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Xiaole (Shirley) Liu, PhD
Professor of Biostatistics and Computational Biology
Department of Data Sciences
Dana-Farber Cancer Institute
Harvard T.H. Chan School of Public Health
Goal: To identify biomarkers that can be used to select patients for immunotherapy or to develop better treatment strategies.
Impact: Dr. Liu has used new technologies to identify targets that may enhance the efficacy of current treatments for patients with triple-negative breast cancer. Characterization of these targets will help to predict patient response to different drugs and provide valuable information which would be useful for early cancer diagnosis and therapy decisions.
What’s next: Her team has identified a gene that works together with immunotherapy in triple-negative breast cancer. They will utilize a method of analyzing individual cells they have developed to identify molecular markers that could predict how tumors respond to different drugs.
Of the various subtypes of breast cancer, triple-negative breast cancer is the one most likely to respond to current immunotherapies, but the response rate remains low. Dr. Liu is seeking to identify biomarkers that could identify patients most likely to respond to these therapies and is also investigating combination approaches that may improve response to immunotherapy in these patients.
Full Research Summary
Research area: Understanding the regulation of genes in breast cancer which may be targeted to improve the response to immunotherapy for patients with triple-negative breast cancer.
Impact: Immunotherapy is an exciting new treatment in several cancers, including some triple-negative breast cancers (TNBC); however, most TNBC patients do not respond to it. Dr. Liu is developing strategies to increase the effectiveness of therapy in TNBC, a particularly aggressive form of the disease. Her team has utilized cutting edge genomics and computational approaches to understand how cancer cell gene regulation and the tumor microenvironment influence drug resistance. They have identified and characterized a gene that may work synergistically with immunotherapy in TNBC. Her team hopes to translate these insights to better guide early cancer diagnosis and therapies.
Current investigation: Dr. Liu and her colleagues are utilizing cutting edge genomics and computational approaches to understand gene regulation in TNBC with the goal of translating these insights to better treatment options for patients.
What she’s learned so far: Dr. Liu has identified novel candidate genes that regulate protein degradation and conducted systematic computational modeling to understand mutations in these genes that influence protein degradation in TNBC tumors. Furthermore, her team has shown that the inhibition of one of these genes, Cop1, synergizes with immunotherapy in laboratory models of TNBC. In other studies, Dr. Liu and her colleagues have developed a computational algorithm, MAESTRO, which can be used for the integrative analyses of single-cell sequence data to study the tumor microenvironment and therapy response.
What’s next: The team will continue to investigate the mechanism of action of the Cop1 gene and gene mutations that influence protein degradation in cancers. They will also continue to use computational algorithms to analyze two single-cell technologies, in which individual breast cancer cells are screened for molecular markers. This technique will improve our understanding of gene regulation in the tumor immune microenvironment and potentially lead to the identification of new therapies to treat TNBC patients.
X Shirley Liu is Professor of Biostatistics and Computational Biology at Harvard University and the Director of the Center of Functional Cancer Epigenetics at Dana-Farber Cancer Institute. 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. She is interested in how nuclear receptors, epigenetic regulators, and protein degradation regulators influence breast tumor growth and breast tumor immunity. She is the PI of the Cancer Immune Data Common, a cancer moonshot project from National Cancer Institute with the goal of identifying biomarkers for optimizing cancer immunotherapy strategies. She has an H-index of 91 and has published over 60 papers in Nature, Science, or Cell series journals. Since becoming a faculty in 2003, she has successfully mentored eighteen trainees to start tenure track faculty positions. She is the recipient of the Sloan Research Fellowship, the Richard E. Weitzman Outstanding Early Career Investigator Award from the Endocrine Society, Breast Cancer Research Foundation Investigator and a fellow of the International Society of Computational Biology.
BCRF Investigator Since
The Estée Lauder Companies' Employee Fundraising Award