RIPK4 regulates cell-cell adhesion in epidermal development and homeostasis.

Epidermal development and maintenance are finely regulated events requiring a strict balance between proliferation and differentiation. Alterations in these processes give rise to human disorders such as cancer or syndromes with skin and annexes defects, known as ectodermal dysplasias (EDs). Here, we studied the functional effects of two novel receptor-interacting protein kinase 4 (RIPK4) missense mutations identified in siblings with an autosomal recessive ED with cutaneous syndactyly, palmoplantar hyperkeratosis and orofacial synechiae. Clinical overlap with distinct EDs caused by mutations in transcription factors (i.e. p63 and interferon regulatory factor 6, IRF6) or nectin adhesion molecules was noticed. Impaired activity of the RIPK4 kinase resulted both in altered epithelial differentiation and defective cell adhesion. We showed that mutant RIPK4 resulted in loss of PVRL4/nectin-4 expression in patient epidermis and primary keratinocytes, and demonstrated that PVRL4 is transcriptionally regulated by IRF6, a RIPK4 phosphorylation target. In addition, defective RIPK4 altered desmosome morphology through modulation of plakophilin-1 and desmoplakin. In conclusion, this work implicates RIPK4 kinase function in the p63-IRF6 regulatory loop that controls the proliferation/differentiation switch and cell adhesion, with implications in ectodermal development and cancer.

Identification of therapeutic targets in osteoarthritis by combining heterogeneous transcriptional datasets, drug-induced expression profiles, and known drug-target interactions.

BACKGROUND: Osteoarthritis (OA) is a multifactorial, hypertrophic, and degenerative condition involving the whole joint and affecting a high percentage of middle-aged people. It is due to a combination of factors, although the pivotal mechanisms underlying the disease are still obscure. Moreover, current treatments are still poorly effective, and patients experience a painful and degenerative disease course. METHODS: We used an integrative approach that led us to extract a consensus signature from a meta-analysis of three different OA cohorts. We performed a network-based drug prioritization to detect the most relevant drugs targeting these genes and validated in vitro the most promising candidates. We also proposed a risk score based on a minimal set of genes to predict the OA clinical stage from RNA-Seq data. RESULTS: We derived a consensus signature of 44 genes that we validated on an independent dataset. Using network analysis, we identified Resveratrol, Tenoxicam, Benzbromarone, Pirinixic Acid, and Mesalazine as putative drugs of interest for therapeutics in OA for anti-inflammatory properties. We also derived a list of seven gene-targets validated with functional RT-qPCR assays, confirming the in silico predictions. Finally, we identified a predictive subset of genes composed of DNER, TNFSF11, THBS3, LOXL3, TSPAN2, DYSF, ASPN and HTRA1 to compute the patient's risk score. We validated this risk score on an independent dataset with a high AUC (0.875) and compared it with the same approach computed using the entire consensus signature (AUC 0.922). CONCLUSIONS: The consensus signature highlights crucial mechanisms for disease progression. Moreover, these genes were associated with several candidate drugs that could represent potential innovative therapeutics. Furthermore, the patient's risk scores can be used in clinical settings.

Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine.

Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical data from diagnostic domains such as clinical imaging, pathology, and next-generation sequencing (NGS), which help characterize individual differences in patients. However, this information needs to be available and suitable to promote and support scientific research and technological development, supporting the effective adoption of the precision medicine approach in clinical practice. Digital biobanks can catalyze this process, facilitating the sharing of curated and standardized imaging data, clinical, pathological and molecular data, crucial to enable the development of a comprehensive and personalized data-driven diagnostic approach in disease management and fostering the development of computational predictive models. This work aims to frame this perspective, first by evaluating the state of standardization of individual diagnostic domains and then by identifying challenges and proposing a possible solution towards an integrative approach that can guarantee the suitability of information that can be shared through a digital biobank. Our analysis of the state of the art shows the presence and use of reference standards in biobanks and, generally, digital repositories for each specific domain. Despite this, standardization to guarantee the integration and reproducibility of the numerical descriptors generated by each domain, e.g. radiomic, pathomic and -omic features, is still an open challenge. Based on specific use cases and scenarios, an integration model, based on the JSON format, is proposed that can help address this problem. Ultimately, this work shows how, with specific standardization and promotion efforts, the digital biobank model can become an enabling technology for the comprehensive study of diseases and the effective development of data-driven technologies at the service of precision medicine.

