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Phase 1 study of SGN-PDL1V, a novel, investigational vedotin antibody–drug conjugate directed to PD-L1, in patients with advanced solid tumors (SGNPDL1V-001, trial in progress).

2022· article· en· W4281709253 on OpenAlexaff
Amita Patnaik, Justin Call, Anna Spreafico, Lisle Nabell, Mingjin Yan, Andres Forero-Torres, Maura L. Gillison

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineTolerabilityCancer researchBrentuximab vedotinAntibody-drug conjugatePharmacologyOncologyInternal medicineAntibodyImmunologyAdverse effectMonoclonal antibodyImmunohistochemistry

Abstract

fetched live from OpenAlex

TPS3154 Background: Programmed cell death ligand 1 (PD-L1) is a cell-surface protein involved in the programmed cell death protein 1 (PD-1)/PD-L1 immune checkpoint, which inhibits T-cell activation. Elevated PD-L1 expression is observed across a broad spectrum of solid tumor types. Expression of PD-L1 in tumors can signal through PD-1 on T cells to inhibit T-cell effector function. Blockade of the PD-1/PD-L1 signaling axis may restore antitumor immunity by reactivating T-cell effector function in the tumor microenvironment. SGN-PDL1V is a novel, investigational vedotin antibody–drug conjugate directed to PD-L1 with multiple proposed mechanisms of action including monomethyl auristatin E (MMAE)-directed cytotoxicity, bystander effect, and immunogenic cell death (ICD). Even in xenograft models with low, heterogeneous PD-L1 expression, SGN-PDL1V demonstrated antitumor activity via direct cytotoxicity and the bystander effect. Cytotoxicity mediated by SGN-PDL1V also led to immune activation due to MMAE-induced ICD (Kwan et al 2021). These preclinical findings provide a rationale for evaluating SGN-PDL1V in patients (pts) with advanced solid tumors. Methods: SGNPDL1V-001 (NCT05208762) is a phase 1, first-in-human, multicenter, open-label trial designed to evaluate the safety, tolerability, pharmacokinetics (PK), and antitumor activity of SGN-PDL1V in pts with advanced solid tumors. This study includes 3 parts: dose escalation (Part A), dose and schedule optimization cohorts (Part B), and dose expansion in disease-specific cohorts and a biology cohort (Part C). Adult pts (≥18 years) with histologically/cytologically confirmed metastatic/unresectable solid tumors, including non-small cell lung cancer, head and neck squamous cell carcinoma, esophageal squamous cell carcinoma, melanoma, or ovarian cancer, will be eligible. Pts must have ECOG PS 0–1 and have failed or are unable to tolerate standard therapies. Pts must have PD-L1 expression ≥1 by tumor proportion score or combined positive score based on historical testing. Prior treatment with an MMAE-containing agent or an anti–PD-L1 agent (within 6 months) is not permitted. Primary endpoints include adverse events, laboratory abnormalities, dose-limiting toxicities, and cumulative dose-level safety. Secondary endpoints include rate and duration of objective response, progression-free survival, overall survival, PK, and incidence of antidrug antibodies. Exploratory endpoints include pharmacodynamics (PD), PK/PD relationships, and patient-reported outcomes. Safety and antitumor activity endpoints will be assessed using descriptive statistics. Objective response rate will be analyzed by tumor type, dose levels, and schedules. Enrollment for Part A is ongoing at sites in North America and is planned in Europe. Clinical trial information: NCT05208762.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
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)0.0040.001

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 head0.062
GPT teacher head0.463
Teacher spread0.401 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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