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Phase Ib study of the anti-TGF-β monoclonal antibody (mAb) NIS793 combined with spartalizumab (PDR001), a PD-1 inhibitor, in patients (pts) with advanced solid tumors.

2021· article· en· W3173110589 on OpenAlexaff
Todd M. Bauer, Chia‐Chi Lin, Richard Greil, Maria-Elisabeth Goebeler, Marie Luise Huetter-Kroenke, Ignacio Garrido‐Laguna, Armando Santoro, Antonella Perotti, Anna Spreafico, Thomas Yau, Markus Joerger, Viviana Cremasco, Mirek Dostalek, Marc R. Pelletier, Louise Barys, Darlene Lu, Vicky Katsanou, Claire Fabre, Toshihiko Doi

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsPrincess Margaret Cancer Centre
FundersNovartis
KeywordsMedicineTolerabilityLung cancerInternal medicineCancerMonoclonal antibodyOncologyPharmacologyAntibodyAdverse effectImmunology

Abstract

fetched live from OpenAlex

2509 Background: TGF-β plays a key role in regulating the tumor microenvironment. Emerging evidence suggests TGF-β is a key activator of cancer-associated fibroblasts, leading to fibrotic network development and immune exclusion. Preclinical data in murine models showed that TGF-β blockade alleviates intratumoral fibrosis, augmenting the efficacy of PD-1 immunotherapy. NIS793 is a human IgG2 mAb that binds to TGF-β. This study investigates NIS793 + spartalizumab in pts with advanced solid tumors. Methods: Pts initially received NIS793 (0.3–1 mg/kg Q3W) monotherapy; following evaluation of two dose levels, dose escalation continued with NIS793 + spartalizumab (NIS793 0.3–30 mg/kg Q3W + spartalizumab 300 mg Q3W; or NIS793 20–30 mg/kg Q2W + spartalizumab 400 mg Q4W) in pts with/without prior anti-PD-(L)1 therapy. In dose expansion, pts with non-small cell lung cancer (NSCLC) resistant to prior anti-PD-(L)1 or pts with microsatellite stable colorectal cancer (MSS-CRC) were treated at the recommended dose for expansion (RDE). Paired tumor biopsies were required from all pts. The primary objectives were to characterize safety and tolerability of the combination and determine the RDE. Results: By December 1, 2020, 60 pts were treated in the dose-escalation phase, mainly with NIS793 + spartalizumab (n = 49), and 60 pts were treated in dose expansion (MSS-CRC: n = 40; NSCLC: n = 20). Two pts were still receiving treatment. No dose-limiting toxicities were observed, and the RDE was established as 30 mg/kg (2100 mg) NIS793 + 300 mg spartalizumab Q3W. Overall 50% pts experienced ≥1 treatment-related AE (TRAE). The most common were rash (n = 15/120), pruritus (n = 10/120), fatigue (n = 9/120), and nausea (n = 8/120). Grade 3/4 TRAEs occurred in 11% pts, with rash (3%) being the most common. Treatment-related serious AEs were reported in 8 pts; 6 were grade 3/4 in severity. No deaths occurred due to AEs; 3 (2.5%) pts discontinued due to AEs. PK for NIS793 was linearly dose proportional with no obvious correlation between exposure and response. Two pts achieved a partial response (PR; one confirmed in clear cell renal cell carcinoma and one unconfirmed in NSCLC) during dose escalation of the combination. Two confirmed PRs were achieved in the MSS-CRC dose-expansion group. Biomarker data showed evidence of target engagement through increased TGF-β/NIS793 complexes and depleted active TGF-β in peripheral blood. Gene expression and protein analyses in tumor biopsies displayed decreased TGF-β target genes, decreased TGF-β signatures and increased immune signatures suggesting modulation of the TGF-β pathway and preliminary evidence of biological activity. Conclusions: Data showing target engagement and TGF-β pathway inhibition supported the proof of mechanism of NIS793. The RDE of the combination was established and well tolerated in pts with advanced solid tumors. Clinical trial information: NCT02947165.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.046
GPT teacher head0.435
Teacher spread0.389 · 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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Citations38
Published2021
Admission routes1
Has abstractyes

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