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Published in: Medical Oncology 9/2020

01-09-2020 | Glioblastoma | Original Paper

Identification of biomarkers associated with extracellular vesicles based on an integrative pan-cancer bioinformatics analysis

Authors: Qiang Wang, Chaoran Yu

Published in: Medical Oncology | Issue 9/2020

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Abstract

Extracellular vesicle (EV) has received increasing attention over the last decade. However, biomarkers and mechanisms underlying remain largely limited. Three microarray profiles, GSE78718 (K562 leukemia cell line), GSE45301 (U87-MG glioblastoma cell line), and GSE9589 (SW480 colon cancer cell line), were analyzed for the overlapped differentially expressed genes (DEGs). SurvExpress was used for the prognostic analysis of hub genes signature. Predicted transcription factors networks were built by NetworkAnalysis. Characterization between hub genes and immune cells was analyzed by the tumor immune estimation resources (TIMER) and single-sample gene set enrichment analysis (ssGSEA). The most significantly enriched pathway was lysosome. Hub genes included lysosomal-associated membrane protein 1 (LAMP1), heat shock protein family A (Hsp70) member 5 (HSPA5), lysosomal-associated membrane protein 2 (LAMP2), integrin subunit alpha V (ITGAV), and transmembrane protein 30A (TMEM30A). Significant prognostic values of hub genes signature were identified in glioblastoma (P-value = 0.006), but not colon cancer. In colon cancer, ITGAV displayed remarkably high correlation with tumor immune infiltrating cells. In glioblastoma, the highest correlation was found between HSPA5 and dendritic cell. Moreover, distinct association of immune cells between cell and EV were identified via ssGSEA. This study identified biomarkers in EV with potential immunological insights and clinical values.
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Literature
2.
go back to reference Muralidharan-Chari V, Clancy JW, Sedgwick A, et al. Microvesicles: mediators of extracellular communication during cancer progression. J Cell Sci. 2010;123(10):1603–11.PubMedPubMedCentralCrossRef Muralidharan-Chari V, Clancy JW, Sedgwick A, et al. Microvesicles: mediators of extracellular communication during cancer progression. J Cell Sci. 2010;123(10):1603–11.PubMedPubMedCentralCrossRef
3.
go back to reference Turturici G, Tinnirello R, Sconzo G, et al. Extracellular membrane vesicles as a mechanism of cell-to-cell communication: advantages and disadvantages. Am J Physiol Cell Physiol. 2014;306(7):C621–C633633.PubMedCrossRef Turturici G, Tinnirello R, Sconzo G, et al. Extracellular membrane vesicles as a mechanism of cell-to-cell communication: advantages and disadvantages. Am J Physiol Cell Physiol. 2014;306(7):C621–C633633.PubMedCrossRef
4.
go back to reference Revenfeld ALS, Bæk R, Nielsen MH, et al. Diagnostic and prognostic potential of extracellular vesicles in peripheral blood. Clin Ther. 2014;36(6):830–46.CrossRefPubMed Revenfeld ALS, Bæk R, Nielsen MH, et al. Diagnostic and prognostic potential of extracellular vesicles in peripheral blood. Clin Ther. 2014;36(6):830–46.CrossRefPubMed
5.
go back to reference Christianson HC, Svensson KJ, Belting M. Exosome and microvesicle mediated phene transfer in mammalian cells[C]//Seminars in cancer biology. Academic Press. 2014;28:31–8. Christianson HC, Svensson KJ, Belting M. Exosome and microvesicle mediated phene transfer in mammalian cells[C]//Seminars in cancer biology. Academic Press. 2014;28:31–8.
6.
go back to reference Cocucci E. Meldolesi J Ectosomes and exosomes: shedding the confusion between extracellular vesicles. Trends Cell Biol. 2015;25(6):364–72.PubMedCrossRef Cocucci E. Meldolesi J Ectosomes and exosomes: shedding the confusion between extracellular vesicles. Trends Cell Biol. 2015;25(6):364–72.PubMedCrossRef
7.
go back to reference Valadi H, Ekström K, Bossios A, et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007;9(6):654.PubMedCrossRef Valadi H, Ekström K, Bossios A, et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007;9(6):654.PubMedCrossRef
8.
