Myocardial dysfunction, characterized by impaired cardiac muscle function, arises from diverse etiologies, including coronary artery disease, myocardial infarction, cardiomyopathies, hypertension, and valvular heart disease. Recent advancements have highlighted the roles of exosomes and non-coding RNAs in the pathophysiology of myocardial dysfunction. Exosomes are small extracellular vesicles released by cardiac and other cells that facilitate intercellular communication through their molecular cargo, including ncRNAs. ncRNAs are known to play critical roles in gene regulation through diverse mechanisms, impacting oxidative stress, fibrosis, and other factors associated with myocardial dysfunction. Dysregulation of these molecules correlates with disease progression, presenting opportunities for therapeutic interventions. This review explores the mechanistic interplay between exosomes and ncRNAs, underscoring their potential as biomarkers and therapeutic agents in myocardial dysfunction. Emerging evidence supports the use of engineered exosomes and modified ncRNAs to enhance cardiac repair by targeting signaling pathways associated with fibrosis, apoptosis, and angiogenesis. Despite promising preclinical results, delivery, stability, and immunogenicity challenges remain. Further research is needed to optimize clinical translation. Understanding these intricate mechanisms may drive the development of innovative strategies for diagnosing and treating myocardial dysfunction, ultimately improving patient outcomes.

• Keywords
• Bioengineering, Cardiomyopathies, Exosomes, Myocardial dysfunction, Non-coding RNAs,
• MeSH
• Exosomes * metabolism   genetics   MeSH
• Fibrosis MeSH
• Cardiomyopathies * genetics   metabolism   physiopathology   therapy   MeSH
• Humans MeSH
• Myocardium * metabolism   pathology   MeSH
• RNA, Untranslated * metabolism   genetics   MeSH
• Signal Transduction MeSH
• Animals MeSH
• Check Tag
• Humans MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• RNA, Untranslated * MeSH

BACKGROUND: Long non-coding RNAs (lncRNAs) as an important fraction of human transcriptome have been shown to exert fundamental role in regulation of signaling pathways implicated in carcinogenesis. Among them is vitamin D receptor (VDR) signaling whose participation in various cancers including breast cancer (BC) is evident. In spite of the presence of several evidences for participation of lncRNAs as well as VDR signaling in BC pathogenesis, no comprehensive study has evaluated the link between lncRNA dysregulation and VDR signaling in BC. AIM: To introduce a bioinformatics approach for identification of lncRNAs that modulate VDR signaling in BC. This approach includes co-expression analysis, in silico identification of lncRNAs that target VDR and literature search. CONCLUSIONS: Tens of lncRNAs are predicted to affect VDR signaling. Among them are some lncRNAs such as MALAT1 which has prominent role in BC pathogenesis. Identification of the lncRNAs that influence VDR gene expression is possible through in silico analysis. Considering the prominent role of VDR in BC pathogenesis as well as availability of VDR modulating agents, evaluation of VDR signaling pathway and related networks are of practical significance and bioinformatics tools are expected to facilitate such action. Key words: vitamin D receptor - long non-coding RNAs - co-expression - bioinformatics - calcitriol receptor - computational biology.

• Keywords
• vitamin D receptor - long non-coding RNAs - co-expression - bioinformatics - calcitriol receptor - computational biology,
• MeSH
• Humans MeSH
• Breast Neoplasms genetics   metabolism   MeSH
• Receptors, Calcitriol metabolism   MeSH
• RNA, Long Noncoding metabolism   MeSH
• Signal Transduction MeSH
• Computational Biology MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Receptors, Calcitriol MeSH
• RNA, Long Noncoding MeSH
• VDR protein, human MeSH Browser

