Ariadne's ChemEffect and Pathway Studio knowledge base

Astrocytes express aberrant immunoglobulins as putative gatekeeper of astrocytes to neuronal progenitor conversion

Using multi-omics analyses including RNAseq, RT-PCR, RACE-PCR, and shotgun proteomic with enrichment strategies, we demonstrated that newborn rat astrocytes produce neural immunoglobulin constant and variable heavy chains as well as light chains. However, their edification is different from the ones found in B cells and they resemble aberrant immunoglobulins observed in several cancers. Moreover, the complete enzymatic V(D)J recombination complex has also been identified in astrocytes. In addition, the constant heavy chain is also present in adult rat astrocytes, whereas in primary astrocytes from human fetus we identified constant and variable kappa chains as well as the substitution lambda chains known to be involved in pre-B cells. To gather insights into the function of these neural IgGs, CRISPR-Cas9 of IgG2B constant heavy chain encoding gene (Igh6), IgG2B overexpression, proximal labeling of rat astrocytes IgG2B and targets identification through 2D gels were performed. In Igh6 KO astrocytes, overrepresentation of factors involved in hematopoietic cells, neural stem cells, and the regulation of neuritogenesis have been identified. Moreover, overexpression of IgG2B in astrocytes induces the CRTC1-CREB-BDNF signaling pathway known to be involved in gliogenesis, whereas Igh6 KO triggers the BMP/YAP1/TEAD3 pathway activated in astrocytes dedifferentiation into neural progenitors. Proximal labeling experiments revealed that IgG2B is N-glycosylated by the OST complex, addressed to vesicle membranes containing the ATPase complex, and behaves partially like CD98hc through its association with LAT1. These experiments also suggest that proximal IgG2B-LAT1 interaction occurs concomitantly with MACO-1 and C2CD2L, at the heart of a potentially novel cell signaling platform. Finally, we demonstrated that these chains are synthesized individually and associated to recognize specific targets. Indeed, intermediate filaments Eif4a2 and Pdia6 involved in astrocyte fate constitute targets for these neural IgGs. Taken together, we hypothese that neural aberrant IgG chains may act as gatekeepers of astrocytes' fate.

Integrative analysis to explore the biological association between environmental skin diseases and ambient particulate matter

Although numerous experimental studies have suggested a significant association between ambient particulate matter (PM) and respiratory damage, the etiological relationship between ambient PM and environmental skin diseases is not clearly understood. Here, we aimed to explore the association between PM and skin diseases through biological big data analysis. Differential gene expression profiles associated with PM and environmental skin diseases were retrieved from public genome databases. The co-expression among them was analyzed using a text-mining-based network analysis software. Activation/inhibition patterns from RNA-sequencing data performed with PM_2.5-treated normal human epidermal keratinocytes (NHEK) were overlapped to select key regulators of the analyzed pathways. We explored the adverse effects of PM on the skin and attempted to elucidate their relationships using public genome data. We found that changes in upstream regulators and inflammatory signaling networks mediated by MMP-1, MMP-9, PLAU, S100A9, IL-6, and S100A8 were predicted as the key pathways underlying PM-induced skin diseases. Our integrative approach using a literature-based co-expression analysis and experimental validation not only improves the reliability of prediction but also provides assistance to clarify underlying mechanisms of ambient PM-induced dermal toxicity that can be applied to screen the relationship between other chemicals and adverse effects.

Apoptotic effects of human amniotic fluid mesenchymal stem cells conditioned medium on human MCF-7 breast cancer cell line

Introduction

Breast cancer, as the most common malignancy among women, is shown to have a high mortality rate and resistance to chemotherapy. Research has shown the possible inhibitory role of Mesenchymal stem cells in curing cancer. Thus, the present work used human amniotic fluid mesenchymal stem cell-conditioned medium (hAFMSCs-CM) as an apoptotic reagent on the human MCF-7 breast cancer cell line.

Methods

Conditioned medium (CM) was prepared from hAFMSCs. After treating MCF-7 cells with CM, a number of analytical procedures (MTT, real-time PCR, western blot, and flow cytometry) were recruited to evaluate the cell viability, Bax and Bcl-2 gene expression, P53 protein expression, and apoptosis, respectively. Human fibroblast cells (Hu02) were used as the negative control. In addition, an integrated approach to meta-analysis was performed.

Results

The MCF-7 cells' viability was decreased significantly after 24 hours (P < 0.0001) and 72 hours (P < 0.05) of treatment. Compared with the control cells, Bax gene's mRNA expression increased and Bcl-2's mRNA expression decreased considerably after treating for 24 hours with 80% hAFMSCs-CM (P = 0.0012, P < 0.0001, respectively); an increasing pattern in P53 protein expression could also be observed. The flow cytometry analysis indicated apoptosis. Results from literature mining and the integrated meta-analysis showed that hAFMSCs-CM is able to activate a molecular network where Bcl2 downregulation stands in harmony with the upregulation of P53, EIF5A, DDB2, and Bax, leading to the activation of apoptosis.

Conclusion

Our finding demonstrated that hAFMSCs-CM presents apoptotic effect on MCF-7 cells; therefore, the application of hAFMSCs-CM, as a therapeutic reagent, can suppress breast cancer cells' viabilities and induce apoptosis.

Splice-disrupt genomic variants in prostate cancer

Background

Splice-disrupt genomic variants are one of the causes of cancer-causing errors in gene expression. Little is known about splice-disrupt genomic variants.

Methods and results

Here, pattern of splice-disrupt variants was investigated using 21,842,764 genomic variants in different types of prostate cancer. A particular attention was paid to genomic locations of splice-disrupt variants on target genes. HLA-A in prostate cancer, MSR1 in familial prostate cancer, and EGFR in both castration-resistant prostate cancer and metastatic castration-resistant had the highest allele frequencies of splice-disrupt variations. Some splice-disrupt variants, located on coding sequences of NCOR2, PTPRC, and CRP, were solely present in the advanced metastatic castration-resistant prostate cancer. High-risk splice-disrupt variants were identified based on computationally calculated Polymorphism Phenotyping (PolyPhen), Sorting Intolerant From Tolerant (SIFT), and Genomic Evolutionary Rate Profiling (GERP) + + scores as well as the recorded clinical significance in dbSNP database of NCBI. Functional annotation of damaging splice-disrupt variants highlighted important cancer-associated functions, including endocrine resistance, lipid metabolic process, steroid metabolic process, regulation of mitotic cell cycle, and regulation of metabolic process. This is the first study that profiles the splice-disrupt genomic variants and their target genes in prostate cancer. Literature mining based variant analysis highlighted the importance of rs1800716 variant, located on the CYP2D6 gene, involved in a range of important functions, such as RNA spicing, drug interaction, death, and urotoxicity.

Conclusions

This is the first study that profiles the splice-disrupt genomic variants and their target genes in different types of prostate cancer. Unravelling alternative splicing opens a new avenue towards the establishment of new diagnostic and prognostic markers for prostate cancer progression and metastasis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11033-022-07257-9.

