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Abstract Prognostic tests and treatment approaches for optimized clinical care of prostatic neoplasms are an unmet need. Prostate cancer (PCa) and derived extracellular vesicles (EVs) proteome changes occur during initiation and progression of the disease. PCa tissue proteome has been previously characterized, but screening of tissue samples constitutes an invasive procedure. Consequently, we focused this study on liquid biopsies, such as urine samples. More specifically, urinary small extracellular vesicle and particles proteome profiles of 100 subjects were analyzed using liquid chromatography coupled to high-resolution mass spectrometry (LC–MS/MS). We identified 171 proteins that were differentially expressed between intraductal prostate cancer/cribriform (IDC/Crib) and non-IDC/non-Crib after correction for multiple testing. However, the strong correlation between IDC/Crib and Gleason Grade complicates the disentanglement of the underlying factors driving this association. Nevertheless, even after accounting for multiple testing and adjusting for ISUP (International Society of Urological Pathology) grading, two proteins continued to exhibit significant differential expression between IDC/Crib and non-IDC/non-Crib. Functional enrichment analysis based on cancer hallmark proteins disclosed a clear pattern of androgen response down-regulation in urinary EVs from IDC/Crib compared to non-IDC/non-Crib. Interestingly, proteome differences between IDC and cribriform were more subtle, suggesting high proteome heterogeneity. Overall, the urinary EV proteome reflected partly the prostate pathology.

Proteomics can be a robust tool in protein identification and regulation, allowing the discovery of potential biomarkers. In clinical practice, the management of endometrial cancer can be challenging. Thus, identifying promising markers could be beneficial, helping both in diagnosis and prognostic stratification, even predicting the response to therapy. Therefore, this manuscript systematically reviews the existing evidence of the proteomic profile of human endometrial cancer. The literature search was conducted via Medline (through PubMed) and the Web of Science. The inclusion criteria were clinical, in vitro, and in vivo original studies reporting proteomic analysis using all types of samples to map the human endometrial cancer proteome. A total of 55 publications were included in this review. Most of the articles carried out a proteomic analysis on endometrial tissue, serum and plasma samples, which enabled the identification of several potential diagnostic and prognostic biomarkers. In addition, eight articles were analyzed regarding the identified proteins, where three studies showed a strong correlation, sharing forty-five proteins. This analysis also allowed the identification of the 10 most frequently reported proteins in these studies: EGFR, PGRMC1, CSE1L, MYDGF, STMN1, CASP3 ANXA2, YBX1, ANXA1, and MYH11. Proteomics-based approaches pointed out potential diagnostic and prognostic candidates for endometrial cancer. However, there is a lack of studies exploring novel therapeutic targets.

Background Blood biomarkers are a potential tool for early stroke diagnosis. We aimed to perform a pilot and exploratory study on untargeted blood biomarkers in patients with suspected stroke by using mass spectrometry analysis. Methods and Results This was a prospective observational study of consecutive patients with suspected stroke admitted within 6 hours of last being seen well. Blood samples were collected at admission. Patients were divided into 3 groups: ischemic stroke (IS), intracerebral hemorrhage (ICH), and stroke mimics. Quantitative analysis from mass spectrometry data was performed using a supervised approach. Biomarker‐based prediction models were developed to differentiate IS from ICH and ICH+stroke mimics. Models were built aiming to minimize misidentification of patients with ICH as having IS. We included 90 patients, one‐third within each subgroup. The median age was 71 years (interquartile range, 57–81 years), and 49 participants (54.4%) were women. In quantitative analysis, C3 (complement component 3), ICAM‐2 (intercellular adhesion molecule 2), PLGLA (plasminogen like A), STXBP5 (syntaxin‐binding protein 5), and IGHV3‐64 (immunoglobulin heavy variable 3‐64) were the 5 most significantly dysregulated proteins for both comparisons. Biomarker‐based models showed 88% sensitivity and 89% negative predictive value for differentiating IS from ICH, and 75% sensitivity and 95% negative predictive value for differentiating IS from ICH+stroke mimics. ICAM‐2, STXBP5, PLGLA, C3, and IGHV3‐64 displayed the highest importance score in our models, being the most informative for identifying patients with stroke. Conclusions In this proof‐of‐concept and exploratory study, our biomarker‐based prediction models, including ICAM‐2, STXBP5, PLGLA, C3, and IGHV3‐64, showed 75% to 88% sensitivity for identifying patients with IS, while aiming to minimize misclassification of ICH. Although our methodology provided an internal validation, these results still need validation in other cohorts and with different measurement techniques.

