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Long Noncoding RNA Expression Independently Predicts Outcome in Pediatric Acute Myeloid Leukemia.
Farrar, Jason E; Smith, Jenny L; Othus, Megan; Huang, Benjamin J; Wang, Yi-Cheng; Ries, Rhonda; Hylkema, Tiffany; Pogosova-Agadjanyan, Era L; Challa, Sneha; Leonti, Amanda; Shaw, Timothy I; Triche, Timothy J; Gamis, Alan S; Aplenc, Richard; Kolb, E Anders; Ma, Xiaotu; Stirewalt, Derek L; Alonzo, Todd A; Meshinchi, Soheil.
Afiliação
  • Farrar JE; Department of Pediatrics, Arkansas Children's Research Institute, University of Arkansas for Medical Sciences, Little Rock, AR.
  • Smith JL; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Othus M; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Huang BJ; Department of Pediatrics, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA.
  • Wang YC; Children's Oncology Group, Monrovia, CA.
  • Ries R; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Hylkema T; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Pogosova-Agadjanyan EL; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Challa S; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Leonti A; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Shaw TI; Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL.
  • Triche TJ; Center for Epigenetics, Van Andel Research Institute, Grand Rapids, MI.
  • Gamis AS; Department of Pediatrics, Children's Mercy Hospitals and Clinics, Kansas City, MO.
  • Aplenc R; Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA.
  • Kolb EA; Nemours Center for Cancer and Blood Disorders and Alfred I. DuPont Hospital for Children, Wilmington, DE.
  • Ma X; Department of Computational Biology, St Jude Children's Research Hospital, Memphis, TN.
  • Stirewalt DL; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Alonzo TA; Children's Oncology Group, Monrovia, CA.
  • Meshinchi S; Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA.
J Clin Oncol ; 41(16): 2949-2962, 2023 06 01.
Article em En | MEDLINE | ID: mdl-36795987
PURPOSE: Optimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML. METHODS: To identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis. RESULTS: Training set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays. CONCLUSION: Inclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda / RNA Longo não Codificante Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Clin Oncol Ano de publicação: 2023 Tipo de documento: Article País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Leucemia Mieloide Aguda / RNA Longo não Codificante Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Clin Oncol Ano de publicação: 2023 Tipo de documento: Article País de publicação: Estados Unidos