Home LiteratureArticle Details
PMID: 29304754 Published · epublish English Journal Article Research Support, Non-U.S. Gov't

Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

BMC genomics ·Vol. 19 ·No. 1 ·2018-00-06 ·Pages 25

Cava C, Bertoli G, Colaprico A, Olsen C, Bontempi G, Castiglioni I

Abstract

Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

Keywords
Genes Multi-networks Pan-cancer Pathways
MeSH Terms
Algorithms Biomarkers, Tumor/genetics Case-Control Studies Gene Expression Profiling Gene Expression Regulation, Neoplastic Gene Regulatory Networks Genomics/methods Humans Neoplasms/genetics Signal Transduction
Chemicals
Biomarkers, Tumor
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Cava Claudia ORCID
Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090, Milan, Segrate-Milan, Italy. claudia.cava@ibfm.cnr.it.
Bertoli Gloria
Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090, Milan, Segrate-Milan, Italy.
Colaprico Antonio
Interuniversity Institute of Bioinformatics in Brussels (IB)2, 1050, Brussels, Belgium. | Machine Learning Group (MLG), Department d'Informatique, Universite libre de Bruxelles (ULB), 1050, Brussels, Belgium.
Olsen Catharina
Interuniversity Institute of Bioinformatics in Brussels (IB)2, 1050, Brussels, Belgium. | Machine Learning Group (MLG), Department d'Informatique, Universite libre de Bruxelles (ULB), 1050, Brussels, Belgium.
Bontempi Gianluca
Interuniversity Institute of Bioinformatics in Brussels (IB)2, 1050, Brussels, Belgium. | Machine Learning Group (MLG), Department d'Informatique, Universite libre de Bruxelles (ULB), 1050, Brussels, Belgium.
Castiglioni Isabella
Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F.Cervi 93, 20090, Milan, Segrate-Milan, Italy. isabella.castiglioni@ibfm.cnr.it.
References (75)
75 references, click to expand
  1. Comparative proteomics of primary breast carcinomas and lymph node metastases outlining markers of tumor invasion.
    Cancer Genomics Proteomics. 2015 Mar-Apr;12(2):89-101 PMID: 25770193
  2. TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages.
    F1000Res. 2016 Jun 29;5:1542 PMID: 28232861
  3. Cancer genes and the pathways they control.
    Nat Med. 2004 Aug;10(8):789-99 PMID: 15286780
  4. De novo discovery of mutated driver pathways in cancer.
    Genome Res. 2012 Feb;22(2):375-85 PMID: 21653252
  5. Comprehensive genomic characterization defines human glioblastoma genes and core pathways.
    Nature. 2008 Oct 23;455(7216):1061-8 PMID: 18772890
  6. DawnRank: discovering personalized driver genes in cancer.
    Genome Med. 2014 Jul 31;6(7):56 PMID: 25177370
  7. Mutational heterogeneity in cancer and the search for new cancer-associated genes.
    Nature. 2013 Jul 11;499(7457):214-218 PMID: 23770567
  8. Identifying in-trans process associated genes in breast cancer by integrated analysis of copy number and expression data.
    PLoS One. 2013;8(1):e53014 PMID: 23382830
  9. A germline FANCA alteration that is associated with increased sensitivity to DNA damaging agents.
    Cold Spring Harb Mol Case Stud. 2017 Sep;3(5): PMID: 28864460
  10. A robust biomarker of differential correlations improves the diagnosis of cytologically indeterminate thyroid cancers.
    Int J Mol Med. 2016 May;37(5):1355-62 PMID: 27035928
  11. Annotating cancer variants and anti-cancer therapeutics in reactome.
    Cancers (Basel). 2012 Nov 08;4(4):1180-211 PMID: 24213504
