Topics included in the book cover oncogenetic trees, stochastic multistage models of carcinogenesis, effects of ionizing radiation on cell cycle and genomic instability, induction of DNA damage by ionizing radiation and its repair, epigenetic cancer models, bystander effects of radiation, multiple pathway models of human colon cancer, and stochastic models of metastasis. The book also provides some important applications of cancer models to the assessment of cancer risk associated with various hazardous environmental agents, to cancer screening by MRI, and to drug resistance in cancer chemotherapy. An updated statistical design and analysis of xenograft experiments as well as a statistical analysis of cancer occult clinical data are also provided.

The book will serve as a useful source of reference for researchers in biomathematics, biostatistics and bioinformatics; for clinical investigators and medical doctors employing quantitative methods to develop procedures for cancer diagnosis, prevention, control and treatment; and for graduate students.

Contents:

• Oncogenetic Trees (A Szabo & K M Boucher)
• Stochastic Multistage Cancer Models: A Fresh Look at an Old Approach (Q Zheng)
• Cancer Biology, Cancer Models and Some New Approaches to Carcinogenesis (W Y Tan et al.)
• Modeling the Effects of Radiation on Cell Cycle Regulation and Carcinogenesis (W D Hazelton)
• Cancer Models, Ionizing Radiation, and Genomic Instability: A Review (M P Little)
• Distribution of the Sizes of Metastases: Mathematical and Biomedical Considerations (L Hanin)
• Mathematical Models of Cancer and Their Relevant Insights (E Afenya)
• Major Epigenetic Hypotheses of Carcinogenesis Revisited (K-T Chung)
• Induction and Repair of DNA Damage Formed by Energetic Electrons and Light Ions (R D Stewart & V A Semenenko)
• Radiation-Induced Bystander Effects (L C DeVeaux)
• A Stochastic Model of Human Colon Cancer Involving Multiple Pathways (W Y Tan et al.)
• Cancer Risk Assessment of Environmental Agents by Stochastic and State Space Models of Carcinogenesis (W Y Tan et al.)
• Stochastic Models for Preneoplastic Lesions and Their Application for Cancer Risk Assessment (A Knopp- Schneider et al.)
• Drug Resistance in Cancer Models (J Smieja)
• Bladder Cancer Screening by Magnetic Resonance Imaging (L-H Li et al.)
• Mathematical Framework and Wavelets Applications in Proteomics for Cancer Study (D Hong & Y Shyr)
• Advanced Statistical Methods for the Design and Analysis of Tumor Xenograft Experiments (M Tan & H-B Fang)
• Analysis of Occult Tumor Studies (S N Rai)

“This is a well-written book that provides an accessible up-to-date overview of a variety of mathematical methods, of which some have been recently developed. It provides both systematic reviews and novel theoretical developments, and contains many examples of successful applications of mathematical modeling to cancer research.”