Abstract
The Group 3 Medulloblastoma (Grp3-MB) is an aggressive molecular subtype with a high incidence of metastasis and deaths. In this study, were used an RNA sequencing data (RNA-Seq) from a Brazilian cohort of MBs to identify hub genes associated with the metastatic risk. Data validation were performed by using multiple large datasets from MBs (GSE85217, GSE37418, and EGAS00001001953). DESeq2 package in R software was used to identify the differentially expressed genes (DEGs) in our RNA-Seq data. The DEGs data were accessed to construct the modules/graphs of co-expression and to identify hub genes through Cytoscape platform. The coregulated genes were enriched by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the protein–protein interaction (PPI) network was visualized by Cytoscape. The Kaplan–Meier plotter and ROC curves were used to validate the diagnostic and prognostic values of specific biomarkers identified through this model. We identified that inositol 1,4,5-trisphosphate receptor type 1 (ITPR1) as a downregulated hub gene, with a high diagnostic accuracy to Grp3-MBs and associated with tumor metastasis. In addition, we identified genes significantly correlated with ITPR1 that were associated with metastasis in Grp3-MB (ATP1A2, MTTL7A, and RGL1) and worst overall survival in MBs (ANTXR1 and RGL1). Our findings suggest that the ITPR1 hub gene is potentially involved in the metastatic process for Grp3-MB. Our data also provide evidence of targets that may serve as prognostic predictors and/or regulators for the metastatic process that maybe explored for further research of individualized therapy to Grp3-MBs.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Availability of Data and Materials
The data and other items supporting the results of the study will be made available upon reasonable request.
References
Bogdanov A, Moiseenko FV, Dubina M (2017) Abnormal expression of ATP1A1 and ATP1A2 in breast cancer. F1000Research 6:10. https://doi.org/10.12688/f1000research.10481.1
Bozhilova LV, Whitmore AV, Wray J et al (2019) Measuring rank robustness in scored protein interaction networks. BMC Bioinformatics 20:446. https://doi.org/10.1186/s12859-019-3036-6
Castillo‑Rodríguez RA, Dávila‑Borja VM, Juárez‑Méndez S (2018) Data mining of pediatric medulloblastoma microarray expression reveals a novel potential subdivision of the Group 4 molecular subgroup. Oncol Lett. https://doi.org/10.3892/ol.2018.8094
Cavalli FMG, Remke M, Rampasek L et al (2017) Intertumoral heterogeneity within medulloblastoma subgroups. Cancer Cell 31:737-754.e6. https://doi.org/10.1016/j.ccell.2017.05.005
Chen D, Bhat-Nakshatri P, Goswami C et al (2013) ANTXR1, a stem cell-enriched functional biomarker, connects collagen signaling to cancer stem-like cells and metastasis in breast cancer. Cancer Res 73:5821–5833. https://doi.org/10.1158/0008-5472.CAN-13-1080
Chen G, Sun L, Han J et al (2019) RILPL2 regulates breast cancer proliferation, metastasis, and chemoresistance via the TUBB3/PTEN pathway. Am J Cancer Res 9:1583–1606
Choi SA, Lee JY, Phi JH et al (2014) Identification of brain tumour initiating cells using the stem cell marker aldehyde dehydrogenase. Eur J Cancer 50:137–149. https://doi.org/10.1016/j.ejca.2013.09.004
Foskett JK, White C, Cheung K-H, Mak D-OD (2007) Inositol trisphosphate receptor Ca 2+ release channels. Physiol Rev 87:593–658. https://doi.org/10.1152/physrev.00035.2006
Fukuhisa H, Seki N, Idichi T et al (2019) Gene regulation by antitumor miR-130b-5p in pancreatic ductal adenocarcinoma: the clinical significance of oncogenic EPS8. J Hum Genet 64:521–534. https://doi.org/10.1038/s10038-019-0584-6
Gambardella J, Lombardi A, Morelli MB et al (2020) Inositol 1,4,5-trisphosphate receptors in human disease: a comprehensive update. J Clin Med 9:1096. https://doi.org/10.3390/jcm9041096
Gu Z, Eils R, Schlesner M (2016) Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32:2847–2849. https://doi.org/10.1093/bioinformatics/btw313
Guo X, Piao H, Zhang Y et al (2020a) Overexpression of microRNA-129–5p in glioblastoma inhibits cell proliferation, migration, and colony-forming ability by targeting ZFP36L1. Bosn J Basic Med Sci. https://doi.org/10.17305/bjbms.2019.4503
