Characterization of breast cancer interstitial fluids by TmT labeling, LTQ-Orbitrap Velos mass spectrometry, and pathway analysis

Urolithin A Protects Hepatocytes from Palmitic Acid-Induced ER Stress by Regulating Calcium Homeostasis in the MAM

An ellagitannin-derived metabolite, Urolithin A (UA), has emerged as a potential therapeutic agent for metabolic disorders due to its antioxidant, anti-inflammatory, and mitochondrial function-improving properties, but its efficacy in protecting against ER stress remains underexplored. The endoplasmic reticulum (ER) is a cellular organelle involved in protein folding, lipid synthesis, and calcium regulation. Perturbations in these functions can lead to ER stress, which contributes to the development and progression of metabolic disorders such as metabolic-associated fatty liver disease (MAFLD). In this study, we identified a novel target protein of UA and elucidated its mechanism for alleviating palmitic acid (PA)-induced ER stress. Cellular thermal shift assay (CETSA)-LC-MS/MS analysis revealed that UA binds directly to the sarcoplasmic/endoplasmic reticulum Ca2+-ATPase (SERCA), an important regulator of calcium homeostasis in mitochondria-associated ER membranes (MAMs). As an agonist of SERCA, UA attenuates abnormal calcium fluctuations and ER stress in PA-treated liver cells, thereby contributing to cell survival. The lack of UA activity in SERCA knockdown cells suggests that UA regulates cellular homeostasis through its interaction with SERCA. Collectively, our results demonstrate that UA protects against PA-induced ER stress and enhances cell survival by regulating calcium homeostasis in MAMs through SERCA. This study highlights the potential of UA as a therapeutic agent for metabolic disorders associated with ER stress.

Proteomics-Based Identification of Dysregulated Proteins and Biomarker Discovery in Invasive Ductal Carcinoma, the Most Common Breast Cancer Subtype

Invasive ductal carcinoma (IDC) is the most common histological subtype of malignant breast cancer (BC), and accounts for 70-80% of all invasive BCs. IDC demonstrates great heterogeneity in clinical and histopathological characteristics, prognoses, treatment strategies, gene expressions, and proteomic profiles. Significant proteomic determinants of the progression from intraductal pre-invasive malignant lesions of the breast, which characterize a ductal carcinoma in situ (DCIS), to IDC, are still poorly identified, validated, and clinically applied. In the era of "6P" medicine, it remains a great challenge to determine which patients should be over-treated versus which need to be actively monitored without aggressive treatment. The major difficulties for designating DCIS to IDC progression may be solved by understanding the integrated genomic, transcriptomic, and proteomic bases of invasion. In this review, we showed that multiple proteomics-based techniques, such as LC-MS/MS, MALDI-ToF MS, SELDI-ToF-MS, MALDI-ToF/ToF MS, MALDI-MSI or MasSpec Pen, applied to in-tissue, off-tissue, BC cell lines and liquid biopsies, improve the diagnosis of IDC, as well as its prognosis and treatment monitoring. Classic proteomics strategies that allow the identification of dysregulated protein expressions, biological processes, and interrelated pathway analyses based on aberrant protein-protein interaction (PPI) networks have been improved to perform non-invasive/minimally invasive biomarker detection of early-stage IDC. Thus, in modern surgical oncology, highly sensitive, rapid, and accurate MS-based detection has been coupled with "proteome point sampling" methods that allow for proteomic profiling by in vivo "proteome point characterization", or by minimal tissue removal, for ex vivo accurate differentiation and delimitation of IDC. For the detection of low-molecular-weight proteins and protein fragments in bodily fluids, LC-MS/MS and MALDI-MS techniques may be coupled to enrich and capture methods which allow for the identification of early-stage IDC protein biomarkers that were previously invisible for MS-based techniques. Moreover, the detection and characterization of protein isoforms, including posttranslational modifications of proteins (PTMs), is also essential to emphasize specific molecular mechanisms, and to assure the early-stage detection of IDC of the breast.

