Arizona Cancer Evolution Center (ACE) will hold its first Methods in Evolution and Cancer Bootcamp between December 2-6, 2019, at Arizona State University in Tempe. During this week-long event, experts will demonstrate cutting-edge techniques in computational biology that enable researchers to better visualize cancer development. Through lectures and hands-on tutorials, students will learn about methods in evolution and cancer, develop new skills, and start new collaborations.
Topics covered will include: how to read the information in a pathology slide, better characterization of tumor clones, building phylogenetic trees from cancer data, science communications, and more. The boot camp will include morning lectures and tutorials. In afternoon sessions, students will engage in hands-on projects and data analyses and work with instructors in small groups.
Who can attend
The boot camp is open to graduate students and postdoctoral researchers. Approximately 15 students will be accepted for the boot camp.
The registration fee of $500 includes attendance at all presentations, tutorials, lodging during the school and meals or per diem. In addition to this subsidized registration fee, students with financial need will have the opportunity to apply for travel grants up to $500.
Application deadline: October 20, 2019.
What Tutorials Do We Offer at the Bootcamp?
Darryl Shibata, Professor, University of Southern California
Reading the information in a pathology slide
Description: Most tissues removed from patients are fixed in formalin, placed on a microscope slide, and examined under the microscope. This tutorial will outline how these specimens are collected and processed, and some basics with respect to how cancers look like and how they spread. In addition, the genomes and epigenomes within the cells on the microscope slide can also be read by modern molecular methods. Cell phenotype, genotype, epigenotype, and ancestry can be integrated by preserving their spatial distributions on a microscope slide.
Noemi Andor, Assistant Professor, Moffitt Cancer Center
Characterizing coexisting tumor clones
Description: Knowing the clonal composition of a tumor can inform what distinguishes sensitive cells from the therapy-resistant cells that seed the recurrence. To underscore the imperfection of our measurements of what really constitutes a clone, I introduce the concepts of “clone identity” and “clone perspectives”. A clone’s identity is given by the full set of its phenotypes, while a perspective is a measurement of one specific aspect of a clone. CLONEID is a framework we developed to integrate different perspectives on intra-tumor heterogeneity – such as single-cell DNA and -RNA sequencing or multiple, related biopsies – into an approximation of the identities of coexisting tumor clones. Knowing what constitutes a distinct clone within a tumor is a powerful metric that informs – in a computationally efficient manner – parameters of tumor evolution that are otherwise difficult to measure directly.
William Cross, Postdoctoral Fellow, Institute of Cancer Research
Phylogenetic methodology in the cancer realm and its application to the adenoma-carcinoma sequence
Description: Oncology has entered an era of increased interest in genomics and clonal evolution. Phylogenetics, the study of evolutionary histories, has become one of the
major tools deployed to reveal the evolutionary underpinnings of cancer, being applied in recent years to a wide variety of genomic datasets. In this session, I outline the methodologies needed to build phylogenetic trees from cancer data and demonstrate how to statistically validate, and make biological conclusions from results. I will focus on example datasets from colorectal cancers and adenomas, which together can be used to study the phenomenon known as the adenoma-carcinoma sequence. I also highlight the challenges and pitfalls that permeate the field, in particular posing unsolved questions regarding the application of chromosome copy changes and other mutation types to the paradigm of phylogenetics.
Khalid Abdul Jabbar, Postdoctoral Fellow, Institute of Cancer Research
Deep learning the tumor microenvironment from histology images
Description: This tutorial is an overview of the latest approaches in computational pathology using advanced machine learning and image analysis. We will mainly focus on the analysis of cell features from standard H&E slides. Expected topics to be covered include, raw cancer histopathology data pre-processing, single-cell detection and classification, spatial analyses, tissue architectural heterogeneity and the detection of more complex morphological patterns.
Pauline Davies, Professor of Practice, Arizona State University
Communicating your message effectively
Description: The ability to communicate complex and sometimes abstract scientific concepts is a critical skill for all those planning a career in science or science administration. This course will teach you the basic ideas needed to convey your message in clear and concise terms, both in the written and spoken form. This session will prove valuable for tutorials, public lecturing, grant writing, journal papers and reports as well as presenting the significance of your work to the media.
Li Liu, Assistant Professor, Arizona State University
Model-based adaptive grouping of subclones (MAGOS)
Description: While single-cell sequencing is on the rise, bulk sequencing remains as the dominant technology that interrogates an amalgam of heterogeneous cells collectively and relies on in silico analysis to de-convolute the mixed populations. Current methods that decompose subclones in a bulk-sequenced tumor require deep coverages (>300x) for reliable inferences, which is seldom available in clinical applications. In this tutorial, we introduce a new MAGOS method that pushes the minimum required sequencing depth to 30x for subclonal inferences. Based on MAGOS analyses of >10,000 tumors, we show that the number of subclones in a tumor has a significant prognostic power of patient survival.
Diego Mallo, Postdoctoral Fellow, Arizona State University
Reconstructing somatic evolutionary processes using Bayesian phylogenetics
Andrea Sottoriva, Team Leader, Institute of Cancer Research
Neutral evolution and selection
Maximilian Mossner, Postdoctoral Fellow, Barts Cancer Institute
Molecular genetics approaches for measuring tumor evolution
Carlo Maley, Professor, Arizona State University
Capturing cancer with music
Dr. Darryl Shibata
After attending UCLA for his undergraduate degree, Dr. Shibata obtained his medical degree from the Keck School of Medicine of USC. After completing his internship training in pediatrics from UC San Diego, Dr. Shibata returned to USC for his residency and fellowship at LAC+USC Medical Center. Currently, Dr. Shibata has clinical appointments at both LAC+USC Medical Center and USC/Norris Comprehensive Cancer Center. In addition to his wide array of responsibilities in the research, education and practitioner capacities, Dr. Shibata sits on the editorial board of the BMC Cancer Journal and the American Journal of Pathology.
