Defining Vulnerabilities of T-cell Lymphomas: we are close to the - - PowerPoint PPT Presentation

defining vulnerabilities of t cell lymphomas we are close
SMART_READER_LITE
LIVE PREVIEW

Defining Vulnerabilities of T-cell Lymphomas: we are close to the - - PowerPoint PPT Presentation

Defining Vulnerabilities of T-cell Lymphomas: we are close to the finalizationof the beginning David Weinstock dweinstock@partners.org http://weinstock.dfci.harvard.edu Disclosures Company Research Speakers Advisory Employee Consultant


slide-1
SLIDE 1

Defining Vulnerabilities of T-cell Lymphomas: we are close to the finalization…of the beginning

David Weinstock dweinstock@partners.org http://weinstock.dfci.harvard.edu

slide-2
SLIDE 2

Company name Research support Employee Consultant Stockholder Speakers bureau Advisory board Other Travera X X Founder Novartis X X Dragonfly X Aileron X Abbvie X Astra Zeneca X Surface Oncology X Monsanto Expert Witness Genentech Expert Witness Verastem X Daiichi X DxTerity X

Disclosures

slide-3
SLIDE 3
slide-4
SLIDE 4

MSKCC Stanford Dana-Farber/BWH

Clinical Core Phase I and II Surgery Pathology Core Characterization, Banking, NGS, Spectral Imaging Model Generation Core PDX development Cell line generation Transgenic models Patient-Derived Xenografts (PDX) Primary lymphomas & PDX cell lines PDX clinical trials Targeted agents T-cell differentiation Lymphomagenesis 2D 3D In vitro drug response

Nebraska Weill-Cornell

Industrial and Academic Partners

GATA-3

Translational Discovery in Peripheral T-Cell Lymphomas

slide-5
SLIDE 5

Wu et al. Cancer Cell 2015 Crescenzo et al. Cancer Cell 2015 Townsend et al. Cancer Cell 2016 Yoda et al. Nature Medicine 2016 Dunford et al. Nature Genetics 2017 Horwitz et al. Blood 2018 Murakami and Weinstock. Nature 2018 Buchner et al. Cell 2018 Ng et al. Nature Communications 2018 (in press) Ng et al. Blood 2018 (in press) Intlekofer et al. Nature 2018 (in press)

3 years of progress

slide-6
SLIDE 6

Cutting edge in genomics-based drug selection

  • Letai. Nature Med 2017
slide-7
SLIDE 7

Personalized Medicine for Cancer: Genetic Testing

Letai et al. Nat. Med. (2017); Vivek Prasad, Nature. (2016); Friedman et al. Nat. Rev. Cancer (2015)

Personalized Medicine for Infectious Disease: Antibiotic Susceptibility Testing Highly successful for some cancers but unavailable for most Highly successful across a wide range of organisms and drugs

Proliferation is a functional biomarker

slide-8
SLIDE 8

Ng et al. Nat Comm 2018 (in press)

Vulnerability screening to define targets

slide-9
SLIDE 9

Aileron Therapeutics

Targeting both MDM2 and MDMX

slide-10
SLIDE 10

Murakami and Weinstock, Nature 2017

Patient-derived xenografts to model human cancer

slide-11
SLIDE 11

Patient Cutaneous NK/T

CD3 CD8 CD56 EBER

Mouse tumor

CD3 CD8 CD56 EBER

slide-12
SLIDE 12

20 40 60 80 100 120 140 160 50 100 Days Survival Survival(%) vs. p=0.0002 vs. p=0.0036

Randomization upon engraftment Pharmacodynamics Biomarkers

Defining biomarkers, toxicity and resistance

Townsend et al. Cancer Cell 2016

slide-13
SLIDE 13

T-ALL AML B-ALL AUL BPDCN Mantle cell lymphoma Double-hit lymphoma Marginal zone lymphoma Follicular lymphoma Transformed follicular lymphoma Diffuse large B-cell lymphoma High-grade with MYC rearr

Enabling Research on Human Cancer

Alveolar Soft Part Sarcoma Inflammatory myofibroblastic tumor Neurofibroma Osteosarcoma Rhabdoid tumor Solid pseudopapillary tumor Wilms Tumor Merkel cell carcinoma 400 Solid Tumors from Novartis HSTL Primary cutaneous CD30+ TCL T-PLL AITL ALK+ ALCL ALK- ALCL Mycosis Fungoides Sezary Syndrome Cutaneous NK/TCL Extranodal NK/TCL PTCL, NOS ATLL

Many, many people and especially Giorgio Inghirami

slide-14
SLIDE 14

Public Repository of Xenografts (www.PRoXe.org)

slide-15
SLIDE 15

Public Repository of Xenografts (www.PRoXe.org)

slide-16
SLIDE 16
slide-17
SLIDE 17

CBTL-81777; Disseminated hepatosplenic T-cell lymphoma

Raphael Koch, Noriaki Yoshida, Amanda Christie, Kay Shigemori

slide-18
SLIDE 18

WCTL-81162; Subcutaneous Alk+ anaplastic large cell lymphoma

Note: 1 ALRN-treated mouse was found dead on day 3, no obvious toxicity, cause of death unknown

