Evidence map›Paper›PMID 34901030›Full record

ArticleFrontiers in cell and developmental biology2021

Colon Cancer-Related Genes Identification and Function Study Based on Single-Cell Multi-Omics Integration.

Xuepu Sun, Yu Guo, Yu Zhang, Peng Zhao, Zhaoqing Wang, Zheng Wei, Haiquan Qiao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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  4. Review
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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

7 authors at 4 institutions in 1 country.

Xuepu SunThe First Affiliated Hospital of Harbin Medical University, Harbin, China.
Yu GuoSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
Yu ZhangDepartment of Neurosurgery, General Hospital of Heilongjiang Province Land Reclamation Bureau, Harbin, China.
Peng ZhaoSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Zhaoqing WangSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Zheng WeiThe First Affiliated Hospital of Harbin Medical University, Harbin, China.
Haiquan QiaoThe First Affiliated Hospital of Harbin Medical University, Harbin, China.
Harbin Institute of Technology · CNHarbin Medical University · CNFirst Affiliated Hospital of Harbin Medical University · CNHeilongjiang Academy of Land Reclamation Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcriptomes and DNA methylation of colon cancer at the single-cell level are used to identify marker genes and improve diagnoses and therapies. Seven colon cancer subtypes are recognized based on the single-cell RNA sequence, and the differentially expressed genes regulated by dysregulated methylation are identified as marker genes for different types of colon cancer. Compared with normal colon cells, marker genes of different types show very obvious specificity, especially upregulated genes in tumors. Functional enrichment analysis for marker genes indicates a possible relation between colon cancer and nervous system disease, moreover, the weak immune system is verified in colon cancer. The heightened expression of markers and the reduction of methylation in colon cancer promote tumor development in an extensive mechanism so that there is no biological process that can be enriched in different types.

Indexed as

colon cancercomprehensive analysismarker genesmethylationsingle celltranscriptome

Identifiers

PMID34901030
PMCPMC8657154
OpenAlexW3217463787

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.