肿瘤生物学与转化医学.ppt

　　肿瘤生物学与转化医学 Cancer Biology & Translation Medicine

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　　Global Action Against Cancer

　　Update Edition 2005

　　Global (Year)

　　7.6 million Deaths

　　10.9 million New Cases

　　5 Liver

　　1 Lung

　　7 Esopha- geal

　　3 Colon

　　2 Breast

　　4 Gastric

　　6 Cervical

　　Cancer

　　Disease Control Division, Ministry of Health of PRC, 2008

　　Cancer

　　6 Cervical

　　5 Colon

　　8 Nasopharyn- geal

　　1 Lung

　　2 Liver

　　7 Breast

　　3 Gastric

　　4 Esopha- geal

　　City 24.41 (2nd)

　　Incidence 2,000,000 Mortality 1,500,000

　　Cancer

　　Countryside 26.93 (1st)

　　Liver Cancer Mortality/100,000

　　Against Cancer in China

　　The third time investigation of death causes: cancer ranks second with a mortality rate of 22.32%. ——Ministry of Health, April 2008

　　(Gp:) 增生

　　(Gp:) 异常

　　(Gp:) Inherited susceptibility Chemical carcinogens Radiation Infectious agents DNA repair system General health (diet, stress, etc) Immune system

　　(Gp:) Cancer Cell: Contributing Factors

　　Cancer Etiology

　　Multiple Carcinogen

　　Cancer: Three Characteristics

　　Tumor Initiation Development Invasion Metastasis

　　(Gp:) Dysplasia

　　(Gp:) Carcinoma in situ

　　(Gp:) Cell

　　(Gp:) Primary cancer

　　(Gp:) Metastasis (2nd Cancer)

　　(Gp:) genomic DNA

　　(Gp:) transcription

　　(Gp:) translation

　　(Gp:) post-transcription

　　(Gp:) post translation

　　Multiple Stages

　　EMBO reports 1, 2, 115-119, 2000

　　Loss of genomic integrity and imbalance of molecules are mechanism for the cancer incidence

　　Multiple Gene Mutation

　　Cancer Initiation & Invasion Four Mechanisms

　　Mining the cancer genome

　　Tobias Sjoblom, et al. Science 314: 268-274, 2006

　　Cancer Genome Atlas

　　(Gp:) Sequencing: 13,023 genes

　　(Gp:) removing errors, normal variants

　　(Gp:) Breast cancer 11 Samples

　　(Gp:) Colon cancer 11 Samples

　　1149 mutation genes (Individual tumors: average 90) (Significant frequency: 189 genes) (Significant frequency: average 11 per tumor)

　　Cancer Molecular Balance & Mutation

　　Sohrab P. Shah, et al. Nature 461: 809-813, 2009

　　Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution

　　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.

　　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

　　Cancer Genome Atlas

　　(Gp:) Travel

　　(Gp:) Intravasation

　　(Gp:) Primary tumor (Cell escape) Invasion

　　(Gp:) Extravasation

　　(Gp:) Transport

　　(Gp:) Growth (2nd tumor)

　　(Gp:) Migration

　　Invasion & Metastasis — Main Death Causes

　　Mesenchymal cell-like movement

　　Amoeba-like movement

　　A little long cell

　　Need protease

　　Form of pseudopodium

　　A little rely on protease

　　Myosin strong Contraction

　　A little circle cell

　　Rac/WAVE2 signal

　　Rho/ROCK signal

　　Cell. 2008 Oct 31; 135 (3): 510-523

　　Adhesion Movement

　　G1→S→G2→M

　　(Gp:) R

　　Control of cell cycle

　　G1: DNA pre-synthesis S: DNA synthesis G2: DNA post- synthesis M: Cell division GO: Oncogenes STOP: Tumor superessor

　　Epithelial lining cells

　　Transformed epithelial cells

　　Tumor fb

　　Tissue Martrix

　　Transformed epithelial cells MMP-7, 13 (9)

　　Epithelial cells of tumor angiogenesis MMP-1, 2, 14

　　Tumor fb MMP-1, 2, 3, 11, 14

　　Matrix degradation: Structural base of tumor invasion & metastasis

　　Matrix Degradation —— MMPs

　　Tumor>2-3mm: Need vessels Key Molecular: MMPs, VEGF, bFGF, PDGF Tumor vessels density is a marker for early diagnosis and prognosis