Path to Clonal Theranostics in Luminal Breast Cancers

Integrating tumor heterogeneity in the drug discovery process is a key challenge to tackle breast cancer resistance. Identifying protein targets for functionally distinct tumor clones is particularly important to tailor therapy to the heterogeneous tumor subpopulations and achieve clonal theranostics. For this purpose, we performed an unsupervised, label-free, spatially resolved shotgun proteomics guided by MALDI mass spectrometry imaging (MSI) on 124 selected tumor clonal areas from early luminal breast cancers, tumor stroma, and breast cancer metastases. 2868 proteins were identified. The main protein classes found in the clonal proteome dataset were enzymes, cytoskeletal proteins, membrane-traffic, translational or scaffold proteins, or transporters. As a comparison, gene-specific transcriptional regulators, chromatin related proteins or transmembrane signal receptor were more abundant in the TCGA dataset. Moreover, 26 mutated proteins have been identified. Similarly, expanding the search to alternative proteins databases retrieved 126 alternative proteins in the clonal proteome dataset. Most of these alternative proteins were coded mainly from non-coding RNA. To fully understand the molecular information brought by our approach and its relevance to drug target discovery, the clonal proteomic dataset was further compared to the TCGA breast cancer database and two transcriptomic panels, BC360 (nanoString^®) and CDx (Foundation One^®). We retrieved 139 pathways in the clonal proteome dataset. Only 55% of these pathways were also present in the TCGA dataset, 68% in BC360 and 50% in CDx. Seven of these pathways have been suggested as candidate for drug targeting, 22 have been associated with breast cancer in experimental or clinical reports, the remaining 19 pathways have been understudied in breast cancer. Among the anticancer drugs, 35 drugs matched uniquely with the clonal proteome dataset, with only 7 of them already approved in breast cancer. The number of target and drug interactions with non-anticancer drugs (such as agents targeting the cardiovascular system, metabolism, the musculoskeletal or the nervous systems) was higher in the clonal proteome dataset (540 interactions) compared to TCGA (83 interactions), BC360 (419 interactions), or CDx (172 interactions). Many of the protein targets identified and drugs screened were clinically relevant to breast cancer and are in clinical trials. Thus, we described the non-redundant knowledge brought by this clone-tailored approach compared to TCGA or transcriptomic panels, the targetable proteins identified in the clonal proteome dataset, and the potential of this approach for drug discovery and repurposing through drug interactions with antineoplastic agents and non-anticancer drugs.

On-tissue spatially resolved glycoproteomics guided by N-glycan imaging reveal global dysregulation of canine glioma glycoproteomic landscape

Here, we present an approach to identify N-linked glycoproteins and deduce their spatial localization using a combination of matrix-assisted laser desorption ionization (MALDI) N-glycan mass spectrometry imaging (MSI) and spatially resolved glycoproteomics. We subjected glioma biopsies to on-tissue PNGaseF digestion and MALDI-MSI and found that the glycan HexNAc4-Hex5-NeuAc2 was predominantly expressed in necrotic regions of high-grade canine gliomas. To determine the underlying sialo-glycoprotein, various regions in adjacent tissue sections were subjected to microdigestion and manual glycoproteomic analysis. Results identified haptoglobin as the protein associated with HexNAc4-Hex5-NeuAc2, thus directly linking glycan imaging with intact glycopeptide identification. In total, our spatially resolved glycoproteomics technique identified over 400 N-, O-, and S- glycopeptides from over 30 proteins, demonstrating the diverse array of glycosylation present on the tissue slices and the sensitivity of our technique. Ultimately, this proof-of-principle work demonstrates that spatially resolved glycoproteomics greatly complement MALDI-MSI in understanding dysregulated glycosylation.

Therapeutic anti-glioma effect of the combined action of PCSK inhibitor with the anti-tumoral factors secreted by Poly (I:C)-stimulated macrophages

Macrophages plasticity is a key feature in cancer progression. Neoplastic cells can alter their immune functions and orient them into a pro-tumoral phenotype. In this context, we developed a new therapeutic strategy to switch macrophages phenotype and reactivate their anti-tumoral functions. We showed a dual activity of a proprotein convertases inhibitor as anti-glioma drug and anti-tumoral macrophages' reactivation drug. Proprotein convertases are proteases that cleave proteins into functional proteins. Several of their substrates are involved in tumorigenesis and immunosuppression. We combine here proprotein convertases inhibitor with Poly (I:C), a TLR3 ligand, to increase the anti-tumoral activity of macrophages. With mass spectrometry-based proteomics, system biology, combined with biological assays, we established that a stimulation of macrophages with Poly (I:C) increased their secretion of pro-inflammatory cytokines and anti-tumoral factors. 3D invasion assay showed the efficacy of these anti-tumoral factors against mixed glioma cells and macrophages spheroids. Besides, immunofluorescence and proliferation assays showed an additive effect of the proprotein convertases inhibitor and the anti-tumoral factors secreted by Poly (I:C)-treated macrophages on both anti-glioma activity and macrophages anti-tumoral orientation directly in tumor microenvironment, leading to an innovative glioma therapy.

Surfaceome Proteomic of Glioblastoma Revealed Potential Targets for Immunotherapy

Glioblastoma (GBM) is the most common and devastating malignant brain tumor in adults. The mortality rate is very high despite different treatments. New therapeutic targets are therefore highly needed. Cell-surface proteins represent attractive targets due to their accessibility, their involvement in essential signaling pathways, and their dysregulated expression in cancer. Moreover, they are potential targets for CAR-based immunotherapy or mRNA vaccine strategies. In this context, we investigated the GBM-associated surfaceome by comparing it to astrocytes cell line surfaceome to identify new specific targets for GBM. For this purpose, biotinylation of cell surface proteins has been carried out in GBM and astrocytes cell lines. Biotinylated proteins were purified on streptavidin beads and analyzed by shotgun proteomics. Cell surface proteins were identified with Cell Surface Proteins Atlas (CSPA) and Gene Ontology enrichment. Among all the surface proteins identified in the different cell lines we have confirmed the expression of 66 of these in patient’s glioblastoma using spatial proteomic guided by MALDI-mass spectrometry. Moreover, 87 surface proteins overexpressed or exclusive in GBM cell lines have been identified. Among these, we found 11 specific potential targets for GBM including 5 mutated proteins such as RELL1, CYBA, EGFR, and MHC I proteins. Matching with drugs and clinical trials databases revealed that 7 proteins were druggable and under evaluation, 3 proteins have no known drug interaction yet and none of them are the mutated form of the identified proteins. Taken together, we discovered potential targets for immune therapy strategies in GBM.

An Integrative Analysis of The Micro-RNAs Contributing in Stemness, Metastasis and B-Raf Pathways in Malignant Melanoma and Melanoma Stem Cell

Objective

Epithelial-mesenchymal transition (EMT) and the stemness potency in association with BRAF mutation are in dispensable to the progression of melanoma. Recently, microRNAs (miRNAs) have been introduced as the regulator of a multitude of oncogenic functions in most of tumors. Therefore identifying and interpreting the expression patterns of these miRNAs is essential. The present study sought to find common miRNAs regulating all three important pathways in melanoma development.

Materials and Methods

In this experimental study, 18 miRNAs that importantly contribute to EMT and have a role in regulating self-renewal and the BRAF pathway were selected based on current literature and cross-analysis with available databases. Subsequently, their expression patterns were evaluated in 20 melanoma patients, normal tissues, serum from patients and control subjects, and melanospheres. Pattern discovery and integrative regulatory network analysis were used to find the most important miRNAs in melanoma progression.

Results

Among 18 selected miRNAs, miR-205, -141, -203, -15b, and -9 were differentially expressed in tumor samples than normal tissues. Among them, miR-205, -15b, and -9 significantly expressed in serum samples and healthy donors. Attribute Weighting and decision trees (DT) analysis presented evidence that the combination of miR-205, -203, -9, and -15b can regulate self-renewal and EMT process, by affecting CDH1, CCND1, and VEGF expression.

Conclusion

We suggested here that miR-205, -15b, -203, -9 pattern as the key miRNAs linked to melanoma status, the pluripotency, proliferation, and motility of malignant cells. However, further investigations are required to find the mechanisms underlying the combinatory effects of the above mentioned miRNAs.

