2014 News

Novel Machine Learning Method Expands the Landscape of Breast Cancer Driver Genes

Expanding the landscape of breast cancer drivers

In comparison with a previous study (Stephens et al., 2012, shown in gray), a new computational approach that focuses on somatic copy number mutations increased the number of known driver mutations in breast tumors to a median of five for each tumor. The findings could raise the likelihood of finding actionable targets in individual patients with breast cancer.

For many years, researchers have known that somatic copy number alterations (SCNA’s) — insertions, deletions, duplications, and transpositions of sections of DNA that are not inherited but occur after birth — play important roles in causing many types of cancer. Indeed, most recurrent drivers of epithelial tumors are copy number alterations, with some found in up to 40% of patients with specific tumor types. However, because SCNA’s occur when entire sections of chromosomes become damaged, biologists have had difficulty developing effective methods for distinguishing genes within SCNA’s that actually drive cancer from those genes that might lie near a driver but do not themselves cause disease.

Helios nearly doubled the number of high-confidence predictions of breast cancer drivers.

In a new paper published in Cell, researchers in the laboratories of Dana Pe’er (Columbia University Departments of Systems Biology and Biological Sciences) and Jose Silva (Icahn School of Medicine at Mount Sinai) report on a new computational algorithm that promises to dramatically improve researchers’ ability to identify cancer-driving genes within potentially large SCNA’s. The algorithm, called Helios, was used to analyze a combination of genomic data and information generated by functional RNAi screens, enabling them to predict several dozen new SCNA drivers of breast cancer. In follow-up in vitro experimental studies, they tested 12 of these predictions, 10 of which were validated in the laboratory. Their findings nearly double the number of breast cancer drivers, providing many new opportunities towards personalized treatments for breast cancer. Their methodology is general and could also be used to locate disease-causing SCNA’s in other cancer types.

Leading this effort was Felix Sanchez-Garcia, a recent PhD graduate from the Pe’er Lab and a first author on the paper. The story of how this breakthrough came about illuminates how the interdisciplinary research and education that take place at the Department of Systems Biology can address important challenges facing biological and biomedical research.

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Improving Single-Cell RNA-Seq at the Columbia Genome Center

Fluidigm C1 Single-Cell Plate

At the core of the Fluidigm C1 Single-Cell Auto Prep System is a 96-well plate containing microfluidics. After individual cells are isolated in their own wells, the device amplifies their cDNA for genome-wide gene expression profiling. Scientists at the Columbia Genome Center are developing methods for addressing the technical and analytical challenges of single-cell RNA sequencing, and have begun generating some exciting data.

Since the invention of the first microscope, a procession of new technologies has enabled scientists to study individual cells at increasingly fine levels of detail. The last two years have witnessed an important next stage in this evolution, with the arrival of the first devices for genetically profiling single cells on a genome-wide scale.

The first commercial product in this field is the Fluidigm C1 Single-Cell Auto Prep System, which uses microfluidics to isolate single cells and offers the ability to generate gene expression profiles for up to 96 cells at a time. But because of the novelty of the technology and the inherent difficulties of working with single cells, it has presented a number of technical challenges for researchers interested in exploring biology at this level.

Now, scientists at the JP Sulzberger Columbia Genome Center led by Assistant Professors Peter Sims and Yufeng Shen have developed an experimental and computational pipeline that optimizes the C1’s capabilities. And even as they work to solve some of the challenges that are inherent to single-cell research, their approach has begun generating some exciting data for studying genetics in a variety of cell types.

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Department of Systems Biology Announces 2014-2015 Seminar Series

Calendar

The Department of Systems Biology is pleased to announce the speakers in its 2014-2015 Seminar Series. The seminar series features leading investigators working in a diverse set of fields, including cancer genomics, systems biology, computational biology, human genetics, cancer biology, RNA splicing regulation, chromatin and cell signaling, and microfluidics and sequencing. Please save the dates!

All events will be held in the Department of Systems Biology Common Room (ICRC 816), unless indicated otherwise. Additional details about these events will be provided at the links below as they become available.

For a continually updated calendar of all Department of Systems Biology events, and to see an archive of past seminars, visit systemsbiology.columbia.edu/events.

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Algorithm Identifies Genetic Driver of Mesenchymal Glioblastoma

DIGGIT identifies mutations upstream of master regulators.

