Scientific Program

Conference Series Ltd invites all the participants across the globe to attend Global Summit on Oncology & Cancer Osaka, Japan.

Day 2 :

Keynote Forum

Lei Huo

University of Texas, USA

Keynote: MicroRNA expression in advanced breast cancer
OMICS International Global Cancer 2017 International Conference Keynote Speaker Lei Huo photo
Biography:

Lei Huo is a practicing Breast Pathologist in The University of Texas MD Anderson Cancer Center. She is actively involved in clinical and translational research in the field of Breast Cancer. Her research interests include molecular and immunohistochemical markers in tumorigenesis, diagnosis and treatment of breast cancer, among others.

Abstract:

Statement of the Problem: Although early stage breast cancer has a high cure rate with current treatment modalities, advanced breast cancer remains a life threatening disease. There is an urgent need for new therapeutic targets. Inflammatory breast cancer, comprising 1-5% of newly diagnosed breast cancer in the United States, is the most aggressive form of breast cancer, characterized by clinical hallmarks of diffuse erythema and edema and rapid progression from the onset. Recent advances have implicated the role of microRNAs as oncogenes or tumor suppressor genes in tumorigenesis, metastasis and response to treatment in various cancer types including breast cancer. The aim of our ongoing study is to identify microRNA molecules that are regulated in advanced breast cancer, including inflammatory breast cancer. Methodology & Theoretical Orientation: MicroRNA expression profiles of human advanced breast cancer including inflammatory breast cancer were compared to normal breast tissue using a previously validated microRNA microarray assay. The results were subsequently validated by quantitative reverse transcription PCR and in situ hybridization. Findings: There was distinct segregation between tumor and normal breast tissue in microRNA expression profiles. In contrast, between inflammatory breast cancer and non-inflammatory breast cancer, distinct clustering was not readily identified in the microarray analysis. However, several microRNAs were differentially expressed in inflammatory breast cancer. We have validated some molecules by quantitative PCR and in situ hybridization. For example, miR-205 expression was decreased not only in tumor compared with normal breast tissue, but also in inflammatory breast cancer compared with non-inflammatory breast cancer. Lower expression of miR-205 was associated with worse distant metastasis-free survival and overall survival in our cohort. Conclusion & Significance: MicroRNAs may serve as therapeutic targets in advanced breast cancer.

Keynote Forum

Jiangwen Zhang

University of Hong Kong, Hong Kong

Keynote: miRNA Cancer MAP: A web server prioritizing tumor associated miRNA
OMICS International Global Cancer 2017 International Conference Keynote Speaker  Jiangwen Zhang photo
Biography:

Jiangwen Zhang has completed his graduation from Johns Hopkins University with PhD. He has worked at Harvard University Genome Center as Senior System Biologist for years before joining University of Hong Kong in 2013. His lab has broad interest in genetic and epigenetic regulation in development and diseases. Currently, his lab is focusing on epigenetic regulation of tumorigenesis. His lab employs high throughput ‘omics’ assays and large scale computation to dissect the gene regulatory network and signaling pathways involved in oncogenesis.

Abstract:

Recent studies have revealed the critical role of miRNAs in oncogenesis and great potential of miRNAs serving as diagnostic and prognostic biomarkers. NGS technologies have led to an exponential growth of miRNAs-related data. The mounting body of miRNA NGS data generated requires highly sophisticated tools for data analysis and integration. Currently, there are many tools available for miRNA target identification and miRNA function prediction. An integrated platform incorporating multiple data sources, methods and reported evidences would improve the accuracy and efficiency of the data analysis. Here we present our current work in this direction, miRNACancerMap, a web server inferring miRNA regulatory network in cancers. We collected miRNA-target information from multiple sources such as validated databases and sequenced-based prediction algorithms. Using text mining method, we discovered thousands of miRNA regulations in cancers from PUBMED. We have found 4,879 papers which reported hundreds of microRNAs related to cancer initiation and progression. We have also conducted data mining of miRNA NGS data from many cancer studies, e.g. genome-wide expression profiling of miRNAs and its mRNA targets. Integration of sequence-based miRNA-target interactions and expression-based miRNA-target correlations enable us to distinguish the activated regulations in cancers. And the annotation of cancer-specific evidences and functional analysis facilitate a better interpretation of the miRNA effects on cancer of the miRNA regulatory. Finally, we build up a userfriendly web server, miRNACancerMap, accessible for users to analyze the mRNAs/miRNAs of their interest and their own expression profile. And the results are presented in a comprehensive knowledge map via interactive visualization.