Abstract Background JUNB transcription factor contributes to the formation of the ubiquitous transcriptional complex AP-1 involved in the control of many physiological and disease-associated functions. The roles of JUNB in the control of cell division and tumorigenic processes are acknowledged but still unclear. Results Here, we report the results of combined transcriptomic, genomic, and functional studies showing that JUNB promotes cell cycle progression via induction of cyclin E1 and repression of transforming growth factor (TGF)-β2 genes. We also show that high levels of JUNB switch the response of TGF-β2 stimulation from an antiproliferative to a pro-invasive one, induce endogenous TGF-β2 production by promoting TGF-β2 mRNA translation, and enhance tumor growth and metastasis in mice. Moreover, tumor genomic data indicate that JUNB amplification associates with poor prognosis in breast and ovarian cancer patients. Conclusions Our results reveal novel functions for JUNB in cell proliferation and tumor aggressiveness through regulation of cyclin E1 and TGF-β2 expression, which might be exploited for cancer prognosis and therapy.

Oxidation of PUFAs in LDLs trapped in the arterial intima plays a critical role in atherosclerosis. Though there have been many studies on the atherogenicity of oxidized derivatives of PUFA-esters of cholesterol, the effects of cholesteryl hemiesters (ChEs), the oxidation end products of these esters, have not been studied. Through lipidomics analyses, we identified and quantified two ChE types in the plasma of CVD patients and identified four ChE types in human endarterectomy specimens. Cholesteryl hemiazelate (ChA), the ChE of azelaic acid (n-nonane-1,9-dioic acid), was the most prevalent ChE identified in both cases. Importantly, human monocytes, monocyte-derived macrophages, and neutrophils exhibit inflammatory features when exposed to subtoxic concentrations of ChA in vitro. ChA increases the secretion of proinflammatory cytokines such as interleukin-1β and interleukin-6 and modulates the surface-marker profile of monocytes and monocyte-derived macrophage. In vivo, when zebrafish larvae were fed with a ChA-enriched diet, they exhibited neutrophil and macrophage accumulation in the vasculature in a caspase 1- and cathepsin B-dependent manner. ChA also triggered lipid accumulation at the bifurcation sites of the vasculature of the zebrafish larvae and negatively impacted their life expectancy. We conclude that ChA behaves as an endogenous damage-associated molecular pattern with inflammatory and proatherogenic properties.

Abstract Alpha-synuclein (aSyn) is a central player in the pathogenesis of synucleinopathies due to its accumulation in typical protein aggregates in the brain. However, it is still unclear how it contributes to neurodegeneration. Type-2 diabetes mellitus is a risk factor for Parkinson’s disease (PD). Interestingly, a common molecular alteration among these disorders is the age-associated increase in protein glycation. We hypothesized that glycation-induced neuronal dysfunction is a contributing factor in synucleinopathies. Here, we dissected the impact of methylglyoxal (MGO, a glycating agent) in mice overexpressing aSyn in the brain. We found that MGO-glycation potentiates motor, cognitive, olfactory, and colonic dysfunction in aSyn transgenic (Thy1-aSyn) mice that received a single dose of MGO via intracerebroventricular injection. aSyn accumulates in the midbrain, striatum, and prefrontal cortex, and protein glycation is increased in the cerebellum and midbrain. SWATH mass spectrometry analysis, used to quantify changes in the brain proteome, revealed that MGO mainly increase glutamatergic-associated proteins in the midbrain (NMDA, AMPA, glutaminase, VGLUT and EAAT1), but not in the prefrontal cortex, where it mainly affects the electron transport chain. The glycated proteins in the midbrain of MGO-injected Thy1-aSyn mice strongly correlate with PD and dopaminergic pathways. Overall, we demonstrated that MGO-induced glycation accelerates PD-like sensorimotor and cognitive alterations and suggest that the increase of glutamatergic signaling may underly these events. Our study sheds new light into the enhanced vulnerability of the midbrain in PD-related synaptic dysfunction and suggests that glycation suppressors and anti-glutamatergic drugs may hold promise as disease-modifying therapies for synucleinopathies.