Bioinformatics Analysis of Allele Frequencies and Expression Patterns of ACE2, TMPRSS2 and FURIN in Different Populations and Susceptibility to SARS-CoV-2

The virus responsible for the COVID-19 global health crisis, SARS-CoV-2, has been shown to utilize the ACE2 protein as an entry point to its target cells. The virus has been shown to rely on the actions of TMPRSS2 (a serine protease), as well as FURIN (a peptidase), for the critical priming of its spike protein. It has been postulated that variations in the sequence and expression of SARS-CoV-2's receptor (ACE2) and the two priming proteases (TMPRSS2 and FURIN) may be critical in contributing to SARS-CoV-2 infectivity. This study aims to examine the different expression levels of FURIN in various tissues and age ranges in light of ACE2 and TMPRSS2 expression levels using the LungMAP database. Furthermore, we retrieved expression quantitative trait loci (eQTLs) of the three genes and their annotation. We analyzed the frequency of the retrieved variants in data from various populations and compared it to the Egyptian population. We highlight FURIN's potential interplay with the immune response to SARS-CoV-2 and showcase a myriad of variants of the three genes that are differentially expressed across populations. Our findings provide insights into potential genetic factors that impact SARS-CoV-2 infectivity in different populations and shed light on the varying expression patterns of FURIN.

In-depth proteomics analysis of sentinel lymph nodes from individuals with endometrial cancer

Endometrial cancer (EC) is one of the most common gynecological cancers worldwide. Sentinel lymph node (SLN) status could be a major prognostic factor in evaluation of EC, but several prospective studies need to be performed. Here we report an in-depth proteomics analysis showing significant variations in the SLN protein landscape in EC. We show that SLNs are correlated to each tumor grade, which strengthens evidence of SLN involvement in EC. A few proteins are overexpressed specifically at each EC tumor grade and in the corresponding SLN. These proteins, which are significantly variable in both locations, should be considered potential markers of overall survival. Five major proteins for EC and SLN (PRSS3, PTX3, ASS1, ALDH2, and ANXA1) were identified in large-scale proteomics and validated by immunohistochemistry. This study improves stratification and diagnosis of individuals with EC as a result of proteomics profiling of SLNs.

A Bioinformatics Systems Biology Analysis of the Current Oral Proteomic Biomarkers and Implications for Diagnosis and Treatment of External Root Resorption

External root resorption (ERR) is a silent destructive phenomenon detrimental to dental health. ERR may have multiple etiologies such as infection, inflammation, traumatic injuries, pressure, mechanical stimulations, neoplastic conditions, systemic disorders, or idiopathic causes. Often, if undiagnosed and untreated, ERR can lead to the loss of the tooth or multiple teeth. Traditionally, clinicians have relied on radiographs and cone beam computed tomography (CBCT) images for the diagnosis of ERR; however, these techniques are not often precise or definitive and may require exposure of patients to more ionizing radiation than necessary. To overcome these shortcomings, there is an immense need to develop non-invasive approaches such as biomarker screening methods for rapid and precise diagnosis for ERR. In this review, we performed a literature survey for potential salivary or gingival crevicular fluid (GCF) proteomic biomarkers associated with ERR and analyzed the potential pathways leading to ERR. To the best of our knowledge, this is the first proteomics biomarker survey that connects ERR to body biofluids which represents a novel approach to diagnose and even monitor treatment progress for ERR.

Secretome Analysis of Inductive Signals for BM-MSC Transdifferentiation into Salivary Gland Progenitors

Severe dry mouth in patients with Sjögren's Syndrome, or radiation therapy for patients with head and neck cancer, significantly compromises their oral health and quality of life. The current clinical management of xerostomia is limited to palliative care as there are no clinically-proven treatments available. Previously, our studies demonstrated that mouse bone marrow-derived mesenchymal stem cells (mMSCs) can differentiate into salivary progenitors when co-cultured with primary salivary epithelial cells. Transcription factors that were upregulated in co-cultured mMSCs were identified concomitantly with morphological changes and the expression of acinar cell markers, such as α-amylase (AMY1), muscarinic-type-3-receptor(M3R), aquaporin-5(AQP5), and a ductal cell marker known as cytokeratin 19(CK19). In the present study, we further explored inductive molecules in the conditioned media that led to mMSC reprogramming by high-throughput liquid chromatography with tandem mass spectrometry and systems biology. Our approach identified ten differentially expressed proteins based on their putative roles in salivary gland embryogenesis and development. Additionally, systems biology analysis revealed six candidate proteins, namely insulin-like growth factor binding protein-7 (IGFBP7), cysteine-rich, angiogenetic inducer, 61(CYR61), agrin(AGRN), laminin, beta 2 (LAMB2), follistatin-like 1(FSTL1), and fibronectin 1(FN1), for their potential contribution to mMSC transdifferentiation during co-culture. To our knowledge, our study is the first in the field to identify soluble inductive molecules that drive mMSC into salivary progenitors, which crosses lineage boundaries.

Epigenetic Studies Revealed a Ghost Proteome in PC1/3 KD Macrophages under Antitumoral Resistance Induced by IL-10

Our previous investigation on macrophages has allowed us to show that the inhibition of the enzyme proprotein convertase (PC1/3) controls the activation of macrophages. We demonstrated that PC1/3 knockdown (KD) in macrophages exhibits an increased secretion of proinflammatory and antitumoral factors. In this biological context, we assessed the presence of histone modifications and the presence and contribution of a "ghost proteome" in these macrophages. We identified a set of alternative proteins (AltProts) that have a key role in the regulation of various signaling pathways. In this study, to further investigate the underlying mechanisms involved in the resistance of PC1/3-KD macrophages to anti-inflammatory stimuli, we have conducted a proteomic system biology study to assess the epigenome variation, focusing on histone modifications. Results from our study have indicated the presence of significant variations in histone modifications along with the identification of 28 AltProts, which can be correlated with antitumoral resistance under IL-10 stimulation. These findings highlight a key role of altered epigenome histone modifications in driving resistance and indicate that like the reference proteins, AltProts can have a major impact in the field of epigenetics and regulation of gene expression, as shown in our results.

Effects of the Oncoprotein PAX3-FOXO1 on Modulation of Exosomes Function and Protein Content: Implications on Oxidative Stress Protection and Enhanced Plasticity

Rhabdomyosarcoma (RMS) is a highly malignant soft tissue sarcoma classified into two major histologic subtypes: embryonal (ERMS) and alveolar (ARMS). ARMS subtype is clinically more aggressive, and characterized by an oncogenic fusion protein PAX3-FOXO1 (P3F) that drives oncogenic cellular properties. To understand the role of the fusion oncoprotein in paracrine signaling, we focused on secreted exosomes, which have been demonstrated to contribute to metastasis in multiple tumor types. Advanced Proteomics-bioinformatics analysis of the protein cargo of exosomes isolated from C2C12 myoblasts transduced with P3F fusion gene revealed 52 deregulated proteins compared to control cells, with 26 enriched and 26 depleted proteins. Using both PANTHER gene classification and Ingenuity Pathway Analysis (IPA) software, we found that the main biological processes in which the 52 deregulated proteins are involved, include “catalytic activity,” “binding,” “metabolic process,” and “cellular process.” The pathways engaging the 26 enriched proteins include the “14-3-3 mediated signaling,” “cell cycle,” and “ERK5, VEGF, IGF1,and p70S6K signaling.” Furthermore, the main nodes in which deregulated exosome proteins and miRNAs intersected revealed pathways conferring protection from stress and promoting plasticity. Based on the bioinformatics analysis and the altered exosome proteome profile, we performed biochemical functional analysis to study the diverse properties of these exosomes where angiogenesis, stemness, and anti-oxidative stress properties were validated using different platforms. P3F-modulated exosomes activated ERK, 4-EBP1, and MMP-2 in recipient cells, and enhanced angiogenesis and stemness. In addition, P3F led to lower cellular reactive oxygen species levels and enhanced resistance against oxidative stress; and treatment of stromal cells with P3F-modulated exosomes also conferred protection against exogenous oxidative stress. Our findings highlight the role of P3F fusion protein in modulating exosome cargo to confer a protective effect on recipient cells against oxidative stress and to promote plasticity and survival, potentially contributing to the known aggressive phenotype of the fusion gene-positive subtype of RMS.

