Negar Sarhangi

Background Cancer treatment has improved over the past decades, but many cancer patients still experience adverse drug reactions (ADRs). Pharmacogenomics (PGx), known as personalized treatment, is a pillar of precision medicine that aims to optimize the efficacy and safety of medications by studying the germline variations. Germline variations in the DPYD lead to significant ADRs. The present cross-sectional study aims to evaluate the allele frequency of the DPYD gene variations in the Iranian population to provide insights into personalized treatment decisions in the Iranian population. Methods The allele frequency of 51 pharmacogenetic variations in the clinically relevant DPYD was assessed in a representative sample set of 1142 unrelated Iranian individuals and subpopulations of different ethnic groups who were genotyped using the Infinium Global Screening Array-24 BeadChip. Results The genotyping assay revealed eight pharmacogenetic variants including DPYD rs1801265 (c.85T > C; DPYD*9A), rs2297595 (c.496A > G), rs1801158 (c.1601G > A; DPYD*4), rs1801159 (c.1627A > G; DPYD*5), rs1801160 (c.2194G > A; DPYD*6), rs17376848 (c.1896T > C), rs56038477 (c.1236G > A; HapB3), and rs75017182 (c.1129-5923C > G; HapB3) with minor allele frequency (MAF) ≥ 1%. Conclusion The results of the study reveal significant genetic variations among Iranian population that could significantly influence clinical decision-making. These variants, with their potential to explain the substantial variability in drug response phenotypes among different populations, shed light on a crucial aspect of pharmacogenomics. These findings not only provide valuable insights but also inspire the design and implementation of future pharmacogenomic clinical trials, motivating further research in this crucial area. Graphical abstract

Objectives The efficacy and safety of drug treatments vary widely due to genetic variations. Pharmacogenomics investigates the impact of genetic variations on patient drug response. This research investigates the frequency of UGT1A1 genetic variations in the Iranian population, comparing them with global data to provide insights into the pharmacogenomic approach in the Iranian population. Methods The study was conducted using the data of the Bushehr Elderly Health (BEH) program, a population-based cohort study of the elderly population aged ≥ 60 years. Genotyping of three UGT1A1 variant alleles (UGT1A1*6, UGT1A1*27, and UGT1A1*80) was performed on a group of 2730 elderly Iranian participants with the Infinium Global Screening Array. Results The genotyping analysis revealed significant differences compared to major global populations that were addressed in the gnomAD database. UGT1A1*80 was found at a high frequency (32.34%), and followed by UGT1A1*6 (0.76%) and UGT1A1*27 (0.018) at a low frequency in the Iranian group. Conclusions The UGT1A1*80 was the more prevalent allele between investigated alleles in the present study which can be considered as an important allele for pharmacogenomic testing.

Breast cancer is a heterogeneous disorder with different molecular subtypes and biological characteristics for which there are diverse therapeutic approaches and clinical outcomes specific to any molecular subtype. It is a global health concern due to a lack of efficient therapy regimens that might be used for all disease subtypes. Therefore, treatment customization for each patient depending on molecular characteristics should be considered. Precision medicine for breast cancer is an approach to diagnosis, treatment, and prevention of the disease that takes into consideration the patient’s genetic makeup. Precision medicine provides the promise of highly individualized treatment, in which each individual breast cancer patient receives the most appropriate diagnostics and targeted therapies based on the genetic profile of cancer. The knowledge about the molecular features and development of breast cancer treatment approaches has increased, which led to the development of new targeted therapeutics. Tumor genomic profiling is the standard of care for breast cancer that could contribute to taking steps to better management of malignancies. It holds great promise for accurate prognostication, prediction of response to common systemic therapies, and individualized monitoring of the disease. The emergence of targeted treatment has significantly enhanced the survival of patients with breast cancer and contributed to reducing the economic costs of the health system. In this review, we summarized the therapeutic approaches associated with the molecular classification of breast cancer to help the best treatment selection specific to the target patient.

