Immuno-Oncology Research

Immunoassays for Immuno-oncology Research

Immuno-oncology Knowledge wins. Take the 360º view.

The discovery that cancer cells evade attacks from the immune system by manipulating immune cells at multiple checkpoints has led to the development of the new drug class of immune checkpoint modulators. Three therapeutic antibodies against two different checkpoint targets recently have been FDA approved. Many other drug candidates targeting different checkpoint pathways are in clinical trials. Ersteller: Dagmar Dietmann, 29/10/2015 PROT13-36 DMR PPX Revision 03 Affymetrix provides a wide portfolio for the immuno-oncology research space, including ELISA and bead-based multiplex immunoassays for the quantification of these important checkpoint modulators. ProcartaPlex® Human Immuno-oncology Checkpoint Panel enables simultaneous quantification of 14 checkpoint modulators.Immuno-Oncology Singleplex assays Panel are available (EPX140-15803-901) for each target included in the ProcartPlex Human Immuno-oncology Checkpoint Panel, and combinableStandardrange with additional of analytes Analytes of interest. Ersteller: Dagmar Dietmann, 29/10/2015 PROT13-36 DMR PPX Revision 03 100000

Immuno-Oncology Panel (EPX140-15803-901) 10000 ProcartaPlex® Human Immuno-oncology Checkpoint Panel Standardrange of Analytes 100000100000

1000 1000010000 MFI

10001000 100 MFI MFI 100100

10 1010

11 1.000 1.000 10.00010.000 100.000100.000 1000.0001000.000 10000.00010000.000 100000.000100000.000 1000000.0001000000.000 10000000.00010000000.000 1 pg/ml 1.000 10.000 100.000 BTLA GITR 1000.000 HVEM pg/mLIDO 10000.000 LAG-‐3 PD-‐1 PD-‐L1 100000.000 1000000.000 10000000.000 PD-‐L2 TIM-‐3 CD28 CD80 pg/ml CTLA-‐4 CD27 CD137 BTLA GITR HVEM IDO LAG-‐3 PD-‐1 PD-‐L1 100000 PD-‐L2 TIM-‐3 CD28 BTLA conc.CD80 pg/ml CTLA-‐4 MFICD27 CD137CV% MEAN blankcorr. % backcalc. 10000 S1 500000.000 14152.0 14239.5 0.4% 14168 102 S2 125000.000 9420.0 9567.0 1.1% 9466 97 1000 S3 31250.000 4494.0 4907.5 6.2% 4673 103 100 ® S4 7812.500 1548.0 1520.0 1.3% 1506 98 Standard curves for the ProcartaPlex HumanS5 Immuno-oncology1953.100 Panel.449.0 435.0 2.2% 414 101 100000 10 S6 488.300 127.5 126.0 0.8% 99 100 BTLAS7 conc. pg/ml122.100 51.0 52.0 MFI 1.4% 24 CV%100 MEAN blankcorr. % backcalc. 10000 1 blank 25.5 30.5 12.6% 0 1.000 10.000 100.000 1000.000 10000.000 100000.000 1000000.000 S1 mean blank 500000.000 28.0 14152.0 14239.5 0.4% 14168 102 10000 S2 125000.000 9420.0 9567.0 1.1% 9466 97 1000 GITR conc. pg/ml MFI CV% MEAN blankcorr. % backcalc. S3S1 100000.0031250.000 7548.0 7874.04494.0 3.0% 4907.57646 1016.2% 4673 103 1000 S2 25000.00 4920.0 4856.0 0.9% 4823 99 100 S4S3 6250.007812.500 2111.5 2093.01548.0 0.6% 1520.02037 1021.3% 1506 98 100 S5S4 1562.501953.100 658.5 657.0449.0 0.2% 435.0592 992.2% 414 101 S5 390.60 227.5 225.0 0.8% 161 100 10 10 S6S6 97.70488.300 118.0 110.0127.5 5.0% 126.0 49 1030.8% 99 100 S7 24.40 82.0 88.0 5.0% 20 94 blankS7 122.100 65.0 66.051.0 1.1% 52.0 0 1.4% 24 100 1 1 mean blank 65.5 1.00 10.00 100.00 1000.00 10000.00 100000.00 blank 25.5 30.5 12.6% 0 1.000 10.000 100.000 1000.000 10000.000 100000.000 1000000.000 100000 HVEM conc.mean pg/ml blank MFI 28.0 CV% MEAN blankcorr. % backcalc. S1 100000.00 13749.0 14247.0 2.5% 13959 101 10000 10000 S2 25000.00 7598.0 7915.5 2.9% 7718 98 GITRS3 conc. pg/ml6250.00 2886.0 3123.0 MFI 5.6% 2966 CV%102 MEAN blankcorr. % backcalc. 1000 S4 1562.50 838.0 876.0 3.1% 818 99 S1S5 390.60100000.00 248.0 7548.0229.5 5.5% 7874.0200 983.0% 7646 101 1000 100 S2S6 97.7025000.00 91.0 4920.092.0 0.8% 4856.053 1050.9% 4823 99 S7 24.40 50.0 53.5 4.8% 13 94 10 blankS3 6250.00 38.0 2111.540.0 3.6% 2093.0 0 0.6% 2037 102 100 1 S4 mean blank 1562.50 39.0 658.5 657.0 0.2% 592 99 1.00 10.00 100.00 1000.00 10000.00 100000.00 S5 390.60 227.5 225.0 0.8% 161 100

