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Abstract Background Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled as a binary classification problem for each pair of genes. A statistical classifier is trained to recognize the relationships between the activation profiles of gene pairs. This approach has been proven to outperform previous unsupervised methods. However, the supervised approach raises open questions. In particular, although known regulatory connections can safely be assumed to be positive training examples, obtaining negative examples is not straightforward, because definite knowledge is typically not available that a given pair of genes do not interact. Results A recent advance in research on data mining is a method capable of learning a classifier from only positive and unlabeled examples, that does not need labeled negative examples. Applied to the reconstruction of gene regulatory networks, we show that this method significantly outperforms the current state of the art of machine learning methods. We assess the new method using both simulated and experimental data, and obtain major performance improvement. Conclusions Compared to unsupervised methods for gene network inference, supervised methods are potentially more accurate, but for training they need a complete set of known regulatory connections. A supervised method that can be trained using only positive and unlabeled data, as presented in this paper, is especially beneficial for the task of inferring gene regulatory networks, because only an incomplete set of known regulatory connections is available in public databases such as RegulonDB, TRRD, KEGG, Transfac, and IPA.

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the leading cause of cancer death worldwide. PDACs are characterized by centrosome aberrations, but whether centrosome-related genes influence patient outcomes has not been tested., Methods: Publicly available RNA-sequencing data of patients diagnosed with PDAC were interrogated with unsupervised approaches to identify centrosome protein-encoding genes with prognostic relevance. Candidate genes were validated by immunohistochemistry and multiplex immunofluorescence in a set of clinical PDAC and normal pancreatic tissues., Results: Results showed that two genes CEP250 and CEP170, involved in centrosome linker and centriolar subdistal appendages, were expressed at high levels in PDAC tissues and were correlated with prognosis of PDAC patients in independent databases. Large clustered γ-tubulin-labelled centrosomes were linked together by aberrant circular and planar-shaped CEP250 arrangements in CEP250-high expressing PDACs. Furthermore, PDACs displayed prominent centrosome separation and reduced CEP164-centrosomal labelling associated with acetylated-tubulin staining compared to normal pancreatic tissues. Interestingly, in a small validation cohort, CEP250-high expressing patients had shorter disease free- and overall-survival and almost none of those who received gemcitabine plus nab-paclitaxel first-line therapy achieved a clinical response. In contrast, weak CEP250 expression was associated with long-term survivors or responses to medical treatments., Conclusions: Alteration of the centriolar cohesion and appendages has effect on the survival of patients with PDAC., (Copyright © 2024 IAP and EPC. Published by Elsevier B.V. All rights reserved.)

Combining exercise with fasting is known to boost fat mass-loss, but detailed analysis on the consequential mobilization of visceral and subcutaneous WAT-derived fatty acids has not been performed. In this study, a subset of fasted male rats (66 h) was submitted to daily bouts of mild exercise. Subsequently, by using gas chromatography-flame ionization detection, the content of 22 fatty acids (FA) in visceral (v) versus subcutaneous (sc) white adipose tissue (WAT) depots was compared to those found in response to the separate events. Findings were related to those obtained in serum and liver samples, the latter taking up FA to increase gluconeogenesis and ketogenesis. Each separate intervention reduced scWAT FA content, associated with increased levels of adipose triglyceride lipase (ATGL) protein despite unaltered AMP-activated protein kinase (AMPK) Thr172 phosphorylation, known to induce ATGL expression. The mobility of FAs from vWAT during fasting was absent with the exception of the MUFA 16:1 n-7 and only induced by combining fasting with exercise which was accompanied with reduced hormone sensitive lipase (HSL) Ser563 and increased Ser565 phosphorylation, whereas ATGL protein levels were elevated during fasting in association with the persistently increased phosphorylation of AMPK at Thr172 both during fasting and in response to the combined intervention. As expected, liver FA content increased during fasting, and was not further affected by exercise, despite additional FA release from vWAT in this condition, underlining increased hepatic FA metabolism. Both fasting and its combination with exercise showed preferential hepatic metabolism of the prominent saturated FAs C:16 and C:18 compared to the unsaturated FAs 18:1 n-9 and 18:2 n-6:1. In conclusion, depot-specific differences in WAT fatty acid molecule release during fasting, irrelevant to their degree of saturation or chain length, are mitigated when combined with exercise, to provide fuel to surrounding organs such as the liver which is correlated with increased ATGL/ HSL ratios, involving AMPK only in vWAT.

