ISSN 2472-0429

Advances in Cancer Prevention
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  • Opinion Article   
  • Adv Cancer Prev 8: 234,

Hereditary Cancer and Personalized Medicine: Tailoring Treatment Based on Genetic Predispositions

Mara Gibe*
Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, United States
*Corresponding Author : Mara Gibe, Department of Translational and Applied Genomics, Kaiser Permanente Center for Health Research, United States, Email: maragibe@gmail.com

Received Date: Jul 01, 2024 / Published Date: Jul 30, 2024

Abstract

Hereditary cancer, driven by genetic predispositions, has significantly transformed the landscape of cancer treatment through the advent of personalized medicine. This paper explores the integration of genetic information into tailored therapeutic strategies, aiming to optimize treatment efficacy and minimize adverse effects for individuals with hereditary cancer. By leveraging insights from genetic testing, healthcare providers can identify specific mutations associated with increased cancer risk and design targeted interventions that address the unique needs of each patient. We examine current advancements in personalized medicine, including the development of targeted therapies, precision drug selection, and personalized screening protocols. Additionally, the paper discusses the challenges and limitations of implementing personalized approaches, such as the need for comprehensive genetic profiling, ethical considerations, and the accessibility of advanced treatments. Through a review of recent research and clinical practices, this paper highlights the potential of personalized medicine to enhance outcomes for patients with hereditary cancer and underscores the ongoing need for innovation and refinement in this evolving field.

Citation: Mara G (2024) Hereditary Cancer and Personalized Medicine: Tailoring Treatment Based on Genetic Predispositions Adv Cancer Prev 8: 234.

Copyright: © 2024 Mara G. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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