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Molecular alterations to predict survival and response to chemotherapy of pediatric low-grade glioma.

2017· article· en· W2890657694 on OpenAlexaff
Michal Zápotocký, Scott Ryall, Anthony Arnoldo, Matthew Mistry, Álvaro Lassaletta, Ana Guerreiro Stücklin, Rahul Krishnatry, Vijay Ramaswamy, Suzanne Laughlin, Peter B. Dirks, Annie Huang, Ute Bartels, Éric Bouffet, Uri Tabori, Cynthia Hawkins

Bibliographic record

VenueJournal of Clinical Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineChemotherapyNeurofibromatosisInternal medicineOncologyGliomaCohortTargeted therapyPathologyCancer researchCancer

Abstract

fetched live from OpenAlex

10503 Background: RAS/MAPK pathway mutations have been identified as the major drivers of pediatric low-grade glioma (pLGG). The impact of these alterations on outcome and response to therapy is still unknown. Methods: We performed a large population based study of all pLGG diagnosed from 1985-2015. Detailed treatment and very long term outcome data was collected on all patients. Known pLGG-related alterations were detected using NanoString and QX200™Droplet Digital™PCR. Molecular data was correlated with outcome and response to chemotherapy. Results: In our cohort of 614 patients, BRAF was found to be altered in 57% and wild-type (WT) in 43% of patients without neurofibromatosis 1 (NF1). Among BRAF-WT we identified H3.3K27M, FGFR1-TACC1, MYBL1 and other alterations. Molecular alterations stratified pLGG into several risk groups. Ten-year progression free survival (PFS) was 72.3% for NF1, 69.5% for KIAA1549-BRAF, 53.5% for BRAF-WT, 30.3% for BRAF-V600E and 0% for H3.3K27M mutations (p < 0.0001). Similarly, overall survival (OS) at 10 years delineated difference between excellent survival of KIAA1549-BRAF and NF1 compared to BRAF-V600E and BRAF-WT (p = 0.0005). Interestingly, all patients with FGFR1-TACC1 and MYBL1 were alive despite observed progressions. Strikingly, response to chemotherapy determined by changes in tumor size at 6 months of therapy correlated with pLGG alteration. Objective response to first line chemotherapy was observed in 46% of patients with KIAA1549-BRAF and 35% of NF1. In contrast, only 15% BRAF-V600E and 18% BRAF-WT responded and 41% tumors grew after six months of chemotherapy. Moreover, 5-year PFS after chemotherapy was strikingly low for BRAF-V600E and BRAF-WT (25% and 31.9% respectively) compared to KIAA1549-BRAF (50%) and NF1 (76.7%) (p = 0.001). This translated to decreased OS for BRAFV600E and BRAF-WT patients (p = 0.042). Conclusions: Our study provides evidence that molecular alterations dictate the outcome of pLGG. KIAA1549-BRAF harbors excellent prognosis and choice of therapy should be made in favor of less toxic agents to minimize deleterious late effects. In contrast, poor prognosis is associated with lack of response to chemotherapy in BRAF-V600E and BRAF-WT tumors.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.083
GPT teacher head0.465
Teacher spread0.381 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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