Evidence map›Paper›PMID 32093341›Full record

ArticleInternational journal of environmental research and public health2020

Network-Based Genetic Profiling Reveals Cellular Pathway Differences Between Follicular Thyroid Carcinoma and Follicular Thyroid Adenoma.

Md Ali Hossain, Tania Akter Asa, Md Mijanur Rahman, Shahadat Uddin, Ahmed A Moustafa, Julian M W Quinn, Mohammad Ali Moni

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 28 citations in OpenAlex.

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  14. Oncology letters · 2021
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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 6 institutions in 2 countries.

Md Ali HossainDepartment of Computer Science & Engineering, Manarat International University, Khagan, Dhaka 1343, Bangladesh.
Tania Akter AsaElectrical and Electronic Engineering, Islamic University, Kushtia 7005, Bangladesh.
Md Mijanur RahmanComputer Science & Engineering, Jatiya Kabi Kazi Nazrul Islam University, Mymensingh 2205, Bangladesh.
Shahadat UddinComplex Systems Research Group & Project Management Program, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia.ORCID 0000-0003-0091-6919
Ahmed A MoustafaMarcs Institute for Brain and Behaviour and School of Psychology, Western Sydney University, Sydney, NSW 2751, Australia.
Julian M W QuinnBone Biology Divisions, Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia.
Mohammad Ali MoniBone Biology Divisions, Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia.ORCID 0000-0003-0756-1006
Garvan Institute of Medical Research · AUIslamic University · BDJatiya Kabi Kazi Nazrul Islam University · BDManarat International University · BDThe University of Sydney · AUWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular mechanisms underlying the pathogenesis and progression of malignant thyroid cancers, such as follicular thyroid carcinomas (FTCs), and how these differ from benign thyroid lesions, are poorly understood. In this study, we employed network-based integrative analyses of FTC and benign follicular thyroid adenoma (FTA) lesion transcriptomes to identify key genes and pathways that differ between them. We first analysed a microarray gene expression dataset (Gene Expression Omnibus GSE82208, n = 52) obtained from FTC and FTA tissues to identify differentially expressed genes (DEGs). Pathway analyses of these DEGs were then performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) resources to identify potentially important pathways, and protein-protein interactions (PPIs) were examined to identify pathway hub genes. Our data analysis identified 598 DEGs, 133 genes with higher and 465 genes with lower expression in FTCs. We identified four significant pathways (one carbon pool by folate, p53 signalling, progesterone-mediated oocyte maturation signalling, and cell cycle pathways) connected to DEGs with high FTC expression; eight pathways were connected to DEGs with lower relative FTC expression. Ten GO groups were significantly connected with FTC-high expression DEGs and 80 with low-FTC expression DEGs. PPI analysis then identified 12 potential hub genes based on degree and betweenness centrality; namely, TOP2A, JUN, EGFR, CDK1, FOS, CDKN3, EZH2, TYMS, PBK, CDH1, UBE2C, and CCNB2. Moreover, transcription factors (TFs) were identified that may underlie gene expression differences observed between FTC and FTA, including FOXC1, GATA2, YY1, FOXL1, E2F1, NFIC, SRF, TFAP2A, HINFP, and CREB1. We also identified microRNA (miRNAs) that may also affect transcript levels of DEGs; these included hsa-mir-335-5p, -26b-5p, -124-3p, -16-5p, -192-5p, -1-3p, -17-5p, -92a-3p, -215-5p, and -20a-5p. Thus, our study identified DEGs, molecular pathways, TFs, and miRNAs that reflect molecular mechanisms that differ between FTC and benign FTA. Given the general similarities of these lesions and common tissue origin, some of these differences may reflect malignant progression potential, and include useful candidate biomarkers for FTC and identifying factors important for FTC pathogenesis.

Indexed as

Adenocarcinoma, FollicularAdenomaGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyGene Regulatory NetworksHumansMicroRNAsThyroid NeoplasmsMicroRNAscarcinomamolecular pathwaysprotein-protein interactionreporter microRNAsreporter transcription factorsthyroid cancer

Identifiers

PMID32093341
PMCPMC7068514
OpenAlexW3007917026

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.