Propranolol: A "Pick and Roll" Team Player in Benign Tumors and Cancer Therapies.

Research on cancer therapies focuses on processes such as angiogenesis, cell signaling, stemness, metastasis, and drug resistance and inflammation, all of which are influenced by the cellular and molecular microenvironment of the tumor. Different strategies, such as antibodies, small chemicals, hormones, cytokines, and, recently, gene editing techniques, have been tested to reduce the malignancy and generate a harmful microenvironment for the tumor. Few therapeutic agents have shown benefits when administered alone, but a few more have demonstrated clear improvement when administered in combination with other therapeutic molecules. In 2008 (and for the first time in the clinic), the therapeutic benefits of the ß-adrenergic receptor antagonist, propranolol, were described in benign tumors, such as infantile hemangioma. Propranolol, initially prescribed for high blood pressure, irregular heart rate, essential tremor, and anxiety, has shown, in the last decade, increasing evidence of its antitumoral properties in more than a dozen different types of cancer. Moreover, the use of propranolol in combination therapies with other drugs has shown synergistic antitumor effects. This review highlights the clinical trials in which propranolol is taking part as adjuvant therapy at single administration or in combinatorial human trials, arising as a good pick and roll partner in anticancer strategies.

A Novel Splicing Mutation in the ACVRL1/ALK1 Gene as a Cause of HHT2.

Hereditary Hemorrhagic Telangiectasia (HHT) is a rare disorder of vascular development. Common manifestations include epistaxis, telangiectasias and arteriovenous malformations in multiple organs. Different deletions or nonsense mutations have been described in the ENG (HHT1) or ACVRL1/ALK1 (HHT2) genes, all affecting endothelial homeostasis. A novel mutation in ACVRL1/ALK1 has been identified in a Peruvian family with a clinical history compatible to HHT. Subsequently, 23 DNA samples from oral exchanges (buccal swaps) of the immediate family members were analyzed together with their clinical histories. A routine cDNA PCR followed by comparative DNA sequencing between the founder and another healthy family member showed the presence of the aforementioned specific mutation. The single mutation detected (c.525 + 1G > T) affects the consensus splice junction immediately after exon 4, provokes anomalous splicing and leads to the inclusion of intron IV between exons 4 and 5 in the ACVRL1/ALK1 mRNA and, therefore, to ALK1 haploinsufficiency. Complete sequencing determined that 10 of the 25 family members analyzed were affected by the same mutation. Notably, the approach described in this report could be used as a diagnostic technique, easily incorporated in clinical practice in developing countries and easily extrapolated to other patients carrying such a mutation.

The Role of Propranolol as a Repurposed Drug in Rare Vascular Diseases.

Rare Diseases (RD) are defined by their prevalence in less than 5 in 10,000 of the general population. Considered individually, each RD may seem insignificant, but together they add up to more than 7000 different diseases. Research in RD is not attractive for pharmaceutical companies since it is unlikely to recover development costs for medicines aimed to small numbers of patients. Since most of these diseases are life threatening, this fact underscores the urgent need for treatments. Drug repurposing consists of identifying new uses for approved drugs outside the scope of the original medical indication. It is an alternative option in drug development and represents a viable and risk-managed strategy to develop for RDs. In 2008, the "off label" therapeutic benefits of propranolol were described in the benign tumor Infantile Hemangioma. Propranolol, initially prescribed for high blood pressure, irregular heart rate, essential tremor, and anxiety, has, in the last decade, shown increasing evidence of its antiangiogenic, pro-apoptotic, vasoconstrictor and anti-inflammatory properties in different RDs, including vascular or oncological pathologies. This review highlights the finished and ongoing trials in which propranolol has arisen as a good repurposing drug for improving the health condition in RDs.

Endoglin Protein Interactome Profiling Identifies TRIM21 and Galectin-3 as New Binding Partners.

