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Record W3209155643 · doi:10.1158/1078-0432.ccr-21-2057

Clinically Tractable Outcome Prediction of Non-WNT/Non-SHH Medulloblastoma Based on TPD52 IHC in a Multicohort Study

2021· article· en· W3209155643 on OpenAlexafffund

Bibliographic record

VenueClinical Cancer Research · 2021
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick ChildrenCanada's Michael Smith Genome Sciences CentreChildren's & Women's Health Centre of British ColumbiaUniversity of British ColumbiaBC Cancer Agency
FundersCanadian Institutes of Health ResearchUniversity of British ColumbiaRussian Science FoundationHannah's Heroes FoundationStand Up To CancerKillam TrustsEntertainment Industry FoundationSt. Baldrick's FoundationAmerican Association for Cancer Research
KeywordsMedulloblastomaRisk stratificationImmunohistochemistryOutcome (game theory)Profiling (computer programming)

Abstract

fetched live from OpenAlex

Abstract Purpose: International consensus and the 2021 WHO classification recognize eight molecular subgroups among non-WNT/non-SHH (Group 3/4) medulloblastoma, representing approximately 60% of tumors. However, very few clinical centers worldwide possess the technical capabilities to determine DNA methylation profiles or other molecular parameters of high risk for group 3/4 tumors. As a result, biomarker-driven risk stratification and therapy assignment constitutes a major challenge in medulloblastoma research. Here, we identify an IHC marker as a clinically tractable method for improved medulloblastoma risk stratification. Experimental Design: We bioinformatically analyzed published medulloblastoma transcriptomes and proteomes identifying as a potential biomarker TPD52, whose IHC prognostic value was validated across three group 3/4 medulloblastoma clinical cohorts (n = 387) treated with conventional therapies. Results: TPD52 IHC positivity represented a significant independent predictor of early relapse and death for group 3/4 medulloblastoma [HRs between 3.67 and 26.7; 95% confidence interval (CI) between 1.00 and 706.23; P = 0.05, 0.017, and 0.0058]. Cross-validated survival models incorporating TPD52 IHC with clinical features outperformed existing state-of-the-art risk stratification schemes, and reclassified approximately 50% of patients into more appropriate risk categories. Finally, TPD52 immunopositivity was a predictive indicator of poor response to chemotherapy [HR, 12.66; 95% CI, 3.53–45.40; P < 0.0001], suggesting important implication for therapeutic choices. Conclusions: This study redefines the approach to risk stratification in group 3/4 medulloblastoma in global practice. Because integration of TPD52 IHC in classification algorithms significantly improved outcome prediction, this test could be rapidly adopted for risk stratification on a global scale, independently of advanced but technically challenging molecular profiling techniques.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.268
GPT teacher head0.564
Teacher spread0.297 · 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 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

Citations15
Published2021
Admission routes2
Has abstractyes

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