A Phase II Study of Perioperative Avelumab plus Chemotherapy for Patients with Resectable Gastric Cancer or Gastroesophageal Junction Cancer – The MONEO Study
Bibliographic record
Abstract
PURPOSE: Immune checkpoint inhibitors combined with chemotherapy have provided successful results in patients with gastric and gastroesophageal junction (G/GEJ) cancers in the metastatic setting. Similar strategies have been explored in earlier stages. In this study, we present the final results of the phase II MONEO trial, which evaluated the addition of avelumab to neoadjuvant chemotherapy. PATIENTS AND METHODS: Patients with untreated, resectable G/GEJ adenocarcinoma received neoadjuvant treatment with four cycles of avelumab plus the FLOT4 regimen, followed by surgery. Upon postoperative recovery, patients underwent four additional adjuvant cycles of the same combination, followed by avelumab monotherapy for up to 1 year. The primary endpoint was pathologic complete response rate. Sequential flow cytometry and cytokine determination were performed in peripheral blood, along with multiplex tissue immunofluorescence and RNA sequencing in tumor specimens. RESULTS: Forty patients were enrolled, achieving a pathologic complete response rate of 21.1% (95% confidence interval, 10.0-37.0). The major pathologic response rate was 28.9%, more pronounced in patients with tumors expressing PD-L1 before treatment as measured by the combined positive score (cutoff, 10; 33.3% vs. 21.1%). The results propose several potential biomarkers considering tumor immune infiltrate, circulating immune cells, and cytokines. Eighty percent of patients experienced treatment-related grade ≥3 adverse events. CONCLUSIONS: The combination of avelumab plus the FLOT4 regimen showed relatively modest efficacy in resectable G/GEJ adenocarcinoma. Better results were observed in PD-L1 combined positive score ≥10% tumors. Exploratory biomarker analyses provide insights that may help to identify candidates most likely to benefit from chemoimmunotherapy as a neoadjuvant treatment.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".