David A. Tice

Supplementary Figure S1. Analytical characterization of INT016-ADCs; Supplementary Figure S2. Validation of B7-H4 antibodies for use in IHC; Supplementary Figure S3. Relationship between B7-H4 expression level and heterogeneity in the studied human triple-negative cohort; Supplementary Figure S4. Binding of antibody INT016 to HEK 293 cells stably expressing human, mouse, or cynomolgus monkey B7-H4; Supplementary Figure S5. Binding of antibody INT016 to human breast cancer cell lines and to HT29 cells stably expressing human B7-H4; Supplementary Figure S6. Internalization and lysosomal trafficking of INT016; Supplementary Figure S7. In vitro stability of INT016-ADCs in mouse and cynomolgus monkey serum; Supplementary Figure S8. In vitro cytotoxicity of INT016-ADCs in HT29 and HT29-huB7-H4 isogenic cell lines; Supplementary Figure S9. In vivo efficacy of INT016-ADCs in the MX-1 xenograft model; Supplementary Figure S10. Growth rate analysis of MX-1 in vivo efficacy study comparing INT016-ADCs from days 14–40.

Surface plasmon resonance; In vitro cytotoxicity assays; In vitro proliferation assays; Internalization assays; Subcellular localization microscopy; Immunoblotting; Statistical analysis

Supplementary Table S1. Primary antibodies used for immunoblotting; Supplementary Table S2. Characterization of ADCs evaluated in this study; Supplementary Table S3. B7-H4 expression in human normal tissue; Supplementary Table S4. Binding affinity of anti-B7-H4 antibody INT016 Fab to human, cynomolgus monkey, and mouse B7-H4, measured by surface plasmon resonance.

Supplementary Figure S11. In vitro cytotoxicity of the TOP1i warhead AZ’0132 to HT29 and HT29-huB7-H4 cells; Supplementary Figure S12. Study design for pharmacodynamic and pharmacokinetic analysis of AZD8205 in HT29 and HT29-huB7-H4 mouse xenograft models; Supplementary Figure S13. DNA damage response signaling in HT29-huB7-H4 and MX-1 cells treated with AZD8205 or the TOP1i warhead AZ’0132; Supplementary Figure S14. Accumulation of AZD8205 and changes in epithelial cell density in HT29 and HT29-huB7-H4 tumor xenografts over time; Supplementary Figure S15. Correlation of B7-H4 mean OD and gene expression in TNBC PDX models; Supplementary Figure S16. Impact of homologous recombination deficiency (HRD) on sensitivity to the TOP1i warhead AZ’0132 in vitro with SK-OV-3 ovarian cancer isogenic cells; Supplementary Figure S17. SLFN11 expression in PDX models; Supplementary Figure S18. Analysis of SLFN11 expression and AZD8205 response in PDX.

Purpose:We evaluated the activity of AZD8205, a B7-H4–directed antibody–drug conjugate (ADC) bearing a novel topoisomerase I inhibitor (TOP1i) payload, alone and in combination with the PARP1-selective inhibitor AZD5305, in preclinical models.Experimental Design:IHC and deep-learning–based image analysis algorithms were used to assess prevalence and intratumoral heterogeneity of B7-H4 expression in human tumors. Several TOP1i-ADCs, prepared with Val-Ala or Gly–Gly–Phe–Gly peptide linkers, with or without a PEG8 spacer, were compared in biophysical, in vivo efficacy, and rat toxicology studies. AZD8205 mechanism of action and efficacy studies were conducted in human cancer cell line and patient-derived xenograft (PDX) models.Results:Evaluation of IHC-staining density on a per-cell basis revealed a range of heterogeneous B7-H4 expression across patient tumors. This informed selection of bystander-capable Val-Ala–PEG8–TOP1i payload AZ14170133 and development of AZD8205, which demonstrated improved stability, efficacy, and safety compared with other linker–payload ADCs. In a study of 26 PDX tumors, single administration of 3.5 mg/kg AZD8205 provided a 69% overall response rate, according to modified RECIST criteria, which correlated with homologous recombination repair (HRR) deficiency (HRD) and elevated levels of B7-H4 in HRR-proficient models. Addition of AZD5305 sensitized very low B7-H4–expressing tumors to AZD8205 treatment, independent of HRD status and in models representing clinically relevant mechanisms of PARPi resistance.Conclusions:These data provide evidence for the potential utility of AZD8205 for treatment of B7-H4–expressing tumors and support the rationale for an ongoing phase 1 clinical study (NCT05123482).See related commentary by Pommier and Thomas, p. 991

PDF file - 98K, Supplementary Figure S4: Caspase activation by G6T8.

PDF file - 63K, Identification of BRAFV600E splice variant lacking exons 2-10 in dabrafenib resistant WMD009 tumour and derived cell line.

PDF file - 85K, Supplementary Figure S2: Specificity of TRAILR2-induced cell killing. TRAIL-sensitive cell lines were incubated with 100pM G6T8 and different concentrations of soluble TRAILR2-Fc fusion protein.

Supplementary Figures 1-14; Supplementary Tables 1-3. Supplementary Figure 1. Lead antibody 80PH3 is a potent inhibitor of recombinant ADAM17 Supplementary Figure 2. 80PH3 is not a potent inhibitor of cellular ADAM17 Supplementary Figure 3. MEDI3622 is highly selective for ADAM17 and does not inhibit ADAM10 or MMP12 Supplementary Figure 4. MEDI3622 does not compete for binding to cellular ADAM17 with the ADAM17 monoclonal antibody 9301 Supplementary Figure 5. MEDI3622 inhibits cellular mouse ADAM17 Supplementary Figure 6. Cell surface levels of HER pathway proteins in OE21 esophageal cancer cells Supplementary Figure 7. The half-life of MEDI3622 in rats is approximately 8 days Supplementary Figure 8. Several phosphorylation sites in EGFR are inhibited by MEDI3622 Supplementary Figure 9. Exposure to MEDI3622 reduces levels of phospho-SRC and phospho-YES Supplementary Figure 10. Percent activated EGFR predicts cetuximab sensitivity in a series of Head and Neck PDX models Supplementary Figure 11. Proliferation of COLO205 colon cancer cells is independent of the HER pathways Supplementary Figure 12. MEDI3622 does not inhibit HER pathways in Colo205 tumors Supplementary Figure 13. Predictive value of ADAM17, EGFR, HER2, and HER3 mRNA levels for sensitivity of cell lines to MEDI3622 Supplementary Figure 14. Sensitivity to MEDI3622 is not predicted my mRNA levels of ADAM1, HER2 OR HER3 in head and neck PDX models Supplementary Table 1. Correlation of MEDI3622 and cetuximab anti-proliferative activity Supplementary Table 2. Identification of ADAM17 substrates in COLO205 cells by SILAC proteomics Supplementary Table 3. Identification of ADAM17 substrates in H358 lung cancer cells by SILAC proteomics