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Utilizing Histology Image Analysis to Improve Drug Response Interpretation within the Tumor Microenvironment Dr. Lorcan Sherry, CSO Company overview OracleBio is a specialized CRO providing histopathology digital image analysis services to support Pre-clinical and clinical Pharma R&D studies Companion diagnostics development Digital pathology review and biomarker research We utilise Definiens Tissue Studio and Indica Labs HALO + Hypercluster image analysis platforms Management has extensive experience (>50 years) within Pharma R&D AstraZeneca, Schering-Plough, Merck & Co Clients within USA, Asia and Europe covering large & small Pharma, Biotech & Academic Institutes www.oraclebio.com Content Utilizing histology image analysis to: 1. Quantify immunotherapy response on immune cell populations within the tumor microenvironment 2. Identify drug PD / target modulation biomarkers in xenograft tissue to support early clinical translational research 3. Select appropriate xenograft models for drug testing based on tissue region specific target expression www.oraclebio.com Quantifying immunotherapy response within xenograft tissue Humanized LNCAP cell derived xenograft Image analysis can be utilised to quantify immunotherapy effects on: Number of immune cells present within tumor and tumor microenvironment Spatial distribution of immune cells within tumor tissue Distance (proximity) of immune cells to tumor regions Tissue courtesy of www.oraclebio.com Number of immune cells within tumor & tumor microenvironment Humanized LNCAP cell derived xenograft CD8+ immune cells (brown); IHC by Aquila Histoplex www.oraclebio.com Number of immune cells within tumor & tumor microenvironment Humanized LNCAP cell derived xenograft CD8+ detection (yellow overlay) Viable Tumor Non-Tumor Analysis Parameter Data Tumor ROI Area (mm2) 24.5 Number of CD8+ cells in Tumor ROI 278 Number of CD8+ cells per mm2 Tumor ROI 11 www.oraclebio.com Spatial distribution of immune cells within tumor tissue Humanized LNCAP cell derived xenograft 1 23 45 Spatial distribution of CD8+ cells within Tumor 180 167 160 140 120 100 80 60 48 43 40 20 20 0 0 Region 1 Region 2 Region 3 Region 4 Region 5 Tumor Non-Tumor www.oraclebio.com Immune cell distance (proximity) to tumor regions No proximity rings CD8+ (brown), Tumor (red) Proximity rings: 10 x 10 microns Immune cells blue (non proximal) and red (proximal) Based on proposed drug MoA, evaluate specific innate/adaptive immune cell populations or other cell types/biomarkers: CD3, FoxP3, CD4, CD8, CD20, CD25, CD56, CD68, CD163, Ki67, PD-1 PDL-1 etc www.oraclebio.com Identifying drug PD / target modulation biomarkers in xenograft tissue Vehicle Group 1 Group 2 Group 3 Myeloma Xenografts Quantitative analysis of tumours ex vivo to confirm MoA and identify target modulation biomarkers www.oraclebio.com Target modulation biomarker p53 p53 IHC tissue image IHC Intensity +ve Low +ve Med +ve High Original p53 IHC (magnified area) Analysis ROI overlay p53 nuclei IHC detection & stain intensity classification Slide name # Nucleus Positive Viable Tumour Area (µm²) Positive Nuclei per mm2 Viable Tumour G3-33 Level 2 22,621 84,855,926 267 2 p 5 3 P o s i t iv e C e ll s p e r m m in V ia b l e T u m o u r p 5 3 P o s i t iv e C e ll s p e r m m 2 in V ia b l e T u m o u r Viable Tumour Necrotic Tumour Artefact White Space / Host Tissue 1000 800 600 400 200 0 G 1 -1 2 1200 2 1000 P o s it iv e C e lls p e r m m P o s it iv e C e lls p e r m m 2 1200 p=0.0012 GG 1 -12- 132 G 1 -2 3 G1 -2 4 800 G 1 -2 4 G 3 -3 0 G 3 -3 0 600 G 3 -3 3 400 G 3 -3 6 G 3 -3 3 G 3 -3 6 200 0 G r o u p 1G r o u p 1 G ro uG p r3o u p 3 Stats: Mann-Whitney non-parametric test www.oraclebio.com Target modulation biomarker Caspase 3 CC3 IHC Slide name G3-33 Level 1 ROI name Tumour CC3 Marker Area (µm²) No Stain Area (µm²) 15,160,638 57,448,708 % Marker Area 20.88 C C 3 % M a r k e r A r e a i n V i a b le T u m o u r p=0.0399 25 Analysis ROI overlay % M a rk e r A re a G 1 -1 2 20 G 1 -2 3 G 1 -2 4 15 G 3 -3 0 G 3 -3 3 10 G 3 -3 6 5 0 G ro u p 1 G ro u p 3 Stats: Mann-Whitney non-parametric test CC3 detection (yellow overlay) Identify drug target modulation biomarkers in CDX models Further evaluate in appropriate PDX models Potential utility as target modulation biomarkers in early clinical PK/PD studies Pre-clinical - Clinical Translational Strategy www.oraclebio.com Utilizing image analysis for xenograft model selection Aim: To select xenograft models with the highest drug target IHC staining within Tumor tissue ROI using a Tissue Multi Array (TMA) collected from different patient-derived xenografts. Mammary PDX TMA cores IHC stained for Target Image Analysis ROI Overlay Viable Tumour Non-Tumour White Space Artefact In collaboration with www.oraclebio.com Utilizing image analysis for xenograft model selection Original IHC Stained Image Formation of cells in Viable Tumour ROI Nuclei Cytoplasm Membrane Classification of cells in Viable Tumour ROI Negative Low Intensity Medium Intensity High Intensity www.oraclebio.com Utilizing image analysis for xenograft model selection Average Histological Score per PDX Approach provides valuable information on drug target or biomarker region specific tissue expression levels in xenograft tissue Provides rapid screen of xenograft samples to allow selection of the most appropriate model for oncology R&D programmes www.oraclebio.com Summary Utilizing histology image analysis can support: An in-depth understanding of immunotherapy treatment on immune cell populations within the tumor microenvironment Identification of tissue based target modulation / PD biomarkers, which may support selection of translational readouts for use in early clinical studies Detailed characterization of target expression across multiple xenograft models to better guide appropriate model selection for oncology R&D programmes www.oraclebio.com