Evidence map›Paper›PMID 33761685›Full record

Observational studyMedicine2021

Identification of core genes and clinical outcomes in tumors originated from endoderm (gastric cancer and lung carcinoma) via bioinformatics analysis.

Yewen Shi, Dongmin Chang, Wenhan Li, FengYu Zhao, Xiaoyong Ren, Bin Hou

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 32% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Expression ofIn vivo (Athens, Greece)
    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

6 authors at 4 institutions in 1 country.

Yewen ShiDepartment of Otorhinolaryngology Head and Neck Surgery, the Second Affiliated Hospital of Xi'an Jiaotong University.
Dongmin ChangDepartment of Surgical Oncology, the First Affiliated Hospital of Xi'an Jiaotong University.
Wenhan LiDepartment of Surgical Oncology, Shaanxi Provincial People's Hospital.
FengYu ZhaoDepartment of Surgical Oncology, the First Affiliated Hospital of Xi'an Jiaotong University.
Xiaoyong RenDepartment of Otorhinolaryngology Head and Neck Surgery, the Second Affiliated Hospital of Xi'an Jiaotong University.
Bin HouThe Third Affiliated Hospital, the School of Medicine Xi'an Jiaotong University.
First Affiliated Hospital of Xi'an Jiaotong University · CNSecond Affiliated Hospital of Xi'an Jiaotong University · CNShaanxi Provincial People's Hospital · CNXi'an Jiaotong University · CN

Funding

Shaanxi Key Science and Technology Innovation Team Project S2018-YF-ZDSF-0102
6 · The paper itself

Abstract

abstractDuring last decade, bioinformatics analysis has provided an effective way to study the relationship between various genes and biological processes. In this study, we aimed to identify potential core candidate genes and underlying mechanisms of progression of lung and gastric carcinomas which both originated from endoderm. The expression profiles, GSE54129 (gastric carcinoma) and GSE27262 (lung carcinoma), were collected from GEO database. One hundred eleven patients with gastric carcinoma and 21 health people were included in this research. Meanwhile, there were 25 lung carcinoma patients. Then, 75 differentially expressed genes were selected via GEO2R online tool and Venn software, including 31 up-regulated genes and 44 down-regulated genes. Next, we used Database for Annotation, Visualization, and Integrated Discovery and Metascpe software to analyze Kyoto Encyclopedia of Gene and Genome pathway and gene ontology. Furthermore, Cytoscape software and MCODE App were performed to construct complex of these differentially expressed genes . Twenty core genes were identified, which mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and PI3K-Akt pathway (P < .01). Finally, the significant difference of gene expression between cancer tissues and normal tissues in both lung and gastric carcinomas was examined by Gene Expression Profiling Interactive Analysis database. Twelve candidate genes with positive statistical significance (P < .01), COMP CTHRC1 COL1A1 SPP1 COL11A1 COL10A1 CXCL13 CLDN3 CLDN1 matrix metalloproteinases 7 ADAM12 PLAU, were picked out to further analysis. The Kaplan-Meier plotter website was applied to examine relationship among these genes and clinical outcomes. We found 4 genes (ADAM12, SPP1, COL1A1, COL11A1) were significantly associated with poor prognosis in both lung and gastric carcinoma patients (P  < .05). In conclusion, these candidate genes may be potential therapeutic targets for cancer treatment.

Indexed as

Computational BiologyADAM12 ProteinBiomarkers, TumorCollagen Type ICollagen Type I, alpha 1 ChainCollagen Type XIDatabases, GeneticGene Expression ProfilingHumansKaplan-Meier EstimateLung NeoplasmsMicroarray AnalysisOsteopontinPrognosisProtein Interaction MapsStomach NeoplasmsADAM12 ProteinADAM12 protein, humanBiomarkers, TumorCOL11A1 protein, humanCollagen Type ICollagen Type I, alpha 1 ChainCollagen Type XIOsteopontin

Identifiers

PMID33761685
PMCPMC10545272
OpenAlexW3137160862

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.