Anti-CSF-1R emactuzumab in combination with anti-PD-L1 atezolizumab in advanced solid tumor patients naïve or experienced for immune checkpoint blockade
Bibliographic record
Abstract
BACKGROUND: This phase 1b study (NCT02323191) evaluated the safety, antitumor activity, pharmacokinetics, and pharmacodynamics of colony-stimulating factor-1 receptor-blocking monoclonal antibody (mAb) emactuzumab in combination with the programmed cell death-1 ligand (PD-L1)-blocking mAb atezolizumab in patients with advanced solid tumors naïve or experienced for immune checkpoint blockers (ICBs). METHODS: Emactuzumab (500-1350 mg flat) and atezolizumab (1200 mg flat) were administered intravenously every 3 weeks. Dose escalation of emactuzumab was conducted using the 3+3 design up to the maximum tolerated dose (MTD) or optimal biological dose (OBD). Extension cohorts to evaluate pharmacodynamics and clinical activity were conducted in metastatic ICB-naive urothelial bladder cancer (UBC) and ICB-pretreated melanoma (MEL), non-small cell lung cancer (NSCLC) and UBC patients. RESULTS: Overall, 221 patients were treated. No MTD was reached and the OBD was determined at 1000 mg of emactuzumab in combination with 1200 mg of atezolizumab. Grade ≥3 treatment-related adverse events occurred in 25 (11.3%) patients of which fatigue and rash were the most common (14 patients (6.3%) each). The confirmed objective response rate (ORR) was 9.8% for ICB-naïve UBC, 12.5% for ICB-experienced NSCLC, 8.3% for ICB-experienced UBC and 5.6% for ICB-experienced MEL patients, respectively. Tumor biopsy analyses demonstrated increased activated CD8 +tumor infiltrating T lymphocytes (TILs) associated with clinical benefit in ICB-naïve UBC patients and less tumor-associated macrophage (TAM) reduction in ICB-experienced compared with ICB-naïve patients. CONCLUSION: Emactuzumab in combination with atezolizumab demonstrated a manageable safety profile with increased fatigue and skin rash over usual atezolizumab monotherapy. A considerable ORR was particularly seen in ICB-experienced NSCLC patients. Increase ofCD8 +TILs under therapy appeared to be associated with persistence of a TAM subpopulation.
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 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".