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Methods for Master Regulator Analysis

Therapeutic checkpoint antibodies blocking programmed death receptor 1/programmed death ligand 1 (PD-L1) signaling have radically improved clinical outcomes in cancer. However, the regulation of PD-L1 expression on tumor cells is still poorly understood. Here we show that intratumoral copper levels influence PD-L1 expression in cancer cells. Deep analysis of the The Cancer Genome Atlas database and tissue microarrays showed strong correlation between the major copper influx transporter copper transporter 1 (CTR-1) and PD-L1 expression across many cancers but not in corresponding normal tissues. Copper supplementation enhanced PD-L1 expression at mRNA and protein levels in cancer cells and RNA sequencing revealed that copper regulates key signaling pathways mediating PD-L1–driven cancer immune evasion. Conversely, copper chelators inhibited phosphorylation of STAT3 and EGFR and promoted ubiquitin-mediated degradation of PD-L1. Copper-chelating drugs also significantly increased the number of tumor-infiltrating CD8+ T and natural killer cells, slowed tumor growth, and improved mouse survival. Overall, this study reveals an important role for copper in regulating PD-L1 and suggests that anticancer immunotherapy might be enhanced by pharmacologically reducing intratumor copper levels.Significance:These findings characterize the role of copper in modulating PD-L1 expression and contributing to cancer immune evasion, highlighting the potential for repurposing copper chelators as enhancers of antitumor immunity.

DC increases tumor-infiltrating immune cells in Th-MYCN mice

Vascularized fibular autografts (VFA) are used in the oncologic skeletal reconstructions of long bones, alone or combined with massive bone allografts (MBA). Data regarding the role of imaging in assessing these complex skeletal reconstructions are lacking, and have mainly focused on Computed Tomography (CT). Our aim was to evaluate if early conventional radiography (CR) findings are correlated with the outcome of these skeletal reconstructions.All consecutive patients who underwent oncologic resection of lower limbs long bones followed by VFA reconstruction were included in this single-center retrospective study. We compared the CR obtained immediately after surgery with the CR at the 6-month control, as well as the CR at 6 months with the CT at 6 months when available. The following scores were assigned to the VFA: 0 (unchanged), 1 (osteopenia-cortical bone thinning), 2 (increase in bone density-cortical thickening). We then investigated whether this score correlated with the implant outcome within 12 months (optimal integration, suboptimal integration, integration requiring further surgery or lack of integration) using Kaplan-Meier and Cox regression analyses, considering the occurrence of integration and the duration time before the surgical removal of the whole bone reconstruction.Forty-five patients were included (32 men [71.1%], mean age 14.6 years), 26 affected by osteosarcoma, 14 by Ewing sarcoma, 3 by adamantinoma and 2 operated for the failure of previous reconstructions for bone sarcoma. VFA changes on 6-month CR were significantly associated with optimal integration of the implants (log-rank P = 0.0137, multivariate Hazard ratio = 7.62, 95% confidence interval = 1.13-51.25). None of the other clinical and surgical features were associated with the implant outcome. The findings on 6-month CR and CT follow-up were not significantly different. CT at 6 months was available in 36 patients (80.0%).The assessment of VFA morphological changes on CR performed at 6 months can predict the outcome of the skeletal implant. This data should be considered for clinical decision-making, selecting patients requiring additional images (CT), and possible subsequent revision surgical procedures.

The Monkeypox virus is the etiological cause of a recent multi-country outbreak, with nearly one hundred distinct cases detected outside the endemic areas of Africa in May 2022. In this article, we analyze the sequences of two full genomes of Monkeypox virus from Portugal and Belgium, and compare them with all available Monkeypox sequences, annotated by year and geographic origin, as well as related Cowpox and Variola (smallpox) virus sequences. Our results show that the recent outbreak is most likely originating from the West African clade of Monkeypox, with >99% sequence identity with sequences derived from historical and recent cases, dating from 1971 to 2017. We analyze specific mutations occurring in viral proteins A42R (for which a crystal structure is available) and H3L (an important epitope in host immune recognition), highlighting specific amino acids varying between the current outbreak, previous Monkeypox and Cowpox sequences and the historical Variola virus. Genome-wide sequence analysis of the recent outbreak and other monkeypox/cowpox/variola viruses shows a very high conservation, with 97.9% (protein-based) and 97.8% (nucleotide-based) sequence identity.

