Prostat kanseri hastalarında IDH 1 gen mutasyonlarının yeni nesil dizileme metodu ile belirlenmesi

The second most common type of cancer among men is prostate cancer. The aim of our study was to evaluate MGMT and ATRX genes, especially IDH1, with next-generation sequencing, to detect potential mutations and their relationship with risk classes of the disease. Analyses were performed using peripheral blood samples from 27 patients diagnosed with prostate cancer. IDH1, MGMT and ATRX genes were evaluated by next generation sequencing. In addition, analysis was performed to evaluate the effects of detected mutations in D'Amico intermediate-risk and high-risk groups. The mean age of the study group was 68 years (53-83); 88.89% of the patients were aged 60 years or older, and 11.11% were under 60 years of age. The prostate volume, PSA level, cT1c, Gleason score, and Tm % of the patient group's clinical data were significantly different between the intermediate-risk and high-risk patient groups (p=0.003, p=0.048, p=0.000, and p=0.001, respectively). The target genes were sequenced, and as a result, 11 mutations were found in total: 3 in IDH1, 6 in MGMT, and 2 in ATRX genes. The majority of the detected mutations in prostate cancer were identified for the first time. According to D'Amico risk groups, it was found that the c.159C>T (rs1803965) and c.250C>T (rs12917) MGMT gene mutations varied significantly from one another (p=0.017). The heterozygous mutant genotypes of the patient with the IDH1 c.548 A>G (rs34599179) missense mutation, the five patients with the MGMT gene c.159C>T synonymous mutation, and the five prostate cancer patients with the MGMT gene c.250C>T missense mutation were confirmed by Sanger sequencing. These identified mutations should undoubtedly be included in the classification of prostate cancer. Whether or not they can be assessed in clinical applications is debatable. However, integrating molecular parameters with standard evaluation criteria will contribute to the application of personalized treatment methods by evaluating the clinical data of prostate cancer patients with a higher accuracy rate.