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Published in: Cancer Cell International 1/2020

Open Access 01-12-2020 | Pancreatic Cancer | Primary research

Bioinformatics analysis combined with experiments to explore potential prognostic factors for pancreatic cancer

Authors: Mu-jing Ke, Lian-dong Ji, Yi-xiong Li

Published in: Cancer Cell International | Issue 1/2020

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Abstract

Background

Pancreatic cancer is a common malignant tumor of the digestive tract. It has a high degree of malignancy and poor prognosis. Finding effective molecular markers has great significance for pancreatic cancer diagnosis and treatment. This study aimed to investigate DLGAP5 expression in pancreatic cancer and explore the possible mechanisms and clinical value of DLGAP5 in tumorigenesis and tumor development.

Methods

Differentially expressed genes were screened using the Gene Expression Omnibus (GEO) data set GSE16515. Gene Ontology (GO)-based functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis were performed on the corresponding proteins of the above genes using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Kaplan–Meier Plotter database was used to analyze the relationship between differentially expressed genes and pancreatic cancer prognosis. The most prognostic gene, DLGAP5, was screened out, and the Oncomine and gene expression profiling interactive analysis (GEPIA) databases were used to analyze its expression in pancreatic cancer and other cancer tissues. The Cancer Genome Atlas (TCGA) database was used to analyze the overall survival of DLGAP5. Gene set enrichment analysis (GSEA) was performed to explore its possible molecular mechanisms in pancreatic cancer. Furthermore, the biological behavior of DLGAP5 in pancreatic cancer was verified by cell function experiments.

Results

A total of 201 significant upregulated differentially expressed genes and 79 downregulated genes were selected. The biological processes with significant enrichment of differential genes included cell adhesion, apoptosis, wound healing, leukocyte migration, angiogenesis. Pathways were mainly enriched in tumor-related signaling pathways such as cancer pathways, the extracellular matrix-receptor interaction pathway, and the p53 signaling pathway. DLGAP5 was significantly expressed in pancreatic cancer, and its expression level had a significant effect on patients’ survival time and progression-free survival. GSEA results indicated that DLGAP5 had significantly enriched into signaling pathways such as the cell cycle, the p53 signaling pathway, and oocyte meiosis. The experimental results showed that when we knocked down the expression of DLGAP5 in pancreatic cancer cells, their proliferation ability was significantly inhibited, and their invasion and migration ability significantly decreased.

