TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures.

Background: In the precision medicine era, identifying predictive factors to select patients most likely to benefit from treatment with immunological agents is a crucial and open challenge in oncology. Methods: This paper presents a pan-cancer analysis of Tumor Mutational Burden (TMB). We developed a novel computational pipeline, TMBcalc, to calculate the TMB. Our methodology can identify small and reliable gene signatures to estimate TMB from custom targeted-sequencing panels. For this purpose, our pipeline has been trained on top of 17 cancer types data obtained from TCGA. Results: Our results show that TMB, computed through the identified signature, strongly correlates with TMB obtained from whole-exome sequencing (WES). Conclusion: We have rigorously analyzed the effectiveness of our methodology on top of several independent datasets. In particular we conducted a comprehensive testing on: (i) 126 samples sourced from the TCGA database; few independent whole-exome sequencing (WES) datasets linked to colon, breast, and liver cancers, all acquired from the EGA and the ICGC Data Portal. This rigorous evaluation clearly highlights the robustness and practicality of our approach, positioning it as a promising avenue for driving substantial progress within the realm of clinical practice.

Measuring cancer driving force of chromosomal aberrations through multi-layer Boolean implication networks.

Multi-layer Complex networks are commonly used for modeling and analysing biological entities. This paper presents the advantage of using COMBO (Combining Multi Bio Omics) to suggest a new role of the chromosomal aberration as a cancer driver factor. Exploiting the heterogeneous multi-layer networks, COMBO integrates gene expression and DNA-methylation data in order to identify complex bilateral relationships between transcriptome and epigenome. We evaluated the multi-layer networks generated by COMBO on different TCGA cancer datasets (COAD, BLCA, BRCA, CESC, STAD) focusing on the effect of a specific chromosomal numerical aberration, broad gain in chromosome 20, on different cancer histotypes. In addition, the effect of chromosome 8q amplification was tested in the same TCGA cancer dataset. The results demonstrate the ability of COMBO to identify the chromosome 20 amplification cancer driver force in the different TCGA Pan Cancer project datasets.

NetMe 2.0: a web-based platform for extracting and modeling knowledge from biomedical literature as a labeled graph.

MOTIVATION: The rapid increase of bio-medical literature makes it harder and harder for scientists to keep pace with the discoveries on which they build their studies. Therefore, computational tools have become more widespread, among which network analysis plays a crucial role in several life-science contexts. Nevertheless, building correct and complete networks about some user-defined biomedical topics on top of the available literature is still challenging. RESULTS: We introduce NetMe 2.0, a web-based platform that automatically extracts relevant biomedical entities and their relations from a set of input texts-i.e. in the form of full-text or abstract of PubMed Central's papers, free texts, or PDFs uploaded by users-and models them as a BioMedical Knowledge Graph (BKG). NetMe 2.0 also implements an innovative Retrieval Augmented Generation module (Graph-RAG) that works on top of the relationships modeled by the BKG and allows the distilling of well-formed sentences that explain their content. The experimental results show that NetMe 2.0 can infer comprehensive and reliable biological networks with significant Precision-Recall metrics when compared to state-of-the-art approaches. AVAILABILITY AND IMPLEMENTATION: https://netme.click/.

Drug resistant epilepsies: A multicentre case series of steroid therapy.

