Abstract
Relevance: Gastric cancer is a heterogeneous disease whose development is associated with both genetic and acquired somatic mutations. Identifying optimal diagnostic markers for gastric cancer with high sensitivity and specificity will improve patient survival rates and contribute to the advancement of personalized medicine. Identifying biomarkers by integrating clinical data and comprehensive genomic analysis can significantly enhance the accuracy of diagnosis, disease progression prediction, recurrence risk assessment, and treatment response. This work discusses promising biological markers that may be used for early diagnosis of gastric cancer and predicting the effectiveness of various treatment methods.The purpose was to analyze current scientific literature to identify new and recently developed biomarkers for diagnostic and prognostic value concerning malignant stomach tumors.Methods: In this review, we searched electronic medical literature in the PubMed and Google Scholar databases. The search utilized keywords: “biomarker,” “gastric cancer,” “early detection,” “diagnosis,” and “prognosis.” Full-text publications in English and Russian, available in open access and focused on the role of biomarkers in early diagnosis and prognosis of gastric cancer, published in the last ten years, were included. Case reports, correspondence, letters, and studies not conducted on humans were excluded from the review. The analysis revealed an insufficient accuracy of existing biomarkers for gastric cancer diagnosis and prognosis. Within the modern approach to disease classification framework, a new molecular type was proposed: tumors infected with the Epstein-Barr virus, tumors with microsatellite instability, genomically stable tumors, and chromosomally unstable tumors.Conclusion: Current research on gastric cancer focuses on identifying and validating new non-invasive biomarkers. Further studies are necessary to enhance sensitivity and broaden the application of these biomarkers for early diagnosis and predicting treatment efficacy
Published Version
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