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Abstract PO-087: Single-cell transcriptome analysis reveals functional changes in tumor-infiltrating macrophages after nutraceutical momordicine-I treatment in head & neck cancer

2023· article· en· W4386784726 on OpenAlexaboutno aff
Subhayan Sur, Robert Steele, Ratna B. Ray

Bibliographic record

VenueClinical Cancer Research · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsTumor microenvironmentTranscriptomeCancerImmune systemMonocyteCancer researchHead and neck cancerMedicineMacrophageHead and neck squamous-cell carcinomaCancer cellBiologyImmunologyInternal medicineGene expressionGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Head & neck cancer is the sixth most prevalent cancer in the world, and oral cancer is the most common subtype with limited effective treatment options. Therefore, there is a critical need to understand the pathogenesis and therapeutic modalities for successful management of head & neck cancer. Momordicine-I (M-I), an active component of bitter melon extract, displayed anti-tumor activity. However, M-I mediated immune modulation of head & neck tumor microenvironment (TME) remains unknown. To improve the efficacy of therapy, it is important to understand the heterogeneity of head & neck cancer in TME and its modulation following treatment at molecular level. In this study, we showed that M-I inhibits head & neck tumor growth in an immunocompetent mouse model. To understand the in-depth changes in immune system, we analyzed the transcriptome profiles of vehicle treated and M-I-treated tumors using single-cell RNA-sequencing. M-I treatment modulates several molecules in monocyte/macrophage clusters in CD45+ populations. Tumor-associated macrophages (TAMs) are crucial barriers to their antitumor effects. We observed that the expression of Sfln4, a myeloid cell differentiation factor, and Cxcl3, a neutrophil chemoattractant, in the monocyte/macrophage populations was significantly reduced following M-I treatment. We further showed that macrophages need to be in close contact with tumor cells to reduce Sfln4 or Cxcl3 expression, suggesting that TAMs are modulated by M-I treatment. Co-culture of macrophages and tumor cells enhances Nos2 expression following M-I treatment, implicating an alteration of the M2 to M1 phenotype of macrophages. In fact, differential expression of macrophage populations from M-I treated tumors showed downregulation of several M2 macrophage marker genes, and their further validations for functional consequence are underway. Together, our results highlight a potential mechanism of immune modulation by M-I, which may help in the development of a combination therapy for head & neck cancer. Citation Format: Subhayan Sur, Robert Steele, Ratna B. Ray. Single-cell transcriptome analysis reveals functional changes in tumor-infiltrating macrophages after nutraceutical momordicine-I treatment in head & neck cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-087.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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)0.0010.000

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 head0.248
GPT teacher head0.477
Teacher spread0.228 · 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 designObservational
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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