The term “pharmacogenetics” is used to describe the study of variability in drug response due to heredity. It is associated with “gene – drug interactions”. Later on, the term “pharmacogenomics” has been introduced and it comprises all genes in the genome that can define drug response. The application of pharmacogenetics in oncology is of a great significance because of the narrow therapeutic index of chemotherapeutic drugs and the risk for life-threatening adverse effects. Many cancer genomics studies have been focused on the acquired, somatic mutations; however, increasing evidence shows that inherited germline genetic variations play a key role in cancer risk and treatment outcome. The aim of this review is to summarize the state of pharmacogenomics in oncology, focusing only on germline mutations. Genetic polymorphisms can be found in the genes that code for the metabolic enzymes and cellular targets for most of the chemotherapy drugs. Nevertheless, predicting treatment outcome is still not possible for the majority of regimens. In this review, we discuss the most comprehensively studied drug-gene pairs – present knowledge and current limitations. However, further studies in larger groups of cancer patients are necessary to be conducted with precise validation of pharmacogenetic biomarkers before these markers could be routinely applied in clinical diagnosis and treatment.

Background/Objectives: Pharmacogenetic variability influences the efficacy and toxicity of anticancer therapies. However, Eastern European populations remain underrepresented in pharmacogenetic databases. This study aimed to characterize pharmacogenetic variants relevant to chemotherapy response in the Bulgarian population and compare their allele frequencies with reference populations. Methods: Ninety individuals were included, comprising 50 patients with colorectal, non-small cell lung, or breast cancer and 40 healthy controls. Genomic DNA and circulating cell-free DNA were analyzed by next-generation sequencing targeting pharmacogenetic genes involved in drug metabolism, transport, and DNA repair. Allele frequencies were compared with gnomAD v2.1.1 reference data. Sensitivity analyses compared Bulgarian controls with Bulgarian non-cancer and combined Southern European, Northwestern European, and Other non-Finnish European non-cancer populations. Results: Twenty-three pharmacogenetic variants were evaluated. Six variants remained statistically significant after Benjamini–Hochberg correction in both Fisher’s exact test and the two-proportion Z-test. Five variants—DPYD c.2194G>A, XPC c.2815C>A, EGFR c.1562G>A, XRCC1 c.1196A>G, and ERCC2 c.2251A>C—showed higher allele frequencies, whereas ERCC2 c.934G>A was less frequent in the Bulgarian cohort. DPYD c.85T>C remained significant after correction in the Z-test but not in Fisher’s exact test. Sensitivity analyses confirmed the significance of XPC c.2815C>A in both reference-population comparisons, while DPYD c.85T>C remained significant only against the combined European reference population. Conclusions: Several pharmacogenetic variants showed distinct allele frequencies in the Bulgarian cohort. XPC c.2815C>A demonstrated the most robust population-specific pattern across sensitivity analyses. These findings highlight the value of locally derived pharmacogenetic data for precision oncology and pharmacogenetically guided treatment strategies.

Background/Objectives: Pharmacogenetic variability plays an important role in determining the efficacy and toxicity of anticancer therapies. However, Eastern European populations remain underrepresented in global pharmacogenetic databases, limiting the implementation of population-specific precision medicine approaches. This study aimed to characterize pharmacogenetic variants relevant to chemotherapy response in the Bulgarian population and compare their allele frequencies with those reported in global populations. Methods: A total of 90 individuals were included, comprising 50 patients diagnosed with colorectal, non-small cell lung, or breast cancer and 40 healthy controls. Genomic DNA and circulating cell-free DNA samples were analyzed using next-generation sequencing targeting clinically relevant pharmacogenetic genes involved in drug metabolism, transport, and DNA repair. Allele frequencies were determined and compared with available global population data. Results: Twenty-three pharmacogenetic variants were evaluated. Six variants, namely MTHFR c.665C>T, DPYD c.2194G>A, XPC c.2815C>A, EGFR c.1562G>A, XRCC1 c.1196A>G, and ERCC2 c.2251A>C, exhibited significantly higher allele frequencies in the Bulgarian cohort than in global populations (p < 0.05). In contrast, four variants, MTHFR c.1286A>C, DPYD c.85T>C, ABCG2 c.421C>A, and ERCC2 c.934G>A, were significantly less frequent (p < 0.05). Conclusions: The Bulgarian population exhibits distinct pharmacogenetic characteristics compared with global reference populations. These findings contribute to the understanding of population-specific genetic variability and support the incorporation of Bulgarian pharmacogenetic data into precision oncology research and pharmacogenetic-guided treatment strategies.