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Hematogenous metastasis limits the survival of colorectal cancer (CRC) patients. Here, we illuminated the roles of CD44 isoforms in this process. Isoforms 3 and 4 were predominantly expressed in CRC patients. CD44 isoform 4 indicated poor outcome and correlated with epithelial–mesenchymal transition (EMT) and decreased oxidative phosphorylation (OxPhos) in patients; opposite associations were found for isoform 3. Pan‐CD44 knockdown (kd) independently impaired primary tumor formation and abrogated distant metastasis in CRC xenografts. The xenograft tumors mainly expressed the clinically relevant CD44 isoforms 3 and 4. Both isoforms were enhanced in the paranecrotic, hypoxic tumor regions but were generally absent in lung metastases. Upon CD44 kd, tumor angiogenesis was increased in the paranecrotic areas, accompanied by reduced hypoxia‐inducible factor‐1α and CEACAM5 but increased E‐cadherin expression. Mitochondrial genes and proteins were induced upon pan‐CD44 kd, as were OxPhos genes. Hypoxia increased VEGF release from tumor spheres, particularly upon CD44 kd. Genes affected upon CD44 kd in xenografts specifically overlapped concordantly with genes correlating with CD44 isoform 4 (but not isoform 3) in patients, validating the clinical relevance of the used model and highlighting the metastasis‐promoting role of CD44 isoform 4.

Within-host infection dynamics of Omicron dramatically differs from previous variants of SARS-CoV-2. However, little is still known about which parameters of virus-cell interplay contribute to the observed attenuated replication and pathogenicity of Omicron. Mathematical models, often expressed as systems of differential equations, are frequently employed to study the infection dynamics of various viruses. Adopting such models for results of in vitro experiments can be beneficial in a number of aspects, such as model simplification (e.g., the absence of adaptive immune response and innate immunity cells), better measurement accuracy, and the possibility to measure additional data types in comparison with in vivo case. In this study, we consider a refinement of our previously developed and validated model based on a system of integro-differential equations. We fit the model to the experimental data of Omicron and Delta infections in Caco-2 (human intestinal epithelium model) and Calu-3 (lung epithelium model) cell lines. The data include known information on initial conditions, infectious virus titers, and intracellular viral RNA measurements at several time points post-infection. The model accurately explains the experimental data for both variants in both cell lines using only three variant- and cell-line-specific parameters. Namely, the cell entry rate is significantly lower for Omicron, and Omicron triggers a stronger cytokine production rate (i.e., innate immune response) in infected cells, ultimately making uninfected cells resistant to the virus. Notably, differences in only a single parameter (e.g., cell entry rate) are insufficient to obtain a reliable model fit for the experimental data.

RNA viruses have been shown to express various short RNAs, some of which have regulatory roles during replication, transcription, and translation of viral genomes. However, short viral RNAs generated from SARS-CoV-1 and SARS-CoV-2 genomic RNAs remained largely unexplored, possibly due limitations of the widely used library preparation methods for small RNA deep sequencing and corresponding data processing. By analyzing publicly available small RNA sequencing datasets, we observed that human Calu-3 cells infected by SARS-CoV-1 or SARS-CoV-2 accumulate multiple previously unreported short viral RNAs. In addition, we verified the presence of the five most abundant SARS-CoV-2 short viral RNAs in SARS-CoV-2-infected human lung adenocarcinoma cells by quantitative PCR. Interestingly, the copy number of the observed SARS-CoV-2 short viral RNAs dramatically exceeded the expression of previously reported viral microRNAs in the same cells. We hypothesize that the reported SARS-CoV-2 short viral RNAs could serve as biomarkers for early infection stages due to their high abundance. Furthermore, unlike SARS-CoV-1, the SARS-CoV-2 infection induced significant (Benjamini-Hochberg-corrected p-value

Alternative splicing is often deregulated in cancer, and cancer-specific isoform switches are part of the oncogenic transformation of cells. Accumulating evidence indicates that isoforms of the multifunctional cell-surface glycoprotein CD44 play different roles in cancer cells as compared to normal cells. In particular, the shift of CD44 isoforms is required for epithelial to mesenchymal transition (EMT) and is crucial for the maintenance of pluripotency in normal human cells and the acquisition of cancer stem cells phenotype for malignant cells. The growing and seemingly promising use of splicing inhibitors for treating cancer and other pathologies gives hope for the prospect of using such an approach to regulate CD44 alternative splicing. This review integrates current knowledge about regulating CD44 alternative splicing by RNA-binding proteins.

