Evidence map›Paper›PMID 34805353›Full record

ArticleAnnals of translational medicine2021

Bioinformatics analysis of high frequency mutations in myelodysplastic syndrome-related patients.

Kun Wu, Bo Nie, Liyin Li, Xin Yang, Jinrong Yang, Zhenxin He, Yanhong Li, Shenju Cheng, Mingxia Shi, Yun Zeng

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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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

10 authors at 2 institutions in 1 country.

Kun Wu *Department of Clinical Laboratory, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Bo Nie *Department of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China.
Liyin LiDepartment of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China.
Xin YangDepartment of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China.
Jinrong YangDepartment of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China.
Zhenxin HeDepartment of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China.
Yanhong LiDepartment of Clinical Laboratory, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Shenju ChengDepartment of Clinical Laboratory, First Affiliated Hospital of Kunming Medical University, Kunming, China.
Mingxia ShiDepartment of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China.
Yun ZengDepartment of Hematology, First Affiliated Hospital of Kunming Medical University, Hematology Research Center of Yunnan Province, Kunming, China.
First Affiliated Hospital of Kunming Medical University · CNKunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMyelodysplastic syndrome (MDS) is a group of hematological malignancies that may progress to acute myeloid leukemia (AML). Bioinformatics-based analysis of high-frequency mutation genes in MDS-related patients is still relatively rare, so we conducted our research to explore whether high-frequency mutation genes in MDS-related patients can play a reference role in clinical guidance and prognosis.

methodsNext generation sequencing (NGS) technology was used to detect 32 mutations in 64 MDS-related patients. We classified the patients' genes and analyzed them by Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, protein-protein interaction (PPI) analysis, and then calculated the gene survival curve of high-frequency mutations.

resultsWe discovered 32 mutant genes such as

conclusionsThirty-two mutant genes were determined in MDS and when mutations occur in

Indexed as

Gene Ontology (GO)Myelodysplastic syndrome (MDS)next generation sequencing (NGS)prognosisprotein-protein interaction (PPI)

Identifiers

PMID34805353
PMCPMC8573449
OpenAlexW3207710986

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.