Towards A New Generation of Cancer Models UK Interdisciplinary Breast Cancer Symposium th January Mathew Garnett

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1 Towards A New Generation of Cancer Models UK Interdisciplinary Breast Cancer Symposium th January 2017 Mathew Garnett 1

2 Precision Cancer Medicine molecular biomarker Diagnosis Prognosis Therapy 2

3 Targeted Therapies in NSCLC Crizotinib, Ceritinib Osimertinib, Erlotinib, Gefitinib Crizotinib 3

4 Number of cell models Cancer Models for Precision Medicine Number of Cancer Models Per Sub-type 300 Number of Cancer Models Per Tissue Most cancer genes occur at 2 20% frequency In the UK, 93% of cancers occur in 24 sites Number of cell lines model 3 models Cancer driver gene frequency (% of tumours) 4

5 Sanger Institute 1000 Cell Line Collection Tissue Cancer sub-type Cell lines are widely used to study cancer biology and during drug development Insufficient numbers to reflect the genetic diversity of human tumours They have adapted to 2D culture in poorly understood ways For most cancer cell lines there is little or no patient genetic data, or clinical or pathological data 5

6 Organoid Culture Efficient derivation of organoids from both normal and diseased tissue with high success rates Suitable for long-term stable propagation in vitro and cryopreservation 3D cultures which better reflect tissue of origin (e.g. histology, growth & function) 6

7 Oesophageal Cancer Two types of oesophageal cancer: ESCC Oesophageal Squamous-Cell Carcinoma OAC Oesophageal Adenocarcinoma OAC is the 8 th most common cancer globally (2012 caused 400,000 deaths) Five-year survival rates are approximately 13-18% Early-stage OAC is usually treated by surgical resection and chemotherapy Lack of good pre-clinical models 7

8 Oesophageal Adenocarcinoma Organoid Cultures OESO_009 p.2 OESO_003 p.2 OESO_005 p.3 9 organoids ~40% success rate Average of 45 days to banking >6 months in culture Linked clinical data Collaboration with Rebecca Fitzgerald (University of Cambridge) as part of the OCCAMS study 8

9 Concordance of Cancer Driver Genes Concordance of mutational signatures and gene expression between patient-matched tumour and organoid 9

10 Clonality and Clonal Dynamics Tumour Organoids Tumour Organoids time 10

11 Drug Sensitivity Testing Color Color Key Key Drugs (n = 24) sensitivity AUC 1 AUC OAC organoid cultures (n = 9) * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * PIK3CA PIK3CA * * * * * * * * * * * * * * * * * * * TP53 CAM247 CAM388 CAM412 CAM408 CAM277 CAM338 CAM401 CAM296 IC 50 <0.1 µm IC 50 < 1 µm * * * * CAM292 Mutational Signature Navitoclax Subtype Navitoclax Sapatinib Sapatinib Afatanib SCH Afatanib SCH Trametinib Trametinib Taselisib ERBB2i MEKi/ERKi BMS Taselisib Camptothecin BMS Camptothecin MK 1775 Nutlin 3a MK 1775 Nutlin 3a Olaparib Doramapimod Olaparib Doramapimod SB Dabrafenib SB Dabrafenib Linsitinib S Crizotinib Linsitinib S Crizotinib Palbociclib PD Palbociclib PD AZD7762 Crizotinib AZD7762 Crizotinib OSI 027 OSI 027 Axitinib MK 2206 Axitinib MK 2206 Alpelisib Mutational Signature Subtype Alpelisib # drugs 11

12 Patient-derived Organoid Biobanks Cancer Publication Genetic Analysis Drug Testing Prostate Gao D, et al. Cell Y Y Colon van de Wetering M, et al. Cell Y Y Pancreas Boj S, et al. Cell Y Y Liver Broutier L, et al. Nature Medicine Y Y 13 types of advanced cancers Pauli C, et al. Cancer Discovery Y Y Endometrial Girda E, et al. Int J Gynecol Cancer Y Breast Sachs N, et al. Cell Y Y Oesophageal Adenocarcinoma Francies H, et al. Submitted Y Y 12