PURPOSE: Our study aimed to evaluate the effectiveness of corticosteroids on seizure control in drug-resistant epilepsies (DREs). Our primary goal was to assess the response to steroids for various underlying etiologies, interictal electroencephalographic (EEG) patterns and electroclinical seizure descriptions. Our second goal was to compare steroid responsiveness to different treatment protocols. METHODS: This is a retrospective multicentre cohort study conducted according to the STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology). The following data were collected for each patient: epilepsy etiology, interictal EEG pattern, seizure types and type of steroid treatment protocol administered. RESULTS: Thirty patients with DRE were included in the study. After 6 months of therapy, 62.7 % of patients experienced reduced seizure frequency by 50 %, and 6.6 % of patients experienced complete seizure cessation. Findings associated with favourable response to steroids included structural/lesional etiology of epilepsy, immune/infectious etiology and focal interictal abnormalities on EEG. Comparing four different steroid treatment protocols, the most effective for seizure control was treatment with methylprednisolone at the dose of 30 mg/kg/day administered for 3 days, leading to greater than 50 % seizure reduction at 6 months in 85.7 % of patients. Treatment with dexamethasone 6 mg/day for 5 days decreased seizure frequency in 71.4 % of patients. Hydrocortisone 10 mg/kg administered for 3 months showed a good response to treatment in 71 %. CONCLUSIONS: In our study, two-thirds of patients with DRE experienced a significant seizure reduction following treatment with steroids. We suggest considering steroids as a potential therapeutic option in children with epilepsy not responding to conventional antiseizure medicines (ASM).

tRFUniverse: A comprehensive resource for the interactive analyses of tRNA-derived ncRNAs in human cancer.

tRNA-derived ncRNAs are a heterogeneous class of non-coding RNAs recently proposed to be active regulators of gene expression and be involved in many diseases, including cancer. Consequently, several online resources on tRNA-derived ncRNAs have been released. Although interesting, such resources present only basic features and do not adequately exploit the wealth of knowledge available about tRNA-derived ncRNAs. Therefore, we introduce tRFUniverse, a novel online resource for the analysis of tRNA-derived ncRNAs in human cancer. tRFUniverse presents an extensive collection of classes of tRNA-derived ncRNAs analyzed across all the TCGA and TARGET tumor cohorts, NCI-60 cell lines, and biological fluids. Moreover, public AGO CLASH/CLIP-Seq data were analyzed to identify the molecular interactions between tRNA-derived ncRNAs and other transcripts. Importantly, tRFUniverse combines in a single resource a comprehensive set of features that we believe may be helpful to investigate the involvement of tRNA-derived ncRNAs in cancer biology.

Efficacy of High-dose Liraglutide 3.0 mg in Patients with Poor Response to Bariatric Surgery: Real-world Experience and Updated Meta-analysis.

PURPOSE: Poor response to bariatric surgery, characterized by insufficient weight loss (IWL) or weight regain (WR), poses a significant challenge in obesity treatment. This study aims to assess the effectiveness of liraglutide in addressing this issue. MATERIALS AND METHODS: A retrospective, multicenter cohort study investigated the impact of liraglutide 3 mg on weight loss in adults with suboptimal responses or weight regain after bariatric surgery (BS). Additionally, a systematic review and meta-analysis were conducted for a comprehensive evaluation. RESULTS: A total of 119 patients (mean age 41.03 ± 11.2 years, 71.4% female) who experienced IWL or WR after BS received pharmacologic therapy with liraglutide 3 mg. Mean percent weight loss in the entire cohort was 5.6 ± 2.6% at 12 weeks and 9.3 ± 3.6% at 24 weeks with a significant reduction in waist circumference (p < 0.0001). No serious side effects were reported. A meta-analysis, utilizing the fixed effect model with the metafor package in R, included 6 and 5 papers for the change in body weight and BMI after liraglutide treatment, respectively. The analysis demonstrated a considerable reduction in body weight (7.9; CI - 10.4; - 5.4, p < 0.0001) and BMI (3.09; CI 3.89; - 2.28, p < 0.0001). CONCLUSION: Liraglutide 3 mg emerges as a viable option for significant weight loss in patients experiencing IWL or WR after BS. Its inclusion in a multimodal, sequential obesity treatment approach proves promising.

Serum and Tissue Biomarkers Associated With Composite of Relevant Endpoints for Sjögren Syndrome (CRESS) and Sjögren Tool for Assessing Response (STAR) to B Cell-Targeted Therapy in the Trial of Anti-B Cell Therapy in Patients With Primary Sjögren Syndrome (TRACTISS).

