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The Future of Precision Cancer Medicine, Inaugural Symposium, MIT Center for Precision Cancer Medicine, December 13, 2018, 8AM-6PM, 50 Memorial Drive, Cambridge, MA

Reporter: Aviva Lev-Ari, PhD, RN

#CPCM2018 @AVIVA1950 @pharma_BI

 

 

Aviva Lev-Ari, PhD, RN, Editor-in-Chief, will attend and cover this event in REAL TIME for

 http://pharmaceuticalintelligence.com 

Over the past decade, there have been major advancements in the field of precision medicine, leading to exciting new treatments for some cancer patients. Much attention has been focused on genomic profiling of tumors to identify genomic alterations that might guide selection of specific therapies for individual patients. Beyond genomics, however, there is a variety of other precision approaches that can identify and exploit cancer-specific biological mechanisms including proteomics, metabolomics, and computational modeling, resulting in the more effective use of existing cancer medicines. On Thursday, December 13, 2018, the MIT Center for Precision Cancer Medicine will hold its inaugural annual symposium in the Samberg Conference Center at MIT. This full-day event will feature leading researchers and clinicians, who will highlight recent advances in precision cancer medicine and share perspectives on the future. An industry panel will also discuss the barriers to instituting precision medicine into current and future clinical trials.

 

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Keynote Address

Charles Sawyers, MD Chair, Human Oncology and Pathogenesis Program Memorial Sloan Kettering Cancer Center

Speakers

	Andrea Califano, PhD Clyde and Helen Wu Professor of Chemical Systems Biology, Columbia University Chair, Department of Systems Biology, Columbia University Director, JP Sulzberger Columbia Genome Center Associate Director, Herbert Irving Comprehensive Cancer Center
	J. Christopher Love, PhD Professor of Chemical Engineering, MIT Associate Member, Ragon Institute of MGH, MIT and Harvard Member, Koch Institute, MIT
	Richard Marais, PhD Professor of Molecular Oncology Director, CRUK Manchester Institute The University of Manchester
	Kenna Mills Shaw, PhD Executive Director Sheikh Khalifa Bin Zayed al Nahyan Institute for Personalized Cancer Therapy MD Anderson Cancer Center
	Alice Shaw, MD, PhD Professor, Harvard Medical School Director, Thoracic Cancer Program, Massachusetts General Hospital
	Matthew Vander Heiden, MD, PhD Associate Professor of Biology, MIT Associate Director, Koch Institute Member, MIT Center for Precision Cancer Medicine
	Michael B. Yaffe, MD, PhD David H. Koch Professor of Science, MIT Professor of Biology and Biological Engineering, MIT Director, MIT Center for Precision Cancer Medicine Director, Koch Institute Clinical Investigator Program
	Jean Zhao, PhD Professor of Biological Chemistry and Molecular Pharmacology Harvard Medical School and Dana-Farber Cancer Institute

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Panelists: Barriers to Instituting Precision Medicine in Clinical Trials

	Peter Hammerman, MD, PhD Global Head, Translational Research Oncology Disease Area Novartis Institutes for BioMedical Research
	Steffan N. Ho, MD, PhD Vice President, Head of Translational Oncology Pfizer Global Product Development
	Shiva Malek, PhD Director and Principal Scientist Department of Discovery Oncology Genentech Inc
	Kevin Marks, PhD VP of Biology Agios Pharmaceuticals
	S. Michael Rothenberg, MD, PhD Vice-President, Research and Development Loxo Oncology, Inc.
	Moderator: Angela Koehler, PhD Goldblith Career Development Professor in Applied Biology, MIT Member, Koch Institute for Integrative Cancer Research Member, MIT Center for Precision Cancer Medicine

Speakers:

• Andrea Califano, Columbia University
• J. Christopher Love, MIT’s Koch Institute
• Richard Marais, CRUK Manchester Institute
• Kenna Mills Shaw, MD Anderson Cancer Center
• Charles Sawyers, Memorial Sloan Kettering Cancer Center
• Alice Shaw, Massachusetts General Hospital
• Matthew Vander Heiden, MIT’s Koch Institute
• Michael B. Yaffe, MIT’s Koch Institute
• Jean Zhao, Dana-Farber Cancer Institute

Panelists:

• Peter Hammerman, Novartis Institutes for BioMedical Research
• Steffan Ho, Pfizer
• Shiva Malek, Genentech, Inc
• Kevin Marks, Agios Pharmaceuticals
• S. Michael Rothenberg, Loxo Oncology, Inc

