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Abstract LB-187: Hsp90 inhibitor SNX-2112 enhances neoantigen presentation on the surface of tumor cells

2019· article· en· W2955298108 on OpenAlexaff
Megan C. Yap, John Walker, Kristi Baker, Richard P. Fahlman, Everardus Orlemans, Paul LaPointe

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMHC class IChemistryCancer researchMolecular biologyCytotoxic T cellBiologyBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Abstract Introduction: SNX-5422 is the orally active prodrug of SNX-2112, a potent, highly selective inhibitor of heat-shock protein 90 (Hsp90) with promising anti-tumor activity in clinical trials. SNX-5422 enhanced anti-PD-1 activity in MC38 murine model. SNX-2112 affects multiple tumor pathways, including the interferon pathway and upregulates genes associated with antigen expression, and T-cell recognition, and it interferes with tumor microenvironment immunoediting associated genes. Methods: Cells were cultured in media supplemented with 10% fetal bovine serum at 37°C, 5% CO2, and 95% humidity. The 50% effective concentration of SNX-2112 on cell viability of SkMel28, MDAMB231, SkMel2 was determined using Cell Titer-Glo® Luminescent Cell Viability Assay. Cells were treated with SNX-2112 or other anti-tumor agents, e.g., vemurafenib, to determine surface expression of MHC class I complexes by flow cytometry using MHC class I monoclonal antibody PE conjugate (Enzo-Cat# ALX-805-711R-C100) and, in parallel, induction of apoptosis by Annexin V APC. Results: At the lowest dose of SNX-2112 required to inhibit activity of model Hsp90 clients (MAPK), a 3 to 5-fold increase in MHC class I presentation was observed in all cells lines. Treatment of MDAMB231 with SNX-2112 caused a 3-fold increase in surface expression of MHC class I complexes, loss of Hsp90 client protein activity, and increased protein ubiquitination, without change in protein levels of immunoproteasome subunits LMP2 and LMP7. Increased surface expression of MHC class I complexes, loss of Hsp90 client function, increased protein ubiquitination without affecting immunoproteasome subunits were also found in both melanoma cell lines. This suggests that upregulation of cell surface MHC class I complexes is driven by increased Hsp90 client protein turnover. SNX-2112 treatment at concentrations sufficient to increase MHC class I surface expression also resulted in a small increase in apoptosis. Interestingly, treatment of SkMel28 with vemurafenib robustly induced apoptosis without any effect on surface expression of MHC class I complexes. Analysis of surface-expressed peptides by mass spectrometry revealed a change in peptide profile after treatment with SNX-2112. Conclusion: SNX-2112 increased surface expression of multiple MHC class I complexes. Results suggest that SNX-2112 can drive the selective surface presentation of Hsp90 client proteins on tumor cell surface and could improve recognition by T cells specific for various cancer-associated antigens derived from mutated genes, making it potential useful in immunotherapy of cancer. This effect of SNX-2112 is independent of the induction of apoptosis as agents like vemurafenib did not elicit the same effect. Ongoing studies are focused on identifying Hsp90 client-derived peptides in surface complexes and their role in anti-tumor immunity. Citation Format: Megan Yap, John W. Walker, Kristi Baker, Richard Fahlman, Everardus Orlemans, Paul Lapointe. Hsp90 inhibitor SNX-2112 enhances neoantigen presentation on the surface of tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-187.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.044
GPT teacher head0.384
Teacher spread0.340 · 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
Published2019
Admission routes1
Has abstractyes

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