A new algorithm called DIGGIT identifies mutations that lie upstream of crucial bottlenecks within regulatory networks. These bottlenecks, called master regulators, integrate these mutations and become essential functional drivers of diseases such as cancer.

Although genome-wide association studies have made it possible to identify mutations that are linked to diseases such as cancer, determining which mutations actually drive disease and the mechanics of how they do so has been an ongoing challenge. In a paper just published in Cell, researchers in the lab of Andrea Califano describe a new computational approach that may help address this problem.

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Prestigious NIH Director's Awards Go to Two Department of Systems Biology Researchers

Dana Pe'er and Kyle Allison

Dana Pe'er has received the Pioneer Award for high-risk, high-reward research, and postdoctoral scientist Kyle Allison has won an Early Independence Award.

Two members of the Columbia University Department of Systems Biology have been named recipients of NIH Director’s Awards from the National Institutes of Health Common Fund.

Associate Professor Dana Pe’er is one of 10 winners of the 2014 NIH Director’s Pioneer Awards. The Pioneer Awards provide up to $2.5 million over 5 years to support exceptionally creative investigators who are pursuing “high risk, high reward” science that holds great potential to transform biomedical or behavioral research. The award will support an ambitious new project to develop the technological and computational methods necessary to create a comprehensive, high-resolution atlas of development for all cell types in the human body.

In addition, Kyle Allison, a postdoctoral scientist in the laboratory of Professor Saeed Tavazoie, has received the NIH Director’s Early Independence Award. (Dr. Tavazoie is also a past winner of the Pioneer Award.) This program enables outstanding young investigators who have recently completed their PhD’s to move rapidly into independent research positions. Dr. Allison is one of just 17 scientists to receive this award this year. In combination with the Department of Systems Biology Fellows program, this five-year, $1.25 million grant will allow him to open his own laboratory at Columbia and pursue independent research to investigate the problem of bacterial persistence. He is the second Department of Systems Biology investigator to receive the Early Independence Award, joining Assistant Professor Harris Wang in being recognized with this honor.

“Having four recipients of NIH Director’s Awards within the Department of Systems Biology — and particularly two in one year — is quite remarkable,” said Department Chair Andrea Califano. “I think it’s a testimony to the timeliness of the perspectives and tools that systems biology offers and to the high quality of research being conducted at Columbia. I look forward to the discoveries that will undoubtedly come from Dana’s and Kyle’s extremely exciting efforts.”

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Three CUMC Faculty Members Receive Interdisciplinary Appointments

We are pleased to announce that Columbia University Medical Center professors Oliver Hobert, Richard Mann, and Rodney Rothstein have been named to interdisciplinary appointments in the Department of Systems Biology. The addition of this new expertise will expand the breadth of science currently being explored in the Department, enhance educational opportunities for students, facilitate new collaborations, and promote the integration of systems biology perspectives and methods into research being conducted elsewhere in the university.

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New Directions in Genome Engineering: An Interview with Harris Wang

Harris Wang

As a graduate student in George Church’s lab at Harvard University, Harris Wang developed MAGE, a revolutionary tool for the field of synthetic biology that made it possible to introduce genomic mutations into E. coli cells in a highly specific and targeted way. Now an Assistant Professor in the Columbia University Department of Systems Biology, Dr. Wang recently published a paper in ACS Synthetic Biology that introduces an important advance in the MAGE technology. The new technique, called (MO)-MAGE, uses microarrays to engineer pools of oligonucleotides that, once amplified and integrated into a genome, can generate thousands or even millions of highly controlled mutations simultaneously. This new method offers a cost-effective way for designing and producing large numbers of genomic variants and provides an efficient platform for experimentally exploring genome-wide landscapes of mutations in bacteria and optimizing the organisms’ biochemical capabilities.

In the following interview, Dr. Wang explains the origins of the new technology, and discusses what he sees as the remarkable potential it holds for both basic biological research and industrial applications of synthetic biology.

How are MAGE and (MO)-MAGE different from more traditional methods in genome engineering?

In traditional genome engineering, researchers would induce genome perturbations randomly. For example, you might use ultraviolet radiation or a mutagen to generate mutations and then do a selection experiment to compare and isolate cells with different genotypes based on how they respond to specific stimuli. The problem with this approach, though, is that you have no way to control what mutations occur, even if you know the mutation you are interested in investigating.

