Systems biomarkers for papillary thyroid cancer prognosis and treatment through multi-omics networks.
Antineoplastic Agents
/ metabolism
Biomarkers, Tumor
/ genetics
Drug Repositioning
Gene Expression
/ physiology
Gene Expression Profiling
Humans
MicroRNAs
/ genetics
Molecular Docking Simulation
Protein Binding
Proteomics
Thyroid Cancer, Papillary
/ genetics
Thyroid Neoplasms
/ genetics
Transcriptome
/ physiology
Biomarker
Metabolic network
Papillary thyroid carcinoma
Protein-protein interaction network
Regulatory network
Thyroid cancer
Journal
Archives of biochemistry and biophysics
ISSN: 1096-0384
Titre abrégé: Arch Biochem Biophys
Pays: United States
ID NLM: 0372430
Informations de publication
Date de publication:
15 01 2022
15 01 2022
Historique:
received:
27
07
2021
revised:
12
11
2021
accepted:
13
11
2021
pubmed:
21
11
2021
medline:
6
1
2022
entrez:
20
11
2021
Statut:
ppublish
Résumé
The identification of biomolecules associated with papillary thyroid cancer (PTC) has upmost importance for the elucidation of the disease mechanism and the development of effective diagnostic and treatment strategies. Despite particular findings in this regard, a holistic analysis encompassing molecular data from different biological levels has been lacking. In the present study, a meta-analysis of four transcriptome datasets was performed to identify gene expression signatures in PTC, and reporter molecules were determined by mapping gene expression data onto three major cellular networks, i.e., transcriptional regulatory, protein-protein interaction, and metabolic networks. We identified 282 common genes that were differentially expressed in all PTC datasets. In addition, six proteins (FYN, JUN, LYN, PML, SIN3A, and RARA), two Erb-B2 receptors (ERBB2 and ERBB4), two cyclin-dependent receptors (CDK1 and CDK2), and three histone deacetylase receptors (HDAC1, HDAC2, and HDAC3) came into prominence as proteomic signatures in addition to several metabolites including lactaldehyde and proline at the metabolome level. Significant associations with calcium and MAPK signaling pathways and transcriptional and post-transcriptional activities of 12 TFs and 110 miRNAs were also observed at the regulatory level. Among them, six miRNAs (miR-30b-3p, miR-15b-5p, let-7a-5p, miR-130b-3p, miR-424-5p, and miR-193b-3p) were associated with PTC for the first time in the literature, and the expression levels of miR-30b-3p, miR-15b-5p, and let-7a-5p were found to be predictive of disease prognosis. Drug repositioning and molecular docking simulations revealed that 5 drugs (prochlorperazine, meclizine, rottlerin, cephaeline, and tretinoin) may be useful in the treatment of PTC. Consequently, we report here biomolecule candidates that may be considered as prognostic biomarkers or potential therapeutic targets for further experimental and clinical trials for PTC.
Identifiants
pubmed: 34800440
pii: S0003-9861(21)00334-9
doi: 10.1016/j.abb.2021.109085
pii:
doi:
Substances chimiques
Antineoplastic Agents
0
Biomarkers, Tumor
0
MIRN15 microRNA, human
0
MIRN30a microRNA, human
0
MIRN30b microRNA, human
0
MicroRNAs
0
mirnlet7 microRNA, human
0
Types de publication
Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
109085Informations de copyright
Copyright © 2021 Elsevier Inc. All rights reserved.