High Prevalence of TERT Mutations in Chronic Lymphocytic Leukemia
Notice bibliographique
Résumé
Abstract Heritable mutations in the genes that encode the three minimal components of the human telomerase complex, hTERT, hTERC and DKC are known to give rise to Dyskeratosis Congenita (DC), a rare disorder characterized by skin pigmentation abnormalities, nail dystrophy and leukoplakia. Telomeres in leukocytes of patients with DC are invariably very short and patients typically succumb to consequences of bone marrow failure, pulmonary fibrosis or malignancies. Other genetic defects including mutations in the telomeric protein TINF2 are also known to give rise to DC. However, not all individuals with mutations in “telomere maintenance” genes such as TERT, TERC, DKC and TINF2 will develop clinical symptoms during their lifetime and some patients, without clinical signs of DC, present with aplastic anemia (AA) and idiopathic pulmonary fibrosis (IPF). It was previously shown that hypomorphic mutations in hTERT are 3-fold more common in patients with acute myeloid leukemia (AML) than in controls (Calado et al., ASH abstracts 2007 110: 16). Together with the increased incidence of malignancies in DC these observations suggest that telomere dysfunction can trigger dysplastic as well as neoplastic disorders, most likely because progressive telomere loss results in loss of normal cells and thereby selects for cells with defects in the DNA damage checkpoint(s) that are normally triggered when chromosome ends have insufficient telomere repeats. Such cells are expected to have DNA repair defects and their malignant evolution could be facilitated further by telomere dysfunction triggering cycles of chromosome fusions/bridge/breakage before telomerase is eventually upregulated. In view of these considerations and the important role of telomeres in B cell biology (with telomeres being elongated in the germinal centre and memory B cells having longer telomeres than naïve B cells) we postulated that heritable genetic defects in telomere maintenance could predispose to B cell malignancies as well as AML. To test this hypothesis we sequenced TERC and TERT genes in 80 consecutive CLL patients. No mutations in TERC were found. Sequence variants in TERT were identified in 14 patients with one patient, a compound heterozygous, carrying 2 separate mutations. 5 of the 80 CLL patients carried the A279T TERT variant but this allele was also present in ~ 3% of control individuals. This TERT allele did not significantly reduce telomerase activity in telomerase reconstitution experiments measured by TRAP assay. All other TERT sequence variants that we found in CLL appear to be hypomorhic mutations (that reduce but not completely disable telomerase reverse transcriptase activity) and all were previously described in DC, AA, AML and IPF. Two common variants, D441E and A1062T were screened by high throughput dotblotting of DNA from CLL patients and frequencies of 3/142 (2.1 %) and 12/195 (6.2 %) were found respectively. The presumed germline origin of the TERT mutations in CLL needs to be confirmed. Our results indicate that hypomorphic TERT mutations are common in CLL and contribute to disease in over 10% of patients.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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.
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 ».