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Record W4229450225 · doi:10.4103/0028-3886.344608

Germline Biallelic Mismatch Repair Deficiency in Childhood Glioblastoma and Implications for Clinical Management

2022· article· en· W4229450225 on OpenAlexaff
Avijeet Kumar Mishra, Rimpa Basu Achari, Lateef Zameer, Gopal Achari, Anisha Gehani, Paromita Roy, Sumedha Sudhaman, Vanessa Bianchi, Melissa Edwards, Saugata Sen, Reghu K. Sukumaran, Arpita Bhattacharyya, Uri Tabori, Anirban Das

Bibliographic record

VenueNeurology India · 2022
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsPMS2MedicineDNA mismatch repairTemozolomideMicrosatellite instabilityLynch syndromeGermline mutationImmunotherapyFamily historyOncologyCancerInternal medicineCancer researchGliomaMutationColorectal cancerGeneticsAlleleGene

Abstract

fetched live from OpenAlex

We report a case of a 9-year-old boy with glioblastoma with a past history of colon cancer. Germline bi-allelic DNA-mismatch repair deficiency was diagnosed by a lack of immunohistochemical staining for PMS2 in the tumor and normal tissue. Family history was lacking. Sequencing confirmed compound heterozygous PMS2 mutations. A second hit in the DNA-polymerase-ε gene led to complete DNA-replication repair deficiency. This contributed to an ultra-hypermutated phenotype. Temozolomide was excluded from the treatment. PD-1 immunotherapy at recurrence contributed to extending post-relapse survival up to 11 months. Challenges included managing initial immune "flare" related to "pseudo-progression" and access to drug. Family screening diagnosed the sibling with Lynch syndrome. This is the first report of a child with a brain tumor treated with immunotherapy from India. Our report supports the routine inclusion of immunohistochemistry for mismatch repair proteins in the evaluation of pediatric high-grade glioma as this may directly impact the clinical care of these children and families.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.334
Teacher spread0.308 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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