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Abstract CT302: Phase Ia/Ib dose-escalation study of the anti-TIGIT antibody tiragolumab as a single agent and in combination with atezolizumab in patients with advanced solid tumors

2020· article· en· W3049330696 on OpenAlexaff
Johanna C. Bendell, Philippe L. Bédard, Yung‐Jue Bang, Patricia LoRusso, Stephen Hodi, Michael S. Gordon, Sandra P. D’Angelo, Jayesh Desai, Elena Garralda, Antoîne Italiano, Myung‐Ju Ahn, Andrés Cervantes, Zev A. Wainberg, Emiliano Calvo, Marta Gil-Martín, Maria Martinez‐García, Rastilav Bahleda, Philippe A. Cassier, Jean‐Pierre Delord, Amy Prawira, Ignacio Melero, Leisha A. Emens, Emanuela Romano, Karen B. Miller, Robert W. Hsieh, Cloris Xue, Kari M. Morrissey, Patrick Twomey, Kelly Gash, Namrata S. Patil, Jane L. Grogan, Raymond D. Meng, Byoung Cho, Tae Won Kim

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsRoche (Canada)Princess Margaret Cancer Centre
Fundersnot available
KeywordsTIGITAtezolizumabMedicineTolerabilityOncologyPharmacodynamicsAntibodyInternal medicinePharmacokineticsPharmacologyCancerImmunotherapyImmunologyAdverse effectNivolumab

Abstract

fetched live from OpenAlex

Abstract Background: The immunomodulatory receptor TIGIT (T-cell Immunoreceptor with Ig and ITIM domains) is a novel inhibitory immune checkpoint present on activated T cells and NK cells in multiple cancers. In preclinical models, co-inhibition of the TIGIT and PD-L1/PD-1 pathways improved anti-tumor activity compared to either agent alone. Tiragolumab (tira or MTIG7192A) is a humanized IgG1/kappa monoclonal antibody (mAb) that binds TIGIT to prevent its interaction with its ligand PVR (CD155). In this first-in-human dose-escalation study, we report the preliminary safety and anti-tumor activity of tira as a single agent and in combination with atezolizumab (atezo) in patients with advanced solid tumors. Methods: Enrolled patients, ECOG PS 0-1, had advanced tumors for whom standard therapy did not exist or was ineffective. Patients received escalating doses of tira alone IV Q3W alone (Phase Ia) or in combination with atezo 1200 mg IV Q3W (Phase Ib) to determine the maximum tolerated dose (MTD) and continued until disease progression, intolerable toxicity, or patient/investigator decision. Study objectives included evaluation of safety and tolerability, pharmacokinetics (PK), pharmacodynamics, and anti-tumor activity of tira alone or tira + atezo. Data cut-off date was April 2019. Results: 73 patients with multiple tumor types were treated in dose-escalation (24 in Phase Ia, 49 in Ib with tira + atezo). In Phase Ia and Phase Ib, median age was 60 and 54 years, ECOG 0 for 29% and 27% of patients, and those who received ≥ 3 prior therapies were 67% and 57%, respectively. No DLTs were observed. Across doses, treatment-related AEs occurred in 67% in Phase Ia and 59% in Phase Ib (Grade ≥ 3: 4% and 4%, respectively), and most common AEs were fatigue (38%) in Phase Ia and anemia (31%) in Phase Ib. Exposure of tira increased with increasing dose, and saturation of nonlinear PK occurred at tira doses ≥ 100 mg Q3W. Complete and sustained occupancy of peripheral TIGIT receptors was observed at tira doses ≥ 30 mg Q3W. In Phase Ia, there were no objective responses, but SD of > 4 months duration was observed (n=4). In Phase Ib, there were 3 responses, which all occurred in PD-L1 positive tumors (2 non-small cell lung cancer [NSCLC]: 1 CR, 1 PR; and 1 head/neck squamous cell carcinoma: PR) with two patients not receiving prior immunotherapy (CIT-naïve). Therefore, expansion cohorts were initiated in PD-L1-positive CIT-naïve indications in Phase Ib. In the metastatic NSCLC expansion cohort (n=14) ORR was 50%, with 1 CR and 6 PRs; DCR was 79%, and the safety profile was similar. Conclusions: Tira monotherapy or combined with atezo was well-tolerated and had an acceptable safety profile across all dose levels. Preliminary anti-tumor activity was observed in Phase Ib with tira + atezo in CIT-naïve PD-L1-positive tumors, including NSCLC, and enrollment is ongoing in these expansion cohorts. Citation Format: Johanna C. Bendell, Philippe Bedard, Yung-Jue Bang, Patricia LoRusso, Stephen Hodi, Michael Gordon, Sandra D'Angelo, Sandra D'Angelo, Jayesh Desai, Elena Garralda, Antoine Italiano, Myung-Ju Ahn, Andres Cervantes, Zev Wainberg, Emiliano Calvo, Marta Gil-Martin, Maria Martinez-Garcia, Rastilav Bahleda, Philippe Cassier, Jean-Pierre Delord, Amy Prawira, Ignacio Melero, Leisha Emens, Emanuela Romano, Karen Miller, Robert W. Hsieh, Cloris Xue, Kari Morrissey, Patrick Twomey, Kelly Gash, Namrata S. Patil, Jane Grogan, Raymond Meng, Byoung Cho, Tae Won Kim. Phase Ia/Ib dose-escalation study of the anti-TIGIT antibody tiragolumab as a single agent and in combination with atezolizumab in patients with advanced solid tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT302.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.401
Teacher spread0.353 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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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Citations64
Published2020
Admission routes1
Has abstractyes

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