Since its original discovery over a decade ago, extracellular RNA (exRNA) has been found in all biological fluids. Furthermore, extracellular microRNA has been shown to be involved in communication between various cell types. Importantly, the exRNA is protected from RNases degradation by certain carriers including membrane vesicles and non-vesicular protein nanoparticles. Each type of carrier has its unique exRNA profile, which may vary depending on cell type and physiological conditions. To clarify putative mechanisms of intercellular communication mediated by exRNA, the RNA profile of each carrier has to be characterized. While current methods of biofluids fractionation are continuously improving, they fail to completely separate exRNA carriers. Likewise, most popular library preparation approaches for RNA sequencing do not allow obtaining exhaustive and unbiased data on exRNA transcriptome. In this mini review we discuss ongoing progress in the field of exRNA, with the focus on exRNA carriers, analyze the key methodological challenges and provide recommendations on how the latter could be overcome.

The diabetic kidney disease (DKD) is the major cause of the chronic kidney disease (CKD). Enhanced plasma vasopressin (VP) levels have been associated with the pathophysiology of DKD and CKD. Stimulation of VP release in DKD is caused by glucose-dependent reset of the osmostat leading to secondary pathophysiologic effects mediated by distinct VP receptor types. VP is a stress hormone exhibiting the antidiuretic action in the kidney along with broad adaptive effects in other organs. Excessive activation of the vasopressin type 2 (V2) receptor in the kidney leads to glomerular hyperfiltration and nephron loss, whereas stimulation of vasopressin V1a or V1b receptors in the liver, pancreas, and adrenal glands promotes catabolic metabolism for energy mobilization, enhancing glucose production and aggravating DKD. Increasing availability of selective VP receptor antagonists opens new therapeutic windows separating the renal and extra-renal VP effects for the concrete applications. Improved understanding of these paradigms is mandatory for further drug design and translational implementation. The present concise review focuses on metabolic effects of VP affecting DKD pathophysiology.

Mathematical modeling is widely used to study within-host viral dynamics. However, to the best of our knowledge, for the case of SARS-CoV-2 such analyses were mainly conducted with the use of viral load data and for the wild type (WT) variant of the virus. In addition, only few studies analyzed models for in vitro data, which are less noisy and more reproducible. In this work we collected multiple data types for SARS-CoV-2-infected Caco-2 cell lines, including infectious virus titers, measurements of intracellular viral RNA, cell viability data and percentage of infected cells for the WT and Delta variants. We showed that standard models cannot explain some key observations given the absence of cytopathic effect in human cell lines. We propose a novel mathematical model for in vitro SARS-CoV-2 dynamics, which included explicit modeling of intracellular events such as exhaustion of cellular resources required for virus production. The model also explicitly considers innate immune response. The proposed model accurately explained experimental data. Attenuated replication of the Delta variant in Caco-2 cells could be explained by our model on the basis of just two parameters: decreased cell entry rate and increased cytokine production rate.

In mid-2021, the SARS-CoV-2 Delta variant caused the third wave of the COVID-19 pandemic in several countries worldwide. The pivotal studies were aimed at studying changes in the efficiency of neutralizing antibodies to the spike protein. However, much less attention was paid to the T-cell response and the presentation of virus peptides by MHC-I molecules. In this study, we compared the features of the HLA-I genotype in symptomatic patients with COVID-19 in the first and third waves of the pandemic. As a result, we could identify the diminishing of carriers of the HLA-A*01:01 allele in the third wave and demonstrate the unique properties of this allele. Thus, HLA-A*01:01-binding immunoprevalent epitopes are mostly derived from ORF1ab. A set of epitopes from ORF1ab was tested, and their high immunogenicity was confirmed. Moreover, analysis of the results of single-cell phenotyping of T-cells in recovered patients showed that the predominant phenotype in HLA-A*01:01 carriers is central memory T-cells. The predominance of T-lymphocytes of this phenotype may contribute to forming long-term T-cell immunity in carriers of this allele. Our results can be the basis for highly effective vaccines based on ORF1ab peptides.

