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Abstract A002: Analysis of tumor microenvironments in ovarian cancer patients receiving anti-BTN1A1 immunotherapy combined with standard-of-care therapy

2023· article· en· W4389228096 on OpenAlexaboutno aff
Stephen Yoo, Youngseung Kim, Seung‐Hoon Lee, Soo Hyun Lee, Sang Joon Shin, Patricia LoRusso, Hyun‐Jin Jung, David S. Hong

Bibliographic record

VenueCancer Immunology Research · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsnot available
Fundersnot available
KeywordsImmunotherapyImmune systemMedicineTumor microenvironmentCancerOvarian cancerMultiplexAntibodyOncologyImmunofluorescenceClinical trialCancer researchCancer immunotherapyMass cytometryInternal medicineImmunologyBioinformaticsBiology

Abstract

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Abstract Background Immune checkpoints have emerged as key regulators of the immune responses against various tumor types. Butyrophilin 1A1 (BTN1A1) has been identified as a novel immune checkpoint protein that has the potential to be targeted for new immunotherapeutic treatment options. We have observed that BTN1A1 and PD-L1 expression are mutually exclusive in various human solid tumors. Recently, Nelmastobart (BTN1A1-targeting antibody, hSTC810) has successfully completed phase 1 clinical trials. To ensure the effectiveness of Nelmastobart, it is crucial to possess a profound comprehension of patients’ tumor microenvironment factors involved. Here, we report Opal multiplex immunofluorescence and Hyperion imaging mass cytometry approach that includes a deeper understanding of the spatial relationships in the tumor microenvironment. Methods In a first-of-its-kind Phase 1 clinical trial, we are to characterize the safety profile and determine the maximum tolerated dose (MTD) and/or recommended Phase 2 dose (RP2D). Nelmastobart is administered as monotherapy at increasing dose levels of 0.3, 1, 3, 6, 10, and 15 mg/kg on a Q2W schedule. To understand the heterogeneity of the interaction mechanisms between immune cells and cancer cells, Patients’ FFPE specimens were stained cancer and immune cells using Opal multiplex immunofluorescence and analyzed Hyperion imaging mass cytometer. Results We enrolled 45 pts with various cancers in a phase I trial of anti-BTN1A1, a novel immunotherapy. We tested doses from 0.3 to 15 mg/kg and found no DLTs. We report results for ovarian cancer. Opal multiplex immunofluorescence analysis showed that anti-BTN1A1 therapy increased the infiltration and activation of CD8+ T cells and NK cells and decreased the level of regulatory T cells in the tumor microenvironment. We also found the opposite expression of BTN1A1 in PD-L1-expressing cancer cells in KI67-negative tumors from ovarian cancer patients. Conclusions Nelmastobart treatment activates immune response pathways and enhances anti-tumor activity with anti-PD-L1 combination therapy in vitro, in vivo, and clinical settings. The results of the study suggest that BTN1A1 is a novel immune checkpoint that can be targeted to overcome resistance to conventional therapies in cancer patients. Citation Format: Stephen S Yoo, Youngseung Kim, Seung Hoon Lee, Soohyeon Lee, Sangjoon Shin, Patricia LoRusso, Hyunjin Jung, David Hong. Analysis of tumor microenvironments in ovarian cancer patients receiving anti-BTN1A1 immunotherapy combined with standard-of-care therapy [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2023 Oct 1-4; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2023;11(12 Suppl):Abstract nr A002.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.030
GPT teacher head0.335
Teacher spread0.304 · 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.

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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