Abstract

BackgroundMost patients with ovarian cancer are diagnosed with advanced stage disease (i.e., stage III-IV), which is associated with a poor prognosis. Differentially expressed genes (DEGs) in stage III serous ovarian carcinoma compared to normal tissue were screened by a new differential display method, the annealing control primer (ACP) system. The potential targets for markers that could be used for diagnosis and prognosis, for stage III serous ovarian cancer, were found by cluster and survival analysis.MethodsThe ACP-based reverse transcriptase polymerase chain reaction (RT PCR) technique was used to identify DEGs in patients with stage III serous ovarian carcinoma. The DEGs identified by the ACP system were confirmed by quantitative real-time PCR. Cluster analysis was performed on the basis of the expression profile produced by quantitative real-time PCR and survival analysis was carried out by the Kaplan-Meier method and Cox proportional hazards multivariate model; the results of gene expression were compared between chemo-resistant and chemo-sensitive groups.ResultsA total of 114 DEGs were identified by the ACP-based RT PCR technique among patients with stage III serous ovarian carcinoma. The DEGs associated with an apoptosis inhibitory process tended to be up-regulated clones while the DEGs associated with immune response tended to be down-regulated clones. Cluster analysis of the gene expression profile obtained by quantitative real-time PCR revealed two contrasting groups of DEGs. That is, a group of genes including: SSBP1, IFI6 DDT, IFI27, C11orf92, NFKBIA, TNXB, NEAT1 and TFG were up-regulated while another group of genes consisting of: LAMB2, XRCC6, MEF2C, RBM5, FOXP1, NUDCP2, LGALS3, TMEM185A, and C1S were down-regulated in most patients. Survival analysis revealed that the up-regulated genes such as DDAH2, RNase K and TCEAL2 might be associated with a poor prognosis. Furthermore, the prognosis of patients with chemo-resistance was predicted to be very poor when genes such as RNase K, FOXP1, LAMB2 and MRVI1 were up-regulated.ConclusionThe DEGs in patients with stage III serous ovarian cancer were successfully and reliably identified by the ACP-based RT PCR technique. The DEGs identified in this study might help predict the prognosis of patients with stage III serous ovarian cancer as well as suggest targets for the development of new treatment regimens.

Highlights

  • Most patients with ovarian cancer are diagnosed with advanced stage disease, which is associated with a poor prognosis

  • For the confirmation of differential expression of the Differentially expressed genes (DEGs), quantitative real-time polymerase chain reaction (PCR) was performed on 38 selected DEGs; the results showed good agreement with the annealing control primer (ACP) findings

  • Expressed genes (DEGs) in stage III serous ovarian cancers The patients included in this study ranged in age between 38 and 69

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Summary

Introduction

Most patients with ovarian cancer are diagnosed with advanced stage disease (i.e., stage III-IV), which is associated with a poor prognosis. The potential targets for markers that could be used for diagnosis and prognosis, for stage III serous ovarian cancer, were found by cluster and survival analysis. Ovarian cancer is a complex disease, characterized by successive accumulation of multiple molecular alterations in both the cells undergoing neoplastic transformation and host cells [1]. These anomalies disturb the example, histologically defined subtypes such as serous, endometrioid, mucinous, and low- and high-grade malignancies all have variable clinical manifestations and underlying molecular signatures [2]. Gene expression has been extensively applied to screening for the prognostic factors associated with ovarian cancer; identification of such factors would help to determine patient prognosis. Identification of a gene responsible for a specialized function during a certain biological stage can be difficult to determine because the gene might be expressed at low levels, whereas the bulk of mRNA transcripts within a cell are abundant [7]

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