Identifying disease genes is very important not only for better understanding of gene function and biological process but also for human medical improvement. Many computational methods have been proposed based on the similarity between all known disease genes (seed genes) and candidate genes in the entire gene interaction network. Under the hypothesis that potential disease-related genes should be near the seed genes in the network and only the seed genes that are located in the same module with the candidate genes will contribute to disease genes prediction, three modularized candidate disease gene prioritization algorithms (MCDGPAs) are proposed to identify disease-related genes. MCDGPA is divided into three steps: module partition, genes prioritization in each disease-associated module, and rank fusion for the global ranking. When applied to the prostate cancer and breast cancer network, MCDGPA significantly improves previous algorithms in terms of cross-validation and disease-related genes prediction. In addition, the improvement is robust to the selection of gene prioritization methods when implementing prioritization in each disease-associated module and module partition algorithms when implementing network partition. In this sense MCDGPA is a general framework that allows integrating many previous gene prioritization methods and improving predictive accuracy.
Get full access to this article
View all access options for this article.
References
1.
AdieE.A., AdamsR.R., EvansK.L., PorteousD.J., PickardB.S.2005. Speeding disease gene discovery by sequence based candidate prioritization. BMC Bioinformatics, 6:55.
2.
AdieE.A., AdamsR.R., EvansK.L., PorteousD.J., PickardB.S.2006. SUSPECTS: enabling fast and effective prioritization of positional candidates. Bioinformatics, 22:773–774.
3.
AertsS., LambrechtsD., MaityS., Van LooP., CoessensB., SmetF.F.et al.2006. Gene prioritization through genomic data fusion. Nat Biotechnol, 24:537–544.
4.
AgarwalR.2000. Cell signaling and regulators of cell cycle as molecular targets for prostate cancer prevention by dietary agents. Biochem Pharmacol, 60:1051–1059.
5.
AlaU., PiroR.M., GrassiE., DamascoC., SilengoL., OtiM.et al.2008. Prediction of human disease genes by human–mouse conserved co-expression analysis. PLoS Comput Biol, 3:e1000043.
6.
AngeleS., FalconerA., EdwardsS.M., DorkT., BremerM., MoullanN.et al.2004. ATM polymorphisms as risk factors for prostate cancer development. Br J Cancer, 91:783–787.
7.
ArasonA., BarkardottirR.B., EgilssonV. 1993. Linkage analysis of chromosome 17q markers and breast–ovarian cancer in icelandic families, and possible relationship to prostatic cancer. Am J Hum Genet, 52:711–717.
BernsE.M., de KleinA., van PuttenW.L., van StaverenI.L., BootsmaA., KlijnJ.G.et al.1995. Association between rb-1 gene alterations and factors of favourable prognosis in human breast cancer, without effect on survival. Int J Cancer, 2:140–145.
10.
BotsteinD., RischN.2003. Discovering genotypes underlying human phenotypes: past successes for mendelian disease, future approaches for complex diseases. Nat Genet, 33:228–237.
11.
BotsteinD., WhiteR.L., SkolnickR., DavisR.D.1980. Constructing of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet, 32:314–331.
12.
BourasT., SoutheyM.C., VenterD.J.2001. Overexpression of the steroid receptor coactivator AIB1 in breast cancer correlates with the absence of estrogen and progesterone receptors and positivity for p53 and HER2/neu. Cancer Res, 3:930–937.
13.
BrunnerH.G., van DrielM.A.2004. From syndrome families to functional genomics. Nat Rev Genet, 5:545–551.
14.
BubendorfL., KononenJ., KoivistoP., SchramlP., MochH., GasserT.C.et al.1999. Survey of gene amplifications during prostate cancer progression by high-throughput fluorescence in situ hybridization on tissue microarrays. Cancer Res, 59:803–806.
15.
BuschmannT., MinamotoT., WagleN., FuchsS.Y., AdlerV., MaiM.et al.2000. Analysis of JNK, Mdm2 and p14ARF contribution to the regulation of mutant p53 stability. J Mol Biol, 295:1009–1021.
16.
ChangB.L., ZhengS.L., IsaacsS.D., WileyK.E., TurnerA., LiG.et al.2004. A polymorphism in the CDKN1B gene is associated with increased risk of hereditary prostate cancer. Cancer Res, 64:1997–1999.
