INTEGRATED MOLECULAR PROFILING FOR ANALYZING AND PREDICTING THERAPEUTIC MECHANISM, RESPONSE, BIOMARKER AND TARGET Jia Jia (B. Sci & M. Sci, Zhejiang University) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF PHARMACY NATIONAL UNIVERSITY OF SINGAPORE 2010 Acknowledgements ACKNOWLEDGEMENTS I would like to deeply thank Professor Chen Yu Zong, for his constant encouragement and advice during the entire period of my postgraduate studies. In particular, he has guided me to make my research applicable to the real world problem. This work would not have been possible without his kindness in supporting me to shape up the manuscript for publication. I am also tremendously benefited from his profound knowledge, expertise in scientific research, as well as his enormous support, which will inspire and motivate me to go further in my future professional career. I am also grateful to our BIDD group members for their insight suggestions and collaborations in my research work: Dr. Tang Zhiqun, Ms. Ma Xiaohua, Mr. Zhu Feng, Ms. Liu Xin, Ms. Shi Zhe, Dr. Cui Juan, Mr. Tu Weimin, Dr. Zhang Hailei, Dr. Lin Honghuang, Dr. Liu Xianghui, Dr. Pankaj Kumar, Dr Yap Chun wei, Ms. Wei Xiaona, Ms. Huang Lu, Mr. Zhang Jinxian, Mr. Han Bucong, Mr. Tao Lin, Dr. Wang Rong, Dr. Yan Kun. I thank them for their valuable support and encouragement in my work. Finally, I owe my gratitude to my parents for their forever love, constant support, understanding, encouragement and strength throughout my life. A special appreciation goes to all for love and support. Jia Jia August 2010 I Table of Contents TABLE OF CONTENTS 1.1 Overview of mechanism and strategies of molecular-targeted therapeutics .................................... 2 1.1.1 Current progress of molecular-targeted cancer therapeutics ..................................................... 3 1.1.2 Challenges of targeted cancer therapy, receptor tyrosine kinase as a case study ...................... 5 1.1.3 Systematic discovery of multicomponent therapies .................................................................. 7 1.2 Current progress in cancer biomarker discovery ............................................................................ 14 1.2.1 Introduction to biomarker in cancer diagnosis and prediction ................................................ 14 1.2.2 Types of cancer biomakers ...................................................................................................... 15 1.2.3 Approaches of cancer biomarker discovery ............................................................................ 16 1.2.4 Brief introduction of microarray technology ........................................................................... 20 1.2.5 The problems of current marker selection methods ................................................................ 29 1.3 Current progress in tumor antigen discovery ................................................................................. 31 1.3.1 Overview of tumor vaccine for cancer immunotherapy .......................................................... 31 1.3.2 Introduction toT cell-defined tumor antigens .......................................................................... 36 1.3.3 Application of computational methods for MHC-binding peptides and epitopes prediction .. 39 1.4 Scope and research objective ........................................................................................................... 41 2.1 Introduction to machine learning methods..................................................................................... 45 2.1.1 Support Vector Machines ........................................................................................................ 47 2.1.2 Probabilistic neural network ................................................................................................... 51 2.1.3 Hierarchical clustering ............................................................................................................ 53 2.1.4 Parameters optimization and model validation ....................................................................... 55 2.1.5 Performance evaluation ........................................................................................................... 56 2.2 Methodology for microarray data processing ................................................................................. 58 2.2.1 Preprocessing of microarray data ............................................................................................ 58 2.2.2 Normalization and scaling ....................................................................................................... 59 2.2.3 Threshold filtering ................................................................................................................... 61 2.2.4 Missing data estimation........................................................................................................... 62 2.3 Feature selection procedure ............................................................................................................ 63 2.3.1 REF based gene selection procedure ....................................................................................... 64 2.3.2 Recursive feature elimination ................................................................................................. 66 2.3.3 Random sampling, feature elimination and consistency evaluation ........................................ 67 2.4 Construction of the feature vector for peptide ................................................................................ 69 2.4.1 Feature vector for peptide ....................................................................................................... 69 2.4.2 Scaling of feature vector ......................................................................................................... 70 3.1 Introduction ..................................................................................................................................... 74 3.2 Materials and Methods .................................................................................................................... 77 3.2.1 Mechanism of drug interactions .............................................................................................. 77 3.2.2 Methods for drug-combination analysis .................................................................................. 78 3.2.3 Collection of literature-reported drug combinations ............................................................... 78 3.3 Results and discussion ..................................................................................................................... 79 3.3.1 Statistics of collected drug combinations and MI profiles ...................................................... 79 3.3.2 Mechanism underlying the pharmacokinetic and pharmacodynamic drug interactions .......... 80 3.4 Conclusion ..................................................................................................................................... 102 4.1 Introduction ................................................................................................................................... 107 4.2 Materials and Methods .................................................................................................................. 109 4.2.1 Data collection and preprocessing......................................................................................... 109 4.2.2 Bypass mechanism of studied tyrosin kinase inhibitors ........................................................ 116 4.2.3 Drug sensitivity evaluation procedure ................................................................................... 116 4.3 Results and discussion ................................................................................................................... 119 II Table of Contents 4.3.1 Assesment of EGFR-I sensitivity prediction by mutation and amplification profiles ........... 119 4.3.2 Assessment of integrated molecular profiling for predicting TKIs sensitivity ...................... 121 4.3.3 The distribution and coexistence of drug sensitive and resistant profiles ............................. 122 4.4 Summary ........................................................................................................................................ 132 5.1 Introduction ................................................................................................................................... 133 5.2 Materials and Methods .................................................................................................................. 136 5.2.1 Collection of genomic, mutation and expression data ........................................................... 136 5.2.2 Collection of tumor-specific antigen ..................................................................................... 136 5.2.3 Computational procedures .................................................................................................... 137 5.3 Results and Discussion .................................................................................................................. 142 5.3.1 Performance of collective approach in genome-scaled TSAs identification ......................... 142 5.4 Conclusion ..................................................................................................................................... 144 6.1 Introduction ..................................................................................................................................