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Xiaole (Shirley) Liu, PhD
Professor, Statistics, Biostatistics and Computational Biology,
Harvard Medical School
Director, Center of Functional Cancer Epigenetics
Dana-Farber Cancer Institute
- Seeking to improve response to immunotherapy by discovering new biomarkers and therapeutic targets.
- A computational model is employed to identify potential targeted therapies for testing in laboratory models of triple negative breast cancer.
- These studies may uncover new strategies that can improve response to these therapies and identify biomarkers that can select the patients most likely to respond.
Triple negative breast cancer is the most likely breast cancer subtype to respond to current immunotherapies, but the response rate remains very low. Dr. Liu is conducting studies to both identify patients most likely to benefit from these therapies as well as pursuing combination approaches to improve response to immunotherapy in patients with triple negative breast cancer.
Full Research Summary
Immunotherapy is emerging as an exciting new treatment in several cancers including some triple negative breast cancers (TNBC), but most of these patients do not respond. Robust biomarkers to predict response to immunotherapy are urgently needed.
Dr. Liu's team has developed a computational model of tumor immune evasion, called "TIDE" (Tumor Immune Dysfunction and Exclusion), which measures the immunogenicity of tumors—meaning how well they will respond to immunotherapy—and has been able to predict response to immunotherapy in laboratory studies. They previously identified tumor-promoting genes as potential targets to improve response to immunotherapy.
This year, they will experimentally validate this biomarker and novel regulators to improve immunotherapy response. They will continue their efforts in advancing a novel combination therapy in TNBC and development of sophisticated computational models of tumor interactions.
X. Shirley Liu received PhD in Biomedical Informatics and PhD minor in Computer Science from Stanford University in 2002. She is now Professor of Statistics, Biostatistics and Computational Biology at Harvard University, Director of the Center of Functional Cancer Epigenetics at Dana-Farber Cancer Institute, and Visiting Professor of Bioinformatics at Tongji Univ.
Her research focuses on algorithm development and integrative modeling of high throughput genomic data to understand the specificity and function of regulator genes in tumor development, progression, drug response and resistance. She is especially interested in genomics and bioinformatics approaches in cancer epigenetics, cancer immunology, and CRISPR screens for translational cancer research.
Her lab developed widely used analysis algorithm for transcription factor motif discovery, ChIP-chip/seq, CRISPR screen, and immune repertoire data analysis. Her computational modeling helped the understanding of ER, AR, FoxA1, XBP1, EGIN2, JARID1B regulation as well as BET bromodomain inhibitor, gamma secretase inhibitor, and CDK4/6 inhibitor function in breast cancers.
Dr. Liu has an H-index of 73 according to Google Scholar statistics and has published over 50 papers in Nature, Science or Cell series journals. She is the recipient of the Sloan Research Fellowship, the Richard E. Weitzman Outstanding Early Career Investigator Award from the Endocrine Society, the Claire W. and Richard P. Morse Research Award, Yangtze River Scholar and 1000 Talent Scholar in China, and the Breast Cancer Research Foundation Investigator. Since becoming a faculty in 2003, she has successfully mentored fourteen trainees to start tenure track faculty positions.