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Enregistrement W2646599743 · doi:10.1182/blood.v128.22.1212.1212

Expanded Phenotypic and Genetic Heterogeneity in the Clinical Spectrum of FPD-AML: Lymphoid Malignancies and Skin Disorders Are Common Features in Carriers of Germline RUNX1 Mutations

2016· article· en· W2646599743 sur OpenAlexaff
Anna Brown, Christopher N Hahn, Catherine Carmichael, Ella Wilkins, Milena Babic, Chan‐Eng Chong, Xiaochun Li, Joëlle Michaud, Ping Cannon, Nicola Poplawski, Meryl Altree, Kerry Phillips, Louise Jaensch, Miriam Fine, Andreas Schreiber, Jinghua Feng, Lesley Rawlings, Cassandra Vakulin, Carolyn M Butcher, Richard J. D’Andrea, Ian D. Lewis, Nigel Patton, Cecily Forsyth, Sally Mapp, Helen Mar Fan, Rachel Susman, Sue Morgan, Julian Cooney, Mark S. Currie, Uday Popat, Kenneth F. Bradstock, April Sorrell, Carolyn Owen, Marshall S. Horwitz, Devendra Hiwase, Alwin Krämer, Stefan Fröhling, Lucy A. Godley, Jane E. Churpek, Hamish S. Scott

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésPlatelet disorderRUNX1GermlineGermline mutationGeneticsLeukemiaBiologyCancer researchMutationCEBPAMedicineImmunologyGeneHaematopoiesisStem cellPlatelet

Résumé

récupéré en direct d'OpenAlex

Abstract Background: This year, germline predisposition to haematological malignancy (HM) debuts in the World Health Organization classification of myeloid neoplasms and acute leukemia (Blood, 2016;127:2391). It has been 17 years since germline mutations in RUNX1 were found to lead to familial platelet disorder (FPD) with predisposition to myelodysplastic syndrome and acute myeloid leukaemia (MDS/AML) (Nat Genet. 1999;23:166). Now, nearly 80 families have been reported with damaging germline mutations or deletions affecting RUNX1 function, associated with FPD, making it an increasingly significant clinical presence. Although thrombocytopenia and platelet dysfunction are present in almost all RUNX1 mutant carriers, we and others have observed that the predisposition to HM varies between family members, with respect to age at diagnosis and the type of malignancy, and in some cases RUNX1 mutation carriers have no apparent HM development over their lifespan. The reasons for this heterogeneity are currently unknown. Aims: We are conducting an international collaborative study examining RUNX1 mutated families. The aim of the research project is to classify the range of phenotypes correlated with RUNX1 mutations comprehensively (including non-malignant phenotypes such as skin disorders) and to determine if the type of RUNX1 mutation and the presence of other germline and acquired mutations in relevant HM genes correlate with the likelihood of HM development, or the type of HM that develops. Across all of our data we aim to analyse clinically relevant information that will be used to inform prognosis and clinical management in germline RUNX1 mutation carriers. Results:From a review of the literature for previously characterised RUNX1 mutant families most mutations are predicted to be loss-of-function, with the combination of frameshift, stopgain, splicing and deletion accounting for the majority of alterations (57, 70%) compared to missense mutations (22, Figure 1). The most common sites of mutation are R201 and R204, affected by both missense and stopgain (10 total), which lie within the nuclear localisation signal at the end of the RUNT domain (Figure 1). We also surveyed in detail 12 RUNX1 pedigrees with both novel and previously described missense, frameshift, stopgain and deletion mutations and found that, while all families developed myeloid malignancies, 6 families also had individuals who developed lymphoid malignancy (most often Acute lymphoblastic leukemia (ALL)) which was heritable in sub-families, and subject to anticipation (e.g see IV-5 and V-5 in Figure 2). Consistent with population genome wide association studies identifying RUNX1 as a susceptibility locus for psoriasis (J Autoimmun. 2015;64:66), we find that skin conditions (psoriasis, eczema) are common, and present in germline RUNX1 carriers in 50% of our families; most commonly observed in families with stopgain and frameshift mutations. Genomic analysis of selected samples confirms that mutation of the other RUNX1 allele is the most commonly acquired mutation in germline RUNX1 mutation carriers developing HM. Alterations of chromosomes 21 and 7 are also common. DNMT3A and PHF6 acquired mutations were the next most frequently observed in tumors and mutations in U2AF1 and ASXL1 in the blood of RUNX1 carriers without HM were observed, suggestive of pre-HM clonal expansion. Finally, in a family with a novel R169I RUNX1 mutation, a rare germline ASXL1 variant (E1102D, 1.0% in ExAC) was found in two RUNX1 carriers who developed early onset AML. This variant is also significantly enriched in an MDS cohort unselected for family history compared to the general population (HR 1.3, p=0.02), as well as ASXL1 N986S (0.1% in ExAC, HR 3.3, p=0.0002) suggesting they operate as germline HM risk modifiers. Interestingly RUNX1 and ASXL1 acquired mutations often co-occur in sporadic MDS/AML and our data suggests this collaboration may also occur at the germline level. Conclusions:Annotation of skin phenotypes co-existent with a family history of haematological malignancy may assist in identifying RUNX1 mutant families. Both acquired and germline mutations in known HM genes may modify germline RUNX1 driven HM penetrance and phenotype. Our data suggest that screening of RUNX1 germline mutation carriers for germline and acquired variants in other HM genes could provide an important tool for defining risk and requires further investigation. Disclosures Owen: Pharmacyclics: Research Funding; Janssen: Honoraria; Roche: Honoraria, Research Funding; Novartis: Honoraria; Gilead: Honoraria, Research Funding; Lundbeck: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Abbvie: Honoraria. Godley:UpToDate: Honoraria; Onconova, Inc.: Research Funding.

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)0,001
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 enseignants0,003
Score d'incertitude au seuil0,012

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
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 ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,018
Tête enseignante GPT0,311
Écart entre enseignants0,294 · 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

Citations4
Publié2016
Routes d'admission1
Résumé présentoui

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