17.
ChenX.F., ThakkarH., TyanF., GimS., RobinsonH., LeeCet al.2001. Constitutively active Akt is an important regulator of TRAIL sensitivity in prostate cancer. Oncogene, 42:6073–6083.
18.
ChenJ., AronowB.J., JeggaA.G.2009. Disease candidate gene identification and prioritization using protein interaction networks. BMC bioinformatics, 10:73.
19.
ChienJ., NaritaK., RattanR., GiriS., ShridharR., StaubJ.et al.2008. A role for candidate tumor-suppressor gene TCEAL7 in the regulation of c-Myc activity, cyclinD1 levels and cellular transformation. Oncogene, 27:7223–7234.
20.
ChinK., SolorzanoC.S.D., KnowlesD., JonesA., ChouW., RodriguezE.G.et al.2004. In situ analyses of genome instability in breast cancer. Nat Genet, 36:984–988.
21.
CoxD.G, HankinsonS.E., HunterD.J.2006. Polymorphisms of the AURKA (STK15/aurora kinase) gene and breast cancer risk (United States)Cancer Causes Control, 17:81–83.
22.
DamarajuS., MurrayD., DufourJ., CarandangD., MyrehaugS., FalloneG.et al.2006. Association of DNA repair and steroid metabolism gene polymorphisms with clinical late toxicity in patients treated with conformal radiotherapy for prostate cancer. Clin Cancer Res, 15:2545–2554.
23.
DeMarzoA.M., NelsonW.G., IsaccsW.B., EpsteinJ.I.2003. Pathological and molecular aspects of prostate cancer. Lancet, 9361:955–996.
24.
Di CristofanoA., De AcetisM., KoffA., Cordon-CardoC., PandolfiP.P.2001. Pten and p27KIP1 cooperate in prostate cancer tumor suppression in the mouse. Nat Genet, 27:222–224.
25.
DingS.L., YuJ.C., ChenS.T., HsuG.C., KuoY.H., LinY.H.et al.2009. Genetic variants of BLM interact with RAD51 to increase breast cancer susceptibility. Carcinogenesis, 30:43–49.
26.
DitemannS., GeorgiiE., AntonovA., TsudaK., MewesH.2009. The DICS repository:module-assisted analysis of diseaserelated gene lists. Bioinformatics, 6:830–831.
27.
Ellwood-YenK., GraeberT.G., WongvipatJ., Iruela-ArispeM.L., ZhangJ.F., MatusikR.et al.2003. Myc-driven murine prostate cancer shares molecular features with human prostate tumors. Cancer Cell, 3:223–238.
28.
EnrightA.J., Van-DongenS., OuzounisC.A.2002. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res, 30:1575–1584.
29.
FortunatoS., CastellanoC.2007. Community structure in graphsEprint arXiv:0712.2716.
30.
FrankeL., van BakelH., FokkensL., De JongE.D., Egmont-PetersenM., WijmengaC.2006. Reconstruction of a functional human gene network, with an application for prioritizing positional candidate genes. Am J Hum Genet, 78:1011–1025.
31.
GandhiT.K., ZhongJ, MathivananS., KarthickL., ChandrikaK.N., MohanS.S.et al.2006. Analysis of the human protein interactome and comparison with yeast, worm and fly interaction datasets. Nat Genet, 38:285–293.
32.
GaoS., ZacharekA., SalkowskiA., GrignonD.J., SakrW., PorterA.T.et al.1995. Loss of heterozygosity of the BRCA1 and other loci on chromosome 17q in human prostate cance. Cancer Res, 55:1002–1005.
33.
GaoX., GrignonD.J., ChbihiT., ZacharekA., ChenY.Q., SakrW.et al.1995. Elevated 12-lipoxygenase mRNA expression correlates with advanced stage and poor differentiation of human prostate cancer. Urology, 46:227–237.
HamoshA., ScottA.F., AmbergerJ.S., BocchiniC.A., McKusickV.A.2005. Online mendelian inheritance in man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res, 33:514–517.
36.
HaoF., TanM.Q., XuX.M., HanJ.H., MillerD.D., TigyiG.et al.2007. Lysophosphatidic acid induces prostate cancer pc3 cell migration via activation of lpa(1), p42 and p38alpha. Biochim Biophys Acta, 1771:883–892.