Introduction: Relapse of breast cancer is one of the key obstacles to successful treatment. Previously we have shown that low expression of ELOVL5 and IGFBP6 genes in breast cancer tissue corresponded to poor prognosis. ELOVL5 participates directly in the elongation of polyunsaturated fatty acids (PUFAs) that are considered to play an important role in cancer cell metabolism. Thus, in this work we studied the changes in lipid metabolism in breast cancer cells with reduced expression of either ELOVL5 or IGFBP6 gene.Methods: MDA-MB-231 cells with a stable knockdown of either ELOVL5 or IGFBP6 gene were used in this study. Transcriptomic and proteomic analysis as well as RT-PCR were utilized to assess gene expression. Content of individual fatty acids in the cells was measured with HPLC-MS. HPLC was used for analysis of the kinetics of PUFAs uptake. Cell viability was measured with MTS assay. Flow cytometry was used to measure activation of apoptosis. Fluorescent microscopy was utilized to assess accumulation of ROS and formation of lipid droplets. Glutathione peroxidase activity was measured with a colorimetric assay.Results: We found that the knockdown of IGFBP6 gene led to significant changes in the profile of fatty acids in the cells and in the expression of many genes associated with lipid metabolism. As some PUFAs are known to inhibit proliferation and cause death of cancer cells, we also tested the response of the cells to single PUFAs and to combinations of docosahexaenoic acid (DHA, a n-3 PUFA) with standard chemotherapeutic drugs. Our data suggest that external PUFAs cause cell death by activation of ferroptosis, an iron-dependent mechanism of cell death with excessive lipid peroxidation. Moreover, both knockdowns increased cells’ sensitivity to ferroptosis, probably due to a significant decrease in the activity of the antioxidant enzyme GPX4. Addition of DHA to commonly used chemotherapeutic drugs enhanced their effect significantly, especially for the cells with low expression of IGFBP6 gene.Discussion: The results of this study suggest that addition of PUFAs to the treatment regimen for the patients with low expression of IGFBP6 and ELOVL5 genes can be potentially beneficial and is worth testing in a clinically relevant setting.

A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman’s correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)—the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3′-UTRs and coding mRNA sequences, while 5′-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples.

Inaccurate cleavage of pri- and pre-miRNA hairpins by Drosha and Dicer results in the generation of miRNA isoforms known as isomiRs. isomiRs with 5′-end variations (5′-isomiRs) create a new dimension in miRNA research since they have different seed regions and distinct targetomes. We developed isomiRTar (https://isomirtar.hse.ru)—a comprehensive portal that allows one to analyze expression profiles and targeting activity of 5′-isomiRs in cancer. Using the Cancer Genome Atlas sequencing data, we compiled the list of 1022 5′-isomiRs expressed in 9282 tumor samples across 31 cancer types. Sequences of these isomiRs were used to predict target genes with miRDB and TargetScan. The putative interactions were then subjected to the co-expression analysis in each cancer type to identify isomiR-target pairs supported by significant negative correlations. Downstream analysis of the data deposited in isomiRTar revealed both cancer-specific and cancer-conserved 5′-isomiR expression landscapes. Pairs of isomiRs differing in one nucleotide shift from 5′-end had poorly overlapping targetomes with the median Jaccard index of 0.06. The analysis of colorectal cancer 5′-isomiR-mediated regulatory networks revealed promising candidate tumor suppressor isomiRs: hsa-miR-203a-3p—+1, hsa-miR-192-5p—+1 and hsa-miR-148a-3p—0. In summary, we believe that isomiRTar will help researchers find novel mechanisms of isomiR-mediated gene silencing in different types of cancer.

Abstract Background Mesothelial E- and P-selectins substantially mediate the intraperitoneal spread of Pancreatic ductal adenocarcinoma (PDA) cells in xenograft models. In the absence of selectins in the host, the integrin subunit alpha-V (ITGAV, CD51) was upregulated in the remaining metastatic deposits. Here we present the first experimental study to investigate if ITGAV plays a functional role in PDA tumor growth and progression with a particular focus on intraperitoneal carcinomatosis. Methods Knockdown of ITGAV was generated using an RNA interference-mediated approach in two PDA cell lines. Tumor growth, intraperitoneal and distant metastasis were analyzed in a xenograft model. Cell lines were characterized in vitro. Gene expression of the xenograft tumors was analyzed. Patient samples were histologically classified and associations to survival were evaluated. Results The knockdown of ITGAV in PDA cells strongly reduces primary tumor growth, peritoneal carcinomatosis and spontaneous pulmonary metastasis. ITGAV activates latent TGF-β and thereby drives epithelial-mesenchymal transition. Combined depletion of ITGAV on the tumor cells and E- and P-selectins in the tumor-host synergistically almost abolishes intraperitoneal spread. Accordingly, high expression of ITGAV in PDA cells was associated with reduced survival in patients. Conclusion Combined depletion of ITGAV in PDA cells and E- and P-selectins in host mice massively suppresses intraperitoneal carcinomatosis of PDA cells xenografted into immunodeficient mice, confirming the hypothesis of a partly redundant adhesion cascade of metastasizing cancer cells. Our data strongly encourage developing novel therapeutic approaches for the combined targeting of E- and P-selectins and ITGAV in PDA.

