Aurora kinase A (AURKA) promotes the progression and imatinib resistance of advanced gastrointestinal stromal tumors

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Abstract

Background

Gastrointestinal stromal tumor (GIST) is a common tumor that originates from the alimentary system mesenchyme. Compared to typical gastrointestinal carcinomas, GISTs exhibit unique malignant behaviors. Bioinformatic tools and subsequent experiments were applied to investigate novel targets involved in GIST progression and imatinib resistance.

Methods

Differences in gene expression profiles between advanced and nonadvanced GISTs were comprehensively analyzed based on the Gene Expression Omnibus (GEO) dataset GSE136755. A protein–protein interaction (PPI) network was constructed to identify the potential target gene. Gene set enrichment analysis (GSEA) was used to elucidate relevant biological events related to the target gene based on the GSE47911 dataset. Subsequently, immunohistochemistry and Kaplan–Meier analysis were performed to validate the prognostic value of the target gene in GISTs. Overexpression of the target gene was conducted to analyze its function in the proliferation, apoptosis, and imatinib resistance of GIST/T1 cells.

Results

In the current study, a total of 606 differentially expressed genes (DEGs) were screened based on the GSE136755 dataset, and the upregulated DEGs in advanced GISTs were mainly involved in cell division through functional annotations. The intersecting hub gene, Aurora kinase A (AURKA), was identified by degree and bottleneck algorithms. GSEA revealed that AURKA was involved in cell cycle-related biological processes. Analysis of the Oncomine and GEPIA databases revealed a pattern of elevated AURKA expression in most human malignances. Clinical assays demonstrated that AURKA could be an independent prognostic factor for GISTs. Additionally, overexpression of AURKA was experimentally demonstrated to promote cell proliferation, inhibit cell apoptosis, and enhance imatinib resistance in GIST/T1 cells.

Conclusions

These findings indicated that overexpression of AURKA promoted GIST progression and enhanced imatinib resistance, implying that AURKA is a potential therapeutic target for GISTs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02111-7.

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Most cited references 44

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Gene Ontology: tool for the unification of biology

Michael Ashburner, Catherine A. Ball, Judith Blake … (2002)

Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.

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A. Subramanian, P. Tamayo, V. K. Mootha … (2005)

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

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Paul Shannon, Andrew Markiel, Owen Ozier … (2003)

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

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Author and article information

Contributors

Weilin Wang: wam@zju.edu.cn

Journal

Journal ID (nlm-ta): Cancer Cell Int

Journal ID (iso-abbrev): Cancer Cell Int

Title: Cancer Cell International

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2867

Publication date (Electronic): 31 July 2021

Publication date PMC-release: 31 July 2021

Publication date Collection: 2021

Volume: 21

Electronic Location Identifier: 407

Affiliations

[1 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Department of Colorectal Surgery, The First Affiliated Hospital, , Zhejiang University School of Medicine, ; Hangzhou, People’s Republic of China

[2 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Department of Intensive Care Unit, The First Affiliated Hospital, , Zhejiang University School of Medicine, ; Hangzhou, People’s Republic of China

[3 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, , Zhejiang University School of Medicine, ; #88 Jiefang Road, Hangzhou, Zhejiang People’s Republic of China

Author information

Xiaobin Cheng http://orcid.org/0000-0002-2347-0318

Article

Publisher ID: 2111

DOI: 10.1186/s12935-021-02111-7

PMC ID: 8325869

PubMed ID: 34332577

SO-VID: 40fee434-30bf-404f-a46a-eef8d8cafa48

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 25 March 2021

Date accepted : 24 July 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100004731, Natural Science Foundation of Zhejiang Province;

Award ID: LBY21H160005

Award Recipient : Xiaobin Cheng

Custom metadata

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: aurka,progression,imatinib resistance,gastrointestinal stromal tumors

Data availability:

ScienceOpen disciplines: Oncology & Radiotherapy

Keywords: aurka, progression, imatinib resistance, gastrointestinal stromal tumors

Aurora kinase A (AURKA) promotes the progression and imatinib resistance of advanced gastrointestinal stromal tumors

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Abstract

Background

Methods

Results

Conclusions

Supplementary Information

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Karger: Oncology

Most cited references 44

Gene Ontology: tool for the unification of biology

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

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