The Metabolome and Transcriptome are mutually communicating within cancer cells, and this interplay is translated into the existence of quantifiable correlation structures between gene expression and metabolite abundance levels. Studying these correlations could provide a novel venue of understanding cancer and the discovery of novel biomarkers and pharmacological strategies, as well as laying the foundation for the prediction of metabolite quantities by leveraging information from the more widespread transcriptomics data. In the current paper, we investigate the correlation between gene expression and metabolite levels in the Cancer Cell Line Encyclopedia dataset, building a direct correlation network between the two molecular ensembles. We show that a metabolite/transcript correlation network can be used to predict metabolite levels in different samples and datasets, such as the NCI-60 cancer cell line dataset, both on a sample-by-sample basis and in differential contrasts. We also show that metabolite levels can be predicted in principle on any sample and dataset for which transcriptomics data are available, such as the Cancer Genome Atlas (TCGA).

Background: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research and as targets for the development of anticancer agents. So far, very few attempts have been made to characterize the surfaceome of patients with breast cancer, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed ‘SURFACER’. Methods: Gene expression data from GTEx were used to build a normal breast network model as input to infer differential cell-surface proteins activity in BRCA tissue samples retrieved from TCGA versus normal samples. Data were stratified according to the PAM50 transcriptional subtypes (Luminal A, Luminal B, HER2 and Basal), while unsupervised clustering techniques were applied to define BRCA subtypes according to cell-surface proteins activity. Results: Our approach led to the identification of 213 PAM50 subtypes-specific deregulated surface genes and the definition of five BRCA subtypes, whose prognostic value was assessed by survival analysis, identifying a cell-surface activity configuration at increased risk. The value of the SURFACER method in BRCA genotyping was tested by evaluating the performance of 11 different machine learning classification algorithms. Conclusions: BRCA patients can be stratified into five surface activity-specific groups having the potential to identify subtype-specific actionable targets to design tailored targeted therapies or for diagnostic purposes. SURFACER-defined subtypes show also a prognostic value, identifying surface-activity profiles at higher risk.

Objective: The aim of this study was to review the existence and types of correlations between body composition densitometric parameters and laboratory values associated to cardiometabolic risk. Methods: We retrospectively analyzed data from 316 individuals in the weight range from normality to super-obesity, submitted to total body dual-energy x-ray absorptiometry (DXA) scans and routine biochemistry at S.Orsola-Malpighi Hospital from June 2010 to March 2014. The study included 182 women, 45.8 ± 13.4 y of age, with a body mass index (BMI) of 31.5 (± 11) kg/m2 (group F) and 134 men, 45.4 ± 13.6 y of age, with a BMI of 27.6 (± 7.8) kg/m2 (group M). All patients underwent whole-body scan (Lunar iDXA, GE Healthcare, Madison, WI, USA) and laboratory analysis (blood fasting glucose, total cholesterol, high-density lipoprotein cholesterol, tricylglycerides [TGs], aspartate aminotransferase, and alanine aminotransferase). Correlation between laboratory values and total body and regional fat mass (including visceral adipose tissue [VAT] and subcutaneous adipose tissue in the android region), and lean mass parameters were analyzed with linear and stepwise regressions analysis (significance limit, P < 0.05). Receiver operating characteristic curves were performed to assess the accuracy of the best-fit DXA parameter (VAT) to identify at least one laboratory risk factor. Results: In both groups, BMI and densitometric parameters showed a linear correlation with fasting blood glucose and TG levels and an inverse correlation with high-density lipoprotein cholesterol (P < 0.05), whereas no correlation was observed with total cholesterol levels. The only densitometric parameter retained in the final model of stepwise multiple regression was VAT for fasting blood glucose (group F: β = 0.4627, P < 0.0001; group M: β = 0.6221, P < 0.0001) and TG levels (group F: β = 0.4931, P < 0.0001; group M: β = 0.1990, P < 0.0261) independently of BMI. The optimal cutoff points of VAT to identify the presence of at least one laboratory risk factor were >1395 g and >1479 cm3 for men and >1281 g and >1357 cm3 for women. Conclusions: DXA analysis of VAT is associated with selected laboratory parameters used for the evaluation of cardiometabolic risk and could be per se a helpful parameter in the assessment of clinical risk.