The ongoing COVID-19 pandemic calls for more effective diagnostic tools. T cell response assessment serves as an independent indicator of prior COVID-19 exposure while also contributing to a more comprehensive characterization of SARS-CoV-2 immunity. In this study, we systematically assessed the immunogenicity of 118 epitopes with immune cells collected from multiple cohorts of vaccinated, convalescent, healthy unexposed, and SARS-CoV-2–exposed donors. We identified 75 immunogenic epitopes, 24 of which were immunodominant. We further confirmed HLA restriction for 49 epitopes and described association with more than 1 HLA allele for 14 of these. Exclusion of 2 cross-reactive epitopes that generated a response in prepandemic samples left us with a 73-epitope set that offered excellent diagnostic specificity without losing sensitivity compared with full-length antigens, and this evoked a robust cross-reactive response. We subsequently incorporated this set of epitopes into an in vitro diagnostic Corona-T-test, which achieved a diagnostic accuracy of 95% in a clinical trial. In a cohort of asymptomatic seronegative individuals with a history of prolonged SARS-CoV-2 exposure, we observed a complete absence of T cell response to our epitope panel. In combination with strong reactivity to full-length antigens, this suggests that a cross-reactive response might protect these individuals.

The T-cell immune response is a major determinant of effective SARS-CoV-2 clearance. Here, using the recently developed T-CoV bioinformatics pipeline (https://t-cov.hse.ru) we analyzed the peculiarities of the viral peptide presentation for the Omicron, Delta and Wuhan variants of SARS-CoV-2. First, we showed the absence of significant differences in the presentation of SARS-CoV-2-derived peptides by the most frequent HLA class I/II alleles and the corresponding HLA haplotypes. Then, the analysis was limited to the set of peptides originating from the Spike proteins of the considered SARS-CoV-2 variants. The major finding was the destructive effect of the Omicron mutations on PINLVRDLPQGFSAL peptide, which was the only tight binder from the Spike protein for HLA-DRB1*03:01 allele and some associated haplotypes. Specifically, we predicted a dramatical decline in binding affinity of HLA-DRB1*03:01 and this peptide both because of the Omicron BA.1 mutations (N211 deletion, L212I substitution and EPE 212-214 insertion) and the Omicron BA.2 mutations (V213G substitution). The computational prediction was experimentally validated by ELISA with the use of corresponding thioredoxin-fused peptides and recombinant HLA-DR molecules. Another finding was the significant reduction in the number of tightly binding Spike peptides for HLA-B*07:02 HLA class I allele (both for Omicron and Delta variants). Overall, the majority of HLA alleles and haplotypes was not significantly affected by the mutations, suggesting the maintenance of effective T-cell immunity against the Omicron and Delta variants. Finally, we introduced the Omicron variant to T-CoV portal and added the functionality of haplotype-level analysis to it.

Feature selection is one of the main techniques used to prevent overfitting in machine learning applications. The most straightforward approach for feature selection is an exhaustive search: one can go over all possible feature combinations and pick up the model with the highest accuracy. This method together with its optimizations were actively used in biomedical research, however, publicly available implementation is missing. We present ExhauFS—the user-friendly command-line implementation of the exhaustive search approach for classification and survival regression. Aside from tool description, we included three application examples in the manuscript to comprehensively review the implemented functionality. First, we executed ExhauFS on a toy cervical cancer dataset to illustrate basic concepts. Then, multi-cohort microarray breast cancer datasets were used to construct gene signatures for 5-year recurrence classification. The vast majority of signatures constructed by ExhauFS passed 0.65 threshold of sensitivity and specificity on all datasets, including the validation one. Moreover, a number of gene signatures demonstrated reliable performance on independent RNA-seq dataset without any coefficient re-tuning, i.e., turned out to be cross-platform. Finally, Cox survival regression models were used to fit isomiR signatures for overall survival prediction for patients with colorectal cancer. Similarly to the previous example, the major part of models passed the pre-defined concordance index threshold 0.65 on all datasets. In both real-world scenarios (breast and colorectal cancer datasets), ExhauFS was benchmarked against state-of-the-art feature selection models, including L1-regularized sparse models. In case of breast cancer, we were unable to construct reliable cross-platform classifiers using alternative feature selection approaches. In case of colorectal cancer not a single model passed the same 0.65 threshold. Source codes and documentation of ExhauFS are available on GitHub: https://github.com/s-a-nersisyan/ExhauFS.