(MO)-MAGE offers a cost-effective and efficient way to simultaneously mutate large numbers of genes in a targeted way.

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Study Sheds Light on Ashkenazi Jewish Genome and Ancestry

Ashkenazi Population Bottleneck Model
The consortium’s model of Ashkenazi Jewish ancestry suggests that the population’s history was shaped by three critical bottleneck events. The ancestors of both populations underwent a bottleneck sometime between 85,000 and 91,000 years ago, which was likely coincident with an Out-of-Africa event. The founding European population underwent a bottleneck at approximately 21,000 years ago, beginning a period of interbreeding between individuals of European and Middle Eastern ancestry. A severe bottleneck occurred in the Middle Ages, reducing the population to under 350 individuals. The modern-day Ashkenazi community emerged from this group.

An international research consortium led by Associate Professor Itsik Pe’er has produced a new panel of reference genomes that will significantly improve the study of genetic variation in Ashkenazi Jews. Using deep sequencing to analyze the genomes of 128 healthy individuals of Ashkenazi Jewish origin, The Ashkenazi Genome Consortium (TAGC) has just published a resource that will be much more effective than previously available European reference genomes for identifying disease-causing mutations within this historically isolated population. Their study also provides novel insights into the historical origins and ancestry of the Ashkenazi community. A paper describing their study has just been published online in Nature Communications.

The dataset produced by the consortium provides a high-resolution baseline genomic profile of the Ashkenazi Jewish population, which they revealed to be significantly different from that found in non-Jewish Europeans. In the past, clinicians’ only option for identifying disease-causing mutations in Ashkenazi individuals was to compare their genomes to more heterogeneous European reference sets. This new resource accounts for the historical isolation of this population, and so will make genetic screening much more accurate in identifying disease-causing mutations.

In an article that appears on the website of Columbia University’s Fu Foundation School of Engineering and Computer Science, Dr. Pe’er explains:

“Our study is the first full DNA sequence dataset available for Ashkenazi Jewish genomes... With this comprehensive catalog of mutations present in the Ashkenazi Jewish population, we will be able to more effectively map disease genes onto the genome and thus gain a better understanding of common disorders. We see this study serving as a vehicle for personalized medicine and a model for researchers working with other populations.”

In addition to offering an important resource for such future translational and clinical research, the paper’s findings also provide new insights that have implications for the much debated question of how European and Ashkenazi Jewish populations emerged historically.

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Columbia Genome Center Now Offers Illumina NextSeq 500 Self-Service

Illumina NextSeq 500 at Columbia University

As genome sequencing technologies evolve, the JP Sulzberger Columbia Genome Center continues to provide the Columbia University biological and biomedical research community access to state-of-the-art tools. In its most recent acquisition, the Genome Center has just installed two Illumina NextSeq 500 sequencers. The NextSeq 500 is a flexible and efficient desktop sequencer that offers powerful high-throughput sequencing capabilities.

Columbia investigators who are experienced with the Illumina next-generation sequencing platform can now schedule time to use the NextSeq 500 for their own research. 

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Researchers Identify RNA Binding Protein that Promotes Breast Cancer Metastasis

Differential decay rates in MDA-LM2 vs. MDA cells

The presence of the structural RNA stability element (sSRE) family of mRNA elements distinguishes transcript stability in metastatic MDA-LM2 breast cancer cell lines from that seen in its parental MDA cell line. Each bin contains differential decay rate measurements for roughly 350 transcripts. From left (more stable in MDA) to right (more stable in MDA-LM2), sRSE-carrying transcripts were enriched among those destabilized in MDA-LM2 cells. The TEISER algorithm collectively depicts sSREs as a generic stem-loop with blue and red circles marking nucleotides with low and high GC content, respectively. Also included are mutual information (MI) values and their associated z-scores. 

Gene expression analysis has become a widely used method for identifying interactions between genes within regulatory networks. If fluctuations in the expression levels of two genes consistently shift in parallel over time, the logic goes, it is reasonable to hypothesize that they are regulated by the same factors. However, such analyses have typically focused on steady-state gene expression, and have not accounted for modifications that messenger RNAs (mRNAs) can undergo during the time between their transcription from DNA and their translation into proteins. Researchers now understand that certain stem loop structures in mRNAs make it possible for proteins to bind to them, often causing RNA degradation and subsequently modulating protein synthesis. From the perspective of systems biology, this can have implications for the activity of entire regulatory networks, and recent studies have even suggested that aberrations in mRNA stability can play a role in disease initiation and progression.