Protein Expression Analysis of an In Vitro Murine Model of Prostate Cancer Progression: Towards Identification of High-Potential Therapeutic Targets

Background: Prostate cancer (PC) is the most frequently diagnosed cancer among men worldwide. The poor prognosis of PC is largely due to late diagnosis of the disease when it has progressed to advanced stages marked by androgen-independence. We interrogated proteomic signatures that embody the transition of PC from an androgen-dependent (AD) to an androgen-independent (AI) state. Methods: We have previously established AD and AI murine PC cell lines, PLum-AD and PLum-AI, respectively, which recapitulate primary and progressive PC at phenotypic and subcellular levels. We statistically surveyed global protein expression profiles in these cell lines. Differential profiles were functionally interrogated by pathways and protein–protein interaction network analyses. Results: Protein expression pattern analysis revealed a total of 683 proteins, among which 99 were significantly differentially altered in PLum-AI cells as compared to PLum-AD cells (45 increased and 54 decreased). Principal component analysis (PCA) revealed that the two different cell lines clearly separated apart, indicating a significant proteome expression difference between them. Four of the proteins (vimentin, catalase, EpCAM, and caspase 3) that were differentially expressed in PLum-AI cells compared to PLum-AD cells were subjected to biochemical validation by Western blotting. Biological process gene ontology (GO) analysis of the differentially expressed proteins demonstrated enrichment of biological functions and pathways in PLum-AI cells that are central to PI3 kinase and androgen receptor pathways. Besides, other relevant biological processes that are enriched in PLum-AI cells included cell adhesion and cell migration processes, cell and DNA damage, apoptosis, and cell cycle regulation. Conclusions: Our protein expression analysis of a murine in vitro model of PC progression identified differential protein spots that denote this progression and that comprise high-potential targets for early treatment of PC with a personalized patient-specific approach. Efforts are underway to functionally assess the potential roles of these proteins as therapeutic targets for PC progression.

Transcriptomic profiling of trophoblast fusion using BeWo and JEG-3 cell lines

In human placenta, alteration in trophoblast differentiation has a major impact on placental maintenance and integrity. However, little is known about the mechanisms that control cytotrophoblast fusion. The BeWo cell line is used to study placental function, since it forms syncytium and secretes hormones after treatment with cAMP or forskolin. In contrast, the JEG-3 cell line fails to undergo substantial fusion. Therefore, BeWo and JEG-3 cells were used to identify a set of genes responsible for trophoblast fusion. Cells were treated with forskolin for 48 h to induce fusion. RNA was extracted, hybridised to Affymetrix HuGene ST1.0 arrays and analysed using system biology. Trophoblast differentiation was evaluated by real-time PCR and immunocytochemistry analysis. Moreover, some of the identified genes were validated by real-time PCR and their functional capacity was demonstrated by western blot using phospho-specific antibodies and CRISPR/cas9 knockdown experiments. Our results identified a list of 32 altered genes in fused BeWo cells compared to JEG-3 cells after forskolin treatment. Among these genes, four were validated by RT-PCR, including salt-inducible kinase 1 (SIK1) gene which is specifically upregulated in BeWo cells upon fusion and activated after 2 min with forskolin. Moreover, silencing of SIK1 completely abolished the fusion. Finally, SIK1 was shown to be at the center of many biological and functional processes, suggesting that it might play a role in trophoblast differentiation. In conclusion, this study identified new target genes implicated in trophoblast fusion. More studies are required to investigate the role of these genes in some placental pathology.

The Role of a Proprotein Convertase Inhibitor in Reactivation of Tumor-Associated Macrophages and Inhibition of Glioma Growth

Tumors are characterized by the presence of malignant and non-malignant cells, such as immune cells including macrophages, which are preponderant. Macrophages impact the efficacy of chemotherapy and may lead to drug resistance. In this context and based on our previous work, we investigated the ability to reactivate macrophages by using a proprotein convertases inhibitor. Proprotein convertases process immature proteins into functional proteins, with several of them having a role in immune cell activation and tumorigenesis. Macrophages were treated with a peptidomimetic inhibitor targeting furin, PC1/3, PC4, PACE4, and PC5/6. Their anti-glioma activity was analyzed by mass spectrometry-based proteomics and viability assays in 2D and 3D in vitro cultures. Comparison with temozolomide, the drug used for glioma therapy, established that the inhibitor was more efficient for the reduction of cancer cell density. The inhibitor was also able to reactivate macrophages through the secretion of several immune factors with antitumor properties. Moreover, two proteins considered as good glioma patient survival indicators were also identified in 3D cultures treated with the inhibitor. Finally, we established that the proprotein convertases inhibitor has a dual role as an anti-glioma drug and anti-tumoral macrophage reactivation drug. This strategy could be used together with chemotherapy to increase therapy efficacy in glioma.

PC1/3 KD Macrophages Exhibit Resistance to the Inhibitory Effect of IL-10 and a Higher TLR4 Activation Rate, Leading to an Anti-Tumoral Phenotype

During tumorigenesis, macrophages are recruited by tumors and orientated towards a pro-tumoral phenotype. One of the main anti-tumoral immunotherapy consists of their re-polarization in an anti-tumoral phenotype. We have demonstrated that the inhibition of proprotein convertase 1/3 combined with TLR4 activation in macrophages is a promising strategy. These macrophages display pro-inflammatory and anti-tumoral phenotypes. A hallmark is a stronger activation of the pro-inflammatory NFKB pathway. We believe that this can be explained by a modification of TLR4 expression at the cell surface or MYD88 cleavage since it exhibits a potential cleavage site for proprotein convertases. We tested these hypotheses through immunofluorescence and Western blot experiments. A proteomics study was also performed to test the sensitivity of these macrophages to IL-10. We demonstrated that these macrophages treated with LPS showed a quicker re-expression of TLR4 at the cell surface. The level of MYD88 was also higher when TLR4 was internalized. Moreover, these macrophages were resistant to the pro-tumoral effect of IL-10 and still produced pro-inflammatory factors. This established that the sensitivity to anti-inflammatory molecules and the length of TLR4 desensitization were reduced in these macrophages. Therefore, during antitumoral immunotherapy, a repeated stimulation of TLR4 may reactivate PC1/3 inhibited macrophages even in an anti-inflammatory environment.

Proteomic Profiling of Rhabdomyosarcoma-Derived Exosomes Yield Insights into Their Functional Role in Paracrine Signaling

Exosomes are important intercellular communication vehicles, secreted into body fluids by multiple cell types, including tumor cells. They have been demonstrated to contribute to the metastatic progression of tumor cells through paracrine signaling. Tumor exosomes contain intact and functional proteins, mRNA and miRNA that may alter the cellular environment to favor tumor growth. We evaluated the protein cargo of exosomes derived from the childhood tumor rhabdomyosarcoma (RMS) and the molecular pathways they are implicated in to decipher their role in the progression of this aggressive disease. We conducted a mass spectrometry analysis of exosome content isolated from five RMS cell lines: three of embryonal RMS (ERMS) and two of alveolar RMS (ARMS) histology and verified results by multiple reaction monitoring and western blot analyses. Results revealed 161 common proteins in ERMS-derived exosomes and 122 common proteins in ARMS-derived exosomes, of which 81 proteins were common to both subtypes. Using both PANTHER gene classification and Pathway Studio software, we assessed the perturbed biological processes and altered pathways in which the exosomal proteins are involved. The 81 commonly expressed proteins included those involved in "cell-signaling," "cell-movement," and "cancer." Pathways engaging the identified proteins revealed 37 common pathways including "integrin signaling pathway," "inflammation mediated by chemokine and cytokine signaling pathway," and "angiogenesis." Finally, a comparison of exosomal proteins of RMS cells with publicly available datasets from other cancer cells revealed that 36 proteins are specific and endogenous to the RMS-exosomes. Taken together, our results reveal that RMS-derived exosomes carry a protein cargo that contributes to conserved cellular signaling networks across multiple cell lines, and we also identify RMS exosome-specific proteins that should be further evaluated as possible novel biomarkers for this tumor.

