Evidence map›Paper›PMID 30237752›Full record

ArticleCancer cell international2018

Identification of critical genes to predict recurrence and death in colon cancer: integrating gene expression and bioinformatics analysis.

Xuan Long, Zhigang Deng, Guoqiang Li, Ziwei Wang

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

15 citing papers in PubMed, 19 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

Xuan Long1Department of Gastroenterological Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, 1# Youyi Road, Chongqing, 400016 People's Republic of China.
Zhigang Deng2Department of General Surgery, Mianyang Central Hospital, Mianyang, 621000 Sichuan People's Republic of China.
Guoqiang Li2Department of General Surgery, Mianyang Central Hospital, Mianyang, 621000 Sichuan People's Republic of China.
Ziwei Wang1Department of Gastroenterological Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing Medical University, 1# Youyi Road, Chongqing, 400016 People's Republic of China.
Mianyang Central Hospital · CNChongqing Medical University · CNFirst Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe purpose of this study was to screen the critical genes for future diagnosis and treatment of colon cancer by bioinformatics method.

methodsIn this study, we used bioinformatics approaches to identify gene alteration that contribute to colon cancer progression via analysis of TCGA RNA sequencing data and other publicly GEO microarray data. The Random forest survival model was used to screen gene sets related to the prognosis in DEGs. Gene ontology and KEGG pathway enrichment analysis were performed to determine the potential function of DEGs.

resultsWe identified versican (VCAN), a member of the aggrecan/versican proteoglycan family, as a key regulator in human colon cancer development and progression involved in cell adhesion, proliferation, migration and angiogenesis and plays a central role in tissue morphogenesis and maintenance. Interestingly, we found that VCAN is highly over-expressed in colon cancer and increased expression of VCAN was associated with the progression of colon cancer. High VCAN levels also predict shorter overall survival of colon cancer patients. Furthermore, in vitro assays of silencing VCAN inhibit HCT116 cell proliferation and invasion.

conclusionsThese data demonstrated VCAN were associated with tumorigenesis and may be as biomarker for identification of the pathological grade of colon cancer.

Indexed as

BiomarkerColon cancerVCAN

Identifiers

PMID30237752
PMCPMC6142417
OpenAlexW2889772346

What Socratic 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 Socratic graph.