OBJECTIVE: This study aimed to identify peripheral and salivary gland (SG) biomarkers of response/resistance to B cell depletion based on the novel concise Composite of Relevant Endpoints for Sjögren Syndrome (cCRESS) and candidate Sjögren Tool for Assessing Response (STAR) composite endpoints. METHODS: Longitudinal analysis of peripheral blood and SG biopsies was performed pre- and post-treatment from the Trial of Anti-B Cell Therapy in Patients With Primary Sjögren Syndrome (TRACTISS) combining flow cytometry immunophenotyping, serum cytokines, and SG bulk RNA sequencing. RESULTS: Rituximab treatment prevented the worsening of SG inflammation observed in the placebo arm, by inhibiting the accumulation of class-switched memory B cells within the SG. Furthermore, rituximab significantly down-regulated genes involved in immune-cell recruitment, lymphoid organization alongside antigen presentation, and T cell co-stimulatory pathways. In the peripheral compartment, rituximab down-regulated immunoglobulins  and auto-antibodies together with pro-inflammatory cytokines and chemokines. Interestingly, patients classified as responders  according to STAR displayed significantly higher baseline levels of C-X-C motif chemokine ligand-13 (CXCL13), interleukin (IL)-22, IL-17A, IL-17F, and tumor necrosis factor-α (TNF-α), whereas a longitudinal analysis of serum T cell-related cytokines showed a selective reduction in both STAR and cCRESS responder patients. Conversely, cCRESS response was better associated with biomarkers of SG immunopathology, with cCRESS-responders showing a significant decrease in SG B cell infiltration and reduced expression of transcriptional gene modules related to T cell costimulation, complement activation, and Fcγ-receptor engagement. Finally, cCRESS and STAR response were associated with a significant improvement in SG exocrine function linked to transcriptional evidence of SG epithelial and metabolic restoration. CONCLUSION: Rituximab modulates both peripheral and SG inflammation, preventing the deterioration of exocrine function with functional and metabolic restoration of the glandular epithelium. Response assessed by newly developed cCRESS and STAR criteria was associated with differential modulation of peripheral and SG biomarkers, emerging as novel tools for patient stratification.

Expression signature of human endogenous retroviruses in chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) is one of the most diagnosed forms of leukemia worldwide and it is usually classified into two forms: indolent and aggressive. These two forms are characterized by distinct molecular features that drive different responses to treatment and clinical outcomes. In this context, a better understanding of the molecular landscape of the CLL forms may potentially lead to the development of new drugs or the identification of novel biomarkers. Human endogenous retroviruses (HERVs) are a class of transposable elements that have been associated with the development of different human cancers, including different forms of leukemias. However, no studies about HERVs in CLL have ever been reported so far. Here, we present the first locus-specific profiling of HERV expression in both the aggressive and indolent forms of CLL. Our analyses revealed several dysregulations in HERV expression occurring in CLL and some of them were specific for either the aggressive or indolent form of CLL. Such results were also validated by analyzing an external cohort of CLL patients and by RT-qPCR. Moreover, in silico analyses have shown relevant signaling pathways associated with them suggesting a potential involvement of the dysregulated HERVs in these pathways and consequently in CLL development.

High-dose liraglutide improves metabolic syndrome in poor responders to bariatric surgery.

