Evidence map›Paper›PMID 26317787›Full record

ArticleOncotarget2015

MicroRNA biomarker identification for pediatric acute myeloid leukemia based on a novel bioinformatics model.

Wenying Yan, Lihua Xu, Zhandong Sun, Yuxin Lin, Wenyu Zhang, Jiajia Chen, Shaoyan Hu, Bairong Shen

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

36 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Aberrant stem cell and developmental programs in pediatric leukemia.Frontiers in cell and developmental biology · 2024
    Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Exosomal MiRNAs in Pediatric Cancers.International journal of molecular sciences · 2019
    Review
  13. Article
  14. Article
  15. Article
  16. MiRNA Dysregulation in Childhood Hematological Cancer.International journal of molecular sciences · 2018
    Review
  17. Article
  18. Article
  19. Article
  20. 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

8 authors at 2 institutions in 1 country.

Wenying YanCenter for Systems Biology, Soochow University, Suzhou, 215006, China.
Lihua XuDepartment of Hematology and Oncology, Children's Hospital of Soochow University, Suzhou 215003, China.
Zhandong SunCenter for Systems Biology, Soochow University, Suzhou, 215006, China.
Yuxin LinCenter for Systems Biology, Soochow University, Suzhou, 215006, China.
Wenyu ZhangCenter for Systems Biology, Soochow University, Suzhou, 215006, China.
Jiajia ChenSchool of Chemistry, Biology and Material Engineering, Suzhou University of Science and Technology, Suzhou 215011, China.
Shaoyan HuDepartment of Hematology and Oncology, Children's Hospital of Soochow University, Suzhou 215003, China.
Bairong ShenCenter for Systems Biology, Soochow University, Suzhou, 215006, China.
Soochow University · CNSuzhou University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute myeloid leukemia (AML) in children is a complex and heterogeneous disease. The identification of reliable and stable molecular biomarkers for diagnosis, especially early diagnosis, remains a significant therapeutic challenge. Aberrant microRNA expression could be used for cancer diagnosis and treatment selection. Here, we describe a novel bioinformatics model for the prediction of microRNA biomarkers for the diagnosis of paediatric AML based on computational functional analysis of the microRNA regulatory network substructure. microRNA-196b, microRNA-155 and microRNA-25 were identified as putative diagnostic biomarkers for pediatric AML. Further systematic analysis confirmed the association of the predicted microRNAs with the leukemogenesis of AML. In vitro q-PCR experiments showed that microRNA-155 is significantly overexpressed in children with AML and microRNA-196b is significantly overexpressed in subgroups M4-M5 of the French-American-British classification system. These results suggest that microRNA-155 is a potential diagnostic biomarker for all subgroups of paediatric AML, whereas microRNA-196b is specific for subgroups M4-M5.

Indexed as

Computational BiologyAdolescentAge of OnsetBiomarkers, TumorChildChild, PreschoolDatabases, GeneticGene Expression RegulationGene Regulatory NetworksGenetic Association StudiesGenetic Predisposition to DiseaseHumansInfantInfant, NewbornLeukemia, Myeloid, AcuteMicroRNAsBiomarkers, TumorMicroRNAsMIRN155 microRNA, humanMIRN196 microRNA, humanbioinformatics modelmicroRNA biomarkersmicroRNA regulatory networkpediatric acute myeloid leukemiatranscription factor

Identifiers

PMID26317787
PMCPMC4694912
OpenAlexW2118088736

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.