Conclusions

DLGAP5 can be used as a prognostic indicator for pancreatic cancer and affect the occurrence and development of pancreatic cancer.
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Literature
5.
go back to reference Matsubayashi H, Takaori K, Morizane C, Maguchi H, Mizuma M, Takahashi H, Wada K, Hosoi H, Yachida S, Suzuki M, Usui R, Furukawa T, Furuse J, Sato T, Ueno M, Kiyozumi Y, Hijioka S, Mizuno N, Terashima T, Mizumoto M, Kodama Y, Torishima M, Kawaguchi T, Ashida R, Kitano M, Hanada K, Furukawa M, Kawabe K, Majima Y, Shimosegawa T. Familial pancreatic cancer: concept, management and issues. World J Gastroenterol. 2017;23:935–48. https://doi.org/10.3748/wjg.v23.i6.935.CrossRefPubMedPubMedCentral Matsubayashi H, Takaori K, Morizane C, Maguchi H, Mizuma M, Takahashi H, Wada K, Hosoi H, Yachida S, Suzuki M, Usui R, Furukawa T, Furuse J, Sato T, Ueno M, Kiyozumi Y, Hijioka S, Mizuno N, Terashima T, Mizumoto M, Kodama Y, Torishima M, Kawaguchi T, Ashida R, Kitano M, Hanada K, Furukawa M, Kawabe K, Majima Y, Shimosegawa T. Familial pancreatic cancer: concept, management and issues. World J Gastroenterol. 2017;23:935–48. https://​doi.​org/​10.​3748/​wjg.​v23.​i6.​935.CrossRefPubMedPubMedCentral
13.
go back to reference Kim E, Naisbitt S, Hsueh YP, Rao A, Rothschild A, Craig AM, Sheng M. GKAP, a novel synaptic protein that interacts with the guanylate kinase-like domain of the PSD-95/SAP90 family of channel clustering molecules. J Cell Biol. 1997;136:669–78.CrossRef Kim E, Naisbitt S, Hsueh YP, Rao A, Rothschild A, Craig AM, Sheng M. GKAP, a novel synaptic protein that interacts with the guanylate kinase-like domain of the PSD-95/SAP90 family of channel clustering molecules. J Cell Biol. 1997;136:669–78.CrossRef
14.
go back to reference Naisbitt S, Kim E, Weinberg RJ, Rao A, Yang FC, Craig AM, Sheng M. Characterization of guanylate kinase-associated protein, a postsynaptic density protein at excitatory synapses that interacts directly with postsynaptic density-95/synapse-associated protein 90. J Neurosci. 1997;17:5687–96.CrossRef Naisbitt S, Kim E, Weinberg RJ, Rao A, Yang FC, Craig AM, Sheng M. Characterization of guanylate kinase-associated protein, a postsynaptic density protein at excitatory synapses that interacts directly with postsynaptic density-95/synapse-associated protein 90. J Neurosci. 1997;17:5687–96.CrossRef
16.
go back to reference Naisbitt S, Valtschanoff J, Allison DW, Sala C, Kim E, Craig AM, Weinberg RJ, Sheng M. Interaction of the postsynaptic density-95/guanylate kinase domain-associated protein complex with a light chain of myosin-V and dynein. J Neurosci. 2000;20:4524–34.CrossRef Naisbitt S, Valtschanoff J, Allison DW, Sala C, Kim E, Craig AM, Weinberg RJ, Sheng M. Interaction of the postsynaptic density-95/guanylate kinase domain-associated protein complex with a light chain of myosin-V and dynein. J Neurosci. 2000;20:4524–34.CrossRef
21.
go back to reference Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY. cytoHubba): identifying hub objects and sub-networks from complex interactome. BMC Syst Biol. 2014;8(S4):S11.CrossRef Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY. cytoHubba): identifying hub objects and sub-networks from complex interactome. BMC Syst Biol. 2014;8(S4):S11.CrossRef
22.
go back to reference Enot DP, Vacchelli E, Jacquelot N, Zitvogel L, Kroemer G. TumGrowth: an open-access web tool for the statistical analysis of tumor growth curves. Oncoimmunology. 2018;7(9):e1462431.CrossRef Enot DP, Vacchelli E, Jacquelot N, Zitvogel L, Kroemer G. TumGrowth: an open-access web tool for the statistical analysis of tumor growth curves. Oncoimmunology. 2018;7(9):e1462431.CrossRef
24.
go back to reference Horning AM, Wang Y, Lin CK, Louie AD, Jadhav RR, Hung CN, Wang CM, Lin CL, Kirma NB, Liss MA, Kumar AP, Sun L, Liu Z, Chao WT, Wang Q, Jin VX, Chen CL, Huang TH. Single-cell RNA-seq reveals a subpopulation of prostate cancer cells with enhanced cell-cycle-related transcription and attenuated androgen response. Cancer Res. 2018;78:853–64. https://doi.org/10.1158/0008-5472.can-17-1924).CrossRefPubMed Horning AM, Wang Y, Lin CK, Louie AD, Jadhav RR, Hung CN, Wang CM, Lin CL, Kirma NB, Liss MA, Kumar AP, Sun L, Liu Z, Chao WT, Wang Q, Jin VX, Chen CL, Huang TH. Single-cell RNA-seq reveals a subpopulation of prostate cancer cells with enhanced cell-cycle-related transcription and attenuated androgen response. Cancer Res. 2018;78:853–64. https://​doi.​org/​10.​1158/​0008-5472.​can-17-1924).CrossRefPubMed
28.
go back to reference Hanks SK, Hunter T, Protein kinases 6. The eukaryotic protein kinase superfamily: kinase (catalytic) domain structure and classification. FASEB J. 1995;9:576–96.CrossRef Hanks SK, Hunter T, Protein kinases 6. The eukaryotic protein kinase superfamily: kinase (catalytic) domain structure and classification. FASEB J. 1995;9:576–96.CrossRef
29.
35.
Metadata
Title
Bioinformatics analysis combined with experiments to explore potential prognostic factors for pancreatic cancer
Authors
Mu-jing Ke
Lian-dong Ji
Yi-xiong Li
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Cancer Cell International / Issue 1/2020
Electronic ISSN: 1475-2867
DOI
https://doi.org/10.1186/s12935-020-01474-7

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