Madina Orazgaliyeva
@onco.kz
molecular genetic research center
KazIOR
RESEARCH, TEACHING, or OTHER INTERESTS
Genetics, Cancer Research
Scopus Publications
Scopus Publications
Jandos Amankulov, Dilyara Kaidarova, Zhamilya Zholdybay, Marianna Zagurovskaya, Oxana Shatkovskaya, Akmaral Ainakulova, and Madina Orazgaliyeva
Termedia Sp. z.o.o.
IntroductionIncreased natural killer cell activity (NKCA) is linked to reduced risk of colorectal cancer (CRC). Several prior studies have investigated the association of NKCA and the incidence of CRC in high-risk subjects. The aim of our study was to investigate NKCA sensitivity in diagnosing advanced neoplasia (AN) and CRC in an average risk population.Material and methodsNKCA was assessed by an enzyme-linked immunosorbent assay (ELISA) blood test in average risk subjects with a range of 25–2500 pg/ml set for ELISA. NKCA higher than 200 pg/ml was defined as negative. The performance of NKCA was evaluated using measures such as sensitivity, specificity, negative and positive predictive values (NPV, PPV), clinical utility index, etc. In addition, odds ratios for developing CRC using logistic regression models were calculated.ResultsNKCA was evaluated in 354 average risk individuals (mean age: 58.5 years; 36.2% male). The diagnostic accuracy of NKCA for CRC and AN was 75.5% and 72.3% respectively, with 96.4% NPV. The NKCA test demonstrated a good negative clinical utility index for CRC and AN (0.664 and 0.741, respectively). Individuals with low NKCA had 6.84 times higher odds of having CRC (95% CI: 2.31–20.27; p < 0.001). NKCA was higher in men vs. women (548.5 pg/ml vs. 500.0 pg/ml) and lower in smokers (412 pg/ml vs. 544 pg/ml), non-exercisers (413 pg/ml vs. 653.5 pg/ml), alcohol users (389 pg/ml vs. 476 pg/ml), and native Kazakhs and other Asian ethnic groups (446 pg/ml vs. 514 pg/ml).ConclusionsA high NKCA level has potential ability to rule out CRC and AN in an average risk population.
Saule Yermekova, Madina Orazgaliyeva, Tatyana Goncharova, Farida Rakhimbekova, Dilyara Kaidarova, and Oxana Shatkovskaya
EpiSmart Science Vector Ltd
Introduction: Gastric and colorectal adenocarcinomas are prevalent malignancies characterized by mutations in genes such as p53, RAS, and MDM2, which play crucial roles in tumorigenesis and cancer progression. Understanding the specific mutational patterns and their implications in these cancers was essential for identifying potential therapeutic targets. Aim: To identify the nature of mutational disorders in the p53, p21Waf1, RAS and MDM2 genes, depending on the degree of cell differentiation by adenocarcinomas of the gastrointestinal tract. Methods: Genomic DNA was isolated from 200 samples of stomach tissue and 233 samples of colon and rectum adenocarcinomas. A total of 433 samples, including gastric adenocarcinomas, colon and rectum adenocarcinomas and adjacent tissues, were collected. Results: Genomic DNA was isolated, and mutational analysis of p53, RAS (HRAS, KRAS, NRAS), and MDM2 genes was performed using polymerase chain reaction, gel electrophoresis, and restriction enzyme analysis. The deletion of p53 exon-intron 5-6, as well as HRAS 12 and HRAS 61 mutations, were detected in 78% of poorly differentiated adenocarcinomas. The deletions of p53 exon-intron 7-9 – in 100% of moderately differentiated adenocarcinomas and 50-60% of adjacent tissues. The loss of WAF1 gene expression was registered in almost 90% of poorly differentiated adenocarcinomas and 20% of adjacent tissue samples. The KRAS and NRAS mutations in almost 63.9% of studied colon and rectal samples indicated autonomous cell growth. This explains the aggressive and metastatic growth of tumours and the ineffectiveness of growth factor inhibitors in colorectal cancer. Finding ways to influence specific substitutions in RAS genes could prevent and eliminate uncontrolled invasive tumour growth. Conclusion: By identifying specific gene mutations and differences in genetic markers, the study provided insights for the development of targeted diagnostic methods and personalised treatment strategies, ultimately improving the clinical outcomes in the field of oncology.
