Transcriptomics,Genomics

Dataset Information

45

A MicroRNA Expression Signature For Cervical Cancer Prognosis


ABSTRACT: In this study, we have identified a microRNA-based signature for the prediction of cervical cancer survival. MicroRNAs (miRNAs) are a newly identified family of small non-coding RNAs that are extensively involved in human cancers. Using our recently established PCR-based miRNA assays, we have analyzed 102 cervical cancers and identified two miRNAs (miR-200a and miR-9) that are likely to predict patient survival. A logistic regression model was developed based on these two miRNAs and the prognostic value of the model was subsequently validated with 42 independent cervical cancers. Furthermore, functional studies were performed to characterize the effect of miRNAs in cervical cancer cells. Our results suggest that both miR-200a and miR-9 could play important regulatory roles in cervical cancer control. In particular, miR-200a is likely to affect the metastatic potential of cervical cancer cells by simultaneously suppressing the expression of multiple genes that are important to cell motility. Overall design: There are five arrays included in this experiment, including one negative control, one mock control, and three arrays to profile for the effects of miRNA overexpression in HeLa cells. Two miRNAs, miR-200a and miR-9 were analyzed.

INSTRUMENT(S): Illumina HumanHT-12 V3.0 expression beadchip

SUBMITTER: Xiaowei Wang 

PROVIDER: GSE18545 | GEO | 2010-02-15

SECONDARY ACCESSION(S): PRJNA121353

REPOSITORIES: GEO

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Publications

A microRNA expression signature for cervical cancer prognosis.

Hu Xiaoxia X   Schwarz Julie K JK   Lewis James S JS   Huettner Phyllis C PC   Rader Janet S JS   Deasy Joseph O JO   Grigsby Perry W PW   Wang Xiaowei X  

Cancer research 20100202 4


Invasive cervical cancer is a leading cause of cancer death in women worldwide, resulting in about 300,000 deaths each year. The clinical outcomes of cervical cancer vary significantly and are difficult to predict. Thus, a method to reliably predict disease outcome would be important for individualized therapy by identifying patients with high risk of treatment failures before therapy. In this study, we have identified a microRNA (miRNA)-based signature for the prediction of cervical cancer surv  ...[more]

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