37.
HoG.Y.F., MelmanA., LiuS.M., LiM., YuH., NegassaAet al.2003. Polymorphism of the insulin gene is associated with increased prostate cancer risk. Br J Cancer, 88:263–269.
38.
HutzJ.Z., KrajaA.T., McleodH.L., ProvinceM.A.2008. CANDID: A flexible method for prioritizing candidate genes for complex human traits. Genet Epidemiol.
39.
IsaacsW., KainuT.2001. Oncogenes and tumor suppressor genes in prostate cancer. Epidemiol Rev, 32:779–790.
40.
KanehisaM., GotoS., KawashimaS., OkunoY., HattoriM.2004. The KEGG resource for deciphering the genome. Nucleic Acids Res, 23:277–280.
41.
KannM.G.2010. Advances in translational bioinformatics: computational approaches for the hunting of disease genes. Brief Bioinform, 11:96–110.
42.
KarppinenaS.M., ErkkoaH., ReinibK., PospiechcH., HeikkinenaK., RapakkoaK.et al.2006. Identification of a common polymorphism in the TopBP1 gene associated with hereditary susceptibility to breast and ovarian cancer. Eur J Cancer, 15:2647–2652.
43.
KibelA.S., SuarezB.K, BelaniJ., OhJ., WebsterR., Brophy-EbbersM.et al.2003. CDKN1A and CDKN1B polymorphisms and risk of advanced prostate carcinoma. Cancer Res, 63:2033–2036.
44.
KöhlerS., BauerS., HornD., RobinsonP.N.2008. Walking the interactome for prioritization of candidate disease genes. Am J Hum Genet, 82:949–958.
45.
KokontisJ., TakakuraK., HayN., LiaoS.1994. Increased androgen receptor activity and altered c-myc expression in prostate cancer cells after long-term androgen deprivation. Cancer Res, 54:1566–1573.
46.
KubotaY., FujinamiK., UemuraH., DobashiY., MiyamotoH., IwasakiY.et al.1995. Retinoblastoma gene mutations in primary human prostate cancer. Prostate, 27:314–320.
47.
LageK., KarlbergE.O., StorlingZ.M., OlasonP.I., PedersenA.G., RiginaO.et al.2007. A human phenome–interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol, 25:309–316.
48.
LancichinettiA., FortunatoS.2009. Community detection algorithms: a comparative analysis. Phys Rev E, 80:056117.
49.
LangstonA.A., StanfordJ., WicklundK.G., ThompsonJ.D., BlazejR.G., OstranderE.A.1996. Germ-line BRCA1 mutations in selected men with prostate cancer. Am J Hum Genet, 58:881–885.
50.
LatilA., BiècheI., PescheS., VolantA., ValèriA., FournierG.et al.1999. Loss of heterozygosity at chromosome arm 13q and RB1 status in human prostate cancer. Hum Pathol, 7:809–815.
51.
LiC.D., LarssonC., FutrealA., LancasterJ., PhelanC., AspenbladU.et al.1998. Identification of two distinct deleted regions on chromosome 13 in prostate cancer. Oncogene, 4:481–487.
52.
LiLC., ZhaoH., ShiinaH., KaneC.J., DahiyaR.2003. Pgdb: a curated and integrated database of genes related to the prostate. Nucleic Acids Res, 31:291–293.
53.
LiLC., OkinoS.T., DahiyaR.2004. DNA methylation in prostate cancer. Bionchim Biophys Acta, 6:87–102.
54.
LimJ., HaoT., ShawC., PatelA.J., SzaboG., RualJ.F.et al.2006. A protein– protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration. Cell, 125:801–814.
55.
LindaB., BuettnerR., SeigneJ., DiazJ., AhmadN., GarciaR.et al.2002. Constitutive activation of Stat3 in human prostate tumors and cell lines. Cancer Res, 62:6659–6666.
56.
MajumderP.K., SellersW.R.2005. Akt-regulated pathways in prostate cancer. Oncogene, 24:7465–7474.
57.
MatsuyamaM., YoshimuraR., MitsuhashiM., HaseT., TsuchidaK., TakemotoY.et al.2004. Expression of lipoxygenase in human prostate cancer and growth reduction by its inhibitor. Int J Oncol, 24:821–827.
58.
