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Abstract Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women’s plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method.

Abstract Clinical interpretation of copy number variants (CNVs) is a complex process that requires skilled clinical professionals. General recommendations have been recently released to guide the CNV interpretation based on predefined criteria to uniform the decision process. Several semiautomatic computational methods have been proposed to recommend appropriate choices, relieving clinicians of tedious searching in vast genomic databases. We have developed and evaluated such a tool called MarCNV and tested it on CNV records collected from the ClinVar database. Alternatively, the emerging machine learning-based tools, such as the recently published ISV (Interpretation of Structural Variants), showed promising ways of even fully automated predictions using broader characterization of affected genomic elements. Such tools utilize features additional to ACMG criteria, thus providing supporting evidence and the potential to improve CNV classification. Since both approaches contribute to evaluation of CNVs clinical impact, we propose a combined solution in the form of a decision support tool based on automated ACMG guidelines (MarCNV) supplemented by a machine learning-based pathogenicity prediction (ISV) for the classification of CNVs. We provide evidence that such a combined approach is able to reduce the number of uncertain classifications and reveal potentially incorrect classifications using automated guidelines. CNV interpretation using MarCNV, ISV, and combined approach is available for non-commercial use at https://predict.genovisio.com/ .

Copy number variants (CNVs) were the subject of extensive research in the past years. They are common features of the human genome that play an important role in evolution, contribute to population diversity, development of certain diseases, and influence host–microbiome interactions. CNVs have found application in the molecular diagnosis of many diseases and in non-invasive prenatal care, but their full potential is only emerging. CNVs are expected to have a tremendous impact on screening, diagnosis, prognosis, and monitoring of several disorders, including cancer and cardiovascular disease. Here, we comprehensively review basic definitions of the term CNV, outline mechanisms and factors involved in CNV formation, and discuss their evolutionary and pathological aspects. We suggest a need for better defined distinguishing criteria and boundaries between known types of CNVs.

Exosomes have the potential to be the future of personalized diagnostics and therapy. They are nano-sized particles between 30 and 100 nm flowing in the extracellular milieu, where they mediate cell–cell communication and participate in immune system regulation. Tumor-derived exosomes (TDEs) secreted from different types of cancer cells are the key regulators of the tumor microenvironment. With their immune suppressive cargo, TDEs prevent the antitumor immune response, leading to reduced effectiveness of cancer treatment by promoting a pro-tumorigenic microenvironment. Involved signaling pathways take part in the regulation of tumor proliferation, differentiation, apoptosis, and angiogenesis. Signal transducers and activators of transcription factors (STATs) and Janus kinase (JAK) signaling pathways are crucial in malignancies and autoimmune diseases alike, and their potential to be manipulated is currently the focus of interest. In this review, we aim to discuss exosomes, TDEs, and the JAK/STAT pathways, along with mediators like interleukins, tripartite motif proteins, and interferons.

Colorectal cancer (CRC) has one of the highest incidences among all types of malignant diseases, affecting millions of people worldwide. It shows slow progression, making it preventable. However, this is not the case due to shortcomings in its diagnostic and management procedure and a lack of effective non-invasive biomarkers for screening. Here, we discuss CRC-associated microRNAs (miRNAs) and gut microbial species with potential as CRC diagnostic and therapy biomarkers. We provide rich evidence of cross-kingdom miRNA-mediated interactions between the host and gut microbiome. miRNAs have emerged with the ability to shape the composition and dynamics of gut microbiota. Intestinal microbes can uptake miRNAs, which in turn influence microbial growth and provide the ability to regulate the abundance of various microbial species. In the context of CRC, targeting miRNAs could aid in manipulating the balance of the microbiota. Our findings suggest the need for correlation analysis between the composition of the gut microbiome and the miRNA expression profile.