Mapping Spatiotemporal Microproteomics Landscape in Experimental Model of Traumatic Brain Injury Unveils a link to Parkinson's Disease

Traumatic brain injury (TBI) represents a major health concerns with no clinically-approved FDA drug available for therapeutic intervention. Several genomics and neuroproteomics studies have been employed to decipher the underlying pathological mechanisms involved that can serve as potential neurotherapeutic targets and unveil a possible underlying relation of TBI to other secondary neurological disorders. In this work, we present a novel high throughput systems biology approach using a spatially resolved microproteomics platform conducted on different brain regions in an experimental rat model of moderate of controlled cortical injury (CCI) at a temporal pattern postinjury (1 day, 3 days, 7 days, and 10 days). Mapping the spatiotemporal landscape of signature markers in TBI revealed an overexpression of major protein families known to be implicated in Parkinson's disease (PD) such as GPR158, HGMB1, synaptotagmin and glutamate decarboxylase in the ipsilateral substantia nigra. In silico bioinformatics docking experiments indicated the potential correlation between TBI and PD through alpha-synuclein. In an in vitro model, stimulation with palmitoylcarnitine triggered an inflammatory response in macrophages and a regeneration processes in astrocytes which also further confirmed the in vivo TBI proteomics data. Taken together, this is the first study to assess the microproteomics landscape in TBI, mainly in the substantia nigra, thus revealing a potential predisposition for PD or Parkinsonism post-TBI.

Ontology mapping for semantically enabled applications

In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an increasing amount and variety of data. This is particularly important for realising the full potential of semantically enabled or enriched applications and for meaningful insights, such as drug discovery, using machine-learning technologies. We discuss challenges and solutions for better ontology mappings, as well as how to select ontologies before their application. In addition, we describe tools and algorithms for ontology mapping, including evaluation of tool capability and quality of mappings. Finally, we outline the requirements for an ontology mapping service (OMS) and the progress being made towards implementation of such sustainable services.

Non-coding and coding genomic variants distinguish prostate cancer, castration-resistant prostate cancer, familial prostate cancer, and metastatic castration-resistant prostate cancer from each other

A considerable number of deposited variants has provided new possibilities for knowledge discovery in different types of prostate cancer. Here, we analyzed variants located on 3'UTR, 5'UTR, CDs, Intergenic, and Intronic regions in castration-resistant prostate cancer (8496 variants), familial prostate cancer (3241 variants), metastatic castration-resistant prostate cancer (3693 variants), and prostate cancer (16599 variants). Chromosome regions 10p15-p14 and 2p13 were highly enriched (P < 0.00001) for variants located in 3'UTR, 5'UTR, CDs, intergenic, and intronic regions in castration-resistant prostate cancer. In contrast, 10p15-p14, 10q23.3, 12q13.11, 13q12.3, 1q25, and 8p22 regions were enriched (P < 0.001) in familial prostate cancer. In metastatic castration-resistant prostate cancer, 10p15-p14, 10q23.3, 11q22-q23, 14q21.1, and 14q32.13 were highly variant regions (P < 0.001). Chromosome 2 and chromosome 1 hosted many enriched variant regions. AKR1C3, BRCA1, BRCA2, CHGA, CYP19A1, HOXB13, KLK3, and PTEN contained the highest number of 3'UTR, 5'UTR, CDs, Intergenic, and Intronic variants. Network analysis showed that these genes are upstream of important functions including prostate gland development, tumor recurrence, prostate cancer-specific survival, tumor progression, cancer mortality, long-term survival, cancer recurrence, angiogenesis, and AR. Interestingly, all of EGFR, JAK2, NR3C1, PDZD2, and SEMA3C genes had single nucleotide polymorphisms (SNP) in castration-resistant prostate cancer, consistent with high selection pressure on these genes during drug treatment and consequent resistance. High occurrence of variants in 3'UTRs suggests the importance of regulatory variants in different types of prostate cancer; an area that has been neglected compared with coding variants. This study provides a comprehensive overview of genomic regions contributing to different types of prostate cancer.

Functional pathways associated with human carotid atheroma: a proteomics analysis

Advances in large-scale analysis are becoming very useful in understanding health and disease. Here, we used high-throughput mass spectrometry to identify differentially expressed proteins between early and advanced lesions. Carotid endarterectomy samples were collected and dissected into early and advanced atherosclerotic lesion portions. Proteins were extracted and subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Differentially expressed proteins were identified and verified using multiple reaction monitoring (MRM), on which advanced systems biology and enrichment analyses were performed. The identified proteins were further compared to the transcriptomic data of 32 paired samples obtained from early and advanced atherosclerotic lesions. A total of 95 proteins were upregulated, and 117 proteins were downregulated in advanced lesions compared to early atherosclerotic lesions (p < 0.05). The upregulated proteins were associated with proatherogenic processes, whereas downregulated proteins were involved in extracellular matrix organization and vascular smooth muscle cytoskeleton. Many of the identified proteins were linked to various "upstream regulators", among which TGFβ had the highest connections. Specifically, a total of 19 genes were commonly upregulated, and 30 genes were downregulated at the mRNA and protein levels. These genes were involved in vascular smooth muscle cell activity, for which enriched transcription factors were identified. This study deciphers altered pathways in atherosclerosis and identifies upstream regulators that could be candidate targets for treatment.

Transcriptomic Analysis of Cholestatic Compounds In Vitro

Drug-induced cholestasis is one of the most severe manifestations of drug-induced liver injury. Drug-induced cholestasis is characterized by an accumulation of endogenous metabolites normally excreted in the bile such as bile salts, cholesterol, bilirubin, or drug metabolites. The possibility to determine early in the drug development process whether a compound presents a risk of inducing drug-induced cholestasis is key information. Since preclinical repeated dose toxicity studies have limited predictive value, large efforts in identifying alternative in vitro models with improved prediction are being made. One of the best current models for in vitro human liver is primary human hepatocytes, and we recently reported that primary human hepatocytes can be kept as long-term cultures in 2D-sandwich configuration when regularly renewing the Matrigel overlay, thereby making the model useful for repeat exposure-related toxicities, as well as for the study of adaptive responses. This primary human hepatocyte culture system combined with transcriptomics carries the future promise to identify individual gene expression profiles predictive of increased drug-induced cholestasis risk.This chapter describes the various steps for culturing and exposing primary human hepatocytes to drugs during long-term 2D-sandwich culture, performing RNA extraction, gene chip assay and selecting hepatotoxic signature using the IPA software and highlighting genes involved in bile acid homeostasis.

