Prioritizing Popular Proteins in Liver Cancer: Remodelling One-Carbon Metabolism

Mapping early serum proteome signatures of liver regeneration in living donor liver transplant cases

The liver is the only solid organ capable of regenerating itself to regain 100% of its mass and function after liver injury and/or partial hepatectomy (PH). This exceptional property represents a therapeutic opportunity for severe liver disease patients. However, liver regeneration (LR) might fail due to poorly understood causes. Here, we have investigated the regulation of liver proteome and phosphoproteome at a short time after PH (9 h), to depict a detailed mechanistic background of the early LR phase. Furthermore, we analyzed the dynamic changes of the serum proteome and metabolome of healthy living donor liver transplant (LDLT) donors at different time points after surgery. The molecular profiles from both analyses were then correlated. Insulin and FXR-FGF15/19 signaling were stimulated in mouse liver after PH, leading to the activation of the main intermediary kinases (AKT and ERK). Besides, inhibition of the hippo pathway led to an increased expression of its target genes and of one of its intermediary proteins (14-3-3 protein), contributing to cell proliferation. In association with these processes, metabolic reprogramming coupled to enhanced mitochondrial activity cope for the energy and biosynthetic requirements of LR. In human serum of LDLT donors, we identified 56 proteins and 13 metabolites statistically differential which recapitulate some of the main cellular processes orchestrating LR in its early phase. These results provide mechanisms and protein mediators of LR that might prove useful for the follow-up of the regenerative process in the liver after PH as well as preventing the occurrence of complications associated with liver resection.

Targeted Proteomics for Monitoring One-Carbon Metabolism in Liver Diseases

Liver diseases cause approximately 2 million deaths per year worldwide and had an increasing incidence during the last decade. Risk factors for liver diseases include alcohol consumption, obesity, diabetes, the intake of hepatotoxic substances like aflatoxin, viral infection, and genetic determinants. Liver cancer is the sixth most prevalent cancer and the third in mortality (second in males). The low survival rate (less than 20% in 5 years) is partially explained by the late diagnosis, which remarks the need for new early molecular biomarkers. One-carbon metabolism integrates folate and methionine cycles and participates in essential cell processes such as redox homeostasis maintenance and the regulation of methylation reactions through the production of intermediate metabolites such as cysteine and S-Adenosylmethionine. One-carbon metabolism has a tissue specific configuration, and in the liver, the participating enzymes are abundantly expressed-a requirement to maintain hepatocyte differentiation. Targeted proteomics studies have revealed significant differences in hepatocellular carcinoma and cirrhosis, suggesting that monitoring one-carbon metabolism enzymes can be useful for stratification of liver disease patients and to develop precision medicine strategies for their clinical management. Here, reprogramming of one-carbon metabolism in liver diseases is described and the role of mass spectrometry to follow-up these alterations is discussed.

Monitoring one-carbon metabolism by mass spectrometry to assess liver function and disease

Precision medicine promises to overcome the constraints of the traditional "one-for-all" healthcare approach through a clear understanding of the molecular features of a disease, allowing for innovative and tailored treatments. State-of-the-art proteomics has the potential to accurately explore the human proteome to identify, quantify, and characterize proteins associated with disease progression. There is a pressing need for informative biomarkers to diagnose liver disease early in its course to prevent severe disease for which no efficient treatment is yet available. Here, we propose the concept of a cellular pathway as a functional biomarker, whose monitorization may inform normal and pathological status. We have developed a standardized targeted selected-reaction monitoring assay to detect and quantify 13 enzymes of one-carbon metabolism (1CM). The assay is compliant with Clinical Proteomics Tumor Analysis Consortium (CPTAC) guidelines and has been included in the protein quantification assays that can be accessed through the assay portal at the CPTAC web page. To test the feasibility of the assay, we conducted a retrospective, proof-of-concept study on a collection of liver samples from healthy controls and from patients with cirrhosis or hepatocellular carcinoma (HCC). Our results indicate a significant reconfiguration of 1CM upon HCC development resulting from a process that can already be identified in cirrhosis. Our findings indicate that the systematic and integrated quantification of 1CM enzymes is a promising cell function-based biomarker for patient stratification, although further experiments with larger cohorts are needed to confirm these findings.