The circulating human transcriptome, which includes both coding and non-coding RNA (ncRNA) molecules, represents a rich source of potential biomarkers for colorectal cancer (CRC) that has only recently been explored. In particular, the release of RNA-containing extracellular vesicles (EVs), in a multitude of different in vitro cell systems and in a variety of body fluids, has attracted wide interest. The role of RNA species in EVs is still not fully understood, but their capacity to act as a form of distant communication between cells and their higher abundance in association with cancer demonstrated their relevance. In this review, we report the evidence from both in vitro and human studies on microRNAs (miRNAs) and other ncRNA profiles analysed in EVs in relation to CRC as diagnostic, prognostic and predictive markers. The studies so far highlighted that, in exosomes, the most studied category of EVs, several miRNAs are able to accurately discriminate CRC cases from controls as well as to describe the progression of the disease and its prognosis. Most of the time, the in vitro findings support the miRNA profiles detected in human exosomes. The expression profiles measured in exosomes and other EVs differ and, interestingly, there is a variability of expression also among different subsets of exosomes according to their proteic profile. On the other hand, evidence is still limited for what concerns exosome miRNAs as early diagnostic and predictive markers of treatment. Several other ncRNAs that are carried by exosomes, mostly long ncRNAs and circular RNAs, seem also to be dysregulated in CRC. Besides various technical challenges, such as the standardisation of EVs isolation methods and the optimisation of methodologies to characterise the whole spectrum of RNA molecules in exosomes, further studies are needed in order to elucidate their relevance as CRC markers.

• MeSH
• Exosomes genetics   metabolism   MeSH
• Extracellular Vesicles genetics   metabolism   MeSH
• Colorectal Neoplasms blood   diagnosis   genetics   metabolism   MeSH
• Humans MeSH
• MicroRNAs genetics   metabolism   MeSH
• Biomarkers, Tumor genetics   metabolism   MeSH
• RNA, Untranslated genetics   metabolism   MeSH
• Disease Progression MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• MicroRNAs MeSH
• Biomarkers, Tumor MeSH
• RNA, Untranslated MeSH

Juvenile myelomonocytic leukemia (JMML) treatment primarily relies on hematopoietic stem cell transplantation and results in long-term overall survival of 50-60%, demonstrating a need to develop novel treatments. Dysregulation of the non-coding RNA transcriptome has been demonstrated before in this rare and unique disorder of early childhood. In this study, we investigated the therapeutic potential of targeting overexpressed long non-coding RNAs (lncRNAs) in JMML. Total RNA sequencing of bone marrow and peripheral blood mononuclear cell preparations from 19 untreated JMML patients and three healthy children revealed 185 differentially expressed lncRNA genes (131 up- and 54 downregulated). LNA GapmeRs were designed for 10 overexpressed and validated lncRNAs. Molecular knockdown (≥ 70% compared to mock control) after 24 h of incubation was observed with two or more independent GapmeRs in 6 of them. For three lncRNAs (lnc-THADA-4, lnc-ACOT9-1 and NRIR) knockdown resulted in a significant decrease of cell viability after 72 h of incubation in primary cultures of JMML mononuclear cells, respectively. Importantly, the extent of cellular damage correlated with the expression level of the lncRNA of interest. In conclusion, we demonstrated in primary JMML cell cultures that knockdown of overexpressed lncRNAs such as lnc-THADA-4, lnc-ACOT9-1 and NRIR may be a feasible therapeutic strategy.

• MeSH
• Child MeSH
• Gene Knockdown Techniques MeSH
• Leukemia, Myelomonocytic, Juvenile blood   drug therapy   genetics   pathology   MeSH
• Infant MeSH
• Bone Marrow pathology   MeSH
• Leukocytes, Mononuclear MeSH
• Humans MeSH
• Adolescent MeSH
• Tumor Cells, Cultured MeSH
• Child, Preschool MeSH
• Primary Cell Culture MeSH
• Antineoplastic Agents pharmacology   therapeutic use   MeSH
• Gene Expression Regulation, Leukemic drug effects   MeSH
• RNA, Long Noncoding antagonists & inhibitors   genetics   metabolism   MeSH
• RNA-Seq MeSH
• Case-Control Studies MeSH
• Healthy Volunteers MeSH
• Check Tag
• Child MeSH
• Infant MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Child, Preschool MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Observational Study MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Antineoplastic Agents MeSH
• RNA, Long Noncoding MeSH

