TAGLN2 promotes papillary thyroid carcinoma invasion via the Rap1/PI3K/AKT axis

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Abstract

TAGLN2, an actin-binding protein, functions as a binding protein to actin to facilitate the formation of intracellular cytoskeleton structures. TAGLN2 overexpression in papillary thyroid carcinoma (PTC) is reported in our previous study. This study aimed to examine the functions and molecular mechanisms of TAGLN2 in PTC. The clinical data analysis showed that TAGLN2 expression was associated with cervical lymph node metastasis in PTC. Gain- and loss-of-function approaches, as well as various cellular function, gene expression profiles, quantitative proteomics, and molecular biology experiments, were further exploited to explore the roles of TAGLN2 in PTC. The results showed that TAGLN2 overexpression significantly promoted the invasion of PTC cell lines (K1, TPC-1, and BCPAP). Besides, the results also indicated that TAGLN2 was associated with regulating proliferation, migration, angiogenesis, and adhesion of PTC cells. Gene expression profile, quantitative proteomics, and Western blotting were performed to identify the relevant pathways and key downstream molecules, and Rap1/PI3K/AKT signalling pathway, ITGB5, LAMC2, CRKL, vimentin, N-cadherin, and E-cadherin were finally focused on. Moreover, rescue experiments validated the involvement of the Rap1/PI3K/AKT signalling pathway in the TAGLN2-mediated invasion of PTC cells. Therefore, TAGLN2 may promote the invasion of PTC cells via the Rap1/PI3K/AKT signalling pathway and may be served as a potential therapeutic target for PTC. Developing antagonists targeting TAGLN2 may be a potentially effective therapeutic strategy for PTC.

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KEGG: kyoto encyclopedia of genes and genomes.

M Kanehisa (2000)

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).

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Toward understanding the origin and evolution of cellular organisms

Minoru Kanehisa (2019)

In this era of high‐throughput biology, bioinformatics has become a major discipline for making sense out of large‐scale datasets. Bioinformatics is usually considered as a practical field developing databases and software tools for supporting other fields, rather than a fundamental scientific discipline for uncovering principles of biology. The KEGG resource that we have been developing is a reference knowledge base for biological interpretation of genome sequences and other high‐throughput data. It is now one of the most utilized biological databases because of its practical values. For me personally, KEGG is a step toward understanding the origin and evolution of cellular organisms.

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KEGG: integrating viruses and cellular organisms

Minoru Kanehisa, Miho Furumichi, Yoko Sato … (2020)

Abstract KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.