13 >20 passages Basement membrane 13

14 Organoids Recapitulate Patient Tumours Representation of histopathological and molecular sub-types Conservation of genomic features SNV, CNV, structural, mut. signatures Retention of cancer driver genes Conservation of expression programs and sub-types Retention of intra-tumour heterogeneity (colon, oesophagus) Suitable for drug testing Suitable for xeno-tranplantation (colon, breast, pancreas) Suitable for most molecular biology experimental approaches 14

15 Human Cancer Models Initiative Wellcome Sanger Institute Cancer Research UK US National Cancer Institute (CHSL & Broad) Hubrecht Organoid Foundation Aim to make 1000 s of new cancer cell models to reflect tumour heterogeneity Focus on cancers of unmet clinical need, poorly represented, paediatric & rare cancers Genomic characterisation performed and linked to patient clinical data Data and models available as a open-access resource for academia and industry 15

16 UK Cell Models Network Genomic datasets Cambridge S hampton B ham patient samples Clinical data Derivation, Analysis & Banking Repository & Distribution Glasgow Clinical sites Drug sensitivity testing Genomics of Drug Sensitivity in Cancer ( 16

17 Derivation of 1,000 Patient-derived Cancer Models Active program Existing protocol Development required Stage/ Subtype Advanced & Metastatic Primary & Barrett s Pancreas High grade serous Triple negative & ER+ metastatic Mesotheliom a & chemorefractory Pediatric and Adult Collaborators A. Beggs A. Mirnezami R.Fitzgerald T. Underwood A. Biankin D. Jodrell J. Brenton I. McNeish R. Rintoul S. Marcinarak Established rare & pediatric cancer models can also be submitted for expansion and distribution 17

18 Sanger Institute Derivation Pipeline QC QC Primary tissue Dissociated cells Passage ~4 Tumour confirmation Freeze/thaw QC (4 passages) Number of Days Derivation Propagation Banking 25 cryovials Characterisation WGS, RNAseq Distribution Receive 7-10 fresh tissue samples per week Dedicated derivation laboratory and technical team LIMS system and database for tracking genomic and clinical datasets Integrated with Sanger Institute genomics core facility and drug testing platform 18

19 50 Banked Organoid Cultures 19

20 Derivation Progress to Date oesophagus All tumour types (n = 236 tissue samples) colon Banked (n =66) 29% 54% Failed (n =122) Projected failure rate 50% pancreas In process (n = 39) (likely to bank) 17% Common reasons for failure are poor sample quality and failure to grow 20

21 Practical Considerations For Using Organoids Are organoids difficult to derive? - There are published protocols for many tissues and the number is expanding - Requires access to high-quality fresh tissue - Typical time for derivation and banking (25 cryovials) is 2-3 months (range: 1 week 5 months) Are organoids are hard to work with? - They are more difficult to culture than cell lines - ~1 week training time to begin - Requires use of specialized medium reagents. Commercial suppliers are entering the market - Amenable to most (all) molecular biology approaches (e.g. cloning, gene-editing, imaging) Is using organoids expensive? - Derivation, expansion and banking costs ~ 1100 per culture. 50% consumbles and 50% staff - Cost to maintain in culture 2x 6 well plates is ~ 2500 per annum 21

22 Acknowledgements Wellcome Trust Sanger Institute Hayley Francies William Barendt Sara Valentini James Gilbert Julia Wilson Mike Stratton Drug Screening Team CGaP Organoid Derivation Team Oxford Big Data Institute David Wedge Cancer Research UK Maria Antonietta Cerone Tosin Sule Rachael Barber Rowena Sharpe Nic Jones Ian Walker UMC Utrecht Hugo Snippert Edwin Cuppen Hans Bos UK Cell Models Network Members MRC Hutchison Cancer Centre Xiaodun Li Maria Secrier Ahmed Miremadi Nicola Grehan Amber Grantham Shona MacRae Rebecca Fitzgerald National Cancer Institute Lou Staudt Daniela Gerhard Hubrecht Institute Marc van de Wetering Sylvia Boj Rob Vries Hans Clevers 22