Lynch syndrome (LS) is an autosomal dominant inherited cancer predisposition disorder, which may manifest as colorectal cancer (CRC), endometrial cancer (EC) or other malignancies of the gastrointestinal and genitourinary tract as well as the skin and brain. Its genetic cause is a defect in one of the four key DNA mismatch repair (MMR) loci. Testing of patients at risk is currently based on the absence of MMR protein staining and detection of mutations in cancer tissue and the germline, microsatellite instability (MSI) and the hypermethylated state of the MLH1 promoter. If LS is shown to have caused CRC, lifetime follow-up with regular screening (most importantly, colonoscopy) is required. In recent years, DNA and RNA markers extracted from liquid biopsies have found some use in the clinical diagnosis of LS. They have the potential to greatly enhance the efficiency of the follow-up process by making it minimally invasive, reproducible, and time effective. Here, we review markers reported in the literature and their current clinical applications, and we comment on possible future directions.

To study the detection limits of chromosomal microaberrations in non-invasive prenatal testing with aim for five target microdeletion syndromes, including DiGeorge, Prader-Willi/Angelman, 1p36, Cri-Du-Chat, and Wolf-Hirschhorn syndromes. We used known cases of pathogenic deletions from ISCA database to specifically define regions critical for the target syndromes. Our approach to detect microdeletions, from whole genome sequencing data, is based on sample normalization and read counting for individual bins. We performed both an in-silico study using artificially created data sets and a laboratory test on mixed DNA samples, with known microdeletions, to assess the sensitivity of prediction for varying fetal fractions, deletion lengths, and sequencing read counts. The in-silico study showed sensitivity of 79.3% for 10% fetal fraction with 20M read count, which further increased to 98.4% if we searched only for deletions longer than 3Mb. The test on laboratory-prepared mixed samples was in agreement with in-silico results, while we were able to correctly detect 24 out of 29 control samples. Our results suggest that it is possible to incorporate microaberration detection into basic NIPT as part of the offered screening/diagnostics procedure, however, accuracy and reliability depends on several specific factors.

Early detection, characterization and monitoring of cancer are possible by using extracellular vesicles (EVs) isolated from non-invasively obtained liquid biopsy samples. They play a role in intercellular communication contributing to cell growth, differentiation and survival, thereby affecting the formation of tumor microenvironments and causing metastases. EVs were discovered more than seventy years ago. They have been tested recently as tools of drug delivery to treat cancer. Here we give a brief review on extracellular vesicles, exosomes, microvesicles and apoptotic bodies. Exosomes play an important role by carrying extracellular nucleic acids (DNA, RNA) in cell-to-cell communication causing tumor and metastasis development. We discuss the role of extracellular vesicles in the pathogenesis of cancer and their practical application in the early diagnosis, follow up, and next-generation treatment of cancer patients.

Prenatal testing in recent years has been moving toward non-invasive methods to determine the fetal risk for genetic disorders without incurring the risk of miscarriage. Rapid progress of modern high-throughput molecular technologies along with the discovery of cell-free fetal DNA in maternal plasma led to novel screening methods for fetal chromosomal aneuploidies. Such tests are referred to as non-invasive prenatal tests (NIPTs), non-invasive prenatal screening, or prenatal cell-free DNA screening. Owing to many advantages, the adoption of NIPT in routine clinical practice was very rapid and global. As an example, NIPT has recently become a standard screening procedure for all pregnant women in the Netherlands. On the other hand, invasive sampling procedures remain important, especially for their diagnostic value in the confirmation of NIPT-positive findings and the detection of Mendelian disorders. In this review, we focus on current trends in the field of NIPT and discuss their benefits, drawbacks, and consequences in regard to routine diagnostics.

Gains and losses of large segments of genomic DNA, known as copy number variants (CNVs) gained considerable interest in clinical diagnostics lately, as particular forms may lead to inherited genetic diseases. In recent decades, researchers developed a wide variety of cytogenetic and molecular methods with different detection capabilities to detect clinically relevant CNVs. In this review, we summarize methodological progress from conventional approaches to current state of the art techniques capable of detecting CNVs from a few bases up to several megabases. Although the recent rapid progress of sequencing methods has enabled precise detection of CNVs, determining their functional effect on cellular and whole-body physiology remains a challenge. Here, we provide a comprehensive list of databases and bioinformatics tools that may serve as useful assets for researchers, laboratory diagnosticians, and clinical geneticists facing the challenge of CNV detection and interpretation.