Comparative proteomics and transcriptomics illustrate the allograft-induced stress response in the pearl oyster (Pinctada fucata martensii)

Implantation of a spherical nucleus into a recipient oyster is a critical step in artificial pearl production. However, the molecular mechanisms underlying the response of the pearl oyster to this operation are poorly understood. In this research, we used transcriptomic and proteomic analyses to examine allograft-induced changes in gene/protein expression patterns in Pinctada fucata martensii 12 h after nucleus implantation. Transcriptome analysis identified 688 differential expression genes (DEGs) (FDR<0.01 and |fold change) ＞ 2). Using a 1.2-fold increase or decrease in protein expression as a benchmark for differentially expressed proteins (DEPs), 108 DEPs were reliably quantified, including 71 up-regulated proteins (DUPs) and 37 down-regulated proteins (DDPs). Further analysis revealed that the GO terms, including "cellular process", "biological regulation" and "metabolic process" were considerably enriched. In addition, the transcriptomics analysis showed that "Neuroactive ligand-receptor interaction", "NF-kappa B signaling pathway", "MAPK signaling pathway", "PI3K-Akt signaling pathway', "Toll-like receptor signaling pathway", and "Notch signaling pathway" were significantly enriched in DEGs. The proteomics analysis showed that "ECM-receptor interaction", "Human papillomavirus infection", and "PI3K-Akt signaling pathway" were significantly enriched in DEPs. The results indicate that these functions could play an important role in response to pear oyster stress at nucleus implantation. To assess the potential relevance of quantitative information between mRNA and proteins, using Ward's hierarchical clustering analysis clustered the protein/gene expression patterns across the experimental and control samples into six groups. To investigate the biological processes associated with the protein in each cluster, we identified the significantly enriched GO terms and KEGG pathways in the proteins in each cluster. Gene set enrichment analysis (GSEA) was used to reveal the potential protein or transcription pathways associated with the response to nuclear implantation. Thus, the study of P. f. martensii is essential to enhance our understanding of the molecular mechanisms involved in pearl biosynthesis and the biology of bivalve molluscs.

Glycoengineering of Mammalian Expression Systems on a Cellular Level

Mammalian expression systems such as Chinese hamster ovary (CHO), mouse myeloma (NS0), and human embryonic kidney (HEK) cells serve a critical role in the biotechnology industry as the production host of choice for recombinant protein therapeutics. Most of the recombinant biologics are glycoproteins that contain complex oligosaccharide or glycan attachments representing a principal component of product quality. Both N-glycans and O-glycans are present in these mammalian cells, but the engineering of N-linked glycosylation is of critical interest in industry and many efforts have been directed to improve this pathway. This is because altering the N-glycan composition can change the product quality of recombinant biotherapeutics in mammalian hosts. In addition, sialylation and fucosylation represent components of the glycosylation pathway that affect circulatory half-life and antibody-dependent cellular cytotoxicity, respectively. In this chapter, we first offer an overview of the glycosylation, sialylation, and fucosylation networks in mammalian cells, specifically CHO cells, which are extensively used in antibody production. Next, genetic engineering technologies used in CHO cells to modulate glycosylation pathways are described. We provide examples of their use in CHO cell engineering approaches to highlight these technologies further. Specifically, we describe efforts to overexpress glycosyltransferases and sialyltransfereases, and efforts to decrease sialidase cleavage and fucosylation. Finally, this chapter covers new strategies and future directions of CHO cell glycoengineering, such as the application of glycoproteomics, glycomics, and the integration of 'omics' approaches to identify, quantify, and characterize the glycosylated proteins in CHO cells. Graphical Abstract.

High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

Comprehensive analysis of the cardiac proteome in a rat model of myocardial ischemia-reperfusion using a TMT-based quantitative proteomic strategy

Background

Traditional studies of the cardiac proteome have mainly investigated in an animal model by two-dimensional gel electrophoresis (2-DE). However, the results have not been of satisfactory quality for an understanding of the underlying mechanism. Recent quantitative proteomic methods have been improved to overcome these limitations. To comprehensively study the cardiac proteome in a rat model of ischemia-reperfusion (IR), we developed a tandem mass tag (TMT)-based quantitative proteomic strategy. Furthermore, using this strategy, we examined the molecular mechanisms underlying the prevention of myocardial infarction by the intake of Triticum aestivum L. extract (TALE), a representative dietary fiber grain.