Background: Bariatric surgery (BS) represents the most effective therapy for obesity class III, or class II with at least one weight-related comorbidity. However, some patients have insufficient weight loss or clinically relevant weight regain after a successful primary procedure. This study aimed to assess the efficacy of liraglutide treatment on weight loss, body composition and improvement of metabolic syndrome (MS) in patients defined as poor responders after BS. Methods: The study involved 59 non-diabetic adults with obesity (M/F: 17/42, age: 38.6 ± 11.8 years, BMI 38.3 ± 5.5 kg/m2) who had been treated with BS and experienced a poor response, categorized as either IWL (insufficient weight loss) or WR (weight regain). All patients were prescribed pharmacological therapy with liraglutide and attended nutritional counseling. Anthropometric and clinical measurements, body composition and the presence of MS defined according to the ATP-III classification were evaluated before starting liraglutide and after 24 weeks of treatment. Results: After 24 weeks of treatment with liraglutide, the mean weight loss was 8.4% ± 3.6% with no difference between gender, bariatric procedure, or type of poor response (IWL or WR). A significant decrease in fat mass, free-fat mass and total body water was documented. After 24 weeks, patients presented significantly lowered fasting glucose, total cholesterol, triglycerides, AST and ALT. The prevalence of MS was reduced from 35% at baseline to 1.6% after 24 weeks. No patients discontinued the treatment during the study. Conclusion: In patients who experience poor response after BS, liraglutide is well tolerated and promotes significant weight loss, ameliorates cardiometabolic comorbidities, and reduces the prevalence of MS.

XRF analysis searching for fingerprint elemental profile in south-eastern Sicily tomatoes.

The implementation of analytical techniques able to certify food quality and origin in a fast and non-destructive way is becoming a widespread need in the agri-food sector. Among the physical non-destructive techniques, X-ray fluorescence (XRF) spectrometry is often used to analyze the elemental composition of biological samples. In this study, X-ray fluorescence (XRF) elemental profiles were measured on tomato samples belonging to different geographical areas in Sicily (Italy). The purpose of this investigation was aiming to establish a protocol for in-situ measurement and analysis able to provide quality assessment and traceability of PGI agri-food products, specifically sustaining health safety and self qualifying bio-chemical signature. In detail, sampling was performed in one of the most tomato productive area of south-eastern Sicily (Pachino district), characterised by a relative higher amount of Organic Carbon and Cation Exchange Capacity, and compared with samples from other growing areas of Sicily, falling in Ragusa province and Mt. Etna region. Experimental data were analyzed in the framework of multivariate analysis by using principal component analysis and further validated by discriminant analysis. The results show the presence of specific elemental signatures associated to several characterizing elements. This methodology establishes the possibility to disentangle a clear fingerprint pattern associated to the geographical origin of an agri-food product.

MultiplexSAGE: A Multiplex Embedding Algorithm for Inter-Layer Link Prediction.

Research on graph representation learning has received great attention in recent years. However, most of the studies so far have focused on the embedding of single-layer graphs. The few studies dealing with the problem of representation learning of multilayer structures rely on the strong hypothesis that the inter-layer links are known, and this limits the range of possible applications. Here we propose MultiplexSAGE, a generalization of the GraphSAGE algorithm that allows embedding multiplex networks. We show that MultiplexSAGE is capable to reconstruct both the intra-layer and the inter-layer connectivity, outperforming competing methods. Next, through a comprehensive experimental analysis, we shed light also on the performance of the embedding, both in simple and multiplex networks, showing that both the density of the graph and the randomness of the links strongly influences the quality of the embedding.

DEGGs: an R package with shiny app for the identification of differentially expressed gene-gene interactions in high-throughput sequencing data.

SUMMARY: The discovery of differential gene-gene correlations across phenotypical groups can help identify the activation/deactivation of critical biological processes underlying specific conditions. The presented R package, provided with a count and design matrix, extract networks of group-specific interactions that can be interactively explored through a shiny user-friendly interface. For each gene-gene link, differential statistical significance is provided through robust linear regression with an interaction term. AVAILABILITY AND IMPLEMENTATION: DEGGs is implemented in R and available on GitHub at https://github.com/elisabettasciacca/DEGGs. The package is also under submission on Bioconductor.

Application of the PHENotype SIMulator for rapid identification of potential candidates in effective COVID-19 drug repurposing.

