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Abstract PO-093: Crenolanib improves PD-1 response and overall survival in immune checkpoint inhibitor resistant murine models of oral squamous cell carcinoma

2023· article· en· W4386784570 on OpenAlexaboutno aff
Xiangfeng Shen, Katherine Gonzalez, Rico Castillo, Ashlyn G. Rickard, Yvonne M. Mowery, Tammara L. Watts

Bibliographic record

VenueClinical Cancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTumor microenvironmentCancer researchHead and neck squamous-cell carcinomaCancerImmunotherapyHead and neck cancerInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background: Present line indications for pembrolizumab are for patients with metastatic or unresectable recurrent (i.e. incurable) head and neck squamous cell carcinoma (HNSCC). However, only a minority of patients on immunotherapy will realize a durable survival benefit because >80% of patients with metastatic HNSCC do not respond to PD-1 blockade. Tumor microenvironment mesenchymal stem cells (MSCs) and cancer associated fibroblasts (CAFs) have been reported significantly contribute to chemotherapy and radiation resistance. Moreover, MSCs have been shown to contribute to an immunosuppressive tumor microenvironment by upregulating PD-L1 in breast cancer models. We have previously shown crenolanib improves MSC mediated cisplatin resistance in vitro through modulation of MSC-mediated activation of AKT signaling, therefore we hypothesize that targeting MSCs may be of therapeutic benefit alone and in combination with anti-PD1 immunotherapy. Methods: Oral cancer was induced in the buccal space of C56/BL6 mice with the murine oral cancer cell lines MOC1 or PD-1 resistant cell line, MOC2. When tumors reached approximately 5 × 5 mm, mice were treated with 15 mg/kg (low dose) or 30 mg/kg crenolanib (high dose) for five consecutive days over 3 weeks. Tissue were harvested for immunohistochemistry and immunofluorescence analysis and ex vivo cell cultures prepared for analysis by western immunoblotting and flow cytometry. Results: There was a significant reduction in tumor volume in mice bearing MOC1 and MOC2 tumors (p<0.03) treated with either low or high dose crenolanib compared to vehicle control. Overall survival was also significantly improved in mice bearing MOC1 tumors treated with high dose crenolanib compared to mice treated with vehicle control (p<0.04) and approached significance in MOC2 mice treated with low dose crenolanib. Tumor sections were imaged by immunofluorescence microscopy. There was a decrease in expression of PDGFR-α on MOC1 tumor cells and α-SMA on tumor microenvironment stromal cells in mice treated with crenolanib compared to vehicle control, suggesting crenolanib targets both cell types. There was a significant reduction in tumor volume (p<0.0001) and improved overall survival (p<0.0004) in mice bearing MOC2 tumors treated with combination crenolanib plus pembrolizumab compared to vehicle plus pembrolizumab. Conclusions: Preliminary in vivo data suggests crenolanib may be efficacious when used in combination with anti-PD1 immunotherapy by inhibiting the immunosuppressive effects of tumor microenvironment MSCs. Citation Format: Xiangfeng Shen, Katherine Gonzalez, Rico Castillo, Ashlyn Rickard, Yvonne Mowery, Tammara Watts. Crenolanib improves PD-1 response and overall survival in immune checkpoint inhibitor resistant murine models of oral squamous cell carcinoma [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-093.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.185
GPT teacher head0.458
Teacher spread0.273 · 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 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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