Integrated Omics: Tools, Advances, and Future Approaches

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

Genomic alterations during p53-dependent apoptosis induced by γ-irradiation of Molt-4 leukemia cells

Molt-4 leukemia cells undergo p53-dependent apoptosis accompanied by accumulation of de novo ceramide after 14 hours of γ-irradiation. In order to identify the potential mediators involved in ceramide accumulation and the cell death response, differentially expressed genes were identified by Affymetrix Microarray Analysis. Molt-4-LXSN cells, expressing wild type p53, and p53-deficient Molt-4-E6 cells were irradiated and harvested at 3 and 8 hours post-irradiation. Human genome U133 plus 2.0 array containing >47,000 transcripts was used for gene expression profiling. From over 10,000 probes, 281 and 12 probes were differentially expressed in Molt-4-LXSN and Molt-4-E6 cells, respectively. Data analysis revealed 63 (upregulated) and 20 (downregulated) genes (>2 fold) in Molt-4-LXSN at 3 hours and 140 (upregulated) and 21 (downregulated) at 8 hours post-irradiation. In Molt-4-E6 cells, 5 (upregulated) genes each were found at 3 hours and 8 hours, respectively. In Molt-4-LXSN cells, a significant fraction of the genes with altered expression at 3 hours were found to be involved in apoptosis signaling pathway (BCL2L11), p53 pathway (PMAIP1, CDKN1A and FAS) and oxidative stress response (FDXR, CROT and JUN). Similarly, at 8 hours the genes with altered expression were involved in the apoptosis signaling pathway (BAX, BIK and JUN), p53 pathway (BAX, CDKN1A and FAS), oxidative stress response (FDXR and CROT) and p53 pathway feedback loops 2 (MDM2 and CDKN1A). A global molecular and biological interaction map analysis showed an association of these altered genes with apoptosis, senescence, DNA damage, oxidative stress, cell cycle arrest and caspase activation. In a targeted study, activation of apoptosis correlated with changes in gene expression of some of the above genes and revealed sequential activation of both intrinsic and extrinsic apoptotic pathways that precede ceramide accumulation and subsequent execution of apoptosis. One or more of these altered genes may be involved in p53-dependent ceramide accumulation.

Spatially-Resolved Top-down Proteomics Bridged to MALDI MS Imaging Reveals the Molecular Physiome of Brain Regions

Tissue spatially-resolved proteomics was performed on 3 brain regions, leading to the characterization of 123 reference proteins. Moreover, 8 alternative proteins from alternative open reading frames (AltORF) were identified. Some proteins display specific post-translational modification profiles or truncation linked to the brain regions and their functions. Systems biology analysis performed on the proteome identified in each region allowed to associate sub-networks with the functional physiology of each brain region. Back correlation of the proteins identified by spatially-resolved proteomics at a given tissue localization with the MALDI MS imaging data, was then performed. As an example, mapping of the distribution of the matrix metallopeptidase 3-cleaved C-terminal fragment of α-synuclein (aa 95–140) identified its specific distribution along the hippocampal dentate gyrus. Taken together, we established the molecular physiome of 3 rat brain regions through reference and hidden proteome characterization.

Dietary folate levels alter the kinetics and molecular mechanism of prostate cancer recurrence in the CWR22 model

Folate impacts the genome and epigenome by feeding into one-carbon metabolism to produce critical metabolites, deoxythymidine monophosphate and s-adenosylmethionine. The impact of folate exposure and intervention timing on cancer progression remains controversial. Due to polyamine metabolism's extraordinary biosynthetic flux in prostate cancer (CaP) we demonstrated androgen stimulated CaP is susceptible to dietary folate deficiency. We hypothesized dietary folate levels may also affect castration recurrent CaP. We used the CWR22 human xenograft model which recurs following androgen withdrawal. Engrafted mice were fed a folate depleted or supplemented diet beginning at androgen withdrawal, or prior to xenograft implantation. Both folate depletion and supplementation at the time of withdrawal significantly decreased recurrence incidence. Folate supplementation prior to xenograft implantation increased time to recurrence, suggesting a protective role. By contrast, folate depleted recurrent tumors exhibited transcriptional adaptive responses that maintained high polyamine levels at the expense of increased DNA damage and DNA methylation alterations. Mining of publically available data demonstrated folate related pathways are exceptionally dysregulated in human CaP, which correlated with decreased time to biochemical recurrence. These findings highlight the potential for novel therapeutic interventions that target these metabolic pathways in CaP and provide a rationale to apply such strategies alongside androgen withdrawal.

Enhancement of anticancer activity by silibinin and paclitaxel combination on the ovarian cancer

BACKGROUND

Ovarian carcinoma is the most lethal cancer among all gynaecological malignancies. One of the most chemotherapy drugs used for ovarian cancer is paclitaxel which induces apoptosis. Paclitaxel has been used for many years. Similar to the most cancers this responds to chemotherapy initially but in a long run, drug resistance happens which fails the treatment procedure. Combination of chemotherapy drugs has been suggested to deal with this issue. Silibinin, a plant extraction, has been used from ancient time in traditional medicine and identified to have powerful antioxidant activity.

AIM

The aim of this study was to examine the effect of paclitaxel and silibinin combination on SKOV-3 cancer cell line.

MATERIALS AND METHODS

The human epithelial ovarian cancer cell line, SKOV-3, was cultured and treated with paclitaxel, silibinin and paclitaxel plus silibinin for 48 hours. MTT assay was carried out to determine cell viability. For apoptotic process, we used real-time PCR to study P53 and P21 genes expression after drug treatment and network analysis was performed using Pathway Studio web tool (Elsevier).

RESULTS

Cell growth was inhibited considerably (p < .05) by combination of paclitaxel and silibinin after 48 hours of treatment. Also silibinin and paclitaxel combination induced apoptosis in SKOV-3 cells. Expression analysis by real-time PCR showed the significant up-regulation of two tumour suppressor genes, P53 and P21 in response to combination of silibinin and paclitaxel. In addition, computational network analysis demonstrated the crosstalk between paclitaxel, silibinin and ovarian cancer.

CONCLUSIONS

Our results showed that combination of chemotherapy drugs of silibinin and paclitaxel can be more efficient in treatment of ovarian cancer cells.

RhoA Inhibitor Treatment At Acute Phase of Spinal Cord Injury May Induce Neurite Outgrowth and Synaptogenesis

The therapeutic use of RhoA inhibitors (RhoAi) has been experimentally tested in spinal cord injury (SCI). In order to decipher the underlying molecular mechanisms involved in such a process, an in vitro neuroproteomic-systems biology platform was developed in which the pan-proteomic profile of the dorsal root ganglia (DRG) cell line ND7/23 DRG was assessed in a large array of culture conditions using RhoAi and/or conditioned media obtained from SCI ex vivo derived spinal cord slices. A fine mapping of the spatio-temporal molecular events of the RhoAi treatment in SCI was performed. The data obtained allow a better understanding of regeneration/degeneration induced above and below the lesion site. Results notably showed a time-dependent alteration of the transcription factors profile along with the synthesis of growth cone-related factors (receptors, ligands, and signaling pathways) in RhoAi treated DRG cells. Furthermore, we assessed in a rat SCI model the in vivo impact of RhoAi treatment administered in situ via alginate scaffold that was combined with FK506 delivery. The improved recovery of locomotion was detected only at the early postinjury time points, whereas after overall survival a dramatic increase of synaptic contacts on outgrowing neurites in affected segments was observed. We validate these results by in vivo proteomic studies along the spinal cord segments from tissue and secreted media analyses, confirming the increase of the synaptogenesis expression factors under RhoAi treatment. Taken together, we demonstrate that RhoAi treatment seems to be useful to stimulate neurite outgrowth in both in vitro as well in vivo environments. However, for in vivo experiments there is a need for sustained delivery regiment to facilitate axon regeneration and promote synaptic reconnections with appropriate target neurons also at chronic phase, which in turn may lead to higher assumption for functional improvement.

Combined Mass Spectrometry Imaging and Top-down Microproteomics Reveals Evidence of a Hidden Proteome in Ovarian Cancer

BACKGROUND

Recently, it was demonstrated that proteins can be translated from alternative open reading frames (altORFs), increasing the size of the actual proteome. Top-down mass spectrometry-based proteomics allows the identification of intact proteins containing post-translational modifications (PTMs) as well as truncated forms translated from reference ORFs or altORFs.