The current, rapidly diversifying pandemic has accelerated the need for efficient and effective identification of potential drug candidates for COVID-19. Knowledge on host-immune response to SARS-CoV-2 infection, however, remains limited with few drugs approved to date. Viable strategies and tools are rapidly arising to address this, especially with repurposing of existing drugs offering significant promise. Here we introduce a systems biology tool, the PHENotype SIMulator, which -by leveraging available transcriptomic and proteomic databases-allows modeling of SARS-CoV-2 infection in host cells in silico to i) determine with high sensitivity and specificity (both>96%) the viral effects on cellular host-immune response, resulting in specific cellular SARS-CoV-2 signatures and ii) utilize these cell-specific signatures to identify promising repurposable therapeutics. Powered by this tool, coupled with domain expertise, we identify several potential COVID-19 drugs including methylprednisolone and metformin, and further discern key cellular SARS-CoV-2-affected pathways as potential druggable targets in COVID-19 pathogenesis.

Long-Term Survivors in a Cohort of People Living with HIV Diagnosed between 1985 and 1994: Predictive Factors Associated with More Than 25 Years of Survival.

Although the mortality rate among individuals diagnosed during the pre-Highly Active Antiretroviral Treatment era has been substantial, a considerable number of them survived. Our study aimed to evaluate the prevalence of HIV long-term survivors in a cohort of People Living with HIV diagnosed between 1985 and 1994 and to speculate about potential predictive factors associated to long survival. This is a retrospective single-center study. Subjects surviving more than 300 months (25 years) from HIV diagnosis were defined as Long Term Survivors. Overall, 210 subjects were enrolled. More than 75.24% of the included people living with HIV were males, with a median age of 28 years (IQR 25-34). The prevalent risk factors for HIV infection were injection drug use (47.62%), followed by unprotected sex among heterosexual individuals (23.81%). Ninety-three individuals (44.29%) could be defined as LTS with a median (IQR) survival of 333 (312-377) months. A hazard ratio of 12.45 (95% CI 7.91-19.59) was found between individuals who were exposed to Highly Active AntiRetroviral Treatment (HAART) and individuals who were not, with the latter being at greater risk of death. The availability and accessibility of effective antiretroviral therapy for people living with HIV remain the cornerstone of survival.

Neuroblastic tumors and neurofibromatosis type 1: A retrospective multicenter study in Italy and systematic review of the literature.

Background: Neuroblastic tumors (NBTs) are the most common extra-cranial solid tumors of childhood. Neurofibromatosis type 1 (NF1) is the most common neurocutaneous disorder with a predisposition to tumors. The co-occurrence of NBTs in the setting of NF1 has been occasionally reported, suggesting a non-casual association and likely configuring a spectrum of neural crest-derived disorders. Aim of the study: To explore the occurrence of NBTs within NF1 and to report on its natural history, therapeutic strategies, and outcomes in an Italian cohort of children with NF1 and in the literature. Subjects and Methods: Study (a): a retrospective analysis of questionnaire-based data [years 1979-2017] derived from the databases of the Italian Registry for Neuroblastoma (RINB) of the Italian Society of Pediatric Onco-Haematology (AIEOP); and Study (b): a systematic review search on NF1/NB co-occurrence. Results: Study (a) identified eight children with NBTs, 0.2% of patients registered in the RINB, fulfilling the diagnostic criteria for NF1. The primary site of NBTs was abdominal in six patients. The NBTs were neuroblastoma (NB) in five patients, ganglioneuroblastoma (GNB) in one, patient, and ganglioneuroma (GN) in two. Metastatic diffusion occurred in three out of eight children. MYCN gene testing, performed in the tumors of five patients, resulted not-amplified. The major features of NF1 included the following: NF1 family history in four patients, café-au-lait spots in all, freckling in six, Lisch nodules in three, and neurofibromas in three. With regard to the outcome, four children survived three of these for the progression of NB and one for a second tumor. Study (b) identified 12 patients with NF1/NB from the years 1966-2017, and the median age at diagnosis was 27 months (range = 0-168 months). The primary site of NB was thoracic. The prevalent histotype was NB in nine patients, GNB in two, and GN in one. Eight/nine NBs were metastatic. The MYCN gene was amplified in the only studied case. The NF1 features included NF1 family history in seven patients; the major NF1 features were café-au-lait spots in nine patients, freckling in one, Lisch nodules in none, and neurofibromas in six. The outcome was good for only two children, while eight children died of neuroblastoma, at a median age of 49.5 months (range = 2.4-174 months), with a median survival time of 21.75 months after diagnosis. Conclusions: To our knowledge, this represents the first systematic study on the occurrence of NBTs in NF1. This confirms that NBs are rare per se in the setting of NF1 (0.2% of all NBs) and even if compared to the overall frequency of malignancies in NF1 (i.e., 14.7%). The male:female ratio in study (a) (0.6) was different from what was recorded in study (b) (1.5) and in line with the overall increased frequency of malignancies in females with NF1. The median ages at diagnosis of NB in either study (a) or (b) were concordant with what occurred in the NB population. In study (a) versus study (b), the frequency of metastatic diffusion was lower, likely indicating less awareness on work-ups for malignancies in old NF1 series in the literature. The outcome was much better in study (a) than in study (b), indicating that multidisciplinary treatment for NB is highly recommended.

