Cancer Biology & Translation Medicine 肿瘤生物学与转化医学 Cancer Biology & Translation Medicine 陈志南 Zhi-Nan Chen 第四军医大学znchen@fmmu.edu.cn

Global Action Against Cancer 1 Lung Global (Year) 7 Esopha- geal 2 Breast 7.6 million Deaths Cancer 10.9 million New Cases 6 Cervical 3 Colon 5 Liver 4 Gastric Update Edition 2005

Against Cancer in China Incidence 2,000,000 Mortality 1,500,000 1 Lung 8 Nasopharyn- geal 2 Liver Liver Cancer Mortality/100,000 Countryside 26.93 (1st) 7 Breast 3 Gastric City 24.41 (2nd) Cancer 6 Cervical 4 Esopha- geal 5 Colon Disease Control Division, Ministry of Health of PRC, 2008

The third time investigation of death causes: 与排名第一的脑血管病仅有0.13%的差距，属于世界较高水平，而且呈持续增长的趋势，与70年代中期相比，死亡率增加了83.1%，与90年代初期相比，也增加了22.5%。其中食管癌、胃癌、宫颈癌、鼻咽癌死亡率及其构成呈明显下降趋势，宫颈癌下降幅度最大；而与环境、生活方式有关的肺癌、肝癌、结直肠癌、乳腺癌、膀胱癌死亡率及其构成呈明显上升趋势，以肺癌和乳腺癌上升幅度最大，过去30年分别上升了46.5%和96%]。原发性肝癌（primary liver cancer）所致的死亡率在世界范围内居于第三位，而在我国一直高居首位，尽管2008年我国死亡原因调查显示，肺癌已代替肝癌成为我国首位恶性肿瘤死亡原因（占全部恶性肿瘤死亡的22.7%），但肝癌的死亡率依然呈上升趋势。另据WHO估计，到2030年，我国因恶性肿瘤所致死亡率将由2005年的20.2%上升至23.6%[57]。可见，不管是在世界范围内，还是在我国，恶性肿瘤依然是威胁人类健康和生命的重大疾病，对其发病机制、早期诊断方法及有效治疗措施的研究仍是全球生物医学研究领域的重中之重。 The third time investigation of death causes: cancer ranks second with a mortality rate of 22.32%. ——Ministry of Health, April 2008

Multiple Carcinogen Cancer: Three Characteristics Cancer Etiology 增生 异常 Cancer Etiology Inherited susceptibility Chemical carcinogens Radiation Infectious agents DNA repair system General health (diet, stress, etc) Immune system Cancer Cell: Contributing Factors Cancer: Three Characteristics Multiple Carcinogen

Multiple Stages Tumor Cell Dysplasia Initiation Development Invasion Carcinoma in situ Cell Primary cancer Metastasis (2nd Cancer) genomic DNA transcription translation post-transcription post translation Tumor Initiation Development Invasion Metastasis Multiple Stages

Multiple Gene Mutation Loss of genomic integrity and imbalance of molecules are mechanism for the cancer incidence Multiple Gene Mutation EMBO reports 1, 2, 115-119, 2000

Cancer Initiation & Invasion Four Mechanisms

removing errors, normal variants Cancer Genome Atlas Mining the cancer genome Sequencing: 13,023 genes removing errors, normal variants Breast cancer 11 Samples Colon cancer 11 Samples Cancer Molecular Balance & Mutation 1149 mutation genes (Individual tumors: average 90) (Significant frequency: 189 genes) (Significant frequency: average 11 per tumor) but that only a subset of these contribute to the neoplastic process. Using stringent criteria to delineate this subset, , vast majority unknown and predicted to affect a wide range of cellular functions, including transcription, adhesion, and invasion provide new targets for diagnostic and therapeutic intervention, and open fertile avenues for basic research in tumor biology Tobias Sjoblom, et al. Science 314: 268-274, 2006