10 100000 S6 97.70 118.0 110.0 5.0% 49 103 S7IDO conc. pg/ml 24.40 MFI 82.0 CV% MEAN blankcorr.88.0 % backcalc. 5.0% 20 94 10000 blankS1 20000.000 24103.5 23990.065.0 0.3% 66.023995 981.1% 0 1 mean blank 65.5 1.00 10.00 100.00 1000.00 10000.00 100000.00

100000 HVEM conc. pg/ml MFI CV% MEAN blankcorr. % backcalc. Filename: Marketing Broschure.xlsx S1 100000.00 13749.0 14247.0 2.5% 13959 101 page 1/3 10000 S2 25000.00 7598.0 7915.5 2.9% 7718 98 S3 6250.00 2886.0 3123.0 5.6% 2966 102 1000 S4 1562.50 838.0 876.0 3.1% 818 99 S5 390.60 248.0 229.5 5.5% 200 98 100 S6 97.70 91.0 92.0 0.8% 53 105 S7 24.40 50.0 53.5 4.8% 13 94 10 blank 38.0 40.0 3.6% 0 1 mean blank 39.0 1.00 10.00 100.00 1000.00 10000.00 100000.00

100000 IDO conc. pg/ml MFI CV% MEAN blankcorr. % backcalc. 10000 S1 20000.000 24103.5 23990.0 0.3% 23995 98

Filename: Marketing Broschure.xlsx page 1/3 Immune response in immuno-oncology

The cancer immunity cycle1 describes the multiple steps in the immune systems response to a tumor. Several biomarkers, especially checkpoint molecules, play a crucial role in this response. It starts with the engulfment of tumor-derived antigens (TDA) by dendritic cells. Highly specialized dendritic cells mature and present their TDAs to T cells. Primed and activated effector T cells are formed, and tumor infiltration starts. Finally, T cells bind to tumor cells and destroy them. More tumor antigens are released and trigger the immunity cycle further.

Soluble forms of the biomarkers included in the cancer immunity cycles have been described in several publications. 2,3,4,5,6,7,8,9,10

Factors involved in the cancer immunity cycle

Step 4: Trafficking T cells to Step 3: tumors T cell priming & activation Fractalkine CD28 Active T cell IP-10 Step 4 PD-L2 Rantes CD152/CTLA-4 Blood vessel CD27 Active T cell CD80 Blood vessel CD137/4-1BB IL-2 IL-12 Step 3 HVEM GlTR Step 5: Lymph node Step 5 Infiltration of T cells into tumors Tumor microenvironment Dendritic cell ICAM-1 VEGF

Step 2 Selectins Step 6 ymph node L

Antigens Step 7 Step 2: Step 1 Cancer antigen presentation

TNF alpha IL-1 Step 6: Recognition of IFN alpha Tumor cell IL-10 cancer cells by T cells IL-4 IL-13 Step 1: Release of cancer cell Step 7: antigens Killing of cancer cells

PD-L1 PD-1 B7.1 IDO BTLA LAG-3 TIM-3 MIC TGF beta Leung et al. CTLA4 levels and ipilimumab efﬁcacy

Table 2 | Demographics of 11 melanoma patients not treated with Table 3 | Univariable Cox Proportional hazard regression analysis of ipilimumab. 5-year overall survival.

