Evidence map›Paper›PMID 35116245›Full record

ArticleTranslational cancer research2021

Identification of six hub genes and analysis of their correlation with drug sensitivity in acute myeloid leukemia through bioinformatics.

Daxia Cai, Jiajian Liang, Xing-Dong Cai, Ying Yang, Gexiu Liu, Fenling Zhou, Dongmei He

Open access · diamondAbstract read
In one paragraph

Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Transcriptome Analysis in Mexican Adults with Acute Lymphoblastic Leukemia.International journal of molecular sciences · 2024
    Article
  5. Article
  6. Article
  7. Secretome profiling ofFrontiers in oncology · 2023
    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

7 authors at 2 institutions in 1 country.

Daxia CaiInstitute of Hematology, Jinan University, Guangzhou, China.
Jiajian LiangInstitute of Hematology, Jinan University, Guangzhou, China.
Xing-Dong CaiDepartment of Respiratory, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Ying YangHealth Management Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Gexiu LiuInstitute of Hematology, Jinan University, Guangzhou, China.
Fenling ZhouInstitute of Hematology, Jinan University, Guangzhou, China.
Dongmei HeInstitute of Hematology, Jinan University, Guangzhou, China.
Jinan University · CNFirst Affiliated Hospital of Jinan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute myeloid leukemia (AML) is a common hematopoietic malignancy and have unsatisfactory prognosis. Our study aimed to identify hub genes in AML and explore potential biomarkers through integrated bioinformatics.

methodsMicroarray datasets were analyzed to screen the differentially expressed genes (DEGs). Functional enrichment analysis was performed, and protein-protein interaction (PPI) network was generated by the STRING (11.0) database and Cytoscape (3.7.2) software. Hub genes were screened and verified through GEPIA2 and GEO microarray database. Sensitivity of AML cell lines with high expression of hub genes to the small-molecule drugs were identified using GSCA Lite.

resultsA total of 456 DEGs were identified and top 100 genes were screened out, of which six genes (

conclusionsIn summary,

Indexed as

Acute myeloid leukemia (AML)differentially expressed genes (DEGs)drug sensitivitysurvival

Identifiers

PMID35116245
PMCPMC8798452
OpenAlexW3127442661

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.