Anti-tumor T Cells: Immune Responsiveness or Immune Ignorance?

Lisa H. Butterfield, PhD. Vice President, PICI Research and Development Adjunct Professor, Microbiology and , UCSF Disclosures:

Calidi Scientific and Medical Advisory Board, April 6, 2017-present NextCure, Scientific Advisory Board, 2018-2019 Western Oncolytics, Scientific Advisory Board, 2018-present Torque Therapeutics, Scientific Advisory Board, 2018-2020 Khloris, Scientific Advisory Board, 2019-present Pyxis, Scientific Advisory Board, 2019-present Cytomix, Scientific Advisory Board, 2019-present Vir, Scientific Advisory Board meeting, Feb. 2020 DCprime, Scientific Advisory Board meeting, Nov. 2020 RAPT, Scientific Advisory Board, 2020-present Our Mission

To accelerate the development of breakthrough immune therapies to turn all cancers into curable diseases. Our Model

SAVE LIVES OUR INFRASTRUCTURE

NEW STANDARD PICI OF CARE PARTNERS Selection for most promising ideas ACADEMIC NEW RESEARCH TECHNOLOGY INSTITUTIONS BOLD IDEAS

EXTRAMURAL NEW RESEARCHERS COMPANY

FIELD AT LARGE FDA-APPROVED Product DRUGS Development

Research Clinical Strategic DIAGRAM KEY: BioTrust Informatics IP Support Projects Development Partnerships Tumor + Immune Cells = complex systems TAM (Tumor Associated )

VEGF, TNF- oncostain, Dendritic CXCL-1/2/3/5/8⍺ cell Neutrophil

PIGF, MCSF, PDGF, MIF, IL-1/8, VEGF, oncostain M, TNF- , TGF-β, PAF, MCP-1, CXCL-1/8, MMP9 COX2, iNos, MMPs, cathepsins ⍺

VEGF-A, endothelin, EMAPII, CCL2, hypoxia B cell

VEGF, HGF, , TGF-β, lactate CXCL-6/8, TNF- , VEGF, PIGF, GM-CSF,CSF2 ⍺ IL-8 IL-1, IFN-γ, b-FGF, NK HB-EGF, TNF, TGF T-cells activity (Natural ⍺ Killer cell) IL-6/10/35, TGF-β T-cells activity FGF2, VEGF, SCF, PD-ECGF, MMP9 VEGF, RANTEES, MCP-1 Tumor CCL3/5/8, TNF , hypoxia Vasculature ANGPT2 T-cell

⍺ G-CSF, Bv8, CXCL-12, hypoxia BFGF, MMP9 angiogenesis Mast cell MMP9, VEGFR2, modulating PECAM1

VEGF, b-FGF, IL-6, CXCL8, PDGF, MMP9, TEM (T Effector Memory cell) CCL11, TGFβ

Eosinophil MDSC (Myeloid Derived Suppressor Cell)

1. Stockmann C et al. Front Oncol. 2014;4:69. 2. Balkwill FR et al. J Cell Sci. 2012;125(Pt 23):5591-5596. Key Challenges in Solid Tumors

For a cell and gene therapy to be effective it has to overcome:

Heterogeneity of Disease-related challenges target Immune- Homing/tumor expression and suppressive penetration loss microenvironment

Cell therapy Access to IP Funding Agent development-related manufacturing Clinical challenges Institutional Vector trial Animal models focused efforts production Parker Institute: Next generation cell therapy

CARL JUNE, MD The University of Novel CARs and vectors for clinical trials Pennsylvania

LEWIS LANIER, PhD NK cell evaluation and engineering UCSF

CASSIAN YEE, MD MD Anderson Endogenous priming and therapeutics

CRYSTALL MACKALL, MD CAR-T persistence and pediatric clinical trials Stanford Medicine

HIDEHO OKADA, MD, PhD UCSF T cell trafficking and glioma targeting

ALEXANDER MARSON, MD, PhD Non-viral methods for T cell engineering UCSF

STEPHEN FORMAN, MD City of Hope Novel cell therapy programs in GBM PICI Brain Tumor Initiative

NanoString-PICI Cell Therapy Antigen / Consortium TCR discovery BRUBECK Myeloid BRUCE screen GBM platform New Partners trial TME Biomarkers / new targets PICI investigators (trials, BRUCE IP translational) License (all tumors)

8 Confidential information – not for distribution Validating H3.3K27M as a viable target for immunotherapy

. We identified an HLA-A2- binding H3.3K27M26-35 epitope . Epitope is naturally presented . Induces antigen-specific response . High avidity T cell receptor (TCR) cloned . No cross-reactive epitopes

Contributed by Alex Sette and John Sidney at Chheda Z., Kohanbash G. et al. La Jolla Institute for Allergy and Immunology J. Exp. Med. (2018)

HCC tumor-derived AFP induces a unique metabolic profile in Dendritic Cells: inhibition of fatty acid oxidation (SCENITH)

OVA DC nAFP DC tAFP DC

Paul Munson/UCSF/Marseille Argüello et al Cell Metab 2020 Mechanism: tAFP induces a decline in fatty acid metabolism and likely decreases the uptake of FAs

