IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0215452.html
   My bibliography  Save this article

Array expression meta-analysis of cancer stem cell genes identifies upregulation of PODXL especially in DCC low expression meningiomas

Author

Listed:
  • Hans-Juergen Schulten
  • Deema Hussein

Abstract

Background: Meningiomas are the most common intracranial tumors, with a subset of cases bearing a progressive phenotype. The DCC netrin 1 receptor (DCC) is a candidate gene for early meningioma progression. Cancer stem cell (CSC) genes are emerging as cancer therapeutic targets, as their expression is frequently associated with aggressive tumor phenotypes. The main objective of the study was to identify deregulated CSC genes in meningiomas. Materials and methods: Interrogating two expression data repositories, significantly differentially expressed genes (DEGs) were determined using DCC low vs. DCC high expression groups and WHO grade I (GI) vs. grade II + grade III (GII + GIII) comparison groups. Human stem cell (SC) genes were compiled from two published data sets and were extracted from the DEG lists. Biofunctional analysis was performed to assess associations between genes or molecules. Results: In the DCC low vs. DCC high expression groups, we assessed seven studies representing each between seven and 58 samples. The type I transmembrane protein podocalyxin like (PODXL) was markedly upregulated in DCC low expression meningiomas in six studies. Other CSC genes repeatedly deregulated included, e.g., BMP/retinoic acid inducible neural specific 1 (BRINP1), prominin 1 (PROM1), solute carrier family 24 member 3 (SLC24A3), rRho GTPase activating protein 28 (ARHGAP28), Kruppel like factor 5 (KLF5), and leucine rich repeat containing G protein-coupled receptor 4 (LGR4). In the GI vs. GII + GIII comparison groups, we assessed six studies representing each between nine and 68 samples. DNA topoisomerase 2-alpha (TOP2A) was markedly upregulated in GII + GIII meningiomas in four studies. Other CSC genes repeatedly deregulated included, e.g., ARHGAP28 and PODXL. Network analysis revealed associations of molecules with, e.g., cellular development and movement; nervous system development and function; and cancer. Conclusions: This meta-analysis on meningiomas identified a comprehensive list of deregulated CSC genes across different array expression studies. Especially, PODXL is of interest for functional assessment in progressive meningiomas.