T. G. Goncharova, N. A. Omarbayeva, D. R. Kaidarova, M. G. Orazgaliyeva, and L. A. Malysheva
Publishing House ABV Press
Introduction. The growth of primary breast tumor morbidity in the last ten years and increased number of patients with disseminated breast cancer in the Republic of Kazakhstan require the search for methods of early diagnosis of malignant tumors. Determination of breast cancer markers in epigenetic studies allows to use them as diagnostic signs of the presence of malignant tumor and as predictors of treatment effectiveness in patients with this pathology.Aim. To perform a search for therapeutic and prognostic breast cancer markers.Materials and methods. The study included samples of biological material (peripheral blood) of 50 deemed healthy individuals and 103 patients with locally advanced and disseminated breast cancer receiving special therapy. The following methods were used: blood collection, DNA extraction, creation of DNA methylation profiles, sequencing, statistical data analysis.Results. The results of search for epigenetic mutations in peripheral blood of patients with breast cancer showed their role as specific diagnostic, therapeutic and prognostic markers with specificity 0.91 % and sensitivity 0.94 %. The hypothesis on therapeutic significance of identified earlier diagnostic markers in patients with breast cancer, namely hypermethylation of CpG islands associated with genes JAM3, C17orf64, MSC, C7orf51 and CpG island associated with intragene part of chromosome 5 (chr5: 77,208,034–77,329,434) was tested and confirmed.Conclusion. A correlation between DNA methylation characteristics and disease progression during treatment was shown. The study results can be used in clinical practice: epigenetic markers, such as methylation in the CpG islets associated with the JAM3, C17orf64, MSC, C7orf51 genes, and in the CpG islet associated with the intragenic site of chromosome 5 (chr5: 77,208,034–77,329,434) can be used as prognostic markers and therapeutic predictors of breast cancer.
Saule Yermekova, Madina Orazgaliyeva, Tatyana Goncharova, Farida Rakhimbekova, Zaure Dushimova, and Tatiana Vasilieva
EpiSmart Science Vector Ltd
Background: Today, genomic changes are an important cause of the occurrence, growth and progression of cancer. Technological advances in cancer genomic analysis platforms have made it possible to identify genomic alterations that may influence response to lung cancer treatment. Methods: The study examined tumor growth-inhibiting oncogenes and genes responsible for cell growth and division to identify mutations characteristic of malignant lung tumors. The mutations were studied in 400 postoperative samples after amplifying p53 and HRAS fragments and p53, p21Waf1, MDM2 mRNA. p53 or p21Waf1 were expressed in 50% of squamous cell carcinomas and adenocarcinomas of the lung. Results: The study examined tumor growth-inhibiting oncogenes and genes responsible for cell growth and division to identify mutations characteristic of malignant lung tumors. The mutations were studied in 400 postoperative samples after amplifying p53 and HRAS fragments and p53, p21Waf1, MDM2 mRNA. p53 or p21Waf1 were expressed in 50% of squamous cell carcinomas and adenocarcinomas of the lung. HRAS mutations were present in most squamous cell carcinomas and adenocarcinomas of the lung. EcoR1- and Pst1- restriction enzymes destroyed the RT-PCR product of the p53 and p21Waf1 mRNA and increased the level of detected mutations in lung adenocarcinoma to 75% and 50 %, respectively. EGFR mutations were more frequent in lung adenocarcinoma than in lung squamous cell carcinoma. Mutations in EGFR exons 19 and 21 found in 65 of 263 lung tumor samples indicated the tumor sensitivity to EGFR tyrosine kinase inhibitors. EGFR deletions in exon 19 occurred mainly in adenocarcinoma, L858R mutations in EGFR exon 21 were quite common in lung adenocarcinoma. Conclusion: The mutations detected in most squamous cell carcinomas and adenocarcinomas of the lung could be used to diagnose and predict the disease severity and targeted therapy efficacy.