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Novel prognostic genes of diffuse large B-cell lymphoma revealed by survival analysis of gene expression data.

ABSTRACT: OBJECTIVE:This study aimed to identify prognostic genes for diffuse large B-cell lymphoma (DLBCL), using bioinformatic methods. METHODS:Five gene expression data sets were downloaded from the Gene Expression Omnibus database. Significance analysis of microarrays algorithm was used to identify differentially expressed genes (DEGs) from two data sets. Functional enrichment analysis was performed for the DEGs with the Database for Annotation, Visualization and Integration Discovery (DAVID). Survival analysis was performed with the Kaplan-Meier method using function survfit from package survival of R for the other three data sets. Cox univariate regression analysis was used to further screen out prognostic genes. RESULTS:Thirty-one common DEGs were identified in the two data sets, mainly enriched in the regulation of lymphocyte activation, immune response, and interleukin-mediated signaling pathway. Combined with 47 DLBCL-related genes acquired by literature retrieval, a total of 78 potential prognostic genes were obtained. Cases from the other three data sets were used in hierarchical clustering, and the 78 genes could cluster them into several subtypes with significant differences in survival curves. Cox univariate regression analysis revealed 45, 33, and eleven prognostic genes in the three data sets, respectively. Five common prognostic genes were revealed, including LCP2, TNFRSF9, FUT8, IRF4, and TLE1, among which LCP2, FUT8, and TLE1 were novel prognostic genes. CONCLUSION:Five prognostic genes of DLBCL were identified in this study. They could not only be used for molecular subtyping of DLBCL but also be potential targets for treatment.

SUBMITTER: Li C

PROVIDER: S-EPMC4655963 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Novel prognostic genes of diffuse large B-cell lymphoma revealed by survival analysis of gene expression data.

Li Chenglong C Zhu Biao B Chen Jiao J Huang Xiaobing X

OncoTargets and therapy 20151118

<h4>Objective</h4>This study aimed to identify prognostic genes for diffuse large B-cell lymphoma (DLBCL), using bioinformatic methods.<h4>Methods</h4>Five gene expression data sets were downloaded from the Gene Expression Omnibus database. Significance analysis of microarrays algorithm was used to identify differentially expressed genes (DEGs) from two data sets. Functional enrichment analysis was performed for the DEGs with the Database for Annotation, Visualization and Integration Discovery ( ...[more]

PMID: 26604798

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Project description:BackgroundWith the improvement of clinical treatment outcomes in diffuse large B cell lymphoma (DLBCL), the high rate of relapse in DLBCL patients is still an established barrier, as the therapeutic strategy selection based on potential targets remains unsatisfactory. Therefore, there is an urgent need in further exploration of prognostic biomarkers so as to improve the prognosis of DLBCL.MethodsThe univariable and multivariable Cox regression models were employed to screen out gene signatures for DLBCL overall survival (OS) prediction. The differential expression analysis was used to identify representative genes in high-risk and low-risk groups, respectively, where student t test and fold change were implemented. The functional difference between the high-risk and low-risk groups was identified by the gene set enrichment analysis.ResultsWe conducted a systematic data analysis to screen the candidate genes significantly associated with OS of DLBCL in three NCBI Gene Expression Omnibus (GEO) datasets. To construct a prognostic model, five genes (CEBPA, CYP27A1, LST1, MREG, and TARP) were then screened and tested using the multivariable Cox model and the stepwise regression method. Kaplan-Meier curve confirmed the good predictive performance of this five-gene Cox model. Thereafter, the prognostic model and the expression levels of the five genes were validated by means of an independent dataset. High expression levels of these five genes were significantly associated with favorable prognosis in DLBCL, both in training and validation datasets. Additionally, further analysis revealed the independent value and superiority of this prognostic model in risk prediction. Functional enrichment analysis revealed some vital pathways responsible for unfavorable outcome and potential therapeutic targets in DLBCL.ConclusionWe developed a five-gene Cox model for the clinical outcome prediction of DLBCL patients. Meanwhile, potential drug selection using this model can help clinicians to improve the clinical practice for the benefit of patients.

Project description:AimsYin Yang 1 (YY1) is a multifunctional transcription factor that plays an important role in tumour development and progression, while its clinical significance in diffuse large B-cell lymphoma (DLBCL) remains largely unexplored. This study aimed to investigate the expression and clinical implications of YY1 in DLBCL.MethodsYY1 expression in 198 cases of DLBCL was determined using immunohistochemistry. The correlation between YY1 expression and clinicopathological parameters as well as the overall survival (OS) and progression-free survival (PFS) of patients was analyzed.ResultsYY1 protein expression was observed in 121 out of 198 (61.1 %) DLBCL cases. YY1 expression was significantly more frequent in cases of the GCB subgroup than in the non-GCB subgroup (P = 0.005). YY1 was positively correlated with the expression of MUM1, BCL6, pAKT and MYC/BCL2 but was negatively associated with the expression of CXCR4. No significant relationships were identified between YY1 and clinical characteristics, including age, sex, stage, localization, and B symptoms. Univariate analysis showed that the OS (P = 0.003) and PFS (P = 0.005) of patients in the YY1-negative group were significantly worse than those in the YY1-positive group. Multivariate analysis indicated that negative YY1 was a risk factor for inferior OS (P < 0.001) and PFS (P = 0.017) independent of the international prognostic index (IPI) score, treatment and Ann Arbor stage. Furthermore, YY1 is more powerful for stratifying DLBCL patients into different risk groups when combined with MYC/BCL2 double-expression (DE) status.ConclusionsYY1 was frequently expressed in DLBCL, especially in those of GCB phenotype and with MYC/BCL2-DE. As an independent prognostic factor, YY1 expression could predict a favourable outcome in DLBCL. In addition, a complex regulatory mechanism might be involved in the interactions between YY1 and MYC, pAKT as well as CXCR4 in DLBCL, which warrants further investigation.

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Novel prognostic genes of diffuse large B-cell lymphoma revealed by survival analysis of gene expression data.

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Novel prognostic genes of diffuse large B-cell lymphoma revealed by survival analysis of gene expression data.

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