Preliminary schedule as of May 23, 2018.

 

Tuesday, May 22nd, 2018

• 12:00 onward: Registration
• 13:00: Welcome Address, Aperitif and Lunch
• 14:00: Marco Antoniotti and Bud Mishra: Cancer Development and Complexity
• 15:00: Bud Mishra, Courant Institute of Mathematical Sciences and Tandon School of Engineering, New York University, New York, USA
  [Tutorial]: Self vs Non-self, Information Asymmetry, Signaling Games and Immunology
  
  I will introduce a mathematical (game theoretic model) of immune systems, with Dendritic and Macrophage playing the roles of sender-receiver pairs and B-cells and T-cells playing the roles of recommender-verifier pairs respectively. I will also delve into the evolution of this complex systems, while distinguishing between jawed and jawless fish. This will help in understanding various issues related to immunotherapy for cancer.

• 16:00: Coffee Break
• 16:30: Abel David González-Pérez, IRB, Barcelona, Spain
  [Tutorial]: Functional annotation of cancer mutations
  
  We will first define driver mutations in cancer using the Darwinian evolutionary model of tumors. Then, using several computational methods (such as OncodriveFML, ) to identify genes under positive selection across cohorts of tumors, we will identify genes driving several malignancies. Then, we will use tools to annotate the functional impact of individual mutations affecting these driver genes, and we will exploit this information as well as accumulated prior knowledge on tumorigenesis to systematically and accurately pinpoint the most likely driver mutations in each cohort. To this end we will employ platforms IntOGen, COSMIC, the cbioportal, the Cancer Genome Interpreter and other platforms. Finally, we will use known and potential biomarkers of anti-cancer drug response to identify clinically actionable mutations in tumors under study. In this endeavor, we will use repositories of biomarkers such as CIViC, cbioportal, and the Cancer Genome Interpreter.
• 17:30: Daily Wrap-up

Wednesday, May 23rd, 2018

• 9:30: Gabriele Dubini, Laboratory of Biological Structure Mechanics, Politecnico di Milano, Milan, Italy
  [Tutorial]: Microfluidic Technologies for Single Cell Manipulation
  
  Over the past 15 years, the advances in microfluidic technologies have spearheaded the integration of several laboratory functions on a single integrated circuit, the so called ‘lab-on-a-chip’. The effective and efficient design of such devices is now possible by means of a combination of numerical simulation, microfabrication technologies and in vitro characterization. In particular, devices for single cell manipulation are now available, which are exploited in many biological fields, including research on cancer.In this tutorial I will give an overview of the physics of the microfluidic environment, will describe the main microfabrication technologies currently adopted, and will address the design issues of microfluidic devices for biotechnological applications.
• 10:30: Coffee Break
• 11:00: Abel David González-Pérez, IRB, Barcelona, Spain
  [Lecture]: Computational genomics at the heart of cancer biology
  
  In our lab, we use data on genomic mutations in tumors in three main lines of research. First, we study the distribution of mutations across different regions in the genome to understand basic questions about molecular biology, such as the interplay between DNA damage and repair, and other cellular processes. (I will briefly present one example of this basic research.) This helps us build refined models of the expected background mutation rate of different genomic elements across cell types. Comparing these models with the observed mutational patterns of genomic elements across cohorts of tumors, we are then able to detect which of them are under positive selection in the process of tumorigenesis. We go one further step to identify which amongst all the mutations (point mutations and structural variants) of these elements detected in a particular tumor are actually tumorigenic. (I will present our work on unraveling the panorama of driver mutations of more than 2500 tumor whole genomes.) Translating this basic knowledge in ways that may bridge the gap to personalized cancer medicine is the third line of research in the lab. We search for the potential clinical significance of individual driver mutations, and we build tools that assist clinical oncologists in therapeutic decision-making. (I will exemplify our translational research with our work on the immune-phenotypes of solid tumors.)
• 12:00: Charles Cantor, Agena Biosciences, Sequenom, Retrotope and Boston University, USA
  [Lecture]
• 13:00: Lunch break
• 14:00: Bertrand Adanve, Ph.D, Genetic Intelligence, Inc, Co-founder & CEO, USA
  [Lecture]: Improvements in the analysis of population admixture
  
