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Published in: Cancer Cell International 1/2017

Open Access 01-12-2017 | Primary Research

Integrated genomic characterization of cancer genes in glioma

Published in: Cancer Cell International | Issue 1/2017

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Abstract

Background

Cancers are caused by the acquisition of somatic mutations. Numerous efforts have been made to characterize the key driver genes and pathways in glioma, however, the etiology of glioma is still not completely known. This study was implemented to characterize driver genes in glioma independently of somatic mutation frequencies.

Methods

Driver genes and pathways were predicted by OncodriveCLUST, OncodriveFM, Icages, Drgap and Dendrix in glioma using 31,958 somatic mutations from TCGA, followed by an integrative characterization of driver genes.

Results

Overall, 685 driver genes and 215 driver pathways were determined by the five tools. FSTL5, HCN1, TMEM132D, TRHDE and KRT222 showed the strongest expression correlation with other genes in the co-expression network of glioma tissues. ST6GAL2, PIK3CA, PIK3R1, TP53 and EGFR are at the core of the protein–protein interaction network. 133 driver genes were up-regulated and associated to poor prognosis, 43 driver genes were down-regulated and related to favorable clinical outcome in glioma patients. The driver genes such as MSH6 and RUNX1T1 might serve as candidate prognostic biomarkers and therapeutic targets in glioma.

