Dr. Shen’s research interest lies in developing statistical and computational genomics approaches and their applications to translational cancer research. She developed iCluster, a statistical data integration method for defining molecular subtypes of cancer and associated biomarkers across multiple “omic” data types simultaneously characterizing genomic, epigenomic, transcriptomic, and proteomic aberrations in a tumor. Her method has been widely used for integrative cancer subtype analysis in large-scale cancer genome consortium studies including the NCI/NHGRI Cancer Genome Atlas (TCGA) and the Canada-UK Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). Working with thoracic oncologists at MSKCC, she applied statistical machine learning approaches for characterizing a patient’s prognostic risk based on the somatic mutational profile of the tumor, and explored the notion of a genomic staging of lung adenocarcinomas (stage IV) in real-world oncology datasets. She is also interested in tumor clonal heterogeneity analysis. Together with Dr. Venkatraman Seshan, she developed FACETS, an allele-specific copy number analysis method that can be used to explore copy number aberrations and clonal heterogeneity within a tumor using whole-genome, whole-exome and targeted capture sequencing data. Her recent research interest also includes a novel investigation of somatic variant richness using statistical methodologies developed in ecology and computational linguistics, a joint work with Dr. Colin Begg and Dr. Saptarshi Chakraborty. This project uses sophisticated statistical tools to extract information from rare variants in existing databases with a view to identifying the site of origin for cancers of unknown primaries and cancers detected from circulating cell-free DNA in the blood.
Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.
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Ronglai Shen discloses the following relationships and financial interests:
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