Methods

Cardiac proteomes were analyzed by 2-DE as a gel-based approach, and TMT labeling coupled with two-dimensional liquid chromatography (2D-LC) and tandem mass spectrometry (MS/MS) as a non-gel-based quantitative approach. Additionally, gene ontology annotation was conducted by PANTHER database. Several proteins of interest were verified by a Western blot analysis.

Results

Total 641 proteins were identified commonly from two independent MS datasets using 2D-LC MS/MS. Among these, we identified 151 IR-related proteins that were differentially expressed between the sham-operation group and IR group, comprising 62 up-regulated proteins and 89 down-regulated proteins. Most of the reduced proteins were involved in metabolic processes. In addition, 57 of the IR-related proteins were affected by TALE intake, representing 25 up-regulated proteins and 32 down-regulated proteins. In particular, TALE intake leads to a switch in metabolism to reduce the loss of high-energy phosphates and the accumulation of harmful catabolites (especially reactive oxygen species (ROS)) and to maintain cytoskeleton balance, leading to a reduction in cardiac IR injury.

Conclusions

Our study provides a comprehensive proteome map of IR-related proteins and potential target proteins and identifies mechanisms implicated in the prevention of myocardial infarction by TALE intake in a rat IR model.

'Omics Approaches to Explore the Breast Cancer Landscape

Breast cancer incidence is increasing worldwide with more than 600,000 deaths reported in 2018 alone. In current practice treatment options for breast cancer patients consists of surgery, chemotherapy, radiotherapy or targeting of classical markers of breast cancer subtype: estrogen receptor (ER) and HER2. However, these treatments fail to prevent recurrence and metastasis. Improved understanding of breast cancer and metastasis biology will help uncover novel biomarkers and therapeutic opportunities to improve patient stratification and treatment. We will first provide an overview of current methods and models used to study breast cancer biology, focusing on 2D and 3D cell culture, including organoids, and on in vivo models such as the MMTV mouse model and patient-derived xenografts (PDX). Next, genomic, transcriptomic, and proteomic approaches and their integration will be considered in the context of breast cancer susceptibility, breast cancer drivers, and therapeutic response and resistance to treatment. Finally, we will discuss how 'Omics datasets in combination with traditional breast cancer models are useful for generating insights into breast cancer biology, for suggesting individual treatments in precision oncology, and for creating data repositories to undergo further meta-analysis. System biology has the potential to catalyze the next great leap forward in treatment options for breast cancer patients.

Shank3 regulates striatal synaptic abundance of Cyld, a deubiquitinase specific for Lys63-linked polyubiquitin chains

The SH3 and multiple ankyrin repeat domains 3 (Shank3) proteins are core organizers of the postsynaptic density in neuronal excitatory synapses, and their defects cause various neurodevelopmental and neuropsychiatric disorders. Mechanistically, Shank3 directly and indirectly interacts with hundreds of synaptic proteins with diverse functions and potentially exerts its regulatory roles in synaptic development and function via these interactors. However, Shank3-dependent regulation of synaptic abundance has been validated in vivo for only a few Shank3 interactors. Here, using a quantitative proteomic analysis, we identified 136 proteins with altered synaptic abundance in the striatum of Shank3-overexpressing transgenic (TG) mice. By comparing these proteins with those found in a previous analysis of the postsynaptic density of Shank3 knock-out (KO) striatum, we identified and confirmed that cylindromatosis-associated deubiquitinase (Cyld), a deubiquitinase specific for Lys63-linked polyubiquitin chains, was up- and down-regulated in Shank3 TG and KO striatal synapses, respectively. Consistently, we found that the synaptic levels of Lys63-linked polyubiquitin chains were down- and up-regulated in the Shank3 TG and KO striata, respectively. Furthermore, by isolating and analyzing the synaptic Cyld complex, we generated a Cyld interactome consisting of 103 proteins, which may include Cyld substrates. Bioinformatic analyses suggested associations of the Cyld interactome with a few brain disorders and synaptic functions. Taken together, these results suggest that Shank3 regulates the synaptic abundance of Cyld in the mouse striatum and, thereby, potentially modulates the Lys63-linked polyubiquitination of striatal synaptic proteins.