Spinal neuronal activity and neuroinflammatory component in a mouse model of CFA-induced vestibulodynia.

Vestibulodynia is a complex pain disorder characterized by chronic discomfort in the vulvar region, often accompanied by tactile allodynia and spontaneous pain. In patients a depressive behaviour is also observed. In this study, we have used a model of vestibulodynia induced by complete Freund's adjuvant (CFA) focusing our investigation on the spinal cord neurons and microglia. We investigated tactile allodynia, spontaneous pain, and depressive-like behavior as key behavioral markers of vestibulodynia. In addition, we conducted in vivo electrophysiological recordings to provide, for the first time to our knowledge, the characterization of the spinal sacral neuronal activity in the L6-S1 dorsal horn of the spinal cord. Furthermore, we examined microglia activation in the L6-S1 dorsal horn using immunofluorescence, unveiling hypertrophic phenotypes indicative of neuroinflammation in the spinal cord. This represents a novel insight into the role of microglia in vestibulodynia pathology. To address the therapeutic aspect, we employed pharmacological interventions using GABApentin, amitriptyline, and PeaPol. Remarkably, all three drugs, also used in clinic, showed efficacy in alleviating tactile allodynia and depressive-like behavior. Concurrently, we also observed a normalization of the altered neuronal firing and a reduction of microglia hypertrophic phenotypes. In conclusion, our study provides a comprehensive understanding of the CFA-induced model of vestibulodynia, encompassing behavioral, neurophysiological and neuroinflammatory aspects. These data pave the way to investigate spinal cord first pain plasticity in vestibulodynia.

Relationship between default mode network and resting-state electroencephalographic alpha rhythms in cognitively unimpaired seniors and patients with dementia due to Alzheimer's disease.

Here we tested the hypothesis of a relationship between the cortical default mode network (DMN) structural integrity and the resting-state electroencephalographic (rsEEG) rhythms in patients with Alzheimer's disease with dementia (ADD). Clinical and instrumental datasets in 45 ADD patients and 40 normal elderly (Nold) persons originated from the PDWAVES Consortium (www.pdwaves.eu). Individual rsEEG delta, theta, alpha, and fixed beta and gamma bands were considered. Freeware platforms served to derive (1) the (gray matter) volume of the DMN, dorsal attention (DAN), and sensorimotor (SMN) cortical networks and (2) the rsEEG cortical eLORETA source activities. We found a significant positive association between the DMN gray matter volume, the rsEEG alpha source activity estimated in the posterior DMN nodes (parietal and posterior cingulate cortex), and the global cognitive status in the Nold and ADD participants. Compared with the Nold, the ADD group showed lower DMN gray matter, lower rsEEG alpha source activity in those nodes, and lower global cognitive status. This effect was not observed in the DAN and SMN. These results suggest that the DMN structural integrity and the rsEEG alpha source activities in the DMN posterior hubs may be related and predict the global cognitive status in ADD and Nold persons.

Endogenous retroviruses co-opted as divergently transcribed regulatory elements shape the regulatory landscape of embryonic stem cells.

Transposable elements are an abundant source of transcription factor binding sites, and favorable genomic integration may lead to their recruitment by the host genome for gene regulatory functions. However, it is unclear how frequent co-option of transposable elements as regulatory elements is, to which regulatory programs they contribute and how they compare to regulatory elements devoid of transposable elements. Here, we report a transcription initiation-centric, in-depth characterization of the transposon-derived regulatory landscape of mouse embryonic stem cells. We demonstrate that a substantial number of transposable element insertions, in particular endogenous retroviral elements, are associated with open chromatin regions that are divergently transcribed into unstable RNAs in a cell-type specific manner, and that these elements contribute to a sizable proportion of active enhancers and gene promoters. We further show that transposon subfamilies contribute differently and distinctly to the pluripotency regulatory program through their repertoires of transcription factor binding site sequences, shedding light on the formation of regulatory programs and the origins of regulatory elements.

