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Abstract PD4-03: PD4-03 Pelareorep primes the tumor for checkpoint inhibition therapy by activating the interferon-gamma signaling pathway and tumor inflammation signature in early breast cancer patients - results of the AWARE-1 trial

2023· article· en· W4322769237 on OpenAlexaff
Houra Loghmani, Joaquín Gavilá, Luís Manso, Matt Coffey, Richard Trauger, Fernando Salvador, Tomás Pascual, Aleix Prat, Thomas Heineman

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsOncolytics Biotech (Canada)
Fundersnot available
KeywordsMedicineImmune checkpointBreast cancerTumor microenvironmentAtezolizumabOncologyLetrozoleCancerInternal medicineImmune systemImmunotherapyOncolytic virusCancer researchImmunologyNivolumab

Abstract

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Abstract Background The status of the tumor microenvironment (TME) can profoundly affect the response to immune-based therapies for the treatment of cancer. Results previously reported from the AWARE-1 study in early breast cancer patients demonstrated that pelareorep (pela, an oncolytic reovirus), alone or in combination with checkpoint inhibitor (CPI) therapy, modified the inflammatory state of the TME. We also showed that many of pela’s effects on the TME were enhanced by the addition of checkpoint blockade. Here, we report the effect of treatment with pela on selected molecular markers associated with enhanced anti-tumor immunity. Methods Newly diagnosed HR+/HER2- early BC patients were enrolled into two cohorts: Cohort 1 (C1): pela + letrozole (n=10); and Cohort 2 (C2): pela + letrozole + atezolizumab (n=10). Pela was intravenously administered on days 1, 2 and 8, 9, and atezolizumab was given on day 3. For this analysis, tumor biopsies (FFPE samples) collected pre-treatment (D1) and on days 3 (D3, prior to the atezolizumab administration) were examined by GeoMx digital spatial profiling (DSP, using Nanostring’s Cancer Transcriptome Atlas [CTA]). Moreover, the expression of 770 immune-related genes was analyzed using a specific immune panel (n=20). Gene Set Enrichment Analysis (GSEA) (version 4.1.0) was used to assess pela-induced activation pathways. Results GeoMx DSP showed that pela therapy significantly activated IFN-gamma signaling and associated interferon response genes from D1 to D3 (Normalized Enrichment Score [NES] = 3.3, p-values < 0.02) in the cytokeratin-positive subset of the tumor samples. GSEA of the immune dataset (730 immune genes + 30 housekeeping genes) from the whole tissue also showed a significant upregulation of IFN-gamma signaling pathway genes (FDR < 25%, p-value< 0.001). Increases were also observed in genes reported to be associated with an enhanced tumor inflammatory signal (TIS) including PD-L1, IDO1, HLA-E and STAT1 (p-values < 0.005). Conclusions These results demonstrate that treatment with pela alters the TME to induce and enhance anti-tumor immunity. This enhancement of anti-tumor immunity may potentiate the TME for CPI therapy. Citation Format: Houra Loghmani, Joaquín Gavilá, Luis Manso, Matt Coffey, Richard Trauger, Fernando Salvador, Tomás Pascual, Aleix Prat, Thomas Heineman. PD4-03 Pelareorep primes the tumor for checkpoint inhibition therapy by activating the interferon-gamma signaling pathway and tumor inflammation signature in early breast cancer patients - results of the AWARE-1 trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD4-03.

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)0.001
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.031
GPT teacher head0.339
Teacher spread0.308 · 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 designNon-randomized trial
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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