Conclusions

The set of new cancer genes and pathways sheds insights into the tumorigenesis of glioma and paves the way for developing driver gene-targeted therapy and prognostic biomarkers in glioma.
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Literature
1.
go back to reference Ostrom QT, Gittleman H, Farah P, Ondracek A, Chen Y, Wolinsky Y, et al. NEURO-ONCOLOGY CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2006–2010. Neuro Oncol. 2013;12:28–36. Ostrom QT, Gittleman H, Farah P, Ondracek A, Chen Y, Wolinsky Y, et al. NEURO-ONCOLOGY CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2006–2010. Neuro Oncol. 2013;12:28–36.
2.
go back to reference Claus EB, Walsh KM, Wiencke JK, Molinaro AM, Wiemels JL, Schildkraut JM, et al. Survival and low-grade glioma: the emergence of genetic information. Neurosurg Focus. 2015;38:1–10.CrossRef Claus EB, Walsh KM, Wiencke JK, Molinaro AM, Wiemels JL, Schildkraut JM, et al. Survival and low-grade glioma: the emergence of genetic information. Neurosurg Focus. 2015;38:1–10.CrossRef
3.
go back to reference McLendon R, Friedman A, Bigner D, Van Meir EG, Brat DJ, Mastrogianakis GM, et al. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455:1061–8.CrossRef McLendon R, Friedman A, Bigner D, Van Meir EG, Brat DJ, Mastrogianakis GM, et al. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455:1061–8.CrossRef
5.
6.
go back to reference Ichimura K, Pearson DM, Kocialkowski S, Bäcklund LM, Chan R, Jones DTW, et al. IDH1 mutations are present in the majority of common adult gliomas but rare in primary glioblastomas. Neuro Oncol. 2009;11:341–7.CrossRefPubMedPubMedCentral Ichimura K, Pearson DM, Kocialkowski S, Bäcklund LM, Chan R, Jones DTW, et al. IDH1 mutations are present in the majority of common adult gliomas but rare in primary glioblastomas. Neuro Oncol. 2009;11:341–7.CrossRefPubMedPubMedCentral
7.
go back to reference Silber JR, Blank A, Bobola MS, Ghatan S, Kolstoe DD, Berger MS. O6-methylguanine-DNA methyltransferase-deficient phenotype in human gliomas: frequency and time to tumor progression after alkylating agent-based chemotherapy. Clin Cancer Res. 1999;5:807–14.PubMed Silber JR, Blank A, Bobola MS, Ghatan S, Kolstoe DD, Berger MS. O6-methylguanine-DNA methyltransferase-deficient phenotype in human gliomas: frequency and time to tumor progression after alkylating agent-based chemotherapy. Clin Cancer Res. 1999;5:807–14.PubMed
8.
go back to reference Jaeckle KA, Eyre HJ, Townsend JJ, Schulman S, Knudson HM, Belanich M, et al. Correlation of tumor O6 methylguanine-DNA methyltransferase levels with survival of malignant astrocytoma patients treated with bis-chloroethylnitrosourea: a Southwest Oncology Group study. J Clin Oncol. 1998;16:3310–5. doi:10.1200/JCO.1998.16.10.3310.CrossRefPubMed Jaeckle KA, Eyre HJ, Townsend JJ, Schulman S, Knudson HM, Belanich M, et al. Correlation of tumor O6 methylguanine-DNA methyltransferase levels with survival of malignant astrocytoma patients treated with bis-chloroethylnitrosourea: a Southwest Oncology Group study. J Clin Oncol. 1998;16:3310–5. doi:10.​1200/​JCO.​1998.​16.​10.​3310.CrossRefPubMed
9.
go back to reference Hegi ME, Diserens A, Godard S, Dietrich P, Regli L, Ostermann S, et al. Clinical trial substantiates the predictive value of O-6-methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide. Clin Cancer Res. 2004;10:1871–4.CrossRefPubMed Hegi ME, Diserens A, Godard S, Dietrich P, Regli L, Ostermann S, et al. Clinical trial substantiates the predictive value of O-6-methylguanine-DNA methyltransferase promoter methylation in glioblastoma patients treated with temozolomide. Clin Cancer Res. 2004;10:1871–4.CrossRefPubMed
10.
go back to reference Chang K, Creighton CJ, Davis C, Donehower L, Drummond J, Wheeler D, et al. The cancer genome atlas pan-cancer analysis project. Nat Genet. 2013;45:1113–20.CrossRef Chang K, Creighton CJ, Davis C, Donehower L, Drummond J, Wheeler D, et al. The cancer genome atlas pan-cancer analysis project. Nat Genet. 2013;45:1113–20.CrossRef
11.
go back to reference Chen Y, Cunningham F, Rios D, McLaren WM, Smith J, Pritchard B, et al. Ensembl variation resources. BMC Genom. 2010;11:293.CrossRef Chen Y, Cunningham F, Rios D, McLaren WM, Smith J, Pritchard B, et al. Ensembl variation resources. BMC Genom. 2010;11:293.CrossRef
12.
go back to reference Tamborero D, Gonzalez-perez A, Lopez-bigas N. Genome analysis OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes. Bioinformatics. 2013;29:2238–44.CrossRefPubMed Tamborero D, Gonzalez-perez A, Lopez-bigas N. Genome analysis OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes. Bioinformatics. 2013;29:2238–44.CrossRefPubMed
13.
