Pharmacogenomics in Solid Tumors: A Comprehensive Review of Genetic Variability and Its Clinical Implications

Abstract

Pharmacogenomics, the study of how genetic variations influence drug response, has become integral to cancer treatment as personalized medicine evolves. This review aims to explore key pharmacogenomic biomarkers relevant to cancer therapy and their clinical implications, providing an updated and comprehensive perspective on how genetic variations impact drug metabolism, efficacy, and toxicity in oncology. Genetic heterogeneity among oncology patients significantly impacts drug efficacy and toxicity, emphasizing the importance of incorporating pharmacogenomic testing into clinical practice. Genes such as CYP2D6, DPYD, UGT1A1, TPMT, EGFR, KRAS, and BRCA1/2 play pivotal roles in influencing the metabolism, efficacy, and adverse effects of various chemotherapeutic agents, targeted therapies, and immunotherapies. For example, CYP2D6 polymorphisms affect tamoxifen metabolism in breast cancer, while DPYD variants can result in severe toxicities in patients receiving fluoropyrimidines. Mutations in EGFR and KRAS have significant implications for the use of targeted therapies in lung and colorectal cancers, respectively. Additionally, BRCA1/2 mutations predict the efficacy of PARP inhibitors in breast and ovarian cancer. Ongoing research in polygenic risk scores, liquid biopsies, gene-drug interaction networks, and immunogenomics promises to further refine pharmacogenomic applications, improving patient outcomes and reducing treatment-related adverse events. This review also discusses the challenges and future directions in pharmacogenomics, including the integration of computational models and CRISPR-based gene editing to better understand gene-drug interactions and resistance mechanisms. The clinical implementation of pharmacogenomics has the potential to optimize cancer treatment by tailoring therapies to an individual's genetic profile, ultimately enhancing therapeutic efficacy and minimizing toxicity.

Keywords: oncology; personalized medicine; pharmacogenomics.

Figure 1

The aims of personalized medicine include the understanding of genetic variability, tumor heterogeneity, and medical context (health records, medical imaging, staging).

Figure 2

Key pharmacogenomic genes with clinical implications in solid tumors. Green arrows indicate a reduction in function, while red arrows indicate an increase. The beam represents dysfunction, which can imply either an increase or a decrease in enzyme function.