MikiY., SwensenJ., Shattuck-EidensD., FutrealP.A., HarshmanK., TavtigianS.et al.1994. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science, 266:66–71.
59.
MorrisonJ.L., BreitlingR., HighamD.J., GilbertD.R.2005. GeneRank: using search engine technology for the analysis of microarray experiments. BMC Bioinformatics, 6:233.
60.
MuhlbauerK.R., GroneH.J., ErnstT., GroneE., TschadaR., HergenhahnM.et al.2003. Analysis of human prostate cancers and cell lines for mutations in the TP53 and KLF6 tumour suppressor genes. Br J Cancer, 89:687–690.
61.
NesterovA., LuX.J., JohnsonM., MilleriG.J., IvashchenkoY., KraftA.S. 2001. Elevated Akt activity protects the prostate cancer cell line LNCaP from TRAIL-induced apoptosis. J Biol Chem, 14:10767–10774.
62.
Olapade-OlaopaE.O., MoscatelloD.K., MacKayE.H., HorsburghT., SandhuD.P.S, TerryT.Ret al.2000. Evidence for differential expression of a variant EGF receptor protein in human prostate cancer. Br J Cancer, 82:186–194.
63.
OsmanI., DrobnjakM., FazzariM., FerraraJ., ScherH.I., Cordon-CardoC.1999. Inactivation of the p53 pathway in prostate cancer: impact on tumor progression. Clin Cancer Res, 5:2082–2088.
64.
OtiM., BrunnerH.G.2007. The modular nature of genetic diseases. Clin Genet, 71:1–11.
OzgurA., VuT., ErkanG., RadevD.R.2008. Identifying gene–disease associations using centrality on a literature mined gene-interaction network. Bioinformatics, 24:277–285.
67.
PallaG., DerenyiI., FarkasI., VicsekT.2005. Uncovering the overlapping community structure of complex networks in nature and society. Nature, 9:814–818.
68.
PalmerD.H., HussainS.A., GanesanR., CookeP.W., WallaceD.M., YoungL.S.et al.2004. CD40 expression in prostate cancer: a potential diagnostic and therapeutic molecule. Oncol Rep, 4:679–682.
69.
PonzielliR., KatzS., Barsyte-LovejoyD., PennL.Z.2005. Cancer therapeutics: targeting the dark side of Myc. Eur J Cancer, 41:2485–2501.
70.
PujanaM.A., HanJ.D.J., StaritaL.M., StevensK.N., TewariM., AhnJ.Set al.2007. Network modeling links breast cancer susceptibility and centrosome dysfunction. Nat.Genet, 11:1338–1349.
71.
RosvallM., BergstromC.T.2008. Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci, 105:1118–1123.
72.
SabatiniD.M.2006. mTOR and cancer: insights into a complex relationship. Net Rev Cancer, 6:729–734.
73.
SarfarazS., AfaqF., AdhamiV.M., MalikA., MukhtaretH.2006. Cannabinoid receptor agonist-induced apoptosis of human prostate cancer cells lncap proceeds through sustained activation of erk1/2 leading to g1 cell cycle arrest. J Biol Chem, 281:39480–39491.
74.
SharplessN.E.2005. INK4a/ARF: a multifunctional tumor suppressor locus. J Mutat Res, 576:22–38.
75.
StarkC., BreitkreutzB.J., RegulyT., BoucherL., BreitkreutzA., TyersetM.2006. BioGRID: a general repository for interaction datasets. Nucleic Acids Res, 34:535–539.
StubbsA.P., AbelP.D., GoldingM., BhangalG., WangQ., WaxmanJ.et al.1999. Differentially expressed genes in hormone refractory prostate cancer: association with chromosomal regions involved with geneticaberrations Am. J Pathol, 5:1335–1343.
78.
TiffinN., KelsoJ.F., PowellA.R., PanH., BajicV.B., HideW.A.2005. Integration of text- and data-mining using ontologies successfully selects disease gene candidates. Nucleic Acids Res, 33:1544–1552.
79.
TrancheventL., BarriotR., YuS., Van VoorenS., Van LooP., CoessensB.et al.2008. ENDEAVOUR update: a web resource for gene prioritization in multiple species. Nucleic Acids Res, 36:377–384.
80.