Moderated by Angela Koehler, MIT’s Koch Institute

Agenda:

8:00 am Registration and continental breakfast

8:45 am Opening remarks by Michael Yaffe (MIT’s Koch Institute)

• Season of great expectation, tumor genetics is just the beginning, beyond: science, engineering, medicine: beyond genomics: immunology, cell biology, early detection, new drug development for the undrugable, system biology, RNAi
• Jack Tyler was the initiator to find a donor for CPCM

9:00 am Keynote Address by Charles L. Sawyers (Memorial Sloan Kettering Cancer Center)

• developed a drug for prostate cancer
• Clinical trained oncologist/genomics
• Lineage Plasticity:

1. luminal cells in histology of origin and basal cells and require androgen receptor AR) function
2. deprive lunimal cells fro growth factor
3. Hormonal therapy Leuprolite, degarelix [castration methastatic]
4. after relapse 2nd generation anti-androgens abirateron
5. PING MU ENZALUTAMIDE RESISTANCE P53/RB! DELETION CONFER
6. TRANSCRIPTION CHANGE: ANTIADROGEN RESISTANCE
7. Lineage shift Sox2 level goes up – prevent drug resistance, in vivo and in vitro
8. SOX2 promotes lineage placticity and antiadrogen resistance in TP53 and RBI-deficient prostate cancer
9. Evolution of Lineage plasticity over time
10. AR Pathway inhibition accelerates lineage plasticity: synaptophysin-positive disease in-vivo
11. scRNA-seq time course – modeled by diffusion map displayed in luminal and basal cells
12. Emergence of EMT phenotype, with retention of epithelial features
13. Use CRISPR to perturb luminal plasticity by phyeno type
14. Genomic landscape of Primary Prostate Cancer: ERG gain drives luminal layer
15. Different classes of FOXA1 mutations in Prostate organoid Cancer – Missense, inframe, truncated
16. FOXA1 key in hormone receptor signaling
17. Hypermorphic peaks – ATAC-seq neomorphic FOXA1 pioneering activity
18. Common Prostate Cancer Genes:differentiation phenotypes: TP53 Loss, RB1 – Loss,
19. work of Matan Hofree – four subtypes of luminal cells
20. involution and regeneration of single cell RNAseq
21. Transcriptional shifts in response to castration/androgen addback
22. androgen addback: 50% of luminal cells are proliferation in 48 hours
23. cell responsible for organ regeneration

 

9:45 am Alice T. Shaw (Massachusetts General Hospital)

• evolution of drug resistance in Lung Cancer
• oncogenic drivers in lung adenocarcenoma –

1. EGFR – sensitizing 19.4% of all patients
2. KRAS
3. ALK
4. ROS1
5. CMET
6. BRAF
7. NTRK1
8. RET

Delay and prevention of drug resistance: liquid biopsy of pleural fluids and serial blood collections

• Crizotinib patient with ROS1 + nsclc
• acquired mutation in ROS1 G2032R – resistance to Crizotinib – Michael Lawrence, MGH – analysis of mutation and resistance
• Repotrectinib – for ROS1 – Resistance mediated by this mutation
• If patient fails three antiinhibitor drugs: secondary ALK mutations mediate Crizotinib Resistance
• 2nd generation of  ALK inhibitors are structurally Distinct molecules
• Lorlatinib – 3rd generation –>> back to 1st generation Crizotinib
• Clonal evolution of resistance in ALK in NSCLC
• compound mutations in ALK mutations – Lorlatinib Resistance
• Sequential TKI therapy foster the development of compound mutation refractory to all generations og ALK TKIs – compound mutation can’t be overcome
• Intratumoral Heterogeneity revealed by multiregion sequencing of renal cell carcinoma and resected NSCLC
• somatic mutations: Pre-treatment to Lorlatinib resistance
• Clonal Analysis: Multiple Drivers of resistance underlie clinical relapse
• genomic instability – eradicate residual disease to eliminate drug resistance and tolerance persistance

 

10:25 am Networking Break

10:45 am Richard Marais (Cancer Research UK, Manchester Institute)

• Melanoma – Precision Medicin
• Request – NOT TO PUBLISH on the INTERNET, some of the work presented is not PUBLISHED.
• Request is honored

11:25 am Matthew Vander Heiden (MIT’s Koch Institute)