Motivation: The process of drug development is inherently complex, marked by extended intervals from the inception of a pharmaceutical agent to its eventual launch in the market. Additionally, each phase in this process is associated with a significant failure rate, amplifying the inherent challenges of this task. Computational virtual screening powered by machine learning algorithms has emerged as a promising approach for predicting therapeutic efficacy. However, the complex relationships between the features learned by these algorithms can be challenging to decipher., Results: We have engineered an artificial neural network model designed specifically for predicting drug sensitivity. This model utilizes a biologically informed visible neural network, thereby enhancing its interpretability. The trained model allows for an in-depth exploration of the biological pathways integral to prediction and the chemical attributes of drugs that impact sensitivity. Our model harnesses multiomics data derived from a different tumor tissue sources, as well as molecular descriptors that encapsulate the properties of drugs. We extended the model to predict drug synergy, resulting in favorable outcomes while retaining interpretability. Given the imbalanced nature of publicly available drug screening datasets, our model demonstrated superior performance to state-of-the-art visible machine learning algorithms., Availability and Implementation: MOViDA is implemented in Python using PyTorch library and freely available for download at https://github.com/Luigi-Ferraro/MOViDA. Training data, RIS score and drug features are archived on Zenodo https://doi.org/10.5281/zenodo.8180380., (© The Author(s) 2023. Published by Oxford University Press.)

A rhabdoid colorectal tumor (RCT) is a rare cancer with aggressive clinical behavior. Recently, it has been recognized as a distinct disease entity, characterized by genetic alterations in the SMARCB1 and Ciliary Rootlet Coiled-Coil ( CROCC ). We here investigate the genetic and immunophenotypic profiling of 21 RCTs using immunohistochemistry and next-generation sequencing. Mismatch repair-deficient phenotypes were identified in 60% of RCTs. Similarly, a large proportion of cancers exhibited the combined marker phenotype (CK7-/CK20-/CDX2-) not common to classical adenocarcinoma variants. More than 70% of cases displayed aberrant activation of the mitogen-activated protein kinase (MAPK) pathway with mutations prevalently in BRAF V600E. SMARCB1/INI1 expression was normal in a large majority of lesions. In contrast, ciliogenic markers including CROCC and γ-tubulin were globally altered in tumors. Notably, CROCC and γ-tubulin were observed to colocalize in large cilia found on cancer tissues but not in normal controls. Taken together, our findings indicate that primary ciliogenesis and MAPK pathway activation contribute to the aggressiveness of RCTs and, therefore, may constitute a novel therapeutic target.

Ribonucleoprotein (RNP) condensates are crucial for controlling RNA metabolism and splicing events in animal cells. We used spatial proteomics and transcriptomic to elucidate RNP interaction networks at the centrosome, the main microtubule-organizing center in animal cells. We found a number of cell-type specific centrosome-associated spliceosome interactions localized in subcellular structures involved in nuclear division and ciliogenesis. A component of the nuclear spliceosome BUD31 was validated as an interactor of the centriolar satellite protein OFD1. Analysis of normal and disease cohorts identified the cholangiocarcinoma as target of centrosome-associated spliceosome alterations. Multiplexed single-cell fluorescent microscopy for the centriole linker CEP250 and spliceosome components including BCAS2, BUD31, SRSF2 and DHX35 recapitulated bioinformatic predictions on the centrosome-associated spliceosome components tissue-type specific composition. Collectively, centrosomes and cilia act as anchor for cell-type specific spliceosome components, and provide a helpful reference for explore cytoplasmic condensates functions in defining cell identity and in the origin of rare diseases., Competing Interests: The authors declare no competing interests., (© 2023 The Author(s).)

In addition to being novel biomarkers for poor cancer prognosis, members of Lymphocyte antigen-6 (Ly6) gene family also play a crucial role in avoiding immune responses to tumors. However, it has not been possible to identify the underlying mechanism of how Ly6 gene regulation operates in human cancers. Transcriptome, epigenome and proteomic data from independent cancer databases were analyzed in silico and validated independently in 334 colorectal cancer tissues (CRC). RNA mediated gene silencing of regulatory genes, and treatment with MEK and p38 MAPK inhibitors were also tested in vitro. We report here that the Lymphocyte antigen 6G6D is universally downregulated in mucinous CRC, while its activation progresses through the classical adenoma-carcinoma sequence. The DNA methylation changes in LY6G6D promoter are intimately related to its transcript regulation, epigenomic and histological subtypes. Depletion of DNA methyltransferase 1 (DNMT1), which maintains DNA methylation, results in the derepression of LY6G6D expression. RNA-mediated gene silencing of p38α MAPK or its selective chemical inhibition, however, reduces LY6G6D expression, reducing trametinib's anti-inflammatory effects. Patients treated with FOLFOX-based first-line therapy experienced decreased survival due to hypermethylation of the LY6G6D promoter and decreased p38α MAPK signaling. We found that cancer-specific immunodominant epitopes are controlled by p38α MAPKs signaling and suppressed by DNA methylation in histological variants with Mucinous differentiation. This work provides a promising prospective for clinical application in diagnosis and personalized therapeutic strategies of colorectal cancer., (© 2022. The Author(s).)