Transcriptome Analysis of Human Endogenous Retroviruses at Locus-Specific Resolution in Non-Small Cell Lung Cancer.

Lung cancer is the second most commonly diagnosed cancer and the leading cause of cancer deaths worldwide. Among its subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the most common, accounting for more than 85% of lung cancer diagnoses. Despite the incredible efforts and recent advances in lung cancer treatments, patients affected by this condition still have a poor prognosis. Therefore, novel diagnostic biomarkers are needed. Recently, a class of transposable elements called human endogenous retroviruses (HERVs) has been found to be implicated in cancer development and later employed as novel biomarkers for several tumor types. In this study, we first ever characterized the expression of HERVs at genomic locus-specific resolution in both LUAD and LUSC cohorts available in The Cancer Genome Atlas (TCGA). Precisely, (i) we profiled the expression of HERVs in TCGA-LUAD and TCGA-LUSC cohorts; (ii) we identified the dysregulated HERVs in both lung cancer subtypes; (iii) we evaluated the impact of the dysregulated HERVs on signaling pathways using neural network-based predictions; and (iv) we assessed their association with overall survival (OS) and relapse-free survival (RFS). In conclusion, we believe this study may help elucidate another layer of dysregulation that occurs in lung cancer involving HERVs, paving the way for identifying novel lung cancer biomarkers.

Soil and Soilless Tomato Cultivation Promote Different Microbial Communities That Provide New Models for Future Crop Interventions.

The cultivation of soilless tomato in greenhouses has increased considerably, but little is known about the assembly of the root microbiome compared to plants grown in soil. To obtain such information, we constructed an assay in which we traced the bacterial and fungal communities by amplicon-based metagenomics during the cultivation chain from nursery to greenhouse. In the greenhouse, the plants were transplanted either into agricultural soil or into coconut fiber bags (soilless). At the phylum level, bacterial and fungal communities were primarily constituted in all microhabitats by Proteobacteria and Ascomycota, respectively. The results showed that the tomato rhizosphere microbiome was shaped by the substrate or soil in which the plants were grown. The microbiome was different particularly in terms of the bacterial communities. In agriculture, enrichment has been observed in putative biological control bacteria of the genera Pseudomonas and Bacillus and in potential phytopathogenic fungi. Overall, the study describes the different shaping of microbial communities in the two cultivation methods.

Network analysis of synovial RNA sequencing identifies gene-gene interactions predictive of response in rheumatoid arthritis.