  12. GC-content normalization for RNA-Seq data.
    BMC Bioinformatics. 2011 Dec 17;12:480 PMID: 22177264
  13. Proteomics. Tissue-based map of the human proteome.
    Science. 2015 Jan 23;347(6220):1260419 PMID: 25613900
  14. Aldehyde dehydrogenase 3B1 (ALDH3B1): immunohistochemical tissue distribution and cellular-specific localization in normal and cancerous human tissues.
    J Histochem Cytochem. 2010 Sep;58(9):765-83 PMID: 20729348
  15. Survivin and gynaecological tumours.
    Pathol Res Pract. 2017 Apr;213(4):295-300 PMID: 28285964
  16. Survivin, a molecular target for therapeutic interventions in squamous cell carcinoma.
    Cell Mol Biol Lett. 2017 Apr 5;22:8 PMID: 28536639
  17. e-Driver: a novel method to identify protein regions driving cancer.
    Bioinformatics. 2014 Nov 1;30(21):3109-14 PMID: 25064568
  18. Role of specialized DNA polymerases in the limitation of replicative stress and DNA damage transmission.
    Mutat Res. 2018 Mar;808:62-73 PMID: 28843435
  19. Hypermutated tumours in the era of immunotherapy: The paradigm of personalised medicine.
    Eur J Cancer. 2017 Oct;84:290-303 PMID: 28846956
  20. Genomic instability--an evolving hallmark of cancer.
    Nat Rev Mol Cell Biol. 2010 Mar;11(3):220-8 PMID: 20177397
  21. Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integration.
    BMC Genomics. 2016 Sep 09;17(1):722 PMID: 27612452
  22. Influence of chemotherapeutic drug-related gene polymorphisms on toxicity and survival of early breast cancer patients receiving adjuvant chemotherapy.
    BMC Cancer. 2017 Jul 26;17(1):502 PMID: 28747156
  23. Functional impact bias reveals cancer drivers.
    Nucleic Acids Res. 2012 Nov;40(21):e169 PMID: 22904074
  24. Cancer genome landscapes.
    Science. 2013 Mar 29;339(6127):1546-58 PMID: 23539594
  25. Polymorphisms of GSTM1, GSTT1, GSTP1 genes and chromosomal aberrations in lung cancer patients.
    J Cancer Res Clin Oncol. 2017 Nov;143(11):2235-2243 PMID: 28770368
  26. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.
    Nat Genet. 2000 May;25(1):25-9 PMID: 10802651
  27. Automated network analysis identifies core pathways in glioblastoma.
    PLoS One. 2010 Feb 12;5(2):e8918 PMID: 20169195
  28. ROS signaling under metabolic stress: cross-talk between AMPK and AKT pathway.
    Mol Cancer. 2017 Apr 13;16(1):79 PMID: 28407774
  29. Somatic mutations affect key pathways in lung adenocarcinoma.
    Nature. 2008 Oct 23;455(7216):1069-75 PMID: 18948947
  30. Aldo-Keto Reductase AKR1C1-AKR1C4: Functions, Regulation, and Intervention for Anti-cancer Therapy.
    Front Pharmacol. 2017 Mar 14;8:119 PMID: 28352233
  31. Why do hubs tend to be essential in protein networks?
    PLoS Genet. 2006 Jun 2;2(6):e88 PMID: 16751849
  32. Sulforaphane, a Dietary Isothiocyanate, Induces G₂/M Arrest in Cervical Cancer Cells through CyclinB1 Downregulation and GADD45β/CDC2 Association.
    Int J Mol Sci. 2016 Sep 12;17(9): PMID: 27626412
  33. IDO1 metabolites activate β-catenin signaling to promote cancer cell proliferation and colon tumorigenesis in mice.
    Gastroenterology. 2013 Aug;145(2):416-25.e1-4 PMID: 23669411
  34. Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential.
    BMC Syst Biol. 2015 Sep 21;9:62 PMID: 26391647
  35. UpSet: Visualization of Intersecting Sets.
    IEEE Trans Vis Comput Graph. 2014 Dec;20(12):1983-92 PMID: 26356912