Guo Y, Huang P, Ning W et al (2020b) Identification of core genes and pathways in medulloblastoma by integrated bioinformatics analysis. J Mol Neurosci 70:1702–1712. https://doi.org/10.1007/s12031-020-01556-1
Hu G, Wang R, Wei B et al (2020) Prognostic markers identification in glioma by gene expression profile analysis. J Comput Biol 27:81–90. https://doi.org/10.1089/cmb.2019.0217
Huang P, Guo Y-D, Zhang H-W (2020) Identification of hub genes in pediatric medulloblastoma by multiple-microarray analysis. J Mol Neurosci 70:522–531. https://doi.org/10.1007/s12031-019-01451-4
Joy A, Moffet J, Neary K et al (1997) Nuclear accumulation of FGF-2 is associated with proliferation of human astrocytes and glioma cells. Oncogene 14:171–183. https://doi.org/10.1038/sj.onc.1200823
Juraschka K, Taylor MD (2019) Medulloblastoma in the age of molecular subgroups: a review. J Neurosurg Pediatr 24:353–363. https://doi.org/10.3171/2019.5.PEDS18381
Kanehisa M (2000) KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 28:27–30. https://doi.org/10.1093/nar/28.1.27
Key J, Mueller AK, Gispert S et al (2019) Ubiquitylome profiling of parkin-null brain reveals dysregulation of calcium homeostasis factors ATP1A2, hippocalcin and GNA11, reflected by altered firing of noradrenergic neurons. Neurobiol Dis 127:114–130. https://doi.org/10.1016/j.nbd.2019.02.008
Li Y, Xiao X, Bossé Y et al (2019) Genetic interaction analysis among oncogenesis-related genes revealed novel genes and networks in lung cancer development. Oncotarget 10:1760–1774. https://doi.org/10.18632/oncotarget.26678
Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of Tumors of the central nervous system: a summary. Neuro Oncol 23:1231–1251. https://doi.org/10.1093/neuonc/noab106
Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. https://doi.org/10.1186/s13059-014-0550-8
McKinnon CM, Mellor H (2017) The tumor suppressor RhoBTB1 controls Golgi integrity and breast cancer cell invasion through METTL7B. BMC Cancer 17:145. https://doi.org/10.1186/s12885-017-3138-3
Menyhárt O, Győrffy B (2019) Principles of tumorigenesis and emerging molecular drivers of SHH-activated medulloblastomas. Ann Clin Transl Neurol 6:990–1005. https://doi.org/10.1002/acn3.762
Montojo J, Zuberi K, Rodriguez H et al (2010) GeneMANIA cytoscape plugin: Fast gene function predictions on the desktop. Bioinformatics. https://doi.org/10.1093/bioinformatics/btq562
Nakanishi S, Maeda N, Mikoshiba K (1991) Immunohistochemical localization of an inositol 1,4,5-trisphosphate receptor, P400, in neural tissue: studies in developing and adult mouse brain. J Neurosci 11:2075–2086. https://doi.org/10.1523/JNEUROSCI.11-07-02075.1991
Northcott PA, Buchhalter I, Morrissy AS et al (2017) The whole-genome landscape of medulloblastoma subtypes. Nature 547:311–317. https://doi.org/10.1038/nature22973
Northcott PA, Robinson GW, Kratz CP et al (2019) Medulloblastoma. Nat Rev Dis Prim 5:11. https://doi.org/10.1038/s41572-019-0063-6
Parys JB, Bultynck G, Vervliet T (2021) IP3 Receptor biology and endoplasmic reticulum calcium dynamics in cancer. pp. 215–237
Politis PK, Akrivou S, Hurel C et al (2008) BM88/Cend1 is involved in histone deacetylase inhibition-mediated growth arrest and differentiation of neuroblastoma cells. FEBS Lett 582:741–748. https://doi.org/10.1016/j.febslet.2008.01.052
Robinson G, Parker M, Kranenburg TA et al (2012) Novel mutations target distinct subgroups of medulloblastoma. Nature 488:43–48. https://doi.org/10.1038/nature1121
Russo PST, Ferreira GR, Cardozo LE et al (2018) CEMiTool: a bioconductor package for performing comprehensive modular co-expression analyses. BMC Bioinformatics 19:56. https://doi.org/10.1186/s12859-018-2053-1
Roth RB, Hevezi P, Lee J et al (2006) Gene expression analyses reveal molecular relationships among 20 regions of the human CNS. Neurogenetics.67–80. http:// doi: https://doi.org/10.1007/s10048-006-0032-6
Shannon P (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504. https://doi.org/10.1101/gr.1239303
Sneyers F, Rosa N, Bultynck G (2020) Type 3 IP3 receptors driving oncogenesis. Cell Calcium 86:102141. https://doi.org/10.1016/j.ceca.2019.102141