Abstract The lung is inhabited by a diverse microbiome that originates from the oropharynx by a mechanism of micro-aspiration. Its bacterial biomass is usually low; however, this condition shifts in lung cancer (LC), chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD). These chronic lung disorders (CLD) may coexist in the same patient as comorbidities and share common risk factors, among which the microbiome is included. We characterized the microbiome of 106 bronchoalveolar lavages. Samples were initially subdivided into cancer and non-cancer and high-throughput sequenced for the 16S rRNA gene. Additionally, we used a cohort of 25 CLD patients where crossed comorbidities were excluded. Firmicutes, Proteobacteria and Bacteroidetes were the most prevalent phyla independently of the analyzed group. Streptococcus and Prevotella were associated with LC and Haemophilus was enhanced in COPD versus ILD. Although no significant discrepancies in microbial diversity were observed between cancer and non-cancer samples, statistical tests suggested a gradient across CLD where COPD and ILD displayed the highest and lowest alpha diversities, respectively. Moreover, COPD and ILD were separated in two clusters by the unweighted UniFrac distance (P value = 0.0068). Our results support the association of Streptoccocus and Prevotella with LC and of Haemophilus with COPD, and advocate for specific CLD signatures.

Multiple myeloma (MM), the third most frequent hematological cancer worldwide, is characterized by the proliferation of neoplastic plasma cells in the bone marrow (BM). One of the hallmarks of MM is a permissive BM microenvironment. Increasing evidence suggests that cell-to-cell communication between myeloma and immune cells via tumor cell-derived extracellular vesicles (EV) plays a key role in the pathogenesis of MM. Hence, we aimed to explore BM immune alterations induced by MM-derived EV. For this, we inoculated immunocompetent BALB/cByJ mice with a myeloma cell line, MOPC315.BM, inducing a MM phenotype. Upon tumor establishment, characterization of the BM microenvironment revealed the expression of both activation and suppressive markers by lymphocytes, such as granzyme B and PD-1, respectively. In addition, conditioning of the animals with MOPC315.BM-derived EV, before transplantation of the MOPC315.BM tumor cells, did not anticipate the disease phenotype. However, it induced features of suppression in the BM milieu, such as an increase in PD-1 expression by CD4+ T cells. Overall, our findings reveal the involvement of MOPC315.BM-derived EV protein content as promoters of immune niche remodeling, strengthening the importance of assessing the mechanisms by which MM may impact the immune microenvironment.

The contribution of radiotherapy, per se, to late cardiotoxicity remains controversial. To clarify its impact on the development of early cardiac dysfunction, we developed an experimental model in which the hearts of rats were exposed, in a fractionated plan, to clinically relevant doses of ionizing radiation for oncological patients that undergo thoracic radiotherapy. Rat hearts were exposed to daily doses of 0.04, 0.3, and 1.2 Gy for 23 days, achieving cumulative doses of 0.92, 6.9, and 27.6 Gy, respectively. We demonstrate that myocardial deformation, assessed by global longitudinal strain, was impaired (a relative percentage reduction of >15% from baseline) in a dose-dependent manner at 18 months. Moreover, by scanning electron microscopy, the microvascular density in the cardiac apex was significantly decreased exclusively at 27.6 Gy dosage. Before GLS impairment detection, several tools (qRT-PCR, mass spectrometry, and western blot) were used to assess molecular changes in the cardiac tissue. The number/expression of several genes, proteins, and KEGG pathways, related to inflammation, fibrosis, and cardiac muscle contraction, were differently expressed in the cardiac tissue according to the cumulative dose. Subclinical cardiac dysfunction occurs in a dose-dependent manner as detected by molecular changes in cardiac tissue, a predictor of the severity of global longitudinal strain impairment. Moreover, there was no dose threshold below which no myocardial deformation impairment was detected. Our findings i) contribute to developing new markers and exploring non-invasive magnetic resonance imaging to assess cardiac tissue changes as an early predictor of cardiac dysfunction; ii) should raise red flags, since there is no dose threshold below which no myocardial deformation impairment was detected and should be considered in radiation-based imaging and -guided therapeutic cardiac procedures; and iii) highlights the need for personalized clinical approaches.