  36. SpidermiR: An R/Bioconductor Package for Integrative Analysis with miRNA Data.
    Int J Mol Sci. 2017 Jan 27;18(2): PMID: 28134831
  37. KEGG: new perspectives on genomes, pathways, diseases and drugs.
    Nucleic Acids Res. 2017 Jan 4;45(D1):D353-D361 PMID: 27899662
  38. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function.
    Nucleic Acids Res. 2010 Jul;38(Web Server issue):W214-20 PMID: 20576703
  39. Identifying cancer driver genes in tumor genome sequencing studies.
    Bioinformatics. 2011 Jan 15;27(2):175-81 PMID: 21169372
  40. The mutational landscape of phosphorylation signaling in cancer.
    Sci Rep. 2013 Oct 02;3:2651 PMID: 24089029
  41. DriverDB: an exome sequencing database for cancer driver gene identification.
    Nucleic Acids Res. 2014 Jan;42(Database issue):D1048-54 PMID: 24214964
  42. How interacting pathways are regulated by miRNAs in breast cancer subtypes.
    BMC Bioinformatics. 2016 Nov 8;17(Suppl 12):348 PMID: 28185585
  43. The cancer genome.
    Nature. 2009 Apr 9;458(7239):719-24 PMID: 19360079
  44. Moving to the Rhythm with Clock (Circadian) Genes, Autophagy, mTOR, and SIRT1 in Degenerative Disease and Cancer.
    Curr Neurovasc Res. 2017;14(3):299-304 PMID: 28721811
  45. A review of the basics of mitochondrial bioenergetics, metabolism, and related signaling pathways in cancer cells: Therapeutic targeting of tumor mitochondria with lipophilic cationic compounds.
    Redox Biol. 2018 Apr;14:316-327 PMID: 29017115
  46. Activity-Based Protein Profiling of Oncogene-Driven Changes in Metabolism Reveals Broad Dysregulation of PAFAH1B2 and 1B3 in Cancer.
    ACS Chem Biol. 2015 Jul 17;10(7):1624-30 PMID: 25945974
  47. Gene expression profiling of colorectal tumors and normal mucosa by microarrays meta-analysis using prediction analysis of microarray, artificial neural network, classification, and regression trees.
    Dis Markers. 2014;2014:634123 PMID: 24959000
  48. The Role of Indoleamine 2, 3-Dioxygenase in Immune Suppression and Autoimmunity.
    Vaccines (Basel). 2015 Sep 10;3(3):703-29 PMID: 26378585
  49. GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor.
    Bioinformatics. 2007 Jul 15;23(14):1846-7 PMID: 17496320
  50. Sine oculis homeobox homolog 1 promotes DNA replication and cell proliferation in cervical cancer.
    Int J Oncol. 2014 Sep;45(3):1232-40 PMID: 24970368
  51. Regulation of DNA polymerase POLD4 influences genomic instability in lung cancer.
    Cancer Res. 2010 Nov 1;70(21):8407-16 PMID: 20861182
  52. The role of ubiquitin-proteasome pathway in oncogenic signaling.
    Cancer Biol Ther. 2002 Jul-Aug;1(4):337-41 PMID: 12432242
  53. Efficient methods for identifying mutated driver pathways in cancer.
    Bioinformatics. 2012 Nov 15;28(22):2940-7 PMID: 22982574
  54. TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data.
    Nucleic Acids Res. 2016 May 5;44(8):e71 PMID: 26704973
  55. FN1, GALE, MET, and QPCT overexpression in papillary thyroid carcinoma: molecular analysis using frozen tissue and routine fine-needle aspiration biopsy samples.
    Diagn Cytopathol. 2011 Aug;39(8):556-61 PMID: 20607686
  56. The Cancer Genome Atlas Pan-Cancer analysis project.
    Nat Genet. 2013 Oct;45(10):1113-20 PMID: 24071849
  57. Cordycepin promotes apoptosis in renal carcinoma cells by activating the MKK7-JNK signaling pathway through inhibition of c-FLIPL expression.