BACKGROUND: To determine whether gene-gene interaction network analysis of RNA sequencing (RNA-Seq) of synovial biopsies in early rheumatoid arthritis (RA) can inform our understanding of RA pathogenesis and yield improved treatment response prediction models. METHODS: We utilized four well curated pathway repositories obtaining 10,537 experimentally evaluated gene-gene interactions. We extracted specific gene-gene interaction networks in synovial RNA-Seq to characterize histologically defined pathotypes in early RA and leverage these synovial specific gene-gene networks to predict response to methotrexate-based disease-modifying anti-rheumatic drug (DMARD) therapy in the Pathobiology of Early Arthritis Cohort (PEAC). Differential interactions identified within each network were statistically evaluated through robust linear regression models. Ability to predict response to DMARD treatment was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: Analysis comparing different histological pathotypes showed a coherent molecular signature matching the histological changes and highlighting novel pathotype-specific gene interactions and mechanisms. Analysis of responders vs non-responders revealed higher expression of apoptosis regulating gene-gene interactions in patients with good response to conventional synthetic DMARD. Detailed analysis of interactions between pairs of network-linked genes identified the SOCS2/STAT2 ratio as predictive of treatment success, improving ROC area under curve (AUC) from 0.62 to 0.78. We identified a key role for angiogenesis, observing significant statistical interactions between NOS3 (eNOS) and both CAMK1 and eNOS activator AKT3 when comparing responders and non-responders. The ratio of CAMKD2/NOS3 enhanced a prediction model of response improving ROC AUC from 0.63 to 0.73. CONCLUSIONS: We demonstrate a novel, powerful method which harnesses gene interaction networks for leveraging biologically relevant gene-gene interactions leading to improved models for predicting treatment response.

Dysregulation of microRNAs and tRNA-derived ncRNAs in mesothelial and mesothelioma cell lines after asbestiform fiber exposure.

Experimental evidence demonstrated that fluoro-edenite (FE) can develop chronic respiratory diseases and elicit carcinogenic effects. Environmental exposure to FE fibers is correlated with malignant pleural mesothelioma (MPM). An early diagnosis of MPM, and a comprehensive health monitoring of the patients exposed to FE fibers are two clinical issues that may be solved by the identification of specific biomarkers. We reported the microRNA (miRNA) and transfer RNA-derived non coding RNA (tRNA-derived ncRNA) transcriptome in human normal mesothelial and malignant mesothelioma cell lines exposed or not exposed to several concentration FE fibers. Furthermore, an interactive mesothelioma-based network was derived by using NetME tool. In untreated condition, the expression of miRNAs and tRNA-derived ncRNAs in tumor cells was significantly different with respect to non-tumor samples. Moreover, interesting and significant changes were found after the exposure of both cells lines to FE fibers. The network-based pathway analysis showed several signaling and metabolic pathways potentially involved in the pathogenesis of MPM. From papers analyzed by NetME, it is clear that many miRNAs can positively or negatively influence various pathways involved in MPM. For the first time, the analysis of tRNA-derived ncRNAs molecules in the context of mesothelioma has been made by using in vitro systems. Further studies will be designed to test and validate their diagnostic potential in high-risk individuals' liquid biopsies.

Virus finding tools: current solutions and limitations.

MOTIVATION: The study of the Human Virome remains challenging nowadays. Viral metagenomics, through high-throughput sequencing data, is the best choice for virus discovery. The metagenomics approach is culture-independent and sequence-independent, helping search for either known or novel viruses. Though it is estimated that more than 40% of the viruses found in metagenomics analysis are not recognizable, we decided to analyze several tools to identify and discover viruses in RNA-seq samples. RESULTS: We have analyzed eight Virus Tools for the identification of viruses in RNA-seq data. These tools were compared using a synthetic dataset of 30 viruses and a real one. Our analysis shows that no tool succeeds in recognizing all the viruses in the datasets. So we can conclude that each of these tools has pros and cons, and their choice depends on the application domain. AVAILABILITY: Synthetic data used through the review and raw results of their analysis can be found at https://zenodo.org/record/6426147. FASTQ files of real data can be found in GEO (https://www.ncbi.nlm.nih.gov/gds) or ENA (https://www.ebi.ac.uk/ena/browser/home). Raw results of their analysis can be downloaded from https://zenodo.org/record/6425917.