Somatic Mutations in TET2, but Not SF3B1, Are Prevalent during Normal Aging Hematopoiesis in Human
Notice bibliographique
Résumé
Abstract BACKGROUND. Somatic mutations acquired in the course of a lifetime contribute to the aging process and to the development of age-associated diseases including cancers. Our capacity to identify such events in the normal aging population prior to the appearance of malignancy is of utmost clinical importance to devise prevention or early intervention strategies. This is particularly relevant to myeloid cancers such as acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS) which incidence increases dramatically with age. Recently, next-generation sequencing (NGS) efforts have helped to establish lists of recurrently mutated genes in these cancers. With these lists of candidate genes in hand, it is now possible to look for the presence of low frequency pre-malignant somatic lesions in the aging population. The contribution of these mutations to cancer development can then be assessed in longitudinal studies. We have previously shown (Nature Genet, 2012; 44:179), that somatic mutations in the epigenetic regulator gene TET2 occur in the normal aging population and is associated with clonal derivation of cells. However, little is known about the occurrence of mutation in other categories of frequently mutated gene in MDS such as the splicing factor SF3B1, which is the second mostly frequently mutated gene after TET2. SUBJECTS AND METHODS. We have selected 217 individuals based on age (>70 years) and clonality status from a well characterized cohort of normal aging individuals (n=4000). This cohort is comprised of women mostly aged greater than 60 years and without any known hematological disorder (medical history reviewed and normal complete blood counts at enrollment). We obtained blood cells and buccal epithelial cells from each subject. Blood cells were separated into polymorphonuclear (PMN) cells and mononuclear cells using standard procedures. T cells (CD3+) were further isolated from mononuclear cells. DNA and RNA were then isolated from all cell populations. X-chromosome inactivation (XCI) patterns at the HUMARA locus was determined in PMN, T-cells to assess the clonality of myeloid derived cells. MUTATIONAL ANALYSIS. We have developed a custom next generation sequencing approach using Ion AmpliSeq libraries on an Ion Torrent PGM sequencer. Extensive experimental validation and algorithm optimisation were performed to ensure the quality of the method, control experiments with positive and negative controls were done to demonstrate the specificity, while dilution curves were run to validate the sensitivity of mutation detection down to 5% variant allele frequency (VAF) at 500x mean coverage. The final validated design is composed of 65 amplicons spanning 9.78kb covering TET2 at 100% and 53 amplicons spanning 8.84kb covering SF3B1at 95.61% including all known hot spots. RESULTS. 14/207 subject had acquired (present in PMN, not in T-cells or epithelial cells) mutation in the TET2 gene in line with our previous results. The VAF varied between 6 and 47%, all mutation were further validated by Sanger sequencing. In contrast to TET2, no subject had mutation in SF3B1gene. CONCLUSION. Mutation in the SF3B1gene does not occur at a significant frequency in the aging population suggesting that alteration of this gene is not an early initiating event in the pathogenesis of MDS. This further suggest that in contrast to the extended number of genes mutated in MDS, only a limited number are likely to be found and implicated in the pre-leukemic phase. It is possible that epigenetic alterations, and not dysfunction of the spliceosome, could be a driving force underlying the pathogenesis of MDS. Complete exome sequencing and iterative studies will help decipher the sequence of events leading to age-associated myeloid cancer. Disclosures No relevant conflicts of interest to declare.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».