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DPX-Survivac and intermittent low-dose cyclophosphamide (CPA) with or without epacadostat (E) in the treatment of subjects with advanced recurrent epithelial ovarian cancer (DeCidE<sup>1</sup> trial): T cell responses and tumor infiltration correlate with tumor regression.

2019· article· en· W2947929331 on OpenAlexaff
János L. Tanyi, Oliver Dorigo, Amit M. Oza, James Strauss, Tanja Pejović, Sharad Ghamande, Prafull Ghatage, Jeannine Villella, Stephan Fiset, Lisa D. MacDonald, Оlga Hrytsenko, Marianne M. Stanford, Robert Newton, Lance Leopold, Gabriela Nicola Rosu

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsImmunovaccine (Canada)Baker Hughes (Canada)Princess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineSurvivinImmune systemT cellTumor microenvironmentInternal medicineOncologyCyclophosphamideClinical trialChemotherapyOvarian cancerCancerUrologyImmunology

Abstract

fetched live from OpenAlex

5576 Background: DPX-Survivac is a novel T cell activating therapy designed to elicit an effective immune response against recurrent ovarian cancers that express the survivin protein. The survivin specific T cells induced by DPX-Survivac can infiltrate the tumors and are associated with clinical responses. It is likely that achieving an anti-tumor effect requires a favorable ratio of T cells to tumor cells. Epacadostat (E) is an IDO1 enzyme inhibitor that may enhance effector T cell proliferation, shifting the tumor microenvironment (TME) away from an immunosuppressive state toward one supporting productive immune response. Methods: Recurrent ovarian cancer patients with advanced and metastatic progressive disease were treated with DPX-Survivac, intermittent low dose CPA with or without E. In the Phase 1b, 53 subjects were enrolled to receive DPX-Survivac, low dose CPA and E BID. In the Phase 2, 12 subjects were randomized to receive DPX-Survivac and low dose CPA with or without E. The data on immunological responses, biomarkers, and clinical responses were analyzed in relation to the baseline sum of target lesions per RECIST 1.1. Results: The study showed that DPX-Survivac and intermittent low dose CPA with or without E can generate strong T cell responses. The infiltration of tumors with survivin-specific T cells correlates with the observed tumor regression. The sum of target tumor measurements at baseline by RECIST 1.1 correlated with observed clinical benefits. In the group of 15 patients with the baseline sum of target lesions less than 5 cm, all subjects have shown clinical benefits. Four of these subjects reached partial response and remained without progression over a prolonged period. Conclusions: The treatment studied leads to strong survivin-specific T cell responses. Infiltration of tumors by survivin-specific T cells correlated with clinical benefit in treated subjects. A predictive model based on tumor size to improve response to DPX-Survivac in recurrent ovarian cancer is being prospectively explored. Clinical trial information: NCT02785250.

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)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.034
GPT teacher head0.361
Teacher spread0.326 · 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".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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