AAV9-TAZ Gene Replacement Ameliorates Cardiac TMT Proteomic Profiles in a Mouse Model of Barth Syndrome

Barth syndrome (BTHS) is a rare mitochondrial disease that causes severe cardiomyopathy and has no disease-modifying therapy. It is caused by recessive mutations in the gene tafazzin (TAZ), which encodes tafazzin-an acyltransferase that remodels the inner mitochondrial membrane lipid cardiolipin. To identify novel mechanistic pathways involved in BTHS and evaluate the effects of gene therapy on proteomic profiles, we performed a multiplex tandem mass tagging (TMT) quantitative proteomics analysis to compare protein expression profiles from heart lysates isolated from BTHS, healthy wild-type (WT), and BTHS treated with adeno-associated virus serotype 9 (AAV9)-TAZ gene replacement as neonates or adults. 197 proteins with ≥2 unique peptides were identified. Of these, 91 proteins were significantly differentially expressed in BTHS compared to WT controls. Cause-effect relationships between tafazzin deficiency and altered protein profiles were confirmed through demonstrated significant improvements in expression levels following administration of AAV9-TAZ. The importance of TMEM65 in Cx43 localization to cardiac intercalated discs was revealed as a novel consequence of tafazzin deficiency that was improved following gene therapy. This study identifies novel mechanistic pathways involved in the pathophysiology of BTHS, demonstrates the ability of gene delivery to improve protein expression profiles, and provides support for clinical translation of AAV9-TAZ gene therapy.

Superhydrophobic lab-on-chip measures secretome protonation state and provides a personalized risk assessment of sporadic tumour

Secretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual’s diagnosis and/or help clarify risk in healthy populations.

A blood test that measures whether molecules secreted by cells contain titratable proton atoms can accurately discriminate between patients who have cancer and those who don’t. Titratable species may in turn influence the protonation state of a solution, i.e. the number of protons added to and the net charge of that solution. A team led by Natalia Malara from University Magna Graecia in Catanzaro, Italy and Enzo Di Fabrizio 
from the King Abdullah University of Science and Technology in Thuwal, Saudi Arabia, Francesco Gentile from the University Federico II in Naples, Italy, and Nicola Coppedè from the Institute of Materials for Electronics and Magnetism in Parma, Italy, created an eletrochemical device that can detect faulty metabolism by quantifying the proportion of secreted proteins with and without extra protons—an indicator of abnormal cell division, proliferation and invasion. The researchers tested the device on blood samples from patients with solid tumors and healthy controls. The method identified cancer patients with a high degree of accuracy. If the findings are confirmed in larger trials, the test could help with the screening, diagnosis and management of cancer.

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

Innovative methods for biomarker discovery in the evaluation and development of cancer precision therapies

The discovery of biomarkers able to detect cancer at an early stage, to evaluate its aggressiveness, and to predict the response to therapy remains a major challenge in clinical oncology and precision medicine. In this review, we summarize recent achievements in the discovery and development of cancer biomarkers. We also highlight emerging innovative methods in biomarker discovery and provide insights into the challenges faced in their evaluation and validation.

Gaining insights into cancer biology through exploration of the cancer secretome using proteomic and bioinformatic tools

INTRODUCTION

Tumor-associated proteins released by cancer cells and by tumor stroma cells, referred as 'cancer secretome', represent a valuable resource for discovery of potential cancer biomarkers. The last decade was marked by a great increase in number of studies focused on various aspects of cancer secretome including, composition and identification of components externalized by malignant cells and by the components of tumor microenvironment. Areas covered: Here, we provide an overview of achievements in the proteomic analysis of the cancer secretome, elicited through the tumor-associated interstitial fluid recovered from malignant tissues ex vivo or the protein component of conditioned media obtained from cultured cancer cells in vitro. We summarize various bioinformatic tools and approaches and critically appraise their outcomes, focusing on problems and challenges that arise when applied for the analysis of cancer secretomic databases. Expert commentary: Recent achievements in the omics- analysis of structural and metabolic aspects of altered cancer secretome contribute greatly to the various hallmarks of cancer including the identification of clinically significant biomarkers and potential targets for therapeutic intervention.