    PLoS One. 2017 Oct 18;12(10):e0186489 PMID: 29045468
  58. The hallmarks of cancer.
    Cell. 2000 Jan 7;100(1):57-70 PMID: 10647931
  59. Elevated Expression of RPA3 Is Involved in Gastric Cancer Tumorigenesis and Associated with Poor Patient Survival.
    Dig Dis Sci. 2017 Sep;62(9):2369-2375 PMID: 28766245
  60. Mutual exclusivity analysis identifies oncogenic network modules.
    Genome Res. 2012 Feb;22(2):398-406 PMID: 21908773
  61. The Reactome Pathway Knowledgebase.
    Nucleic Acids Res. 2018 Jan 4;46(D1):D649-D655 PMID: 29145629
  62. OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes.
    Bioinformatics. 2013 Sep 15;29(18):2238-44 PMID: 23884480
  63. Discovery of co-occurring driver pathways in cancer.
    BMC Bioinformatics. 2014 Aug 09;15:271 PMID: 25106096
  64. DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer.
    Genome Biol. 2012 Dec 22;13(12):R124 PMID: 23383675
  65. LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.
    Sci Rep. 2016 Jan 11;6:18871 PMID: 26750448
  66. Clinical response to chemotherapy in oesophageal adenocarcinoma patients is linked to defects in mitochondria.
    J Pathol. 2013 Aug;230(4):410-9 PMID: 23592244
  67. Prognostic role of survivin in renal cell carcinoma: A system review and meta-analysis.
    Eur J Intern Med. 2016 Sep;33:102-7 PMID: 27350406
  68. Decreased expression and aberrant methylation of Gadd45G is associated with tumor progression and poor prognosis in esophageal squamous cell carcinoma.
    Clin Exp Metastasis. 2013 Dec;30(8):977-92 PMID: 23793925
  69. A network-based gene-weighting approach for pathway analysis.
    Cell Res. 2012 Mar;22(3):565-80 PMID: 21894192
  70. The glutathione S-transferase supergene family: regulation of GST and the contribution of the isoenzymes to cancer chemoprotection and drug resistance.
    Crit Rev Biochem Mol Biol. 1995;30(6):445-600 PMID: 8770536
  71. Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma.
    Proc Natl Acad Sci U S A. 2007 Dec 11;104(50):20007-12 PMID: 18077431
  72. Detection of gene communities in multi-networks reveals cancer drivers.
    Sci Rep. 2015 Dec 07;5:17386 PMID: 26639632
  73. Integrating omics data and protein interaction networks to prioritize driver genes in cancer.
    Oncotarget. 2017 Jul 22;8(35):58050-58060 PMID: 28938536
  74. Inverse correlation between tumoral indoleamine 2,3-dioxygenase expression and tumor-infiltrating lymphocytes in endometrial cancer: its association with disease progression and survival.
    Clin Cancer Res. 2008 Apr 15;14(8):2310-7 PMID: 18413819
  75. Integrative Analysis with Monte Carlo Cross-Validation Reveals miRNAs Regulating Pathways Cross-Talk in Aggressive Breast Cancer.
    Biomed Res Int. 2015;2015:831314 PMID: 26240829
Article Info
Journal
BMC genomics
Abbr.
BMC Genomics
ISSN
1471-2164
DOI
10.1186/s12864-017-4423-x
Email
claudia.cava@ibfm.cnr.it
isabella.castiglioni@ibfm.cnr.it
Published
2018-00-06
Epub
2018-00-06
Pages
25
Language
English
Region
England
NLM ID
100965258
PMCID
PMC5756345
Subset
IM
Grants
INTEROMICS flagship project · CUP Grant B91J12000190001 · International
External Links
PubMed source DOI: 10.1186/s12864-017-4423-x PMC Full Text View journal details
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: product@genelibs.com

Copyright © 2026.Genelibs Jinan Honghui Biotechnology Co., Ltd. 鲁ICP备20007159号-2