Interactions of the extracellular matrix (ECM) and cellular receptors constitute one of the crucial pathways involved in colorectal cancer progression and metastasis. With the use of bioinformatics analysis, we comprehensively evaluated the prognostic information concentrated in the genes from this pathway. First, we constructed a ECM–receptor regulatory network by integrating the transcription factor (TF) and 5’-isomiR interaction databases with mRNA/miRNA-seq data from The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD). Notably, one-third of interactions mediated by 5’-isomiRs was represented by noncanonical isomiRs (isomiRs, whose 5’-end sequence did not match with the canonical miRBase version). Then, exhaustive search-based feature selection was used to fit prognostic signatures composed of nodes from the network for overall survival prediction. Two reliable prognostic signatures were identified and validated on the independent The Cancer Genome Atlas Rectum Adenocarcinoma (TCGA-READ) cohort. The first signature was made up by six genes, directly involved in ECM–receptor interaction: AGRN, DAG1, FN1, ITGA5, THBS3, and TNC (concordance index 0.61, logrank test p = 0.0164, 3-years ROC AUC = 0.68). The second hybrid signature was composed of three regulators: hsa-miR-32-5p, NR1H2, and SNAI1 (concordance index 0.64, logrank test p = 0.0229, 3-years ROC AUC = 0.71). While hsa-miR-32-5p exclusively regulated ECM-related genes (COL1A2 and ITGA5), NR1H2 and SNAI1 also targeted other pathways (adhesion, cell cycle, and cell division). Concordant distributions of the respective risk scores across four stages of colorectal cancer and adjacent normal mucosa additionally confirmed reliability of the models.

Colorectal cancer (CRC) is one of the most common and lethal types of cancer. Although researchers have made significant efforts to study the mechanisms underlying CRC drug resistance, our knowledge of this disease is still limited, and novel therapies are in high demand. It is urgent to find new targeted therapy considering limited chemotherapy options. KRAS mutations are the most frequent molecular alterations in CRC. However, there are no approved K-Ras targeted therapies for these tumors yet. GSK-3β is demonstrated to be a critically important kinase for the survival and proliferation of K-Ras–dependent pancreatic cancer cells. In this study, we tested combinations of standard-of-care therapy and 9-ING-41, a small molecule inhibitor of GSK-3β, in CRC cell lines and patient-derived tumor organoid models of CRC. We demonstrate that 9-ING-41 inhibits the growth of CRC cells via a distinct from chemotherapy mechanism of action. Although molecular biomarkers of 9-ING-41 efficacy are yet to be identified, the addition of 9-ING-41 to the standard-of-care drugs 5-FU and oxaliplatin could significantly enhance growth inhibition in certain CRC cells. The results of the transcriptomic analysis support our findings of cell cycle arrest and DNA repair deficiency in 9-ING-41–treated CRC cells. Notably, we find substantial similarity in the changes of the transcriptomic profile after inhibition of GSK-3β and suppression of STK33, another critically important kinase for K-Ras–dependent cells, which could be an interesting point for future research. Overall, the results of this study provide a rationale for the further investigation of GSK-3 inhibitors in combination with standard-of-care treatment of CRC.

Since 2003, the world has been confronted with three new betacoronaviruses that cause human respiratory infections: SARS-CoV, which causes severe acute respiratory syndrome (SARS), MERS-CoV, which causes Middle East respiratory syndrome (MERS), and SARS-CoV-2, which causes Coronavirus Disease 2019 (COVID-19). The mechanisms of coronavirus transmission and dissemination in the human body determine the diagnostic and therapeutic strategies. An important problem is the possibility that viral particles overcome tissue barriers such as the intestine, respiratory tract, blood-brain barrier, and placenta. In this work, we will 1) consider the issue of endocytosis and the possibility of transcytosis and paracellular trafficking of coronaviruses across tissue barriers with an emphasis on the intestinal epithelium; 2) discuss the possibility of antibody-mediated transcytosis of opsonized viruses due to complexes of immunoglobulins with their receptors; 3) assess the possibility of the virus transfer into extracellular vesicles during intracellular transport; and 4) describe the clinical significance of these processes. Models of the intestinal epithelium and other barrier tissues for in vitro transcytosis studies will also be briefly characterized.

