Identification of interconnected markers for T-cell acute lymphoblastic leukemia.
T-cell acute lymphoblastic leukemia (T-ALL) is a complex disease, resulting from proliferation of differentially arrested immature T cells. The molecular mechanisms and the genes involved in the generation of T-ALL remain largely undefined. In this study, we propose a set of genes to differentiate i...
| Publicado en: | BioMed Research International Vol. 2013; pp. 210253 - 210254 |
|---|---|
| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
2013
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104088534&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104088534 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 2013 vid: 2013 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104088534 104088534 2012229194 NLM23956970 PMC3727179 104088534 ppf: 210253 ppct: 1 formats: fmt: @attributes: type: P tig: atl: Identification of interconnected markers for T-cell acute lymphoblastic leukemia. aug: au: Guven Maiorov, Emine Keskin, Ozlem Hatirnaz Ng, Ozden Ozbek, Ugur Gursoy, Attila affil: Center for Computational Biology and Bioinformatics and College of Engineering, Koç University, Rumelifeneri Yolu, Sariyer, 34450 Istanbul, Turkey. sug: subj: Proteins Metabolism Leukemia, Lymphocytic, Acute Metabolic Networks and Pathways RNA Genes Human Microarray Analysis Polymorphism, Genetic Leukemia, Lymphocytic, Acute Pathology Tumor Markers, Biological ab: T-cell acute lymphoblastic leukemia (T-ALL) is a complex disease, resulting from proliferation of differentially arrested immature T cells. The molecular mechanisms and the genes involved in the generation of T-ALL remain largely undefined. In this study, we propose a set of genes to differentiate individuals with T-ALL from the nonleukemia/healthy ones and genes that are not differential themselves but interconnected with highly differentially expressed ones. We provide new suggestions for pathways involved in the cause of T-ALL and show that network-based classification techniques produce fewer genes with more meaningful and successful results than expression-based approaches. We have identified 19 significant subnetworks, containing 102 genes. The classification/prediction accuracies of subnetworks are considerably high, as high as 98%. Subnetworks contain 6 nondifferentially expressed genes, which could potentially participate in pathogenesis of T-ALL. Although these genes are not differential, they may serve as biomarkers if their loss/gain of function contributes to generation of T-ALL via SNPs. We conclude that transcription factors, zinc-ion-binding proteins, and tyrosine kinases are the important protein families to trigger T-ALL. These potential diseasecausing genes in our subnetworks may serve as biomarkers, alternative to the traditional ones used for the diagnosis of T-ALL, and help understand the pathogenesis of the disease. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|