METHODS

Top-down tissue microproteomics was applied on benign, tumor and necrotic-fibrotic regions of serous ovarian cancer biopsies, identifying proteins exhibiting region-specific cellular localization and PTMs. The regions of interest (ROIs) were determined by MALDI mass spectrometry imaging and spatial segmentation.

FINDINGS

Analysis with a customized protein sequence database containing reference and alternative proteins (altprots) identified 15 altprots, including alternative G protein nucleolar 1 (AltGNL1) found in the tumor, and translated from an altORF nested within the GNL1 canonical coding sequence. Co-expression of GNL1 and altGNL1 was validated by transfection in HEK293 and HeLa cells with an expression plasmid containing a GNL1-FLAG(V5) construct. Western blot and immunofluorescence experiments confirmed constitutive co-expression of altGNL1-V5 with GNL1-FLAG.

CONCLUSIONS

Taken together, our approach provides means to evaluate protein changes in the case of serous ovarian cancer, allowing the detection of potential markers that have never been considered.

Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification

An integrated diagnosis using molecular features is recommended in the 2016 World Health Organization (WHO) classification. Our aim was to explore non-targeted molecular classification using MALDI mass spectrometry imaging (MALDI MSI) associated to microproteomics in order to classify anaplastic glioma by integration of clinical data. We used fresh-frozen tissue sections to perform MALDI MSI of proteins based on their digestion peptides after in-situ trypsin digestion of the tissue sections and matrix deposition by micro-spraying. The generated 70μm spatial resolution image datasets were further processed by individual or global segmentation in order to cluster the tissues according to their molecular protein signature. The clustering gives 3 main distinct groups. Within the tissues the ROIs (regions of interest) defined by these groups were used for microproteomics by micro-extraction of the tryptic peptides after on-tissue enzymatic digestion. More than 2500 proteins including 22 alternative proteins (AltProt) are identified by the Shotgun microproteomics. Statistical analysis on the basis of the label free quantification of the proteins shows a similar classification to the MALDI MSI segmentation into 3 groups. Functional analysis performed on each group reveals sub-networks related to neoplasia for group 1, glioma with inflammation for group 2 and neurogenesis for group 3. This demonstrates the interest on these new non-targeted large molecular data combining both MALDI MSI and microproteomics data, for tumor classification. This analysis provides new insights into grade III glioma organization. This specific information could allow a more accurate classification of the biopsies according to the prognosis and the identification of potential new targeted therapeutic options. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats

Traumatic brain injury (TBI) represents a critical health problem of which diagnosis, management, and treatment remain challenging. TBI is a contributing factor in approximately one-third of all injury-related deaths in the United States. The Centers for Disease Control and Prevention estimate that 1.7 million people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics–systems biology is proving to be a prominent tool in biomarker discovery for central nervous system injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI) model of experimental TBI in rat model to assess the temporal–global proteome changes after acute (1 day) and for the first time, subacute (7 days), post-injury time frame using the established cation–anion exchange chromatography-1D SDS gel electrophoresis LC–MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entity, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day) and subacute (7 days) periods post-TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7 days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is among the first to assess temporal neuroproteome changes in the CCI model. Data presented here unveil potential neural biomarkers and therapeutic targets that could be used for diagnosis, for treatment and, most importantly, for temporal prognostic assessment following brain injury. Of interest, this work relies on in silico bioinformatics approach to draw its conclusion; further work is conducted for functional studies to validate and confirm the omics data obtained.

Deciphering the Role of Emx1 in Neurogenesis: A Neuroproteomics Approach

Emx1 has long been implicated in embryonic brain development. Previously we found that mice null of Emx1 gene had smaller dentate gyri and reduced neurogenesis, although the molecular mechanisms underlying this defect was not well understood. To decipher the role of Emx1 gene in neural regeneration and the timing of its involvement, we determine the frequency of neural stem cells (NSCs) in embryonic and adult forebrains of Emx1 wild type (WT) and knock out (KO) mice in the neurosphere assay. Emx1 gene deletion reduced the frequency and self-renewal capacity of NSCs of the embryonic brain but did not affect neuronal or glial differentiation. Emx1 KO NSCs also exhibited a reduced migratory capacity in response to serum or vascular endothelial growth factor (VEGF) in the Boyden chamber migration assay compared to their WT counterparts. A thorough comparison between NSC lysates from Emx1 WT and KO mice utilizing 2D-PAGE coupled with tandem mass spectrometry revealed 38 proteins differentially expressed between genotypes, including the F-actin depolymerization factor Cofilin. A global systems biology and cluster analysis identified several potential mechanisms and cellular pathways implicated in altered neurogenesis, all involving Cofilin1. Protein interaction network maps with functional enrichment analysis further indicated that the differentially expressed proteins participated in neural-specific functions including brain development, axonal guidance, synaptic transmission, neurogenesis, and hippocampal morphology, with VEGF as the upstream regulator intertwined with Cofilin1 and Emx1. Functional validation analysis indicated that apart from the overall reduced level of phosphorylated Cofilin1 (p-Cofilin1) in the Emx1 KO NSCs compared to WT NSCs as demonstrated in the western blot analysis, VEGF was able to induce more Cofilin1 phosphorylation and FLK expression only in the latter. Our results suggest that a defect in Cofilin1 phosphorylation induced by VEGF or other growth factors might contribute to the reduced neurogenesis in the Emx1 null mice during brain development.

Deciphering glycomics and neuroproteomic alterations in experimental traumatic brain injury: Comparative analysis of aspirin and clopidogrel treatment

As populations age, the number of patients sustaining traumatic brain injury (TBI) and concomitantly receiving preinjury antiplatelet therapy such as aspirin (ASA) and clopidogrel (CLOP) is rising. These drugs have been linked with unfavorable clinical outcomes following TBI, where the exact mechanism(s) involved are still unknown. In this novel work, we aimed to identify and compare the altered proteome profile imposed by ASA and CLOP when administered alone or in combination, prior to experimental TBI. Furthermore, we assessed differential glycosylation PTM patterns following experimental controlled cortical impact model of TBI, ASA, CLOP, and ASA + CLOP. Ipsilateral cortical brain tissues were harvested 48 h postinjury and were analyzed using an advanced neuroproteomics LC-MS/MS platform to assess proteomic and glycoproteins alterations. Of interest, differential proteins pertaining to each group (22 in TBI, 41 in TBI + ASA, 44 in TBI + CLOP, and 34 in TBI + ASA + CLOP) were revealed. Advanced bioinformatics/systems biology and clustering analyses were performed to evaluate biological networks and protein interaction maps illustrating molecular pathways involved in the experimental conditions. Results have indicated that proteins involved in neuroprotective cellular pathways were upregulated in the ASA and CLOP groups when given separately. However, ASA + CLOP administration revealed enrichment in biological pathways relevant to inflammation and proinjury mechanisms. Moreover, results showed differential upregulation of glycoproteins levels in the sialylated N-glycans PTMs that can be implicated in pathological changes. Omics data obtained have provided molecular insights of the underlying mechanisms that can be translated into clinical bedside settings.