Breast cancer (BC) is the leading cause of death from malignant neoplasms among women worldwide, and metastatic BC presents the biggest problems for treatment. Previously, it was shown that lower expression of ELOVL5 and IGFBP6 genes is associated with a higher risk of the formation of distant metastases in BC. In this work, we studied the change in phenotypical traits, as well as in the transcriptomic and proteomic profiles of BC cells as a result of the stable knockdown of ELOVL5 and IGFBP6 genes. The knockdown of ELOVL5 and IGFBP6 genes was found to lead to a strong increase in the expression of the matrix metalloproteinase (MMP) MMP1. These results were in good agreement with the correlation analysis of gene expression in tumor samples from patients and were additionally confirmed by zymography. The knockdown of ELOVL5 and IGFBP6 genes was also discovered to change the expression of a group of genes involved in the formation of intercellular contacts. In particular, the expression of the CDH11 gene was markedly reduced, which also complies with the correlation analysis. The spheroid formation assay showed that intercellular adhesion decreased as a result of the knockdown of the ELOVL5 and IGFBP6 genes. Thus, the obtained data indicate that malignant breast tumors with reduced expression of the ELOVL5 and IGFBP6 genes can metastasize with a higher probability due to a more efficient invasion of tumor cells.

Hypoxia is an extensively investigated condition due to its contribution to various pathophysiological processes including cancer progression and metastasis formation. MicroRNAs (miRNAs) are well-known post-transcriptional gene expression regulators. However, their contribution to molecular response to hypoxia is highly dependent on cell/tissue types and causes of hypoxia. One of the most important examples is colorectal cancer, where no consensus on hypoxia-regulated miRNAs has been reached so far. In this work, we applied integrated mRNA and small RNA sequencing, followed by bioinformatics analysis, to study the landscape of hypoxia-induced miRNA and mRNA expression alterations in human colorectal cancer cell lines (HT-29 and Caco-2). A hypoxic microenvironment was chemically modeled using two different treatments: cobalt(II) chloride and oxyquinoline. Only one miRNA, hsa-miR-210-3p, was upregulated in all experimental conditions, while there were nine differentially expressed miRNAs under both treatments within the same cell line. Further bioinformatics analysis revealed a complex hypoxia-induced regulatory network: hypoxic downregulation of hsa-miR-148a-3p led to the upregulation of its two target genes, ITGA5 and PRNP, which was shown to be a factor contributing to tumor progression and poor survival in colorectal cancer patients.

Human leukocyte antigen (HLA) class I molecules play a crucial role in the development of a specific immune response to viral infections by presenting viral peptides at the cell surface where they will be further recognized by T cells. In the present manuscript, we explored whether HLA class I genotypes can be associated with the critical course of Coronavirus Disease-19 by searching possible connections between genotypes of deceased patients and their age at death. HLA-A, HLA-B, and HLA-C genotypes of n = 111 deceased patients with COVID-19 (Moscow, Russia) and n = 428 volunteers were identified with next-generation sequencing. Deceased patients were split into two groups according to age at the time of death: n = 26 adult patients aged below 60 and n = 85 elderly patients over 60. With the use of HLA class I genotypes, we developed a risk score (RS) which was associated with the ability to present severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) peptides by the HLA class I molecule set of an individual. The resulting RS was significantly higher in the group of deceased adults compared to elderly adults [p = 0.00348, area under the receiver operating characteristic curve (AUC ROC = 0.68)]. In particular, presence of HLA-A*01:01 allele was associated with high risk, while HLA-A*02:01 and HLA-A*03:01 mainly contributed to low risk. The analysis of patients with homozygosity strongly highlighted these results: homozygosity by HLA-A*01:01 accompanied early deaths, while only one HLA-A*02:01 homozygote died before 60 years of age. Application of the constructed RS model to an independent Spanish patients cohort (n = 45) revealed that the score was also associated with the severity of the disease. The obtained results suggest the important role of HLA class I peptide presentation in the development of a specific immune response to COVID-19.

Analysis of regulatory networks is a powerful framework for identification and quantification of intracellular interactions. We introduce miRGTF-net, a novel tool for construction of miRNA-gene-TF networks. We consider multiple transcriptional and post-transcriptional interaction types, including regulation of gene and miRNA expression by transcription factors, gene silencing by miRNAs, and co-expression of host genes with their intronic miRNAs. The underlying algorithm uses information on experimentally validated interactions as well as integrative miRNA/mRNA expression profiles in a given set of samples. The latter ensures simultaneous tissue-specificity and biological validity of interactions. We applied miRGTF-net to paired miRNA/mRNA-sequencing data of breast cancer samples from The Cancer Genome Atlas (TCGA). Together with topological analysis of the constructed network we showed that considered players can form reliable prognostic gene signatures for ER-positive breast cancer. A number of signatures demonstrated remarkably high accuracy on transcriptomic data obtained by both microarrays and RNA sequencing from several independent patient cohorts. Furthermore, an essential part of prognostic genes were identified as direct targets of transcription factor E2F1. The putative interplay between estrogen receptor alpha and E2F1 was suggested as a potential recurrence factor in patients treated with tamoxifen. Source codes of miRGTF-net are available at GitHub (https://github.com/s-a-nersisyan/miRGTF-net).