Demographic sCTLA4 200 sCTLA4 >200 p-Value Variable p-Value Hazard ratio 95% CI ≤ pg/mL (n %) pg/mL (n %)

Elisa <200 vs. >200 0.04 5.29 1.06–26.4

Sex 0.34 Male vs. female 0.97 0.97 0.26–3.66

Male 3 (100) 6 (75) Age at diagnosis 0.52 0.97 0.90–1.06

Female 0 (0) 2 (25) Breslow depth 0.67 1.02 0.94–1.11

Age 0.40 Ulcerated vs. non-ulcerated 0.51a NA NA

Average 41 52 M1abc 0.32

Primary 0.17 M1a vs. M1c 0.20 3.19 0.55–18.59

Trunk 2 (66.7) 3 (37.5) M1b vs. M1c 0.64 0.60 0.07–5.35

Extremity 0 (0) 5 (62.5) a Head and neck 1 (33.3) 0 (0) By log-rank test (Hazard ratio approached zero so log-rank test was done instead). Immuno-oncology checkpoint molecules M status 0.38 Multivariable analysis incorporating all the above variables showed that all the

M1a 5 (33.3) 4 (50) other variables except (ELISA) were not signiﬁcant. Thus, the univariable model with ELISA is the ﬁnal model. M1b 0 (0) 2 (25) CD152/CTLA-4

M1c 2 (66.7) 2 (25) Cytotoxic T-lymphocyte antigen 4 (CTLA-4) inhibits 1.00 CTLA-4 >200 1.00 CTLA-4 >200 antigen-specific T cell proliferation and cytokine CTLA-4 <200 production, qualifying CTLA-4 as target for cancer p= 0.02 0.800.80 immunotherapy. Ipilimumab, an FDA-approved monoclonal

antibody against CTLA-4, demonstrated an overall survival 0.600.60 (OS) benefit for patients with metastatic melanoma with a response rate of <25%. It has been shown that

0.40 soluble CTLA-4 levels were statistically higher in patients Overall survival 0.40 responding to Ipilimumab treatment (Figure 1).2 Overall survival 0.200.20

Figure 1: Overall 5-year survival of patients treated 0.000.00 with Ipilimumab. 0 12 24 36 48 60 0 12 24 36 48 60 Months from Ipilimumab Overall survival (5 years) of patients treated with Ipilimumab comparing Months from Ipilimumab those with greater than 200 pg/mL serum of soluble CTLA-4 (sCTLA-4)

FIGURE 2 | Overall survival after ipilimumab treatment is greater in to those with less than or equal to 200 pg/mL. sCTLA-4 levels were

patients with serum CTLA4 levels above 200 pg/mL for quantified using human sCD152/CTLA-4 Platinum ELISA from Affymetrix. ipilimumab-treated patients. Overall survival curves (5 years) of patients treated with ipilimumab comparing those with greater than 200 pg/mL PD-1serum sCTLA4 to those with less than or equal to 200 pg/mL.

