Ravi Salgia, MD, PhD Professor and Chair, Medical Oncology and - PowerPoint PPT Presentation

ics of lung cancer—Utilization of disease registries in the precision world Ravi Salgia, MD, PhD Professor and Chair, Medical Oncology and Therapeutics Research City of Hope 04/04/2018

Objectives • Lung Cancer Overview • Heterogeneity • Macro- and Micro-Heterogeneity • Spatial- and Temporal-Heterogeneity • Registry of Hope • City of Hope Thoracic Oncology Registry (THOR) • THOR and Data Analysis

Lung Cancer Severity and Impact Siegel et. al. Cancer Statistics, 2018

NSCLC SCLC 85% of all cases of lung cancer 15% of all cases of lung cancer Small cell carcinoma >90% Adenocarcinoma ~40% Combined small cell carcinoma <10% Squamous cell carcinoma ~25-30% Variant <5% Large cell carcinoma ~10-15% 5-year relative survival rates 5-year relative survival rates Stage I: ~66-82% Stage I: ~31% Stage II: ~19% Stage II: ~47-52% Stage III: ~8% Stage III: ~19-36% Stage IV: ~2% Stage IV: ~6% Markers of NSCLC subtypes Markers of Neuroendocrine Differentiation TTF-1 Chromogrannin A Napsin A Synaptophysin CK7 Leu-7 p63 Bombesin or Gastrin Releasing Peptide CK5/6 Fast growing and aggresive Grows more slowly Surgery possible in <10% of patients Surgery possible in 35% of patients >80% chemotherapy response rate <40% chemotherapy response rate Chemotherapy indicated in All Patients Chemotherapy indicated in Select Patients Treatment limited to Platinum chemo and radiation Targeted and immunotherapy available MORE AND MORE MORE WORK NEEDS TO BE DONE THERAPEUTIC OPTIONS IN TERMS OF BIOLOGY AND TO BECOME AVAILABLE THERAPEUTICS

Case Example of Various Heterogeneities Temporal Spatial Macro Micro Mambetsariev et. int. Salgia, BMC Cancer, 2018

Macro-Heterogeneity Salgia Expert Rev Mol Diagn. 2016

Micro-Heterogeneity in lung cancer Hensing, Mambetsariev, Salgia; 2017

Micro-Heterogeneity in lung cancer Hensing, Mambetsariev, Salgia; 2017

City of Hope: Registry Conception • Identified a need for clinical data collection and translation research integration • Assessed the importance of inter- and intra-disease team communication and collaboration (both clinical and research) • Incorporated the previous lessons with databases to build the Thoracic Oncology Registry (THOR) • Observed innumerable examples of macro- and micro-heterogeneity; spatial- and temporal- heterogeneity • Addressed the need for disease team focused registries by implementing the Registry of Hope platform Mambetsariev et int. Salgia, 2018

City of Hope Experience: THOR SOP • 300 page-document detailing the procedures for the consenting process, enrollment of patients, and data abstraction of clinical information into THOR. Mambetsariev et int. Salgia, 2018

THOR Infrastructure Creation and Development Process Medical Oncology : Pa#ent Registry Template : Ravi Salgia -Curated various literature and publicly available Karen Reckamp databases for data dicAonary templates Marianna Koczywas Personnel : Isa Mambetsariev Erminia Massarelli Tarrah Kirkpatrick Radiology : Lalit Vora THOR Data Dic#onary Crea#on: THOR Data Dic#onary Modifica#on: -Combined various databases, guidelines, and medical -Modified the Data DicAonary based on individual City Radia#on Oncology : terminology in one data dicAonary of Hope modificaAons and preferences Sagus Sampath Personnel : Isa Mambetsariev Personnel : Isa Mambetsariev Rebecca Pharaon Rebecca Pharaon Blake Hewelt Blake Hewelt Pathology : Peiguo Vijay Nair Tarrah Kirkpatrick Chu Tarrah Kirkpatrick Surgery : Jae Kim Data Dic#onary Upload : Data Dic#onary Update : Dan Raz IniAal REDcap upload for immediate data THOR data dicAonary updated and LoreSa abstracAon perfected alongside REDcap database Erhunmwunsee Omics : Salgia Data Transfer : Data Dic#onary Upload : TranslaAonal Transfer data abstracted in REDcap to THOR data dicAonary uploaded to the Laboratory the Registry of Hope plaVorm Registry of Hope plaVorm Women’s Cancer: Susan Yost Registry of Hope PlaAorm Developed : Website and registry database created Registry of Hope beyond THOR : Head and Neck: with Center for InformaAcs. UAlize lessons from THOR to help Rebecca Pharaon Personnel : Sorena Nadaf establish other disease teams Vijay Nair Genomics script : Yingyu Wang Mambetsariev et int. Salgia, 2018

Registry of Hope • Multi-Disciplinary integration • 10 Disease Teams • Disease Team focused and owned • Data abstraction: • Automatically from AllScripts and EPIC EMRs • Genomic data abstracted using python scripts from Foundation Medicine, Guardant 360, CARIS, etc. • Automatic Abstraction and Manual Validation from CoPath SQL database • Manual Abstraction of non- discreet data Mambetsariev et int. Nadaf, Salgia, 2018

Registry of Hope Current Build Registry of Hope Advantages : • Greater accessibility and customization • Integration directly with EPIC EMR • 1700+ genetic tissue and blood markers • Future integration with Translational Laboratory and Biorepository