Objectives The aim of this work was to examine the cross-sectional relationship between body composition (BC) markers for adipose and lean tissue and bone mass, and a wide range of specific inflammatory and adipose-related markers in healthy elderly Europeans. Methods A whole-body dual-energy X-ray absorptiometry (DXA) scan was made in 1121 healthy (65–79 years) women and men from five European countries of the “New dietary strategies addressing the specific needs of elderly population for a healthy aging in Europe” project (NCT01754012) cohort to measure markers of adipose and lean tissue and bone mass. Pro-inflammatory (IL-6, IL-6Rα, TNF-α, TNF-R1, TNF-R2, pentraxin 3, CRP, alpha-1-acid glycoprotein, albumin) and anti-inflammatory (IL-10, TGF-β1) molecules as well as adipose-related markers such as leptin, adiponectin, ghrelin, and resistin were measured by magnetic bead-based multiplex-specific immunoassays and biochemical assays. Results BC characteristics were different in elderly women and men, and more favorable BC markers were associated with a better adipose-related inflammatory profile, with the exception of skeletal muscle mass index. No correlation was found with the body composition markers and circulating levels of some standard pro- and anti-inflammatory markers like IL-6, pentraxin 3, IL-10, TGF-β1, TNF-α, IL-6Rα, glycoprotein 130, TNF-α-R1, and TNF-α-R2. Conclusions The association between BC and inflammatory and adipose-related biomarkers is crucial in decoding aging and pathophysiological processes, such as sarcopenia. DXA can help in understanding how the measurement of fat and muscle is important, making the way from research to clinical practice. Key Points • Body composition markers concordantly associated positively or negatively with adipose-related and inflammatory markers, with the exception of skeletal muscle mass index. • No correlation was found with the body composition markers and circulating levels of some standard pro- and anti-inflammatory markers like IL-6, pentraxin 3, IL-10, TGF-β1, TNF-α, IL-6Rα, gp130, TNF-α-R1, and TNF-α-R2. • Skeletal muscle mass index (SMI) shows a good correlation with inflammatory profile in age-related sarcopenia. Electronic supplementary material The online version of this article (10.1007/s00330-018-5973-2) contains supplementary material, which is available to authorized users.

The global crisis of opioid overdose fatalities has led to an urgent search to discover the neurobiological mechanisms of opioid use disorder (OUD). A driving force for OUD is the dysphoric and emotionally painful state (hyperkatifeia) that is produced during acute and protracted opioid withdrawal. Here, we explored a mechanistic role for extrahypothalamic stress systems in driving opioid addiction. We found that glucocorticoid receptor (GR) antagonism with mifepristone reduced opioid addiction-like behaviors in rats and zebrafish of both sexes and decreased the firing of corticotropin-releasing factor neurons in the rat amygdala (i.e., a marker of brain stress system activation). In support of the hypothesized role of glucocorticoid transcriptional regulation of extrahypothalamic GRs in addiction-like behavior, an intra-amygdala infusion of an antisense oligonucleotide that blocked GR transcriptional activity reduced addiction-like behaviors. Finally, we identified transcriptional adaptations of GR signaling in the amygdala of humans with OUD. Thus, GRs, their coregulators, and downstream systems may represent viable therapeutic targets to treat the "stress side" of OUD.

MotivationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease, 2019; COVID-19) is associated with adverse outcomes in patients. It has been observed that lethality seems to be related to the age of patients. Moreover, it has been demonstrated that ageing causes some modifications at a molecular level.ObjectiveThe study aims to shed out light on a possible link between the increased COVID-19 lethality and the molecular changes that occur in elderly people.MethodsWe considered public datasets on ageing-related genes and their expression at tissue level. We selected interactors that are known to be related to ageing process. Then, we performed a network-based analysis to identify interactors significantly related to both SARS-CoV-2 and ageing. Finally, we investigated changes on the expression level of coding genes at tissue, gender and age level.ResultsWe observed a significant intersection between some SARS-CoV-2 interactors and ageing-related genes suggesting that those genes are particularly affected by COVID-19 infection. Our analysis evidenced that virus infection particularly affects ageing molecular mechanisms centred around proteins EEF2, NPM1, HMGA1, HMGA2, APEX1, CHEK1, PRKDC, and GPX4. We found that HMGA1, and NPM1 have a different expression in lung of males, while HMGA1, APEX1, CHEK1, EEF2, and NPM1 present changes in expression in males due to aging effects.ConclusionOur study generated a mechanistic framework to explaining the correlation between COVID-19 incidence in elderly patients and molecular mechanisms of ageing. This will provide testable hypotheses for future investigation and pharmacological solutions tailored on specific age ranges.

