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Phase 2 dose expansion of START-001: A phase 1/2 study of invikafusp alfa (STAR0602), a first-in-class, selective T cell receptor (TCR)-targeting, bifunctional antibody-fusion molecule, as monotherapy in patients with antigen-rich tumors resistant to anti-PD(L)-1.

2025· article· en· W4410810027 on OpenAlexaff
Claire F. Friedman, Ryan J. Sullivan, Nicholas Tschernia, Guru Sonpavde, Mercedes Herrera, Kai He, Marijo Bilušić, Elena Garralda, Alberto Hernando‐Calvo, Ann W. Silk, Matthieu Roulleaux-Dugage, Antoine Italiano, Manuel Pedregal, Muhammad Wasif Saif, Kevin M. Chin, Zhen Su, Ke Liu, Lillian L. Siu, James L. Gulley, Aurélien Marabelle

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineT-cell receptorBifunctionalAntibodyReceptorCancer researchImmunologyPharmacologyMolecular biologyInternal medicineT cellBiochemistryBiologyImmune system

Abstract

fetched live from OpenAlex

TPS2687 Background: Many patients do not respond to anti-PD(L)-1-based therapies and most responders eventually develop resistance. Thus, the development of effective therapies for anti-PD(L)-1 resistance is a significant unmet medical need. Invikafusp, a selective, dual T cell agonist targeting Vβ6/Vβ10 T cells, is being evaluated in START-001: a multicenter Phase 1/2 monotherapy trial in patients with anti-PD(L)1-resistant, antigen-rich (TMB-H, MSI-H/dMMR, or virally associated) solid tumors. The completed Phase 1 dose escalation of intravenous invikafusp, Q2W, per 3+3 design, identified a recommended Phase 2 dose (RP2D) of 0.08 mg/kg, and demonstrated clinically meaningful single-agent anti-tumor activity in patients with anti-PD(L)-1 resistant tumors, including confirmed partial responses in TMB-H, microsatellite stable, colorectal cancer (CRC) patients with one durable response lasting ~12 months. It promoted potent and selective expansion of mainly CD8+ Vβ6/ Vβ10 T cells with a novel central memory T cell phenotype, and led to ctDNA decrease and expansion of antigen-specific T cells. Based on these results, the US FDA granted Fast Track Designation for invikafusp in TMB-H CRC. Methods: Study design: Using an optimal Simon’s 2 stage design, Phase 2 of START-001 is a dose expansion at the RP2D, to further investigate the safety and anti-tumor activity of invikafusp in 9 cohorts of patients who have the following solid tumors: 1) tissue-agnostic, TMB-H; 2) tissue-agnostic, dMMR/MSI-H; 3) CRC (both Ras wild-type and mutant) TMB-H and/or MSI-H/dMMR); 4) virally associated tumors such as Merkel cell carcinoma, cervical, oropharyngeal, anal, penile, vaginal, and vulvar cancers, or EBV-related solid tumors; 5) metastatic triple-negative breast cancer; 6) platinum-resistant epithelial ovarian cancer; 7) metastatic castration-resistant prostate cancer; 8) primary stage IV or recurrent non-small cell lung cancer; and 9) immunogenic tumors (e.g., cSCC, melanoma and RCC). Major Eligibility criteria: ≤ 3 lines of prior cancer therapies [anti-PD(L)-1s allowed] for advanced or metastatic disease; intolerance to standard therapies including anti-PD(L)-1s allowed; no liver metastases or adequately treated liver metastases either locally (e.g., by surgery, radiofrequency ablation, or chemoembolization) or systemically and stable for 3 months. Primary objective: to further evaluate anti-tumor activity of invikafusp as monotherapy in each of the above-described 9 cohorts of patients with anti-PD(L)-1-resistant, unresectable, locally advanced, or metastatic solid tumors. Primary endpoint: overall response rate (ORR) per iRECIST. The enrollment to the first three cohorts has begun. 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: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.004
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 head0.039
GPT teacher head0.434
Teacher spread0.395 · 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 designRandomized 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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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