Multiple myeloma (MM) is a hematological malignancy of clonal antibody–secreting plasma cells (PCs). MM diagnosis and risk stratification rely on bone marrow (BM) biopsy, an invasive procedure prone to sample bias. Liquid biopsies, such as extracellular vesicles (EV) in peripheral blood (PB), hold promise as new minimally invasive tools. Real-world studies analyzing patient-derived EV proteome are rare. Here, we characterized a small EV protein content from PB and BM samples in a cohort of 102 monoclonal gammopathies patients routinely followed in the clinic and 223 PB and 111 BM samples were included. We investigated whether EV protein and particle concentration could predict an MM patient prognosis. We found that a high EV protein/particle ratio, or EV cargo >0.6 µg/108 particles, is related to poorer survival and immune dysfunction. These results were supported at the protein level by mass spectrometry. We report a set of PB EV-proteins (PDIA3, C4BPA, BTN1A1, and TNFSF13) with a new biomarker potential for myeloma patient outcomes. The high proteomic similarity between PB and BM matched pairs supports the use of circulating EV as a counterpart of the BM EV proteome. Overall, we found that the EV protein content is related to patient outcomes, such as survival, immune dysfunction, and possibly treatment response.

Through lateral transfer, extra-cellular vesicles (EVs) transport their DNA, miRNA, mRNA and proteins such as enzymes mediating drug resistance, transporters as well as growth factors to neighboring cells. By virtue of this horizontal transfer, EVs potentially regulate cell growth, migration, angiogenesis and metastasis and increase tissue permeability in cancer. Furthermore, EVs regulate immune factors and allow the tumor cells to evade immune recognition and cell death. To explore if the proteomes of exosomes support functional transfer of cancer hallmarks, in this meta-analysis, we compared EVs and whole cell proteomes from the NCI-60 human tumor cell line panel. We observed a subgroup of proteins in each cancer hallmark signature as highly abundant and consistently expressed in EVs from all cell lines. Among these were oncoproteins frequently targeted in cancer therapies whose presence on EVs could potentially render therapies less effective by serving as decoys.

The prognosis of diffuse large B cell lymphoma (DLBCL) is inaccurately predicted using clinical features and immunohistochemistry (IHC) algorithms. Nomination of a panel of molecules as the target for therapy and predicting prognosis in DLBCL is challenging because of the divergences in the results of molecular studies. Mass spectrometry (MS)-based proteomics in the clinic represents an analytical tool with the potential to improve DLBCL diagnosis and prognosis. Previous proteomics studies using MS-based proteomics identified a wide range of proteins. To achieve a consensus, we reviewed MS-based proteomics studies and extracted the most consistently significantly dysregulated proteins. These proteins were then further explored by analyzing data from other omics fields. Among all significantly regulated proteins, interferon regulatory factor 4 (IRF4) was identified as a potential target by proteomics, genomics, and IHC. Moreover, annexinA5 (ANXA5) and nucleobindin1 (NUCB1) were two of the most up-regulated proteins identified in MS studies. Functional enrichment analysis identified the light zone reactions of the germinal center (LZ-GC) together with cytoskeleton locomotion functions as enriched based on consistent, significantly dysregulated proteins. In this study, we suggest IRF4 and NUCB1 proteins as potential biomarkers that deserve further investigation in the field of DLBCL sub-classification and prognosis.

Background: Localized stress and cell death in chronic inflammatory diseases may release tissue-specific lipids into the circulation causing the blood plasma lipidome to reflect the type of inflammation. However, deep lipid profiles of major chronic inflammatory diseases have not been compared. Methods: Plasma lipidomes of patients suffering from two etiologically distinct chronic inflammatory diseases, atherosclerosis-related vascular disease, including cardiovascular (CVD) and ischemic stroke (IS), and systemic lupus erythematosus (SLE), were screened by a top-down shotgun mass spectrometry-based analysis without liquid chromatographic separation and compared to each other and to age-matched controls. Lipid profiling of 596 lipids was performed on a cohort of 427 individuals. Machine learning classifiers based on the plasma lipidomes were used to distinguish the two chronic inflammatory diseases from each other and from the controls. Findings: Analysis of the lipidomes enabled separation of the studied chronic inflammatory diseases from controls based on independent validation test set classification performance (CVD vs control - Sensitivity: 0.94, Specificity: 0.88; IS vs control - Sensitivity: 1.0, Specificity: 1.0; SLE vs control – Sensitivity: 1, Specificity: 0.93) and from each other (SLE vs CVD ‒ Sensitivity: 0.91, Specificity: 1; IS vs SLE - Sensitivity: 1, Specificity: 0.82). Preliminary linear discriminant analysis plots using all data clearly separated the clinical groups from each other and from the controls, and partially separated CVD severities, as classified into five clinical groups. Dysregulated lipids are partially but not fully counterbalanced by statin treatment. Interpretation: Dysregulation of the plasma lipidome is characteristic of chronic inflammatory diseases. Lipid profiling accurately identifies the diseases and in the case of CVD also identifies sub-classes. Funding: Full list of funding sources at the end of the manuscript.