Development of a Standardized MRM Method for the Quantification of One Carbon Metabolism Enzymes

One-carbon metabolism (1CM) plays a central role in liver physiology, being the source of essential metabolites such as S-adenosylmethionine, the main alkylating agent in living cells, and glutathione, their most important nonenzymatic antioxidant defense. Impairment of 1CM in hepatocytes is a recognized factor associated to chronic liver disorders and hepatocellular carcinoma. With this in mind, we have proposed the concept of functional biomarker referring to a cellular pathway that can be systematically monitored as indicative of a particular physiological or pathological condition. Here we describe a targeted mass spectrometry (MRM) protocol to simultaneously quantify 13 1CM enzymes in liver tissue specimens.

A convergent synthetic platform for dual anticancer drugs functionalized by reduced graphene nanocomposite delivery for hepatocellular cancer

Hepatocellular carcinoma (HCC) is widespread cancer with a high degree of morbidity and mortality in individuals worldwide and a serious concern for its resistance to present chemotherapy drugs. In this investigation, the combination of cisplatin (CPT) and metformin (MET) to kill the HepG2 and caco-2 cells was developed into a new pH-responding magnetic nanocomposite based on reduced graphene oxide. Polyhydroxyethyl methacrylic (PHEA) was then linked employing grafting from approach to the reduced graphene oxide by ATRP polymerization (Fe3O4@rGO-G-PSEA). FT-IR, SEM, XRD, DLS, and TGA analyses evaluated physicochemical characteristics of the nanocomposite. In addition, the cellular uptake property of the nanocomposites was examined by the HepG2 cells. The outcomes of cell viability results indicate that the nanoparticles loaded with MET&CPT showed the lowest concentration rate of HepG2 and Caco-2 cells compared to the drug-loaded single nanocomposite groups and free drugs. The histological analysis has demonstrated relatively safe and does not produce different stress such as swelling and inflammation of the mice organs. Our results show the enhancement in cytotoxicity in HepG2 and Cocoa-2 cells by MET and CPT graphene oxide-based nanocomposite by promoting apoptotic response. Moreover, Fe3O4@rGO-G-PSEA showed potent in vivo antitumor efficacy but showed no adverse toxicity to normal tissues. Together, this study can provide insight into how surface embellishment may tune these nanocomposites' tumor specificity and provide the basis for developing anticancer efficacy.

Functionathon: a manual data mining workflow to generate functional hypotheses for uncharacterized human proteins and its application by undergraduate students

About 10% of human proteins have no annotated function in protein knowledge bases. A workflow to generate hypotheses for the function of these uncharacterized proteins has been developed, based on predicted and experimental information on protein properties, interactions, tissular expression, subcellular localization, conservation in other organisms, as well as phenotypic data in mutant model organisms. This workflow has been applied to seven uncharacterized human proteins (C6orf118, C7orf25, CXorf58, RSRP1, SMLR1, TMEM53 and TMEM232) in the frame of a course-based undergraduate research experience named Functionathon organized at the University of Geneva to teach undergraduate students how to use biological databases and bioinformatics tools and interpret the results. C6orf118, CXorf58 and TMEM232 were proposed to be involved in cilia-related functions; TMEM53 and SMLR1 were proposed to be involved in lipid metabolism and C7orf25 and RSRP1 were proposed to be involved in RNA metabolism and gene expression. Experimental strategies to test these hypotheses were also discussed. The results of this manual data mining study may contribute to the project recently launched by the Human Proteome Organization (HUPO) Human Proteome Project aiming to fill gaps in the functional annotation of human proteins. Database URL: http://www.nextprot.org.

UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

The Human Proteome Project (HPP) is leading the international effort to characterize the human proteome. Although the main goal of this project was first focused on the detection of missing proteins, a new challenge arose from the need to assign biological functions to the uncharacterized human proteins and describe their implications in human diseases. Not only the proteins with experimental evidence (uPE1 proteins) but also the uncharacterized missing proteins (uMPs) were the objects of study in this challenge, neXt-CP50. In this work, we developed a new bioinformatic approach to infer biological annotations for the uPE1 proteins and uMPs based on a "guilt-by-association" analysis using public RNA-Seq data sets. We used the correlation of these proteins with the well-characterized PE1 proteins to construct a network. In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. All of the generated information was stored in a database. In addition, we implemented the web application UPEFinder (https://upefinder.proteored.org) to facilitate the access to this new resource. This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).