go back to reference Deregibus MC, Cantaluppi V, Calogero R, et al. Endothelial progenitor cell–derived microvesicles activate an angiogenic program in endothelial cells by a horizontal transfer of mRNA. Blood. 2007;110(7):2440–8.PubMedCrossRef Deregibus MC, Cantaluppi V, Calogero R, et al. Endothelial progenitor cell–derived microvesicles activate an angiogenic program in endothelial cells by a horizontal transfer of mRNA. Blood. 2007;110(7):2440–8.PubMedCrossRef
9.
go back to reference Pap E, Pallinger E, Pasztoi M, et al. Highlights of a new type of intercellular communication: microvesicle-based information transfer. Inflamm Res. 2009;58(1):1–8.PubMedCrossRef Pap E, Pallinger E, Pasztoi M, et al. Highlights of a new type of intercellular communication: microvesicle-based information transfer. Inflamm Res. 2009;58(1):1–8.PubMedCrossRef
10.
go back to reference van der Vos KE, Balaj L, Skog J, et al. Brain tumor microvesicles: insights into intercellular communication in the nervous system. Cell Mol Neurobiol. 2011;31(6):949–59.PubMedPubMedCentralCrossRef van der Vos KE, Balaj L, Skog J, et al. Brain tumor microvesicles: insights into intercellular communication in the nervous system. Cell Mol Neurobiol. 2011;31(6):949–59.PubMedPubMedCentralCrossRef
11.
go back to reference Barteneva NS, Maltsev N, Vorobjev IA. Microvesicles and intercellular communication in the context of parasitism. Front Cell Infect Microbiol. 2013;3:49.PubMedPubMedCentralCrossRef Barteneva NS, Maltsev N, Vorobjev IA. Microvesicles and intercellular communication in the context of parasitism. Front Cell Infect Microbiol. 2013;3:49.PubMedPubMedCentralCrossRef
12.
go back to reference Lee Y, El Andaloussi S, Wood MJA. Exosomes and microvesicles: extracellular vesicles for genetic information transfer and gene therapy. Hum Mol Genet. 2012;21(R1):R125–R134134.PubMedCrossRef Lee Y, El Andaloussi S, Wood MJA. Exosomes and microvesicles: extracellular vesicles for genetic information transfer and gene therapy. Hum Mol Genet. 2012;21(R1):R125–R134134.PubMedCrossRef
14.
go back to reference Yang M, Chen J, Su F, et al. Microvesicles secreted by macrophages shuttle invasion-potentiating microRNAs into breast cancer cells. Mol Cancer. 2011;10(1):117.PubMedPubMedCentralCrossRef Yang M, Chen J, Su F, et al. Microvesicles secreted by macrophages shuttle invasion-potentiating microRNAs into breast cancer cells. Mol Cancer. 2011;10(1):117.PubMedPubMedCentralCrossRef
15.
go back to reference Castellana D, Toti F, Freyssinet JM. Membrane microvesicles: macromessengers in cancer disease and progression. Thromb Res. 2010;125:S84–S8888.PubMedCrossRef Castellana D, Toti F, Freyssinet JM. Membrane microvesicles: macromessengers in cancer disease and progression. Thromb Res. 2010;125:S84–S8888.PubMedCrossRef
16.
go back to reference Lee H, Zhang D, Zhu Z, et al. Epithelial cell-derived microvesicles activate macrophages and promote inflammation via microvesicle-containing microRNAs. Sci Rep. 2016;6:35250.PubMedPubMedCentralCrossRef Lee H, Zhang D, Zhu Z, et al. Epithelial cell-derived microvesicles activate macrophages and promote inflammation via microvesicle-containing microRNAs. Sci Rep. 2016;6:35250.PubMedPubMedCentralCrossRef
17.
go back to reference Kahlert C, Kalluri R. Exosomes in tumor microenvironment influence cancer progression and metastasis. J Mol Med. 2013;91(4):431–7.PubMedCrossRef Kahlert C, Kalluri R. Exosomes in tumor microenvironment influence cancer progression and metastasis. J Mol Med. 2013;91(4):431–7.PubMedCrossRef
19.
go back to reference Milani G, Lana T, Bresolin S, et al. Expression profiling of circulating microvesicles reveals intercellular transmission of oncogenic pathways. Mol Cancer Res. 2017;15(6):683–95.PubMedCrossRef Milani G, Lana T, Bresolin S, et al. Expression profiling of circulating microvesicles reveals intercellular transmission of oncogenic pathways. Mol Cancer Res. 2017;15(6):683–95.PubMedCrossRef
20.
go back to reference Kucharzewska P, Christianson HC, Belting M. Global profiling of metabolic adaptation to hypoxic stress in human glioblastoma cells. PLoS ONE. 2015;10(1):e0116740.PubMedPubMedCentralCrossRef Kucharzewska P, Christianson HC, Belting M. Global profiling of metabolic adaptation to hypoxic stress in human glioblastoma cells. PLoS ONE. 2015;10(1):e0116740.PubMedPubMedCentralCrossRef
21.
