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Enregistrement W2602310116 · doi:10.1182/blood.v128.22.607.607

Frequent Genetic Alterations of PI3K-AKT Pathway and Their Clinical Significance in Germinal Center B-Cell-like Diffuse Large B-Cell Lymphoma

2016· article· en· W2602310116 sur OpenAlexaff
Daisuke Ennishi, Ali Bashashati, Saeed Saberi, Anja Mottok, Barbara Meissner, Merrill Boyle, Susana Ben‐Neriah, Robert Kridel, David Dominguez-Sola, Kerry J. Savage, Laurie H. Sehn, Joseph M. Connors, Ryan D. Morin, Marco A. Marra, Sohrab P. Shah, Christian Steidl, David W. Scott, Randy D. Gascoyne

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensCanada's Michael Smith Genome Sciences CentreSimon Fraser UniversityBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésDiffuse large B-cell lymphomaPTENGerminal centerPI3K/AKT/mTOR pathwayCancer researchBiologyProtein kinase BLymphomaB cellGeneticsSignal transductionImmunology

Résumé

récupéré en direct d'OpenAlex

Abstract Diffuse large B cell lymphoma (DLBCL) comprises two distinct molecular subtypes: germinal center B cell (GCB) subtype and activated B cell (ABC) subtype. The pathogenesis of ABC-DLBCL is characterized by two processes - the activation of NF-KB and a block in terminal B-cell differentiation. However, in GCB-DLBCL only a few biologically relevant pathways have been identified, which has hampered the development of targeted therapies with specific efficacy in this subtype. Recurrent genetic alterations involved in PI3K-AKT signaling pathway have been identified in the patients with solid cancers, and dramatic responses have been observed to PI3K inhibitors in clinical trials. The prevalence and clinical significances of genetic alterations in PI3K-AKT pathway have not been well studied in DLBCL. Previous studies have reported that loss of PTEN expression was observed in almost half of GCB-DLBCL cases but were largely absent in the ABC-DLBCL. In addition, functional studies have recently shown that the inactivation of Gα13 signaling pathway genes may also activate AKT in germinal center driven lymphoma, raising the possibility that additional genes within these pathways are affected in GCB-DLBCL. Herein, we identified genetic alterations involved in the PI3K-AKT pathway and evaluated their clinical impact. We analyzed biopsies from 347 patients newly diagnosed with de novo DLBCL uniformly treated with R-CHOP at the BC Cancer Agency. High-resolution copy number analyses were performed using Affymetrix SNP 6.0 arrays. Mutation status was determined using deep targeted re-sequencing of the coding exons of 61 genes with a Truseq Custom Amplicon assay (Illumina) and/or Fluidigm Access Array chips, and RNAseq. Immunohistochemical staining of phospho-AKT (pAKT) was performed on tissue microarrays (n=332). Cell-of-origin (COO) was assigned by gene expression (Lymph2Cx assay) in 323 cases - 183 GCB, 104 ABC and 36 unclassifiable. GISTIC analysis revealed several COO-specific peaks with copy number changes. Among them, focal 10q23.3 deletion including PTEN was detected in GCB-DLBCL (q-value=1.7e-7), but not in ABC-DLBCL. We also identified two focal amplification peaks in GCB-DLBCL containing microRNAs MIR17HG (13q31.1;q=1.01e-24) and MIR21 (17q23.3; q=1.45e-6), which are known to down-regulate PTEN and result in activation of PI3K-AKT signaling. Furthermore, we detected recurrent INPP4B deletion (4q21.23) in GCB-DLBCL (q= 0.004) only. Of note, the lipid phosphatase INPP4B has been shown to play a role as a tumor suppressor that controls the levels of PI3K lipid products leading to AKT activation and metastasis of some solid cancers. This is consistent with the observation that PTEN and INPP4B deletions were individually associated with increased pAKT protein expression in our cohort (p=0.015 and p<0.0001, respectively). With respect to mutations, GNA13, P2RY8 and ARHGEF1 were more frequently mutated in the GCB than ABC subtype (26% vs 0.6%; p<.0001, 25% vs 7%; p=.0002, and 8% vs 0.5%; p=0.008, respectively). Previously known mutations of PI3KCA and PI3KCB were not recurrently observed in GCB-DLBCL. Based on these genetic data, we found that the PI3K-AKT signaling pathway was more commonly altered in GCB-DLBCL (64% (114/177)) than in ABC-DLBCL (23% (23/98) p<0.0001; Fig1). Consistent with this, pAKT protein expression was significantly higher in GCB-DLBCL than ABC-DLBCL (p<0.0001). The cases with higher pAKT protein expression (defined as the 25% highest pAKT protein expressors) were associated with significantly inferior outcome in GCB-DLBCL (5y-PFS 75% vs 59 %, p= 0.007 and 5y-OS 81% vs 64%, p=0.004; Fig2). At the genetic level PTEN and INPP4B deletions were individually associated with poor outcome in GCB-DLBCL (p=0.01 and p=0.045, respectively), and further, patients whose tumors harbored both genetic alterations had even worse prognosis (p= 0.004, Fig 3). In conclusion, genetic alterations in the PI3K-AKT pathway were frequently observed in GCB-DLBCL and were associated with activation of the pathway and inferior outcomes. These results suggested that AKT and mTOR inhibitors might be beneficial in a greater proportion of GCB-DLBCL than expected. Fig 1. The distribution of genetic alterations of PI3K-AKT pathway and pAKT protein expression. Fig 1. The distribution of genetic alterations of PI3K-AKT pathway and pAKT protein expression. KM curves according to pAKT protein expression (Fig 2) and PTEN and INPP4B deletions (Fig 3). KM curves according to pAKT protein expression (Fig 2) and PTEN and INPP4B deletions (Fig 3). Disclosures Sehn: roche/genentech: Consultancy, Honoraria; amgen: Consultancy, Honoraria; seattle genetics: Consultancy, Honoraria; abbvie: Consultancy, Honoraria; TG therapeutics: Consultancy, Honoraria; celgene: Consultancy, Honoraria; lundbeck: Consultancy, Honoraria; janssen: Consultancy, Honoraria. Connors:F Hoffmann-La Roche: Research Funding; Millennium Takeda: Research Funding; Seattle Genetics: Research Funding; Bristol Myers Squib: Research Funding; NanoString Technologies: Research Funding. Scott:NanoString Technologies: Patents & Royalties: named inventor on a patent for molecular subtyping of DLBCL that has been licensed to NanoString Technologies.

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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
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 Opus0,015
Tête enseignante GPT0,257
Écart entre enseignants0,241 · 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'étudeObservationnel
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

Citations1
Publié2016
Routes d'admission1
Résumé présentoui

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