• Targeting Metabolism is altered in cancer
• Metabolism is glucose carbohydrates, lipids – conversion of nutrients into biomass: ATP, Protein, Nucleic acid,
• Not -proliferating cells vs proliferating cells
• genetic mutations, tissue of origin, lineage of cells — metabolism takes place: combination of these three facto
• environment consists the metabolic network definers.d by cell intrinsic network
• Assessment of nutrient levels in tumor microenvironment
• Metabolite analysis: ion suppression vs nutrients
• nutrients are available to cells in tumors
• depletion of glucose vs enrichment
• metabolite most different: Gluthamine, needed for cancer to grow
• Lineage can contribute – tryptophane and argenine
• gluthamine – Cyctine affect gluthamine sensitivity to gluthamine inhibitors
• what you eat, where is the tumor locate, tissue environment — more important
• therapeutic window: metabolism processes – cell proliferation
• ability to make aspartate – given to mice pancreatic  — tumor grow faster
• cellular oxidation state correlate with pyruvate oxidation — PDH Activator suppress oxidation
• Aspartate vs NAD+/NADH – lactate TCA – form more carbon
• PDH activation reduces Redux
• Serine availability can limit proliferation even in cells with increase
• Serine vs NAD regeneration
• which cancer falls into which group : Serine pathway – increase serine synthesis: Melanoma vs Breast cancer
• growth of breast cancer: Serine availability dependent – accelerate of inhibit growth by level of serine
• Model for how nutrient limitation affect tumor growth, tumor size depends of serine levels

 

12:05 pm Box lunch

12:30 pm Industry panel: Barriers to instituting precision medicine into clinical trials

• Long term benefits of Precision Medicine
• What phynotype are now looked for?

Michael Rothenberg

1. short term, identify mutations
2. more testing is needed
3. sequencing the therapies
4. challenge getting tissue, doing experiments in house
5. Industry needs Academia collaboration for accelerated innovations
6. AI may lower the cost of drug discovery

KEVIN MARX:

1. MECHANISM OF RESISTANCE – COMBINATORIAL DRUG DISCOVERY
2. phynotyping, tissue acquisition immune phenotype, what drive therapeutic response?
3. genetic drivers
4. HR seeks Scientistist that worked in TEAMS, collaborative science

STEPHAN HO

1. long term benefits are very important
2. Stage III disease – technology advances
3. advanced in the regulatory space
4. smaller cohort size to approve a drug
5. biologic complexity, driver oncogenes, precision to imprecision
6. cost of risk in investment in innovations
7. check point inhibitor – known biology and immuno-modulation, data hypothesis and moving forward
8. Organizational culture, interaction in teams, functional behavior
9. commit to deliverable, perfect timing contingent on work of others.

Peter Hammerman

1. single cell tumor immunity in combination drug therapy
2. Tumor monitoring over time
3. Novartis is interested to collaborate with innovators in Academia and in other institutions
4. critical thinking on DATA and on negative data
5. Combination drug therapy: orthogonal mechanism of actions and drug classed – toxicity is an issue

Shiva Malek

1. How to drug mutations on DATA
2. Acquired and intrinsic mutations
3. exposure and patient safety
4. UCSF’s Ashkenazi’s Team and Genetech – basic biology area selection
5. Failure are not talked about
6. Round table for problem solvers, how you approach a problem
7. translational work require skills beyond technical expertise
8. learning the navigation inside an organization
9. leadership in R&D, expected to demonstrate leadership, the Scientist needs to have command of the field and of desirable directions of research

 

2:00 pm J. Christopher Love (MIT’s Koch Institute)

Acceleration of the PROCESS to develop Precision Medicine products

• design, build, test – PROCESS
• New drugs and vaccines – the process is iterative
• measurements, with use of smallest number of samples
• deliver precision medical: small f patients or large population or
• clinical samples provide rich source of information: Blood or tissue sample
• Tissue – extract RNA, component cells, single-cell RNA sequencing,
• Challenges of enabling scRNA-seq in clinical labs
• Probability, scale, capture efficiencies, temporal uniformity
• single-cell sequencing
• Seq-Well: method for scRNA-Seq
• New Chemistries for T-cell
• Blood: cell, cfDNA, Exosomes
• map cancer genome from blood
• Tissue:
• Single circulating Tumor cells:
• yield genomic landscape of cancer
• cell free DNA, vells, proteins, metabolite, Tumor is existence, draw blood
• cfDNA Tumor Fraction is prognostic of survival in mTNBC
• automate to 13 cancer types
• Rs is now possible
• reduce sample requirement
• cost is low digital information from clinical samples
• Keytruda – is a molecular Signature
• low volume product, advanced preparation (mo-years) __>>> agile solutions (days to years)
• bentchtop, on-demand manufacturing system: Production, Purification, Formulation
• hand-free production of formulated G-CSF: comparable to licensed products.
• Plug and play manufacturing using  InSeq
• Novel MAbs from patients
• Many molecules to many products