go back to reference Hong BS, Cho JH, Kim H, et al. Colorectal cancer cell-derived microvesicles are enriched in cell cycle-related mRNAs that promote proliferation of endothelial cells. BMC Genomics. 2009;10(1):556.PubMedPubMedCentralCrossRef Hong BS, Cho JH, Kim H, et al. Colorectal cancer cell-derived microvesicles are enriched in cell cycle-related mRNAs that promote proliferation of endothelial cells. BMC Genomics. 2009;10(1):556.PubMedPubMedCentralCrossRef
22.
go back to reference Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30(1):207–10.PubMedPubMedCentralCrossRef Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30(1):207–10.PubMedPubMedCentralCrossRef
23.
go back to reference Davis S, Meltzer PS. GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics. 2007;23(14):1846–7.PubMedCrossRef Davis S, Meltzer PS. GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor. Bioinformatics. 2007;23(14):1846–7.PubMedCrossRef
24.
25.
go back to reference Barrett T, Troup DB, Wilhite SE, et al. NCBI GEO: mining tens of millions of expression profiles—database and tools update. Nucleic Acids Res. 2006;35(suppl_1):D760–D765765.PubMedPubMedCentral Barrett T, Troup DB, Wilhite SE, et al. NCBI GEO: mining tens of millions of expression profiles—database and tools update. Nucleic Acids Res. 2006;35(suppl_1):D760–D765765.PubMedPubMedCentral
26.
go back to reference Van Deun J, Mestdagh P, Agostinis P, et al. EV-TRACK: transparent reporting and centralizing knowledge in extracellular vesicle research. Nat Methods. 2017;14:228–32.PubMedCrossRef Van Deun J, Mestdagh P, Agostinis P, et al. EV-TRACK: transparent reporting and centralizing knowledge in extracellular vesicle research. Nat Methods. 2017;14:228–32.PubMedCrossRef
30.
go back to reference Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44.PubMedCrossRef Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44.PubMedCrossRef
31.
go back to reference Szklarczyk D, Franceschini A, Wyder S, et al. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2014;43(D1):D447–D45252.PubMedPubMedCentralCrossRef Szklarczyk D, Franceschini A, Wyder S, et al. STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2014;43(D1):D447–D45252.PubMedPubMedCentralCrossRef
32.
go back to reference Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.PubMedPubMedCentralCrossRef Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504.PubMedPubMedCentralCrossRef
33.
go back to reference Aguirre-Gamboa R, Gomez-Rueda H, Martínez-Ledesma E, et al. SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis. PLoS ONE. 2013;8(9):e74250.PubMedPubMedCentralCrossRef Aguirre-Gamboa R, Gomez-Rueda H, Martínez-Ledesma E, et al. SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis. PLoS ONE. 2013;8(9):e74250.PubMedPubMedCentralCrossRef
34.
go back to reference Xia J, Gill EE, Hancock RE. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nat Protoc. 2015;10(6):823.PubMedCrossRef Xia J, Gill EE, Hancock RE. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nat Protoc. 2015;10(6):823.PubMedCrossRef
35.
go back to reference Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS, et al. TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Can Res. 2017;77(21):e108–e110110.CrossRef Li T, Fan J, Wang B, Traugh N, Chen Q, Liu JS, et al. TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Can Res. 2017;77(21):e108–e110110.CrossRef
36.
go back to reference Barbie DA, Tamayo P, Boehm JS, et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature. 2009;462(7269):108–12.PubMedPubMedCentralCrossRef Barbie DA, Tamayo P, Boehm JS, et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature. 2009;462(7269):108–12.PubMedPubMedCentralCrossRef
37.
go back to reference Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinform. 2013;14:7.CrossRef Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinform. 2013;14:7.CrossRef
38.
go back to reference Charoentong P, Finotello F, Angelova M, et al. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep. 2017;18(1):248–62.PubMedCrossRef Charoentong P, Finotello F, Angelova M, et al. Pan-cancer immunogenomic analyses reveal genotype-immunophenotype relationships and predictors of response to checkpoint blockade. Cell Rep. 2017;18(1):248–62.PubMedCrossRef
39.