Exosomal amyloid A and lymphatic vessel endothelial hyaluronic acid receptor-1 proteins are associated with disease activity in rheumatoid arthritis

Background

Exosomes are thought to play an important role in exchanging information between cells. The proteins and lipids in exosomes play roles in mediating inflammatory and autoimmune diseases. The aim of this study was to identify exosomal candidate proteins that are related to other inflammatory parameters in rheumatoid arthritis (RA).

Methods

The study population consisted of 60 patients with RA: 30 in the clinical remission (CR) group with a Disease Activity Score in 28 joints based on erythrocyte sedimentation rate (DAS28-ESR) ≤2.6 and 30 in the non-clinical remission (non-CR) group with a DAS28-ESR >2.6. Preparation of exosomes from patient serum samples was performed with the ExoQuick kit, and protein identification/quantification was performed using tandem mass tag labeling/mass spectrometry and an enzyme-linked immunosorbent assay. Comparisons between groups were made using Student’s t test or the Mann-Whitney U test, as appropriate. Spearman’s correlation coefficients (ρ) were calculated.

Results

We identified six candidate proteins. Exosomal levels of amyloid A (AA) and lymphatic vessel endothelial hyaluronic acid receptor-1 (LYVE-1) differed between the CR and non-CR groups. Both serum and exosomal AA levels were higher in the non-CR group than in the CR group (p = 0.001). Significant positive correlations were found between exosomal AA and C-reactive protein (CRP) as well as between serum AA and CRP (ρ = 0.614, p = 0.001, and ρ = 0.624, p = 0.001, respectively). Although serum levels of LYVE-1 did not differ between the non-CR and CR groups, exosomal levels of LYVE-1 were lower in the non-CR group than in the CR group (p = 0.01). We identified positive correlations between serum/exosomal LYVE-1 and CRP only in the non-CR group (serum ρ = 0.376, p = 0.04; exosome ρ = 0.545, p = 0.002).

Conclusions

Exosomal LYVE-1 shows potential for use as an additional marker of disease activity in patients with RA, and exosomes may carry other useful markers for RA.

Deciphering Clostridium tyrobutyricum Metabolism Based on the Whole-Genome Sequence and Proteome Analyses

Clostridium tyrobutyricum is a Gram-positive anaerobic bacterium that efficiently produces butyric acid and is considered a promising host for anaerobic production of bulk chemicals. Due to limited knowledge on the genetic and metabolic characteristics of this strain, however, little progress has been made in metabolic engineering of this strain. Here we report the complete genome sequence of C. tyrobutyricum KCTC 5387 (ATCC 25755), which consists of a 3.07-Mbp chromosome and a 63-kbp plasmid. The results of genomic analyses suggested that C. tyrobutyricum produces butyrate from butyryl-coenzyme A (butyryl-CoA) through acetate reassimilation by CoA transferase, differently from Clostridium acetobutylicum, which uses the phosphotransbutyrylase-butyrate kinase pathway; this was validated by reverse transcription-PCR (RT-PCR) of related genes, protein expression levels, in vitro CoA transferase assay, and fed-batch fermentation. In addition, the changes in protein expression levels during the course of batch fermentations on glucose were examined by shotgun proteomics. Unlike C. acetobutylicum, the expression levels of proteins involved in glycolytic and fermentative pathways in C. tyrobutyricum did not decrease even at the stationary phase. Proteins related to energy conservation mechanisms, including Rnf complex, NfnAB, and pyruvate-phosphate dikinase that are absent in C. acetobutylicum, were identified. Such features explain why this organism can produce butyric acid to a much higher titer and better tolerate toxic metabolites. This study presenting the complete genome sequence, global protein expression profiles, and genome-based metabolic characteristics during the batch fermentation of C. tyrobutyricum will be valuable in designing strategies for metabolic engineering of this strain.