(1) Background: Pancreatic ductal adenocarcinoma (PDAC) is expected to be the second-leading cause of cancer deaths by 2030. Imaging techniques are the standard for monitoring the therapy response in PDAC, but these techniques have considerable limits, including delayed disease progression detection and difficulty in distinguishing benign from malignant lesions. Extracellular vesicle (EV) liquid biopsy is an emerging diagnosis modality. Nonetheless, the majority of research for EV-based diagnosis relies on point analyses of EVs at specified times, while longitudinal EV population studies before and during therapeutic interventions remain largely unexplored. (2) Methods: We analyzed plasma EV protein composition at diagnosis and throughout PDAC therapy. (3) Results: We found that IgG is linked with the diagnosis of PDAC and the patient’s response to therapy, and that the IgG+ EV population increases with disease progression and reduces with treatment response. Importantly, this covers PDAC patients devoid of the standard PDAC seric marker CA19.9 expression. We also observed that IgG is bound to EVs via the tumor antigen MAGE B1, and that this is independent of the patient’s inflammatory condition and IgG seric levels. (4) Conclusions: We here propose that a population analysis of IgG+ EVs in PDAC plasma represents a novel method to supplement the monitoring of the PDAC treatment response.

Pancreatic cancers (PC) are highly metastatic with poor prognosis, mainly due to delayed detection. We previously showed that PC-derived extracellular vesicles (EVs) act on macrophages residing in the liver, eliciting extracellular matrix remodeling in this organ and marked hepatic accumulation of CD11b+ bone marrow (BM) cells, which support PC liver metastasis. We here show that PC-EVs also bind to CD11b+ BM cells and induce the expansion of this cell population. Transcriptomic characterization of these cells shows that PC-EVs upregulate IgG and IgA genes, which have been linked to the presence of monocytes/macrophages in tumor microenvironments. We also report here the transcriptional downregulation of genes linked to monocyte/macrophage activation, trafficking, and expression of inflammatory molecules. Together, these results show for the first time the existence of a PC–BM communication axis mediated by EVs with a potential role in PC tumor microenvironments.

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

This article presents proteomics data referenced in [1] Using proteomics-based evaluation of red blood cells (RBCs), we have identified differentially abundant proteins associated with Obstructive Sleep Apnea Syndrome (OSA). RBCs were collected from peripheral blood of patients with moderate/severe OSA or snoring at pre- (evening) and post-night (morning) polysomnography, so that proteome variations between these time points could be assessed. RBC cytoplasmic fraction depleted of hemoglobin, using Hemovoid™ system, were analyzed by two-dimensional fluorescence difference gel electrophoresis (2D-DIGE), the 2D image software-based analyzed and relevant differentially abundant proteins identified by mass spectrometry (MS). MS identified 31 protein spots differentially abundant corresponding to 21 unique proteins possibly due to the existence of post-translational modification regulations. Functional analysis by bioinformatics tools indicated that most proteins are associated with catalytic, oxidoreductase, peroxidase, hydrolase, ATPase and anti-oxidant activity. At morning a larger numbers of differential proteins including response to chemical stimulus, oxidation reduction, regulation of catalytic activity and response to stress were observed in OSA. The data might support further research in OSA biomarker discovery and validation.

The most common cystic fibrosis-causing mutation (F508del, present in ~85% of CF patients) leads to CFTR misfolding, which is recognized by the endoplasmic reticulum (ER) quality control (ERQC), resulting in ER retention and early degradation. It is known that CFTR exit from the ER is mediated by specific retention/sorting signals that include four arginine-framed tripeptide (AFT) retention motifs and a diacidic (DAD) exit code that controls the interaction with the COPII machinery. Here, we aim at obtaining a global view of the protein interactors that regulate CFTR exit from the ER. We used mass spectrometry-based interaction proteomics and bioinformatics analyses to identify and characterize proteins interacting with selected CFTR peptide motifs or full-length CFTR variants retained or bypassing these ERQC checkpoints. We conclude that these ERQC trafficking checkpoints rely on fundamental players in the secretory pathway, detecting key components of the protein folding machinery associated with the AFT recognition and of the trafficking machinery recognizing the diacidic code. Furthermore, a greater similarity in terms of interacting proteins is observed for variants sharing the same folding defect over those reaching the same cellular location, evidencing that folding status is dominant over ER escape in shaping the CFTR interactome.

