Valentina D. Yakushina

The liver is the central organ in metabolism; however, modeling hepatic diseases remains limited by current experimental models. Animal models frequently fail to predict human liver physiology, while primary hepatocytes rapidly dedifferentiate in culture. We performed comprehensive transcriptomic profiling of induced pluripotent stem cells (iPSCs) differentiation into hepatocyte-like cells (HLCs) under two-dimensional (2D) and three-dimensional (3D) culture conditions. RNA sequencing analysis revealed the sequential activation of lineage-specific markers across major developmental stages: definitive endoderm (FOXA2, SOX17, CXCR4, CER1, GATA4), posterior foregut (PROX1, GATA6), and hepatoblasts (HNF4A, AFP). Comparative analysis demonstrated a markedly enhanced hepatic gene expression of 3D organoids, as demonstrated by a 33-fold increase in HNF4A expression and elevated levels of mature hepatocyte markers, including ALB, SERPINA1, and UGT2B15. However, the 3D cultures retained fetal characteristics (290-fold higher AFP expression) and exhibited significantly impaired metabolic function, with CYP3A4 expression levels reduced by 2000-fold compared to the adult human liver. This partial maturation was further supported by a moderate correlation with adult liver tissue (ρ = 0.57). We demonstrated high reproducibility across five biologically distinct iPSCs lines, including those derived from patients with rare monogenic disorders. The establishment of quantitative benchmarks provides a crucial tool for standardizing in vitro liver models. Furthermore, we delineate the specific limitations of the current model, highlighting the need for further protocol optimization to enhance metabolic maturation and P450 enzyme activity. Functional validation of metabolic activity (CYP enzyme assays, albumin secretion) was not performed; therefore, conclusions regarding hepatocyte functionality are based on transcriptomic evidence.

Microsatellite instability (MSI) is one of the most important molecular characteristics of a tumor, which occurs among various tumor types. In this review article, we examine the molecular characteristics of MSI tumors, both sporadic and Lynch-associated. We also overview the risks of developing hereditary forms of cancer and potential mechanisms of tumor development in patients with Lynch syndrome. Additionally, we summarize the results of major clinical studies on the efficacy of immune checkpoint inhibitors for MSI tumors and discuss the predictive role of MSI in the context of chemotherapy and checkpoint inhibitors. Finally, we briefly discuss some of the underlying mechanisms causing therapy resistance in patients treated with immune checkpoint inhibitors.

The main types of thyroid neoplasms, follicular adenoma (FA), follicular thyroid carcinoma (FTC), classical and follicular variants of papillary carcinoma (clPTC and fvPTC), and anaplastic thyroid carcinoma (ATC), differ in prognosis, progression rate and metastatic behaviour. Specific patterns of lncRNAs involved in the development of clinical and morphological features can be presumed. LncRNA landscapes within distinct benign and malignant histological variants of thyroid neoplasms were not investigated. The aim of the study was to discover long noncoding RNA landscapes common and specific to major benign and malignant histological subtypes of thyroid neoplasms. LncRNA expression in FA, FTC, fvPTC, clPTC and ATC was analysed with comprehensive microarray and RNA-Seq datasets. Putative biological functions were evaluated via enrichment analysis of coexpressed coding genes. In the results, lncRNAs common and specific to FTC, clPTC, fvPTC, and ATC were identified. The discovered lncRNAs are putatively involved in L1CAM interactions, namely, pre-mRNA processing (lncRNAs specific to FTC); PCP/CE and WNT pathways (lncRNAs specific to fvPTC); extracellular matrix organization (lncRNAs specific to clPTC); and the cell cycle (lncRNAs specific to ATC). Known oncogenic and suppressor lncRNAs (RMST, CRNDE, SLC26A4-AS1, NR2F1-AS1, and LINC00511) were aberrantly expressed in thyroid carcinomas. These findings enhance the understanding of lncRNAs in the development of subtype-specific features in thyroid cancer.

Background: The main types of thyroid neoplasms, follicular adenoma (FA), follicular thyroid carcinoma (FTC), classical and follicular variants of papillary carcinoma (clPTC and fvPTC), anaplastic thyroid carcinoma (ATC), are differ in the prognosis, rate of progression and metastatic behavior. It can be supposed that there are specific patterns of lncRNAs involved in the development of clinical and morphological features. The lncRNA landscapes within distinct benign and malignant histological variants of thyroid neoplasm are unknown. Methods: Comprehensive set of Microarray and RNA-Seq datasets was analyzed for the expression of lncRNAs in FA, FTC, fvPTC, clPTC and ATC. The potential biological functions were evaluated via coexpression and enrichment analysis. Results and conclusion: Abberant expression of lncRNA in FA, FTC, fvPTC, clPTC and ATC was established. The lncRNAs common for benign and malignant neoplasms, specific for papillary carcinomas, specific for clPTC, fvPTC and ATC are determined. The determined common and specific lncRNAs are found to be putatively involved into L1CAM interactions; processing of capped intron-containing pre-mRNA; Tryptophan metabolism; PCP/CE pathway and Beta-catenin independent WNT signaling; extracellular matrix organization and cell cycle and mitotic. The patterns of lncRNA expression in FA and FTC are appeared to be similar with no genes significantly differentially expressed within these subtypes. Previously known oncogenic and supressor lncRNAs (NR2F1-AS1, LINC00511, SLC26A4-AS1, CRNDE, LINC01116, RMST) are found aberrantly expressed in thyroid carcinomas. The findings enhance the understanding of lncRNA landscape in thyroid neoplasms and its role in thyroid cancer progression.

Approximately 5–20% of chronic myeloid leukemia (CML) patients demonstrate primary resistance or intolerance to imatinib. None of the existing predictive scores gives a good prognosis of TKI efficacy. Gene polymorphisms, expression and microRNAs are known to be involved in the pathogenesis of TKI resistance in CML. The aim of our study is to find new molecular markers of TKI therapy efficacy in CML patients. Newly diagnosed patients with Ph+ CML in chronic phase were included in this study. Optimal and non-optimal responses to TKI were estimated according to ELN 2013 recommendation. We performed genotyping of selected polymorphisms in 62 blood samples of CML patients, expression profiling of 33 RNA samples extracted from blood and miRNA profiling of 800 miRNA in 12 blood samples of CML patients. The frequencies of genotypes at the studied loci did not differ between groups of patients with an optimal and non-optimal response to TKI therapy. Analysis of the expression of 34,681 genes revealed 26 differently expressed genes (p < 0.05) in groups of patients with different TKI responses, but differences were very small and were not confirmed by qPCR. Finally, we did not find difference in miRNA expression between the groups. Using modern high-throughput methods such as whole-exome sequencing, transcriptome and miRNA analysis, we could not find reliable molecular markers for early prediction of TKI efficiency in Ph+ CML patients.

Gene fusions are known in many cancers as driver or passenger mutations. They play an important role in both etiology and pathogenesis of cancer and are considered as potential diagnostic and prognostic markers and possible therapeutic targets. Spectrum and prevalence of gene fusions in thyroid cancer ranges from single cases up to 80% depending on specific type of cancer. During last three years massive parallel sequencing technologies revealed new fusions and allowed detailed characteristics of fusions in different types of thyroid cancer. This article reviews all known fusions and their prevalence in papillary, poorly differentiated and anaplastic carcinomas, follicular and medullary carcinomas. We describe the mechanisms of fusion formation. Besides, the mechanisms of oncogenic transformation, such as altered gene expression, forced oligomerization and subcellular localization are given. Prognostic value and perspectives of utilization gene fusions as therapeutic targets are discussed.