Regulation of anti-tumor immunity through migration of immune cell subsets within the tumor microenvironment Thomas F. Gajewski, M.D., Ph.D.

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Regulation of anti-tumor immunity through migration of immune cell subsets within the tumor microenvironment Thomas F. Gajewski, M.D., Ph.D. Professor, Departments of Pathology and Medicine Program Leader, Immunology and Cancer Program of the University of Chicago Comprehensive Cancer Center

Disclosure Information Thomas F. Gajewski, M.D., Ph.D. Honoraria: BMS GSK-Bio Genzyme Eisai Clinical trial grant support: BMS GSK-Bio Eisai Incyte Roche Novartis

Founding Hypothesis Features of the tumor microenvironment could dominate at the effector phase of the anti-tumor T cell response and limit efficacy of current immunotherapies T cell trafficking into tumor Immune suppressive mechanisms at tumor site Tumor cell biology and susceptibility to immune-mediated killing Complexities of the tumor stroma (vasculature, fibrosis) Reasoned that these features could be interrogated through pre-treatment gene expression profiling of tumor site in each individual patient Such an analysis could identify a predictive biomarker profile associated with clinical response, and also highlight new biologic barriers that need to be overcome to optimize therapeutic efficacy of vaccines and other immunotherapies

Anti-tumor immune responses: Taking into account the effector phase in the tumor microenvironment Vaccine Endogenous APC Lymphatic APC Inhibitory mechanisms ncd8 ecd8 Granzymes perforin IL-2 Blood ecd8 Chemokines IFN- ecd8 Lymph node (Priming phase) Tumor microenvironment (Effector phase)

Affymetrix gene array analysis of pre-treatment biopsies from patients on melanoma vaccine sorted by clinical outcome 6 months SD or better: Includes transcripts for TCR, CXCL9, CCL21

Expression of a subset of chemokine genes is associated with presence of CD8 transcripts CD8 CCL2 CCL4 CCL5 CXCL9 CXCL10 CCL19 CCL21

A subset of melanoma cell lines expresses a broad array of chemokines SKMel23 M888 M537 3 4 1 2 1 2 Gro- IL-8 10 11 7 8 9 5 6 CCL2 CCL4 CCL5 CXCL9 CXCL10 Implies that in some cases, the melanoma tumor cells themselves can produce the entire panel of key chemokines

Superior recruitment of human CD8 + effector T cells in NOD/scid mice bearing chemokine-high M537 melanomas Blood Spleen Tumor ( Chemokine-high ) ( Chemokine-low )

Chemokine-mediated recruitment of CD8 + effector T cells into tumor microenvironment Effector CD8 + T cells upregulate expression of CCR1, CCR2, CCR5, and CXCR3 Migration supported by 6 chemokines that act via these receptors: CCL2, -3, -4, -5 and CXCL9, -10 A subset of melanoma cell lines expresses a range of chemokines capable of recruiting CD8 + effector cells in vitro and in vivo Experiments aimed at determining the most critical of these chemokines to express in the tumor microenvironment to promote optimal recruitment are ongoing Harlin et al. Can. Res. 2009

Two broad categories of tumor microenvironments defined by gene expression profiling and confirmatory assays CD8 IHC A B Gajewski, Brichard Cancer J. 2010 T cell poor Lack chemokines for recruitment Low indicators of inflammation T cell rich Chemokines for T cell recruitment CD8 + T cells in tumor microenvironment Broad inflammatory signature Apparently predictive of clinical benefit to several vaccines

Two broad categories of tumor microenvironments defined by gene expression profiling and confirmatory assays A B CD8 IHC T cell poor Why are tumors that contain activated CD8 + T cells not rejected spontaneously? Gajewski, Brichard Cancer J. 2010 Lack chemokines for recruitment Low indicators of inflammation T cell rich Chemokines for T cell recruitment CD8 + T cells in tumor microenvironment Broad inflammatory signature Apparently predictive of clinical benefit to several vaccines

Two broad categories of tumor microenvironments defined by gene expression profiling and confirmatory assays A B CD8 IHC Gajewski, Brichard Cancer J. 2010 T cell poor Lack chemokines for recruitment Low indicators of inflammation What are the innate immune mechanisms T cell rich that promote spontaneous T cell priming in a subset of patients? Chemokines for T cell recruitment CD8 + T cells in tumor microenvironment Broad inflammatory signature Apparently predictive of clinical benefit to several vaccines

Why are melanomas that do attract CD8 + T cell not rejected spontaneously? IDO (indoleamine-2,3- dioxygenase) PD-L1 (engages PD-1) CD4 + CD25 + FoxP3 + Tregs T cell anergy (B7-poor) Immunol. Rev. 2006, Clin. Can. Res. 2007

IHC for IDO, FoxP3, and PD-L1 shows expression in distinct cell subsets in melanoma metastases A: IDO B: FoxP3 C: PD-L1

Correlated expression of IDO, FoxP3, and PD-L1 transcripts in individual tumors Note: these are highest in tumors that contain CD8 + T cells

Is there a causal relationship between the accumulation of CD8 + T cells and the presence of immune inhibitory pathways? It is assumed that the tumor establishes an immune suppressive microenvironment so that T cells that infiltrate become inhibited However, we observe higher expression of immune inhibitory pathways in tumors that contain T cells New hypothesis: The expression of IDO and PD-L1, and the accumulation of Tregs, may depend upon the infiltration of CD8 + T cells in the tumor site These might be induced by specific factors produced by activated CD8 + T cells To test these notions, in vivo mouse models were utilized

