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TTI-622-01: A phase 1a/1b dose-escalation and expansion trial of TTI-622 in patients with advanced hematologic malignancies, including diffuse large B-cell lymphoma (DLBCL).

2022· article· en· W4281654580 on OpenAlexaff
Krish Patel, Dahlia Sano, Michael Maris, Alexander M. Lesokhin, Gottfried von Keudell, Kimberley Doucette, Radhakrishnan Ramchandren, Dmitri Pavlov, Robert A. Uger, Naomi Molloy, Ingmar Bruns, Anita Scheuber, Swaminathan P. Iyer

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsPfizer (Canada)Trillium Therapeutics (Canada)
Fundersnot available
KeywordsCD47MedicineCancer researchPhagocytosisLymphomaImmune systemCD20CancerImmunologyInternal medicine

Abstract

fetched live from OpenAlex

TPS7595 Background: CD47 is an innate immune checkpoint that binds signal regulatory protein alpha (SIRPα) and delivers a "don’t eat me" signal to suppress macrophage phagocytosis. Overexpression of CD47 on cancer cells serves as a mechanism of immune surveillance evasion, and is associated with poor prognosis in both hematologic and solid malignancies. TTI-622 is a fusion protein consisting of the CD47-binding domain of human SIRPα linked to the Fc region of human IgG4. It is designed to enhance phagocytosis and antitumor activity by preventing CD47 from delivering its inhibitory signal as well as generating a moderate pro-phagocytic signal via IgG4 Fc. Importantly, unlike many CD47-blocking agents, TTI-622 does not bind to human red blood cells. Preclinical studies demonstrate that TTI-622 induces macrophage-mediated phagocytosis of different malignant cell lines, including DLBCL cells, decreases tumor growth and improves survival in a DLBCL xenograft tumor model. Anti-CD47 antibody enhances rituximab stimulated macrophage-mediated phagocytosis of non-GCB DLBCL cell lines (Bouwstra et al, Cancer Immunol Res. 2019). The ongoing phase 1a part of this study has been previously described. Here we describe 2 cohorts within the phase 1b part of the study that are intended to determine the safety and preliminary efficacy of TTI-622 when given in combination with anti-CD20 targeting agent in patients with CD20+ relapsed/refractory (RR) DLBCL. Methods: TTI-622-01 is a multi-center Phase 1a/1b study. Phase 1a was designed to determine the MTD, pharmacokinetics (PK), pharmacodynamics, and preliminary antitumor activity of QW, Q2W, and Q3W single-agent TTI-622 in R/R lymphoma using a 3+3 dose escalation schema. Phase 1b, ongoing, will determine the safety, recommended dose and preliminary efficacy of TTI-622 in combination with select approved anticancer treatments for patients with hematological malignancies including, but not limited to anti-CD20 therapy in patients with CD20+ RR DLBCL. Secondary objectives are to further characterize safety, PK and immunogenicity of TTI-622 when combined with approved therapies. Patients will be enrolled in 2 cohorts exploring different doses of TTI-622 in combination with anti-CD20 therapy. Cohorts will open in a staggered manner. In each cohort 3 patients will be dosed and followed for 28 days before expanding enrolment to additional 27 patients per cohort. Key eligibility criteria include: age ≥18 years; relapsed and/or refractory disease after ≥1 prior line of therapy; not eligible for or have progressed after high dose chemotherapy (HDT)/auto-SCT; ≥1 site of measurable disease (Lugano 2014 classification); ECOG PS ≤2; adequate organ functions, no known CNS involvement; no prior anti-CD47 or anti-SIRPα therapy. Patient recruitment is planned or ongoing at 40 sites worldwide. Clinical trial information: NCT03530683.

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)0.000
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 score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
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 head0.054
GPT teacher head0.374
Teacher spread0.320 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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