2020 News

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Video message for the CUIMC community from Lee Goldman, MD, dean of the Faculties of Health Sciences and Medicine and chief executive of CUIMC; Jack Cioffi, MD, president of ColumbiaDoctors; and Donna Lynne, DrPH, chief operating officer of CUIMC.

At first, Xuebing Wu , PhD, was on track to pursue a research career in computer engineering. After taking a course by Dr. Yanda Li, a pioneer of bioinformatics, Dr. Wu’s interest quickly shifted and he soon got hooked on genomics research and computational biology.

Xuebing Wu, PhD
Xuebing Wu, PhD

“Around that time—2003 to 2004—the human genome project had just been completed, and there had been lots of enthusiasm about using computational approaches to decipher the human genome,” he said. “I was excited to dive into this field that seemed wide open for research possibilities.”

Dr. Wu joined Columbia University’s Department of Systems Biology in the fall of 2018, with a joint appointment in the Department of Medicine’s Cardiology Division . He also is a member of the Herbert Irving Comprehensive Cancer Center at NewYork-Presbyterian/Columbia and the Columbia Data Science Institute , and his lab straddles basic science and computational biology. Dr. Wu and collaborators often consider how their work can make an impact in novel therapeutics. 

At the center of his interests is understanding the fundamental principles of gene regulation in human cells through integrative genomics approaches. His previous work has uncovered important roles of RNA sequence and structure signals in controlling the expression and evolution of the mammalian genome. His lab currently studies RNA-centric gene regulation, focusing on mRNA structures and mRNA translation. Dr. Wu and his team are increasingly turning their attention to the development of genomic technologies such as the revolutionary CRISPR/Cas system and a high throughput analysis technology called massively parallel reporter assays (MPRA), as well as novel computational tools and deep learning models to study gene regulation at a global scale. 

In recognition of Dr. Andrea Califano's recent Ruth Leff Siegel Award , an annual prize that honors and supports an investigator who has made outstanding contributions to our understanding of pancreatic cancer, Let's Win! Pancreatic Cancer has published the following feature article spotlighting his innovative approach to cancer research.

Dr. Andrea Califano
Dr. Andrea Califano, 2019 recipient of annual Ruth Leff Sigel Award for pancreatic cancer research. (Photo: Jörg Meyer/Columbia Magazine)

If you look at our basic biology, humans are big, cumbersome living organisms with a lot of moving parts.

For most of our lives, the cellular machinery that keeps us functioning goes off without a hitch. Starting at conception, cells have been growing and dividing, structuring themselves in a highly organized fashion. Liver cells know their job. And brain and spinal cord cells know their jobs, too.

Cancer is also a living organism. After all, it grows and evolves just like healthy cells. But cancer cells are cheats, ignoring the rules that other healthy cells play by. They mutate and divide uncontrollably, finding ways to evade our immune systems, which try to keep these invaders in check. To complicate matters, cancer cells are what scientists call heterogeneous. That means that even in the same malignant tumor there can be a variety of mutations, which is one reason why cancer treatment often fails. Drugs simply can’t target all of those mutations.

New Book Coauthored by Raul Rabadan, PhD
Dr. Raul Rabadan coauthors new book that introduces techniques of topological data analysis, a rapidly growing subfield of mathematics. (Cambridge University Press)

The deluge of data in the diverse field of biology comes with it the challenge of extracting meaningful information from large biological data sets. A new book, Topological Data Analysis for Genomics and Evolution, introduces central ideas and techniques of topological data analysis and aims to explain in detail a number of specific applications to biology.

“High-throughput genomics has profoundly transformed the field of modern biology and has made it possible for scientists to make rapid scientific advances,” says the book’s co-author Dr. Raul Rabadan, professor of systems biology and founding director of Columbia University’s Program for Mathematical Genomics. “The explosion of data has hit biology, and as a result, we need new, more innovative analytical and computational tools to make sense of it all.”

Co-authored with Andrew J. Blumberg, PhD, professor of mathematics at University of Texas at Austin, the new book discusses techniques of topological data analysis, a rapidly developing subfield of mathematics that provides a methodology for analyzing the shape of data sets. The book offers several examples of these techniques and their use in multiple areas of biology, including the evolution of viruses, bacteria and humans, genomics of cancer, and single cell characterization of developmental processes.

Yufeng Shen , PhD, found his passion for science in childhood, but he developed a fascination for both math and physics as his education progressed. In an earlier generation, he would have needed to choose between divergent paths. Instead, he chased his calling within an important emerging discipline. 

Yufeng Shen, PhD
Dr. Yufeng Shen

Dr. Shen was awarded tenure and promoted to the rank of associate professor in Columbia University's Departments of Systems Biology and Biomedical Informatics (DBMI) last summer. Utilizing new methods, he answers long-standing questions that impact health. Specifically, his research has focused on discovering novel genetic variants that cause human diseases.

His current work focuses on developing new computational methods to interpret genome data, identifying genetic causes of human diseases by integrating multiple types of genomic data, and modeling of immune cell populations. That research has led to important findings, including his work on the Deep Genetic Connection between Cancer and Developmental Disorders , published in Human Mutation.

Using innovative sequencing techniques from published studies of cancer and developmental disorders, Dr. Shen and his students identified a significant number of genes implicated in both diseases.

“This project allows us to use the larger cancer data to inform analysis in genetic variations of developmental disorders, and to find new risk genes and new risk variance,” he said. “It also provides a new perspective on how to optimize care for kids with developmental disorders. There is probably two to three times more risk of developing cancer for kids with developmental disorders than otherwise healthy kids.”