Synopsis
Chapter 1. Introduction.- Chapter 1.1. Overview of cancer genomics.- Chapter 1.2. Organization and variations in human genome.- Chapter 1.3. Genomic technologies (Sequencing, next generation sequencing, biomarkers, DNA micro-arrays, tissue microarrays).- Chapter 1.4. Metabolic changes and their characterization.-Chapter 1.5. Sequencing in cancer prognosis and treatment.- Chapter 1.6. Unravelling genomics targets of small molecules.- Chapter 1.7. Application of CRISPR-Cas 9 system in genomic editing in cancer.- Chapter 1.8. Role of nanomedicine in cancer detection and inhibition (drug delivery systems).- Chapter 1.9. Clinical application of cancer genomics.- Chapter 2. Cancer Metastasis.- Chapter 2.1. Role of Genomic instability and cancer metastasis.- Chapter 2.2. Tumour dormancy and metastasis.- Chapter 2.3. Response of DNA damage repair pathways.- Chapter 2.4. Micro-environmental control.- Chapter 2.5. Role of mechanotransduction and immunomodulation in cancer metastasis and genomic instability.- Chapter 2.6. Synthetic genetic strategies.- Chapter 3. Role of Transcriptomics in cancer treatment strategies.- Chapter 3.1. Cancer transcriptome sequencing and analysis.- Chapter 3.2. Association of Transcriptomics with treatment strategies.- Chapter 3.3. Importance of microRNAs in cancer.- Chapter 3.4. RNA-seq and precision medicine.- Chapter 3.5. Translational genomics.- Chapter 3.6. Genomic medicine.- Chapter 3.7. Clinical oncology.- Chapter 3.8. Role of non-coding sequence variants in cancer. Chapter 3.9. Translational research in oncology.- Chapter 3.10. Analysis of proteomic approaches for cancer treatments.- Chapter 3.11. Concepts of personalized medicine based on proteomics. Chapter 4. Computational approaches.- Chapter 4.1. System biology and system medicine.- Chapter 4.2. Computational analysis.- Chapter 4.3. Mathematical modelling and genomic medicine.- Chapter 4.4. Prognostic and predictive methods towards precision medicine. Chapter 5. Biostatistics and clinical oncology.- Chapter 5.1.Variables and their distribution.- Chapter 5.2. Sample size calculations, study designs, regression analysis, survival analysis (OS and PFS/TTS).- Chapter 5.3. Randomized clinical trials, meta-analysis, statistical models.- Chapter 5.4. Challenges faced during analysing data on quality of life in cancer patients.- Chapter 6. Pharmacogenomics in cancer.- Chapter 6.1. Importance of pharmacogenomics,.- Chapter 6.2. Linking cancer genomics with pharmacological factors.- Chapter 6.3. Peads pharmacogenomics and cancer.- Chapter 6.4. Future of pharmacogenomics in cancer.- Chapter 7. Case studies. -Chapter 7.1. Case studies on the role of precision medicine in cancer.- Chapter 7.2. Current challenges on genomic research.- Chapter 7.3. Future perspectives of cancer genomics.
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