go back to reference Gonzalez-Perez A, Lopez-Bigas N. Functional impact bias reveals cancer drivers. Nucleic Acids Res. 2012;40:1–10.CrossRef Gonzalez-Perez A, Lopez-Bigas N. Functional impact bias reveals cancer drivers. Nucleic Acids Res. 2012;40:1–10.CrossRef
15.
go back to reference Dong C, Yang H, He Z, Liu X, Wang K. iCAGES: integrated cancer genome score for comprehensively prioritizing cancer driver genes in personal genomes. Genome Med. 2016;8:135.CrossRefPubMedPubMedCentral Dong C, Yang H, He Z, Liu X, Wang K. iCAGES: integrated cancer genome score for comprehensively prioritizing cancer driver genes in personal genomes. Genome Med. 2016;8:135.CrossRefPubMedPubMedCentral
16.
go back to reference Vandin F, Upfal E, Raphael BJ, Hormozdiari F, Hajirasouliha I, Mcpherson A. De novo discovery of mutated driver pathways in cancer. Genome Res. 2012;22:375–85.CrossRefPubMedPubMedCentral Vandin F, Upfal E, Raphael BJ, Hormozdiari F, Hajirasouliha I, Mcpherson A. De novo discovery of mutated driver pathways in cancer. Genome Res. 2012;22:375–85.CrossRefPubMedPubMedCentral
17.
go back to reference Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45:D362-D368.CrossRefPubMed Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein–protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45:D362-D368.CrossRefPubMed
18.
go back to reference Gill BJ, Pisapia DJ, Malone HR, Goldstein H, Lei L, Sonabend A, et al. MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma. Proc Natl Acad Sci USA. 2014;111:12550–5.CrossRefPubMedPubMedCentral Gill BJ, Pisapia DJ, Malone HR, Goldstein H, Lei L, Sonabend A, et al. MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma. Proc Natl Acad Sci USA. 2014;111:12550–5.CrossRefPubMedPubMedCentral
19.
go back to reference Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 2008;9:559.CrossRef Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 2008;9:559.CrossRef
21.
go back to reference Anaya J. OncoLnc : linking TCGA survival data to mRNAs, miRNAs, and lncRNAs. 2016. Anaya J. OncoLnc : linking TCGA survival data to mRNAs, miRNAs, and lncRNAs. 2016.
22.
go back to reference Geisbrecht BV, Gould SJ. The human PICD gene encodes a cytoplasmic and peroxisomal NADP+-dependent isocitrate dehydrogenase. J Biol Chem. 1999;274:30527–33.CrossRefPubMed Geisbrecht BV, Gould SJ. The human PICD gene encodes a cytoplasmic and peroxisomal NADP+-dependent isocitrate dehydrogenase. J Biol Chem. 1999;274:30527–33.CrossRefPubMed
24.
go back to reference Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.CrossRefPubMedPubMedCentral Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.CrossRefPubMedPubMedCentral
25.
go back to reference Liu Y, Sun J, Zhao M. ONGene: a literature-based database for human oncogenes. J Genet Genom. 2016;44:2016–8. Liu Y, Sun J, Zhao M. ONGene: a literature-based database for human oncogenes. J Genet Genom. 2016;44:2016–8.
26.
go back to reference Zhao M, Sun J, Zhao Z. TSGene: a web resource for tumor suppressor genes. Nucleic Acids Res. 2013;41:970–6.CrossRef Zhao M, Sun J, Zhao Z. TSGene: a web resource for tumor suppressor genes. Nucleic Acids Res. 2013;41:970–6.CrossRef
27.
go back to reference Li H, Yu B, Li J, Su L, Yan M, Zhang J, et al. Characterization of differentially expressed genes involved in pathways associated with gastric cancer. PLoS ONE. 2015;10:1–17. Li H, Yu B, Li J, Su L, Yan M, Zhang J, et al. Characterization of differentially expressed genes involved in pathways associated with gastric cancer. PLoS ONE. 2015;10:1–17.
28.
go back to reference Plaschke J, Krüger S, Dietmaier W, Gebert J, Sutter C, Mangold E, et al. Eight novel MSH6 germline mutations in patients with familial and nonfamilial colorectal cancer selected by loss of protein expression in tumor tissue. Hum Mutat. 2004;23:285.CrossRefPubMed Plaschke J, Krüger S, Dietmaier W, Gebert J, Sutter C, Mangold E, et al. Eight novel MSH6 germline mutations in patients with familial and nonfamilial colorectal cancer selected by loss of protein expression in tumor tissue. Hum Mutat. 2004;23:285.CrossRefPubMed
29.
go back to reference Kolodner R, Tytell J, Schmeits J, Kane MF, Gupta RD, Wahlber S, et al. Germline msh6 mutations in colorectal cancer families. Cancer Res. 1999;59:5068–74.PubMed Kolodner R, Tytell J, Schmeits J, Kane MF, Gupta RD, Wahlber S, et al. Germline msh6 mutations in colorectal cancer families. Cancer Res. 1999;59:5068–74.PubMed
30.
go back to reference Grindedal EM, Møller P, Eeles R, Stormorken AT, Bowitz-Lothe IM, Landrø SM, et al. Germ-line mutations in mismatch repair genes associated with prostate cancer. Cancer Epidemiol Biomark Prev. 2009;18:2460–7.CrossRef Grindedal EM, Møller P, Eeles R, Stormorken AT, Bowitz-Lothe IM, Landrø SM, et al. Germ-line mutations in mismatch repair genes associated with prostate cancer. Cancer Epidemiol Biomark Prev. 2009;18:2460–7.CrossRef