Structurally similar catalytic subunits A of ricin (RTA) and viscumin (MLA) exhibit cytotoxic activity through ribosome inactivation. Ricin is more cytotoxic than viscumin, although the molecular mechanisms behind this difference are still poorly understood. To shed more light on this problem, we used a combined biochemical/molecular modeling approach to assess possible relationships between the activity of toxins and their structural/dynamic properties. Based on bioassay measurements, it was suggested that the differences in activity are associated with the ability of RTA and MLA to undergo structural/hydrophobic rearrangements during trafficking through the endoplasmic reticulum (ER) membrane. Molecular dynamics simulations and surface hydrophobicity mapping of both proteins in different media showed that RTA rearranges its structure in a membrane-like environment much more efficiently than MLA. Their refolded states also drastically differ in terms of hydrophobic organization. We assume that the higher conformational plasticity of RTA is favorable for the ER-mediated translocation pathway, which leads to a higher rate of toxin penetration into the cytoplasm.

Host miRNAs are known as important regulators of virus replication and pathogenesis. They can interact with various viruses through several possible mechanisms including direct binding of viral RNA. Identification of human miRNAs involved in coronavirus-host interplay becomes important due to the ongoing COVID-19 pandemic. In this article we performed computational prediction of high-confidence direct interactions between miRNAs and seven human coronavirus RNAs. As a result, we identified six miRNAs (miR-21-3p, miR-195-5p, miR-16-5p, miR-3065-5p, miR-424-5p and miR-421) with high binding probability across all analyzed viruses. Further bioinformatic analysis of binding sites revealed high conservativity of miRNA binding regions within RNAs of human coronaviruses and their strains. In order to discover the entire miRNA-virus interplay we further analyzed lungs miRNome of SARS-CoV infected mice using publicly available miRNA sequencing data. We found that miRNA miR-21-3p has the largest probability of binding the human coronavirus RNAs and being dramatically up-regulated in mouse lungs during infection induced by SARS-CoV.

Development of novel approaches for regulating the expression of angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) is becoming increasingly important within the context of the ongoing COVID-19 pandemic since these enzymes play a crucial role in cell infection. In this work we searched for putative ACE2 and TMPRSS2 expression regulation networks mediated by various miRNA isoforms (isomiR) across different human organs using publicly available paired miRNA/mRNA-sequencing data from The Cancer Genome Atlas (TCGA) project. As a result, we identified several miRNA families targeting ACE2 and TMPRSS2 genes in multiple tissues. In particular, we found that lysine-specific demethylase 5B (JARID1B), encoded by the KDM5B gene, can indirectly affect ACE2 / TMPRSS2 expression by repressing transcription of hsa-let-7e / hsa-mir-125a and hsa-mir-141 / hsa-miR-200 miRNA families which are targeting these genes.

In contrast to traditional 2D cell cultures, both 3D models and organ-on-a-chip devices allow the study of the physiological responses of human cells. These models reconstruct human tissues in conditions closely resembling the body. Translation of these techniques into practice is hindered by associated labor costs, a need which may be remedied by automation. Impedance spectroscopy (IS) is a promising, automation-compatible label-free technology allowing to carry out a wide range of measurements both in real-time and as endpoints. IS has been applied to both the barrier cultures and the 3D constructs. Here we provide an overview of the impedance-based analysis in different setups and discuss its utility for organ-on-a-chip devices. Most attractive features of impedance-based assays are their compatibility with high-throughput format and supports for the measurements in real time with high temporal resolution, which allow tracing of the kinetics. As of now, IS-based techniques are not free of limitations, including imperfect understanding of the parameters that have their effects on the impedance, especially in 3D cell models, and relatively high cost of the consumables. Moreover, as the theory of IS stems from electromagnetic theory and is quite complex, work on popularization and explanation of the method for experimental biologists is required. It is expected that overcoming these limitations will lead to eventual establishing IS based systems as a standard for automated management of cell-based experiments in both academic and industry environments.