  Artificial intelligence (AI) holds great promise to precisely classify human ancestry and the genetic causes of complex diseases. We have constructed an unsupervised machine learning paradigm that examines the whole genome as a hyper-dense, nonlinear, multidimensional feature space. Our AI system culminates in neurons that can identify an individual’s component genetic heritages, which also provide interesting early data about the distribution of the human population. The system holds great potential to help further other use-cases, including use as a tool to better explore and understand oncogenic processes.
• 15:00: Olivier Elemento, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, USA
  [Tutorial]: Network Analysis
• 16:00: Coffee Break
• 16:30: Participants Presentations

Thursday, May 24th, 2018

• 9:30: Daniele Merico, Director of Molecular Genetics, Deep Genomics Inc., Visiting Scientist, The Centre for Applied Genomics (TCAG) / The Hospital for Sick Children (SickKids), Toronto, Canada
  [Tutorial]: Making sense of cancer somatic SNVs and indels: from variant effects to pathways
  
  We will review commonly used models and resources for determining variant effects; we will start from gene product annotation using gene models; we will then review the most commonly used models to predict amino acid impact (e.g. SIFT, PolyPhen2, Mutation Assessor, etc…), discuss methodological issues with measuring performance and specific challenges of gain-of-function prediction. Finally, we will briefly review methods for understanding pathway and network-level effects of somatic variants.
• 10:30: Coffee Break
• 11:00:Bud Mishra, Courant Institute of Mathematical Sciences and Tandon School of Engineering, New York University, New York, USA
  [Lecture]: Immune Systems: Genomics
• 12:00: Olivier Elemento, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, USA
  [Lecture]: cancer precision medicine driven by multi-omics, analytics and modeling
  
  This talk will review the development and implementation of clinical grade (CLIA) whole-exome sequencing based genomic tests for precision cancer medicine and immunotherapy. A novel analytical pipeline will be described that evaluates genomic profiles to unravel the immune landscape of tumors and integrates multi-omics features using machine learning to predict immunotherapy response. Finally, high-throughput single-cell genomic approaches will be presented that dissect the tumor microenvironment and unravel immune repertoires at single-cell resolution.
• 13:00: Lunch
• 14:00: Valentina Boeva, Institut Cochin, Paris, France
  [Tutorial]: Analysis of epigenetics and chromatin states in normal and cancer cells
  
  I will talk about the role of chromatin modifications in normal and cancer cells: DNA methylation and histone modifications. I will also present the first steps of bioinformatics analysis of ChIP-seq data needed to characterize histone modification profiles.
• 15:00: Participants Presentations
• 16:00: Coffee Break
• 16:30: Participants Presentations
• 19:30: Social Dinner (location: ‘Gesumin’ Restaurant – via Cinque Giornate 46, Como)

Friday, May 25th, 2018

• 9:30: Valentina Boeva, Institut Cochin, Paris, France
  [Lecture]: Analysis of neuroblastoma super-enhancer landscape identifies two distinct malignant cell types
  
  We analyzed super-enhancer landscape in 25 neuroblastoma cell lines and six patient-derived mouse xenografts. We detected transcription factors that constitute the core neuroblastoma regulatory circuitries and drive expression of genes determining cell identity in neuroblastoma. Based on the super-enhancer landscape, we defined two neuroblastoma cell identity subtypes. These subtypes have different sensitivity to chemotherapy. Using single cell experiments, we showed that these two epigenetically and transcriptionally different cell identity may coexist within the same patient.
  Reference: Boeva et al, Heterogeneity of neuroblastoma cell identity defined by transcriptional circuitries, Nature Genetics, 2017, 49(9):1408-1413.
• 10:30: Coffee break
• 11:00: Daniele Merico, Director of Molecular Genetics, Deep Genomics Inc., Visiting Scientist, The Centre for Applied Genomics (TCAG) / The Hospital for Sick Children (SickKids), Toronto, Canada
  [Lecture]: Non-coding somatic variant rewiring transcriptional regulation in cancer
  
  We will examine how difficult it is to predict transcription factor binding changes using in-silico predictors (DeepBind, DeepSEA, etc..) and an allele-specific binding benchmark. We will then review a couple of recent research papers looking at non-coding variants causing transcriptional regulation rewiring in cancer.
• 12:00: Round Table and Wrap-up
• 13:00: Closing lunch