Understanding protein interaction networks and their dynamic changes is a major challenge in modern biology. Currently, several experimental and in silico approaches allow the screening of protein interactors in a large-scale manner. Therefore, the bulk of information on protein interactions deposited in databases and peer-reviewed published literature is constantly growing. Multiple databases interfaced from user-friendly web tools recently emerged to facilitate the task of protein interaction data retrieval and data integration. Nevertheless, as we evidence in this report, despite the current efforts towards data integration, the quality of the information on protein interactions retrieved by in silico approaches is frequently incomplete and may even list false interactions. Here we point to some obstacles precluding confident data integration, with special emphasis on protein interactions, which include gene acronym redundancies and protein synonyms. Three human proteins (choline kinase, PPIase and uromodulin) and three different web-based data search engines focused on protein interaction data retrieval (PSICQUIC, DASMI and BIPS) were used to explain the potential occurrence of undesired errors that should be considered by researchers in the field. We demonstrate that, despite the recent initiatives towards data standardization, manual curation of protein interaction networks based on literature searches are still required to remove potential false positives. A three-step workflow consisting of: (i) data retrieval from multiple databases, (ii) peer-reviewed literature searches, and (iii) data curation and integration, is proposed as the best strategy to gather updated information on protein interactions. Finally, this strategy was applied to compile bona fide information on human DREAM protein interactome, which constitutes liable training datasets that can be used to improve computational predictions.

The search for novel anticancer small molecules and strategies remains a challenge. Our previous studies have identified TXA1 (1-{[2-(diethylamino)ethyl]amino}-4-propoxy-9H- thioxanthen-9-one) as a hit compound, with in vitro antitumor potential by modulating autophagy and apoptosis in human tumor cell lines. In the present study, the mechanism of action and antitumor potential of the soluble salt of this molecule (TXA1.HCl) was further investigated using in vitro and mouse xenograft tumor models of NSCLC. Our results showed that TXA1.HCl affected steroid biosynthesis, increased RagD expression, and caused abnormal cellular cholesterol localization. In addition, TXA1.HCl treatment presented no toxicity to nude mice and significantly reduced the growth of human NSCLC cells xenografts in mice. Overall, this work provides new insights into the mechanism of action of TXA1, which may be relevant for the development of anticancer therapeutic strategies, which target cholesterol transport.

Nonalcoholic fatty liver disease (NAFLD) is a risk factor for Hepatocellular carcinoma (HCC), but he transition from NAFLD to HCC is poorly understood. Feature selection algorithms in human and genetically modified mice NAFLD and HCC microarray data were applied to generate signatures of NAFLD progression and HCC differential survival. These signatures were used to study the pathogenesis of NAFLD derived HCC and explore which subtypes of cancers that can be investigated using mouse models. Our findings show that: (I) HNF4 is a common potential transcription factor mediating the transcription of NAFLD progression genes (II) mice HCC derived from NAFLD co-cluster with a less aggressive human HCC subtype of differential prognosis and mixed etiology (III) the HCC survival signature is able to correctly classify 95% of the samples and gives Fgf20 and Tgfb1i1 as the most robust genes for prediction (IV) the expression values of genes composing the signature in an independent human HCC dataset revealed different HCC subtypes showing differences in survival time by a Logrank test. In summary, we present marker signatures for NAFLD derived HCC molecular pathogenesis both at the gene and pathway level.