Programmed cell death protein 1 (PD-1) promotes apoptosis in antigen-specific T cells and reduces apoptosis in regulatory To determine whether sCTLA4 levels correlate with survival (suppressive) T cells at the same time. Nivolumab and Pembrolizumab are FDA-approved therapeutic antibodies against in general, rather than only in those patients who are treated PD-1 for the treatment of melanoma (response rates: 40%). with anti-CTLA4, we also tested stage IV melanoma patients who FIGURE 1 | Serum sCTLA4 levels correlate with clinical benefit to had not received ipilimumab (n 11). Using the same cutoff of PD-1 ligands PD-L1 and PD-L2= ipilimumab treatment. sCTLA4 levels were measured by ELISA and 200 pg/mL, the two survival curves were not statistically different, individual values plotted according to clinical response. Values are with 33.4 and 29.6 months median OS for patients with sCTLA4 expressed as the mean value of triplicate wells. The sensitivity of the ELISA It has been shown that PD-L1 and PD-L2 are expressed on various tumor cells. Some studies indicate that high levels of 200 pg/mL and sCTLA4 >200 pg/mL, respectively (p 0.60) was 100 pg/mL. Two-tailed Mann–Whitney test was used to evaluate the ≤ = 7,11 significance of the differences between patients who received (n 9) or did soluble(Figure PD-1 3). ligands in tumor cells correlate with lower survival and response rates. = not receive (n 5) benefit from ipilimumab treatment. The cutoff sCTLA4 = level for prediction of clinical benefit was determined using a threshold of CD27DISCUSSION 200 pg/mL based on ROC curve analysis. Here, we report serum sCTLA4 levels of ipilimumab-treated Thepatients TNF withreceptor advanced superfamily melanoma member from samples CD27 collected is required prior tofor generation and long-term maintenance of T cell immunity. 9 for patients with sCTLA4 200 pg/mL and sCTLA4 >200 pg/mL, Theipilimumab interaction therapy. between Our preliminary CD27 and findings its ligand, show CD70, that elevated is implicated in regulating cellular immune responses to cancer. ≤ respectively (Figure 2). Multivariable analysis showed that no serum levels of sCTLA4 are associated with clinical benefit to ipil- covariate other than elevated sCTLA4 level was associated with CD80imumab in this initial cohort. Patients with elevated sCTLA4 also prolonged 5-year OS (Table 3). showed a significant survival benefit over those with low sCTLA4 CD80 is present on activated B cells and monocytes and functions as costimulatory signal which is needed for T cell www.frontiersin.org activation and survival. CD80 hasMay two 2014 ligands, | Volume 4CD28 | Article and 110 | 3CTLA-4. Soluble CD80 restores T cell activation and overcomes PDL-1 mediated immune suppression.8

HVEM-BTLA

Herpes virus entry mediator (HVEM) is also known as TNF receptor superfamily member 14. HVEM is expressed on certain tumor cell types (e.g., melanoma) and on tumor-associated endothelial cells. Interestingly, HVEM is the ligand of B- and T-lymphocyte attenuator (BTLA). It is exceptional that a TNF family member interacts with an immunoglobulin supergene family member. Evidence suggests that the HVEM-BTLA pathway is an inhibitory checkpoint for dendritic cell homeostasis in lymphoid tissue.

LAG-3

Lymphocyte activation gene 3 protein (LAG-3) is another immune checkpoint receptor, which is being investigated in various ongoing trials. It has been shown that soluble human LAG-3 amplifies tumor-specific immunity.7 ProcartaPlex® Immunoassays