In a new paper published in the journal Nature, Department of Systems Biology Professor Saeed Tavazoie and collaborators at the Rockefeller University describe a new computational and experimental approach for identifying post-transcriptional modifications and investigating their effects in biological systems. In a study of metastatic breast cancer, they determined that when the protein TARBP2 binds to a specific structural element in mRNA transcripts, it increases the likelihood that cancer cells will become invasive and spread. Interestingly, they also found that TARBP2 causes metastasis by binding transcripts of two genes — amyloid precursor protein (APP) and zinc finger protein 395 (ZNF395) — that have previously been implicated in Alzheimer’s disease and Huntington’s disease, respectively. Although the nature of this intersection between the regulatory networks underlying cancer and neurodegenerative diseases is unclear, the finding raises a tantalizing question about whether these very different disorders might be linked at some basic biological level.

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MAGNet Releases Web Browser-Enabled Version of geWorkbench Bioinformatics Software Platform

geWorkbench screenshot

A new version of geWorkbench lets researchers access a range of powerful, integrated bioinformatics tools using a standard web browser. Here, an ARACNe-generated gene regulatory network is displayed using the Cytoscape Web plugin.

Since its creation in 2005, investigators in Columbia University’s Center for the Multiscale Analysis of Genomic and Cellular Networks (MAGNet) have developed a large number of computational tools for studying biological systems from the perspectives of structural biology and systems biology. To consolidate and disseminate these tools to the wider research community, MAGNet developed geWorkbench (genomics Workbench), a free, open-source bioinformatics application that gathers all of the Center’s software and databases into one integrated software platform. These include applications for the analysis of cellular regulatory networks, protein structure, DNA and protein sequences, gene expression, and other kinds of biological data.

Initially, geWorkbench was made available as a software package that users could install and run on their local computers. Now, in a major upgrade, MAGNet has released a web-based version that makes these tools accessible through a browser interface.

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Columbia Launches Initiative to Advance Personalized Medicine

Personalized Medicine

Illustration by Davide Bonazzi, courtesy of Columbia Medicine.

The cover article of the Spring 2014 issue of Columbia Medicine reports on a new, Columbia University-wide effort to harness the potential of new scientific approaches and technological developments to advance the personalized treatment of cancer and other diseases. Announced in February by Columbia President Lee Bollinger, an interdisciplinary task force has been formed to coordinate the scientific, policy, and clinical components necessary to achieve this goal. The Department of Systems Biology, including its Center for Computational Biology and Bioinformatics and JP Sulzberger Columbia Genome Center, has been identified as a key partner in this interdisciplinary effort. As the article reports:

Rapidly evolving technologies that make DNA sequencing dramatically faster and less expensive along with new technologies to monitor virtually all aspects of cell physiology have led to the generation of unprecedented amounts of information (big data) that is starting to yield to new computational approaches and high speed computers, all of which promise to make diagnosis and treatment as patient-specific and precise as possible.

To harness the potential created by these scientific advances for the benefit of patients, [College of Physicians & Surgeons] Dean Lee Goldman, MD, has made personalized medicine a key goal of the medical school’s strategic plan. “At Columbia, we have enthusiastic consensus in support of personalized medicine—the personalized application of scientific advances to modern diagnosis and treatment, easily accessible and attentive care for the people who entrust us with their health, and personalized education for each of our individual students,” says Dr. Goldman…

At the center of Columbia’s personalized medicine effort is the new Department of Systems Biology, which brings together researchers specializing in molecular biology, genetics, computational biology and bioinformatics, structural biology, mathematics, chemistry and chemical biology, physics, computer science, and other fields. According to founding director and chair Andrea Califano, PhD, the Clyde and Helen Wu Professor of Chemical Systems Biology, the new department seeks to provide an in-depth, systemwide characterization of all molecular interactions. It is this systems-level approach to disease biology that can systematically identify disease drivers and druggable targets for the 90 percent of cancer patients who lack a clearly actionable genetic mutation. This has become possible only in recent years through major advances in science and technology that require a fully interdisciplinary approach.