Several SARS-CoV-2 variants have emerged, posing a renewed threat to COVID-19 containment and to vaccine and drug efficacy. In this study, we analyzed more than 1,000,000 SARS-CoV-2 genomic sequences deposited up to April 27, 2021 on the GISAID public repository, and identified a novel T478K mutation located on the SARS-CoV-2 Spike protein. The mutation is structurally located in the region of interaction with human receptor ACE2 and was detected in 11,435 distinct cases. We show that T478K has appeared and risen in frequency since January 2021, predominantly in Mexico and USA, but we could also detect it in several European countries.

SARS-CoV-2 entry in human cells is mediated by the interaction between the viral Spike protein and the human ACE2 receptor. This mechanism evolved from the ancestor bat coronavirus and is currently one of the main targets for antiviral strategies. However, there currently exist several Spike protein variants in the SARS-CoV-2 population as the result of mutations, and it is unclear if these variants may exert a specific effect on the affinity with ACE2 which, in turn, is also characterized by multiple alleles in the human population. In the current study, the GBPM analysis, originally developed for highlighting host-guest interaction features, has been applied to define the key amino acids responsible for the Spike/ACE2 molecular recognition, using four different crystallographic structures. Then, we intersected these structural results with the current mutational status, based on more than 295,000 sequenced cases, in the SARS-CoV-2 population. We identified several Spike mutations interacting with ACE2 and mutated in at least 20 distinct patients: S477N, N439K, N501Y, Y453F, E484K, K417N, S477I and G476S. Among these, mutation N501Y in particular is one of the events characterizing SARS-CoV-2 lineage B.1.1.7, which has recently risen in frequency in Europe. We also identified five ACE2 rare variants that may affect interaction with Spike and susceptibility to infection: S19P, E37K, M82I, E329G and G352V. Communicated by Ramaswamy H. Sarma

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) is a recently established multimodal single cell analysis technique combining the immunophenotyping capabilities of antibody labeling and cell sorting with the resolution of single-cell RNA sequencing (scRNA-seq). By simply adding a 12-bp nucleotide barcode to antibodies (cell hashing), CITE-seq can be used to sequence antibody-bound tags alongside the cellular mRNA, thus reducing costs of scRNA-seq by performing it at the same time on multiple barcoded samples in a single run. Here, we illustrate an ideal CITE-seq data analysis workflow by characterizing the transcriptome of SH-SY5Y neuroblastoma cell line, a widely used model to study neuronal function and differentiation. We obtained transcriptomes from a total of 2879 single cells, measuring an average of 1600 genes/cell. Along with standard scRNA-seq data handling procedures, such as quality checks and cell filtering procedures, we performed exploratory analyses to identify most stable genes to be possibly used as reference housekeeping genes in qPCR experiments. We also illustrate how to use some popular R packages to investigate cell heterogeneity in scRNA-seq data, namely Seurat, Monocle, and slalom. Both the CITE-seq dataset and the code used to analyze it are freely shared and fully reusable for future research.

Copper is an essential transition metal frequently increased in cancer known to strongly influence essential cellular processes. Targeted therapy protocols utilizing both novel and repurposed drug agents initially demonstrate strong efficacy, before failing in advanced cancers as drug resistance develops and relapse occurs. Overcoming this limitation involves the development of strategies and protocols aimed at a wider targeting of the underlying molecular changes. Receptor Tyrosine Kinase signaling pathways, epigenetic mechanisms and cell metabolism are among the most common therapeutic targets, with molecular investigations increasingly demonstrating the strong influence each mechanism exerts on the others. Interestingly, all these mechanisms can be influenced by intracellular copper. We propose that copper chelating agents, already in clinical trial for multiple cancers, may simultaneously target these mechanisms across a wide variety of cancers, serving as an excellent candidate for targeted combination therapy. This review summarizes the known links between these mechanisms, copper, and copper chelation therapy.

