2017 Korean Society of Gynecologic Oncology Symposium An integrative approach to cancer precision medicine Sung-Yup Cho, M.D., Ph.D. Ewha Institute of Convergence Medicine EWHA WOMANS UNIVERSITY MEDICAL CENTER
The Precision Medicine Initiative (I) In his 2015 State of the Union address, President Obama announced that he's launching the Precision Medicine Initiative. Precision medicine is an emerging approach for disease prevention and treatment that takes into account people s individual variations in genes, environment, and lifestyle. The Precision Medicine Initiative will generate the scientific evidence needed to move the concept of precision medicine into clinical practice. http://syndication.nih.gov/multimedia/pmi/infographics/pmi-infographic.pdf
The Precision Medicine Initiative (II) http://syndication.nih.gov/multimedia/pmi/infographics/pmi-infographic.pdf
Cancer Precision Medicine
Next-Generation Sequencing (NGS) http://www.corning.com/uploadedfiles/lifesciences/pdfs/axygen_pdfs/ngs%20overview.pdf
Sequencing cost and data output http://www.genome.gov/sequencingcosts/ Mol Cell. 2015 May 21;58(4):586-97
International consortiums for cancer genomics
Genomic alterations of ovarian cancers PARP inhibitor PI3K inhibitor Wee1 inhibitor Best Pract Res Clin Obstet Gynaecol. 2016 pii: S1521-6934(16)30142-0 Nature. 2011 Jun 29;474(7353):609-15
Integration of genomics and drug test Mol Cells. 2016 Feb;39(2):77-86
Patient-derived xenografts (PDXs) PDXs are established by the transfer of patient tumors into immunodeficient mice 10
Patient-derived xenografts (PDXs) PDX models retain many of the key characteristics of patients tumors including histology, genomic signature, cellular heterogeneity, and drug responsiveness. These models are valuable for diverse drug development processes including biomarker development, preclinical drug testing, co-clinical trials, and personalized drug selection. Finally, development of mutation-specified PDX collections by integrating sequencing data will provide novel opportunities for therapeutic optimization, improved clinical outcomes, and precision cancer medicine. 11
NSG Mice Deficient in multiple cytokine signaling pathways NOD-scid-IL2Rg null (NSG) No T, B or NK cells Long life span (>15 months) Enhanced binding to hcd47 by NOD SIRP-a Reduced dendritic cell & macrophage function Platform for developing future models Completely deficient adaptive immune system and severely deficient innate immune system 12
PDX workflow Stage 1: Tumor Procurement Hospital notifies potential tumor specimens Clinician place the tumor sample into the refrigerator The courier is ordered to pick up samples Technician pick up samples and transport the tumor samples into the animal operation room Stage 2: Tumor Registration Generate the animal ID number Record the engraftment injection process Create the cage card for the cage Stage 3: Tumor Engraftment Stage 4: Tumor Monitoring Shave and notch mice in preparation for injection Anesthetize mice Transfer tumor sample and media from original tube onto a petri dish Cut the tumor up into fragments for engraftment Engraft tumor fragments into mice Place all genomics and histology samples in the storage areas Monitor the cage for signs of tumor growth for the next 3 months Update the tumor model status weekly in the Tumor Log When a tumor reach 1000mm³ in size, the tumor graduation process begin Stage 5: Tumor Graduation Stage 6: Tumor Cryopreservation Obtain the animal bearing the P0 tumor Dissect into trocar size pieces Transfer in to cryovials (5 fragments per vial) w/ cryomedia Transfer into freezing tank for permanent storage 13
Patient tumor samples for PDX model 14
Trocar injection procedure for tumor engraftment 15
PDX model details Model Details PDX ID: 14081902110 1 Primary Site: Stomach Tumor Site: Stomach Hospital: SNUH Diagnosis: Adenocarcinoma TNM Stage 3a Lauren Type: Intestinal Patient Sex: Male Age: 81 Engraftment Host Strain: NSG Model Characterization Implantatio n Site: Subcutaneous Race / Ethnicity: Sample Type: Histology: Patient tumor P0 Xenograft tumor Asian / Korean Fragment NGS Data WES: Blood Xenograft RNA-seq: Patient nontumor Xenograft 16
PDX resource status Gastric cancer Adenocarcinoma Lymphoma Unknown 156 Graduation Lymphoma Primary tumor 48 51 38 Metastatic tumor 11 3 5 59 54 76 73 44 Unknown Breast cancer ER+ 4 HER2+ 7 TNBC 35 43 8 1 Phyllodes 1 Unknown 26 Colon cancer Primary 35 Metastatic 41
PDX models for ovarian cancers Gynecol Oncol. 2015 Aug;138(2):486-91
Overview of gastric cancer Gastric cancer Third leading cause of cancer-related deaths in the world Heterogeneous disease: TCGA classification Epstein-Barr virus (EBV)-positive Microsatellite instable (MSI) Genomically stable (GS) Chromosomal instability (CIN) Standard of care for gastric cancer: Oxaliplatin, 5-fluorouracil (5-FU) Approved targeted drugs for gastric cancer: only 2 drugs trastuzumab (ERBB2 antagonist), - ramucirumab (VEGFR2 antagonist) Additional molecular targets and targeted drugs are required 19
Genomic alteration profiles for Korean gastric cancer patients Amplification of BCL2L1: 18.4% 20 PNAS 2015 Oct 6;112(40):12492-7
Synergistic effect of BCL2L1 inhibitor-based combination therapy Gastric cancer cell lines Gastric cancer PDX models PNAS 2015 Oct 6;112(40):12492-7 21
Overview of colorectal cancer (CRC) The third most common cancer worldwide and ranks as the fourth most prevalent cause of cancer-related deaths Heterogeneous characteristics in terms of genomic alterations, expression signature and drug responsiveness CMS1: MSI immune CMS2: Canonical CSM3: Metabolic CMS4: Mesenchymal (Guinney J et al., Nat Med. 2015, 21(11):1350-6) Patients with mutations in either KRAS (30% - 45% frequency) or BRAF (5% - 15% frequency) have a worse prognosis, and are resistant to anti-egfr treatments such as panitumumab and cetuximab
BCL2L1 expressions in CRC B C
In vivo synergistic effect of combination
Summary Genomic analysis Whole genome / exome sequencing RNA-sequencing Functional genomics Functional analysis Cell line / primary culture / 3D culture Gene function Mutagenesis Drug screening Drug responsiveness PDX models GEM models Patient data 25
Acknowledgement Ewha Womans University Charles Lee Deukchae Na Jieun Lee Wonyoung Kang Jooyoung Kim Jee Yun Han Seoyeon Min Jinjoo Kang Ahra Lee Eunhye Kwak GIST Hansoo Park Seoul National University Hospital Han-Kwang Yang Hyuk-Joon Lee Seong-Ho Kong Yun-Suhk Suh Dong-Young Noh Hyeong-Gon Moon Seock-Ah Im Gil Medical Center Won-Suk Lee Seoul National University Jong-Il Kim Jeesoo Chae