Specificity of RNAi to selected target is challenged by off-target effects, both canonical and non-canonical. Notably, more than half of all human microRNAs are co-expressed with hosting them proteincoding genes. Here we dissect regulatory subnetwork centered on IGFBP6 gene, which is associated with low proliferative state and high migratory activity of basal-like breast cancer. We inhibited expression of IGFBP6 gene in a model cell line for basal-like breast carcinoma MDA-MB-231, then traced secondary and tertiary effects of this knockdown to LAMA4, a laminin encoding gene that contributes to the phenotype of triple-negative breast cancer. LAMA4-regulating miRNA miR-4274 and its host gene SORCS2 were highlighted as intermediate regulators of the expression levels of LAMA4, which correlated in a basal-like breast carcinoma sample subset of TCGA to the levels of SORCS2 negatively. Overall, our study points that the secondary and tertiary layers of regulatory interactions are certainly underappreciated. As these types of molecular event may significantly contribute to the formation of the cell phenotypes after RNA interference based knockdowns, further studies of multilayered molecular networks affected by RNAi are warranted.

Exosomes and microvesicles are two major categories of extracellular vesicles (EVs) released by almost all cell types and are highly abundant in biological fluids. Both the molecular composition of EVs and their release are thought to be strictly regulated by external stimuli. Multiple studies have consistently demonstrated that EVs transfer proteins, lipids and RNA between various cell types, thus mediating intercellular communication, and signaling. Importantly, small non-coding RNAs within EVs are thought to be major contributors to the molecular events occurring in the recipient cell. Furthermore, RNA cargo in exosomes and microvesicles could hold tremendous potential as non-invasive biomarkers for multiple disorders, including pathologies of the immune system. This mini-review is aimed to provide the state-of-the-art in the EVs-associated RNA transcriptome field, as well as the comprehensive analysis of previous studies characterizing RNA content within EVs released by various cells using next-generation sequencing. Finally, we highlight the technical challenges associated with obtaining pure EVs and deep sequencing of the EV-associated RNAs.

One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined samples, i.e., false positives. We propose a post-processing algorithm which performs scoring of miRNAs in the results of microarray analysis based on expression values, time of discovery of miRNA, and correlation level between the expressions of miRNA and corresponding pre-miRNA in considered samples. The algorithm was successfully validated by the comparison of the results of its application to miRNA microarray breast tumor samples with publicly available miRNA-seq breast tumor data. Additionally, we obtained possible reasons why miRNA can appear as a false positive in microarray study using paired miRNA sequencing and array data. The use of DNA microarrays for estimating miRNA expression profile is limited by several factors. One of them consists of problems with comparing expression values of different miRNAs. In this work, we show that situation can be significantly improved if some additional information is taken into consideration in a comparison.

Non-alcoholic fatty liver disease (NAFLD) is the worldwide most common cause of chronic liver pathology, which prevalence strongly correlates with the increasing incidence of diabetes, obesity and metabolic syndrome in the general population. Simple steatosis, the earliest NAFLD stage, usually remains asymptomatic, and appropriate changes in the lifestyle, as well as the diet, can reverse the affected liver into the healthy state. The potential of simple steatosis to progress into severe fibrotic stages and to facilitate carcinogenesis necessitates timely NAFLD detection and risk stratification in community-based healthcare settings. Since their initial discovery a decade ago, extracellular circulating miRNAs have been found in all human biological fluids including blood and shown to hold great promises as non-invasive biomarkers. Normally, intracellular miRNAs participate in the regulation of gene expression, but once released by dying/dead cells they remain highly stable in the extracellular environment for prolonged periods. Therefore, circulating miRNA profiles can reflect the ongoing pathogenic processes in body’s tissues and organs, and enable highly sensitive non-invasive diagnosis of multiple disorders. A non-urgent character of the NAFLD-related decision-making justifies the use of chronic liver diseases as an excellent test case for examining the practical utility of circulating miRNAs as biomarkers for longitudinal monitoring of human health. In this review, we summarize the state-of-the-art in the field of early diagnosis of NAFLD using circulating blood miRNAs, and stress the necessity of additional experimental validation of their diagnostic potential. We further emphasize on the potential diagnostics promises of other cell-free RNA species found in human biological fluids.

Physical stress affects the immune system, activates the sympathetic (SNS) and parasympathetic (PNS) subsytems of autonomic nervous system (ANS), and increases the activity of the hypothalamic-pituitary-adrenal axis (HPA). The specific response of the major regulatory systems depends on the human functional state. Saliva is a unique diagnostic fluid, the composition of which immediately reflects the SNS, PNS, HPA and immune system response to stress. A new method of saliva biomarker determination by Attenuated Total Reflection Fourier-Transform Infrared (ATR FTIR) spectroscopy has been developed to monitor the exercise induced metabolic changes in saliva from male endurance athletes. The method has been tested using a group of professional athletes by analysing saliva samples collected before and after the exercise, and the saliva composition monitoring by ATR FTIR spectroscopy was shown to be suitable for real-time checking of response to stress. [ABSTRACT FROM AUTHOR]