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LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT

March 13, 2017 by 2012pharmaceutical

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN

Summer Symposium 2017

https://ki.mit.edu/news/symposium/2017

@kochinstitute #KIsymposium @Pharma_BI @AVIVA1950

A leader in Convergence, MIT’s Koch Institute for Integrative Cancer Research will, on June 16, present its 16th annual Summer Symposium: the Convergence of Science and Engineering in Cancer Research. Convergence—the merging of historically distinct disciplines such as engineering, physics, computer science, chemistry, mathematics, and the life sciences—has created extraordinary opportunities in cancer research and care. Leaders in this emerging field will discuss innovative new approaches and technologies to better detect, monitor, treat, and prevent cancer. The symposium will also feature a panel of experts to discuss the impact of Convergence on the future of medical care.

INTRODUCTORY REMARKS

Tyler Jacks, PhD
Director, Koch Institute, MIT
David H. Koch Professor of Biology, MITLIVE – new Solutions for Cancer the mission og KI. Sponsors: Affiliates, Collaborators, Patrons, Friends, Vendors. Introduction to Prof. Sharp. 40th Anniversary of RNA related discovery leading to Nobel Prize of Prof. Sharp.

Concluding the Symposium

continum
June 15, 2018 – NanoMedicine
Fall Symposium in September 2017

Phillip A. Sharp, PhD
Institute Professor, MIT
Koch Institute, MIT

LIVE – Convergence of Science and Engineering. Key note by a convergent personality – Eric Lander.

Convergence is a blueprint for innovation – NOW transformation of Life Science that follows the transformation of Physical sccience. Molecular biology – Delbruck, transmission of genetic phenotypes. Revolution of Biological Sciences in 20th Century

1st Revolution – DNA Structure, 1953

2nd Revolution – genomics Human Genome 2003

3rd Revolution – Integration of Science and the Environment in 21st Century

Such Small investment, 3.4% of NI Funding went to PI in BioEngineering 2000-2016

Introduction to Eric Lander – 1986 – to Whitehead Institute and MIT, now at Broad

KEYNOTE SPEAKER

30 Years of Convergence

Eric Lander, PhD
President and Founding Director, Broad Institute of Harvard and MIT
Professor of Biology, Department of Biology, MIT
Koch Institute, MIT
Professor of Systems Biology, Harvard Medical School

LIVE – Personal Reflection on Convergence in BioMedicine

Process is important inconvergence — WHAT ARE WE CONVERGING TOWARD?

1985 — today — 2045

BioMedicine – born from 4 Intellectual Revolutions:

Biochemistry – since 1890
Genetics – since 1900
Molecular Biology – since 1945, 1953, 2003
Recombinant DNA – since 1970

GENOMICS comes along: a View of

Completeness, Nature, 1986 – before the flood of data

Biology is Finite – systematically perturbed
Proteomics

Comprehensive views

Discovering Disease Genes – 1980s: Mendelian rare inherited, Common variation, Somatic

Human Genome – Finished, 2003
DNA, RNA, Proteins (Kinase, E3 Ligase) are finite and can be recognized from signatures

Human Genome Variations

Discovering Disease Genes – 2000s:

2017: 100 diseases are derived from Genome variation

Disease Pathways discovered systematically: schesophrenia
Cancer – Chromatin regulators and remodelers
Regulatory elements: Conversation of species – finite and tractable

Evolutionary
signatures of cellular processes – connectivity map Dependency Map
3D

Programmable Genome Targeting –

CRISPR GPS
Genome-wide CRISPR Screen

Human cells – unified coordinated to classify Cells and Tissues

Combine single cells with CRISPR Screening to systematically discover cellularpathway

Comprehensive Tools

Programmable Therapeutics –

DNA-directed Chemical synthesis
DNA-encoded Chemical Libraries
Programmable activation in cell type

