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Enregistrement W2988560554 · doi:10.1182/blood-2019-132223

Targeting Neurotrophic Receptor Tyrosine Kinase (NTRK) Fusion Structural Homologs in Refractory Pediatric Acute Lymphoblastic Leukemia (ALL)

2019· article· en· W2988560554 sur OpenAlexaff
Son Tran, Mehul Gupta, Sunand Kannappan, Chunfen Zhang, Aru Narendran

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Lymphoblastic Leukemia research
Établissements canadiensAlberta Children's HospitalUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésTrk receptorTyrosine kinaseCancer researchMedicineFusion geneBiologyBioinformaticsReceptorInternal medicineNeurotrophinGeneGenetics

Résumé

récupéré en direct d'OpenAlex

Introduction: Currently, the 5-year overall survival rate in relapsed pediatric ALL patients is only about 30%. Hence, new treatment approaches are urgently needed. Tyrosine receptor kinase (TRK) signalling pathways have been previously implicated in pediatric ALL relapse, although efficacious molecularly targeted therapies remain elusive. Larotrectinib is a recently approved inhibitor of Neurotrophic Receptor Tyrosine Kinase (NTRK) fusion proteins. Clinical trials have shown high efficacy of Larotrectinib, with limited side effects, in both adult and pediatric solid tumours. Here we show substantial homology between common NTRK fusion proteins and candidate members of the SRC family of TRKs, as well as high binding affinity of Larotrectinib to identified candidates and an impact on patient survival and prognosis. Our data provide the first evidence for a unique therapeutic approach for a subpopulation of refractory pediatric ALL. Methods: Using AutoDock Vina, molecular docking studies were conducted between Larotrectinib and multiple NTRK fusion structures to identify interaction regions with high affinity for Larotrectinib. Structural homologs with significant homology and coverage of substantial interaction regions were identified, and binding affinity to Larotrectinib was compared between the NTRK fusion structures and the identified homologs. To evaluate differential expression of these homologs, the mRNA expression of pediatric ALL bone marrow and normal bone marrow was collected from the GSE7186 dataset on the Gene Expression Omnibus (GEO). P-values of differential expression between ALL and normal mRNA expression of genes that encode for the identified homologs was determined. To evaluate the prognostic potential of the identified homologs in pediatric ALL, mRNA expression z-scores and overall survival data were collected from the recently published TARGET ALL dataset on cBioPortal. mRNA expression z-scores for the identified homologs were separated into quartiles, and survival of patients within the top and bottom quartiles were compared using the Kaplan-Meier survival analysis and the log-rank test for statistical significance. To evaluate the therapeutic potential of Larotrectinib, an inhibitor of both NTRK and the identified homologs was selected and its IC50 z-scores across cell lines and mRNA expression z-scores were analyzed from Genomics of Drug Sensitivity (GDSC) and Cancer Cell Line Encyclopedia (CCLE). IC50s were then compared between ALL and other cell lines. Spearman correlation values between the IC50s and mRNA expression of the identified homologs across all cell lines were verified to evaluate dose-dependency. Results: Four structural homologs were identified with significant homology and coverage with the NTRK fusion structures: FYN, YES1, FGR and SRC. Binding affinities to Larotrectinib for NTRK fusion structures and the identified homologs were not statistically significantly different. Differentially expressed genes in T-cell ALL were FYN (p=0.008), and YES1 (p=0.057) and in B-cell ALL was FYN (p=0.016). Kaplan-Meier survival analysis showed that poor prognosis was associated with low expression of FYN (p=0.006) and YES1 (p=0.000) and with high expression of FGR (p=0.068) and SRC (p=0.252). WZ3105 was identified as another inhibitor of both NTRK and the SRC kinase family, and IC50 of ALL cell lines were shown to be significantly more sensitive to this inhibitor than all other cell lines (p=0.016). Spearman analysis showed significant correlation between IC50s of WZ1305 and cell line mRNA expression of SRC (p=0.015) and FGR (p=0.027), indicating dose-dependency. Conclusion: In addition to NTRK fusion structures, Larotrectinib has been found to have substantial binding affinity with several members of the SRC kinase family. Among the homologs, both FYN and YES1 showed significant differential expression and prognostic significance in ALL. Interestingly, high expressions FGR and SRC are associated with poor prognosis in ALL, therefore representing potential targets. The Larotrectinib analog, WZ3105, is particularly efficacious in ALL cell lines, and dose-dependency with FGR and SRC expression. As such, we provide molecular bioinformatics and data from experimental studies for the potential therapeutic efficacy of Larotrectinib in pediatric ALL, as an inhibitor for NTRK fusion structural homologs, specifically FGR and SRC. Disclosures Narendran: Bayer: Honoraria, Other: CANTRK Advisory Board .

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,009
Tête enseignante GPT0,253
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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