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Updated: Jan 13, 2026

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
Published on: September 20, 2016
Genetic Landscape of Solid Malignant Tumors in a Russian Cohort of Patients
Iurii K Slepov1,2,3, Evgeniy D Kopylov1, Anton A Turchin1
1Petrovsky National Research Centre of Surgery, 119435 Moscow, Russia.
Abstract:
Background/Objectives: Comprehensive genomic profiling (CGP) is a cornerstone of personalized oncology. However, large-scale, systematic data on the somatic mutation spectrum in Russian cancer patients are scarce. This study aimed to characterize the genomic landscape and assess the potential for matched therapy in a Russian cohort of patients with solid tumors. Methods: This retrospective study included 204 patients with various solid tumors. CGP was performed using the FoundationOne®CDx (FFPE tissue) and FoundationOne®Liquid CDx (cfDNA) platforms. The analysis assessed single-nucleotide variants, indels, copy number alterations, gene fusions, tumor mutational burden (TMB), microsatellite instability (MSI), and PD-L1 expression. Results: The most frequently mutated genes were TP53 (61.5%) and KRAS. The median TMB was 4.0 mut/Mb and was significantly lower in stage IV tumors. Significant co-occurrence was observed between KRAS and TP53 mutations, as well as between APC and KRAS mutations, which were particularly characteristic of colorectal cancer. KRAS mutations were associated with higher combined positive score (CPS) values in cases with lung cancer. Based on the CGP results, 44% of patients had findings that supported the use of an approved matched targeted therapy or immunotherapy for their tumor type. An additional 36% of patients had alterations indicating potential benefit from off-label targeted therapy. Conclusions: This study reveals the distinct genomic characteristics of solid tumors in a Russian cohort and confirms the high clinical utility of CGP for identifying actionable targets. Implementing CGP early in the diagnostic process is a necessary step towards realizing personalized treatment strategies for cancer patients.
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