Biomarker and pharmacodynamic activity of the transforming growth factor‐beta (<scp>TGFβ)</scp> inhibitor <scp>SAR439459</scp> as monotherapy and in combination with cemiplimab in a phase I clinical study in patients with advanced solid tumors
Bibliographic record
Abstract
SAR439459, a 'second-generation' human anti-transforming growth factor-beta (TGFβ) monoclonal antibody, inhibits all TGFβ isoforms and improves the antitumor activity of anti-programmed cell death protein-1 therapeutics. This study reports the pharmacodynamics (PD) and biomarker results from phase I/Ib first-in-human study of SAR439459 ± cemiplimab in patients with advanced solid tumors (NCT03192345). In dose-escalation phase (Part 1), SAR439459 was administered intravenously at increasing doses either every 2 weeks (Q2W) or every 3 weeks (Q3W) with cemiplimab IV at 3 mg/kg Q2W or 350 mg Q3W, respectively, in patients with advanced solid tumors. In dose-expansion phase (Part 2), patients with melanoma received SAR439459 IV Q3W at preliminary recommended phase II dose (pRP2D) of 22.5/7.5 mg/kg or at 22.5 mg/kg with cemiplimab 350 mg IV Q3W. Tumor biopsy and peripheral blood samples were collected for exploratory biomarker analyses to assess target engagement and PD, and results were correlated with patients' clinical parameters. SAR439459 ± cemiplimab showed decreased plasma and tissue TGFβ, downregulation of TGFβ-pathway activation signature, modulation of peripheral natural killer (NK) and T cell expansion, proliferation, and increased secretion of CXCL10. Conversion of tumor tissue samples from 'immune-excluded' to 'immune-infiltrated' phenotype in a representative patient with melanoma SAR439459 22.5 mg/kg with cemiplimab was observed. In paired tumor and plasma, active and total TGFβ1 was more consistently elevated followed by TGFβ2, whereas TGFβ3 was only measurable (lower limit of quantitation ≥2.68 pg/mg) in tumors. SAR439459 ± cemiplimab showed expected peripheral PD effects and TGFβ alteration. However, further studies are needed to identify biomarkers of response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".