Immunotherapy, a class of drugs that enable a patient’s immune system to fight cancer, has emerged as a promising area of cancer drug development in recent years. However, not all patients respond to these treatments, and many patients who do will have a recurrence of their cancer. The biological mechanisms behind these differences in response to immunotherapy are currently poorly understood. However, recent improvements in sequencing technology now allow scientists to examine the behavior of genes in individual cells and how those cells resemble or differ from other cells around them. With this new data also comes the need to create new computational methods to analyze it. On this project, the student will work at the intersection of algorithm development and cancer biology to interpret single-cell sequencing data of cancer samples with the goal of understanding how cancer cells interact with the nearby immune cell populations and how these interactions affect response to treatment. Students will work in a multidisciplinary environment, collaborating with biologists, software developers, and experts in the fields of immunology and oncology. Interested students should have prior experience with programming, preferably in Python or R. This project can be done for class credit or as an internship.
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