 

2:40 pm Andrea Califano (Columbia University, System Biology)

Mechanistic Framework for the systematic pharmacological targeting of Non-Oncogene Dependencies – Precise Precision Oncology

• systematic elucidation od critical cancer cell dependencies
• drug MOA
• Tumor dependencies to Drug MOA
• Tumor heterogeneity
• ARACNe – regulatory targets of regulatory proteins
• Combinational Therapy: HER@ inhibitor and JAK1/JAK2 inhibitor
• Driver Mutations
• ARACNe; MINDy DIGGIT; Expression VIPER: MetaVIPER
• Aberrantly activated protein for Prioritizing treatment in patients
• Checkpoint activity reversal – prioritize drugs based on
• Tumor model selection: GIST
• 260 patients, 14 untreatable cancers — N of 1 Study
• Single cell Studies – active proteins in stem-like progenitor cells
• Ivermectin Treatment vs Control (7d vs 14d)

 

3:20 pm Networking Break

3:40 pm Jean Zhao (Dana Farber Cancer Institute)

Immunotherapy and Targeted Therapy in Cancer Therapy

• Targeting cancer with CDK4/6 inhibitors
• CDK4/6 inhibitors causes tumor regression in breast cancer and regression of CT-26 colorectal cancer
• CDK4/6DNMT1 inducing viral mimicry
• PARP inhibitors  changing treatment in ovarian cancer
• FDA approved three drugs for ovarian cancer
• p53-null; BRCA-null; myc high – model testing

 

4:20 pm Kenna Mills Shaw (MD Anderson Cancer Center)

• PM nor a Silver bullet nor a Dream Illusion
• 2013: not all mutations are equally actionable
• Context of Biomarkers
• co-mutations in lung cancer identity – therapeutic vulnerability
• NGS cost decrease leads to increases in Data generation
• there are only 125 genes ACTIONABLE IN THE CLINIC
• finding biomarkers beyond direct targets
• clinical actionability:80K mutation – 32%
• patients: No standard treatment available
• Enrollment inGenotype Matched TRIALS
• MUTATIONS SCREENED: LACK OF ENROLLMENT NOT DUE TO LACK OF MATCHING PROCESS
• 69% GOT NEW REGIMEN, 17% did not come back — no one called them
• 58% enrolled on genotrype-matched trials
• Beyond NGS:

www.personalizedcancertherapy.org

• DECISION SUPPORT IN REAL TIME IMPROVES “MATCHING” TO RIGHT DRUG.
• MULTIFACTORS: CO-MOEBIDITIES, MICROBIOME, IMMUNE PHYNOTYPING, GENOMICS, MICROBIOME, ZIP CODE, INFECTION

5:00 pm Michael Yaffe (MIT)

• AUGMENTED SYNTHETIC LETHALITY
• CANCER CELLS ARE UNDER CONSTANT STRESS
• inflammation
• Therpeutics-targeted Synthetic Lethality
• BRCA mutation seen in 10%-20% of patients
• p53 mutations DNA demage – leads to apoptosis p38 MK2 as a pathway is taking over repair DNA and no apotosis occurs.
• doxorubicin
• Nanoparticle targeting of siRNAs to established tumors
• The Concept of augmented Synthetic Lethality   —- enhance a prevosly known synthetic interaction by targeting additional pathways
• combination of repair pathway  and checkpoint activation – lead to better therapeutic results
• MK2 – targets hnRNP A0 (an RNA binding protein)  – Cleaved Caspase 3 – is synthetic lethal with p53 mutuant tumors, not just p53 null alleles
• MK2 links Inflammation and Cancer – IBD –>> polyps and Colon Cancer
• myeloid cell recruitment to inflammatory tumors in
• MK2 KO mice: IL-4 –M2 magrophage – tumor progression; regulate the tumor microenvironment
• IFNgamma –>M1 macrophages – tumor suppression

 

 

 

SOURCE

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