A Comprehensive Analysis of the Structural Recognition between KCTD Proteins and Cullin 3.

KCTD ((K)potassium Channel Tetramerization Domain-containing) proteins constitute an emerging class of proteins involved in fundamental physio-pathological processes. In these proteins, the BTB domain, which represents the defining element of the family, may have the dual role of promoting oligomerization and favoring functionally important partnerships with different interactors. Here, by exploiting the potential of recently developed methodologies for protein structure prediction, we report a comprehensive analysis of the interactions of all KCTD proteins with their most common partner Cullin 3 (Cul3). The data here presented demonstrate the impressive ability of this approach to discriminate between KCTDs that interact with Cul3 and those that do not. Indeed, reliable and stable models of the complexes were only obtained for the 15 members of the family that are known to interact with Cul3. The generation of three-dimensional models for all KCTD-Cul3 complexes provides interesting clues on the determinants of the structural basis of this partnership as clear structural differences emerged between KCTDs that bind or do not bind Cul3. Finally, the availability of accurate three-dimensional models for KCTD-Cul3 interactions may be valuable for the ad hoc design and development of compounds targeting specific KCTDs that are involved in several common diseases.

Familial Dilated Cardiomyopathy: A Novel MED9 Short Isoform Identification.

Familial dilated cardiomyopathy (DCM) is among the leading indications for heart transplantation. DCM alters the transcriptomic profile. The alteration or activation/silencing of physiologically operating transcripts may explain the onset and progression of this pathological state. The mediator complex (MED) plays a fundamental role in the transcription process. The aim of this study is to investigate the MED subunits, which are altered in DCM, to identify target crossroads genes. RNA sequencing allowed us to identify specific MED subunits that are altered during familial DCM, transforming into human myocardial samples. N = 13 MED subunits were upregulated and n = 7 downregulated. MED9 alone was significantly reduced in patients compared to healthy subjects (HS) (FC = -1.257; p < 0.05). Interestingly, we found a short MED9 isoform (MED9s) (ENSG00000141026.6), which was upregulated when compared to the full-transcript isoform (MED9f). Motif identification analysis yielded several significant matches (p < 0.05), such as GATA4, which is downregulated in CHD. Moreover, although the protein-protein interaction network showed FOG2/ZFPM2, FOS and ID2 proteins to be the key interacting partners of GATA4, only FOG2/ZFPM2 overexpression showed an interaction score of "high confidence" ≥ 0.84. A significant change in the MED was observed during HF. For the first time, the MED9 subunit was significantly reduced between familial DCM and HS (p < 0.05), showing an increased MED9s isoform in DCM patients with respect to its full-length transcript. MED9 and GATA4 shared the same sequence motif and were involved in a network with FOG2/ZFPM2, FOS, and ID2, proteins already implicated in cardiac development.

[Italian Cystic Fibrosis Registry (ICFR). Report 2021-2022]. / Registro Italiano Fibrosi Cistica (RIFC). Rapporto 2021-2022.