A series of duplication events led to an expansion of clade B Serine Protease Inhibitors (SERPIN), currently displaying a large repertoire of functions in vertebrates. Accordingly, the recent duplicates SERPINB3 and B4 located in human 18q21.3 SERPIN cluster control the activity of different cysteine and serine proteases, respectively. Here, we aim to assess SERPINB3 and B4 coevolution with their target proteases in order to understand the evolutionary forces shaping the accelerated divergence of these duplicates. Phylogenetic analysis of primate sequences placed the duplication event in a Hominoidae ancestor (∼30 Mya) and the emergence of SERPINB3 in Homininae (∼9 Mya). We detected evidence of strong positive selection throughout SERPINB4/B3 primate tree and target proteases, cathepsin L2 (CTSL2) and G (CTSG) and chymase (CMA1). Specifically, in the Homininae clade a perfect match was observed between the adaptive evolution of SERPINB3 and cathepsin S (CTSS) and most of sites under positive selection were located at the inhibitor/protease interface. Altogether our results seem to favour a coevolution hypothesis for SERPINB3, CTSS and CTSL2 and for SERPINB4 and CTSG and CMA1. A scenario of an accelerated evolution driven by host-pathogen interactions is also possible since SERPINB3/B4 are potent inhibitors of exogenous proteases, released by infectious agents. Finally, similar patterns of expression and the sharing of many regulatory motifs suggest neofunctionalization as the best fitted model of the functional divergence of SERPINB3 and B4 duplicates.

Gonadal failure, along with early pregnancy loss and perinatal death, may be an important filter that limits the propagation of harmful mutations in the human population. We hypothesized that men with spermatogenic impairment, a disease with unknown genetic architecture and a common cause of male infertility, are enriched for rare deleterious mutations compared to men with normal spermatogenesis. After assaying genomewide SNPs and CNVs in 323 Caucasian men with idiopathic spermatogenic impairment and more than 1,100 controls, we estimate that each rare autosomal deletion detected in our study multiplicatively changes a man's risk of disease by 10% (OR 1.10 [1.04-1.16], p

SUMOylation contributes to the regulation of many essential cellular factors. Diverse techniques have been used to explore the functional consequences of protein SUMOylation. Most approaches consider the identification of sequences on substrates, adaptors, or receptors regulating the SUMO conjugation, recognition, or deconjugation. The large majority of the studied SUMOylated proteins contain the sequence [IVL]KxE. SUMOylated proteins are recognized by at least 3 types of hydrophobic SUMO-interacting motifs (SIMs) that contribute to coordinate SUMO-dependent functions. Typically, SIMs are constituted by a hydrophobic core flanked by one or two clusters of negatively charged amino acid residues. Multiple SIMs can integrate SUMO binding domains (SBDs), optimizing binding, and control over SUMO-dependent processes. Here, we present a survey of the methodologies used to study SUMO-regulated functions and provide guidelines for the identification of cis and trans sequences controlling SUMOylation. Furthermore, an integrative analysis of known and putative SUMO substrates illustrates an updated landscape of several SUMO-regulated events. The strategies and analysis presented here should contribute to the understanding of SUMO-controlled functions and provide rational approach to identify biomarkers or choose possible targets for intervention in processes where SUMOylation plays a critical role.

Metallothioneins (MT) are small proteins involved in heavy metal detoxification and protection against oxidative stress and cancer. The mammalian MT family originated through a series of duplication events which generated four major genes (MT1 to MT4). MT1 and MT2 encode for ubiquitous proteins, while MT3 and MT4 evolved to accomplish specific roles in brain and epithelium, respectively. Herein, phylogenetic, transcriptional and polymorphic analyses are carried out to expose gains, losses and diversification of functions that characterize the evolutionary history of the MT family. The phylogenetic analyses show that all four major genes originated through a single duplication event prior to the radiation of mammals. Further expansion of the MT1 gene has occurred in the primate lineage reaching in humans a total of 13 paralogs, five of which are pseudogenes. In humans, the reading frame of all five MT1 pseudogenes is reconstructed by sequence homology with a functional duplicate revealing that loss of invariant cysteines is the most frequent event accounting for pseudogeneisation. Expression analyses based on EST counts and RT-PCR experiments show that, as for MT1 and MT2, human MT3 is also ubiquitously expressed while MT4 transcripts are present in brain, testes, esophagus and mainly in thymus. Polymorphic variation reveals two deleterious mutations (Cys30Tyr and Arg31Trp) in MT4 with frequencies reaching about 30% in African and Asian populations suggesting the gene is inactive in some individuals and physiological compensation for its loss must arise from a functional equivalent. Altogether our findings provide novel data on the evolution and diversification of MT gene duplicates, a valuable resource for understanding the vast set of biological processes in which these proteins are involved.