Evidence map›Paper›PMID 19222862›Full record

ArticleBMC systems biology2009

Using cell fate attractors to uncover transcriptional regulation of HL60 neutrophil differentiation.

Albert C Huang, Limei Hu, Stuart A Kauffman, Wei Zhang, Ilya Shmulevich

Open access · diamondAbstract readComparative Study
In one paragraph

Article in BMC systems biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

15 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. AClinical and experimental immunology · 2021
    Article
  3. A roadmap towards personalized immunology.NPJ systems biology and applications · 2018
    Article
  4. Article
  5. A global assessment of stem cell engineering.Tissue engineering. Part A · 2014
    Article
  6. Article
  7. Article
  8. Modeling and visualizing cell type switching.Computational and mathematical methods in medicine · 2014
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Systems biology of stem cell fate and cellular reprogramming.Nature reviews. Molecular cell biology · 2009
    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

5 authors at 4 institutions in 2 countries.

Albert C HuangUniversity of Washington, Seattle, USA. achuang@u.washington.edu
Limei Hu
Stuart A Kauffman
Wei Zhang
Ilya Shmulevich
The University of Texas MD Anderson Cancer Center · USSeattle University · USUniversity of Calgary · CAUniversity of Washington · US

Funding

Quantitative Systems BiologyP50GM076547 · NIGMS · INSTITUTE FOR SYSTEMS BIOLOGY · PI BALIGA, NITIN S · 2006 to 2016
$30.6M
Genetic Regulatory Networks: Comp. &Ext. InvestigationsR01GM072855 · NIGMS · UNIVERSITY OF TEXAS MD ANDERSON CAN CTR · PI SHMULEVICH, ILYA · 2004 to 2009
$1.0M
Genomic Characterization - Differentiation &HomeostasisR21GM070600 · NIGMS · UNIVERSITY OF TEXAS MD ANDERSON CAN CTR · PI SHMULEVICH, ILYA · 2004 to 2005
$403k
NIGMS NIH HHS P50 GM076547NIGMS NIH HHS R01 GM072855NIGMS NIH HHS R21 GM070600
6 · The paper itself

Abstract

backgroundThe process of cellular differentiation is governed by complex dynamical biomolecular networks consisting of a multitude of genes and their products acting in concert to determine a particular cell fate. Thus, a systems level view is necessary for understanding how a cell coordinates this process and for developing effective therapeutic strategies to treat diseases, such as cancer, in which differentiation plays a significant role. Theoretical considerations and recent experimental evidence support the view that cell fates are high dimensional attractor states of the underlying molecular networks. The temporal behavior of the network states progressing toward different cell fate attractors has the potential to elucidate the underlying molecular mechanisms governing differentiation.

resultsUsing the HL60 multipotent promyelocytic leukemia cell line, we performed experiments that ultimately led to two different cell fate attractors by two treatments of varying dosage and duration of the differentiation agent all-trans-retinoic acid (ATRA). The dosage and duration combinations of the two treatments were chosen by means of flow cytometric measurements of CD11b, a well-known early differentiation marker, such that they generated two intermediate populations that were poised at the apparently same stage of differentiation. However, the population of one treatment proceeded toward the terminally differentiated neutrophil attractor while that of the other treatment reverted back toward the undifferentiated promyelocytic attractor. We monitored the gene expression changes in the two populations after their respective treatments over a period of five days and identified a set of genes that diverged in their expression, a subset of which promotes neutrophil differentiation while the other represses cell cycle progression. By employing promoter based transcription factor binding site analysis, we found enrichment in the set of divergent genes, of transcription factors functionally linked to tumor progression, cell cycle, and development.

conclusionSince many of the transcription factors identified by this approach are also known to be implicated in hematopoietic differentiation and leukemia, this study points to the utility of incorporating a dynamical systems level view into a computational analysis framework for elucidating transcriptional mechanisms regulating differentiation.

Indexed as

Binding SitesCD11b AntigenCell DifferentiationComputational BiologyFlow CytometryGene Expression RegulationHL-60 CellsHumansMicroarray AnalysisNeutrophilsPromoter Regions, GeneticTretinoinCD11b AntigenTretinoin

Identifiers

PMID19222862
PMCPMC2652435
OpenAlexW2048939079

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.