Cancer Genome Atlas Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution Sohrab P. Shah, Ryan D. Morin, Jaswinder Khattra, Leah Prentice, Trevor Pugh, Angela Burleigh, Allen Delaney, Karen Gelmon, Ryan Guliany, Janine Senz, Christian Steidl, Robert A. Holt, Steven Jones, Mark Sun, Gillian Leung, Richard Moore, Tesa Severson, Greg A. Taylor, Andrew E. Teschendorff, Kane Tse, Gulisa Turashvili, Richard Varhol, René L. Warren, Peter Watson, Yongjun Zhao, Carlos Caldas, David Huntsman, Martin Hirst, Marco A. Marra & Samuel Aparicio Recent advances in next generation sequencing 1, 2, 3, 4 have made it possible to precisely characterize all somatic coding mutations that occur during the development and progression of individual cancers. We found 32 somatic non-synonymous coding mutations present in the metastasis. Five of the 32 mutations (in ABCB11, HAUS3, SLC24A4, SNX4 and PALB2) were prevalent in the DNA of the primary tumour removed at diagnosis 9 years earlier, six (in KIF1C, USP28, MYH8, MORC1, KIAA1468 and RNASEH2A) were present at lower frequencies (1–13%), 19 were not detected in the primary tumour, and two were undetermined. but that only a subset of these contribute to the neoplastic process. Using stringent criteria to delineate this subset, , vast majority unknown and predicted to affect a wide range of cellular functions, including transcription, adhesion, and invasion provide new targets for diagnostic and therapeutic intervention, and open fertile avenues for basic research in tumor biology Sohrab P. Shah, et al. Nature 461: 809-813, 2009

Invasion & Metastasis — Main Death Causes Travel Intravasation Primary tumor (Cell escape) Invasion Invasion & Metastasis — Main Death Causes Extravasation Transport Growth (2nd tumor) Migration

Mesenchymal cell-like movement Adhesion Movement A little long cell Need protease Mesenchymal cell-like movement Form of pseudopodium Rho/ROCK signal A little circle cell A little rely on protease Amoeba-like movement Myosin strong Contraction Rac/WAVE2 signal Cell. 2008 Oct 31; 135 (3): 510-523

Control of cell cycle G1→S→G2→M G1: DNA pre-synthesis S: DNA synthesis G2: DNA post- synthesis M: Cell division GO: Oncogenes STOP: Tumor superessor 13

Matrix Degradation —— MMPs Structural base of tumor invasion & metastasis Transformed epithelial cells Epithelial lining cells Tumor fb MMP-1, 2, 3, 11, 14 Tissue Martrix Tumor fb Transformed epithelial cells MMP-7, 13 (9) Epithelial cells of tumor angiogenesis MMP-1, 2, 14

Angiogenesis Tumor>2-3mm: Need vessels Key Molecular: MMPs, VEGF, bFGF, PDGF Tumor vessels density is a marker for early diagnosis and prognosis Tumor capillary basement membrane is often flawed. It is of importance to tumor metastasis 肿瘤新生毛细血管基底膜往往存在缺陷，对肿瘤转移的发生具有重要意义 Nature Rev Cancer, 4, 2004

The Chain of Inflammation & Cancer Cancer: Wounds that fail to heal The Chain of Inflammation & Cancer Tumor Development Nature, 420, 2002

Strong association: inflammation and cancer Bacterial H pylori 幽门螺杆菌 Virus EB, HCV Parasite flukes, schistosomes 吸虫，血吸虫 Chemial irritis PMA 佛波酯 Nondigestible Particles asbestos, silica 石棉纤维，矽 Cancer Chronic inflammation

Oxidized DNA nucleosides Oxidative Stress氧化应激 Chronic inflammation ROS 活性氧 RNS 活性氮 Oxidized DNA nucleosides 氧化脱氧核苷酸 Peroxynitrite 过氧亚硝基 Aldehydes醛 DNA mutation DNA damage P53、Rb DNA repair

Inflammatory cytokines & Oncogenes Tumor inflammation environment RAS IL-1a, IL-1b, IL-6, CXCL8, IL-11 MYC IL-1b, CCL2, CCL5, CCL7, CXCL1, CXCL2 RET tyrosine kinase CXCL8, CXCR4, CCL2, MCP-1, GM-CSF EGFR CXCL8 proto-oncogene Tpl2 NF-kB OncomiRs, miR-155 Inflammatory mediators in macrophages and in monocytes Tumor inflammation environment Cancer Letters, 267, 2008