Endoglin is a 180-kDa glycoprotein receptor primarily expressed by the vascular endothelium and involved in cardiovascular disease and cancer. Heterozygous mutations in the endoglin gene (ENG) cause hereditary hemorrhagic telangiectasia type 1, a vascular disease that presents with nasal and gastrointestinal bleeding, skin and mucosa telangiectases, and arteriovenous malformations in internal organs. A circulating form of endoglin (alias soluble endoglin, sEng), proteolytically released from the membrane-bound protein, has been observed in several inflammation-related pathological conditions and appears to contribute to endothelial dysfunction and cancer development through unknown mechanisms. Membrane-bound endoglin is an auxiliary component of the TGF-ß receptor complex and the extracellular region of endoglin has been shown to interact with types I and II TGF-ß receptors, as well as with BMP9 and BMP10 ligands, both members of the TGF-ß family. To search for novel protein interactors, we screened a microarray containing over 9000 unique human proteins using recombinant sEng as bait. We find that sEng binds with high affinity, at least, to 22 new proteins. Among these, we validated the interaction of endoglin with galectin-3, a secreted member of the lectin family with capacity to bind membrane glycoproteins, and with tripartite motif-containing protein 21 (TRIM21), an E3 ubiquitin-protein ligase. Using human endothelial cells and Chinese hamster ovary cells, we showed that endoglin co-immunoprecipitates and co-localizes with galectin-3 or TRIM21. These results open new research avenues on endoglin function and regulation.

Activating transcription factor 6 derepression mediates neuroprotection in Huntington disease.

Deregulated protein and Ca2+ homeostasis underlie synaptic dysfunction and neurodegeneration in Huntington disease (HD); however, the factors that disrupt homeostasis are not fully understood. Here, we determined that expression of downstream regulatory element antagonist modulator (DREAM), a multifunctional Ca2+-binding protein, is reduced in murine in vivo and in vitro HD models and in HD patients. DREAM downregulation was observed early after birth and was associated with endogenous neuroprotection. In the R6/2 mouse HD model, induced DREAM haplodeficiency or blockade of DREAM activity by chronic administration of the drug repaglinide delayed onset of motor dysfunction, reduced striatal atrophy, and prolonged life span. DREAM-related neuroprotection was linked to an interaction between DREAM and the unfolded protein response (UPR) sensor activating transcription factor 6 (ATF6). Repaglinide blocked this interaction and enhanced ATF6 processing and nuclear accumulation of transcriptionally active ATF6, improving prosurvival UPR function in striatal neurons. Together, our results identify a role for DREAM silencing in the activation of ATF6 signaling, which promotes early neuroprotection in HD.

Nanotechnology in the Fabrication of Protein Microarrays.

Protein biochips are the heart of many medical and bioanalytical applications. Increasing interest of protein biochip fabrication has been focused on surface activation and subsequent functionalization strategies for the immobilization of these molecules.

High-throughgput phage-display screening in array format.

Emerging technologies for the design and generation of human antibodies require improved approaches enabling their screening, characterization and validation. Currently, strategies based on ELISA or western blot are used to that aim. However, the ever increasing number of novel antibodies generated would benefit from the development of new high-throughput (HT) platforms facilitating rapid antibody identification and characterization. Herein, we describe a protein chip bearing recombinant phage particles and based on a large phage antibody library. In this paper we have set forth a novel implementation which provides a powerful and simple methodology enabling the identification of single-chain variable fragments (scFv). As a proof-of-principle of this method, we tested it with recombinant antigen (human recombinant interleukin 8). Additionally, we developed a novel bioinformatics tool that serves to compare this novel strategy with traditional methods. The method described here, together with associated informatics tools, is robust, relatively fast and represents a step-forward in protocols including phage library screenings.

NAPPA as a Real New Method for Protein Microarray Generation.