　　Nature Rev Cancer, 4, 2004

　　Angiogenesis

　　Cancer: Wounds that fail to heal

　　Nature, 420, 2002

　　The Chain of Inflammation & Cancer Tumor Development

　　(Gp:) Cancer

　　(Gp:) Chronic inflammation

　　(Gp:) Bacterial H pylori 幽门螺杆菌

　　(Gp:) Virus EB, HCV

　　(Gp:) Parasite flukes, schistosomes 吸虫，血吸虫

　　(Gp:) Chemial irritis PMA 佛波酯

　　(Gp:) Nondigestible Particles asbestos, silica 石棉纤维，矽

　　Strong association: inflammation and cancer

　　Oxidative Stress氧化应激

　　Aldehydes醛

　　Oxidized DNA nucleosides 氧化脱氧核苷酸

　　DNA mutation

　　Peroxynitrite 过氧亚硝基

　　ROS 活性氧

　　DNA damage

　　(Gp:) P53、Rb

　　(Gp:) DNA repair

　　(Gp:) DNA repair

　　RNS 活性氮

　　Chronic inflammation

　　Inflammatory cytokines & Oncogenes

　　Cancer Letters, 267, 2008

　　Tumor inflammation environment

　　ROS

　　HIF

　　Blood vessel

　　Cancer cell

　　Macrophage

　　Cytokines

　　Chemokines

　　CD147

　　CypA

　　Erk1/2

　　P38

　　Proliferation

　　Anti-apoptosis

　　Angiogenesis

　　CypA

　　Hypoxia

　　Our study

　　Not confirmed

　　Reported

　　PI3K

　　Signal Transduction

　　The Seven Hallmarks of Cancer and Their Links to Tumor Metabolism

　　Cancer Cell. 13: 472-482, 2008

　　(Gp:) 凋亡

　　(Gp:) 血管 生成

　　(Gp:) 无限 增殖

　　(Gp:) 侵袭转移

　　(Gp:) 抵抗 抑瘤

　　(Gp:) 免疫 逃避

　　(Gp:) 增生 环路

　　Tumor Metabolism

　　J Clin Invest. 118 (12): 3835-3837, 2008

　　Intratumoral hypoxia and metabolic symbiosis

　　or Aerobic stromal cell

　　Anaerobic glycolysis

　　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

　　Leland H. Hartwell, et al. Nat Biotech,?24?(8), 2006

　　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

　　Cancer Biomarker -- A Systems Approach

　　Biomarker Discovery: Expression Mapping (Modification mapping) Functional proteomics: interaction of the proteins Epitope mapping (active core)

　　(Gp:) 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

　　How Identified Cancer Biomarker?

　　System Biology Approaches “-omic” Technologies (Preclinical or Clinical Utilization)

　　Trends Biotechnol. 23 (11), 544-546, 2005

　　Amplichip Cyp 450 Test Global SNP Arrays

　　Microarray SAGE

　　MALDI-MS/MS 2D Gels- MS

　　NMR GC-MS LC-MS FT-IR

　　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

　　Cancer Biomarker and Types of Cancer: statistically significant association between a particular cancer and the associated cancer marker (s)

　　(Gp:) 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

　　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

　　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.

　　(Gp:) 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

　　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”

　　转化医学概念

　　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

　　转化医学发展现状

　　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%

　　中国的转化医学

　　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

　　(Gp:) Lifestyle changes

　　(Gp:) Screening

　　(Gp:) Chemoprevention

　　(Gp:) Prophylactic Surgery

　　(Gp:) Average Moderate High Very High

　　(Gp:) 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

　　Herceptin, the first marketed personalized medicine, was approved using a coordinated drug/diagnostic approval process that will become more common.

　　Personalized Medicine – 个体化治疗

　　(Gp:) Our Study

　　(Gp:) Molecular Docking HAb18G & Its Antibodies

　　HAb18G/CD147 & HAb18, 6H8, 5A12 Antibodies

　　(Gp:) HAb18G/CD147 I Set

　　(Gp:) Our Study

　　(Gp:) Crystal Structure of HAb18G/CD147

　　(Gp:) C2

　　(Gp:) 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

　　(Gp:) HAb18G/CD147

　　(Gp:) Our Study

　　(Gp:) Tissue Atlas - HAb18G/CD147

　　(Gp:) HAb18G/CD147

　　(Gp:) Our Study

　　(Gp:) Tissue Atlas - HAb18G/CD147

　　(Gp:) Our Study

　　(Gp:) Tissue Atlas - HAb18G/CD147

　　Shao-Hui Hu, Zhi-Nan Chen, et al. Proteomics, 7 (13), 2007

　　(Gp:) Lung

　　(Gp:) Liver

　　(Gp:) Fetal

　　(Gp:) Normal

　　(Gp:) Cancer

　　Yu Li, Zhi-Nan Chen, et al. Histopathology, 2009

　　(Gp:) Our Study

　　(Gp:) Tissue Atlas - HAb18G/CD147

　　Cancer Biol Ther 5 (7), 2006

　　(Gp:) Our Study

　　(Gp:) Iodine (131I) Metuximab Injection (LICARTINTM)

　　Anti-recurrence Treatment after Liver Transplantation

　　(Gp:) recurrence rate 30.42↓

　　(Gp:) survival rate 20.62↑

　　(Gp:) AFP

　　(Gp:) 44.08%

　　(Gp:) 57.09%

　　(Gp:) 26.67%

　　(Gp:) 82.50%

　　(Gp:) 61.88%

　　(Gp:) P=0.0174

　　(Gp:) P=0.0289

　　(Gp:) P=0.0016

　　(Gp:) Control group Treatment group

　　(Gp:) 60 cases HCC (III, IV stage)

　　(Gp:) 87.82%

　　(Gp:) Our Study

　　(Gp:) Iodine (131I) Metuximab Injection (LICARTINTM)

　　Hepatology, 45 (2): 269-276, 2007

　　(Gp:) Our Study

　　(Gp:) Iodine (131I) Metuximab Injection (LICARTINTM)

　　(Gp:) 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

　　千里之行，始于足下