Supernatant from activated human CD8 + T cells recruits sorted CD4 + CD25 + T cells in a CCL22-dependent fashion

Superior migration of human Tregs into melanoma xenograft when CD8s are co-transferred

Summary of regulation of immune suppressive mechanisms in the tumor microenvironment The three major immune inhibitory mechanisms confirmed to be present in the melanoma tumor microenvironment appear to be immuneintrinsic, driven by CD8 + T cells and not driven by the tumor For IDO and PD-L1, IFN- is the major mediator For Tregs, CCL22 production by CD8 + effector cells is the major mediator Blockade of these mechanisms therefore represent attractive strategies to restore antitumor T cell function and promote tumor rejection in patients

Strategies to block immune inhibitory mechanisms tested in mouse models and being translated to the clinic IDO inhibition 1-methyltryptophan (RAID program) New more potent IDO inhibitors (Incyte) Blockade of PD-L1/PD-1 interactions Anti-PD-1 and anti-pd-l1 mabs (Medarex/BMS) Depletion of CD4 + CD25 + FoxP3 + Tregs Ontak (IL-2/DT fusion) Daclizumab (anti-il-2r mab) Ex vivo bead depletion of CD25 + cells from T cell product for adoptive transfer Anergy reversal Introduction of B7-1 into tumor sites Homeostatic cytokine-driven proliferation T cell adoptive transfer into lymphopenic recipient Exogenous IL-7/IL-15 Decipher molecular mechanism and develop small molecule inhibitors to restore T cell function Combinations of negative regulatory pathway blockade Synergy between blockade of 2 or more pathways

Anti-PD-1 mab phase I (MDX-1106; BMS 936558): Tumor response 60.00 40.00 20.00 0.00-20.0-40.0-60.0-80.0-100 Melanoma New lesions after cycle 1 Patients ~30% response rate also seen in NSCLC and renal cell carcinoma Sznol et al. ASCO 2010

What initiates spontaneous T cell priming and recruitment in a subset of melanomas? Melanoma metastases that contain T cell transcripts also contain transcripts known to be induced by type I IFNs A: IRF1 B: IFN-induced p30

Implantation of B16 melanoma results in IFN- production in the tumor-draining lymph node IFN- mrna in DLN cells 0.0000002 0.00000018 0.00000016 0.00000014 0.00000012 0.0000001 0.00000008 0.00000006 0.00000004 0.00000002 0 w/o tumor w/ B16 B6 129

Multiple tumor types elicit IFN- production in the tumor-draining lymph node A: IFN- mrna in DLN cells B: IFN- mrna based on CD11c

Host IFN- R is critical for generating a spontaneous tumor-specific T cell response A: IFN- Rko B: Stat1ko

New questions surrounding IFN- -centered innate immune response to tumors 1. What are the tumor-derived factors that induce IFN- on host CD11c + cells, and through what receptor system? 2. By what mechanism is IFN- promoting cross-priming of host CD8 + T cells by DCs?

What are the APC defects in type I IFNRko (or Stat1ko) mice? Bone marrow chimera and adoptive transfer experiments map the defect to the level of host APCs Apparently normal: Numbers of dendritic cell subsets in spleen and tumor-draining LNs (mdc, CD8 DC, pdc) Expression of MHCI/II, CD40, B7-1, B7-2 by these DC subsets Ability of DCs to stimulate naïve CD8 + TCR Tg T cells in vitro Migration of DCs from skin to lymph node (FITC painting) Expression of class I/SIY peptide complexes (using TCR tetramer) on intratumoral APCs (CD11b +, CD11c + )

Anti-tumor immune responses: Working model for innate immune signals and tumor antigen cross-presentation IFN- IFN- CD8 DC pdc? mdc? Lymphatic CD8 DC pdc? mdc? Tumor-derived factors: HMGB1? DNA? RNA? UA? ATP? ncd8 ecd8 IL-2 Blood ecd8 ecd8 Lymph node Tumor microenvironment

Conclusions Multiple key factors in the tumor microenvironment linked to immune-mediated tumor control depend on regulated recruitment of inflammatory cell subsets This includes the priming phase (CD8 + DC recruitment), the effector phase (CD8 + effector cell recruitment) and negative regulation (Treg recruitment) CD8 + effector T cells appear to be recruited via CCL2-5 and/or CXCL9-10, whereas Tregs are largely recruited via CCL22 produced by activated CD8 + T cells Innate immune recognition of tumor, when it does occur, drives expression of Type I IFNs Type I IFN signals drive recruitment of the CD8 + DC subset-- participating chemokine(s) currently being evaluated Understanding these aspects should enable the development of new interventions to modify the microenvironment and better support T cell-mediated rejection

Acknowledgments Melanoma gene array/ Chemokines/Tregs Helena Harlin Yuan-yuan Zha Ruth Meng Amy Peterson Mark McKee Craig Slingluff Functional genomics core Type I IFNs Mercedes Fuertes Robbert Spaapen Aalok Kacha Justin Kline David Kranz Hans Schreiber Ken Murphy Uncoupling negative regulation Robbert Spaapen Justin Kline Yuan-yuan Zha Christian Blank Amy Peterson Ian Brown Collaborative vaccine/gene array data Gerold Schuler (Erlangen group) Vincent Brichard (GSK-Bio)