Evidence map›Paper›PMID 26397705›Full record

ArticlePloS one2015

Transcriptome Profiling of Pediatric Core Binding Factor AML.

Chih-Hao Hsu, Cu Nguyen, Chunhua Yan, Rhonda E Ries, Qing-Rong Chen, Ying Hu, Fabiana Ostronoff, Derek L Stirewalt, George Komatsoulis, Shawn Levy and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.1field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
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  4. Review
  5. Article
  6. Article
  7. BBA advances · 2022
    Article
  8. Clinical significance of CD34Frontiers of medicine · 2021
    Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Chih-Hao HsuCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America.
Cu NguyenCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America.
Chunhua YanCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America.
Rhonda E RiesFred Hutchinson Cancer Research Center, Seattle, WA, United States of America.
Qing-Rong ChenCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America.
Ying HuCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America.
Fabiana OstronoffFred Hutchinson Cancer Research Center, Seattle, WA, United States of America.
Derek L StirewaltFred Hutchinson Cancer Research Center, Seattle, WA, United States of America.
George KomatsoulisCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America.
Shawn LevyHudson Alpha Institute for Biotechnology, Huntsville, AL, United States of America.
Daoud MeerzamanCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, United States of America.
Soheil MeshinchiFred Hutchinson Cancer Research Center, Seattle, WA, United States of America.
National Cancer Institute · USFred Hutch Cancer Center · USHudsonAlpha Institute for Biotechnology · US

Funding

NCTN BIQSFP ANBL1531 (NRT)U10CA180886 · NCI · PUBLIC HEALTH INSTITUTE · PI Douglas S. Hawkins · 2014 to 2026
$390.6M
TRAINING IN CANCER BIOLOGY &TRANSPLANTATIONT32CA009515 · NCI · UNIVERSITY OF WASHINGTON · PI NANCY ELLEN DAVIDSON, Effie W Petersdorf · 1985 to 2026
$16.2M
Biology/prognostic implications of Flt3 mutations in AMLR01CA114563 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI MESHINCHI, SOHEIL · 2005 to 2016
$4.4M
NCI NIH HHS 5 R01 CA114563-08NCI NIH HHS R01 CA114563NCI NIH HHS T32 CA009515NCI NIH HHS U10 CA180886NCI NIH HHS U10CA180886
6 · The paper itself

Abstract

The t(8;21) and Inv(16) translocations disrupt the normal function of core binding factors alpha (CBFA) and beta (CBFB), respectively. These translocations represent two of the most common genomic abnormalities in acute myeloid leukemia (AML) patients, occurring in approximately 25% pediatric and 15% of adult with this malignancy. Both translocations are associated with favorable clinical outcomes after intensive chemotherapy, and given the perceived mechanistic similarities, patients with these translocations are frequently referred to as having CBF-AML. It remains uncertain as to whether, collectively, these translocations are mechanistically the same or impact different pathways in subtle ways that have both biological and clinical significance. Therefore, we used transcriptome sequencing (RNA-seq) to investigate the similarities and differences in genes and pathways between these subtypes of pediatric AMLs. Diagnostic RNA from patients with t(8;21) (N = 17), Inv(16) (N = 14), and normal karyotype (NK, N = 33) were subjected to RNA-seq. Analyses compared the transcriptomes across these three cytogenetic subtypes, using the NK cohort as the control. A total of 1291 genes in t(8;21) and 474 genes in Inv(16) were differentially expressed relative to the NK controls, with 198 genes differentially expressed in both subtypes. The majority of these genes (175/198; binomial test p-value < 10(-30)) are consistent in expression changes among the two subtypes suggesting the expression profiles are more similar between the CBF cohorts than in the NK cohort. Our analysis also revealed alternative splicing events (ASEs) differentially expressed across subtypes, with 337 t(8;21)-specific and 407 Inv(16)-specific ASEs detected, the majority of which were acetylated proteins (p = 1.5 x 10(-51) and p = 1.8 x 10(-54) for the two subsets). In addition to known fusions, we identified and verified 16 de novo fusions in 43 patients, including three fusions involving NUP98 in six patients. Clustering of differentially expressed genes indicated that the homeobox (HOX) gene family, including two transcription factors (MEIS1 and NKX2-3) were down-regulated in CBF compared to NK samples. This finding supports existing data that the dysregulation of HOX genes play a central role in biology CBF-AML hematopoiesis. These data provide comprehensive transcriptome profiling of CBF-AML and delineate genes and pathways that are differentially expressed, providing insights into the shared biology as well as differences in the two CBF subsets.

Indexed as

Gene Expression ProfilingAcetylationAlternative SplicingBinding SitesChromosome InversionChromosomes, Human, Pair 16Chromosomes, Human, Pair 21Chromosomes, Human, Pair 8Core Binding Factor Alpha 2 SubunitCore Binding Factor alpha SubunitsCore Binding Factor beta SubunitGene Regulatory NetworksHomeodomain ProteinsHumansKaryotypingLeukemia, Myeloid, AcuteCore Binding Factor Alpha 2 SubunitCore Binding Factor alpha SubunitsCore Binding Factor beta SubunitHomeodomain ProteinsMEIS1 protein, humanMyeloid Ecotropic Viral Integration Site 1 ProteinNeoplasm ProteinsNKX2-3 protein, humanTranscription Factors

Identifiers

PMID26397705
PMCPMC4580636
OpenAlexW2341654426

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.