Gene-set enrichment analysis is the key methodology for obtaining biological information from transcriptomic space's statistical result. Since its introduction, Gene-set Enrichment analysis methods have obtained more reliable results and a wider range of application. Great attention has been devoted to global tests, in contrast to competitive methods that have been largely ignored, although they appear more flexible because they are independent from the source of gene-profiles. We analyzed the properties of the Mann-Whitney-Wilcoxon test, a competitive method, and adapted its interpretation in the context of enrichment analysis by introducing a Normalized Enrichment Score that summarize two interpretations: a probability estimate and a location index. Two implementations are presented and compared with relevant literature methods: an R package and an online web tool. Both allow for obtaining tabular and graphical results with attention to reproducible research.

Brain-derived neurotrophic factor (BDNF) plays a pivotal role in neuronal growth and differentiation, neuronal plasticity, learning, and memory. Using CRISPR/Cas9 technology, we generated a vital Bdnf null mutant line in zebrafish and carried out its molecular and behavioral characterization. Although no defects are evident on a morphological inspection, 66% of coding genes and 37% of microRNAs turned out to be differentially expressed in bdnf -/- compared with wild type sibling embryos. We deeply investigated the circadian clock pathway and confirmed changes in the rhythmic expression of clock ( arntl1a , clock1a and clock2 ) and clock-controlled ( aanat2 ) genes. The modulatory role of Bdnf on the zebrafish circadian clock was then validated by behavioral tests highlighting the absence of circadian activity rhythms in bdnf -/- larvae. The circadian behavior was partially rescued by pharmacological treatment. The bdnf -/- zebrafish line presented here is the first valuable and stable vertebrate model for the study of BDNF-related neurodevelopmental diseases., Competing Interests: The authors declare no competing interests., (© 2022 The Authors.)

It is currently unknown how many RNA transcripts are able to induce degradation of microRNAs (miRNA) via the mechanism known as target-directed miRNA degradation (TDMD). We developed TDMDfinder, a computational pipeline that identifies 'high confidence' TDMD interactions in the Human and Mouse transcriptomes by combining sequence alignment and feature selection approaches. Our predictions suggested that TDMD is widespread, with potentially every miRNA controlled by endogenous targets. We experimentally tested 37 TDMDfinder predictions, of which 17 showed TDMD effects as measured by RT-qPCR and small RNA sequencing, linking the miR-17, miR-19, miR-30, miR-221, miR-26 and miR-23 families to novel endogenous TDMDs. In some cases, TDMD was found to affect different members of the same miRNA family selectively. Features like complementarity to the miRNA 3' region, bulge size and hybridization energy appeared to be the main factors determining sensitivity. Computational analyses performed using the multiomic TCGA platform substantiated the involvement of many TDMD transcripts in human cancer and highlighted 36 highly significant interactions, suggesting TDMD as a new potential oncogenic mechanism. In conclusion, TDMDfinder provides the first inventory of bona fide human and mouse TDMDs. Available as a free webtool, TDMDfinder allows users to search for any TDMD interaction of interest by customizing its selection criteria., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Motivation: The cost of drug development has dramatically increased in the last decades, with the number new drugs approved per billion US dollars spent on R&D halving every year or less. The selection and prioritization of targets is one the most influential decisions in drug discovery. Here we present a Gaussian Process model for the prioritization of drug targets cast as a problem of learning with only positive and unlabeled examples., Results: Since the absence of negative samples does not allow standard methods for automatic selection of hyperparameters, we propose a novel approach for hyperparameter selection of the kernel in One Class Gaussian Processes. We compare our methods with state-of-the-art approaches on benchmark datasets and then show its application to druggability prediction of oncology drugs. Our score reaches an AUC 0.90 on a set of clinical trial targets starting from a small training set of 102 validated oncology targets. Our score recovers the majority of known drug targets and can be used to identify novel set of proteins as drug target candidates., Availability and Implementation: The matrix of features for each protein is available at: https://bit.ly/3iLgZTa. Source code implemented in Python is freely available for download at https://github.com/AntonioDeFalco/Adaptive-OCGP., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Metastasis is a process by which cancer cells escape from the location of the primary tumor invading normal tissues at distant organs. Chromosomal instability (CIN) is a hallmark of human cancer, associated with metastasis and therapeutic resistance. The centrosome plays a major role in organizing the microtubule cytoskeleton in animal cells regulating cellular architecture and cell division. Loss of centrosome integrity activates the p38-p53-p21 pathway, which results in cell-cycle arrest or senescence and acts as a cell-cycle checkpoint pathway. Structural and numerical centrosome abnormalities can lead to aneuploidy and CIN. New findings derived from studies on cancer and rare genetic disorders suggest that centrosome dysfunction alters the cellular microenvironment through Rho GTPases, p38, and JNK (c-Jun N-terminal Kinase)-dependent signaling in a way that is favorable for pro-invasive secretory phenotypes and aneuploidy tolerance. We here review recent data on how centrosomes act as complex molecular platforms for Rho GTPases and p38 MAPK (Mitogen activated kinase) signaling at the crossroads of CIN, cytoskeleton remodeling, and immune evasion via both cell-autonomous and non-autonomous mechanisms.

