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Activity Number: 467 - Statistical Advances for Cancer Genomics and Immunogenomics - from Single-Cell to Correlated Population
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #328742
Title: Using RNA-Seq Data to Study Patients' Response on Tumor Immunotherapy
Author(s): Wei Sun* and Chong Jin and Paul Little and Danyu Lin and Mengjie Chen
Companies: Fred Hutchinson Cancer Research Center and UNC-Chapel Hill and UNC Chapel Hill and University of North Carolina and University of Chicago
Keywords: immunotherapy; RNA-seq

Cancer immunotherapy has made huge success in treating certain types of cancers. However, durable clinical response of immunotherapy is only observed in a subset of patients. For example, approximately 20% of melanoma and lung cancer patients show response to immune checkpoint inhibitors. To improve the efficacy of immunotherapy (e.g., to identify the patients who can benefit from immunotherapy or to develop new treatment strategy), it is crucial to have a mechanistic understanding of immunotherapy failure. One of the most promising biomarkers is immune cell composition around tumors. Using RNA-seq data, we develop a new statistical method to estimate immune cell composition as well cell type specific gene expression, and associate it with immunotherapy response.

Authors who are presenting talks have a * after their name.

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