The article describes how research by Department of Systems Biology faculty members including Dr. Califano, Nicholas Tatonetti, Brent Stockwell, and Tuuli Lappalainen, along with that of investigators in departments across the university, is contributing to this ambitious initiative. Read the complete article here.

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Department of Systems Biology Holds Annual MAGNet Retreat

Sayantan Bose Receives Best Poster Award

Associate Professor Harmen Bussemaker (left) presents the best poster award to postdoc Sayantan Bose for his efforts to develop a high-throughput platform for performing single-cell RNA-Seq.

On May 30, 2014, the Columbia University Department of Systems Biology and its Center for Multiscale Analysis of Genomic and Cellular Networks (MAGNet) held its annual retreat at Tappan Hill Mansion in Tarrytown, NY. The event provided an overview of some recent work undertaken by Department investigators, and provided a comfortable setting for department members to socialize and exchange ideas about their current research interests.

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Synergy between Two Genes Drives Aggressive Prostate Cancer

Comparing human and mouse prostate cancer networks

Computational synergy analysis depicting FOXM1 and CENPF regulons from the human (left) and mouse (right) interactomes showing shared and nonshared targets. Red corresponds to overexpressed targets and blue to underexpressed targets.

Two genes work together to drive the most lethal forms of prostate cancer, according to new research by investigators in the Columbia University Department of Systems Biology.  These findings could lead to a diagnostic test for identifying those tumors likely to become aggressive and to the development of novel combination therapy for the disease.

The two genes—FOXM1 and CENPF—had been previously implicated in cancer, but none of the prior studies suggested that they might work synergistically to cause the most aggressive form of prostate cancer. The study was published today in the online issue of Cancer Cell.

“Individually, neither gene is significant in terms of its contribution to prostate cancer,” said co-senior author Andrea Califano, the Clyde and Helen Wu Professor of Chemical Biology in Biomedical Informatics and Chair of the Department of Systems Biology. “But when both genes are turned on, they work together synergistically to activate pathways associated with the most aggressive form of the disease.”

Co-principal investigator Andrea Califano discusses the new study.

“Ultimately, we expect this finding to allow doctors to identify patients with the most aggressive prostate cancer so that they can get the most effective treatments,” said co-senior author Cory Abate-Shen, the Michael and Stella Chernow Professor of Urologic Sciences and also a member of the Department of Systems Biology. “Having biomarkers that predict which patients will respond to specific drugs will hopefully provide a more personalized way to treat cancer.”

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Molly Przeworski Named Professor at Columbia

Molly PrzeworskiMolly Przeworski has joined Columbia University as Professor in the Department of Systems Biology and Department of Biological Sciences. The Przeworski lab investigates how natural selection, genetic drift, mutation, and recombination shape the heritable differences seen among individuals and species. To this end, they develop models of the evolutionary process, create statistical tools, and analyze large-scale variation data sets. Among the goals of their research are to understand how natural selection has shaped patterns of genetic variation, and to identify the causes and consequences of variation in recombination and mutation rates, in humans and other organisms.

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Using New Single-Cell Technologies, Researchers Create Comprehensive Map of Human B Cell Development

Distribution of marker expression across development

A new algorithm called Wanderlust uses single-cell measurements to detect how marker expression changes across development.

In a new paper published in the journal Cell, a team of researchers led by Dana Pe’er at Columbia University and Garry Nolan at Stanford University describes a powerful new method for mapping cellular development at the single cell level. By combining emerging technologies for studying single cells with a new, advanced computational algorithm, they have designed a novel approach for mapping development and created the most comprehensive map ever made of human B cell development. Their approach will greatly improve researchers’ ability to investigate development in cells of all types, make it possible to identify rare aberrations in development that lead to disease, and ultimately help to guide the next generation of research in regenerative medicine.

Pointing out why being able to generate these maps is an important advance, Dr. Pe’er, an associate professor in the Columbia University Department of Systems Biology and Department of Biological Sciences, explains, “There are so many diseases that result from malfunctions in the molecular programs that control the development of our cell repertoire and so many rare, yet important, regulatory cell types that we have yet to discover. We can only truly understand what goes wrong in these diseases if we have a complete map of the progression in normal development. Such maps will also act as a compass for regenerative medicine, because it’s very difficult to grow something if you don’t know how it develops in nature. For the first time, our method makes it possible to build a high-resolution map, at the single cell level, that can guide these kinds of research.”