Nucleic Acid Programmable Protein Arrays (NAPPA) have emerged as a powerful and innovative technology for the screening of biomarkers and the study of protein-protein interactions, among others possible applications. The principal advantages are the high specificity and sensitivity that this platform offers. Moreover, compared to conventional protein microarrays, NAPPA technology avoids the necessity of protein purification, which is expensive and time-consuming, by substituting expression in situ with an in vitro transcription/translation kit. In summary, NAPPA arrays have been broadly employed in different studies improving knowledge about diseases and responses to treatments. Here, we review the principal advances and applications performed using this platform during the last years.

High-throughput proteomic characterization of plasma rich in growth factors (PRGF-Endoret)-derived fibrin clot interactome.

Plasma rich in growth factors (PRGF®-Endoret®) is an autologous technology that contains a set of proteins specifically addressed to wound healing and tissue regeneration. The scaffold formed by using this technology is a clot mainly composed of fibrin protein, forming a three-dimensional (3D) macroscopic network. This biomaterial is easily obtained by biotechnological means from blood and can be used in a range of situations to help wound healing and tissue regeneration. Although the main constituent of this clot is the fibrin scaffold, little is known about other proteins interacting in this clot that may act as adjuvants in the healing process. The aim of this study was to characterize the proteins enclosed by PRGF-Endoret scaffold, using a double-proteomic approach that combines 1D-SDS-PAGE approach followed by LC-MS/MS, and 2-DE followed by MALDI-TOF/TOF. The results presented here provide a description of the catalogue of key proteins in close contact with the fibrin scaffold. The obtained lists of proteins were grouped into families and networks according to gene ontology. Taken together, an enrichment of both proteins and protein families specifically involved in tissue regeneration and wound healing has been found.

Screening of protein-protein and protein-DNA interactions using microarrays: applications in biomedicine.

In this report, we focus on two different array-based technologies that enable large-scale screening of protein interactions. First, protein arrays focus on the identification of protein-protein interactions (PPIs). Second, DNA arrays have also evolved to explore the identification of protein-DNA interactions (PDIs), offering novel tools to control key biological processes. Such a tool is termed protein-binding DNA arrays (also protein-DNA arrays or protein-binding microarrays). These two array-based technologies share unrivaled screening capabilities and constitute valid approaches to address biological questions at the molecular level and, eventually, may be used in biomedical applications. Outstanding achievements of these technologies and their eventual application in biomedicine are discussed here, including the identification and characterization of biomarkers, screening of PPIs, detection of protein posttranslational modifications and biofluid profiling. Advantages and limitations of protein arrays, protein-binding arrays, and other proteomic technologies are also discussed here. Finally, we built a list of dedicated databases and on-line resources comprising updated information on human PPIs and PDIs that can serve as a toolbox for researchers in the field.

Evaluation of homo- and hetero-functionally activated glass surfaces for optimized antibody arrays.

Antibody arrays hold great promise for biomedical applications, but they are typically manufactured using chemically functionalized surfaces that still require optimization. Here, we describe novel hetero-functionally activated glass surfaces favoring oriented antibody binding for improved performance in protein microarray applications. Antibody arrays manufactured in our facility using the functionalization chemistries described here proved to be reproducible and stable and also showed good signal intensities. As a proof-of-principle of the glass surface functionalization protocols described in this article, we built antibody-based arrays functionalized with different chemistries that enabled the simultaneous detection of 71 human leukocyte membrane differentiation antigens commonly found in peripheral blood mononuclear cells. Such detection is specific and semi-quantitative and can be performed in a single assay under native conditions. In summary, the protocol described here, based on the use of antibody array technology, enabled the concurrent detection of a set of membrane proteins under native conditions in a specific, selective, and semi-quantitative manner and in a single assay.

Differential plant proteome analysis by isobaric tags for relative and absolute quantitation (iTRAQ).