Long non-coding RNAs (lncRNAs) are DNA transcripts longer than 200 nucleotides without protein-coding potential. As they are key regulators of gene expression at chromatic, transcriptional and posttranscriptional level, they play important role in various biological and pathological processes. Dysregulation of lncRNAs has been observed in several diseases including cancer. Breast cancer is heterogeneous disease with many molecular subtypes specific in different prognosis and treatment responses. Hypoxia, a common micro-environmental feature of rapidly growing tumour is associated with metastases, recurrences and resistance to therapy. Aberrant expression of hypoxia related lncRNAs significantly correlates with poor outcomes in cancer patients, as the lncRNAs play an important regulatory role in the breast cancer-cell survival. Thus, a better understanding of lncRNAs role in the hypoxic conditions of breast cancer is crucial for precise understanding of the tumorigenesis, disease features and poor clinical outcome, especially in highly aggressive breast cancer subtypes (HER2-positive and triple-negative types). Moreover, lncRNAs may represent tumour marker predicting prognosis and therapeutic targets improving precise and personalized therapy for better patient´s survival. In this review, we summarize the recent information on lncRNAs in breast cancer with special focus on the hypoxia-responsive lncRNAs and their potential impact on the prognosis, therapy algorithms and individual outcomes. Presented data helps in better understanding of the specific mechanisms predicting new therapeutic agents and strategies for the pharmacological intervention.

• Keywords
• Breast cancer, Hypoxia-responsive lncRNA, Individual outcomes, Molecular signature, Prediction, Prognosis,
• MeSH
• Cell Hypoxia genetics   MeSH
• Clinical Trials as Topic MeSH
• Humans MeSH
• Breast Neoplasms genetics   pathology   therapy   MeSH
• RNA, Long Noncoding genetics   metabolism   MeSH
• Check Tag
• Humans MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• RNA, Long Noncoding MeSH

PURPOSE: Renal cell carcinoma belongs among the deadliest malignancies despite great progress in therapy and accessibility of primary care. One of the main unmet medical needs remains the possibility of early diagnosis before the tumor dissemination and prediction of early relapse and disease progression after a successful nephrectomy. In our study, we aimed to identify novel diagnostic and prognostic biomarkers using next-generation sequencing on a novel cohort of RCC patients. METHODS: Global expression profiles have been obtained using next-generation sequencing of paired tumor and non-tumor tissue of 48 RCC patients. Twenty candidate lncRNA have been selected for further validation on an independent cohort of paired tumor and non-tumor tissue of 198 RCC patients. RESULTS: Sequencing data analysis showed significant dysregulation of more than 2800 lncRNAs. Out of 20 candidate lncRNAs selected for validation, we confirmed that 14 of them are statistically significantly dysregulated. In order to yield better discriminatory results, we combined several best performing lncRNAs into diagnostic and prognostic models. A diagnostic model consisting of AZGP1P1, CDKN2B-AS1, COL18A1, and RMST achieved AUC 0.9808, sensitivity 95.96%, and specificity 90.4%. The model for prediction of early relapse after nephrectomy consists of COLCA1, RMST, SNHG3, and ZNF667-AS1 and achieved AUC 0.9241 with sensitivity 93.75% and specificity 71.07%. Notably, no combination has outperformed COLCA1 alone. Lastly, a model for stage consists of ZNF667-AS1, PVT1, RMST, LINC00955, and TCL6 and achieves AUC 0.812, sensitivity 85.71%, and specificity 69.41%. CONCLUSION: In our work, we identified several lncRNAs as potential biomarkers and developed models for diagnosis and prognostication in relation to stage and early relapse after nephrectomy.

• Keywords
• Biomarker, Diagnosis, Early relapse, Long non-coding RNA, Next-generation sequencing, Prognosis,
• MeSH
• Carcinoma, Renal Cell * diagnosis   genetics   surgery   MeSH
• Humans MeSH
• Neoplasm Recurrence, Local diagnosis   genetics   surgery   MeSH
• Biomarkers, Tumor genetics   MeSH
• Kidney Neoplasms * diagnosis   genetics   surgery   MeSH
• Nephrectomy MeSH
• Gene Expression Regulation, Neoplastic MeSH
• RNA, Long Noncoding * genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Biomarkers, Tumor MeSH
• RNA, Long Noncoding * MeSH