INTRODUCTION: Italian Cystic Fibrosis Registry (ICFR) collects data of patients with cystic fibrosis (CF) through the collaboration with Italian CF referral and support Centres (Italian law 548/93). It aims at analysing medium and long-term clinical and epidemiological trends, identifying healthcare needs at regional and national levels, contributing to healthcare programmes, and resource allocation. Italian data are also compared at international level through the collaboration with the European CF Registry for sharing epidemiological data on general aspects like CF epidemiology and specific topics such as the use of CFTR modulators. OBJECTIVES: The purpose of this Report is to provide updated demographic and clinical data of the Italian FC population for the years 2021 and 2022, to contribute essential information for the implementation of projects aimed at improving the management of patients affected by this disease. DESIGN: Analyses and results presented in this Report pertain to patients currently under care at Italian National Referral and Support Centres for Cystic Fibrosis and Paediatric Hospital 'Bambino Gesù' in the 2021-2022 period. Data were submitted by clinical Centres through a dedicated web-based software and underwent dual quality control (QC) measures: automated quantitative QC within the software and secondary QC at the European level before the integration into the European Cystic Fibrosis Registry. These measures ensure data completeness, accuracy, and longitudinal consistency with European core data. SETTING AND PARTICIPANTS: A total of 27 CF Centres, including referral and support centres, as well as 'Bambino Gesù' Children's Hospital CF centre, submitted their data to ICFR for the years 2021-2022. Althourgh CF Centres in Verona and Messina do not use the ICFR software, their data are centrally collected and subsequently forwarded to the European Registry. Data from service centres in Treviso and Rovereto are transmitted via the Verona CF Centre. Data from Sardinia Centre are currently unavailable. RESULTS: The results section provides a comprehensive overview of various aspects of CF epidemiology and patient characteristics. 1.Demography: in 2021 and 2022, 5,977 and 6,077 CF patients were respectively included in the ICFR, with median ages of 23.3 and 23.7 years. The prevalence rates were 10.1 and 10.3 per 100,000 residents in Italy for the respective years, with males comprising 51.6% on average. The distribution by age showed a higher frequency among patients aged 7 to 35 years; adult patients constituted 63.5% on average in both years. 2. Diagnosis: most CF patients were diagnosed before the age of two (mean value 57.9%), with a significant percentage diagnosed in adult age (35.4% in 2021 and 25.6% in 2022). 3.New diagnoses: there were 113 new diagnoses in 2021 and 121 in 2022, with estimated incidences of 1 in 9,097 living births in 2021 and 1 in 6,232 in 2022. 4. Genetics: genetic analyses were conducted on 99.9% of patients, revealing CFTR gene mutations in over 98% of cases. The F508del mutation was the most common (44% of alleles in 2021), with 18% of patients having at least one "residual function" mutation. Gating mutations were present in 3.4% of Italian patients, while 20% had at least one-stop codon mutation. 5.Lung function: lung function, measured by percent predicted (pp)FEV1 (Forced Expiratory Volume in the first second) progressively declined before adulthood, with the majority of paediatric patients (92.8% in 2021 and 93.8% in 2022) maintaining a ppFEV1≥70%. 6.Nutrition: critical periods for nutrition were identified as the first 6 months of life and adolescence, with higher prevalence of malnourished male adolescents compared to females. Suboptimal BMI values were more common in adult females (28.7% in 2021 and 26.9% in 2022) compared to males (14.2% in 2021 and 12.6% in 2022). 7. Complications: CF-related liver disease without cirrhosis was prevalent in patients under 18 years (21.9% in 2021 and 21.2 in 2022), while CF-related diabetes was most frequent in adults (24.2%). 8.Transplantation: over the two-year period, 28 patients underwent double-lung transplantation, with median ages of 29.1 in 2021 and 35.3 in 2022, respectively. Median waiting times ranged from 9.4 to 11.6 months. 9.Microbiology: chronic Pseudomonas aeruginosa infection affected 37.2% of adult patients in 2021 and 36.0% in 2022, compared to 7.4% and 6.5% in paediatric patients. Staphylococcus aureus infection rates were 34.6% and 42.2% in 2021 among adults and 34.4% and 36.7% in 2022 among paediatric patients. 10. Mortality: a total of 34 patients died during the 2021-22 period (19 females, 15 males), with median ages at death of 43.7 years in 2021 and 46 years in 2022 (excluding transplanted patients). CONCLUSIONS: The present Report is an update of the data published in the past years and summarizes the main epidemiological and clinical data regarding Italian CF subjects in the years 2021 and 2022. The number of patients registered in 2021 was 5,977, while in 2022 was 6,077. The population coverage estimates for 2022 to be around 97%. In 2020, 60.5% of patients were older than 18 years, in 2022 adult patients account for 63.5% of the Italian CF population. Over the years, therefore, an increase in the median age of Italian CF patients has been observed, reaching 23.7 years in 2022. The absolute number of new diagnoses per year remains substantially unchanged over the years (a total of 234 in the period under review). The median age at diagnosis in 2022 was 2.5 months, 62.6% of subjects are really diagnosed within the first year of life and almost 90% of them are diagnosed through neonatal screening. In 2022, almost all patients underwent genetic analysis (99.9%). Data collected confirm the great variability among Italian CF patients. As regards respiratory function, what is reported in previous reports is here confirmed, with an ever-increasing percentage of subjects under the age of 18 having normal respiratory function, moreover, less than 1% of paediatric patients has a severe lung function (ppFEV1<40). The marked improvement in this indicator in the adult population seems to be mainly due to the introduction from 2021 in Italy of therapy with highly effective CFTR modulators. At the same time, the close positive correlation between nutritional status and respiratory function is confirmed for the adult population. As regards chronic infection by Pseudomonas aeruginosa, in 2022, a reduction in the percentage of chronic infection is observed both among adults (36% vs 38.8% in 2020) and in paediatric patients (6.5% vs 7.6% in 2020). The most frequent complication in both paediatric and adult populations is liver disease (respectively, in 24.2% and 41.3% of subjects). In the two-year period, 34 patients died; their median age at death was between 43 and 46 years (transplant patients excluded); only two patients under the age of 18 died in the period 2021 and 2022, confirming once again that mortality in paediatric age is a rare event. The data presented in this Report shows how the register can be a national and international point of reference for CF patients and the scientific community, a tool for describing the Italian CF population over the years, and a starting point for planning epidemiological studies and clinical studies.