ProcartaPlex® Immuno-Oncology Checkpoint Panel ELISA Format Part Number EPX140-15803-901 BTLA Platinum ELISA BMS2217 CD137/4-1BB Platinum ELISA BMS289 BTLA PD-L2 CD152/CTLA4 Platinum ELISA BMS276 GlTR TIM-3 CD27 Instant ELISA® BMS286INST HVEM CD28 CD28 Platinum ELISA BMS290 IDO CD80 CD80 Instant ELISA® BMS291INST LAG-3 CD137/4-1BB GlTR Platinum ELISA BMS2210 PD-1 CD27 HVEM Platinum ELISA BMS2218 ICAM-1 Platinum ELISA BMS201 PD-L1 CD152/CTLA Platinum ELISA BMS241 Instant ELISA® BMS201INST ProcartaPlex® Simplex Kits Part Number IDO Platinum ELISA BMS2213 IL-2 EPX01A-10221-901 IFN alpha Ready-SET-Go!® ELISA 88-7389 ® Fractalkine EPX01A-12121-901 Instant ELISA BMS216INST Platinum ELISA BMS216 CD152/CTLA4 EPX01A-10276-901 IL-1 alpha Platinum ELISA BMS243/2 CD27 EPX01A-10286-901 IL-10 Ready-SET-Go!® ELISA 88-7106 CD80 EPX01A-10291-901 High Sensitivity ELISA BMS215HS GlTR EPX01A-12210-901 Instant ELISA® BMS215INST ICAM-1 EPX01A-10201-901 Platinum ELISA BMS215/2 IL-10 EPX01A-10215-901 IL-12p70 High Sensitivity ELISA BMS238HS ® IFN alpha EPX01A-10216-901 IL-13 Ready-SET-Go! ELISA 88-7439 Instant ELISA® BMS231INST IL-4 EPX01A-10225-901 Platinum ELISA BMS231/3 IL-12p70 EPX01A-10238-901 IL-1 beta Ready-SET-Go!® ELISA 88-7261 CD154 (CD40 Ligand) EPX01A-10239-901 High Sensitivity ELISA BMS224HS IL-1 alpha EPX01A-10243-901 Instant ELISA® BMS224INST VEGF-A EPX01A-10277-901 Platinum ELISA BMS224/2 ® IP-10 EPX01A-10284-901 IL-2 Ready-SET-Go! ELISA 88-7025 High Sensitivity ELISA BMS221HS Rantes EPX01A-10287-901 Instant ELISA® BMS221INST CD137/4-1BB EPX01A-10289-901 Platinum ELISA BMS221/2 CD28 EPX01A-10290-901 IL-4 Ready-SET-Go!® ELISA 88-7046 TWEAK EPX01A-12006-901 High Sensitivity ELISA BMS225HS VEGF-D EPX01A-12076-901 Instant ELISA® BMS225INST IL-12p40 EPX01A-12090-901 Platinum ELISA BMS225/2 IP-10 Instant ELISA® BMS284INST TSLP EPX01A-12164-901 Platinum ELISA BMS6018 LAG-3 EPX01A-12211-901 LAG-3 Platinum ELISA BMS2211 PD-L1 EPX01A-12212-901 PD-1 Platinum ELISA BMS2214 IDO EPX01A-12213-901 PD-L1 Platinum ELISA BMS2212 PD-1 EPX01A-12214-901 PD-L2 Platinum ELISA BMS2215 ® PD-L2 EPX01A-12215-901 Rantes Instant ELISA BMS287/2INST TIM-3 Platinum ELISA BMS2219 BTLA EPX01A-12217-901 VEGF-A Platinum ELISA BMS277/2 HVEM EPX01A-12218-901 OX40 (CD134) Platinum ELISA BMS296 TIM-3 EPX01A-12219-901 CD154 (CD40 Ligand) Platinum ELISA BMS239 Instant ELISA® BMS239INST CD258 (LIGHT) Ready-SET-Go!® ELISA 88-7258 CD276 (B7-H3) Ready-SET-Go!® ELISA 88-50370 CD40 Platinum ELISA BMS265 TSLP Ready-SET-Go!® ELISA 88-7497 TWEAK Instant ELISA® BMS2006INST References 1. Chen D. S., et al. Oncology meets immunology: the cancer-immunity cycle. Immunity 39(1):1–10 (2013). 2. Leung A. M., et al. Clinical benefit from ipilimumab therapy in melanoma patients may be associated with serum CTLA4 levels. Frontiers in Oncology 4:1–5 (2014). 3. Ostrand-Rosenbert S., et al. Novel strategies for inhibiting PD‑1 pathway‑mediated immune suppression while simultaneously delivering activating signals to tumor‑reactive T cells. Cancer Immunology, Immunotherapy 64:1287–1293 (2015). 4. Heo S. K., et al. The presence of high level soluble herpes virus entry mediator in sera of gastric cancer patients. Experimental and Molecular Medicine 44(2):149–158 (2012). 5. Taylor L., et al. Identification of a soluble OX40 isoform: development of a specific and quantitative immunoassay. Journal of Immunological Methods 255(1–2):67–72 (2001). 6. Casati C., et al. Soluble Human LAG-3 Molecule Amplifies the In vitro Generation of Type 1 Tumor-Specific Immunity. Cancer Research 66(8):4450–4460 (2006). 7. Wang L., et al. Serum levels of soluble programmed death ligand 1 predict treatment response and progression free survival in multiple myeloma. Oncotarget 1(6):41228–41236 (2015). 8. Haile S. T., et al. Soluble CD80 Restores T Cell Activation and Overcomes Tumor Cell Programmed Death Ligand 1–Mediated Immune Suppression. Journal of Immunology 191(5):2829–2836 (2013). 9. Huang J., et al. Soluble CD27-pool in humans may contribute to T cell activation and tumor immunity. Journal of Immunology 190(12):6250–6258 (2013). 10. Tieu R., et al. TIM-3, a Possible Target for Immunotherapy in Cancer and Chronic Viral Infections. Austin Virology and Retro Virology 1(2): 1–12 (2014). 11. Okazaki T., et al. PD-1 and PD-1 ligands: from discovery to clinical application. International Immunology 19(7):813–824 (2007).

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