DIPG is an incurable and inoperable pediatric brain cancer in the ventral pons characterized by its complex mutational profile. Epigenetic mutations to H3K27M are seen in up to 81% of patients, resulting in the global loss of the repressive H3K27 trimethylation marker, increasing chromatin accessibility and deregulating gene expression. However, these epigenetic changes are often partnered by secondary mutations, with activating mutations and copy number gains observed in a wide variety of RTK genes and their associated signaling pathways. The combination of these two mutational paradigms results in the broad alteration of cellular and metabolic mechanisms, complicating the search for effective targeted therapeutic strategies. Copper, a metal ion essential for normal cellular function is known to be highly expressed in the pons, and influence ERK and PI3K/AKT signaling. Importantly, excess copper accumulation has been implicated in the pathogenesis of multiple neurological diseases and cancers. Copper chelation therapy is a clinically approved strategy for pediatric patients with Wilson’s Disease, known to improve their neurological symptoms, and is under investigation for use in a number of cancers. Therefore, we hypothesized copper chelation may be an effective therapeutic strategy for DIPG. Cytotoxicity assays using copper chelator tetraethylenepentamine (TEPA) demonstrated millimolar efficacy and synergized with mTOR inhibitor everolimus in a panel of DIPG cell lines, with H3-K27M mutant cell lines found to be more sensitive. Western blots were used to identify copper integrated pathways, with DIPG cell lines stimulated with sub-lethal copper concentrations demonstrating increased phosphorylated expression of ERK1/2, ERK5, AKT and p70SK61. TEPA reduced the phosphorylation of these markers compared to controls. Importantly, epigenetic mechanisms were sensitive to copper, as both copper stimulation and TEPA modulated H3K27 trimethylation, and TEPA decreased pro-expression H3K27 acetylation. In further blots examining epigenetic regulators, TEPA reduced the expression of EZH2, DNMT3B and DNMT1. RNA-sequencing analysis revealed TEPA downregulated genes involved in S-adenosylmethionine production metabolism, DNA regulation, cell cycle and mTORC signaling and specifically, EZH2, DNMT3B and DNMT1 expression. In vivo investigations demonstrated TEPA’s ability to improve survival in an orthotopic xenograft model, and via xenogen luminescence imaging complete tumor regression in 25% of treated mice. This study indicates copper directly impacts epigenetic and RTK mechanisms, and that their targeting through copper chelation agents represents a potential therapeutic strategy for DIPG, both as a single agent and in combination. Citation Format: Filip Michniewicz, Federica Saletta, Tayla Watkinson, Daniele Mercatelli, Federico M. Giorgi, Jessica Bell, Maria Tsoli, David Ziegler, Orazio Vittorio. Using copper chelating agents to simultaneously target epigenetic mechanisms and receptor tyrosine kinase (RTK) signaling in diffuse intrinsic pontine glioma (DIPG) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5716.

Immunotherapy remains a promising approach in the treatment of high-risk neuroblastoma, however efficacy is hampered by the immunosuppressive tumor microenvironment. We previously reported a link between intratumoral copper levels and Programmed Death-Ligand 1 (PD-L1) expression and therefore sought to elucidate the wider impact of copper chelation on immune evasion strategies (Voli et al 2020). Here we profile key elements of the neuroblastoma tumor microenvironment which work in concert to promote immunosuppression and tumor progression. Using the murine TH-MYCN model, animals were treated daily with the copper chelation agent tetraethylenepentamine (TEPA) for seven days before tumor resection and processing. Transcriptome analyses using single-cell RNA-sequencing revealed copper chelation positively skewed the functional status of tumor, immune and stromal compartments to enhance the anti-tumor immune response. This was supported by a tissue microarray screen using NanoString Digital Spatial Profiling which identified increased immune cell infiltration and regions of active tumor killing. High-resolution mass-spectrometry detected upregulation of major histocompatibility complex (MHC) proteins and exclusive antigenic signatures in peptide repertoires. A multiplex cytokine array indicated an improved anti-tumorigenic response underscored by T cell and Natural Killer cell activation. Importantly, combination of copper chelation and anti-GD2 antibody therapy led to tumor regression and significantly improved survival in vivo. Collectively, this study demonstrates the ability of copper chelation to successfully mitigate tumoral immune evasion strategies while providing remarkable insight into neuroblastoma biology. Findings provide crucial evidence in support of combining clinically approved copper chelators with immunotherapy to improve outcomes for neuroblastoma patients. Citation Format: Jourdin R. Rouaen, Daniele Mercatelli, Federica Saletta, Ensieh M. Poursani, Jayne E. Murray, Nicodemus Tedla, Federico M. Giorgi, Orazio Vittorio. Copper chelation overcomes the immunosuppressive tumor microenvironment in neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5214.