Healthcare systems –>> Learning systems

SPEAKERS

	Synthetic biology and next-generation diagnostics James Collins, PhD Termeer Professor of Medical Engineering and Science and Professor of Biological Engineering, MIT Broad Institute of Harvard and MIT Wyss Institute LIVE Synthetic Biology – Reprogramming life Design & model network Encode into DNA plasmid Transfer to cell monitor results Potential for Synthetic Gene Biology Paper-based synthetic Biology distribution without refrigeration RNA sensors with Colorimetric output Rapid prototyping: Ebola sensors Key features of Fieldable paper-based system CRISPR-Cas9 Component for Strain Discrimination – NASBA-CRISPR Cleavage Paper-based Diagnostics for the GUT microbiome Paper-based Diagnostics for HPV: Rapid, Inexpensive Sherlock – Nucleic Acid Detection with CRISPR-Cas13a Human Genotyping Using SHERLOCK Single-based gene usong Shrlock
	Cancer Genome and the Cloud Gad A. Getz, PhD Director, Cancer Genome Computational Analysis Group, Broad Institute of Harvard and MIT LIVE – Cancer is a disease of the Genome and epigenome – Life history of a Tumor Drivers: Cancer phenotype Smoking Defect in DNA repair Mutation type: C->T Part 1: Finding Drivers Score genes by number and type of mutations: mutation tally and score of repair 450 genes va 11 genes 33 NEW cancer genes: 4,729 tumors, 21 tumor type, 254 significant genes Gene Catalogue by Tumor type – 2,000 samples needed – to detect 90% Burden clustering Non-coding drivers: Promoter, Insulator 9 significant mutations in Breast cancer gene – promoter Hotspot in FOXA1 is activated through E2F – Estrogene receptor Mutational Signatures Non-negative Matrix Factorization (NMF) posterior distribution of the signatures Homologuos recombination repair pathway BRCA1/2: Signature analyzer: Breast Cancer mutation signatures Mono-alleleic inactivation of BRCA Germline mutation PALB2 PAthogenic mutations in genes RAD51C – the third BRCA Signature 3 is associated with BRCA www.firecloud.org
	Targeting Aggressive Cancers Nanolayers at a Time: A Platform Approach to Engineered Nanomedicine Paula T. Hammond, PhD David H. Koch Professor in Engineering, MIT Head of the Department of Chemical Engineering, MIT Koch Institute, MIT LIVE Layer-by-Layer (LBL) Assembly – The ultimate Nanofab Tool Multilayered, multifunctional LbL Nanoparticles – chemotherapy at the core of a sphere Engineering, Biology and Medicine — to understand activation Incorporate siRNA – a modular design pH-Dependent [6.0 – 7.4] Cell Uptake at Hypoxic Conditions surface induce acid pH avtive Tumor targeting (CD44) – Drug-loaded nanoparticle/PLL Triple Targeting Threat: size, tumor hypoxia, cell receptor A model target: MRP1 protein – Multidrug resistance A tumor treatment study in TNBC subcutaneous model using synergisitc siRNA Combo LbL NanoP’s work KRAS inhibition: NSCLC: Kras siRNA + miRNA miR34a MicroRNA cisplatin naoparticle – Orthotopic KP model: siRNA Second Window NIR Imaging (NIR-II) – deep tissue of Ovarian Cancer Nanoparticle Characterization Ovarian Cancer imaging Charged Assembly a Different way: Electrostatic Self-assembly of Oligopeptide Amphiphiles Peptide Nanoparticles are suitable for Vivo – p53-Deficient Cells Target: MK2 Mediates DNA Damage Repair Small molecules: Not safe not specific
	New chemical engieering approaches to convergence Robert S. Langer, ScD David H. Koch Institute Professor, MIT Koch Institute, MIT LIVE Lysozyme soybean Trypsin inhibitor Alkaline phosphatase Catalase Combinatorial lipid synthesis Next generation LNPs: with novel lipids – potency improvement Nano formulations for Entdothelium – combinatorial generation Nano particle library Current techniques: Electroporation – insert inside the gene – CellSqueeze of the cytoplasm Full transcriptome microarray Applications to Personalized Medicine Injectable chip with combination drug therapy inserted into the Tumor, MIS, Confining region of tumor Conversion : Clinicians and Engineers
	Understanding transcription and splicing heterogeneity in cancer progression Daniel Larson, PhD NIH Stadtman Investigator, Center for Cancer Research Head, Systems Biology of Gene Expression, National Cancer Institute Daniel Larson, NCI – Transcription and Splicing in Heterogeneity in Cancer Progression LIVE TFF1 Transcription in living cells: Estrogene response Transcription occures in bursts: seconds to several hours – regulated over multiple timescale 4oth Anniversary of Splicing high throughput approach for labelling thousands of genes at their endogenous loci SLC2A1 Splicing times andd burst size are highly similar across genes. Strong conservation in Eucaryote ccells Splicing factor mutations emerged in almost all tumor types 3″ SS recognition factor U2AF1 has a missense mutation in the zinc finger domain DNA damage after X-Ray treatment: U2AF1 S34F cells show – cell survive high dose (20 Gy) irradiation, becomes senescent and live >1 month in culture abd secrete interleukin 8 Interleukin 8 Upregulated even before DNA damage – expression and secretion in rare cells IL-8 induces Epithelial-Mesenchymal Transition i primary mamary epithelial cells Stochastic transcription and RNA splicing – IL-8 Secretion
