Evidence map›Paper›PMID 33841642›Full record

ArticleAmerican journal of translational research2021

Potential targets identified in adenoid cystic carcinoma point out new directions for further research.

Zhenan Liu, Jian Gao, Yihui Yang, Huaqiang Zhao, Chuan Ma, Tingting Yu

Open access · greenAbstract read
In one paragraph

Article in American journal of translational research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. A pilot study ofEJNMMI research · 2022
    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 1 institution in 1 country.

Zhenan LiuDepartment of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration Jinan, China.
Jian GaoDepartment of Stomatology, Xintai Hospital of Traditional Chinese Medicine Taian, China.
Yihui YangDepartment of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration Jinan, China.
Huaqiang ZhaoDepartment of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration Jinan, China.
Chuan MaDepartment of Oral and Maxillofacial Surgery, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration Jinan, China.
Tingting YuDepartment of Oral and Maxillofacial Surgery, Jinan Stomatological Hospital Jinan, China.
Shandong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adenoid cystic carcinoma (AdCC) of the head and neck originates from salivary glands, with high risks of recurrence and metastasis that account for the poor prognosis of patients. The purpose of this research was to identify key genes related to AdCC for further investigation of their diagnostic and prognostic significance. In our study, the AdCC sample datasets GSE36820, GSE59702 and GSE88804 from the Gene Expression Omnibus (GEO) database were used to explore the abnormal coexpression of genes in AdCC compared with their expression in normal tissue. A total of 115 DEGs were obtained by screening with GEO2R and FunRich software. According to functional annotation analysis using Enrichr, these DEGs were mainly enriched in the SOX2, AR, SMAD and MAPK signaling pathways. A protein-protein network of the DEGs was established by the Search Tool for the Retrieval of Interacting Genes (STRING) and annotated through the WEB-based Gene SeT AnaLysis Toolkit (WebGestalt) and was shown to be enriched with proteins involved in cardiac muscle cell proliferation and extracellular matrix organization. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that ITGA9, LAMB1 and BAMBI were associated with the PI3K-Akt and TGF-β pathways. Furthermore, 36 potential target miRNAs were identified by the OncomiR and miRNA Pathway Dictionary Database (miRPathDB). In conclusion, SLC22A3, FOXP2, Cdc42EP3, COL27A1, DUSP1 and HSPB8 played critical roles according to the enrichment analysis; ITGA9, LAMB1 and BAMBI were involved in significant pathways according to the KEGG analysis; ST3Gal4 is a pivotal component of the PPI network of all the DEGs obtained; SPARC, COL4A2 and PRELP were highly related to multiple malignancies in pan-cancer research; hsa-miR-29-3p, hsa-miR-132-3p and hsa-miR-708-5p were potential regulators in AdCC. The involved pathways, biological processes and miRNAs have been shown to play significant roles in the genesis, growth, invasion and metastasis of AdCC. In this study, these identified DEGs were considered to have a potential influence on AdCC but have not been studied in this disease. The analysis results promote our understanding of the molecular mechanisms and biological processes of AdCC, which might be useful for targeted therapy or diagnosis.

Indexed as

Adenoid cystic carcinomabioinformaticsdifferentially expressed genesmiRNA

Identifiers

PMID33841642
PMCPMC8014416
OpenAlexW3156700265

What OpenQuestion holds

Textmetadata
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.