31.
go back to reference Devlin LA, Graham CA, Price JH, Morrison PJ. Germline MSH6 mutations are more prevalent in endometrial cancer patient cohorts than hereditary non polyposis colorectal cancer cohorts. Ulster Med J. 2008;77:25–30.PubMedPubMedCentral Devlin LA, Graham CA, Price JH, Morrison PJ. Germline MSH6 mutations are more prevalent in endometrial cancer patient cohorts than hereditary non polyposis colorectal cancer cohorts. Ulster Med J. 2008;77:25–30.PubMedPubMedCentral
32.
go back to reference Alvino E, Passarelli F, Cannavò E, Fortes C, Mastroeni S, Caporali S, et al. High expression of the mismatch repair protein MSH6 is associated with poor patient survival in melanoma. Am J Clin Pathol. 2014;142:121–32.CrossRefPubMed Alvino E, Passarelli F, Cannavò E, Fortes C, Mastroeni S, Caporali S, et al. High expression of the mismatch repair protein MSH6 is associated with poor patient survival in melanoma. Am J Clin Pathol. 2014;142:121–32.CrossRefPubMed
33.
go back to reference Jentzsch T, Robl B, Husmann M, Bode-Lesniewska B, Fuchs B. Expression of MSH2 and MSH6 on a tissue microarray in patients with osteosarcoma. Anticancer Res. 2014;34:6961–72.PubMed Jentzsch T, Robl B, Husmann M, Bode-Lesniewska B, Fuchs B. Expression of MSH2 and MSH6 on a tissue microarray in patients with osteosarcoma. Anticancer Res. 2014;34:6961–72.PubMed
34.
go back to reference Mulloy JC, Cammenga J, Berguido FJ, Wu K, Zhou P, Comenzo RL, et al. Maintaining the self-renewal and differentiation potential of human CD34+ hematopoietic cells using a single genetic element. Blood. 2003;102:4369.CrossRefPubMed Mulloy JC, Cammenga J, Berguido FJ, Wu K, Zhou P, Comenzo RL, et al. Maintaining the self-renewal and differentiation potential of human CD34+ hematopoietic cells using a single genetic element. Blood. 2003;102:4369.CrossRefPubMed
35.
go back to reference Heidenreich O, Riehle H, Hadwiger P, John M, Heil G, Vornlocher H, et al. AML1/MTG8 oncogene suppression by small interfering RNAs supports myeloid differentiation of t (8;21)-positive leukemic cells. Gene Expr. 2003;101:3157–63. Heidenreich O, Riehle H, Hadwiger P, John M, Heil G, Vornlocher H, et al. AML1/MTG8 oncogene suppression by small interfering RNAs supports myeloid differentiation of t (8;21)-positive leukemic cells. Gene Expr. 2003;101:3157–63.
36.
go back to reference Martinez N, Drescher B, Riehle H, Cullmann C, Vornlocher H-P, Ganser A, et al. The oncogenic fusion protein RUNX1-CBFA2T1 supports proliferation and inhibits senescence in t(8;21)-positive leukaemic cells. BMC Cancer. 2004;4:44.CrossRefPubMedPubMedCentral Martinez N, Drescher B, Riehle H, Cullmann C, Vornlocher H-P, Ganser A, et al. The oncogenic fusion protein RUNX1-CBFA2T1 supports proliferation and inhibits senescence in t(8;21)-positive leukaemic cells. BMC Cancer. 2004;4:44.CrossRefPubMedPubMedCentral
37.
go back to reference Martinez Soria N, Tussiwand R, Ziegler P, Manz MG, Heidenreich O. Transient depletion of RUNX1/RUNX1T1 by RNA interference delays tumour formation in vivo. Leukemia. 2009;23:188–90.CrossRefPubMed Martinez Soria N, Tussiwand R, Ziegler P, Manz MG, Heidenreich O. Transient depletion of RUNX1/RUNX1T1 by RNA interference delays tumour formation in vivo. Leukemia. 2009;23:188–90.CrossRefPubMed
38.
go back to reference Alfayez M, Vishnubalaji R, Alajez NM. Runt-related transcription factor 1 (runx1t1) suppresses colorectal cancer cells through regulation of cell proliferation and chemotherapeutic drug resistance. Anticancer Res. 2016;36:5257–63.CrossRefPubMed Alfayez M, Vishnubalaji R, Alajez NM. Runt-related transcription factor 1 (runx1t1) suppresses colorectal cancer cells through regulation of cell proliferation and chemotherapeutic drug resistance. Anticancer Res. 2016;36:5257–63.CrossRefPubMed
39.
go back to reference Yeh KT, Chen TH, Yang HW, Chou JL, Chen LY, Yeh CM, et al. Aberrant TGFβ/SMAD4 signaling contributes to epigenetic silencing of a putative tumor suppressor, RunX1T1 in ovarian cancer. Epigenetics. 2011;6:727–39.CrossRefPubMedPubMedCentral Yeh KT, Chen TH, Yang HW, Chou JL, Chen LY, Yeh CM, et al. Aberrant TGFβ/SMAD4 signaling contributes to epigenetic silencing of a putative tumor suppressor, RunX1T1 in ovarian cancer. Epigenetics. 2011;6:727–39.CrossRefPubMedPubMedCentral
Metadata
Title
Integrated genomic characterization of cancer genes in glioma
Publication date
01-12-2017
Published in
Cancer Cell International / Issue 1/2017
Electronic ISSN: 1475-2867
DOI
https://doi.org/10.1186/s12935-017-0458-y

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