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Record W4399809563 · doi:10.1093/noajnl/vdae102

An update on central nervous system tumors in germline replication-repair deficiency syndromes

2024· review· en· W4399809563 on OpenAlexafffund
Anirban Das, Ayse B. Ercan, Uri Tabori

Bibliographic record

VenueNeuro-Oncology Advances · 2024
Typereview
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersStand Up To CancerCanadian Institutes of Health ResearchHospital for Sick ChildrenBristol-Myers SquibbV Foundation for Cancer Research
KeywordsGermlineReplication (statistics)MedicineBiologyCancer researchNeuroscienceGeneticsVirologyGene

Abstract

fetched live from OpenAlex

DNA replication-repair deficiency (RRD) arises from pathogenic variants in the mismatch repair and/or polymerase-proofreading genes. Multiple germline cancer predisposition syndromes in children and young adults, including constitutional mismatch repair deficiency (CMMRD), Lynch, polymerase-proofreading deficiency, and rare digenic syndromes can lead to RRD cancers. The most frequent brain tumors in these children are high-grade gliomas. Embryonal tumors like medulloblastoma have also been described. Lower-grade tumors are reported from cancer surveillance initiatives. The latter has an extremely high rate of malignant transformation. Novel functional assays quantifying the genomic microsatellite indel load have been demonstrated to be highly sensitive and specific for the diagnosis of RRD cancers and children with germline CMMRD. Importantly, RRD brain tumors uniformly harbor high mutation and microsatellite burden. High T-cell infiltration makes these aggressive cancers amenable to immune checkpoint inhibition, irrespective of their germline genetic background. Synergistic combinations are reported to be successful in patients failing checkpoint inhibitor monotherapy. Future directions include the development of innovative approaches to improve immune surveillance for RRD brain cancers. Additionally, the use of novel tools including circulating tumor DNA and quantifying microsatellite indel load over time can be useful to monitor disease burden and treatment responses in patients.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.004

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.

Opus teacher head0.036
GPT teacher head0.379
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations12
Published2024
Admission routes2
Has abstractyes

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