CD36

Pepino et al Annu Rev Nutr 2014 Mitochondrial mass segregates DC on key immune proteins Mito Lo Mito Mid/Lo. Mito Mid/Hi. Mito Hi. tSNE on Mito Hi parameters Mito Mid/Hi (excluding Mito Mid/Lo previous Mito Lo parameters and mitotracker)

mDC’s – (HLA-DR/CD206/CD86) No Metabolic Inhibitors OVA Mitotracker tSNE2 nAFP tSNE1 tAFP Mito Hi Mito Mid/Hi Mito Mid/Lo Mito Lo OVA nAFP tAFP

CD80 ICOSLG Multi-Antigen-AdV-Transduced DC +/- IFNα Boost Trial

IFNα boost

leukapheresis

Leukapheresis/Biopsy: 30 Patients Randomized: CD8+/CD4+ PBMC: 1:1 to high dose i.v. IFNα -Multi- ELISPOT for DC immunizing -Determinant Spreading ELISPOT 3 tumor 3 , -Serum Luminex antigen i.d.,107 DC per -Tetramer Assay/phenotyping Adenovirus injection, -Avidity (A2/DR4) every other week -NK activation Tumor Biopsy: -TIL analyses -Tumor antigen analysis Analysis of antigens Analysis of additional antigens

SCHEDULE Randomize AdV/DC AdV/DC AdV/DC 50% to IFNα Leuk. #1 #1 #2 #3 Leuk. #2 Leuk. #3

day –14 day 0 day +14 day +28 day +43 day +56 (for 4 weeks) 14 days post IFNα

CMV-Tyrosinase-IRES-MART-1-SV40pA RSV-MAGEA6-BGHpA VECTOR MAP E1 AdV type 5 E3 JITC, 2019 NFĸB Signaling is Predicted to Be Dysregulated in Melanoma Patient Dendritic Cells

-log(p value) UP-regulated -12 -6 0 6 12

Sirtuin Signaling Pathway HD DOWN-regulated Toll Like Receptor Signaling Melanoma NFkB Signaling Leukocyte Extravasation Signaling

Super-pathway of Methionine Degradation 3-Phosphoinositide Biosynthesis IL8 Signaling Fatty Acid Beta-Oxidation 1 Oxidative Phosphorylation

DOWN UP

Maurer, CIR, 2020 SCENITH Analysis of Skewed Dendritic Cells tSNE clustering: DC/immune markers

Selected immune markers: J. Adamik and Krummel/Pierre: Argüello et al, Cell Metabolism 2020 scMEP CyTOF metabolic mediators examined

PD-L1high Elevated expression in activated DC Elevated expression in tolerogenic DC

PFK B4 ENO PD-L1high high high PD-L1 PD-L1 1 PD-L1high PD-L1high TOMM20

PD-L1high IDH2 PD-L1high

NDUFB 8 mTOR PD-L1high P

PD-L1high PD-L1high PD-L1high HADH Hartmann FJ, Nature A Biotechnology 2020 Adamik & Bendall Lab The Parker Translational Suite: Deep Immune Profiling

Discovery Germline WES HLA Determination Samples (MHC Class I and II)

Tumor WES Neo-epitope Prediction TCRseq (tumor & blood) Tumor Genome/TMB RNAseq (tumor & blood) TME Gene Expression Signature Tumor Multiparameter Tissue Imaging (Including PDL1) Immune Profile CyTOF and Flow C. Multiplex Cytokine Blood (plasma/serum) Patient Samples Samples Patient Stool/Microbiome Computational Emerging Deep Learning Clinical Technologies Metadata

Harmonized methods of collection and processing at a central biorepository Anti-tumor T Cell Responses Antigens Matter: The shared DIPG brain tumor antigen H3.3K27M promotes clinically relevant T cells; ACT may be more potent. AFP antigen induces metabolic suppression in DC with downstream impact on T cells.

Checkpoint Molecules Matter: High CTLA-4 and PD-1 gene expression networks on lymphocytes correlated with inferior clinical outcomes.

Signaling and Costimulation Matters: Patient DC have significant NFkB signaling defects that negatively impact costimulation (including ICOSL).

Metabolism Matters: cellular metabolism is impacted by tumors, and defects in metabolic pathways are correlates of key immune molecule expression, in vivo antitumor immunity and clinical outcomes. Acknowledgements Butterfield Lab East and West/Past and Present: Patricia Santos, Ph.D., Deena Maurer, Ph.D., Juraj Adamik, Ph.D.,; Paul Munson, Ph.D., Immunologic Monitoring and Cellular Products Lab, John M. Kirkwood, Ahmad Tarhini, Hussein Tawbi (Melanoma); Greg Delgoffe; D. Stroncek, NIH; The Parker Institute for Cancer Immunotherapy Hideho Okada’s Lab/UCSF NIH RO1 CA104524, NIH RO1 CA 138635 P50 CA121973-03 Skin SPORE (Kirkwood),

NanoString: Sarah Warren, Afshin Hossein, Greg Gonye. UCSF: Krummel lab/Stanford: Bendell lab