In recent years, the fields of epigenetics and PGx have intersected in fascinating ways, some very positive and others leading to questions around the validity or utility of PGx and its role in personalized or precision medicine. Both areas of genomics play a role in understanding how genes influence drug response and how modifications in gene expression can affect health outcomes and responses to medications. By overlaying epigenetic profiles onto PGx data, research is uncovering a more detailed understanding of individual variability in drug efficacy and toxicity. New clinical research is also leveraging drugs that modify disease-associated epigenetic targets in ways unimaginable just a few years ago. In this blog we explain how our knowledge of these two distinct fields of genomics is collectively expanding our understanding of phenotypic variations, and how by combining these traits will expand our understanding of individual drug responses (Peedicayil, 2006).

Pharmacogenomics is the study of how a person's genetic makeup affects their response to drugs and aims to predict whether a patient will respond well to a medication, experience side effects, or need a different dosage (Szyf, 2004). It is a field of genomics that has been gaining traction as more clinical evidence supports its value to patients.

Epigenetics, on the other hand, refers to changes in gene expression that do not involve alterations in the DNA sequence itself, but rather modifications of the chromatin structure. These changes are influenced by environmental factors, lifestyle choices, and physiological states, and they can regulate when and how certain genes are activated or silenced. There are a few distinct epigenetic mechanisms that include DNA methylation, histone modification, and non-coding RNA activity, all of which play crucial roles in regulating gene expression. These epigenetic processes ensure that genes are turned "on" or "off" as needed, allowing cells to differentiate and function in specific ways. However, when these mechanisms go awry, they can contribute to diseases such as cancer, diabetes, and neurodegenerative disorders.

Epigenetic Driven Drug Responses

While PGx focuses primarily on static genetic variations, such as single nucleotide polymorphisms (SNPs), epigenetics introduces a dynamic layer of control over gene expression. This means that even if two individuals have the same genetic variations related to drug metabolism, differences in their epigenetic landscapes could result in different responses to the same medication. This has recently been described by the term pharmacoepigenetics - referring to epigenetic modification in gene expression of drug-metabolizing proteins and membrane transporters that may result in a variation in response to a given drug.

In a hypothetical example, DNA methylation patterns can silence or activate the CYP2D6 gene involved in the metabolism of tamoxifen, a drug used to treat breast cancer. DNA methylation or histone modifications in the promoter region of the CYP2D6 gene may silence its expression, even in individuals without genetic polymorphisms. The result is that even if the patient has a genetic profile consistent with an extensive metabolizer, epigenetic silencing of the CYP2D6 gene would have the effect of reducing tamoxifen metabolism, thereby decreasing the production of the active molecule, endoxifen; this potentially decreases the efficacy of the drug and increases the risk of cancer recurrence in the patient.

There are some well characterized real world scenarios where pharmacoepigenetic profiling is helping to identify responding patient cohorts, much in the same way as other companion diagnostic tests that are used in precision medicine. For example, the drugs Azacitidine and Decitabine are DNA methylation inhibitors that are used to treat myelodysplastic syndromes (MDS). They have shown the most efficacy in patients with hypermethylated tumor suppressor genes, as they work to reverse the methylation and activate the silenced genes, enabling the patient to respond to the tumor.

Conversely, epigenetic modifications have also been shown to mediate drug resistance by either silencing or activating genes involved in drug metabolism or transport, or the protein target of the drug. For example, resistance of ovarian cancer to platinum-based chemotherapeutics such as Cisplatin is associated with the hypermethylation of genes such as MLH1 that are involved in DNA mismatch repair. By monitoring patients for these epigenetic changes in the tumor and surrounding tissue, clinicians are more effectively able to manage the therapeutic intervention and combine treatments with epigenetic drugs (Lugones et. al. 2022).

Epigenetic Drug Development

With the increased understanding of epigenetic mechanisms, there has been a push to develop drugs that reverse aberrant epigenetic modifications, particularly in the field of oncology, to manage disease progression. These are frequently used in combination with chemotherapy or immunotherapy to overcome acquired resistance. Vorinostat is one such drug, approved for the treatment of cutaneous T-cell lymphoma by modifying histone acetylation to reactivate silenced tumor suppressor genes (Marks and Dokmanovic, 2005). Epigenetic changes in cancer cells and within the tumor microenvironment have also been shown to influence a patient’s response to checkpoint inhibitors such as anti-PD-1 or anti-CTLA-4 therapies, and the incorporation of demethylation agents has been shown to improve the efficacy of checkpoint therapies by altering the tumor microenvironment (Yang et. al. 2023).

There are caveats with all this that research is working through; firstly, epigenetic changes are fluid, and reversible, and secondly, epigenetic changes can be considered cell and/or tissue specific. This makes it challenging to both identify the epigenetic modifications as well as assess their significance and potential impact. Furthermore, epigenetic changes can take several different forms including DNA methylation, histone acetylation, phosphorylation, ubiquitylation and sumolyation. The implications of these different modifications are varied and may work to create complex regulatory networks that fine-tune gene expression in response to changing cellular needs (see Table 1).