Introduction: In recent years, advancements in statistical methodologies for estimating single nucleotide polymorphism (SNP) heritability have revolutionized our understanding of the genetic factors that contribute to complex diseases. SNP heritability refers to the proportion of phenotypic variance in a population that can be explained by genetic variation, specifically the SNPs present within the studied cohort. This concept is pivotal in understanding how genetic variants influence drug responses, disease susceptibility, and other complex traits. In the context of leukemia treatment, understanding genetic variation is particularly crucial. Individual differences in drug response and adverse effects can significantly impact the effectiveness of chemotherapy or targeted therapies, highlighting the need for personalized approaches in oncology. This study investigates the role of SNPs in three key genes—DKC1, CTC1, and TERT—which are involved in telomere maintenance and have been linked to cancer progression and treatment outcomes. By exploring the SNP profiles in these genes, we aim to uncover their potential effects on drug response and adverse drug reactions, contributing to the development of more personalized, genetically informed treatment strategies for leukemia patients.
Methods: To assess the genetic factors influencing drug responses in leukemia, we utilized polymorphism data from the National Center for Biotechnology Information (NCBI) database, which provides a comprehensive resource of genetic variants linked to various diseases and traits. This database was specifically used to extract SNP data for the genes DKC1, CTC1, and TERT—all of which play pivotal roles in maintaining telomere integrity, a process essential for cellular aging, proliferation, and cancerogenesis. These genes were selected for their relevance to leukemia, as disruptions in telomere maintenance are known to contribute to tumorigenesis and therapeutic resistance. The MEGAGENE software was employed to analyze these SNPs, allowing us to estimate their heritability and evaluate how variations in these genes might influence both the efficacy of leukemia therapies and the occurrence of side effects. Through this approach, we sought to explore the genetic basis for variability in drug responses, with the ultimate goal of providing insights into how genetic testing can guide more effective and personalized leukemia treatment.
Results: Our analysis identified several SNPs within the DKC1, CTC1, and TERT genes that were significantly associated with variations in drug efficacy and adverse drug reactions in leukemia patients. Notably, certain polymorphisms in the DKC1 gene were linked to an increased susceptibility to severe side effects during chemotherapy, suggesting that these genetic variants might predispose patients to higher risks of toxicity. Conversely, specific SNPs in the TERT gene were associated with improved therapeutic responses, indicating that these variants may enhance the effectiveness of certain chemotherapy drugs and reduce treatment resistance. The CTC1 gene, involved in telomere maintenance, showed both positive and negative associations with drug efficacy, suggesting that it may play a dual role in modulating treatment outcomes. Overall, SNP heritability estimates for these three genes indicated that genetic variations in DKC1, CTC1, and TERT contribute significantly to the observed variability in drug response and side effect profiles. These findings underscore the importance of genetic testing in predicting patient-specific treatment outcomes and highlight the potential for tailoring drug therapies to minimize side effects and maximize therapeutic efficacy.
Conclusion: This study demonstrates the critical role of genetic variation in influencing drug responses and adverse effects, particularly in the context of leukemia treatment. Our findings suggest that genetic testing for SNPs in key genes such as DKC1, CTC1, and TERT can provide valuable information for guiding treatment decisions. By identifying genetic polymorphisms that are linked to either improved therapeutic outcomes or increased risks of side effects, clinicians can more accurately select the most appropriate drugs for individual patients. This personalized approach could reduce the likelihood of adverse reactions and enhance the overall effectiveness of leukemia therapies. The results from this study support the integration of pharmacogenomic testing into clinical practice, where genetic information can be used to tailor treatments to the unique genetic profile of each patient. In addition, our findings reinforce the growing emphasis on personalized medicine in oncology, where genetic testing is becoming an essential tool for optimizing patient care and improving therapeutic outcomes. Future studies should aim to validate these findings in larger patient cohorts and further refine the genetic markers that can be used to predict drug responses, ultimately leading to more effective and individualized treatment strategies for leukemia and other cancers.
Keywords: SNP heritability, Personalized Medicine, DKC1, CTC1, TERT