A Magnetic Resonance Imaging-Chemical Exchange Saturation Transfer (MRI-CEST) Method for the Detection of Water Cycling across Cellular Membranes.

Water cycling across the membrane transporters is considered a hallmark of cellular metabolism and it could be of high diagnostic relevance in the characterization of tumors and other diseases. The method relies on the response of intracellular proton exchanging molecules to the presence of extracellular Gd-based contrast agents (GBCAs). Paramagnetic GBCAs enhances the relaxation rate of water molecules in the extracellular compartment and, through membrane exchange, the relaxation enhancement is transferred to intracellular molecules. The effect is detected at the MRI-CEST (Magnetic Resonance Imaging - Chemical Exchange Saturation Transfer) signal of intracellular proton exchanging molecules. The magnitude of the change in the CEST response reports on water cycling across the membrane. The method has been tested on Red Blood Cells and on orthotopic murine models of breast cancer with different degree of malignancy (4T1, TS/A and 168FARN). The distribution of voxels reporting on membrane permeability fits well with the cells' aggressiveness and acts as an early reporter to monitor therapeutic treatments.

Identifying interactions in omics data for clinical biomarker discovery using symbolic regression.

MOTIVATION: The identification of predictive biomarker signatures from omics and multi-omics data for clinical applications is an active area of research. Recent developments in assay technologies and machine learning (ML) methods have led to significant improvements in predictive performance. However, most high-performing ML methods suffer from complex architectures and lack interpretability. RESULTS: We present the application of a novel symbolic-regression-based algorithm, the QLattice, on a selection of clinical omics datasets. This approach generates parsimonious high-performing models that can both predict disease outcomes and reveal putative disease mechanisms, demonstrating the importance of selecting maximally relevant and minimally redundant features in omics-based machine-learning applications. The simplicity and high-predictive power of these biomarker signatures make them attractive tools for high-stakes applications in areas such as primary care, clinical decision-making and patient stratification. AVAILABILITY AND IMPLEMENTATION: The QLattice is available as part of a python package (feyn), which is available at the Python Package Index (https://pypi.org/project/feyn/) and can be installed via pip. The documentation provides guides, tutorials and the API reference (https://docs.abzu.ai/). All code and data used to generate the models and plots discussed in this work can be found in https://github.com/abzu-ai/QLattice-clinical-omics. SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

CRISPR genome surgery in a novel humanized model for autosomal dominant retinitis pigmentosa.