Proteomic Analysis of the Spatio-temporal Based Molecular Kinetics of Acute Spinal Cord Injury Identifies a Time- and Segment-specific Window for Effective Tissue Repair

Spinal cord injury (SCI) represents a major debilitating health issue with a direct socioeconomic burden on the public and private sectors worldwide. Although several studies have been conducted to identify the molecular progression of injury sequel due from the lesion site, still the exact underlying mechanisms and pathways of injury development have not been fully elucidated. In this work, based on OMICs, 3D matrix-assisted laser desorption ionization (MALDI) imaging, cytokines arrays, confocal imaging we established for the first time that molecular and cellular processes occurring after SCI are altered between the lesion proximity, i.e. rostral and caudal segments nearby the lesion (R1-C1) whereas segments distant from R1-C1, i.e. R2-C2 and R3-C3 levels coexpressed factors implicated in neurogenesis. Delay in T regulators recruitment between R1 and C1 favor discrepancies between the two segments. This is also reinforced by presence of neurites outgrowth inhibitors in C1, absent in R1. Moreover, the presence of immunoglobulins (IgGs) in neurons at the lesion site at 3 days, validated by mass spectrometry, may present additional factor that contributes to limited regeneration. Treatment in vivo with anti-CD20 one hour after SCI did not improve locomotor function and decrease IgG expression. These results open the door of a novel view of the SCI treatment by considering the C1 as the therapeutic target.

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.

Integrating multiple omics to unravel mechanisms of Cyclosporin A induced hepatotoxicity in vitro

In order to improve attrition rates of candidate-drugs there is a need for a better understanding of the mechanisms underlying drug-induced hepatotoxicity. We aim to further unravel the toxicological response of hepatocytes to a prototypical cholestatic compound by integrating transcriptomic and metabonomic profiling of HepG2 cells exposed to Cyclosporin A. Cyclosporin A exposure induced intracellular cholesterol accumulation and diminished intracellular bile acid levels. Performing pathway analyses of significant mRNAs and metabolites separately and integrated, resulted in more relevant pathways for the latter. Integrated analyses showed pathways involved in cell cycle and cellular metabolism to be significantly changed. Moreover, pathways involved in protein processing of the endoplasmic reticulum, bile acid biosynthesis and cholesterol metabolism were significantly affected. Our findings indicate that an integrated approach combining metabonomics and transcriptomics data derived from representative in vitro models, with bioinformatics can improve our understanding of the mechanisms of action underlying drug-induced hepatotoxicity. Furthermore, we showed that integrating multiple omics and thereby analyzing genes, microRNAs and metabolites of the opposed model for drug-induced cholestasis can give valuable information about mechanisms of drug-induced cholestasis in vitro and therefore could be used in toxicity screening of new drug candidates at an early stage of drug discovery.

Clustering gene expression regulators: new approach to disease subtyping

One of the main challenges in modern medicine is to stratify different patient groups in terms of underlying disease molecular mechanisms as to develop more personalized approach to therapy. Here we propose novel method for disease subtyping based on analysis of activated expression regulators on a sample-by-sample basis. Our approach relies on Sub-Network Enrichment Analysis algorithm (SNEA) which identifies gene subnetworks with significant concordant changes in expression between two conditions. Subnetwork consists of central regulator and downstream genes connected by relations extracted from global literature-extracted regulation database. Regulators found in each patient separately are clustered together and assigned activity scores which are used for final patients grouping. We show that our approach performs well compared to other related methods and at the same time provides researchers with complementary level of understanding of pathway-level biology behind a disease by identification of significant expression regulators. We have observed the reasonable grouping of neuromuscular disorders (triggered by structural damage vs triggered by unknown mechanisms), that was not revealed using standard expression profile clustering. For another experiment we were able to suggest the clusters of regulators, responsible for colorectal carcinoma vs adenoma discrimination and identify frequently genetically changed regulators that could be of specific importance for the individual characteristics of cancer development. Proposed approach can be regarded as biologically meaningful feature selection, reducing tens of thousands of genes down to dozens of clusters of regulators. Obtained clusters of regulators make possible to generate valuable biological hypotheses about molecular mechanisms related to a clinical outcome for individual patient.

Drug reformulations and repositioning in pharmaceutical industry and its impact on market access: reassessment of nomenclature

BACKGROUND

Medicinal products that have been developed and approved for one disease may be the object of additional clinical development in other disease areas or of additional pharmaceutical development for new and different formulations. The newly developed products can be named as repositioned or reformulated products, respectively. Market access of repositioned or reformulated products in Europe and the United States is an interesting object of study as it may provide clarity about which parameters are assessed and considered to bring added value, other than the molecule itself. As such, we aim to evaluate if the added value of repositioned or reformulated medicinal products can be systematically described, quantified, and predicted. As a first step toward investigating the impact of market access on drug research and development trends for repositioned and reformulated products, it is necessary to have consistency in the designations for the case studies evaluated in this project. In an attempt to achieve that consistency, the current study aims to propose harmonized definitions for the repositioning and reformulation strategies and to propose a taxonomy for the medicinal products derived thereof.

METHODS

A systematic literature review was conducted to collect information on existing cases of repositioning or reformulation. A search strategy was developed by defining the search objectives, targeted data sources, search keywords, and inclusion/exclusion criteria for the retrieved documents.

RESULTS

A total of 505 publications were retrieved through a search of the main data sources. The screenings and the ad hoc search led to a total of 56 publications to be used for the case study data extraction. In total, 87 repositioning and/or reformulation cases were found described in the literature, 23 of which presented different definitions and/or classifications by different authors.

CONCLUSION

Given the disparity and inconsistency of terminologies and classifications in the literature, a harmonized nomenclature for drug repositioning, reformulation, and combination cases will allow for a robust analysis of the added value and market access conditions attributed for each strategy and case type as assessed by regulators and payors in Europe and the United States. After evaluation of the existing terminologies and given the absence of clear and consistent definitions for drug reformulation and repositioning in the literature, we propose a global terminology and taxonomy in order to cover all of the previously unclear definitions and classifications for repositioned and reformulated products.

Integrating fragmented software applications into holistic solutions: focus on drug discovery

INTRODUCTION

Current advances in software development and global molecular profiling technologies allow the development of holistic software solutions for drug discovery. Such solutions must streamline in silico drug and therapy development by integrating all types of data into one knowledge base and also by enabling continuous analysis workflows uninterrupted by manual restructuring of inputs and outputs from workflow components. They must provide a collaborative environment for data sharing between multiple users and allow importing of all types of experimental data for subsequent analysis.

AREAS COVERED

The reader is provided with a review of disparate software applications currently used in drug development and a discussion of existing organizational challenges for development of holistic software solutions. The reader is also provided with a proposed conceptual framework for integration of software components and some details for its implementation are suggested.

EXPERT OPINION

Holistic solutions can undoubtedly affect the speed, quality and cost of drug development and personalized therapy. However, it must be constantly evolved to rapidly adopt new experimental and statistical methods, incorporate advances in software technologies and allow perpetual optimization of its components. Perpetual improvements in data structure, data quality, statistical algorithms and other mathematical approaches for computer modeling can gradually shift financial and cultural emphasis in the pharmaceutical industry away from traditional experimental approaches and towards computational approaches.

Computational approaches for drug repositioning and combination therapy design

Heterogeneous high-throughput biological data become readily available for various diseases. The amount of data points generated by such experiments does not allow manual integration of the information to design the most optimal therapy for a disease. We describe a novel computational workflow for designing therapy using Ariadne Genomics Pathway Studio software. We use publically available microarray experiments for glioblastoma and automatically constructed ResNet and ChemEffect databases to exemplify how to find potentially effective chemicals for glioblastoma--the disease yet without effective treatment. Our first approach involved construction of signaling pathway affected in glioblastoma using scientific literature and data available in ResNet database. Compounds known to affect multiple proteins in this pathway were found in ChemEffect database. Another approach involved analysis of differential expression in glioblastoma patients using Sub-Network Enrichment Analysis (SNEA). SNEA identified angiogenesis-related protein Cyr61 as the major positive regulator upstream of genes differentially expressed in glioblastoma. Using our findings, we then identified breast cancer drug Fulvestrant as a major inhibitor of glioblastoma pathway as well as Cyr61. This suggested Fulvestrant as a potential treatment against glioblastoma. We further show how to increase efficacy of glioblastoma treatment by finding optimal combinations of Fulvestrant with other drugs.