The stratification of patients at risk of progression of COVID-19 and their molecular characterization is of extreme importance to optimize treatment and to identify therapeutic options. The bioinformatics community has responded to the outbreak emergency with a set of tools and resource to identify biomarkers and drug targets that we review here. Starting from a consolidated corpus of 27 570 papers, we adopt latent Dirichlet analysis to extract relevant topics and select those associated with computational methods for biomarker identification and drug repurposing. The selected topics span from machine learning and artificial intelligence for disease characterization to vaccine development and to therapeutic target identification. Although the way to go for the ultimate defeat of the pandemic is still long, the amount of knowledge, data and tools generated so far constitutes an unprecedented example of global cooperation to this threat., (© The Author(s) 2020. Published by Oxford University Press.)

Background: Breast carcinoma with extensive peritumoral vascular invasion (ePVI-BC) is a cancer with massive vascular invasion (>10) detected in more than one slide. This neoplasm shows clinic-pathological affinity with inflammatory breast carcinoma (IBC). In this paper we evaluate their biological relationship through the study of surrogate markers (β-catenin and NFAT5) of Canonical (cWnt) and non-canonical (nWnt) Wnt pathways activation., Methods: By immunoistochemistry, we investigate β-catenin and NFAT5 in 39 IBC, 74 ePVI-BC and 84 control cases (CG-BC)., Results: cWnt was activated in 100 % of ePVI-BC, in 64 % of IBC and 10 % of CG-BC. nWnt was activated in 20 % of ePVI-BC, 50 % of IBC and 1% of CG-BC. The prognosis of carcinomas with nWnt activated was poor similar to IBC. The statistical analysis evidences as both the pathways are synergistic in malignant progression and survival time. β-catenin show an important association with prognostic factors and NFAT5 shows a relevant prognostic role on OS (p = 1.5*10 -6 ) and DFS (P = 1,2*10 -4 ). nWnt is associated with a worse prognosis independently of cWnt. cWnt is associated with adverse prognosis (DFS p = 0.0469; OS p = 0.004891) but its prognostic role is indifferent in carcinoma with nWnt activated., Conclusions: Canonical Wnt pathway is involved in malignant progression with dominant role for vascular invasion whereas non canonical Wnt pathway plays an important role on survival time including the capacity to identify carcinomas with IBC-like prognosis. Furthermore ePVI may represent a "prodromal form of IBC" as demonstrated by its clinicopathological and biological similarity with IBC., (Copyright © 2021. Published by Elsevier GmbH.)

Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many biological processes and diseases. The lack of a complete comprehension of their biological functionality, especially in a genome-wide scenario, has demanded new computational approaches to annotate their roles. It is widely known that secondary structure is determinant to know RNA function and machine learning based approaches have been successfully proven to predict RNA function from secondary structure information. Here we show that RNA function can be predicted with good accuracy from a lightweight representation of sequence information without the necessity of computing secondary structure features which is computationally expensive. This finding appears to go against the dogma of secondary structure being a key determinant of function in RNA. Compared to recent secondary structure based methods, the proposed solution is more robust to sequence boundary noise and reduces drastically the computational cost allowing for large data volume annotations. Scripts and datasets to reproduce the results of experiments proposed in this study are available at: https://github.com/bioinformatics-sannio/ncrna-deep., Competing Interests: The authors have declared that no competing interests exist.