Mutations in rhodopsin (RHO) are the most common causes of autosomal dominant retinitis pigmentosa (adRP), accounting for 20% to 30% of all cases worldwide. However, the high degree of genetic heterogeneity makes development of effective therapies cumbersome. To provide a universal solution to RHO-related adRP, we devised a CRISPR-based, mutation-independent gene ablation and replacement (AR) compound therapy carried by a dual AAV2/8 system. Moreover, we developed a novel hRHOC110R/hRHOWT humanized mouse model to assess the AR treatment in vivo. Results show that this humanized RHO mouse model exhibits progressive rod-cone degeneration that phenocopies hRHOC110R/hRHOWT patients. In vivo transduction of AR AAV8 dual vectors remarkably ablates endogenous RHO expression and overexpresses exogenous WT hRHO. Furthermore, the administration of AR during adulthood significantly hampers photoreceptor degeneration both histologically and functionally for at least 6 months compared with sole gene replacement or surgical trauma control. This study demonstrates the effectiveness of AR treatment of adRP in the human genomic context while revealing the feasibility of its application for other autosomal dominant disorders.

The visual encoding of graspable unfamiliar objects.

We explored by eye-tracking the visual encoding modalities of participants (N = 20) involved in a free-observation task in which three repetitions of ten unfamiliar graspable objects were administered. Then, we analysed the temporal allocation (t = 1500 ms) of visual-spatial attention to objects' manipulation (i.e., the part aimed at grasping the object) and functional (i.e., the part aimed at recognizing the function and identity of the object) areas. Within the first 750 ms, participants tended to shift their gaze on the functional areas while decreasing their attention on the manipulation areas. Then, participants reversed this trend, decreasing their visual-spatial attention to the functional areas while fixing the manipulation areas relatively more. Crucially, the global amount of visual-spatial attention for objects' functional areas significantly decreased as an effect of stimuli repetition while remaining stable for the manipulation areas, thus indicating stimulus familiarity effects. These findings support the action reappraisal theoretical approach, which considers object/tool processing as abilities emerging from semantic, technical/mechanical, and sensorimotor knowledge integration.

Prime Editing Strategy to Install the PRPH2 c.828+1G>A Mutation.

Mutations in peripherin 2 (PRPH2) are associated with a spectrum of inherited retinal diseases (IRDs) including retinitis pigmentosa (RP) and macular degeneration. As PRPH2 is localized to cone and rod outer segments, mutations in PRPH2 lead the disorganization or absence of photoreceptor outer segments. Here, we report on a patient with PRPH2-linked RP who exhibited widespread RPE atrophy with a central area of macular atrophy sparing the fovea. In future studies, we plan to model the pathobiology of PRPH2-based RP using induced pluripotent stem cell (iPSC)-derived retinal organoids. To effectively model rare mutations using iPSC-derived retinal organoids, we first require a strategy that can install the desired mutation in healthy wild-type iPSC, which can efficiently generate well-laminated retinal organoids. In this study, we developed an efficient prime editing strategy for the installation of the pathogenic PRPH2 c.828+1 G>A splice-site mutation underlying our patient's disease.

Generation of an Avian Myeloblastosis Virus (AMV) Reverse Transcriptase Prime Editor.

Prime editing (PE) is a novel, double-strand break (DSB)-independent gene editing technology that represents an exciting avenue for the treatment of inherited retinal diseases (IRDs). Given the extensive and heterogenous nature of the 280 genes associated with IRDs, genome editing has presented countless complications. However, recent advances in genome editing technologies have identified PE to have tremendous potential, with the capability to ameliorate small deletions and insertions in addition to all twelve possible transition and transversion mutations. The current PE system is based on the fusion of the Streptococcus pyogenes Cas9 (SpCas9) nickase H840A mutant and an optimized Moloney murine leukemia virus (MMLV) reverse-transcriptase (RT) in conjunction with a PE guide RNA (pegRNA). In this study, we developed a prime editor based on the avian myeloblastosis virus (AMV)-RT and showed its applicability for the installation of the PRPH2 c.828+1G>A mutation in HEK293 cells.

