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Enregistrement W4310112231 · doi:10.1182/blood-2022-165616

Extranodal Marginal Zone Lymphomas Show Recurrent Mutations in DNA Repair Genes, Cancer-Associated Proliferative Signaling and NOTCH1 Signaling Pathways, Regardless of Anatomic Site

2022· article· en· W4310112231 sur OpenAlexaffabout
Jennifer R. Chapman‐Fredricks, Devang Thakkar, Juan Pablo Alderuccio, Kikkeri N. Naresh, Sarah L. Ondrejka, Eric D. Hsi, Mina L. Xu, Nathan Paulson, Jean L. Koff, David L. Jaye, Jonathon B. Cohen, Anne Ortved Gang, Rebecca J. Leeman‐Neill, Tushar Dave, Lanie E. Happ, Cassandra Love, Sasan Zandi, Hina Naushad, Emily F. Mason, Abner Louissaint, Haley Martin, Choon Kiat Ong, Raju Pillai, Mette Ølgod Pedersen, C. Cameron Yin, William Choi, Rex Au-Yeung, Marja‐Liisa Karjalainen‐Lindsberg, Amy Chadburn, Vincent Sarno, Matthew McKinney, Payal Sojitra, Andrew G. Evans, Amir Behdad, Carlos Galvez, Chee Leong Cheng, Magdalena Czader, Jiong Yan, Sandeep S. Davé, Izidore S. Lossos

Notice bibliographique

RevueBlood · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésExomeBiologyTranscriptomePopulationHematopathologyGeneticsGeneExome sequencingCancer researchMedicineMutationGene expressionChromosomeCytogenetics

Résumé

récupéré en direct d'OpenAlex

Extranodal marginal zone lymphomas (EMZL) are usually indolent B cell lymphomas arising in acquired mucosa-associated lymphoid tissue (MALT) as a result of chronic antigen stimulation from infection or autoimmune processes. EMZLs occurring at different MALT sites have shared and unique genetic events including site-associated chromosomal structural changes and mutations. While large scale genetic analyses of EMZL are lacking, previous small studies have shown that EMZL often show activation of NF-κB through chronic stimulation of the B cell receptor and other cooperating genetic events that include somatic mutations, most frequently in TNFAIP3. Here, we report the largest whole exome sequencing (WES) and copy number (CN) analysis to date in EMZL. Formalin-fixed paraffin-embedded (FFPE) samples of EMZL were collected as part of the Atlas of Blood Cancer Genomes (ABCG) consortium. All cases underwent central pathology review by expert hematopathologists and diagnoses were confirmed as defined by the 2016 WHO classification. We defined global CN gains and losses at log2 fold change value of ±0.3, a value used by many CN tools. DNA and RNA WES were performed using the Illumina platform and DNA and RNA reads aligned to the GRCh38 genome and transcriptome, respectively. Exonic variants were identified and filtered using normal samples and population-based databases to identify putative driver mutations which were then aggregated at the gene level. Mutational analysis was done on samples that passed quality filtering. 225 unique diagnostic specimens were collected from 24 academic hematopathology departments. Cases originated from North America (USA and Canada, 86%), Europe (8%), and Asia (Singapore and China, 6%). 72 tumors were excluded due to inadequate mean coverage related to size of the biopsy or its quality. CN analysis and WES to identify non-silent mutations was performed in 153 unique EMZL including ocular adnexal (31), stomach (26), lung (23), salivary gland (23), and other extranodal locations (50). Average patient age was 63 years (range 53-71 years), female: male ratio of 1.6. Mutation calls identified 718 variants (613 missense mutations and 105 truncating mutations) across 59 putative driver genes detected in ≥5% cases across all the anatomic locations. Among the most commonly mutated genes, we detected genes previously reported to be altered by targeted sequencing in EMZL (e.g., SPEN (12%), TNFAIP3 (A20) (8%), CREBBP (8%), TBL1XR1 (7%), and others) confirming our filtering strategy. A total of 44 focal CN alterations (24 gains and 20 CN losses) were detected for our set of recurrently mutated genes. Global CN gains included chromosome 3 (6%), 6p (7%), 8 (3%), 12 (4%), and 18 (5%) and losses in 21p (10%). Previously described tumor suppressor genes such as TNFAIP3 showed a typical pattern of alterations consisting of CN losses (6q23.3 deletion in 6%) and/or mostly truncating mutations (8%). Combining DNA mutations and CN alterations, the number of genetic lesions per tumor sample in the 59 putative driver genes ranged from 1 to 21, with an average load of 4.9 aberrations per case, consistent with previous genetic studies in other types of MZL lymphoma. The most frequent mutations across all sites were IGLL5 (22%), KMT2C (15%), KMT2D (14%), SPEN (12%), PRDM2 (11%), and NCOR1 (10%). Analysis using Elsevier Pathway Collection, BioPlanet 2019 and Go Biological Process 2021 revealed adjusted statistically significant enrichment of aberrations in genes in NOTCH signaling, DNA repair, cancer-associated sustaining of proliferative signaling, cancer associated histone methylation and positive regulation of transcription, by DNA-templated (GO:0045893) and RNA polymerase II (GO:0045944). Many of the mutated genes were previously not reported in EMZL. Some of the mutations were shared by tumors at different anatomic locations while some were more unique. Mutations in TET2, previous reported as specific for thyroid EMZL, were also detected in ocular adnexa, gastric and salivary gland MZL. Mutations in PTPRD, previously suggested as specific for NMZL, were detected also in EMZL. Overall, this analysis of a large number of samples from different anatomic locations further refines the mutational landscape in EMZL and provides novel clues on pathogenesis. More detailed analyses of mutations, CN variations and RNA expression will be presented at the meeting.

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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,009

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 savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,019
Tête enseignante GPT0,251
Écart entre enseignants0,232 · 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
Publié2022
Routes d'admission2
Résumé présentoui

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