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Record W2044934700 · doi:10.1158/1538-7445.am2014-5028

Abstract 5028: Metronomic cyclophosphamide enhances the immunogenicity and anti-tumor activity of a DepoVax based vaccine and may be further enhanced with inhibitors of CTLA-4 or PD-1

2014· article· en· W2044934700 on OpenAlexaff
Genevieve Weir, Оlga Hrytsenko, Marianne M. Stanford, Neil L. Berinstein, Mohan Karkada, Robert Liwski, Marc Mansour

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsQueen Elizabeth II Health Sciences CentreSunnybrook Health Science CentreHealth Sciences CentreImmunovaccine (Canada)
Fundersnot available
KeywordsELISPOTCytotoxic T cellImmune systemImmunogenicityImmunologyCancer vaccineCD8CyclophosphamideAntigenGranzyme BCancer researchMedicineImmunotherapyBiologyInternal medicineChemotherapyIn vitro

Abstract

fetched live from OpenAlex

Abstract To counteract tumor-induced immune suppression, cancer vaccines are increasingly being combined with immune modulators that can not only reverse immune suppression but also enhance vaccine induced immune responses. We found that metronomic cyclophosphamide (50 mg BID) enhanced the immunogenicity of a DepoVaxTM (DPX) based cancer vaccine (DPX-Survivac) in ovarian cancer patients in a phase I clinical study. We emulated these results using transplantable tumor models which allowed us to study the underlying mechanisms of cyclophosphamide induced immune modulation. In several different models, mice were given mCPA on alternating weeks (20 mg/kg/day PO) in combination with a DPX vaccine containing relevant peptide antigens every three weeks. In these models, only the combination provided effective and significant long-term control of tumor growth. Notably, we found that the efficacy of the combination was comparable when vaccine was given at the beginning or end of a cycle of mCPA. Metronomic CPA had a pronounced lymphodepletive effect on the vaccine draining lymph node, yet did not reduce the development of antigen-specific CD8+ T cells induced by vaccination as detected by MHC-multimer flow cytometry. Combination treatment also increased cytotoxic T cell activity in the spleen measured by IFN-γ ELISPOT and in vivo cytotoxic T cell assay. Analysis of immune gene signatures in the tumor microenvironment by RT-qPCR detected elevated levels of cytotoxic markers, such as IFN-γ and granzyme B, as well as co-inhibitory markers, such as PD-1 and CTLA-4, in mice treated with combination therapy, the latter providing a strong rational for modulating these pathways with recently available monoclonal antibodies. Analysis of spleen cell populations by flow cytometry indicated that mCPA induced transient lymphodepletion that was marked by a selective expansion of myeloid-derived suppressor cells in the absence of vaccination. Selective depletion of regulatory T cells was not observed, in contrast to other regimens of low dose CPA. These results demonstrate that mCPA provides a complex form of immune modulation that is most effective when combined with active immunization. Using these models we can evaluate other immune modulator agents that may enhance vaccine activity, including checkpoint inhibitors or other immune based therapies. Citation Format: Genevieve Weir, Olga Hrytsenko, Marianne M. Stanford, Neil L. Berinstein, Mohan Karkada, Robert S. Liwski, Marc Mansour. Metronomic cyclophosphamide enhances the immunogenicity and anti-tumor activity of a DepoVax based vaccine and may be further enhanced with inhibitors of CTLA-4 or PD-1. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5028. doi:10.1158/1538-7445.AM2014-5028

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 score0.009

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)0.0030.000

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 head0.023
GPT teacher head0.317
Teacher spread0.294 · 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
Published2014
Admission routes1
Has abstractyes

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