In recent years, artificial intelligence (AI) shows promising results in the diagnosis, prediction, and management of diseases. The move from handwritten medical notes to electronic health records and a huge number of digital data commenced in the era of big data in medicine. AI can improve physician performance and help better clinical decision making which is called augmented intelligence. The methods applied in the research of AI and endocrinology include machine learning, artificial neural networks, and natural language processing. Current research in AI technology is making major efforts to improve decision support systems for patient use. One of the best-known applications of AI in endocrinology was seen in diabetes management, which includes prediction, diagnosis of diabetes complications (measuring microalbuminuria, retinopathy), and glycemic control. AI-related technologies are being found to assist in the diagnosis of other endocrine diseases such as thyroid cancer and osteoporosis. This review attempts to provide insight for the development of prospective for AI with a focus on endocrinology.

Background Type 2 diabetes mellitus (T2DM) is a common chronic condition characterized by high blood glucose levels which is caused by genetic and environmental factors. Currently, pharmacogenomics (PGx) is anticipated to enable the development of personalized treatment in a wide range of health issues. Sulfonylureas (SFUs) are among the oral anti-diabetic drugs that are very popular due to their low cost. Genetic variants in transcription factor 7 like 2 (TCF7L2) and potassium voltage-gated channel subfamily Q member 1 (KCNQ1) have been reported for altered therapeutic response to sulfonylurea. The aim of the present study is to evaluate any association between common genetic variant of the TCF7L2 and KCNQ1 (rs7903146 and rs2237892, respectively) and the response to sulfonylurea in a group of Iranian patients for the first time. Methods Genotyping was carried out in 30 T2DM patients who received sulfonylurea treatment for more than two months in addition to previous medication using the Sanger sequencing method. Results In 30 T2DM patients who received SFUs treatment, 60%, 33.3% and 6.7% had CC, CT and TT genotypes, respectively. After treatment, adjusted fasting blood sugar (FBS) mean reduction level in CT and TT carriers was lower than CC carriers. Adjusted hemoglobin A1c (HbA1c) mean reduction level was also lower in CT and TT compared with CC carriers, but, none of these differences were statistically significant. Genotype frequencies of TT, CT and CC genotypes of rs2237892 variant of KCNQ1 gene were 0 (0%), 3 (10%) and 27 (90%) respectively. Patients with CT and CC genotypes of rs2237892 variant had also similar changes in FBS (P=0.200) and HbA1c (P=0.436) after treatment with SFUs. Conclusions Genotypes of TCF7L2 and KCNQ1 common variant did not show any impact on the treatment response among T2DM patients receiving SFUs.

Background The most effective and common treatment for end-stage renal disease is kidney transplantation. The personalized approach to kidney transplantation, which utilizes precision medicine principles, determines distinctive genomics characteristics of candidates/recipients that must be taken into account. Cytotoxic T lymphocyte associated protein 4 (CTLA4) may be a suitable candidate gene for studying allograft rejection. The aim of this study was to understand whether we can consider two common variants of the CTLA4 gene as a risk factor of transplant rejection in a group of Iranian population. Methods Totally, 169 kidney transplant recipients, including acute rejections (N=39) and non-rejection (N=130) groups who underwent transplantation were included in this study. The genotyping of rs5742909 (−318C/T) and rs231775 (+49A/G) variants of the CTLA4 gene were performed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. Results The AG genotype frequency of rs231775 variant was the same in both patients with and without a history of rejection while, none of those groups had homozygote genotype. In rs5742909, both CT and TT frequencies of patients with rejected transplant were lower than patients with a normal outcome. Conclusions The results of the presented study suggest that rs231775 and rs5742909 of CTLA4 genetic variants are not linked to acute rejection who underwent kidney transplantation. So, these variants cannot be considered as risk factors of acute allograft rejection in a group of Iranian renal transplantation recipients. However, the transplantation precision medicine may be an important area for the improvement of patients outcome as the precision medicine has already entered clinical practice in kidney transplantation.