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Record W2562983905 · doi:10.1158/1538-7445.am2015-5017

Abstract 5017: The discovery of novel therapeutics that restore antigen processing pathways in immune-edited metastatic cancers

2015· article· en· W2562983905 on OpenAlexaff
Lilian L. Nohara, Reinhard Gabathuler, Paul Hangsan Ahn, Ping Cheng, David E. Williams, Raymond J. Andersen, Wilfred A. Jefferies

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
Fundersnot available
KeywordsImmune systemBiologyMajor histocompatibility complexAntigenAntigen processingCancer researchImmunologyImmunotherapyAntigen presentationMHC class ICTL*CancerT cellCD8Genetics

Abstract

fetched live from OpenAlex

Abstract Cancer immune-editing resulting in immune escape where Major Histocompatibility Complex I (MHC I) molecules and the endogenous Antigen Processing Pathway (APP) leading to MHC I expression are down regulated, are prevalent in metastatic forms of cancer. In the absence of MHC I, these tumors subvert host immune surveillance mechanisms and are thus resistant to many of the immunotherapies approaches that evoke adaptive immunity to eradicate tumors in humans. Previously, we showed that by restoring TAP-1 expression in metastatic disease it is possible to restore the APP and the CTL recognition of tumor specific antigen loaded MHC-I molecules in carcinomas. We continued to investigate this mechanism of TAP deficiencies leading to APP defects and were the first to discover that this phenotype is not regulated by defects or mutations in the TAP-1 gene, but it is epigenetically regulated and can be restored by treatment with Histone Deacetylase Inhibitors (HDACi). Here, we describe a novel mechanism of action of compounds in promoting immune responses against tumors. We have developed a high-throughput screening assay to identify compounds that induce antigen presentation in metastatic prostate and lung carcinomas. We have used this system to screen a pharmacological library made from deep-sea sponge extracts, as it has been found that marine invertebrates are a diverse source of pharmaceutical leads and also of chemical diversity. Our results exploiting this system indicate several extracts isolated from amongst 500 sea sponges result in an increase a significant increase in surface MHC I expression, while at the same time exhibiting low cytotoxicity. The chemical structures of several of the active components of these extracts have been determined and one particularly promising candidate has been synthesized and produced in sufficient quantities to commence animal testing. Initial studies indicate the compound is well tolerated and there is no toxicity in animals at the doses that were studied. Results will be presented regarding the activity of the compound against subcutaneously implanted metastatic tumors. The work described herein will provide new therapeutic candidates for harnessing the power of the immune system to recognize and destroy metastatic cancers. Citation Format: Lilian Nohara, Reinhard Gabathuler, Paul Ahn, Ping Cheng, David Williams, Raymond Andersen, Wilfred A. Jefferies. The discovery of novel therapeutics that restore antigen processing pathways in immune-edited metastatic cancers. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 5017. doi:10.1158/1538-7445.AM2015-5017

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 score0.004
Threshold uncertainty score0.014

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)0.0040.001

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 head0.198
GPT teacher head0.406
Teacher spread0.208 · 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
Published2015
Admission routes1
Has abstractyes

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