Suggested Citation

  • Hans-Juergen Schulten & Deema Hussein, 2019. "Array expression meta-analysis of cancer stem cell genes identifies upregulation of PODXL especially in DCC low expression meningiomas," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-20, May.
    • Handle: RePEc:plo:pone00:0215452
    DOI: 10.1371/journal.pone.0215452
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0215452
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0215452&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0215452?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mayumi Okamoto & Takaki Miyata & Daijiro Konno & Hiroki R. Ueda & Takeya Kasukawa & Mitsuhiro Hashimoto & Fumio Matsuzaki & Ayano Kawaguchi, 2016. "Cell-cycle-independent transitions in temporal identity of mammalian neural progenitor cells," Nature Communications, Nature, vol. 7(1), pages 1-16, September.
    2. Colin T Maguire & Bradley L Demarest & Jonathon T Hill & James D Palmer & Arthur R Brothman & H Joseph Yost & Maureen L Condic, 2013. "Genome-Wide Analysis Reveals the Unique Stem Cell Identity of Human Amniocytes," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-16, January.
    3. Adaikalavan Ramasamy & Adrian Mondry & Chris C Holmes & Douglas G Altman, 2008. "Key Issues in Conducting a Meta-Analysis of Gene Expression Microarray Datasets," PLOS Medicine, Public Library of Science, vol. 5(9), pages 1-13, September.
    4. Irène Aksoy & Vincent Giudice & Edwige Delahaye & Florence Wianny & Maxime Aubry & Magali Mure & Jiaxuan Chen & Ralf Jauch & Gireesh K. Bogu & Tobias Nolden & Heinz Himmelbauer & Michael Xavier Doss &, 2014. "Klf4 and Klf5 differentially inhibit mesoderm and endoderm differentiation in embryonic stem cells," Nature Communications, Nature, vol. 5(1), pages 1-15, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Miranda van Uitert & Perry D Moerland & Daniel A Enquobahrie & Hannele Laivuori & Joris A M van der Post & Carrie Ris-Stalpers & Gijs B Afink, 2015. "Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    2. Hailun Zhu & Sihai Dave Zhao & Alokananda Ray & Yu Zhang & Xin Li, 2022. "A comprehensive temporal patterning gene network in Drosophila medulla neuroblasts revealed by single-cell RNA sequencing," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    3. Diego A Forero & Sandra Lopez-Leon & Yeimy González-Giraldo & Pantelis G Bagos, 2019. "Ten simple rules for carrying out and writing meta-analyses," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-7, May.
    4. Won Jun Lee & Sang Cheol Kim & Jung-Ho Yoon & Sang Jun Yoon & Johan Lim & You-Sun Kim & Sung Won Kwon & Jeong Hill Park, 2016. "Meta-Analysis of Tumor Stem-Like Breast Cancer Cells Using Gene Set and Network Analysis," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-20, February.
    5. Cheng-Wei Chang & Wei-Chung Cheng & Chaang-Ray Chen & Wun-Yi Shu & Min-Lung Tsai & Ching-Lung Huang & Ian C Hsu, 2011. "Identification of Human Housekeeping Genes and Tissue-Selective Genes by Microarray Meta-Analysis," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-10, July.
    6. Cherif Ben Hamda & Raphael Sangeda & Liberata Mwita & Ayton Meintjes & Siana Nkya & Sumir Panji & Nicola Mulder & Lamia Guizani-Tabbane & Alia Benkahla & Julie Makani & Kais Ghedira & H3ABioNet Consor, 2018. "A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-21, July.
    7. Zhiguang Huo & Li Zhu & Tianzhou Ma & Hongcheng Liu & Song Han & Daiqing Liao & Jinying Zhao & George Tseng, 2020. "Two-Way Horizontal and Vertical Omics Integration for Disease Subtype Discovery," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(1), pages 1-22, April.
    8. Atle van Beelen Granlund & Arnar Flatberg & Ann E Østvik & Ignat Drozdov & Bjørn I Gustafsson & Mark Kidd & Vidar Beisvag & Sverre H Torp & Helge L Waldum & Tom Christian Martinsen & Jan Kristian Damå, 2013. "Whole Genome Gene Expression Meta-Analysis of Inflammatory Bowel Disease Colon Mucosa Demonstrates Lack of Major Differences between Crohn's Disease and Ulcerative Colitis," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-14, February.
    9. Hao He & Shaolong Cao & Tianhua Niu & Yu Zhou & Lan Zhang & Yong Zeng & Wei Zhu & Yu-ping Wang & Hong-wen Deng, 2016. "Network-Based Meta-Analyses of Associations of Multiple Gene Expression Profiles with Bone Mineral Density Variations in Women," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-16, January.
    10. Peter Langfelder & Paul S Mischel & Steve Horvath, 2013. "When Is Hub Gene Selection Better than Standard Meta-Analysis?," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-16, April.
    11. Stephen Huang & Casie Reed & Melissa Ilsley & Graham Magor & Michael Tallack & Michael Landsberg & Helen Mitchell & Kevin Gillinder & Andrew Perkins, 2024. "Mutations in linker-2 of KLF1 impair expression of membrane transporters and cytoskeletal proteins causing hemolysis," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    12. K. A. Gajewska & H. Lescesen & M. Ramialison & K. M. Wagstaff & D. A. Jans, 2021. "Nuclear transporter Importin-13 plays a key role in the oxidative stress transcriptional response," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    13. Wei-Chung Cheng & Cheng-Wei Chang & Chaang-Ray Chen & Min-Lung Tsai & Wun-Yi Shu & Chia-Yang Li & Ian C Hsu, 2011. "Identification of Reference Genes across Physiological States for qRT-PCR through Microarray Meta-Analysis," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-8, February.
    14. Claire Grills & Puthen V Jithesh & Jaine Blayney & Shu-Dong Zhang & Dean A Fennell, 2011. "Gene Expression Meta-Analysis Identifies VDAC1 as a Predictor of Poor Outcome in Early Stage Non-Small Cell Lung Cancer," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
    15. Bidossessi Wilfried Hounkpe & Rafaela de Oliveira Benatti & Benilton de Sá Carvalho & Erich Vinicius De Paula, 2020. "Identification of common and divergent gene expression signatures in patients with venous and arterial thrombosis using data from public repositories," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-19, August.
    16. Daniel Baron & Armelle Magot & Gérard Ramstein & Marja Steenman & Guillemette Fayet & Catherine Chevalier & Philippe Jourdon & Rémi Houlgatte & Frédérique Savagner & Yann Pereon, 2011. "Immune Response and Mitochondrial Metabolism Are Commonly Deregulated in DMD and Aging Skeletal Muscle," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-11, November.
    17. Ram Bhupal Reddy & Anupama Rajan Bhat & Bonney Lee James & Sindhu Valiyaveedan Govindan & Rohit Mathew & Ravindra DR & Naveen Hedne & Jeyaram Illiayaraja & Vikram Kekatpure & Samanta S Khora & Wesley , 2016. "Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-21, January.
    18. Julie E. Goodman & Catherine Petito Boyce & Sonja N. Sax & Leslie A. Beyer & Robyn L. Prueitt, 2015. "Rethinking Meta‐Analysis: Applications for Air Pollution Data and Beyond," Risk Analysis, John Wiley & Sons, vol. 35(6), pages 1017-1039, June.
    19. Raihan K Uddin & Shiva M Singh, 2013. "Hippocampal Gene Expression Meta-Analysis Identifies Aging and Age-Associated Spatial Learning Impairment (ASLI) Genes and Pathways," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-16, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0215452. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.