	Computational Models of Cancer Franziska Michor, PhD Professor of Computational Biology, Dana-Farber Cancer Institute Harvard T.H. Chan School of Public Health LIVE Tumor evolve by natural selection Tarceva – approval 2004 – NSCLC – patients with EGRF mutant Effect of dosing:Number of sensitive cells in Two drug concentrations: Sensitive vs Resistant cells Combination Treatment Better parameter estimation: using single cell lineage tracing data microenvironment determinants of Treatment response Determining Optimum radiation schedules in GBM mathematical modeling of treatment response understanding the intratumor heterogeneity based on mouse modeling optimal radiation schedule –>> dose constraints – Ultra fractionated dose vs. Practicality constraints slower proliferation Radiation plus temozolomide: Optimized; time post treatment/percent survival Treatment modalities: Immunotherapy, chemo drugs
	Spherical Nucleic Acids as a Powerful New Platform for Cancer Therapy Chad A. Mirkin, PhD Director, International Institute for Nanotechnology George B. Rathmann Professor of Chemistry, Department of Chemistry, Northwestern University LIVE Next wave of Pharmaceuticals Small molecules’ biologics Nucleic Acids – limitations: Address disease in the Liver The Promise of Therapeutic Oligonucleotides Antisense DNA Spherical Nucleic Acids (SNA) – New way of thinking on DNA and RNA Hybridization Thermodynamics of SNAs SNAs enter cells rapidly and efficiently – over 60 different Cell Types Cy5-labeled SNA SNAs Come in many forms: Micellar SNA, Protein SNAs, Lipoprotein SNAs Late endosome nOT lysosomeow How does cell membrane recognition of SNAs and trigger exocytosis SNAs as Therapeutics: Skin (topical for Psoriasis), Brain (GBM) Immunostimulatory SNAs – activity of IS-SNAs in Vivo Oligonucleitides strands mimicking bacterial DNA or RNA SNA – Vaccines: Antigen presenting cells 3D Architecture of SNAs leads ti enhanced TLP9 Activation – B-cell NF-KB Activation SNAs Vaccines: -In Vivo Testing: retired Tumor growth vs control – inserted inside liposome Advantages SNAs Vaccine vs Standard Formulations vs adjuvant (antigen) SNA TLR-9 Activator Treatmeent vs Linear Oligo (EMT-6 Breast Cancer Model] – it potentiates activity of Anti-PD-1 Antibodies in PD-1 Resistant tumor confers immunity SNA Competitive advantage
	Dissecting the tumor ecosystem with single cell genomics Aviv Regev, PhD Director, Klarman Cell Observatory and Cell Circuits Program, Broad Institute of Harvard and MIT Professor of Biology, Department of Biology, MIT Koch Institute, MIT LIVE – Tumors: A complex cellular Ecosystem How to use Genomic sto study tumors? Option 1: Gene Atlas – single cell genomics can help dissect thie ecosystem – bulk cell Option 2: Tumor Cell Atlas – single cell Single cell RNA-Seq in Precision Medicine pipeline 19 metastasis melanomas: “non-design” design – 4600 cells Malignant or not? DNA or RNA-inferred Micronvironment of the cell – Diverse T cells, Naive, – Tumar infiltrating T cells: Activation-independent variation in exhaustion program across cells cytotoxicity, exhausion, naive RNA-Seq associates T cell clones with their states Cell-types and states in the melanoma ecosystem: single cell signature used to cluster bulk tumors by their microenvironment composition TCGA – Tumors – melanoma vs Cell type specific signature genes inferring cell-cell interactions: Cell type A and Cell type B: Correlation of gene’s expression with inferred proportion of cell type B (bulk samples) CAF expression of chemokines and complement associated with CD8 T cell infiltration Primary Test Stronger control The ecosystem of Malignant Melanoma – 19 malignant cells Treatment naive vs Immunotherapy resistant (ITR) – CD8 cells from ITR sample – intratumor variation How malignant melanocyte affect T-cells? Infiltrated tumor vs exclusion tumor ITR has prognostic value – predicts response to anti-PD1 in Pationts ITR Signatures in malignant and CD8 T cells
	Illuminating biology at the nanoscale and systems scale using single-molecule and super-resolution imaging Xiaowei Zhuang, PhD David B. Arnold Professor of Science, Harvard University Session I: NEW VIEW Xiaowei Zhuang, Harvard University — Single-Cell Transcriptome and Genome Imaging, Science, 2015, PNAS, 2016 LIVE molecular specificity moleculare-scale resolution genome scale throughputspatially-resolved single-cell transcriptome subcellular organization of the transcriptome Spatial organization of transcriptome in tissue Transcriptome Imaging single-molecule FISH (smFISH) [Image 1,2,3,4,, Decoded Image] Error-robust encoding: Hamming code Modified Hamming distance 4 – multiplexed, hydridization Applications: MERFISH imaging of Tissue Spacial organization of cells in Tissues High throughput image-based screening: Barcodes, gene activation/inhibition agents Tracing the 3D conformation of Chromatin Spatial organization of A-B compartments: Transient, Polarized, radial Super resolution of chromatin imaging with Transcriptome imaging