Signal Transduction Cancer cell Blood vessel Cytokines Chemokines Macrophage CypA CD147 Hypoxia ROS CypA Erk1/2 PI3K P38 HIF Proliferation Anti-apoptosis Angiogenesis Reported Cancer cell Our study Not confirmed

The Seven Hallmarks of Cancer and Their Links to Tumor Metabolism 凋亡 血管 生成 无限 增殖 侵袭转移 抵抗 抑瘤 免疫 逃避 增生 环路 Tumor Metabolism Cancer Cell. 13: 472-482, 2008

Anaerobic glycolysis Intratumoral hypoxia and metabolic symbiosis or Aerobic stromal cell J Clin Invest. 118 (12): 3835-3837, 2008

Molecular Mechanisms of Cancer-Specific Metabolic Reprogramming 葡萄糖转运 糖原分解 乳酸产生 氧化磷酸化降低 脂类合成 氧化抑制

Cancer Biomarker -- A Systems Approach 高危评估 Risk assessment 早期诊断 Noninvasive screening for early-stage disease 检测定位 Detection and localization 预后判断 Disease stratification and prognosis 治疗反应 Response to therapy 复发监测 Screening for disease recurrence Leland H. Hartwell, et al. Nat Biotech, 24 (8), 2006

How Identified Cancer Biomarker? Biomarker Discovery: Expression Mapping (Modification mapping) Functional proteomics: interaction of the proteins Epitope mapping (active core) Seperation and identification of mixture sample Ab array, Cell array, Tissue array, Co-IP (pull-down), Biosence, etc. Comparative proteomics 2DE, 2DELC-MS Validation peptides sequence of protein MALDI-MS, SELDI-MS, LC-MSMS, ESI-MS (m/z) Analysis of the databases

System Biology Approaches “-omic” Technologies (Preclinical or Clinical Utilization) MALDI-MS/MS 2D Gels- MS NMR GC-MS LC-MS FT-IR Microarray SAGE Amplichip Cyp 450 Test Global SNP Arrays Trends Biotechnol. 23 (11), 544-546, 2005

What is an Ideal Cancer Biomarker? Screening a healthy population or a high risk population for the presence of cancer Making a diagnosis of cancer or of a specific type of cancer Determining the prognosis in a patient Monitoring the course in a patient in remission or while receiving surgery, radiation, chemotherapy, or biotherapy Screening a healthy population or a high risk population for the presence of cancer Making a diagnosis of cancer or of a specific type of cancer Determining the prognosis in a patient Monitoring the course in a patient in remission or while receiving surgery, radiation, chemotherapy, or biotherapy

Application of Cancer Biomarker Identification and diagnosis Individuals affected with disease People who may be at risk but do not yet exhibit symptoms Monitor progress of disease Monitor effects of treatment Remission Follow-up Cancers found in early stage: low morbidity and recurrence rates Cancers identified in late stage: high recurrence and mortality rates

AFP = alpha fetoprotein CEA = carcinogenic embryonic antigen CA 15-3 = carbohydrate antigen 15-3 CA 19-9 = carbohydrate antigen 19-9 CA 125 = carbohydrate antigen 125 PSA = free prostate specific antigen + prostate specific antigen - alpha(1)antichymotrypsin complex PSAF = free prostate specific antigen PSAC = prostate specific antigen - alpha(1)antichymotrypsin complex PAP = prostatic acid phosphatase hTG = human thyroglobulin hCGb = human chorionic gonadotropin beta Ferr = Ferritin NSE = neuron specific enolase IL-2 = interleukin 2 IL-6 = interleukin 6 A2M = alpha 2 macroglobulin B2M = beta 2 microglobulin Cancer Biomarker and Types of Cancer: statistically significant association between a particular cancer and the associated cancer marker (s)

Problems of Cancer Biomarker No cancer biomarker is absolutely specific No cancer biomarker test is free of false negatives No cancer biomarker test is free of false positives No cancer biomarker is absolutely specific No cancer biomarker test is free of false negatives No cancer biomarker test is free of false positives

