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Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Defective DNA mismatch repair (dMMR) is associated with many cancer types including colon, gastric, endometrial, ovarian, hepatobiliary tract, urinary tract, brain and skin cancers. Lynch syndrome - a hereditary cause of dMMR - confers increased lifetime risk of malignancy in different organs and tissues. These Lynch syndrome pathogenic alleles are widely present in humans at a 1:320 population frequency of a single allele and associated with an up to 80% risk of developing microsatellite unstable cancer (microsatellite instability - high, or MSI-H). Advanced MSI-H tumors can be effectively treated with checkpoint inhibitors (CPI), however, that has led to response rates of only 30-60% despite their high tumor mutational burden and favorable immune gene signatures in the tumor microenvironment (TME). We and others have characterized a subset of MSI-H associated highly recurrent frameshift mutations that yield shared immunogenic neoantigens. These frameshifts might serve as targets for off-the-shelf cancer vaccine designs. In this review we discuss the current state of research around MSI-H cancer vaccine development, its application to MSI-H and Lynch syndrome cancer patients and the utility of MSI-H as a biomarker for CPI therapy. We also summarize the tumor intrinsic mechanisms underlying the high occurrence rates of certain frameshifts in MSI-H. Finally, we provide an overview of pivotal clinical trials investigating MSI-H as a biomarker for CPI therapy and MSI-H vaccines. Overall, this review aims to inform the development of novel research paradigms and therapeutics.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it