Registry of Hope Data Collection Mambetsariev et int. Salgia, 2018

THOR Patients Pilot Project • Evaluated 350 lung adenocarcinoma patients from the Thoracic Oncology Registry • Analyzed the detailed clinical information as well as the comprehensive genomic data available from commercial tests • Showcase the insight provided into real- world data by a comprehensive disease team registry

Thoracic Oncology Registry (THOR) Profile of Adenocarcinomas Total EGFR KRAS ALK MET BRAF ROS1 RET NTRK % (#) % (#) % (#) % (#) % (#) % (#) % (#) % (#) % (#) N = 350 178 55 30 18 17 8 12 12 Sex Male 41% (142) 36% (64) 42% (23) 27% (8) 61% (11) 41% (7) 50% (4) 33% (4) 25% (3) Female 59% (208) 64% (114) 58% (32) 73% (22) 39% (7) 59% (10) 50% (4) 67% (8) 75% (9) Age Mean 61.8 61.1 66.2 49.8 65.9 64.6 57.9 58.0 52.7 Race Caucasian 57% (198) 44% (78) 78% (43) 47% (14) 61% (11) 76% (13) 62% (5) 67% (8) 67% (8) African American 2% (8) 2% (4) 5% (3) 3% (1) 0% 6% (1) 0% 0% 0% Asian 34% (119) 48% (86) 9% (5) 30% (9) 39% (7) 12% (2) 38% (3) 16.5% (2) 16.5% (2) Native Hawaiian 0.5% (1) 0% 2% (1) 0% 0% 0% 0% 0% 0% American Indian 0.5% (1) 0% 2% (1) 0% 0% 0% 0% 0% 0% Other/Unknown 7% (23) 6% (10) 4% (2) 20% (6) 0% 6% (1) 0% 16.5% (2) 16.5% (2) Smoking Status Smoker 47% (166) 31% (56) 84% (46) 40% (12) 61% (11) 59% (10) 12% (1) 42% (5) 67% (8) Non-Smoker 52% (182) 69% (122) 16% (9) 60% (18) 39% (7) 41% (7) 88% (7) 58% (7) 33% (4) Unknown 1% (2) 0% 0% 0% 0% 0% 0% 0% 0% Stage of Disease Stage I 5% (18) 4% (8) 11% (6) 3% (1) 11% (2) 12% (2) 12% (1) 0% 0% Stage II 3% (11) 2% (3) 5.5% (3) 0% 6% (1) 6% (1) 0% 0% 8% (1) Stage III 6% (20) 3% (5) 5.5% (3) 3% (1) 6% (1) 12% (2) 0% 0% 8% (1) Stage IV 86% (300) 91% (162) 78% (43) 94% (28) 77% (14) 70% (12) 88% (7) 100% (12) 84% (10) Unknown 0.5% (1) 0% 0% 0% 0% 0% 0% 0% 0% Mambetsariev et int. Salgia. 2018

THOR Genomic Characteristics Mambetsariev et int. Salgia. 2018

THOR Genomic Characteristics Mambetsariev et int. Salgia. 2018

Mambetsariev et int. Salgia. 2018

THOR Age Distribution Mambetsariev et int. Salgia. 2018

THOR Metastatic Sites Mambetsariev et int. Salgia. 2018

THOR Survival by Actionability Mambetsariev et int. Salgia. 2018

THOR Survival by Driver Mambetsariev et int. Salgia. 2018

Understanding ALK Heterogeneity within THOR • Extracted ALK mutated lung adenocarcinoma patients from the Thoracic Oncology Registry • Performed comprehensive radiogenomic analysis of patients’ tumor profile and radiological signature of primary tumor as well as metastatic sites • Performed innovative 3D volumetric analysis of metastatic sites

Receptor Tyrosine Kinases Blume-Jensen, Nature 2001

ALK NSCLC Patients Metastatic Sites Gupta et int. Salgia. 2018

ALK NSCLC Patients Metastatic Sites Unusual Sites of Metastasis Physiological landscape of unusual metastaAc sites Peritoneal Ovarian Omental Spleen PancreaAc Thyroid Epidural Kidney Chest wall Skin Abdominal wall Tracheal Mesenteric Leptomeningeal Pericardial So_ Assue 0 1 2 3 4 5 6 7 8 Number of paAents (total n=24) Gupta et int. Salgia. 2018

Mutations associated with ALK+ NSCLC based on NGS sequencing Gupta et int. Salgia. 2018

Mutations associated with uncommon metastatic sites Gupta et int. Salgia. 2018

Examples of 3D volumetric images of unusual sites of metastasis PaAent with adnexal metastasis PaAent with abdominal metastasis PaAent with renal and abdominal metastasis Rahmanuddin/Gupta et int. Salgia. 2018

ALK Survival by Metastatic status Gupta et int. Salgia. 2018

ALK rearranged NSCLC SeIng Drug Genera#on FDA EMA Key trials approval approval Second awaited First line AlecAnib ü J-ALEX/ALEX First line CrizoAnib First ü ü PROFILE 1014 Second awaited First line CeriAnib ü ASCEND 1,3,4 Post crizoAnib CeriAnib Second ü ü ASCEND 1,2,5 Post crizoAnib BrigaAnib Second ü awaited ALTA Post crizoAnib AlecAnib Second ü awaited Phase 2 NA, Intl Post chemo CrizoAnib First ü ü PROFILE 1005,1007

FDA-approved and promising targeted therapies Mayekar et al. Clinical Pharmacology & Therapeutics, 2017