Protein relative quantitation is one of the main targets in many proteomic experiments. Among the range of techniques available for both top-down and bottom-up approaches, isobaric tags for relative and absolute quantitation (iTRAQ) have gained positions within the top-rank techniques used for this purpose in the recent years. Briefly, each iTRAQ reagent consists of three different components: a reporter group (with a variable mass in the range of 114-117 amu), a balance group, and an amino-reactive group. The isobaric nature of iTRAQ-labeled peptides adds a signal to every peptide in the sample which is detectable in both MS and MS/MS spectra, thus enhancing the sensitivity of detection. During MS/MS, the reporter groups are released as singly charged ions with m/z ratios ranking from 114 to 117 amu, visible in the low mass region of MS/MS spectra. The iTRAQ technology can be used to analyze up to four different samples using the 4-plex kit (reporter groups 114-115 amu) or can be scaled up to eight different samples using the 8-plex kit (reporter groups 113-121 amu). In this chapter, we focus on the experimental procedures typically using 4-plex labeling, including tips leading to successful application of iTRAQ technology for the analysis of plant protein mixtures.

Suspension-cultured plant cells as a tool to analyze the extracellular proteome.

Suspension-cultured cells (SCC) are generally considered the most suitable cell systems to carry out scientific studies, including the extracellular proteome (secretome). SCC are initiated by transferring friable callus fragments into flasks containing liquid culture medium for cell biomass growth, and they are maintained in an orbital shaker to supply the sufficient oxygen that allows cell growth. SCC increase rapidly during the exponential phase and after 10-20 days (depending on the cell culture nature), the growth rate starts to decrease due to limitation of nutrients, and to maintain for decades these kinds of cell cultures is needed to transfer a portion of these SCC into a fresh culture medium. Despite the central role played by extracellular proteins in most processes that control growth and development, the secretome has been less well characterized than other subcellular compartments, meaning that our understanding of the cell wall physiology is still very limited. Useful proteomic tools have emerged in recent years to unravel metabolic network that occurs in cell walls. With the recent progress made in mass spectrometry technology, it has become feasible to identify proteins from a given organ, tissue, cells, or even a subcellular compartment. Compared with other methods used to isolate cell wall proteins, the spent medium of SCC provides a convenient, continuous, and reliable and unique source of extracellular proteins. Therefore, this biological system could be used as a large-scale cell culture from which these proteins can be secreted, easily separated from cells without cell disruption, and so, without any cytosolic contamination, easily recovered from the extracellular medium. This nondestructive cell wall proteome approach discloses a set of proteins that are specifically expressed in the remodelling of the cell wall architecture and stress defense.

Protein chimerism: novel source of protein diversity in humans adds complexity to bottom-up proteomics.

Three main molecular mechanisms are considered to contribute expanding the repertoire and diversity of proteins present in living organisms: first, at DNA level (gene polymorphisms and single nucleotide polymorphisms); second, at messenger RNA (pre-mRNA and mRNA) level including alternative splicing (also termed differential splicing or cis-splicing); finally, at the protein level mainly driven through PTM and specific proteolytic cleavages. Chimeric mRNAs constitute an alternative source of protein diversity, which can be generated either by chromosomal translocations or by trans-splicing events. The occurrence of chimeric mRNAs and proteins is a frequent event in cells from the immune system and cancer cells, mainly as a consequence of gene rearrangements. Recent reports support that chimeric proteins may also be expressed at low levels under normal physiological circumstances, thus, representing a novel source of protein diversity. Notably, recent publications demonstrate that chimeric protein products can be successfully identified through bottom-up proteomic analyses. Several questions remain unsolved, such as the physiological role and impact of such chimeric proteins or the potential occurrence of chimeric proteins in higher eukaryotic organisms different from humans. The occurrence of chimeric proteins certainly seems to be another unforeseen source of complexity for the proteome. It may be a process to take in mind not only when performing bottom-up proteomic analyses in cancer studies but also in general bottom-up proteomics experiments.

Protein-Protein Interactions: Gene Acronym Redundancies and Current Limitations Precluding Automated Data Integration.

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.

