Is There a Role for Programmed Death Ligand-1 Testing and Immunotherapy in Colorectal Cancer With Microsatellite Instability? Part I—Colorectal Cancer: Microsatellite Instability, Testing, and Clinical Implications
Bibliographic record
Abstract
CONTEXT: - Colorectal cancer (CRC) represents the third most-common cancer in developed countries and is a leading cause of cancer deaths worldwide. Two recognized pathways contribute to CRC development: a more-common chromosomal instability pathway and, in 15% of cases, a deficient mismatch repair or microsatellite instability-high (MSI-H) pathway. The MSI-H CRC can be associated with somatic or germline mutations. Microsatellite status has been recognized as a prognostic and predictive biomarker. OBJECTIVES: - To summarize the molecular pathways of CRC, with an emphasis on the MSI (mismatch repair) pathway; the recommended MSI testing algorithms and interpretation; and the prognostic and predictive role of MSI-H status in personalized treatment, including adjuvant chemotherapy, targeted therapy, and immune checkpoint inhibitor therapy. DATA SOURCES: - A PubMed (US National Library of Medicine, Bethesda, Maryland) review was performed for articles pertaining to CRC, MSI and mismatch repair systems, molecular classification, immune response, programmed death receptor-1/programmed death ligand-1, and immunotherapy. CONCLUSIONS: - Although the TNM classification of malignant tumor stage remains the key determinant of CRC prognosis and treatment, there are considerable stage-independent, interindividual differences in clinical outcome and therapy response by patients. In addition, MSI-H status has an important role in CRC management and can be reliably detected by molecular and immunohistochemistry techniques and genetic testing. Efforts must be made to identify whether MSI-H CRC is germline or sporadic to ensure appropriate treatment, accurate prognosis, and risk assessment for relatives. Microsatellite status has been recognized as a good prognostic indicator and is predictive of a poor response to 5-fluorouracil-based chemotherapy and a good response to programmed death ligand-1 inhibitor pembrolizumab in metastatic/refractory MSI-H CRC.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".