Antibody Based Cancer Biomarkers Cancer Marker Antibody Cancer CA125 OC 125 ovarian cancer CA 15-3 DF3, 115D8 breast cancer, ovarian cancer CA 549 BC4E549, BC4N154 CA 27-29 B27.29 breast cancer MCA b-12 DU-PAN-2 Du-PAN-2 pancreatic cancer, ovarian cancer, gastrointestinal cancers, lung cancer CA 19-9 19-9 pancreatic cancer, liver cancer, gastrointestinal cancers CA 19-5 19-5 CA 50 C50 pancreatic cancer, rectal cancer, CA 72-4 B27.3, cc49 gastric carcinoma, pancreatic cancer, CA 242 C242 pancreatic cancer Her-2/neu Herceptin HAb18G/CD147 HAb18 hepatocellular carcinoma, ect

Antibody Based Cancer Biomarkers Human genome is 2.91-billion base pairs in length (1990) There are about 25,000 genes exist in the human genome (42% have an unknown function) Approximately 12,000 genes that appear to have the capacity to make secreted proteins, all the genes have been determined the entire nucleotide sequences (3141 genes locus on the first chromosome) At May 2006, the first chromosome sequences were completed, at least 1,000 new genes were found. This is the end of 16 year’s Human Genomic Plan. This has empowered more direct means of target identification, e.g. by expanding protein databases and enabling the mapping of novel cancer-associated genes (Venter et al. 2001).

Antibody Based Cancer Biomarkers Complete genome sequences have provided a plethora of potential drug targets. But the hard task of finding their weak spots is just beginning (about 5000 genes can be used as drug target) A challenging new development in the field of drug-target discovery is systems biology, or the recognition that genes, or better the gene products, are part of, and function, in large complex networks. Nature, 428, 225-231, 2004.

转化医学与公众健康

转化医学概念 EA. Zerhouni，NIH路线图计划（NIH Roadmap），2003 将医学生物学基础研究成果迅速有效的转化为可在临床实际 应用的理论、技术、方法和药物 基础研究→临床应用，实验室成果→产业化 在实验室到病房（Bench to Bedside, B2B）之间架起一条 快速通道 双向、开放： 基础研究提供新疗法、新药物 临床研究者对疾病的进程和特性提供反馈意见 “驱动临床研究引擎的激发器”

转化医学发展现状 美国已经在38所大学建立了转化医学研究中心，在2012年以 前将会达到60个以上，NIH每年资助经费达5亿美元 英国已投入4.5亿英镑用于转化医学研究，并启动世界上首个 转化医学合作研究中心 欧洲共同体为转化医学计划投入60亿欧元 Science Translational Medicine、Journal of Translational Medicine和Translational Research三本国际性专业杂志

中国的转化医学 转化医学战略研讨会 2009，中国工程院 2010，中国科学院 转化医学中心 中南大学 上海交通大学 同济大学 成果转化率：25%，商品化：<15%

转化医学与4P医学 Predictive Medicine – 预测医学 Preventive Medicine – 预防医学 Personalized Medicine – 个体化医学 Participate Medicine – 参与医学

Personalized Prevention & Early Detection Lifestyle changes Screening Chemoprevention Prophylactic Surgery Average Moderate High Very High RISK

Personalized Medicine – 个体化治疗 No “one size fits all” drug Most drugs work for 30% to 70% of patients Multiple factors determine drug responses Phamacogenetics is essential for individualized therapy

Personalized Medicine – 个体化治疗 Herceptin, the first marketed personalized medicine, was approved using a coordinated drug/diagnostic approval process that will become more common.

