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Trial START-001: A phase 1/2 study of STAR0602, a first-in-class, selective T cell receptor (TCR)-targeting, bifunctional antibody-fusion molecule, as monotherapy in patients with antigen-rich tumors post checkpoint inhibitor (CPI) treatment.

2023· article· en· W4379283399 on OpenAlexaff
Ryan J. Sullivan, Ke Liu, Jason M. Redman, Nicholas Tschernia, Andrew Bayliffe, Alyssa Marino, Karunya Srinivasan, Madan Katragadda, Jacques Moisan, Rajesh Chopra, Aurélien Marabelle, Howard L. Kaufman, Lillian L. Siu, Zhen Su, James L. Gulley

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineTolerabilityT-cell receptorCD8AntigenImmunologyCytokine release syndromeCancer researchT cellPharmacologyOncologyInternal medicineImmune systemChimeric antigen receptorAdverse effect

Abstract

fetched live from OpenAlex

TPS2671 Background: Many patients do not respond to CPI-based therapies and most responders eventually develop resistance. Thus, the development of more effective therapies for CPI treatment resistance is a significant unmet medical need. STAR0602, a first-in-class, TCR β chain-targeting bifunctional antibody fused to a costimulatory molecule, binds the germline Vβ6/Vβ10 TCRs of human alpha/beta (aβ) T cells, and promotes the selective activation and expansion of CD8+ and CD4+ Vβ6/Vβ10 effector memory T cells by simultaneously engaging direct TCR activation with IL-2 receptor binding and activation in cis. Preclinical studies with STAR0602 and its murine surrogate showed potent single-agent anti-tumor activity in multiple CPI-refractory human organoid and murine syngeneic tumor models, and acceptable tolerability and limited cytokine release in monkeys and mice. Durable anti-tumor responses, with long-term protection from tumor re-challenge, was associated with de novo expansion and tumor infiltration of targeted Vβ T cell subsets with a novel effector memory gene signature and striking increase in TCR repertoire diversity. These data provide strong scientific rationale to investigate the safety and efficacy of STAR0602 in patients with CPI-resistant cancers. Methods: Using a 3+3 trial design, Phase 1 of START-001 is a dose escalation through eight provisional dose levels of STAR0602, administered via an intravenous infusion once every two weeks, to determine a recommended Phase 2 dose (RP2D), based on safety and tolerability, pharmacokinetics, pharmacodynamics, and preliminary anti-tumor activity. Subjects must have one of the following, histologically confirmed solid tumors that are unresectable, locally advanced or metastatic and for which standard curative therapies do not exist or are no longer effective: 1) high mutational burden solid tumors (TMB-H); 2) MSI-H/mismatch repair-deficient (dMMR) cancers; 3) Virally associated tumors including Merkel cell carcinoma, cervical, oropharyngeal, anal, penile, vaginal, and vulval cancers. After an RP2D is selected, Phase 2 (dose expansion at this RP2D) will begin to further investigate the safety and preliminary anti-tumor activity of STAR0602 in 10 provisional cohorts of patients who have the following solid tumors: TMB-H, CPI experienced; TMB-H, no prior CPI experience; MSI-H/dMMR; virally associated tumors; K-RAS wild-type and MSI-L/MMR proficient colorectal cancer (CRC); K-Ras mutant CRC; metastatic triple-negative breast cancer; relapsed and refractory epithelial ovarian cancer; metastatic castration-resistant prostate cancer; primary stage IV or recurrent non-small cell lung cancer. Phase 1 enrollment has begun since January 2023. Clinical trial information: NCT05592626 .

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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.058
GPT teacher head0.434
Teacher spread0.376 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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