DIPG is an incurable pediatric brain cancer of the ventral pons characterized by its complex epigenetic profile. Up to 81% of patients present with mutation H3K27M, resulting in the global reduction of H3K27 trimethylation and increased H3K27 acetylation, deregulating gene expression through an aberrant pattern of epigenetic modification. These alterations affect many cellular and metabolic mechanisms, complicating the search for effective targeted therapeutic strategies. Copper is highly abundant in the pons and is essential for normal brain function and development. However, excess copper accumulation is implicated in several neurological diseases and cancers. Incidentally, recent investigations have indicated the H3-H4 dimer can interact with copper acting as a reductase enzyme. Copper chelation therapy is clinically approved for pediatric patients with Wilson’s Disease, improving their neurological symptoms, and is being trialed in several cancers. We therefore hypothesized copper chelation may represent an effective therapeutic strategy for DIPG. Copper chelator tetraethylenepentamine (TEPA) decreased cell growth and induced apoptosis in DIPG cell lines. To understand these results, unbiased RNA-seq and metabolomics analyses were performed, revealing downregulation of EZH2, DNMT1 and DNMT3B, upregulation of KDM6B and the disruption of key enzymes in the S-adenosylmethionine (SAM)-cycle. Importantly, TEPA downregulated SAM, which donates methyl groups for methylation, S-adenosylhomocysteine, its post-methylation product and α-ketoglutarate, a co-factor for KDM6B. Western blots confirmed the reduced expression of EZH2, DNMT1 and DNMT3B, with further blots examining the chromatin cell fraction revealing modulation of H3K27 trimethylation through copper or TEPA stimulation, and reduction of H3K27 acetylation by TEPA. Importantly, in vitro combinations with Panobinostat were synergistic, while in vivo investigations demonstrated TEPA improved survival in an orthotopic patient derived xenograft (PDX) model, showing complete tumor regression in 25% of treated mice. This study indicates a novel use for copper chelators as epigenetic drugs, and their potential as therapeutics for DIPG.

Aims and objectives Methods and materials Results Conclusion Personal information References, Aims and objectives: Ageing of the global population has become a public health concern, considering the impact of age-related diseases in terms of healthcare and social costs [1]. One of the health problems that is emerging is frailty, a clinical syndrome in which...

Aims and objectives Methods and materials Results Conclusion Personal information References, Aims and objectives: Neurofibromatosis type 1 (NF-1) is an autosomal-dominant disease that occurs with a prevalence of one on 3000, although 50% of cases are due to spontaneous mutations [1]. Most common clinical manifestation include “cafè au lait” skin...

The avalanche of genomic data generated from the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) virus requires the development of tools to detect and monitor its mutations across the world. Here, we present a webtool, coronapp, dedicated to easily processing user‐provided SARS‐CoV‐2 genomic sequences and visualizing the current worldwide status of SARS‐CoV‐2 mutations. The webtool allows users to highlight mutations and categorize them by frequency, country, genomic location and effect on protein sequences, and to monitor their presence in the population over time. The tool is available at http://giorgilab.unibo.it/coronannotator/ for the annotation of user‐provided sequences. The full code is freely shared at https://github.com/federicogiorgi/giorgilab/tree/master/coronannotator.

SARS-CoV-2 entry in human cells is mediated by the interaction between the viral Spike protein and the human ACE2 receptor. This mechanism evolved from the ancestor bat coronavirus and is currently one of the main targets for antiviral strategies. However, there currently exist several Spike protein variants in the SARS-CoV-2 population as the result of mutations, and it is unclear if these variants may exert a specific effect on the affinity with ACE2 which, in turn, is also characterized by multiple alleles in the human population. In the current study, the GBPM analysis, originally developed for highlighting host-guest interaction features, has been applied to define the key amino acids responsible for the Spike/ACE2 molecular recognition, using four different crystallographic structures. Then, we intersected these structural results with the current mutational status, based on more than 295,000 sequenced cases, in the SARS-CoV-2 population. We identified several Spike mutations interacting with ACE2 and mutated in at least 20 distinct patients: S477N, N439K, N501Y, Y453F, E484K, K417N, S477I and G476S. Among these, mutation N501Y in particular is one of the events characterizing SARS-CoV-2 lineage B.1.1.7, which has recently risen in frequency in Europe. We also identified five ACE2 rare variants that may affect interaction with Spike and susceptibility to infection: S19P, E37K, M82I, E329G and G352V.Significance StatementWe developed a method to identify key amino acids responsible for the initial interaction between SARS-CoV-2 (the COVID-19 virus) and human cells, through the analysis of Spike/ACE2 complexes. We further identified which of these amino acids show variants in the viral and human populations. Our results will facilitate scientists and clinicians alike in identifying the possible role of present and future Spike and ACE2 sequence variants in cell entry and general susceptibility to infection.

