Genomic Colocalization And Enrichment Analyses

Genomic Colocalization and Enrichment Analyses

Genetic and Epigenetic Control on Immune Responses Regulating Molecules in Cancer Development, Progression, and Treatment

In line with recent evidence, the development of cancer has been described as uncontrolled cell growth that results from gradual accumulation of genetic and epigenetic alterations, involving aberrations in oncogenes, tumor suppressor genes, and defects in genes engaged in DNA repair. As a result, cancer cells acquire a neoplastic phenotype and tumor-associated antigens (TAAs) are presented on their surface. These target structures should be recognized by cells of the immune system. However, a sequence of events at the genetic and epigenetic level disturb immune cells, and in consequence, make them unable to eliminate cancer cells. Both innate and adaptive immunity are mobilized against cancer cells. In response to the appearance of cells with malignant transformation, NK cells release perforin and granzyme, causing direct cytolysis of the target cells. They can also secrete pro-inflammatory cytokines and in that way enhance the anticancer response. The activity of NK cells is regulated by a variety of activating and inhibitory receptors including NKG2D, KIR, CD94 -NKG2 heterodimers and natural cytotoxicity receptors, TNF family ligands, as well as co-stimulatory receptors, which recognize related molecules on target cells. A fundamental trigger of the anticancer immune response is the recognition of TAAs by T cells, via the major histocompatibility complex (MHC), which should be followed by signals from co-stimulatory molecules. Full activation of T lymphocytes requires a third signal provided by the presence of cytokines, and this leads to cell proliferation, differentiation, and secretion of chemokines and cytokines. The effect is to drive the clonal expansion of the T cells directed against TAAs and to recruit other immune effector cells in order to enhance immune defense.

Handbook of Statistical Genomics

A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.