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Enregistrement W2900883426 · doi:10.1182/blood-2018-99-113918

High Expression of SPAG1 Is Associated with a Worse Clinical Outcome in Intermediate Risk Acute Myeloid Leukemia That Can be Partially Overcome By Hematopoietic Stem Cell Transplantation

2018· article· en· W2900883426 sur OpenAlexaff
Guillaume Richard‐Carpentier, Miriam Marquis, Guy Sauvageau, Josée Hébert

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensInstitute for Research in Immunology and CancerUniversité de MontréalHôpital Maisonneuve-Rosemont
Organismes subventionnairesnon disponible
Mots-clésNPM1CEBPAOncologyInternal medicineHematopoietic stem cell transplantationHazard ratioMedicineTransplantationMyeloid leukemiaUnivariate analysisProportional hazards modelImmunologyMultivariate analysisBiologyKaryotypeGeneConfidence interval

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Acute myeloid leukemia (AML) is a heterogeneous disease with variable responses to therapy and clinical outcomes. Cytogenetics and molecular analyses help to stratify patients and to select therapy, especially regarding indication of hematopoietic stem cell transplant (HSCT) after achieving complete remission (CR). Patients in the intermediate cytogenetic risk category (~40%) represent a clinical dilemma regarding consolidation because of the high rate of relapse with chemotherapy alone and high rate of morbidity/mortality with HSCT. Consequently, we aimed to identify new prognostic markers to refine the risk stratification of this patients' subgroup and to identify which patients are most likely to benefit from HSCT. Methods: We analyzed RNA sequencing data of 263 specimens from patients with de novo AML treated with curative intent including 165 patients with intermediate risk cytogenetics. Data from 24 586 genes were normalized as RPKM values with logarithmic transformation and standardization. Cox proportional hazard models were used to assess the prognostic impact of gene expression (GE) on overall survival (OS) and relapse-free survival (RFS). We performed univariate analyses (UVA) and multivariate analyses (MVA) adjusted for age and white blood cell count (WBC) at diagnosis, mutations in NPM1, FLT3, CEBPA, RUNX1, ASXL1, TP53 and DNMT3A and HSCT as a time-dependent (TD) covariate. Interaction between GE and TD-HSCT was tested in MVA for OS and RFS. Genes with a significant interaction between GE and TD-HSCT (p < 0.10) were retained for further analyses. GE of candidate markers were dichotomized using a bioinformatic method assessing hazard ratios (HR) and p values for all potential cut-offs to identify the most optimal threshold. The markers were finally reassessed as dichotomic variables for association with covariates, CR rates, RFS and OS. All statistical tests were two-sided with p values < 0.05 considered significant. Results: We identified SPAG1 (Sperm Associated Antigen 1) as the gene with the highest HR for OS and RFS in the intermediate cytogenetic risk group. SPAG1 expression was dichotomized on the median RPKM value in the global cohort of 263 de novo AML specimens (RPKM cut-off 2.06). Using this cut-off, 79 patients had low expression of SPAG1 and 86 patients had high expression of SPAG1 in the intermediate cytogenetic risk cohort. Median age, sex, WBC at diagnosis and HSCT in CR1 rates were similar between the two groups. Patients with high expression of SPAG1 had a higher frequency of FLT3-ITD (51.2% vs 32.9%, p = 0.02) and DNMT3A mutations (51.2% vs 32.9%, p = 0.02). SPAG1-high patients were enriched in the NPM1/FLT3-ITD/DNMT3A triple positive mutation population (SPAG1-high 24/33 vs SPAG1-low 9/33, OR 3.00, p = 0.01). The frequencies of all other analyzed mutations were similar between both groups. CR rates did not differ between the two groups (SPAG1-high 77.9% vs SPAG1-low 79.7%, p = 0.77). In UVA with censorship at time of HSCT, SPAG1-high patients had worse OS (5-year estimates 14.2% vs 28.1%, HR 1.75, 95% CI 1.16-2.63, p < 0.01) and RFS (5-year estimates 9.3% vs 27.1%, HR 1.90, 95% CI 1.20-3.01, p < 0.01) (Figure 1). In MVA with censorship at time of HSCT, high expression of SPAG1 remained significantly associated with OS (HR 1.78, 95% CI 1.12-2.83, p = 0.01) and RFS (HR 2.34, 95% CI 1.38-3.96, p < 0.01). Furthermore, there was a significant interaction between SPAG1 GE and TD-HSCT (p = 0.09) in the RFS model. Importantly, SPAG1 had a lower prognostic impact for RFS in the model including TD-HSCT (HR 1.65, 95% CI 1.07-2.55, p = 0.02) compared with the model in which survival was censored at time of HSCT (HR 2.34, p < 0.01). High SPAG1 expression was also associated with worse OS in the TCGA AML dataset which is enriched in intermediate cytogenetic risk samples (p < 0.001). Conclusion: In patients with intermediate cytogenetic risk AML, high expression of SPAG1 is independently associated with worse OS and RFS. The prognostic impact of SPAG1 expression on RFS is lower when adjusted for TD-HSCT indicating that the adverse prognosis conferred by high expression of this gene may be partially overcome by HSCT in CR1. Consequently, SPAG1 expression might help identify AML patients with intermediate cytogenetic risk who are most likely to benefit from HSCT in CR1. These results need to be validated in other independent cohorts and prospective studies before implementation into clinics. Disclosures Sauvageau: ExCellThera: Employment, Equity Ownership.

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)0,000
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 enseignants0,002
Score d'incertitude au seuil0,005

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,027
Tête enseignante GPT0,303
Écart entre enseignants0,276 · 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

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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