A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer.

Breast Cancer (BC) is the most common cancer among women worldwide and is characterized by intra- and inter-tumor heterogeneity that strongly contributes towards its poor prognosis. The Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2), and Ki67 antigen are the most examined markers depicting BC heterogeneity and have been shown to have a strong impact on BC prognosis. Radiomics can noninvasively predict BC heterogeneity through the quantitative evaluation of medical images, such as Magnetic Resonance Imaging (MRI), which has become increasingly important in the detection and characterization of BC. However, the lack of comprehensive BC datasets in terms of molecular outcomes and MRI modalities, and the absence of a general methodology to build and compare feature selection approaches and predictive models, limit the routine use of radiomics in the BC clinical practice. In this work, a new radiomic approach based on a two-step feature selection process was proposed to build predictors for ER, PR, HER2, and Ki67 markers. An in-house dataset was used, containing 92 multiparametric MRIs of patients with histologically proven BC and all four relevant biomarkers available. Thousands of radiomic features were extracted from post-contrast and subtracted Dynamic Contrast-Enanched (DCE) MRI images, Apparent Diffusion Coefficient (ADC) maps, and T2-weighted (T2) images. The two-step feature selection approach was used to identify significant radiomic features properly and then to build the final prediction models. They showed remarkable results in terms of F1-score for all the biomarkers: 84%, 63%, 90%, and 72% for ER, HER2, Ki67, and PR, respectively. When possible, the models were validated on the TCGA/TCIA Breast Cancer dataset, returning promising results (F1-score = 88% for the ER+/ER- classification task). The developed approach efficiently characterized BC heterogeneity according to the examined molecular biomarkers.

Role of gut microbiota in neuropathy and neuropathic pain states: A systematic preclinical review.

Gut microbiota has implications in Central Nervous System (CNS) disorders. Our study systematically identified preclinical studies aimed to investigate the possible gut microbiota contribution in neuropathy and neuropathic pain. The systematic review is reported in accordance with PRISMA checklist and guidelines outlined updated to 2020. We included research articles reporting neuropathy-related behavioral evaluations and/or neurological scores coupled to gut microbiota analysis performed by high-throughput technologies in the last ten years. Two investigators performed a search through 3 electronic bibliographic databases for full-text articles (PubMed, Scopus, and EMBASE) and three registries (Prospero, SyRF, and bioRxiv), cross-references, and linear searches. We assessed the methodological quality via the CAMARADES checklist and appraised the heterogeneous body of evidence by narrative synthesis. In total, there were 19 eligible studies. The most of these reports showed significant changes in gut microbiota setting in neuropathy conditions. The major gut microbiome remodeling was through fecal microbiome transplantation. Mechanistic proof of the gut-CNS communication was achieved by measuring inflammatory mediators, metabolic products, or neurotransmitters. As a limitation, we found considerable heterogeneity across eligible studies. We conclude that the current understanding of preclinical findings suggested an association between neuropathy and/or neuropathic pain and gut microbiota modifications. Our analysis provides the basis for further studies targeting microbiota for managing symptoms of neuropathy or other neuroinflammation-based CNS disorders. The systematic review protocol was registered on the international database Prospero under the registration number (257628).

Novel TONSL variants cause SPONASTRIME dysplasia and associate with spontaneous chromosome breaks, defective cell proliferation and apoptosis.