Differences in MicroRNA Expression in Chronic Hepatitis B Patients with Early Liver Fibrosis Based on Traditional Chinese Medicine Syndromes

The aim of this study was to determine if microRNA (miRNA) expression is different among chronic hepatitis B (CHB) patients with early liver fibrosis classified according to traditional Chinese medicine (TCM) syndromes. Eighteen CHB-fibrosis patients and 12 CHB patients without fibrosis were enrolled. The CHB-fibrosis group included 9 patients with the TCM syndrome of Ganyu Pixu Xueyu (GYPXXY), characterized by liver stagnation, spleen deficiency, and blood stasis, and 9 patients with the TCM syndrome of Qixu Xueyu (QXXY), characterized by deficiency of qi, blood, and blood stasis. Agilent miRNA microarray was performed first in liver specimens to determine whether miRNA expression is different in patients with these two TCM syndromes of CHB-fibrosis. Gene Ontology (GO) analysis and KEGG analysis were applied to determine the roles of the differentially expressed miRNAs. QRT-PCR was performed to validate the Agilent miRNA microarray results. Compared with GYPXXY patients, 6 differentially expressed miRNAs were upregulated (miR-144-5p, miR-18a-5p, miR-148b-3p, miR-654-3p, miR-139-3p, and miR-24-1-5p) and 1 was downregulated (miR-6834-3p) in QXXY patients. According to qRT-PCR data, miR-144-5p and miR-654-3p were confirmed as upregulated in CHB-liver fibrosis patients compared to CHB patients without fibrosis, whereas the other 4 miRNAs were not significantly different. More importantly, miR-654-3p was confirmed to be significantly upregulated in QXXY patients compared with values in GYPXXY patients, whereas no significant difference was found in miR-144-5p. Moreover, the pathways of central carbon metabolism in cancer and cell cycle related to miR-654-3p and the target genes of PTEN and ATM were found to be different between QXXY patients and GYPXXY patients. These results indicate that there are different miRNAs, pathways, and target genes between QXXY patients and GYPXXY patients. However, due to the limited sample, whether miR-654-3p and the target genes PTEN and ATM could be molecular markers to differentiate TCM syndromes could not be established.

Blockade of the trans-sulfuration pathway in acute pancreatitis due to nitration of cystathionine β-synthase

Acute pancreatitis is an inflammatory process of the pancreatic gland that may lead to dysregulation of the trans-sulfuration pathway. The aims of this work were firstly to study the methionine cycle as well as the trans-sulfuration pathway using metabolomic and proteomic approaches identifying the causes of this dysregulation in an experimental model of acute pancreatitis; and secondly to reveal the effects of S-adenosylmethionine administration on these pathways. Acute pancreatitis was induced by cerulein in mice, and a group of animals received S-adenosylmethionine treatment. Cerulein-induced acute pancreatitis rapidly caused marked depletion of methionine, S-adenosylmethionine, 5'-methylthioadenosine, cystathionine, cysteine, and glutathione levels in pancreas, but S-adenosylhomocysteine and homocysteine remained unchanged. Protein steady-state levels of S-adenosylhomocysteine-hydrolase and cystathionine gamma-lyase diminished but methylthioadenosine phosphorylase levels increased in pancreas with acute pancreatitis. Although cystathionine β-synthase protein levels did not change with acute pancreatitis, Nos2 mRNA and protein levels were markedly up-regulated and caused tyrosine nitration of cystathionine β-synthase in pancreas. S-adenosylmethionine administration enhanced Nos2 mRNA expression and cystathionine β-synthase nitration and triggered homocysteine accumulation in acute pancreatitis. Furthermore, S-adenosylmethionine administration promoted enrichment of the euchromatin marker H3K4me3 in the promoters of Tnf-α, Il-6, and Nos2 and enhanced the mRNA up-regulation of these genes. Accordingly, S-adenosylmethionine administration increased inflammatory infiltrate and edema in pancreas with acute pancreatitis. In conclusion, tyrosine-nitration of cystathionine β-synthase blockades the trans-sulfuration pathway in acute pancreatitis promoting homocysteine accumulation upon S-adenosylmethionine treatment.

Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome: Where There Is a Will, There Is a Way

There is an exponential increase in biological complexity as initial gene transcripts are spliced, translated into amino acid sequence, and post-translationally modified. Each protein can exist as multiple chemical or sequence-specific proteoforms, and each has the potential to be a critical mediator of a physiological or pathophysiological signaling cascade. Here, we provide an overview of how different proteoforms come about in biological systems and how they are most commonly measured using mass spectrometry-based proteomics and bioinformatics. Our goal is to present this information at a level accessible to every scientist interested in mass spectrometry and its application to proteome profiling. We will specifically discuss recent data linking various protein post-translational modifications to cardiovascular disease and conclude with a discussion for enablement and democratization of proteomics across the cardiovascular and scientific community. The aim is to inform and inspire the readership to explore a larger breadth of proteoform, particularity post-translational modifications, related to their particular areas of expertise in cardiovascular physiology.