Analyzes of cell-free nucleic acids (cfNAs) have shown huge potential in many biomedical applications, gradually entering several fields of research and everyday clinical care. Many biological properties of cfNAs can be informative to gain deeper insights into the function of the organism, such as their different types (DNA, RNAs) and subtypes (gDNA, mtDNA, bacterial DNA, miRNAs, etc.), forms (naked or vesicle bound NAs), fragmentation profiles, sequence composition, epigenetic modifications, and many others. On the other hand, the workflows of their analyzes comprise many important steps, from sample collection, storage and transportation, through extraction and laboratory analysis, up to bioinformatic analyzes and statistical evaluations, where each of these steps has the potential to affect the outcome and informational value of the performed analyzes. There are, however, no universal or standard protocols on how to exactly proceed when analyzing different cfNAs for different applications, at least according to our best knowledge. We decided therefore to prepare an overview of the available literature and products commercialized for cfNAs processing, in an attempt to summarize the benefits and limitations of the currently available approaches, devices, consumables, and protocols, together with various factors influencing the workflow, its processes, and outcomes.

Liquid biopsy recently became a very promising diagnostic method that has several advantages over conventional invasive methods. Liquid biopsy may serve as a source of several important biomarkers including cell-free nucleic acids (cf-NAs). Cf-DNA is widely used in prenatal testing in order to characterize fetal genetic disorders. Analysis of cf-DNA may provide information about the mutation profile of tumor cells, while cell-free non-coding RNAs are promising biomarker candidates in the diagnosis and prognosis of cancer. Many of these markers have the potential to help clinicians in therapy selection and in the follow-up of patients. Thus, cf-NA-based diagnostics represent a new path in personalized medicine. Although several reviews are available in the field, most of them focus on a limited number of cf-NA types. In this review, we give an overview about all known cf-NAs including cf-DNA, cf-mtDNA and cell-free non-coding RNA (miRNA, lncRNA, circRNA, piRNA, YRNA, and vtRNA) by discussing their biogenesis, biological function and potential as biomarker candidates in liquid biopsy. We also outline possible future directions in the field.

Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study.

Abstract Background Whole exome sequencing (WES) and whole genome sequencing (WGS) have become standard methods in human clinical diagnostics as well as in population genomics (POPGEN). Blood-derived genomic DNA (gDNA) is routinely used in the clinical environment. Conversely, many POPGEN studies and commercial tests benefit from easy saliva sampling. Here, we evaluated the quality of variant call sets and the level of genotype concordance of single nucleotide variants (SNVs) and small insertions and deletions (indels) for WES and WGS using paired blood- and saliva-derived gDNA isolates employing genomic reference-based validated protocols. Methods The genomic reference standard Coriell NA12878 was repeatedly analyzed using optimized WES and WGS protocols, and data calls were compared with the truth dataset published by the Genome in a Bottle Consortium. gDNA was extracted from the paired blood and saliva samples of 10 participants and processed using the same protocols. A comparison of paired blood–saliva call sets was performed in the context of WGS and WES genomic reference-based technical validation results. Results The quality pattern of called variants obtained from genomic-reference-based technical replicates correlates with data calls of paired blood–saliva-derived samples in all levels of tested examinations despite a higher rate of non-human contamination found in the saliva samples. The F1 score of 10 blood-to-saliva-derived comparisons ranged between 0.8030–0.9998 for SNVs and between 0.8883–0.9991 for small-indels in the case of the WGS protocol, and between 0.8643–0.999 for SNVs and between 0.7781–1.000 for small-indels in the case of the WES protocol. Conclusion Saliva may be considered an equivalent material to blood for genetic analysis for both WGS and WES under strict protocol conditions. The accuracy of sequencing metrics and variant-detection accuracy is not affected by choosing saliva as the gDNA source instead of blood but much more significantly by the genomic context, variant types, and the sequencing technology used.

