Profile

Education:1999 Anhui Agriculture University, MS2003 Zhejiang University, Ph.DExperience:2003-2004 Creighton University, Postdoctoral Researcher2004-2007 Washington University in St Louis, Postdoctoral Researcher2007-2008 Washington University in St Louis, Senior Scientist 2008-2010 Washington University in St Louis, Research Assistant Professor2010-2014 Medical College of Wisconsin, Tenure-tracked Assistant ProfessorResearch Interest:Dr. Yan Lu’s laboratory is focused on understanding the molecular mechanisms underlying gynecologic cancer and developing analysis pipelines for high throughput genomics and epigenomics data. Both experimental and computational approaches are used in combination to identify and model gene functions in both human patients and animal models. The ultimate goal of our projects is to discovery new diagnostic and prognostic biomarkers and therapeutic targets for gynecologic cancers. 1. CREBBP mutations as a novel prognosis biomarker for ovarian cancer relapse. Ovarian cancer is the fifth-leading cause of cancer death among women in the world. Most deaths (~70%) are of patients presenting with advanced-stage, high-grade serous ovarian cancer (HGS-OvCa). The 5-year survival rate of HGS-OvCa is only 31% and novel approaches are needed to identify new therapeutic targets. Recently, my lab identified CREBBP/CBP as a novel candidate driver gene that is significantly mutated in HGS-OvCa. CREBBP encodes the transcriptional coactivator and histone acetyltransferase CREB-binding protein. We further discovered a unique molecular subtype of HGS-OvCA characterized with somatically acquired mutations or deletions in CREBBP that are significantly associated with increased disease recurrence and poor prognosis.  To translate our recent discovery into the clinic, one of major future research focuses is to systematically characterize somatic mutations of CREBBP in HGS-OvCa and to determine the mechanisms by which CREBBP contributes to relapse in HGS-OvCa. Our long-term goal is to understand how CREBBP and its downstream effectors can be used as prognostic biomarkers and therapeutic targets, with the ultimate goal to improve outcomes of women with HGS-OvCa. 2. Identification of diagnostic and prognostic exosomal microRNAs and piwi-RNAs  in early stage ovarian cancer. Circulating microvesicles such as exosomes contain nuclei acids that may serve as biomarkers for disease diagnosis and prognosis. We will do miRNA-Seq using plasma exosomal RNAs derived from patients with early stage ovarian cancer to identify possible diagnostic and prognostic exosomal microRNAs and piwi-RNAs. Plasma exosomal miRNAs and piwi-RNAs may provide an easily accessible resource for biomarker development in prognosis of ovarian cancer. If further validated, the exosome-based miRNA signature may help physician more effectively treat cancer patients.3.  Developing analysis pipelines for high throughput genomics and epigenomics data.Introduction of new technologies often leads to breakthrough of scientific discoveries. Recently, the most exciting novel technology in molecular and genomic biology is the next generation sequencing (NGS). To fully utilize this in our research,  a set of protocols and software tools that are specific for the NGS technology have been developed in my laboratory, including RNA-Seq, miRNA-Seq, Methy-Seq, Chip-Seq and capture sequencing. Currently, we are applying these tools to TCGA sequencing data and the sequencing data generated by ourselves. We will improve these tools, especially for piwi-RNA analysis of miRNA-Seq data and the combination analysis of Methylation and hydroxymethylation sequencing data.Technique used: Next-generation sequencing, bioinformatics, computational algorithms, cell assays, microarray, mouse models,  siRNA, small molecules in clinical trials.Key publications:Hua X, Xu H, Yang Y, Zhu J, Liu P*, Lu Y*. DrGaP: A Powerful Tool for Identifying Driver Genes and Pathways in Cancer Sequencing Studies. Am J Hum Genet. 2013 Sep 5;93(3):439-51 (co-corresponding author).Lu Y, Govindan R, Wang L, Liu P, Goodgame B, Wen W, Sezhiyan A,  Li Y, Hua X, Wang Y,  Yang P, You M. MicroRNA profiling and prediction of recurrence/relapse-free survival in stage I lung cancer. Carcinogenesis. 2012 May;33(5):1046-54.Lu Y, Liu P, James M, Vikis HG, Liu H, Wen W, et al. Genetic variants cis-regulating Xrn2 expression contribute to the risk of spontaneous lung tumor. Oncogene. 2010;29:1041-9.Lu Y, Lemon W, Liu PY, Yi Y, Morrison C, Yang P, et al. A gene expression signature predicts survival of patients with stage I non-small cell lung cancer. PLoS Med.2006;3:e467.Lu Y, Yao R, Yan Y, Wang Y, Hara Y, Lubet RA, et al. A gene expression signature that can predict green tea exposure and chemopreventive efficacy of lung cancer in mice. Cancer Res. 2006;66:1956-63.