Progress on Identifying and Characterizing the Human Proteome: 2018 Metrics from the HUPO Human Proteome Project

The Human Proteome Project (HPP) annually reports on progress throughout the field in credibly identifying and characterizing the human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2018-01-17, the baseline for this sixth annual HPP special issue of the Journal of Proteome Research, contains 17 470 PE1 proteins, 89% of all neXtProt predicted PE1-4 proteins, up from 17 008 in release 2017-01-23 and 13 975 in release 2012-02-24. Conversely, the number of neXtProt PE2,3,4 missing proteins has been reduced from 2949 to 2579 to 2186 over the past two years. Of the PE1 proteins, 16 092 are based on mass spectrometry results, and 1378 on other kinds of protein studies, notably protein-protein interaction findings. PeptideAtlas has 15 798 canonical proteins, up 625 over the past year, including 269 from SUMOylation studies. The largest reason for missing proteins is low abundance. Meanwhile, the Human Protein Atlas has released its Cell Atlas, Pathology Atlas, and updated Tissue Atlas, and is applying recommendations from the International Working Group on Antibody Validation. Finally, there is progress using the quantitative multiplex organ-specific popular proteins targeted proteomics approach in various disease categories.

Identifying High-Priority Proteins Across the Human Diseasome Using Semantic Similarity

Identifying the genes and proteins associated with a biological process or disease is a central goal of the biomedical research enterprise. However, relatively few systematic approaches are available that provide objective evaluation of the genes or proteins known to be important to a research topic, and hence researchers often rely on subjective evaluation of domain experts and laborious manual literature review. Computational bibliometric analysis, in conjunction with text mining and data curation, attempts to automate this process and return prioritized proteins in any given research topic. We describe here a method to identify and rank protein-topic relationships by calculating the semantic similarity between a protein and a query term in the biomerical literature while adjusting for the impact and immediacy of associated research articles. We term the calculated metric the weighted copublication distance (WCD) and show that it compares well to related approaches in predicting benchmark protein lists in multiple biological processes. We used WCD to extract prioritized "popular proteins" across multiple cell types, subanatomical regions, and standardized vocabularies containing over 20 000 human disease terms. The collection of protein-disease associations across the resulting human "diseasome" supports data analytical workflows to perform reverse protein-to-disease queries and functional annotation of experimental protein lists. We envision that the described improvement to the popular proteins strategy will be useful for annotating protein lists and guiding method development efforts as well as generating new hypotheses on understudied disease proteins using bibliometric information.

Liver cancer-associated changes to the proteome: what deserves clinical focus?

Hepatocellular carcinoma (HCC) is recognized as the fifth most common neoplasm and currently represents the second leading form of cancer-related death worldwide. Despite great progress has been done in the understanding of its pathogenesis, HCC represents a heavy societal and economic burden as most patients are still diagnosed at advanced stages and the 5-year survival rate remain below 20%. Early detection and revolutionary therapies that rely on the discovery of new molecular biomarkers and therapeutic targets are therefore urgently needed to develop precision medicine strategies for a more efficient management of patients. Areas covered: This review intends to comprehensively analyse the proteomics-based research conducted in the last few years to address some of the principal still open riddles in HCC biology, based on the identification of molecular drivers of tumor progression and metastasis. Expert commentary: The technical advances in mass spectrometry experienced in the last decade have significantly improved the analytical capacity of proteome wide studies. Large-scale protein and protein variant (post-translational modifications) identification and quantification have allowed detailed dissections of molecular mechanisms underlying HCC progression and are already paving the way for the identification of clinically relevant proteins and the development of their use on patient care.

Progress and Future Direction of Chromosome-Centric Human Proteome Project

This special issue of JPR celebrates the fifth anniversary of the Chromosome-Centric Human Proteome Project (C-HPP). We present 27 manuscripts in four categories: (i) Metrics of Progress and Resources, (ii) Missing Protein Detection and Validation, (iii) Analytical Methods and Quality Assessment, and (iv) Protein Functions and Disease. We briefly introduce key messages from each paper, mostly from C-HPP teams and some from the Biology and Disease-driven HPP. From the first few months of the C-HPP NeXt-MP50 Missing Proteins Challenge, authors report 73 missing protein detections that meet the HPP guidelines using several novel approaches. Finally, we discuss future directions.