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Partial Least Squares Based Gene Expression Analysis in EBV-Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders

  • Wu, Sa (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine) ;
  • Zhang, Xin (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine) ;
  • Li, Zhi-Ming (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine) ;
  • Shi, Yan-Xia (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine) ;
  • Huang, Jia-Jia (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine) ;
  • Xia, Yi (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine) ;
  • Yang, Hang (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine) ;
  • Jiang, Wen-Qi (Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine)
  • Published : 2013.11.30

Abstract

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

Keywords

Post-transplant lymphoproliferative disorder;Epstein-Barr virus;partial least squares

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