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Grant Will Support Annotation of Metabolic Networks in Pathogenic Bacteria

M. Tuberculosis Culture

M. tuberculosis bacterial colonies. Photo credit: CDC/Dr. George Kubica [Public domain], via Wikimedia Commons

Dennis Vitkup, an associate professor in the Columbia University Department of Systems Biology and Department of Biomedical Informatics, has  been awarded an R01 grant from the National Institute of General Medical Sciences (NIGMS) to develop a computational pipeline for predicting bacterial metabolic networks. Building on a framework called GLOBUS that was previously developed in his lab, the project will produce probabilistic annotations of metabolic networks for all of the major bacterial species that cause disease in humans. It will both offer a method that can be used to study metabolism in any species of bacteria and produce valuable information that will aid researchers who are looking for therapies against many of the world’s most deadly pathogens.

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Brent Stockwell Receives 2014 Lenfest Distinguished Teaching Award

Brent Stockwell Congratulations to Brent Stockwell, one of 10 recipients of the 2014 Lenfest Distinguished Teaching Awards. Dr. Stockwell is an Associate Professor of Chemistry and Biological Sciences, and a member of the Columbia University Department of Systems Biology.

Established through a donation by trustee Gerry Lenfest (Law '58), the Lenfest Award recognizes faculty who are not only accomplished scholars but also exhibit excellence in instruction and mentorship, as well as university citizenship and professional involvement. Each recipient of the Lenfest Award receives a prize of $25,000 for a three-year period and is recognized at the Lenfest Award dinner.

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Why the New York Times Hired a Biology Researcher as Its Chief Data Scientist

Chris Wiggins

In a “Most Creative People” feature, Fast Company magazine recently interviewed associate professor Chris Wiggins, a faculty member of the Department of Systems Biology and Center for Computational Biology and Bioinformatics, about his new appointment at one of the world’s most respected outlets for digital journalism. In this role, he will lead the development of a machine learning team that will help the New York Times to better understand how its audience is using and navigating its content.

In the interview Dr. Wiggins explains why machine learning is becoming increasingly important in the age of big data, and about the shared challenges that the natural sciences and the media are now both facing.

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Systems Biology Throws You Out of the Box: An Interview with Saeed Tavazoie

Saeed Tavazoie

One of the defining features of systems biology has been its integration of computational and experimental methods for probing networks of molecular interactions. The research of Saeed Tavazoie, a professor in the Columbia University Department of Systems Biology, has been emblematic of this approach. After undergraduate studies in physics, he became fascinated by the processes that govern gene expression, particularly in understanding how gene expression is regulated by information encoded in the genome. Since then, his multidisciplinary approach to research has generated important insights into the principles that orchestrate genome regulation, as well as a number of novel algorithms and technologies for exploring this complex landscape.

In this conversation, Dr. Tavazoie discusses his research in the areas of gene transcription, post-transcriptional regulation, and molecular evolution, as well as some innovative technologies and experimental methods his lab has developed.

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Peter Sims Appointed to Columbia Genome Center

Peter SimsPeter Sims, an assistant professor in the Columbia University Department of Systems Biology, has been named Associate Director for Novel Technologies at the JP Sulzberger Columbia Genome Center. In this role he will devise, direct, and implement strategies for incorporating new high-throughput experimental methods into the research done at the Genome Center.

Trained as a physical chemist, Dr. Sims has been developing a number of innovative technologies for studying single cells in a high-throughput setting. Using a type of microfluidics called soft lithography, his laboratory has designed a method for creating arrays composed of wells just tens of microns in diameter, small enough to isolate and perform high-throughput experiments on individual cells.  

Appointing Dr. Sims to his new role will enable the Columbia Genome Center to develop a variety of new applications that will benefit researchers across the Columbia University community. 

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Dana Pe’er Wins 2014 Overton Prize

Dana Pe'erDana Pe’er, an associate professor in the Columbia University Department of Biological Sciences and Department of Systems Biology has been named the winner of the 2014 Overton Prize. Awarded by the International Society for Computational Biology (ISCB) since 2001, the Overton Prize recognizes one outstanding early- to mid-career scientist each year who has already made a significant contribution to the field of computational biology through research, education, service, or a combination of the three. The award recognizes Dr. Pe'er "for her cutting-edge research that applies computational methods to complex data to understand the organization of molecular networks in cells at a holistic systems level."

