Computational Methods for Precision Oncology

Precision medicine holds great promise for the treatment of cancer and represents a unique opportunity for accelerated development and application of novel and repurposed therapeutic approaches. Current studies and clinical trials demonstrate the benefits of genomic profiling for patients whose cancer is driven by specific, targetable alterations. However, precision oncologists continue to be challenged by the widespread heterogeneity of cancer genomes and drug responses in designing personalized treatments. Chapters provide a comprehensive overview of the computational approaches, methods, and tools that enable precision oncology, as well as related biological concepts. Covered topics include genome sequencing, the architecture of a precision oncology workflow, and introduces cutting-edge research topics in the field of precision oncology. This book is intended for computational biologists, bioinformaticians, biostatisticians and computational pathologists working in precision oncology and related fields, including cancer genomics, systems biology, and immuno-oncology.

Autorentext

Alessandro Laganà is Assistant Professor of Oncological Sciences at the Icahn School of Medicine at Mount Sinai, NY. Dr. Laganà's main research interests are integrative cancer genomics, cancer network biology and precision oncology. His current research is focused on the treatment of Multiple Myeloma (malignancy of bone marrow plasma cells). He received both his M.Sc. and Ph.D. from the University of Catania in Catania, Italy. He is also the author of the Humana Press title MicroRNA Target Identification: Methods and Protocols (2019).

Inhalt

Part I: Basic Concepts in Precision Oncology

1. Design and implementation of a precision oncology workflow

2. An overview of cancer genome sequencing

3. Software infrastructures for precision medicine workflows

Part II: Current Computational Methods and Tools in Precision Oncology

4. Somatic and germline variant calling from next-generation sequencing data

5. Identification of copy number alterations from next-generation sequencing data

6. Genome-wide discovery of large-scale structural variants from next-generation sequencing data

7. Assessment of microsatellite instability from next-generation sequencing data

8. Computational approaches for the investigation of intra-tumor heterogeneity and clonal evolution from bulk sequencing data

9. Analysis of the transcriptome for precision oncology applications

10. Computational methods for drug repurposing

11. Pathway analysis for precision oncology applications

12. Identification of fusion transcripts from RNA-seq

13. Computational resources for the interpretation of variations in cancer

14. Analysis of electronic health records for precision oncology

15. Network approaches for precision oncology

16. Experimental validation of genomic alterations

Part III: Advanced Concepts - The Future of Precision Oncology

17. Molecular profiling of liquid biopsies for precision oncology

18. Artificial intelligence for precision oncology

19. Single-cell technologies in precision oncology

20. Computational approaches for precision immuno-oncology

21. Multi-omics profiling of the tumor microenvironment

22. Epigenetic and precision oncology

23. Next-generation knowledge bases to support precision oncology