Home > Events > 2012 Seminars & Colloquia > XIAOLE SHIRLEY LIU - Harvard School of Public Health

XIAOLE SHIRLEY LIU - Harvard School of Public Health

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” AN INTEGRATED APPROACH TO DECIPHER LARGE NON-CODING RNA (lncRNA) FUNCTION IN CANCER ”
When
11 October 2012 from 4:00 PM to 5:00 PM
Where
111 Tyson Bldg.
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Recent genome-wide studies revealed that the human genome encodes thousands of large non-coding RNAs (lncRNAs) with little protein-coding capacity. Growing evidence suggests that many lncRNAs may have important functions in cancer and lncRNAs are potentially a new class of therapeutic targets for treating cancer. In contrast to the fast pace of cataloguing lncRNAs in the human genome, the function of the vast majority of lncRNAs in cancer remain unknown. Advances in genomic technologies provide unparalleled opportunities to characterize lncRNA function in cancer. However, analysis and integration of different types of genomic datasets to generate testable hypotheses regarding lncRNA function is challenging, and systematic approaches to characterize lncRNA function in cancer are lacking. To address this challenge, we developed an integrative computational strategy for predicting lncRNAs that may be functionally important for tumorigenesis or tumor suppression via analysis of lncRNA expression profiles, clinical information and somatic genomic alteration profiles of tumor samples. We applied this approach to predict lncRNAs that are important for prostate tumorigenesis and experimentally validate our computational predictions. We further extended this analysis to other cancer types including glioblastoma multiforme, ovarian cancer and squamous cell lung cancer, and discovered the lncRNAs that exhibit unique expression signature across clinically important molecular subtypes or whose expressions are predictive of patient survival. Our results indicate that our integrated approach enables the systematic discovery of lncRNAs that are functionally important in cancer and enables identifying the lncRNAs whose expression can serve as prognostic biomarkers in cancer.

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