Reproducibility of the NanoString 22‐gene molecular subgroup assay for improved prognostic prediction of medulloblastoma
Bibliographic record
Abstract
Medulloblastoma is the most frequent malignant brain tumor in children. Four medulloblastoma molecular subgroups, MBSHH, MBWNT, MBGRP3 and MBGRP4, have been identified by integrated high‐throughput platforms. Recently, a 22‐gene panel NanoString‐based assay was developed for medulloblastoma molecular subgrouping, but the robustness of this assay has not been widely evaluated. Mutations in the gene for human telomerase reverse transcriptase (hTERT) have been found in medulloblastomas and are associated with distinct molecular subtypes. This study aimed to implement the 22‐gene panel in a Brazilian context, and to associate the molecular profile with patients’ clinical‐pathological features. Formalin‐fixed, paraffin‐embedded (FFPE) medulloblastoma samples (n = 104) from three Brazilian centers were evaluated. Expression profiling of the 22‐gene panel was performed by NanoString and a Canadian series (n = 240) was applied for training phase. hTERT mutations were analyzed by PCR followed by direct Sanger sequencing and the molecular profile was associated with patients’ clinicopathological features. Overall, 65% of the patients were male, average age at diagnosis was 18 years and 7% of the patients presented metastasis at diagnosis. The molecular classification was attained in 100% of the cases, with the following frequencies: MBSHH (n = 51), MBWNT (n = 19), MBGRP4 (n = 19) and MBGRP3 (n = 15). The MBSHH and MBGRP3 subgroups were associated with older and younger patients, respectively. The MBGRP4 subgroup exhibited the lowest 5‐year cancer‐specific overall survival (OS), yet in the multivariate analysis, only metastasis at diagnosis and surgical resection were associated with OS. hTERT mutations were detected in 29% of the cases and were associated with older patients, increased hTERT expression and MBSHH subgroup. The 22‐gene panel provides a reproducible assay for molecular subgrouping of medulloblastoma FFPE samples in a routine setting and is well‐suited for future clinical trials.
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".