Evidence map›Paper›PMID 33327880›Full record

ArticleTechnology in cancer research & treatment

Identifications of Candidate Genes Significantly Associated With Rectal Cancer by Integrated Bioinformatics Analysis.

Zhili Xu, Yan Li, Yiyi Cui, Yong Guo

Open access · goldAbstract read
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Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 19% 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

9 citing papers in PubMed, 14 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 2 institutions in 1 country.

Zhili XuThe First Clinical Medical College, Zhejiang Chinese Medical University, Zhejiang, China.
Yan LiThe First Clinical Medical College, Zhejiang Chinese Medical University, Zhejiang, China.
Yiyi CuiThe Third Affiliated Hospital of Zhejiang Chinese Medical University, Zhejiang, China.
Yong GuoThe First Clinical Medical College, Zhejiang Chinese Medical University, Zhejiang, China.ORCID 0000-0002-9997-0052
Zhejiang Chinese Medical University · CNThe Third Affiliated Hospital of Zhejiang Chinese Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRectal cancer ranks as the eighth in cancer-related morbidity and the tenth in the cancer-related mortality. A few studies have explored several biomarkers for colorectal cancer. However, there is still a great need for us to excavate novel biomarkers with effective and efficient diagnostic and prognostic values to discover the etiology and pathogenesis of rectal cancer separately. Therefore, we aimed to identify more novel candidate genes that were significantly associated with rectal cancer through integrated bioinformatics analysis.

methodsWe analyzed the gene expression profiles of GSE15781 and GSE20842 from Gene Expression Omnibus database to identify differentially expressed genes between normal rectal tissue and rectal cancer tissue.

resultsWe searched for core genes, carried out survival analysis and analyzed the expressions of core genes. We found that 142 genes were significantly upregulated, and 229 genes were significantly downregulated in all 3 independent studies. In KEGG analysis, the upregulated genes were significantly enriched in cytokine-cytokine receptor interaction, IL-17 signaling pathway, cell cycle, etc. The downregulated genes were primarily enriched in nitrogen metabolism, mineral absorption and pentose and glucuronate interconversions. Inhibin subunit beta B (INHBB) expressed markedly higher in rectal cancer tissues compared with normal tissues, and claudins (CLDN) 23 expressed significantly lower in rectal cancer tissues.

conclusionIn conclusion, we discovered that INHBB could provide a great significant diagnostic and prognostic values for rectal cancer.

Indexed as

Biomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticTranscriptomeAge FactorsComputational BiologyDatabases, GeneticFemaleGene OntologyHumansMalePrognosisProtein Interaction MappingProtein Interaction MapsRectal NeoplasmsSex FactorsBiomarkers, TumorINHBBintegrated bioinformaticsrectal cancer

Identifiers

PMID33327880
PMCPMC7750891
OpenAlexW3112017439

What OpenQuestion holds

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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.