Dr. Noemi Andor
My Ph.D. in Bioinformatics was under the supervision of Hans Werner Mewes from the Technical University in Munich and Claudia Petritsch from the University of California, San Francisco. Together we developed one of the first algorithms that deconvolutes a tumor’s sequencing data into clones that coexist in the tumor biopsy. As a postdoctoral fellow, together with Hanlee Ji and Carlo Maley, I quantified intra-tumor heterogeneity in >1000 primary tumors to find that coexistence of multiple clones in the same tumor is indeed the norm. As an Instructor at Stanford in Prof. Ji’s lab, I integrated bulk- and single-cell sequencing approaches to zoom into different perspectives of intra-tumor heterogeneity. The newly gained resolution on coexisting clones and their microenvironment puts us in the yet best position to control and steer subclonal evolution.
Dr. William Charles Hemming Cross
My primary research interests are cancer genetics and clonal evolution but I also have specialist interests in colorectal cancer, chromosomal instability, and aneuploidy. I am currently working on several projects related to colorectal cancer and its premalignant stages, including sporadic adenomas and inflammatory bowel disease. My aim is to reveal how aneuploidy relates to the evolution and transformation to colorectal carcinomas. I have specialist skills in bioinformatics and computational biology/mathematical modeling but I also have a background in molecular genetics that includes sequencing and PCR based technologies.
Dr. Khalid Abdul Jabbar joined ICR in August 2017 as a postdoc in the Computational Pathology and Integrative Genomics team and has been mainly working on the TRACERx lung project. Using his computer vision and machine learning background, Khalid looks closely at the computational pathology data to study the interplay of an evolving cancer and its immune microenvironment. His work relies on integrating geospatial observations from the tumor microenvironment, mapped by deep learning with the phylogenetics of the tumor. He is keen to explore novel clonality detection methods, and better understand the relationships between genomic and spatial histological intra-tumor heterogeneities. Khalid received his Ph.D. from the Bristol Robotics Laboratory, UWE Bristol in 2017. His multidisciplinary Ph.D. research focused on the use of novel 3D computer vision and pattern recognition techniques to invasively detect early lameness in quadrupeds. Prior to his research career, Khalid was trained as an R&D Electronics Engineer and worked in the industry developing autonomous aerial systems.
Pauline Davies teaches science and health communication at Arizona State University. She is an award-winning broadcaster with an extensive international career. She spent many years with the BBC’s World Service where her programs reached audiences of tens of millions worldwide. Her topics ranged from fundamental physics to human origins and she has reported from conflict zones on maternal health and combatant injuries. She continues to make documentaries from across the sciences for public broadcasters worldwide. She leads the outreach for ACE, finding new ways to bring fundamental research findings to the science community and the public.
Dr. Andrea Sottoriva uses genomics and computational approaches to understand cancer as a complex system. He obtained a degree in computer science and worked in particle physics before switching to biomedical research. He is the Deputy Director of the ICR’s Centre for Evolution and Cancer.
Dr. Diego Mallo
Diego Mallo is a biologist and computational phylogeneticist aspiring to understand the evolution of somatic cells. He develops computational methods that use genomic information to reconstruct the past; specifically, how cancers initiate and evolve within a patient. He thinks that understanding the mechanisms and dynamics of this process are not only discoveries by themselves but will also change how cancer is prevented and managed in the clinic. He has also worked on evolutionary modeling and species tree reconstruction methods and is a firm supporter of open source and data.
Dr. Li Liu
Dr. Liu is an assistant professor of Biomedical Informatics and the director of the Bioinformatics Core Facility at Arizona State University. She holds an M.D. degree in Medicine and an M.S. degree in Information System. As a trained clinician and a bioinformatics researcher, she fully appreciates the critical roles genomic medicine and bioinformatics play in advancing precision medicine. By integrating genomic, phylogenetic, population genetic, statistical and machine-learning techniques, Dr. Liu and her research team investigate clinical and molecular signatures of human diseases, and develop novel computational methods to discover biomarkers for early diagnosis and accurate prediction of therapeutic responses for individual patients. Before joining ASU, Dr. Liu helped build and directed the bioinformatics core facility at the University of Florida.
Dr. Carlo Maley
Carlo Maley is a cancer biologist, evolutionary biologist, and computational biologist, working at the intersection of those fields. He directs the Arizona Cancer Evolution Center at Arizona State University. His team uses tools from evolution and ecology to help solve four problems in cancer: a) they use evolutionary and ecological measures of neoplasms to distinguish high from low-risk tumors, b) they develop new approaches for delaying or deflecting the evolutionary trajectories of premalignant neoplasms to prevent cancer, c) they develop methods to prevent or control the evolution of therapeutic resistance in cancers, d) they seek to discover the mechanisms that have evolved to suppress cancer in large, long-lived animals like elephants and whales, a problem known as Peto Paradox.
Dr. Maximilian Mossner
My research is focussed on the disturbed epigenomic landscape within pancreatic tumors. In particular, I investigate the bi-directional epigenetic reprogramming between the tumor microenvironment and pancreatic cancer stem cells that leads to cooperative tumor outgrowth.