TsuruokaY., TateishiY., KimJ.D., OhtaT., McnaughtJ.et al.2005. Developing a robust part-of-speech tagger for biomedical text. Proceedings of the 10th Panhellenic Conference on Informatics, Volos, GreeceLNCS 3746382–392.
81.
Van DongenS.2000. Graph clustering by flow simulation. PHD Thesis. University of Utrecht: The Netherlands.
82.
Van DrielM.A.V., BruggemanJ., VriendG., BrunnerH.G., LeunissenJ.A.M.2006. A text-mining analysis of the human phenome. Eur J Hum Genet, 14:535–542.
83.
VanunuO., MaggerO., RuppinE., ShlomiP., SharanR.2010. Associating genes and protein complexes with disease via network propagation. PLoS Comput Biol, 6:e1000641.
84.
VaraJ.A.F., CasadoE., de CastroJ., CejasP., Belda-IniestaC., Gonzalez-BaronM.2004. PI3K/Akt signaling pathway and cancer. Cancer Treat Rev, 30:193–204.
85.
WainH.M., LushM.J., DucluzeauF., KhodiyarV.K., PoveyS.2004. Genew: the human gene nomenclature database, 2004 updates. Nucleic Acids Res, 32:1257–1261.
86.
WangH., YuD., AgrawalS., ZhangR.W.2003. Experimental therapy of human prostate cancer by inhibiting mdm2 expression with novel mixed-backbone antisense oligonucleotides: in vitro and in vivo activities and mechanisms. Prostate, 54:194–205.
87.
WangL., SunF.Z., ChenT.2008. Prioritizing functional modules mediating genetic perturbations and their phenotypic effects: a global strategy. Genome Biol, 12:537–544.
88.
WangL.Z., HabuchiT., MitsumoriK., LiZ.H., KamotoT., KinoshitaH.et al.2003. Increased risk of prostate cancer associated with AA genotype of cyclin D1 gene A870G polymorphism. Int J Cancer, 103:116–120.
89.
WeiQ., LiM., FuX., TangR., NaY., JiangM.et al.2007. Global analysis of differentially expressed genes in androgen-independent prostate cancer. Prostate Cancer Prostatic Dis, 10:167–174.
90.
WoodL.D., ParsonsD.W., JonesS., LinJ., SjoblomT., LearyR.J.et al.2007. The genomic landscapes of human breast and colorectal cancers. Science, 318:1108–1113.
91.
WuG.J., SinclairC.S., PaapeJ., IngleJ.N., RocheP.C., JamesC.D.et al.2000. 17q23 amplifications in breast cancer involve the PAT1, RAD51C, PS6K, and SIGMA1B genes. Cancer Res, 60:5371–5375.
92.
WuX.B., JiangR., ZhangM.Q., LiS.2008. Network-based global inference of human disease genes. Mol Syst Biol, 4:189–199.
93.
WuX.B., LiuQ.F., JiangR.2009. Align human interactome with phenome to identify causative genes and networks underlying disease families. Bioinformatics, 25:98–104.
94.
XuW.S., NgoL., PerezG., DokmanovicM., MarksP.A.2006. Intrinsic apoptotic and thioredoxin pathways in human prostate cancer cell response to histone deacetylase inhibitor. Proc Natl Acad Sci USA, 42:15540–15545.
95.
YeeC.J., RoodiN., VerrierC.S., ParlF.F.1994. Microsatellite instability and loss of heterozygosity in breast cancer. Cancer Res, 7:1641–1644.
96.
ZhangZ., LiM., WangH., AgrawalS., ZhangR.W.2003. Antisense therapy targeting mdm2 oncogene in prostate cancer: effects on proliferation, apoptosis, multiple gene expression, and chemotherapy. Proc Natl Acad Sci USA, 100:11636–11641.
97.
ZhaoC., YasuiK., LeeC.J., KuriokaH., HosokawaY., OkaT.et al.2003. Elevated expression levels of NCOA3, TOP1, and TFAP2C in breast tumors as predictors of poor prognosis. Cancer, 1:18–23.
98.
ZiX.L., AgarwalR.1999. Silibinin decreases prostate-specific antigen with cell growth inhibition via G1 arrest, leading to differentiation of prostate carcinoma cells: implications for prostate cancer intervention. Proc Natl Acad Sci USA, 13:7490–7495.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
