This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Computational biologist Christina Leslie, Ph.D., has spent nearly two decades at Memorial Sloan Kettering Cancer Center (MSK) building computational tools that help make sense of some of the most complex data in biology. Today, Leslie's work sits at the crossroads of two technological revolutions.
Single-cell genomics is allowing scientists to probe the activation of genes in individual cells, revealing the distinct roles, identities, and behaviors of every cell type in a tissue or tumor. Meanwhile, the rise of artificial intelligence (AI) is making it possible to find meaningful patterns in complex single-cell data sets at a scale far beyond more traditional computational methods. Memorial Sloan Kettering Cancer Center sat down with Leslie to discuss the promise—and limitations—of this frontier, and how these advances could help researchers design better therapies, decode why tumors resist treatment, and tailor treatments to each individual and their unique cancer.
The theme of my lab, which is in MSK's Sloan Kettering Institute, is studying how gene expression is regulated in mammalian cells—including in the immune system and in cancer. We use tools from what used to be called machine learning and is now called artificial intelligence. In the past few years, we've been using AI to analyze three increasingly powerful types of biological data.
AI gives us the computational power to make sense of all three of these complex data types and to find the patterns within them that would otherwise be invisible. Single-cell genomics is an increasingly important way that we make new discoveries in biology. Before, we would do what's known as "bulk" analysis, which allowed us to look at what was happening in a tissue sample—but with the molecular data from all the cells mixed together.
Now, we have ways of barcoding individual cells in a sample so that we can understand how cells play different functional roles in a particular system. And we can discover new cell types and functional specializations. Let me give you two examples from recent work done at MSK: We collaborated with Dr.
Chrysothemis Brown using single-cell approaches to discover a new specialized type of immune cell called Thetis cells, which help explain how the immune system learns to tolerate food and helpful gut bacteria early in life. This work is shedding new light on childhood food allergies. We also worked with the lab of Dr.
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