Su Z, Yang Z, Xu Y et al (2015) Apoptosis, autophagy, necroptosis, and cancer metastasis. Mol Cancer 14:48. https://doi.org/10.1186/s12943-015-0321-5
Szklarczyk D, Franceschini A, Wyder S et al (2015) STRING v10: protein–protein interaction networks, integrated over the tree of life. Nucleic Acids Res 43:D447–D452. https://doi.org/10.1093/nar/gku1003
Tan F, Zhu H, Tao Y et al (2015) Neuron navigator 2 overexpression indicates poor prognosis of colorectal cancer and promotes invasion through the SSH1L/cofilin-1 pathway. J Exp Clin Cancer Res 34:117. https://doi.org/10.1186/s13046-015-0237-3
Tenan M, Aurrand-Lions M, Widmer V et al (2009) Cooperative expression of junctional adhesion molecule-C and -B supports growth and invasion of glioma. Glia NA-NA. https://doi.org/10.1002/glia.20941
Wang L, Yao L, Zheng Y-Z et al (2015a) Expression of autophagy-related proteins ATG5 and FIP200 predicts favorable disease-free survival in patients with breast cancer. Biochem Biophys Res Commun 458:816–822. https://doi.org/10.1016/j.bbrc.2015.02.037
Wang M, Liu Y, Zou J, et al (2015b) Transcriptional co-activator TAZ sustains proliferation and tumorigenicity of neuroblastoma by targeting CTGF and PDGF-β. Oncotarget 6:9517–9530. https://doi.org/10.18632/oncotarget.3367
Warde-Farley D, Donaldson SL, Comes O et al (2010) The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res 38:W214–W220. https://doi.org/10.1093/nar/gkq537
Wright KL, Adams JR, Liu JC et al (2015) Ras signaling is a key determinant for metastatic dissemination and poor survival of luminal breast cancer patients. Cancer Res 75:4960–4972. https://doi.org/10.1158/0008-5472.CAN-14-2992
Xu S, Wang P, Zhang J et al (2019) Ai-lncRNA EGOT enhancing autophagy sensitizes paclitaxel cytotoxicity via upregulation of ITPR1 expression by RNA-RNA and RNA-protein interactions in human cancer. Mol Cancer 18:89. https://doi.org/10.1186/s12943-019-1017-z
Yan J, Zhao Q, Gabrusiewicz K et al (2019) FGL2 promotes tumor progression in the CNS by suppressing CD103+ dendritic cell differentiation. Nat Commun 10:448. https://doi.org/10.1038/s41467-018-08271-x
Yao M, Zhou X, Zhou J et al (2018) PCGF5 is required for neural differentiation of embryonic stem cells. Nat Commun 9:1463. https://doi.org/10.1038/s41467-018-03781-0
Yu X, Feng L, Liu D, et al (2016) Quantitative proteomics reveals the novel co-expression signatures in early brain development for prognosis of glioblastoma multiforme. Oncotarget 7:14161–14171. https://doi.org/10.18632/oncotarget.7416
Acknowledgements
We want to thank and acknowledge patients and families affected by medulloblastomas for their generous contributions to these studies.
Funding
The study was supported by public Brazilian grants from the São Paulo State Research Foundation (FAPESP), Grant numbers: 2014/20341–0, 2017/26160–5, Brazilian Research Council (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES) Financial Code 001, and Foundation for Support of Education, Research, and Assistance (FAEPA), Brazil.
Author information
Authors and Affiliations
Contributions
P.F.C designed, conducted, and interpreted all experiments, and wrote the manuscript. G.R.S, L.C.V, A.M.S, C.A.P.C; G.A.V.C, and L.F.P.N wrote and organized the data, created the figures/tables, and edited and critically revised the manuscript. R.G.P.Q, S.K.N.M, S.R.B, C.A.S, and L.G.T revised the text for important intellectual content. E. T. V designed the study and critically read the manuscript. All authors critically read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethics Approval and Consent to Participate
This study was approved by the HC/FMRP-USP Research Ethics Committee (Approval number: CAAE: 62604816.4.000.5440), and informed consent was obtained from all patients included.
Consent for Publication
Not applicable.
Competing Interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
das Chagas, P.F., de Sousa, G.R., Veronez, L.C. et al. Identification of ITPR1 as a Hub Gene of Group 3 Medulloblastoma and Coregulated Genes with Potential Prognostic Values. J Mol Neurosci 72, 633–641 (2022). https://doi.org/10.1007/s12031-021-01942-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12031-021-01942-3