Targeting Oncogenic Drivers and Signaling Pathways in Lymphoid Malignancies : : From Concept to Practice [Internet] / / edited by Owen A. O'Conner, Stephen M. Ansell, and John F. Seymour.

• TeilnehmendeR: Seymour, John F.,; Ansell, Stephen M.,; O'Conner, Owen A.,
• Place / Publishing House: Hoboken (NJ) : : Wiley-Blackwell,, 2023.; ©2023
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource (112 pages)
• Other title: Targeting Oncogenic Drivers and Signaling Pathways in Hematologic Malignancies
• Bibliography: Includes bibliographical references and index.
• Hierarchical level: Monograph
• Statement of Responsibility: edited by Owen A. O'Conner, Stephen M. Ansell, and John F. Seymour.

Currently, genomic databases offer a vast amount of information on mutational profiles and records of statistically significant genetic associations with diseases. However, the functional interpretation of frequently mutated genes implicated in cancer is essential for the development and clinical implementation of efficient targeted therapies. This review identifies and describes the most affected signaling pathways that are found deregulated in several cancer types and reports on corresponding targeted therapies, aiming to unravel literature gaps and to highlight targets of high therapeutic potential. To this purpose, we collected gene lists from the TCGA Pan-Cancer Atlas and OncoKB and employed the Onco Query Language (cBioPortal) search, to identify somatic driver events in 10,439 tumor samples. Each mutation was linked to the affected pathways and to the corresponding tumorigenic potential. Based on this analysis, the 10 most frequently mutated signaling pathways were selected for this review. A detailed description of the mechanistic implications of the identified mutations, as well as the corresponding cancer types and cognate therapeutic applications currently being employed or being under clinical investigation in clinical trials, is discussed. This review aims to explain how the utilization of available genomic mutation data can be employed for the development of targeted therapies, thereby advancing personalized medicine.