Background: Single-cell RNA sequencing is the reference technique for characterizing the heterogeneity of the tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is of fundamental importance for the identification of immuno-oncology therapeutic targets., Results: We present a novel method, single-cell Tumor-Host Interaction tool (scTHI), to identify significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand-receptor interactions in glioma using 6 publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma., Conclusions: Our results provide a complete map of the active tumor-host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumor., (© The Author(s) 2020. Published by Oxford University Press GigaScience.)

Background: Glioblastoma (GBM) is a complex disease with extensive molecular and transcriptional heterogeneity. GBM can be subcategorized into four distinct subtypes; tumors that shift towards the mesenchymal phenotype upon recurrence are generally associated with treatment resistance, unfavorable prognosis, and the infiltration of pro-tumorigenic macrophages., Results: We explore the transcriptional regulatory networks of mesenchymal-associated tumor-associated macrophages (MA-TAMs), which drive the malignant phenotypic state of GBM, and identify macrophage receptor with collagenous structure (MARCO) as the most highly differentially expressed gene. MARCO high TAMs induce a phenotypic shift towards mesenchymal cellular state of glioma stem cells, promoting both invasive and proliferative activities, as well as therapeutic resistance to irradiation. MARCO high TAMs also significantly accelerate tumor engraftment and growth in vivo. Moreover, both MA-TAM master regulators and their target genes are significantly correlated with poor clinical outcomes and are often associated with genomic aberrations in neurofibromin 1 (NF1) and phosphoinositide 3-kinases/mammalian target of rapamycin/Akt pathway (PI3K-mTOR-AKT)-related genes. We further demonstrate the origination of MA-TAMs from peripheral blood, as well as their potential association with tumor-induced polarization states and immunosuppressive environments., Conclusions: Collectively, our study characterizes the global transcriptional profile of TAMs driving mesenchymal GBM pathogenesis, providing potential therapeutic targets for improving the effectiveness of GBM immunotherapy.

Embryonic stem cells (ESCs) are derived from inner cell mass (ICM) of the blastocyst. In serum/LIF culture condition, they show variable expression of pluripotency genes that mark cell fluctuation between pluripotency and differentiation metastate. The ESCs subpopulation marked by zygotic genome activation gene (ZGA) signature, including Zscan4 , retains a wider differentiation potency than epiblast-derived ESCs. We have recently shown that retinoic acid (RA) significantly enhances Zscan4 cell population. However, it remains unexplored how RA initiates the ESCs to 2-cell like reprogramming. Here we found that RA is decisive for ESCs to 2C-like cell transition, and reconstructed the gene network surrounding Zscan4 . We revealed that RA regulates 2C-like population co-activating Dux and Duxbl1 . We provided novel evidence that RA dependent ESCs to 2C-like cell transition is regulated by Dux , and antagonized by Duxbl1 . Our suggested mechanism could shed light on the role of RA on ESC reprogramming., (Copyright © 2020 Tagliaferri, Mazzone, Noviello, Addeo, Angrisano, Del Vecchio, Visconte, Ruggieri, Russi, Caivano, Cantone, De Felice, Ceccarelli, Cerulo and Falco.)

Chronic myeloid leukemia (CML) is a stem cell derived malignant disorder result of translocation t(9;22)(q34;q11) called Philadelphia chromosome (Ph + ). microRNAS (miRNAs) are involved in several biological processes, altering the progression of various pathologies, including CML. This study evaluated whether circulating miRNAs display differential expression profiles in peripheral blood of CML-Chronic Phase (CML-CP) patients newly diagnosed in comparison with CML-CP treated with imatinib. We obtained peripheral blood samples from CML-CP Ph + patients divided among group 1 (untreated newly diagnosed) and group 2 (treated with imatinib). A pool of total leukocytes from healthy donors was considered as control group. Expression analyses were performed for 768 miRNAs by RT-qPCR array. Bioinformatic tools were used to identify significant pathways and interaction networks. We found 80 deregulated miRNAs between the groups and, according to bioinformatic analysis, they are involved in different pathways, including molecular mechanisms of cancer. The study allows better understanding of disease molecular behavior, and it is useful for possible monitoring CML treatment and prognostic biomarkers identification.