Evidence map›Paper›PMID 16418266›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2006

Gene expression profiles in acute myeloid leukemia with common translocations using SAGE.

Sanggyu Lee, Jianjun Chen, Guolin Zhou, Run Zhang Shi, Gerard G Bouffard, Masha Kocherginsky, Xijin Ge, Miao Sun, Nimanthi Jayathilaka, Yeong Cheol Kim and 13 more

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 17% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Modeling the Hematopoietic Landscape.Frontiers in cell and developmental biology · 2019
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Analysis of Chromosomal Aberrations and FLT3 gene Mutations in Childhood Acute Myelogenous Leukemia Patients.Turkish journal of haematology : official journal of Turkish Society of Haematology · 2012
    Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
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

23 authors at 1 institution in 1 country.

Sanggyu LeeDepartment of Medicine, University of Chicago, IL 60637, USA.
Jianjun Chen
Guolin Zhou
Run Zhang Shi
Gerard G Bouffard
Masha Kocherginsky
Xijin Ge
Miao Sun
Nimanthi Jayathilaka
Yeong Cheol Kim
Neelmini Emmanuel
Stefan K Bohlander
Mark Minden
Justin Kline
Ozden Ozer
Richard A Larson
Michelle M LeBeau
Eric D Green
Jeffery Trent
Theodore Karrison
Piu Paul Liu
San Ming Wang
Janet D Rowley
Translational Genomics Research Institute · US

Funding

UCCRC--ETIOLOGY OF TREATMENT-INDUCED SECONDARY LEUKEMIAP01CA040046 · NCI · UNIVERSITY OF CHICAGO · PI LE BEAU, MICHELLE M · 1985 to 2012
$19.9M
Multi-Species Comparative Sequencing of Targeted GenomicZ01HG000196 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI GREEN, ERIC · 2001 to 2008
$19.1M
MOLECULAR PATHOGENESIS OF CHROMOSOME 16 INVERSION INHUMAN LEUKEMIAZ01HG000030 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI LIU, PU PAUL · 1995 to 2008
$2.5M
Identification of novel genes in human genomeR01HG002600 · NHGRI · UNIVERSITY OF CHICAGO · PI WANG, SAN MING · 2003 to 2005
$1.7M
MAPPING AND CLONING TRANSLOCATION BREAKPOINTSR01CA084405 · NCI · UNIVERSITY OF CHICAGO · PI ROWLEY, JANET D · 2000 to 2004
$1.5M
Intramural NIH HHSNCI NIH HHS CA40046NCI NIH HHS CA84405NCI NIH HHS P01 CA040046NCI NIH HHS R01 CA084405NHGRI NIH HHS R01 HG002600
6 · The paper itself

Abstract

Identification of the specific cytogenetic abnormality is one of the critical steps for classification of acute myeloblastic leukemia (AML) which influences the selection of appropriate therapy and provides information about disease prognosis. However at present, the genetic complexity of AML is only partially understood. To obtain a comprehensive, unbiased, quantitative measure, we performed serial analysis of gene expression (SAGE) on CD15(+) myeloid progenitor cells from 22 AML patients who had four of the most common translocations, namely t(8;21), t(15;17), t(9;11), and inv(16). The quantitative data provide clear evidence that the major change in all these translocation-carrying leukemias is a decrease in expression of the majority of transcripts compared with normal CD15(+) cells. From a total of 1,247,535 SAGE tags, we identified 2,604 transcripts whose expression was significantly altered in these leukemias compared with normal myeloid progenitor cells. The gene ontology of the 1,110 transcripts that matched known genes revealed that each translocation had a uniquely altered profile in various functional categories including regulation of transcription, cell cycle, protein synthesis, and apoptosis. Our global analysis of gene expression of common translocations in AML can focus attention on the function of the genes with altered expression for future biological studies as well as highlight genes/pathways for more specifically targeted therapy.

Indexed as

Gene Expression RegulationGene Expression Regulation, NeoplasticTranslocation, GeneticApoptosisCell DifferentiationChromosomes, Human, Pair 11Chromosomes, Human, Pair 9Computational BiologyDNA, ComplementaryExpressed Sequence TagsGene Expression ProfilingGene LibraryHumansLeukemiaLeukemia, Myeloid, AcuteLeukocytes, MononuclearDNA, ComplementaryLewis X AntigenRNARNA, Messenger

Identifiers

PMID16418266
PMCPMC1347995
OpenAlexW2144264159

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.