OBJECTIVES: Long non-coding RNAs (lncRNAs) are RNA transcripts longer than 200 nucleotides that are not translated into proteins. They are involved in pathogenesis of many diseases including cancer and have a potential to serve as diagnostic and prognostic markers. We aimed to investigate lncRNA expression profiles in bone marrow plasma cells (BMPCs) of newly diagnosed multiple myeloma (MM) patients in comparison to normal BMPCs of healthy donors (HD) in a three-phase biomarker study. METHODS: Expression profile of 83 lncRNA was performed by RT2 lncRNA PCR Array (Qiagen), followed by quantitative real-time PCR using specific TaqMan non-coding RNA assays analyzing 84 newly diagnosed MM patients and 25 HD. RESULTS: Our analysis revealed dysregulation of two lncRNAs; NEAT1 (sensitivity of 55.0% and specificity of 79.0%) and UCA1 (sensitivity of 85.0% and specificity of 94.7%). UCA1 levels correlated with albumin and monoclonal immunoglobulin serum levels, cytogenetic aberrations, and survival of MM patients. CONCLUSION: Our study suggests a possible prognostic impact of UCA1 expression levels on MM patients.

• Keywords
• biomarker, long non-coding RNA, multiple myeloma, plasma cells, prognosis, quantitative real-time PCR,
• MeSH
• Biomarkers MeSH
• Chromosome Aberrations MeSH
• Diagnosis, Differential MeSH
• In Situ Hybridization, Fluorescence MeSH
• Kaplan-Meier Estimate MeSH
• Real-Time Polymerase Chain Reaction MeSH
• Middle Aged MeSH
• Humans MeSH
• Multiple Myeloma diagnosis   genetics   mortality   therapy   MeSH
• Biomarkers, Tumor * MeSH
• Prognosis MeSH
• Gene Expression Regulation, Neoplastic * MeSH
• RNA, Long Noncoding genetics   MeSH
• ROC Curve MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Neoplasm Staging MeSH
• Gene Expression Profiling MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Biomarkers MeSH
• Biomarkers, Tumor * MeSH
• NEAT1 long non-coding RNA, human MeSH Browser
• RNA, Long Noncoding MeSH
• UCA1 RNA, human MeSH Browser

Emerging evidence has suggested a potential role for long non-coding RNAs (lncRNAs) in transcriptome dysregulation during Mycobacterium tuberculosis (Mtb) infection. Understanding the regulatory functions of lncRNAs can provide further insight into the interaction between Mtb and the host. In this study, we sought to explore the lncRNA signature in the Mtb-infected THP1 macrophages (H37Rv, H37Ra, and BCG strains) using the publicly available RNA sequencing dataset of GSE162729. Our analysis identified 6202 putative lncRNAs, with the majority being novel lncRNAs, indicating their significant involvement in the Mtb-infected macrophages. We also identified several differentially expressed lncRNA genes specifically induced in each infected group. Reactome enrichment pathway analysis on cis target genes of lncRNAs revealed that inflammatory immune responses were the predominant features of lncRNAs induced during the H37Rv infection compared to H3Ra and BCG infection. Scavenging by class A receptors and inflammasomes were also highlighted as the common enriched terms among Mtb- and BCG-infected groups. Moreover, we highlighted several potential lncRNAs as hub genes in the predicted regulatory network between the differentially expressed lncRNAs and miRNAs in Mtb-infected THP-1 cells. These findings suggested a possible diverse regulatory role for lncRNAs in the macrophage response to different Mycobacterium strain infections. Further functional study of the lncRNA genes in Mtb infection, while considering the genetic background of the Mtb strain, will be a promising focus for future research.