Uromodulin and α(1)-antitrypsin urinary peptide analysis to differentiate glomerular kidney diseases.

BACKGROUND/AIMS: Glomerular kidney disease (GKD) is suspected in patients based on proteinuria, but its diagnosis relies primarily on renal biopsy. We used urine peptide profiling as a noninvasive means to link GKD-associated changes to each glomerular entity. METHODS: Urinary peptide profiles of 60 biopsy-proven glomerular patients and 14 controls were analyzed by combining magnetic bead peptide enrichment, MALDI-TOF MS analysis, and ClinProTools v2.0 to select differential peptides. Tentative identification of the differential peptides was carried out by HPLC-MS/MS. RESULTS: The HPLC-MS/MS results suggest that uromodulin (UMOD; m/z: 1682, 1898 and 1913) and α(1)-antitrypsin (A1AT; m/z: 1945, 2392 and 2505) are differentially expressed urinary peptides that distinguish between GKD patients and healthy subjects. Low UMOD and high A1AT peptide abundance was observed in 80-92% of patients with GKD. Proliferative forms of GKD were distinguished from nonproliferative forms, based on a combination of UMOD and A1AT peptides. Nonproliferative forms correlated with higher A1AT peptide levels - focal segmental glomerulosclerosis was linked more closely to high levels of the m/z 1945 peptide than minimal change disease. CONCLUSION: We describe a workflow - urinary peptide profiling coupled with histological findings - that can be used to distinguish GKD accurately and noninvasively, particularly its nonproliferative forms.

Integrative analysis of the ubiquitin proteome isolated using Tandem Ubiquitin Binding Entities (TUBEs).

The successful use of proteasome inhibitors in clinical trials revealed the potential of the Ubiquitin Proteasome System for drug development. Protein remodeling through ubiquitylation is known to regulate the stability and activity of essential cellular factors through largely uncharacterized mechanisms. Here, we used Tandem repeated Ubiquitin Binding Entities (TUBEs) under non-denaturing conditions followed by mass spectrometry analysis to study global ubiquitylation events that may lead to the identification of potential drug targets. Using this approach we identified 643 proteins including known and unknown ubiquitin targets from human breast adenocarcinoma MCF7 cells treated with Adriamycin. Coherent with a global cellular response to this genotoxic insult, cellular factors identified are involved in protein synthesis, cellular transport, RNA post-transcriptional modification and signaling pathways regulating early stress responses. This includes components of large macromolecular complexes such as subunits and regulators of the proteasome, supporting the use of this method to characterize networks of molecular interactions coordinated by ubiquitylation. Further in vitro and in silico analysis confirmed that 84% of the total proteins identified here, are ubiquitylated. More importantly the enrichment of known biomarkers and targets for drug development, underlined the potential of this approach for the identification of this clinically relevant information. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Data Analysis Strategies for Protein Microarrays.

Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation.

Approaches for the study of cancer: towards the integration of genomics, proteomics and metabolomics.

Recent technological advances, combined with the development of bioinformatic tools, allow us to better address biological questions combining -omic approaches (i.e., genomics, metabolomics and proteomics). This novel comprehensive perspective addresses the identification, characterisation and quantitation of the whole repertoire of genes, proteins and metabolites occurring in living organisms. Here we provide an overview of recent significant advances and technologies used in genomics, metabolomics and proteomics. We also underline the importance and limits of mass accuracy in mass spectrometry-based -omics and briefly describe emerging types of fragmentation used in mass spectrometry. The range of instruments and techniques used to address the study of each -omic approach, which provide vast amounts of information (usually termed "high-throughput" technologies in the literature) is briefly discussed, including names, links and descriptions of the main databases, data repositories and resources used. Integration of multiple -omic results and procedures seems necessary. Therefore, an emerging challenge is the integration of the huge amount of data generated and the standardisation of the procedures and methods used. Functional data integration will lead to answers to unsolved questions, hopefully, applicable to clinical practice and management of patients.