Literature DB >> 22274917

Identification of a 7-gene signature that predicts relapse and survival for early stage patients with cervical carcinoma.

Long Huang1, Min Zheng, Qing-Ming Zhou, Mei-Yin Zhang, Yan-Hong Yu, Jing-Ping Yun, Hui-Yun Wang.   

Abstract

There is no gene signature for predicting relapse and survival of cervical cancer with early stage currently. In this study, we investigate whether gene expression profiling of cervical cancer could be used to predict the prognosis of patient. A series of 100 primary cervical cancer patients who underwent radical hysterectomy between January 2001 and October 2006 were analyzed for gene expression profiles by using a custom oligonucleotide microarray containing probes for 1440 human tumor-related gene transcripts. Supervised analysis of gene expression data identified 19 genes that exhibited differential expression between cervical cancer and normal cervix. Then, all 100 patients were divided into the training (n=50) and testing sets (n=50). Using Cox regression and risk-score analysis, we identified a 7-gene (UBL3, FGF3, BMI1, PDGFRA, PTPRF, RFC4, and NOL7) signature for predicting relapse of patient in the training set. The 7-gene signature was validated by the testing set (sensitivity, 84.6%; specificity, 91.9%; positive predictive value, 78.6%; negative predictive value, 94.4%). Patients with high-risk 7-gene signature had poor relapse-free survivals (RFS) than patients with low-risk 7-gene signature in both training set (P=0.026) and testing set (P=0.042). Multivariate analysis showed that the FIGO stage and 7-gene signature are independent prognostic factors associated with RFS of cervical cancer patients. The 7-gene signature can predict cancer recurrence and survival of cervical cancer patients. This may have prognostic or therapeutic implications for the future management of cervical cancer patients.

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Year:  2012        PMID: 22274917     DOI: 10.1007/s12032-012-0166-3

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.064


  28 in total

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4.  Gene expression pattern associated with radiotherapy sensitivity in cervical cancer.

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Journal:  Cancer J       Date:  2006 May-Jun       Impact factor: 3.360

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  16 in total

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Authors:  Tanmayi P Mankame; Mark W Lingen
Journal:  Neoplasia       Date:  2012-12       Impact factor: 5.715

3.  Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer.

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Review 4.  Receptor-type protein tyrosine phosphatases in cancer.

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Journal:  Oncotarget       Date:  2017-11-25

7.  GeneExpressScore Signature: a robust prognostic and predictive classifier in gastric cancer.

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8.  Multi-Scale Genomic, Transcriptomic and Proteomic Analysis of Colorectal Cancer Cell Lines to Identify Novel Biomarkers.

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10.  Potential new biomarkers for squamous carcinoma of the uterine cervix.

Authors:  Peter A van Dam; Christian Rolfo; Rossana Ruiz; Patrick Pauwels; Christophe Van Berckelaer; Xuan Bich Trinh; Jose Ferri Gandia; Johannes P Bogers; Steven Van Laere
Journal:  ESMO Open       Date:  2018-06-28
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