Prognostic Impact of TS, MTHFR and XRCC1 Genetic Variants in 113 Patients with Myelodysplastic Syndromes
Notice bibliographique
Résumé
Abstract Background: Several studies have suggested that genetic variability related with single nucleotide polymorphisms (SNPs) of the BER system, DNA synthesis and folate-metabolizing pathway genes could modulate DNA repair capacity. Moreover, these genes are supposed to be related to cancer risk. However, the prognostic impact of the association of individual and/or combined genetic variants in patients with myelodysplastic syndromes (MDS) remains undetermined. Methods: We genotyped 113 MDS patients, 54 with IPSS low/int-1 receiving only best supportive care (BSC group) and 59 with IPSS int-2/high treated with azacitidine (AZA-group), for the following polymorphisms: XRCC1 194 and 399, APE1 148, XRCC3 241, TS5'-UTR (2R/3R and G/C) and 3'-UTR (6bp+/6bp-), MTHFR 677 and 1298. Genomic DNA was analyzed by High Resolution Melting assay and restriction digests of PCR products. Overall survival (OS) was calculated using the Kaplan-Meier estimate probabilities, and differences between survival curves were analyzed by the log-rank test. Multivariate analyses were performed using the Cox method. Results: For all the target genes, the distribution of genotypes was consistent with the Hardy-Weinberg equilibrium. Among the baseline characteristics analyzed (age, sex, diagnosis according to WHO, hemoglobin) there was no statistically significant difference in the genotype distribution of studied polymorphisms. In the BSC group, the variants XRCC1 399 GG [Hazard ratio (HR)=7.07; p=0.02], -6/-6 of TS3'-UTR (HR=4.65; p=0.05), 2R/3G, 3C/3G, 3G/3G of TS5'-UTR (HR=11.44; p=0.02) and TT of MTHFR 677 (HR=67.12; p<0.001), were associated with a statistically significant adverse clinical outcome compared to variant alleles (Table 1). This is consistent with the enzymatic activity reduction attributed to these genetic variants. Multivariable regression model analysis was also performed in the AZA group for the same genetic variants. We found similar results for the association between XRCC1 399 GG(HR=5.71 p=0.002), TS3'-UTR +6/+6(HR=0.097 p=0.004), MTHFR 677 TT (HR=8.58 p<0.001) and survival, but not for SNPs in TS5'-UTR (Table 2). Finally, we performed an exploratory analysis to investigate the combined effect of the unfavorable genotypes on survival. In the BSC group, the 3-year OS was 33% for those patients with ≥2 variant alleles, as compared to 62.5%, and 100%, respectively, for those with 2 or 0/1 variant alleles. The predictive role of the adverse genotypes combination on survival was confirmed also in the AZA group, suggesting that patients with a higher number of genetic variants had a shorter survival. Interestingly, when we compared survival of patients with adverse genotypes between BSC and AZA groups, we did not find any statistically significant difference between the 2 groups (Kaplan-Meyer and Log-rank test). Therefore, we speculated that azacitidine could give a survival advantage to patients with unfavorable genetic variants, independently from IPSS at diagnosis. Conclusion: Our study reveals, for the first time, an associations between genetic variants in TS, MTHFR and XRCC1 genes, BSC, azacitidine and survival in MDS patients. If confirmed, they could represent new prognostic markers able to provide guidance for clinical management of MDS patients. In particular, the presence of adverse genotypes could represent a biomarker to treat patients with low-risk IPSS with azacitidine, if confirmed on larger series. Further studies with larger population are needed to validate these associations, especially in SNPs with low variant allele frequency. Table 1. Gene Genotype Hazard risk 95,0% CI forHazard Risk Lower 95,0% CI forHazard Risk Upper p value XRCC1 399 [G/G] versus [A/G-A/A] 7,072 1,295 38,619 0,024 TS5'-UTR [3G/3G, 3G/3C, 2R/3G] versus [2R/2R, 2R/3C, 3C/3C] 11,447 1,330 98,544 0,026 TS3'-UTR [Del/Del] versus [Del/Ins, Ins/Ins] 4,653 0,946 22,874 0,058 MTHFR 677 [T/T] versus [C/T-C/C] 67,125 6,409 703,081 <0,001 Table 2. Gene Genotype Hazard risk 95,0% CI forHazard Risk Lower 95,0% CI forHazard Risk Upper p value XRCC1 399 [G/G] versus [A/G-A/A] 5,713 1,904 17,142 0,002 TS3'-UTR [Ins/Ins] versus [Ins6/del6, del6/del6] 0,097 0,019 0,479 0,004 MTHFR 677 [T/T] versus [C/T-C/C] 8,587 2,749 26,828 <0,001 Disclosures Finelli: Celgene: Other: Speaker, Research Funding; Novartis: Other: Speaker; Janssen: Other: Speaker.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 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) | 0,001 | 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 ».