SPONASTRIME dysplasia is an ultrarare spondyloepimetaphyseal dysplasia featuring short stature and short limbs, platyspondyly, depressed nasal bridge with midface hypoplasia and striated metaphyses. In 2019, an autosomal recessive inheritance was demonstrated by the identification of bi-allelic hypomorphic alleles in TONSL. The encoded protein has a critical role in maintaining genome integrity by promoting the homologous recombination required for repairing spontaneous replication-associated DNA lesions at collapsed replication forks. We report a 9-year-old girl with typical SPONASTRIME dysplasia and resulted in carrier of the novel missense p.(Gln430Arg) and p.(Leu1090Arg) variants in TONSL at whole-exome sequencing. In silico analysis predicted that these variants induced thermodynamic changes with a pathogenic impact on protein function. To support the pathogenicity of the identified variants, cytogenetic analysis and microscopy assays showed that patient-derived fibroblasts exhibited spontaneous chromosomal breaks and flow cytometry demonstrated defects in cell proliferation and enhanced apoptosis. These findings contribute to our understanding of the molecular pathogenesis of SPONASTRIME dysplasia and might open the way to novel therapeutic approaches.

Identification of functional pathways and molecular signatures in neuroendocrine neoplasms by multi-omics analysis.

BACKGROUND: Neuroendocrine neoplasms (NENs) represent a heterogeneous class of rare tumors with increasing incidence. They are characterized by the ability to secrete peptide hormones and biogenic amines but other reliable biomarkers are lacking, making diagnosis and identification of the primary site very challenging. While in some NENs, such as the pancreatic ones, next generation sequencing technologies allowed the identification of new molecular hallmarks, our knowledge of the molecular profile of NENs from other anatomical sites is still poor. METHODS: Starting from the concept that NENs from different organs may be clinically and genetically correlated, we applied a multi-omics approach by combining multigene panel testing, CGH-array, transcriptome and miRNome profiling and computational analyses, with the aim to highlight common molecular and functional signatures of gastroenteropancreatic (GEP)-NENs and medullary thyroid carcinomas (MTCs) that could aid diagnosis, prognosis and therapy. RESULTS: By comparing genomic and transcriptional profiles, ATM-dependent signaling emerged among the most significant pathways at multiple levels, involving gene variations and miRNA-mediated regulation, thus representing a novel putative druggable pathway in these cancer types. Moreover, a set of circulating miRNAs was also selected as possible diagnostic/prognostic biomarkers useful for clinical management of NENs. CONCLUSIONS: These findings depict a complex molecular and functional landscape of NENs, shedding light on novel therapeutic targets and disease biomarkers to be exploited.

Evolution of intra-tumoral heterogeneity across different pathological stages in papillary thyroid carcinoma.

BACKGROUND: Intra-tumor heterogeneity (ITH) results from the continuous accumulation of mutations during disease progression, thus impacting patients' clinical outcome. How the ITH evolves across papillary thyroid carcinoma (PTC) different tumor stages is lacking. METHODS: We used the whole-exome sequencing data from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) cohort to track the ITH and assessed its relationship with clinical features through different stages of the PTC progression. We further assayed the expression levels of the specific genes in papillary thyroid cancer cell lines compared to an immortalized normal thyroid epithelial cell line by qRT-PCR. RESULTS: We revealed the timing of mutational processes and the dynamics of the temporal acquisition of somatic events during the lifetime of the PTC. ITH significantly influences the PTC patient's survival rate and, as genetic heterogeneity increases, the prognosis gets worse in advanced tumor stages. ITH also affects the mutational architecture of each clinical stage which is subject to periodic fluctuations. Different mutational processes may cooperate to shape a stage-specific mutational spectrum during the progression from early to advanced tumor stages. Moreover, different evolutionary paths characterize PTC progression across pathological stages due to both mutations recurrently occurring in all stages in hotspot positions and distinct codon changes dominating in different stages. A different expression level of specific genes also exists in different thyroid cancer cell lines. CONCLUSIONS: Our findings suggest ITH as a potential unfavorable prognostic factor in PTC and highlight the dynamic changes in different clinical stages of PTC, providing some clues for the precision medicine and suggesting different diagnostic decisions depending on the clinical stages of patients. Finally, complete clear guidelines to define risk stratification of PTC patients are lacking; thus, this work could contribute to defining patients who need more aggressive treatments and, in turn, could reduce the social burden of this cancer.