As the winner of the 2014 Overton Prize, Dr. Pe’er will receive the award and present a keynote address at the ISCB’s 22nd Annual International Conference on Intelligent Systems for Molecular Biology, which will be held in July 2014 in Boston.

In her research, Dr. Pe’er leads the development of computational methods for integrating large, diverse collections of high-throughput biological data, with the goal of understanding the structure and function of molecular networks. In recent work, she has focused on developing methods for interpreting data from single cells and characterizing heterogeneity in populations of cells with diverse phenotypes. She is also developing computational models for understanding the effects of epigenetic variation on regulatory network function and how these changes in regulatory networks lead to specific phenotypes in health and disease. These areas of investigation are particularly relevant within the field of cancer research, and the Pe’er lab’s findings and computational methods have offered new strategies for improving personalized medicine for cancer care.

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Tuuli Lappalainen Joins Columbia University Department of Systems Biology

Tuuli LappalainenTuuli Lappalainen has joined Columbia University as an assistant professor in the Department of Systems Biology. Dr. Lappalainen is a specialist in the analysis of RNA sequencing data, with research interests including functional variation in the human genome, population genetic background of variation in the human genome, and interpretation of genome function.

Dr. Lappalainen joins the Department of Systems Biology in co-appointment with the New York Genome Center (NYGC), where she will also serve as a Junior Investigator and Core Member. Based in lower Manhattan, NYGC is a consortium made up primarily of New York-area institutions that is designed to translate promising genomics-based research into new strategies for treating, preventing, and managing disease. This co-appointment with Columbia University — an institutional founding member of the NYGC — will enhance collaboration between the two institutions. (Read an interview with Dr. Lappalainen at the New York Genome Center website.)

Dr. Lappalainen earned her PhD in genetics at the University of Helsinki, Finland, and held appointments as a postdoctoral researcher in at the University of Geneva Medical School, Switzerland and at the Stanford University School of Medicine. She is the chair of the analysis group for the Genetic European Variation in Health and Disease (Geuvadis) Consortium’s RNA sequencing project, a member of the analysis group for the National Institute of Health’s Genotype Tissue Expression (GTEx) project, and a member of the analysis and functional interpretation groups for the 1000 Genomes Project.

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Synthetic and Systems Biology: Reinventing the Code of Life

A panel at the Helix Center, titled "Synthetic and Systems Biology: Reinventing the Code of Life included Columbia University professors Saeed Tavazoie and Andrea Califano, as well as Michael Hecht (Professor of Chemistry, Princeton University), Mark Fishman (President, Novartis Institutes for BioMedical Research), Christopher Mason (Assistant Professor of Physiology and Biophysics, Institute for Computational Biology, Weill Cornell Medical College), and Michael Waldholz (Medical Science Writer and Media Consultant).

Advances in genomics and the development of new technologies over the past decade have given biologists the ability to engineer DNA to perform specific functions. This emerging science, called synthetic biology, holds great potential for a number of applications, and experiments have already been done to reprogram algae to produce biofuels, design bacteria that can sense and consume toxic substances, and use living cells to manufacture compounds that can be used as drugs.

Synthetic biology has emerged in parallel with systems biology, but in many ways the two sciences are closely intertwined. As systems biology improves our mechanistic understanding of how biology functions at the molecular level, synthetic biology is taking this knowledge to push biology in new directions, from synthesizing molecules using biology all the way to synthesizing new forms of biological life.

In a public roundtable discussion at the Helix Center in New York City, Columbia University Department of Systems Biology professors Saeed Tavazoie  and Andrea Califano  joined a panel of experts in discussing the intersection of systems and synthetic biology, and the role that these two disciplines will play in the development of the biological and biomedical sciences in the coming years.

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Target Identified for Reversing Drug Resistance in Acute Lymphoblastic Leukemia

Reversing glucocorticoid resistance

A representative example of tumor load analysis using bioluminescence imaging in mice following xenograft with T-ALL. Treatment with either MK2206 or dexamethasone showed limited efficacy, while combination treatment saw near complete elimination of tumor cells.

In a paper published in Cancer Cell, a team of researchers led by Adolfo Ferrando and Andrea Califano at Columbia University has identified the protein kinase AKT as a target for reversing resistance to glucocorticoid therapy in patients with acute lymphoblastic leukemia (ALL).  

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