Evidence map›Paper›PMID 42087892›Full record

ArticleHuman mutation2026

Multiomics Analysis of Nucleotide Metabolism Highlights the Important Role of Adenylate Kinase 4 in Pancreatic Cancer.

Jun Li, Yiqun Yao, Wei Zhang, Dianlong Zhang

Abstract read
In one paragraph

Article in Human mutation, 2026. 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
–field-weighted citation impact
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.

  1. Review
  2. 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

4 authors.

Jun LiDepartment of Breast and Thyroid Surgery, The Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China.ORCID https://orcid.org/0000-0001-8030-4474
Yiqun YaoDepartment of Breast and Thyroid Surgery, The Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China.ORCID https://orcid.org/0000-0002-1106-2114
Wei ZhangState Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment, School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian, Liaoning, China, dlut.edu.cn.ORCID https://orcid.org/0000-0002-8475-3143
Dianlong ZhangDepartment of Breast and Thyroid Surgery, The Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China.ORCID https://orcid.org/0009-0009-7212-9464

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nucleotide metabolism significantly influences tumor cell proliferation, yet its specific profile in pancreatic cancer remains inadequately understood. This study was aimed at characterizing the nucleotide metabolic profile in pancreatic cancer and assessing the contribution of the key gene adenylate kinase (AK) 4. Multiomics data, including transcriptomic, single-cell sequencing, spatial transcriptomic, and metabolomics datasets, were obtained from publicly accessible platforms. The impact of AK4, a key gene of nucleotide metabolism, on the proliferation and migration of pancreatic cancer cells was investigated using various molecular biological techniques. Nucleotide pathway-related metabolites exhibited marked differences in abundance between pancreatic cancer tissues and normal pancreatic tissues. Single-cell sequencing analysis identified MKI67

Indexed as

Adenylate KinaseNucleotidesPancreatic NeoplasmsBiomarkers, TumorCell Line, TumorCell ProliferationGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMetabolomicsMultiomicsPrognosisSingle-Cell Gene Expression AnalysisTranscriptomeTumor MicroenvironmentAdenylate KinaseBiomarkers, TumorNucleotidesadenylate kinase 4metabolomics analysisnucleotide metabolismpancreatic cancerRNA-seq analysissingle-cell sequencing analysisspatial transcriptomics analysis

Identifiers

PMID42087892
PMCPMC13136522

What OpenQuestion holds

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LicenceCC BY
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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.