Safety and Antitumor Activity of α-PD-L1 Antibody as Monotherapy or in Combination with α-TIM-3 Antibody in Patients with Microsatellite Instability–High/Mismatch Repair–Deficient Tumors
Bibliographic record
Abstract
PURPOSE: Immune checkpoint inhibitors show high response rates and durable clinical benefit in microsatellite instability-high/mismatch repair-deficient (MSI-H/dMMR) tumors. However, 50%-60% do not respond to single-agent anti-programmed death-1/programmed death ligand 1 (PD-1/PD-L1) antibodies, and approximately 50% of responders relapse within 6-12 months. This phase Ib trial evaluated safety and antitumor activity of anti-PD-L1 antibody LY3300054 monotherapy or in combination with anti-TIM-3 antibody LY3321367 in patients with MSI-H/dMMR advanced solid tumors. PATIENTS AND METHODS: = 22). LY3300054 (700 mg) and anti-TIM-3 antibody (cycles 1-2: 1,200 mg, cycle 3 onward: 600 mg) were administered intravenously every 2 weeks. Primary endpoints were safety and tolerability. RESULTS: = 14, 17.1%) tumors. More than 70% of patients in the PD-1/PD-L1 inhibitor-resistant/refractory combination cohort had received ≥3 treatment lines. Treatment-related adverse events (TRAE) occurred in 22 patients (55.0%) receiving monotherapy, 13 (65.0%) in the PD-1/PD-L1 inhibitor-naïve combination cohort, and 6 (27.3%) in the PD-1/PD-L1 inhibitor-resistant/refractory combination cohort. A total of 2 patients (5.0%) receiving monotherapy and 3 (7.1%) receiving the combination experienced grade ≥3 TRAEs. Objective responses occurred in 13 patients (32.5%) with monotherapy, 9 (45.0%) in the PD-1/PD-L1 inhibitor-naïve combination cohort, and 1 patient (4.5%) in the PD-1/PD-L1 inhibitor-resistant/refractory combination cohort. CONCLUSIONS: LY3300054 monotherapy and combined LY3300054/anti-TIM-3 had manageable safety profiles. Both regimens showed promising clinical activity against PD-1/PD-L1 inhibitor-naïve MSI-H/dMMR tumors. The combination had limited clinical benefit in patients with PD-1/PD-L1 inhibitor-resistant/refractory MSI-H/dMMR tumors.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".