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Aim. To assess the efficacy and safety of lenvatinib and pembrolizumab for the treatment of mismatch repair-proficient endometrial cancer (EC) in routine clinical practice in Russia.Materials and methods. This multicenter, retrospective, cohort study included patients with recurrent and metastatic EC from 37 cancer centers in Russia treated between May 2020 and April 2023. Patients with histologically verified EC without microsatellite instability who received ≥1 course of pembrolizumab/lenvatinib therapy were included in the study. The primary endpoint was progression-free survival; the clinical characteristics of the patients were additionally analyzed, the objective response rate and the toxicity profile of therapy were assessed.Results. The study included 100 patients. Median age was 65 (30–83) years. The most common histologic tumor subtype was endometrioid adenocarcinoma (68 %); serous adenocarcinoma was diagnosed in 22 % of cases, other types of tumor – 10 % of cases. All patients had pMMR/microsatellite-stable tumors. The median progression-free survival was 7.75 months (95 % confidence interval 0.7–33.8), and a partial response to therapy was observed in 24 % of patients. Almost half of the patients (44 %) required dose reduction due to adverse events. The most common adverse events included fatigue (n = 26; 26 %), hypertension (n = 20; 20 %), and hypothyroidism (n = 14; 14 %).Conclusion. This study confirms the clinical efficacy of lenvatinib and pembrolizumab in patients with recurrent and metastatic EC without mismatch repair system deficiency (pMMR-tumors) in routine clinical practice.

Deficient DNA mismatch repair (dMMR) is a rare molecular disorder found in 20-30 % of endometrial tumors. Laboratory identification of dMMR/microsatellite instability (MSI) has a high diagnostic value, since these impairments are considered as biomarkers of endometrial adenocarcinoma. They help to identify patients at high risk of Lynch syndrome, evaluate the disease prognosis, and estimate the efficacy of immune checkpoint inhibitors and their combinations. This review details current concepts of MSI diagnostics and discusses its predictive value in patients with endometrial cancer. It also describes a new diagnostic algorithm for the detection of dMMR and MSI.

A model of abstracting textual information, based on the formalization of information languages by a special generative grammar and the concepts of word self-descriptiveness and contextual links between words, is considered. A method of abstracts synthesis for textual documents by identifying informative sentences, constructing their context and generating chains of syntax trees is suggested.