HAb18G/CD147 & HAb18, 6H8, 5A12 Antibodies Our Study Molecular Docking HAb18G & Its Antibodies HAb18G/CD147 I Set 经过上述抗原抗体分子对接，证明三个抗体结合表位是在该分子胞外段的不同部位 HAb18G/CD147 & HAb18, 6H8, 5A12 Antibodies

Crystal Structure of HAb18G/CD147 Our Study Crystal Structure of HAb18G/CD147 C2 I Xiao-Ling Yu, Zhi-Nan Chen, J Biol Chem, 283 (26), 2008 National patent: 200710018514.X PCT patent: PCT/CN2007/003034 PDB ID: 3B5H

Our Study Tissue Atlas - HAb18G/CD147 HAb18G/CD147

Our Study Tissue Atlas - HAb18G/CD147 HAb18G/CD147

Our Study Tissue Atlas - HAb18G/CD147 66.45 Fetal Normal Cancer Case Lung Liver Fetal Normal Cancer Case Positive Positive Rate (%) P Fetal 67 1 1.49 <0.0001 Normal 196 16 8.16 Cancer 1565 1040 66.45 Shao-Hui Hu, Zhi-Nan Chen, et al. Proteomics, 7 (13), 2007

Our Study Tissue Atlas - HAb18G/CD147 组织类型 病例数 阳性率 灵敏度 （真阳性率） 特异度 （真阴性率） 肝 癌 147例 77.66% 100% 良性病变肝组织 44例 0.00% 肺 癌 186例 95.04% 98% 良性肺疾病 100例 2.00% 乳腺癌 200例 65.35% 91% 良性乳腺疾病 9.00% 食管癌 199例 86.22% 97.5% 良性食管疾病 80例 2.77% 卵巢癌 101例 76.23% 83.67% 良性卵巢疾病 52例 16.33% 胃癌 193例 76.68% 83.37% 良性胃疾病 98例 16.63% 宫颈癌 120例 71.84% 88.46% 良性宫颈疾病 55例 11.54% 直肠癌 195例 77.68% 93.93% 良性直肠疾病 6.07% 平 均 值 78.75% 91.73% Yu Li, Zhi-Nan Chen, et al. Histopathology, 2009

Iodine (131I) Metuximab Injection Our Study Iodine (131I) Metuximab Injection (LICARTINTM) Panel A, a defect in the upper region of the right lobe of the liver (arrow) in 99mTc-sodium phytate-colloid scan. Panel B, the hot region of HCC (arrow) in SPECT 7 days after LICARTIN treatment. Panel C, the CT scans of one patient (PR ). Panel D, the CT scans of one patient (CR ). Cancer Biol Ther 5 (7), 2006

Iodine (131I) Metuximab Injection Our Study Iodine (131I) Metuximab Injection (LICARTINTM) Anti-recurrence Treatment after Liver Transplantation recurrence rate 30.42↓ survival rate 20.62↑ AFP 44.08% 57.09% 26.67% 82.50% 61.88% P=0.0174 P=0.0289 P=0.0016 Control group Treatment group 60 cases HCC (III, IV stage) 87.82% Then the anti-metastasis and recurrence effect of LICARTIN was determined in the post-orthotopic liver transplantation (OLT) HCC patients. Our initial results showed that LICARTIN significantly decreased recurrence rate and increased survival rate of HCC patients, compared with untreated control group. So LICARTIN is a promising new anti-metastasis and recurrence agent for treating HCC. Hepatology, 45 (2): 269-276, 2007

Iodine (131I) Metuximab Injection Our Study Iodine (131I) Metuximab Injection (LICARTINTM) 四期临床（截至21010年4月累计使用1500支） 北京利卡汀治疗基地，原子能研究院401医院 上海利卡汀临床研究中心，东方肝胆医院 广州利卡汀治疗基地，广州军区458医院 北京佑安医院 解放军总医院 武警总医院 北大肿瘤医院 上海中山医院 上海东方肝胆医院 中山大学肿瘤医院 浙江大学一院、二院 浙江省肿瘤医院 四川大学华西医院 华中附属协和医院 湖南省医院 中南大学湘雅医院 福建医大第一医院 四军大唐都医院 郑州大学一附院 河南省医院 中国医大一附院、二附院 福建医大协和医院 Then the anti-metastasis and recurrence effect of LICARTIN was determined in the post-orthotopic liver transplantation (OLT) HCC patients. Our initial results showed that LICARTIN significantly decreased recurrence rate and increased survival rate of HCC patients, compared with untreated control group. So LICARTIN is a promising new anti-metastasis and recurrence agent for treating HCC.

千里之行，始于足下