• Keywords
• Mycobacterium tuberculosis, Long non-coding RNAs, Transcriptomics, Tuberculosis,
• Publication type
• Journal Article MeSH

Clear-cell renal cell carcinoma (ccRCC) is a common urological malignancy with an increasing incidence. The development of molecular biomarkers that can predict the response to treatment and guide personalized therapy selection would substantially improve patient outcomes. Dysregulation of non-coding RNA (ncRNA) has been shown to have a role in the pathogenesis of ccRCC. Thus, an increasing number of studies are being carried out with a focus on the identification of ncRNA biomarkers in ccRCC tissue samples and the connection of these markers with patients' prognosis, pathological stage and grade (including metastatic potential), and therapy outcome. RNA sequencing analysis led to the identification of several ncRNA biomarkers that are dysregulated in ccRCC and might have a role in ccRCC development. These ncRNAs have the potential to be prognostic and predictive biomarkers for ccRCC, with prospective applications in personalized treatment selection. Research on ncRNA biomarkers in ccRCC is advancing, but clinical implementation remains preliminary owing to challenges in validation, standardization and reproducibility. Comprehensive studies and integration of ncRNAs into clinical trials are essential to accelerate the clinical use of these biomarkers.

• MeSH
• Carcinoma, Renal Cell * genetics   MeSH
• Humans MeSH
• Biomarkers, Tumor genetics   MeSH
• Kidney Neoplasms * genetics   MeSH
• RNA, Untranslated * genetics   MeSH
• Prognosis MeSH
• Transcriptome * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• Biomarkers, Tumor MeSH
• RNA, Untranslated * MeSH

BACKGROUND: Glioblastoma (GBM) is the most frequent primary brain tumor characterized by an unfavourable prognosis despite multimodal therapy. Therefore, a lot of efforts and financial resources are dedicated to the research of new therapeutic targets and prognostic or predictive biomarkers. Long non-coding RNAs (lncRNAs) are regulators of gene expression which play a significant role in GBM pathology and, thus, present promising candidates. MATERIAL AND METHODS: Our study included 14 patients with GBM and 8 patients with intractable epilepsy from whom we acquired brain tissues during surgical intervention. Ribosomal RNA depleted RNA was used for sequencing by NextSeq 500 instrument (Illumina). Statistical analysis evaluated 24,087 protein-coding and 8,414 non-coding RNAs and their sequential variants with non-zero reads per kilobase per million mapped reads (RPKM) at least in one sample. CLC Genomic Workbench was used for the alignment and target counts. Targeted downregulation of up-regulated ZFAS1, one of the identified lncRNA, level has been carried out by the transient transfection of specific small interfering RNA (siRNA) in GBM stable cell lines (A172, U87MG, T98G). The success of transfection and viability were analyzed in vitro using quantitative real time polymerase chain reaction and MTT assay, resp. RESULTS: Statistical analysis has revealed 274 (p < 0.01) dysregulated lncRNAs in GBMs in comparison with non-tumor brain tissues. Moreover, the results have showed 489 dysregulated mRNAs (p < 0.0001) and 26 mRNAs (p < 0.000001). Transfection of ZFAS1 inhibitor led to successful downregulation of ZFAS1 expression level, although it did not have a significant effect on proliferation of GBM cells. CONCLUSION: We described a significant dysregulation of lncRNAs and mRNAs in GBM tissue in comparison with non-tumor tissue. We also succesfully decreased expression level of ZFAS1, which in turn, however, had no impact on the viability of GBM cell lines.Key words: glioblastoma - long non-coding RNA - next-generation sequencing The authors declare they have no potential conflicts of interest concerning drugs, products, or services used in the study. The Editorial Board declares that the manuscript met the ICMJE recommendation for biomedical papers. This tudy was supported by Ministry of Health of the Czech Republic, grant No. 15-33158A. All rights reserved.Submitted: 19. 3. 2018Accepted: 10. 4. 2018.

• MeSH
• Epilepsy genetics   MeSH
• Glioblastoma genetics   MeSH
• Humans MeSH
• RNA, Small Interfering genetics   MeSH
• RNA, Messenger MeSH
• Brain metabolism   MeSH
• Biomarkers, Tumor genetics   MeSH
• Cell Line, Tumor MeSH
• Brain Neoplasms genetics   MeSH
• Cell Proliferation MeSH
• RNA, Long Noncoding * MeSH
• Sequence Analysis, RNA MeSH
• Cell Survival MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• RNA, Small Interfering MeSH
• RNA, Messenger MeSH
• Biomarkers, Tumor MeSH
• RNA, Long Noncoding * MeSH