Raphael Koch, Noriaki Yoshida, Amanda Christie, Kay Shigemori

slide-19
SLIDE 19

DFTL-78024; Disseminated angioimmunoblastic T-cell lymphoma

Raphael Koch, Noriaki Yoshida, Amanda Christie, Kay Shigemori

slide-20
SLIDE 20

DFTL-22685; Cutaneous T-cell lymphoma/Sezary

Raphael Koch, Noriaki Yoshida, Amanda Christie, Kay Shigemori

slide-21
SLIDE 21

DFTL-28776; Disseminated T-cell prolymphocytic leukemia

Raphael Koch, Noriaki Yoshida, Amanda Christie, Kay Shigemori

slide-22
SLIDE 22

Stapled peptide against MDM2/MDM4 – patients #1 and #2

Oct 22, 2015: Pre-Dose, 2.1 mg/kg May 2, 2016: Cycle 6

slide-23
SLIDE 23

Start with low-hanging fruit: highly targetable

WCTL-81162 WCTL-91953 SR786 Karpas299 KIJK SUPM2 SUDHL1 L82 DL40 SMZ1 MTA HH FEPD MAC2A DFTL-28776 MyLa DFTL-78024 DFTL-94393 DERL-2 NPM1:ALK TBL1XR1:TP63 FOXK2:TP63 MKLN1-AS1:DUSP22 PCM1:JAK2 BCR:JAK2 NPM1:TYK2 FYN:BACH2 VAV1:SF1 CD53:PDGFRB Classification Sample type no fusion Alteration fusion Classification AITL Alk+ ALCL Alk- ALCL CTCL T-PLL HS-TCL NKT PTCL-NOS Sample type Cell Line PDX

Ng et al. Nature Commun 2018 (in press)

slide-24
SLIDE 24

spleen infiltration spleen/body weight

Ruxolitinib

Start with low-hanging fruit: JAK2 fusions

Wu et al. Cancer Cell 2015; Ng et al. Nature Commun 2018 (in press)

slide-25
SLIDE 25

Nat Genet. 2015 47(9):1056-60

CTLA4-CD28 and ICOS-CD28 fusions co-opt checkpoint signaling

Jurkat APC TCL cell CD80 CD86

CTLA4-CD28

Anti-CTLA4

slide-26
SLIDE 26

2 4

EV-Av WT-Av Mut-Av

Ratio to day 0

Empty Vector CTLA4-CD28 Mutated CTLA4-CD28 1 5 10 20 CTLA4-Ab (ug/mL)

day3

Ipilimumab blocks CTLA4-CD28-mediated transformation

slide-27
SLIDE 27

Raphael Koch, Liz Brem, Tony Letai

slide-28
SLIDE 28
slide-29
SLIDE 29

Requirements

1. Rapid and precise 2. Small sample size from blood or fine needle aspirate 3. Single cell resolution

Defining therapeutic vulnerabilities using functional approaches

Scott Manalis, PhD Koch Institute/MIT

slide-30
SLIDE 30

Change in mass indicates drug effect

slide-31
SLIDE 31

time frequency

Suspended mic icrochannel resonator (SMR)

slide-32
SLIDE 32

Suspended microchannel resonator (SMR) in array

Cermak et al. Nat Biotech 2016

slide-33
SLIDE 33

Serial SMR

slide-34
SLIDE 34

Testing multiple drugs in leukemia samples

Cermak et al. Nat Biotech 2016, Stevens et al. Nat Biotech 2016

Mark Murakami, MD Mark Stevens, PhD

slide-35
SLIDE 35

Linking Mass and MAR to scRNA-Seq for each cell

Alex Shalek, Doug Lauffenberger, MIT

slide-36
SLIDE 36

Ten systems are up up and run unning Si Single-box design

slide-37
SLIDE 37

Stage II: LifeScaleAST for Rapid Antibiotic Susceptibility Testing

slide-38
SLIDE 38

fNIH funded testing in humans – 2018

slide-39
SLIDE 39

Testing in humans – projected 2019

Patients with relapsed hematologic malignancies Empiric trial selection SMR-driven trial selection Failure Failure Examples of available agents IDH2 inhibitors BCL2 inhibitors PI3K inhibitors MCL1 inhibitors CDK9 inhibitors XPO1 inhibitors Bromodomain inhibitors SYK inhibitors JAK inhibitors MDM2 inhibitors HSP90 inhibitors Spliceosome inhibitors Demethylating agents Anti-metabolites Antibody-drug conjugates Novel chemotherapies

slide-40
SLIDE 40

Weinstock laboratory

  • Nicolas Cordero
  • Tovah Day, Ph.D.
  • Hailey Fuchs
  • Saliva Jain, M.D.
  • Kristen Jones
  • Jacob Layer, M.S.
  • Catharine Leahy
  • Loretta Li, M.D.
  • Huiyun Liu
  • Chen Lossos, M.S.
  • Abner Louissaint, M.D., Ph.D.
  • Sara Morrow
  • Mark Murakami, M.D.
  • Sam Ng, M.D., Ph.D.
  • Foster Powers
  • Kay Shigemori
  • Tony Tran
  • Alex van Scoyk
  • Amanda Christie (former)
  • Mark Stevens, Ph.D. (former)
  • Noriaki Yoshida, M.D. (former)