This paper presents a comprehensive investigation of machine learning-based intrusion detection methods to reveal cyber attacks in railway axle counting networks. In contrast to the state-of-the-art works, our experimental results are validated with testbed-based real-world axle counting components. Furthermore, we aimed to detect targeted attacks on axle counting systems, which have higher impacts than conventional network attacks. We present a comprehensive investigation of machine learning-based intrusion detection methods to reveal cyber attacks in railway axle counting networks. According to our findings, the proposed machine learning-based models were able to categorize six different network states (normal and under attack). The overall accuracy of the initial models was ca. 70–100% for the test data set in laboratory conditions. In operational conditions, the accuracy decreased to under 50%. To increase the accuracy, we introduce a novel input data-preprocessing method with the denoted gamma parameter. This increased the accuracy of the deep neural network model to 69.52% for six labels, 85.11% for five labels, and 92.02% for two labels. The gamma parameter also removed the dependence on the time series, enabled relevant classification of data in the real network, and increased the accuracy of the model in real operations. This parameter is influenced by simulated attacks and, thus, allows the classification of traffic into specified classes.

Abstract Background Knowledge about the expression and thus a role of enzymes that produce endogenous H2S - cystathionine-β-synthase, cystathionine γ-lyase and mercaptopyruvate sulfurtransferase - in renal tumors is still controversial. In this study we aimed to determine the expression of these enzymes relatively to the expression in unaffected part of kidney from the same patient and to found relation of these changes to apoptosis. To evaluate patient’s samples, microarray and immunohistochemistry was used. Methods To determine the physiological importance, we used RCC4 stable cell line derived from clear cell renal cell carcinoma, where apoptosis induction by a mixture of five chemotherapeutics with/without silencing of H2S-producing enzymes was detected. Immunofluorescence was used to determine each enzyme in the cells. Results In clear cell renal cell carcinomas, expression of H2S-producing enzymes was mostly decreased compared to a part of kidney that was distal from the tumor. To evaluate a potential role of H2S-producing enzymes in the apoptosis induction, we used RCC4 stable cell line. We have found that silencing of cystathionine-β-synthase and cystathionine γ-lyase prevented induction of apoptosis. Immunofluorescence staining clearly showed that these enzymes were upregulated during apoptosis in RCC4 cells. Conclusion Based on these results we concluded that in clear cell renal cell carcinoma, reduced expression of the H2S-producing enzymes, mainly cystathionine γ-lyase, might contribute to a resistance to the induction of apoptosis. Increased production of the endogenous H2S, or donation from the external sources might be of a therapeutic importance in these tumors.

In recent years, the Industry 4.0 paradigm has accelerated the digitalization process of the industry, and it slowly diminishes the line between information technologies (IT) and operational technologies (OT). Among the advantages, this brings up the convergence issue between IT and OT, especially in the cybersecurity-related topics, including new attack vectors, threats, security imperfections, and much more. This cause raised new topics for methods focused on protecting the industrial infrastructure, including monitoring and detection systems, which should help overcome these new challenges. However, those methods require high quality and a large number of datasets with different conditions to adapt to the specific systems effectively. Unfortunately, revealing field factory setups and infrastructure would be costly and challenging due to the privacy and sensitivity causes. From the lack of data emerges the new topic of industrial testbeds, including sub-real physical laboratory environments, virtual factories, honeynets, honeypots, and other areas, which helps to deliver sufficient datasets for mentioned research and development. This paper summarizes related works in the area of industrial testbeds. Moreover, it describes best practices and lessons learned for assembling physical, simulated, virtual, and hybrid testbeds. Additionally, a comparison of the essential parameters of those testbeds is presented. Finally, the findings and provided information reveal research and development challenges, which must be surpassed.

The low-power wide-area (LPWA) technologies, which enable cost and energy-efficient wireless connectivity for massive deployments of autonomous machines, have enabled and boosted the development of many new Internet of things (IoT) applications; however, the security of LPWA technologies in general, and specifically those operating in the license-free frequency bands, have received somewhat limited attention so far. This paper focuses specifically on the security and privacy aspects of one of the most popular license-free-band LPWA technologies, which is named LoRaWAN. The paper’s key contributions are the details of the design and experimental validation of a security-focused testbed, based on the combination of software-defined radio (SDR) and GNU Radio software with a standalone LoRaWAN transceiver. By implementing the two practical man-in-the-middle attacks (i.e., the replay and bit-flipping attacks through intercepting the over-the-air activation procedure by an external to the network attacker device), we demonstrate that the developed testbed enables practical experiments for on-air security in real-life conditions. This makes the designed testbed perspective for validating the novel security solutions and approaches and draws attention to some of the relevant security challenges extant in LoRaWAN.