A Phase I Monotherapy Study of RG7212, a First-in-Class Monoclonal Antibody Targeting TWEAK Signaling in Patients with Advanced Cancers
Bibliographic record
Abstract
PURPOSE: Tumor necrosis factor (TNF)-like weak inducer of apoptosis (TWEAK) and fibroblast growth factor-inducible molecule 14 (Fn14) are a ligand-receptor pair frequently overexpressed in solid tumors. TWEAK: Fn14 signaling regulates multiple oncogenic processes through MAPK, AKT, and NFκB pathway activation. A phase I study of RG7212, a humanized anti-TWEAK IgG1κ monoclonal antibody, was conducted in patients with advanced solid tumors expressing Fn14. EXPERIMENTAL DESIGN: Dose escalations, over a 200- to 7,200-mg range, were performed with patients enrolled in weekly (QW), bi-weekly (Q2W), or every-three-week (Q3W) schedules. Primary objectives included determination of dose and safety profile. Secondary endpoints included assessments related to inhibition of TWEAK: Fn14 signaling, tumor proliferation, tumor immune cell infiltration, and pharmacokinetics. RESULTS: In 192 treatment cycles administered to 54 patients, RG7212 was well-tolerated with no dose-limiting toxicities observed. More than 95% of related adverse events were limited to grade 1/2. Pharmacokinetics were dose proportional for all cohorts, with a t1/2 of 11 to 12 days. Pharmacodynamic changes included clearance of free and total TWEAK ligand and reductions in tumor Ki-67 and TRAF1. A patient with BRAF wild-type melanoma who received 36 weeks of RG7212 therapy had tumor regression and pharmacodynamic changes consistent with antitumor effects. Fifteen patients (28%) received 16 or more weeks of RG7212 treatment. CONCLUSION: RG7212 demonstrated excellent tolerability and favorable pharmacokinetics. Pharmacodynamic endpoints were consistent with reduced TWEAK: Fn14 signaling. Tumor regression was observed and prolonged stable disease was demonstrated in multiple heavily pretreated patients with solid tumors. These encouraging results support further study of RG7212. Clin Cancer Res; 21(2); 258-66. ©2014 AACR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".