M.L. Nikonorova1, L.K. Kats2, N.Ya. Pichugina3

1,2 Federal State Budgetary Educational Institution of Higher Education Academician I.P. Pavlov First St. Petersburg State Medical University of the Ministry of Healthcare of Russian Federation (Saint–Petersburg, Russia)
3 Federal State Autonomous Educational Institution of Higher Education Saint-Petersburg State University of Aerospace Instrumentation (SUAI) (Saint–Petersburg, Russia)

1 nikonorovaml@1spbgmu.ru, 2 leonidkats2003@mail.ru, 3 nike.pichugina@gmail.com

Cancer is a serious health issue which requires complex treatment. Acute myeloid leukemia is one of the most common kinds of leukemia among adults and averages 3-5 per 100,000 people per year. The average age of people when they are first diagnosed with AML is about 68. Advances in next-generation sequencing (NGS) allow the detection of clinically relevant gene mutations, making NGS an increasingly important diagnostic tool in the characterization of myeloid malignancies. Finding the most significant genes that influence the development of the disease is necessary for the disease prognosis.

This study aims at doing something a systematic review of authors’ gene panels and perform a meta-analysis to assess the statistical association between the prognostic value of genetic mutations and the authors' gene panels. The systematic literature review using eLibrary & PubMed identified 465 relevant publications from 1996 to 2023. The inclusion criteria were as follows: patient characteristics (sex, age), adequacy of sample size (more than 30 patients), the presence of control group, size of the gene panel (more than 40 genes), method of gene panel analysis, number of mutations detected, statistical evaluation of the obtained results. The exclusion criteria were the following: abstracts do not meet the main purpose of this review, animal studies, clinical guidelines, lack of clear distribution of data, access to the full text of the study is restricted, materials of conferences, forums and congresses. Rayyan online program was used to track duplicate publications. Meta-analysis was performed using the RStudio application package. The meta-analysis includes 19 studies with a total number of 7252 patients. The difference between the authors' panel of genes characterizing the patients' disease and the identified mutations was found to be highly statistically significant (p-value < 0.0001). Cochran's Q-test (Q = 54.69) and Higgins & Thompson statistic (67.1%) show the significant heterogeneity of the included studies. Funnel plot and quantitative Egger's test results showed no publication bias.

This meta-analysis summarizes data from several studies (gene panels, identified mutations and their prognostic changes). The studies were conducted from 2015 to 2023 in the following countries: Canada, China, Japan, Portugal, Republic of Korea, Russia, Spain, USA. 5 studies did not separate patients by sex, 14 studies included 1437 males and 1025 females.

The size of the authors' panels ranged from 40 to 236 genes; the number of detected mutations ranged from 10 to 76. Noticeably, the maximum number of mutations is detected among patients older than 60 years (panel of 79 genes). Likewise, a panel of 80 genes reveals 58 mutations. Among patients under 18 years mutations averaged about 30% of the gene panel size.

Statistically significant difference between genetic mutations and author's gene panels was obtained in 8 studies. In 3 studies, 100% sensitivity and specificity were found, but this does not mean that the results are perfect; false positives are possible, which may lead to diagnostic errors.

The meta-analysis shows that the most frequently mutated genes in OML are: NPM1, FLT3 (unfavorable prognosis), CEBPA (favorable prognosis), RUNX1 (unfavorable prognosis), PAC, TP53 (unfavorable prognosis). The understanding of the statistical relationship between genetic mutations and mutant genes is critical to the disease study.

Nikonorova M.L., Kats L.K., Pichugina N.Ya. Quantitative analysis of the author's gene panels and identified mutations in patients with acute myeloid leukemia (meta-analysis). Technologies of Living Systems. 2025. V. 22. № 1. Р. 31-41. DOI: https://doi.org/10.18127/ j20700997-202501-03 (In Russian).

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