female obese mouse model and authenticated TNBC C0321 claudin low mouse tumor cells (In Vitro Technologies) were used for engrafting tumor. We used a probiotic formulation from Creative Enzyme which is a blend of 13 human probiotic strains (Cat # PRBT-035, NY). Results: One way ANOVA comparing three groups of mice (anti-PD1, anti-PD-1+ serotype and probiotics + anti-PD1) produced a statistically significant outcome confirming our prediction that probiotics positively affect anti-PD1 therapy. A Kaplan-Meier survival plot based on our record of mouse survival over the course of the treatment demonstrates that only probiotics plus anti-PD1 therapy could provoke statistically significant survival benefit over isotype control (p=0.046) in our study. Analysis of cytokine profile revealed elevated level of interferon-γ and downregulation of proinflammatory cytokines in plasma from mice treated with probiotics only. Furthermore, we observed increased CD8+T and CD4 +T cells in the tumor tissue of probiotics treated mice when compared to untreated mice in our Immunohistochemistry analysis. For feasibility study in human subjects, our pilot study is recruiting volunteers (NCT06318507) to confirm whether the fecal microbiome differs between patients with and without obesity and early TNBC and who achieve pCR from preoperative anti-PD-1 therapy. Impact: The study provides critical experimental data to demonstrate causality and feasibility to justify larger-scale interrogations to modulate the gut microbiome in women with early TNBC who plan to begin anti-PD-1 therapy. Innovation: This study is the first to determine how a probiotic supplement can enhance anti-PD-1 efficacy in early TNBC. Citation Format: Samarpan Majumder, Manisha Poudel, Fokhrul Hossain, Luis Del Ville, Lucio Miele, Justin Brown. Modulating gut microbiota to enhance the efficacy of immunotherapy in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2216.

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)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.027
GPT teacher head0.426
Teacher spread0.400 · 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
Published2025
Admission routes1
Has abstractyes

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