<scp>IDH</scp> mutation, glioma immunogenicity, and therapeutic challenge of primary mismatch repair deficient <scp>IDH</scp>‐mutant astrocytoma <scp>PMMRDIA</scp>: a systematic review
Bibliographic record
Abstract
In 2021, Suwala et al. described Primary Mismatch Repair Deficient IDH-mutant Astrocytoma (PMMRDIA) as a distinct group of gliomas. In unsupervised clustering, PMMRDIA forms distinct cluster, separate from other IDH-mutant gliomas, including IDH-mutant gliomas with secondary mismatch repair (MMR) deficiency. In the published cohort, three patients received treatment with an immune checkpoint blocker (ICB), yet none exhibited a response, which aligns with existing knowledge about the decreased immunogenicity of IDH-mutant gliomas in comparison to IDH-wildtype. In the case of PMMRDIA, the inherent resistance to the standard-of-care temozolomide caused by MMR deficiency is an additional challenge. It is known that a gain-of-function mutation of IDH1/2 genes produces the oncometabolite R-2-hydroxyglutarate (R-2-HG), which increases DNA and histone methylation contributing to the characteristic glioma-associated CpG island methylator phenotype (G-CIMP). While other factors could be involved in remodeling the tumor microenvironment (TME) of IDH-mutant gliomas, this systematic review emphasizes the role of R-2-HG and the subsequent G-CIMP in immune suppression. This highlights a potential actionable pathway to enhance the response of ICB, which might be relevant for addressing the unmet therapeutic challenge of PMMRDIA.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".