EXPERT PANEL: CONVERGENCE IN HEALTH

	LIVE Cori Bargmann, PhD President of Science, Chan Zuckerberg Initiative Torsten N. Wiesel Professor, The Rockefeller University LIVE – translation of the needs in computational, biology, IT, mathematician, medicine, physics and engineering. BRAIN Initiative at NIH. How to motivate? by a Problem in need for solution
	Marc N. Casper, MBA President and CEO, Thermo Fisher Scientific LIVE – convergence from a tool perspectiveLast 20 years – integration of Biology into the physical sciences, SCREENING AND DIAGNOSTICS
	Victor Dzau, MD President, National Academy of Medicine LIVE As cardiologist: Pace maker Convergence in Research. Funding research does not encourage convergence innovation is killing disease, need to introduce cost effectiveness – economics into the play. Recognition of cost in Precision Medicine: economic model as a tool to consider cost effectiveness, Convergence to include SOcial Sciences and Economics Diagnostics;
	Tyler Jacks, PhD Director, Koch Institute, MIT David H. Koch Professor of Biology, MIT LIVE – Convergence at Koch NIH created few CENTERS for research in Cancer, Brain, Nanotech, focus on Cancer did help the convergence Next step of Convergence: common language, Learning by doing, mechanisms to encourage and continue the convergence Better efficiency: Which Drug to which Patient Early detection and prevention
	Nancy Simonian, MD CEO, Syros Pharmaceuticals, Inc. LIVE – convergence is required to understand the biology of a disease, genomics, computational biology and chemistry is a new approach Cost of Medicines: reibbursement per value vs no concern to value. Innovation t carry premium allowing cost reduction while effciency is been exploled.
	Elias Zerhouni, MD President for Global Research and Development, Sanofi Former Director, NIH LIVE Convergence of multidisciplines is a must for scientific solutions to emerge, horizontal integration Patient Bill of Right Defficiet every year in the US,
	Moderated by: Susan Hockfield, PhD President Emerita, MIT Professor of Neuroscience, MIT Koch Institute, MIT