Controversies and management of deficient mismatch repair gastrointestinal cancers in the neoadjuvant setting
Bibliographic record
Abstract
High microsatellite instability (MSI-H)/deficient mismatch repair (dMMR) phenotype is a distinct molecular signature across gastrointestinal cancers characterized by high tumor mutational burden and high neoantigen load. Tumors harboring dMMR are highly immunogenic and heavily infiltrated by immune cells; consequently, they are uniquely vulnerable to therapeutic strategies enhancing immune antitumor response such as checkpoint inhibitors. The MSI-H/dMMR phenotype arose as a powerful predictor of response to immune checkpoint inhibitors with evidence supporting significantly improved outcomes in the metastatic setting. On the other hand, the genomic instability characteristic of MSI-H/dMMR tumors appears to be associated with decreased sensitivity to chemotherapy, and the benefits of standard adjuvant or neoadjuvant chemotherapy approaches in this subtype are being increasingly questioned. Here, we review the prognostic and predictive impact of MMR status in localized gastric and colorectal cancers, and highlight the emerging clinical data incorporating checkpoint inhibitors in the neoadjuvant setting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".