Deciphering the FGFR2 Code: Innovative Targets in Gastric Cancer Therapy
Bibliographic record
Abstract
Gastric cancer (GC) represents a major global health challenge as a highly prevalent disease with high mortality whose global incidence and mortality are predicted to worsen over the coming years. To date, our standard of care for advanced gastric cancer of combination chemotherapy and immunotherapy has a 1-year overall survival rate of 55%. Significant efforts have gone into identifying targetable alterations in gastric cancer, ultimately yielding the Fibroblast Growth Factor Receptors (FGFRs) family, specifically FGFR2 as a promising target. FGFR2 is overexpressed in GC, particularly diffuse-type GC, and is associated with poor prognostic outcomes. In recent years, there has been an increasing number of small molecule inhibitors and monoclonal antibodies targeting FGFR2 that have entered into clinical trials. Specifically for GC, these agents are currently being trialed in various phases as monotherapies or with standard-of-care treatments to make a clinically meaningful impact on what appears to be an important biological axis of GC. In this review, we outline the underlying biology of FGFR2, its putative role in GC, and the various FGFR2-targeted agents currently in clinical trials for gastric cancer patients as well as postulate some challenges in adopting these therapeutics for clinically meaningful benefit.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".