Advanced breast cancer diagnosis: Multiplex RT-qPCR for precise typing and angiogenesis profiling.

Breast cancer (BC) remains the foremost cause of cancer-related mortality, with an estimated 2.3 million new cases anticipated globally. The timely diagnosis of BC is pivotal for effective treatment. Currently, BC diagnosis predominantly relies on Immunohistochemistry (IHC), a method known for its sluggishness, expense, and dependence on proficient pathologists for confident cancer typing. In this study, we introduce a novel approach to enhance the accuracy, speed, and cost-effectiveness of BC diagnosis. We employ multiplex Reverse Transcription quantitative Polymerase Chain Reaction (RT-qPCR) with touch-down methods, which consistently yield significantly lower Cycle Threshold (CT) values. The study evaluates gene expression profiles of HER2, PGR, ESR, and Ki67 genes across 61 samples representing four BC subtypes, using RPL13A as the endogenous control gene. The results demonstrate that our method offers remarkable precision, nearly equivalent to IHC, in detecting gene expressions vital for BC diagnosis and subtyping. Moreover, we explore the gene expression of Hif1A, ANG, and VEGFR genes involved in angiogenesis, shedding light on the metastatic potential of the tested BC tumours. Notably, numerous samples exhibit elevated levels of Hif1A and VEGFR, indicating their potential as valuable biomarkers for assessing metastatic status. Collectively, our RT-qPCR methodology emerges as a powerful diagnostic tool for swiftly identifying BC subtypes and can be complemented with other essential tumorigenic biomarker assessments, such as angiogenesis, to further refine cancer characterisation and inform personalised therapeutic strategies for BC patients. This innovation holds the promise of revolutionising BC diagnosis and treatment, offering expedited and reliable insights for improved patient care.

Identification of DNA methylation of CAPN10 gene changes in the patients with type 2 diabetes mellitus as a predictive biomarker instead of HbA1c, random blood sugar, lipid profile, kidney function test, and some risk factors.

Objective. Nowadays, type 2 diabetes mellitus (T2DM) is the most common chronic endocrine disorder, affecting an estimated 5-10% of adults worldwide and this disease rapidly increases in the Kurdistan region population. This research aims to identify DNA methylation change in the CPAN10 gene as a predictive biomarker in T2DM and the association between DNA methylation status with lipid profile and kidney function test. Methods. The participants (113) were divided into three groups: diabetes group (47), prediabetes group (36), and control group (30). The study was carried out on patients who visited the private clinical sectors between August and December 2021 in the Koya city Kurdistan region of Iraq. To determine DNA methylation status, methylation-specific PCR (MPS) with paired primer for each methylated and unmethylated region was used. The Mann-Whitney U test and Spearman's correlation were performed for statistical analysis of data and a value of p<0.05 was considered significant. Results. The obtained results show that DNA hypermethylation was recorded in the promoter region in the samples of the diabetes and prediabetes groups compared to the healthy group (control). Various factors also affected the level of DNA methylation, such as HbA1c in prediabetes group and body mass index in the control group. Conclusion. These results indicate that DNA methylation changes in the CAPN10 gene promoter region may be used as a potential predictive biomarker to diagnose T2DM; however, this study requires further data to support this evidence.

Identification of DNA methylation change in TCF7L2 gene in the blood of type 2 diabetes mellitus as a predictive biomarker in Iraq Kurdistan region by using methylation-specific PCR.

Objective. Nowadays, type 2 diabetes mellitus (T2D) is the most common chronic endocrine disorder affecting an estimated 5-10% of adults worldwide, and this disease also rapidly increased among the population in the Kurdistan region. This research aims to identify DNA methylation change in the TCF7L2 gene as a possible predictive T2D biomarker. Methods. One hundred and thirteen participants were divided into three groups: diabetic (47), prediabetic (36), and control (30). The study was carried out in patients who visited the private clinical sector between August and December 2021 in Koya city (Iraq Kurdistan region) to determine DNA methylation status using a methylation-specific PCR (MSP) with paired primers for each methylated and non-methylated region. In addition, the X2 Kruskal-Wallis statistical and Wilcoxon signed-rank tests were used, p<0.05 was considered significant. Results. The results showed hypermethylation of DNA in the promoter region in diabetic and prediabetic groups compared to the healthy controls. Different factors affected the DNA methylation level, including body max index, alcohol consumption, family history, and physical activity with the positive Coronavirus. Conclusion. The results obtained indicate that DNA methylation changes in the TCF7L2 promoter region may be used as a potential predictive biomarker of the T2D diagnosis. However, the findings obtained in this study should be supported by additional data.