The avalanche of genomic data generated from the SARS-CoV-2 virus requires the development of tools to detect and monitor its mutations across the world. Here, we present a webtool, coronapp, dedicated to easily processing user-provided SARS-CoV-2 genomic sequences and visualizing current worldwide status of SARS-CoV-2 mutations.The webtool allows users to highlight mutations and categorize them by frequency, country, genomic location and effect on protein sequences, and to monitor their presence in the population over time.The tool is available at http://giorgilab.unibo.it/coronapp/ for the worldwide dataset and at http://giorgilab.unibo.it/coronannotator/ for the annotation of user-provided sequences. The full code is freely shared at https://github.com/federicogiorgi/giorgilab/tree/master/coronappData Availability StatementThe data that support the findings of this study derive from the GISAID consortium and are openly available in Github, in Rdata format for the R environment, in files results.rda and metadata.rda, at the following link: https://github.com/federicogiorgi/giorgilab/tree/master/coronapp/data

Gene-regulatory networks reconstruction has become a very popular approach in applied biology to infer and dissect functional interactions of Transcription Factors (TFs) driving a defined phenotypic state, termed as Master Regulators (MRs). In the present work, cutting-edge bioinformatic methods were applied to re-analyze experimental data on leukemia cells (human myelogenous leukemia cell line THP-1 and acute myeloid leukemia MOLM-13 cells) treated for 6 h with two different Ribosome-Inactivating Proteins (RIPs), namely Shiga toxin type 1 (400 ng/mL) produced by Escherichia coli strains and the plant toxin stenodactylin (60 ng/mL), purified from the caudex of Adenia stenodactyla Harms. This analysis allowed us to identify the common early transcriptional response to 28S rRNA damage based on gene-regulatory network inference and Master Regulator Analysis (MRA). Both toxins induce a common response at 6 h which involves inflammatory mediators triggered by AP-1 family transcriptional factors and ATF3 in leukemia cells. We describe for the first time the involvement of MAFF, KLF2 and KLF6 in regulating RIP-induced apoptotic cell death, while receptor-mediated downstream signaling through ANXA1 and TLR4 is suggested for both toxins.

the recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 and causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus.

MotivationGene Network Inference and Master Regulator Analysis (MRA) have been widely adopted to define specific transcriptional perturbations from gene expression signatures. Several tools exist to perform such analyses, but most require a computer cluster or large amounts of RAM to be executed.ResultsWe developed corto, a fast and lightweight R package to infer gene networks and perform MRA from gene expression data, with optional corrections for Copy Number Variations (CNVs) and able to run on signatures generated from RNA-Seq or ATAC-Seq data. We extensively benchmarked it to infer context-specific gene networks in 39 human tumor and 27 normal tissue datasets.AvailabilityCross-platform and multi-threaded R package on CRAN (stable version) https://cran.rproject.org/package=corto and Github (development release) https://github.com/federicogiorgi/corto.Contactfederico.giorgi@unibo.it

Histone deacetylases (HDACs) are evolutionary conserved enzymes which operate by removing acetyl groups from histones and other protein regulatory factors, with functional consequences on chromatin remodeling and gene expression profiles. We provide here a review on the recent knowledge accrued on the zinc-dependent HDAC protein family across different species, tissues, and human pathologies, specifically focusing on the role of HDAC inhibitors as anti-cancer agents. We will investigate the chemical specificity of different HDACs and discuss their role in the human interactome as members of chromatin-binding and regulatory complexes.

Therapeutic checkpoint antibodies blocking programmed death receptor 1/programmed death ligand 1 (PD-L1) signaling have radically improved clinical outcomes in cancer. However, the regulation of PD-L1 expression on tumor cells is still poorly understood. Here we show that intratumoral copper levels influence PD-L1 expression in cancer cells. Deep analysis of the The Cancer Genome Atlas database and tissue microarrays showed strong correlation between the major copper influx transporter copper transporter 1 (CTR-1) and PD-L1 expression across many cancers but not in corresponding normal tissues. Copper supplementation enhanced PD-L1 expression at mRNA and protein levels in cancer cells and RNA sequencing revealed that copper regulates key signaling pathways mediating PD-L1–driven cancer immune evasion. Conversely, copper chelators inhibited phosphorylation of STAT3 and EGFR and promoted ubiquitin-mediated degradation of PD-L1. Copper-chelating drugs also significantly increased the number of tumor-infiltrating CD8+ T and natural killer cells, slowed tumor growth, and improved mouse survival. Overall, this study reveals an important role for copper in regulating PD-L1 and suggests that anticancer immunotherapy might be enhanced by pharmacologically reducing intratumor copper levels. Significance: These findings characterize the role of copper in modulating PD-L1 expression and contributing to cancer immune evasion, highlighting the potential for repurposing copper chelators as enhancers of antitumor immunity.