DFCI Hematologic Oncology

  • Andrew Lane, M.D., Ph.D.
  • Dan DeAngelo, M.D., Ph.D.
  • Arnie Freedman, M.D.
  • Ilene Galinsky, N.P.
  • Jim Griffin, M.D.
  • Margaret Shipp, M.D.
  • Philippe Armand, M.D., Ph.D.
  • Richard Stone, M.D.
  • Martha Wadleigh, M.D.
  • David Fisher, M.D.
  • Eric Jacobsen, M.D.
  • Caron Jacobson, M.D.
  • Ann LaCasce, M.D.
  • Marlise Luskin, M.D.
  • Ore Odejide, M.D.

DF/HCC

  • Jon Aster, M.D., Ph.D.
  • David Dorfman, M.D., Ph.D.
  • Alejandra Gutierrez, M.D., Ph.D.
  • Tim Graubert, M.D.
  • Marian Harris, M.D.
  • Tom Kupper, M.D., Ph.D.
  • Tom Look, M.D.
  • Marcela Maus, M.D., Ph.D.
  • Elizabeth Morgan, M.D.
  • Stu Orkin, M.D.
  • Hidde Plough, Ph.D.
  • Jerry Ritz, M.D.
  • Scott Rodig, M.D., Ph.D.
  • Scott Armstrong, M.D., Ph.D.
  • David Williams, M.D., Ph.D.
  • Henry Long, Ph.D.
  • Myles Brown, M.D., Ph.D.

MSKCC

  • Andy Intlekoffer, M.D., Ph.D.
  • Steve Horwitz, M.D.
  • Allison Moskowitz, M.D.
  • Natasha Galasso
  • Craig Thompson, M.D.
  • Ahmet Dogan, M.D., Ph.D.
  • Ross Levine, M.D.

Koch Institute-MIT

  • Scott Manalis, Ph.D.
  • Alex Shalek, Ph.D.

Cornell

  • Giorgio Inghirami, M.D., Ph.D
  • Danilo Fiore, Ph.D.
  • Jia Ruan, M.D.

Stanford University

  • Youn Kim, M.D.
  • Michael Khodadoust, M.D.

University of Gottingen

  • Raphael Koch, M.D.

Aileron Therapeutics

  • Manuel Aivado, M.D.

Travera, inc.

  • Mark Stevens, Ph.D.
  • Rob Kimmerling, Ph.D.
slide-41
SLIDE 41

Linked scRNA-seq: Workflow

From SMR scRNA-seq library prep (smart-seq2) and sequencing

1 2

Gene1 Gene2 Cell1 Cell2

. . . . . .

Genes x cells matrix Trimming for quality cells (scone*)

*Cole, M. et al. Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq (bioRxiv, 2017)

Prioritize normalization schemes (scone*) Analyze complete dataset

*SMR step is a “viability filter” so we enrich for at least somewhat healthy cells

slide-42
SLIDE 42

Pretreatment Treated

B Cell development / HSC Translation / tRNA charging Heat shock / UPR response mTOR signaling down Proliferation / cell cycle progression

scRNA-seq: Treatment

633 cells; 6 individual mice treated and untreated; spleen and bone marrow

slide-43
SLIDE 43

Minimal residual disease is the roadblock to cure

Ding et al. Nature 2013

Presents with leukemia Remission Relapse

slide-44
SLIDE 44

Current approach to minimal residual disease (MRD)

Luskin et al. Nature Reviews Cancer 2018

slide-45
SLIDE 45

Tumor MRD

Iteratively test MRD to identify effective treatment

Treatment

Observation or continuation of same treatment

Potential advantages of targeting MRD 1) Less clonal complexity 2) Loss of chemoprotective microenvironment 3) Improved patient performance status 4) Enrichment of “cancer stem cells” tested for functional responses 5) Fewer cells to cure

>99% reduction Regrowth

Relapse

Cure?

Potential disadvantages of targeting MRD 1) Excess toxicity and cost from treatments (i.e., overtreatment) 2) Therapeutic selection confounded by unrepresentative MRD sampling (i.e., wrong treatment) 3) Morbidity/mortality of repeated MRD sampling

Iteratively change treatment based on testing

Minimum detectable threshold MRD relapse

Paradigm of precision targeting for MRD

Luskin et al. Nature Reviews Cancer 2018