go back to reference Saftig P, Klumperman J. Lysosome biogenesis and lysosomal membrane proteins: trafficking meets function. Nat Rev Mol Cell Biol. 2009;10(9):623.PubMedCrossRef Saftig P, Klumperman J. Lysosome biogenesis and lysosomal membrane proteins: trafficking meets function. Nat Rev Mol Cell Biol. 2009;10(9):623.PubMedCrossRef
40.
go back to reference Zheng J, Tan J, Miao YY, et al. Extracellular vesicles degradation pathway based autophagy lysosome pathway. Am J Transl Res. 2019;11(3):1170.PubMedPubMedCentral Zheng J, Tan J, Miao YY, et al. Extracellular vesicles degradation pathway based autophagy lysosome pathway. Am J Transl Res. 2019;11(3):1170.PubMedPubMedCentral
42.
go back to reference Tancini B, Buratta S, Sagini K, et al. Insight into the role of extracellular vesicles in lysosomal storage disorders. Genes. 2019;10(7):510.PubMedCentralCrossRef Tancini B, Buratta S, Sagini K, et al. Insight into the role of extracellular vesicles in lysosomal storage disorders. Genes. 2019;10(7):510.PubMedCentralCrossRef
43.
go back to reference Fehrenbacher N, Bastholm L, Kirkegaard-Sørensen T, et al. Sensitization to the lysosomal cell death pathway by oncogene-induced down-regulation of lysosome-associated membrane proteins 1 and 2. Can Res. 2008;68(16):6623–33.CrossRef Fehrenbacher N, Bastholm L, Kirkegaard-Sørensen T, et al. Sensitization to the lysosomal cell death pathway by oncogene-induced down-regulation of lysosome-associated membrane proteins 1 and 2. Can Res. 2008;68(16):6623–33.CrossRef
45.
go back to reference Mambula SS, Calderwood SK. Heat shock protein 70 is secreted from tumor cells by a nonclassical pathway involving lysosomal endosomes. J Immunol. 2006;177(11):7849–57.PubMedCrossRef Mambula SS, Calderwood SK. Heat shock protein 70 is secreted from tumor cells by a nonclassical pathway involving lysosomal endosomes. J Immunol. 2006;177(11):7849–57.PubMedCrossRef
46.
go back to reference Atay S, Gercel-Taylor C, Kesimer M, et al. Morphologic and proteomic characterization of exosomes released by cultured extravillous trophoblast cells. Exp Cell Res. 2011;317(8):1192–202.PubMedCrossRef Atay S, Gercel-Taylor C, Kesimer M, et al. Morphologic and proteomic characterization of exosomes released by cultured extravillous trophoblast cells. Exp Cell Res. 2011;317(8):1192–202.PubMedCrossRef
47.
go back to reference Waisberg J, Viana LDS, Junior RJA, et al. Overexpression of the ITGAV gene is associated with progression and spread of colorectal cancer. Anticancer Res. 2014;34(10):5599–607.PubMed Waisberg J, Viana LDS, Junior RJA, et al. Overexpression of the ITGAV gene is associated with progression and spread of colorectal cancer. Anticancer Res. 2014;34(10):5599–607.PubMed
48.
go back to reference Luo Z, Li D, Luo X, et al. Decreased expression of miR-548c-3p in osteosarcoma contributes to cell proliferation via targeting ITGAV. Cancer Biother Radiopharm. 2016;31(5):153–8.PubMedCrossRef Luo Z, Li D, Luo X, et al. Decreased expression of miR-548c-3p in osteosarcoma contributes to cell proliferation via targeting ITGAV. Cancer Biother Radiopharm. 2016;31(5):153–8.PubMedCrossRef
49.
go back to reference Chen R, Brady E, McIntyre TM. Human TMEM30a promotes uptake of antitumor and bioactive choline phospholipids into mammalian cells. J Immunol. 2011;186(5):3215–25.PubMedCrossRef Chen R, Brady E, McIntyre TM. Human TMEM30a promotes uptake of antitumor and bioactive choline phospholipids into mammalian cells. J Immunol. 2011;186(5):3215–25.PubMedCrossRef
50.
go back to reference Li N, Yang Y, Liang C, et al. Tmem30a plays critical roles in ensuring the survival of hematopoietic cells and leukemia cells in mice. Am J Pathol. 2018;188(6):1457–68.PubMedCrossRef Li N, Yang Y, Liang C, et al. Tmem30a plays critical roles in ensuring the survival of hematopoietic cells and leukemia cells in mice. Am J Pathol. 2018;188(6):1457–68.PubMedCrossRef
Metadata
Title
Identification of biomarkers associated with extracellular vesicles based on an integrative pan-cancer bioinformatics analysis
Authors
Qiang Wang
Chaoran Yu
Publication date
01-09-2020
Publisher
Springer US
Published in
Medical Oncology / Issue 9/2020
Print ISSN: 1357-0560
Electronic ISSN: 1559-131X
DOI
https://doi.org/10.1007/s12032-020-01404-7

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