Bone and muscle are two deeply interconnected organs and a strong relationship between them exists in their development and maintenance. The peak of both bone and muscle mass is achieved in early adulthood, followed by a progressive decline after the age of 40. The increase in life expectancy in developed countries resulted in an increase of degenerative diseases affecting the musculoskeletal system. Osteoporosis and sarcopenia represent a major cause of morbidity and mortality in the elderly population and are associated with a significant increase in healthcare costs. Several imaging techniques are currently available for the non-invasive investigation of bone and muscle mass and quality. Conventional radiology, dual energy X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound often play a complementary role in the study of osteoporosis and sarcopenia, depicting different aspects of the same pathology. This paper presents the different imaging modalities currently used for the investigation of bone and muscle mass and quality in osteoporosis and sarcopenia with special emphasis on the clinical applications and limitations of each technique and with the intent to provide interesting insights into recent advances in the field of conventional imaging, novel high-resolution techniques and fracture risk.

Purpose Methods and Materials Results Conclusion References Personal Information, Purpose: Bone is a common location for metastases in advanced cancer. Patients with bone metastases frequently suffer from significant pain that has a negative impact on patients’ well-being. Magnetic resonance-guided focused ultrasound surgery (MRgFUS)...

The aging process is characterized by the chronic inflammatory status called “inflammaging”, which shares major molecular and cellular features with the metabolism-induced inflammation called “metaflammation.” Metaflammation is mainly driven by overnutrition and nutrient excess, but other contributing factors are metabolic modifications related to the specific body composition (BC) changes occurring with age. The aging process is indeed characterized by an increase in body total fat mass and a concomitant decrease in lean mass and bone density, that are independent from general and physiological fluctuations in weight and body mass index (BMI). Body adiposity is also re-distributed with age, resulting in a general increase in trunk fat (mainly abdominal fat) and a reduction in appendicular fat (mainly subcutaneous fat). Moreover, the accumulation of fat infiltration in organs such as liver and muscles also increases in elderly, while subcutaneous fat mass tends to decrease. These specific variations in BC are considered risk factors for the major age-related diseases, such as cardiovascular diseases, type 2 diabetes, sarcopenia and osteoporosis, and can predispose to disabilities. Thus, the maintenance of a balance rate of fat, muscle and bone is crucial to preserve metabolic homeostasis and a health status, positively contributing to a successful aging. For this reason, a detailed assessment of BC in elderly is critical and could be an additional preventive personalized strategy for age-related diseases. Despite BMI and other clinical measures, such as waist circumference measurement, waist-hip ratio, underwater weighing and bioelectrical impedance, are widely used as a surrogate measure for body adiposity, they barely reflect the distribution of body fat. Because of the great advantages offered by imaging tools in research and clinics, the attention of clinicians is now moving to powerful imaging techniques such as computed tomography, magnetic resonance imaging, dual-energy X-ray absorptiometry and ultrasound to obtain a more accurate estimation of BC. The aim of this review is to present the state of the art of the imaging techniques that are currently available to measure BC and that can be applied to the study of BC changes in the elderly, outlining advantages and disadvantages of each technique.

Cancer is a disease often characterized by the presence of multiple genomic alterations, which trigger altered transcriptional patterns and gene expression, which in turn sustain the processes of tumorigenesis, tumor progression, and tumor maintenance. The links between genomic alterations and gene expression profiles can be utilized as the basis to build specific molecular tumorigenic relationships. In this study, we perform pan-cancer predictions of the presence of single somatic mutations and copy number variations using machine learning approaches on gene expression profiles. We show that gene expression can be used to predict genomic alterations in every tumor type, where some alterations are more predictable than others. We propose gene aggregation as a tool to improve the accuracy of alteration prediction models from gene expression profiles. Ultimately, we show how this principle can be beneficial in intrinsically noisy datasets, such as those based on single-cell sequencing.

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