IMPORTANCE

Bio-based production of chemicals from renewable biomass has become increasingly important due to our concerns on climate change and other environmental problems. C. tyrobutyricum has been used for efficient butyric acid production. In order to further increase the performance and expand the capabilities of this strain toward production of other chemicals, metabolic engineering needs to be performed. For this, better understanding on the metabolic and physiological characteristics of this bacterium at the genome level is needed. This work reporting the results of complete genomic and proteomic analyses together with new insights on butyric acid biosynthetic pathway and energy conservation will allow development of strategies for metabolic engineering of C. tyrobutyricum for the bio-based production of various chemicals in addition to butyric acid.

Macrophage-secreted granulin supports pancreatic cancer metastasis by inducing liver fibrosis

Pancreatic ductal adenocarcinoma (PDAC) is a devastating metastatic disease for which better therapies are urgently needed. Macrophages enhance metastasis in many cancer types; however, the role of macrophages in PDAC liver metastasis remains poorly understood. Here we found that PDAC liver metastasis critically depends on the early recruitment of granulin-secreting inflammatory monocytes to the liver. Mechanistically, we demonstrate that granulin secretion by metastasis-associated macrophages (MAMs) activates resident hepatic stellate cells (hStCs) into myofibroblasts that secrete periostin, resulting in a fibrotic microenvironment that sustains metastatic tumour growth. Disruption of MAM recruitment or genetic depletion of granulin reduced hStC activation and liver metastasis. Interestingly, we found that circulating monocytes and hepatic MAMs in PDAC patients express high levels of granulin. These findings suggest that recruitment of granulin-expressing inflammatory monocytes plays a key role in PDAC metastasis and may serve as a potential therapeutic target for PDAC liver metastasis.

Acidosis-Induced Changes in Proteome Patterns of the Prostate Cancer-Derived Tumor Cell Line AT-1

Under various pathological conditions, such as inflammation, ischemia and in solid tumors, physiological parameters (local oxygen tension or extracellular pH) show distinct tissue abnormalities (hypoxia and acidosis). For tumors, the prevailing microenvironment exerts a strong influence on the phenotype with respect to proliferation, invasion, and metastasis formation and therefore influences prognosis. In this study, we investigate the impact of extracellular metabolic acidosis (pH 7.4 versus 6.6) on the proteome patterns of a prostate cancer-derived tumor cell type (AT-1) using isobaric labeling and LC-MS/MS analysis. In total, 2710 proteins were identified and quantified across four biological replicates, of which seven were significantly affected with changes >50% and used for validation. Glucose transporter 1 and farnesyl pyrophosphatase were found to be down-regulated after 48 h of acidic treatment, and metallothionein 2A was reduced after 24 h and returned to control values after 48 h. After 24 and 48 h at pH 6.6, glutathione S transferase A3 and NAD(P)H dehydrogenase 1, cellular retinoic acid-binding protein 2, and Na-bicarbonate transporter 3 levels were found to be increased. The changes in protein levels were confirmed by transcriptome and functional analyses. In addition to the experimental in-depth investigation of proteins with changes >50%, functional profiling (statistical enrichment analysis) including proteins with changes >20% revealed that acidosis upregulates GSH metabolic processes, citric acid cycle, and respiratory electron transport. Metabolism of lipids and cholesterol biosynthesis were downregulated. Our data comprise the first comprehensive report on acidosis-induced changes in proteome patterns of a tumor cell line.

Tumor Interstitial Fluid Formation, Characterization, and Clinical Implications

The interstitium, situated between the blood and lymph vessels and the cells, consists of a solid or matrix phase and a fluid phase representing the tissue microenvironment. In the present review, we focus on the interstitial fluid phase of solid tumors, the tumor interstitial fluid (TIF), i.e., the fluid bathing the tumor and stroma cells, also including immune cells. This is a component of the internal milieu of a solid tumor that has attracted regained attention. Access to this space may provide important insight into tumor development and therapy response. TIF is formed by transcapillary filtration, and since this fluid is not readily available we discuss available techniques for TIF isolation, results from subsequent characterization and implications of recent findings with respect to fluid filtration and uptake of macromolecular therapeutic agents. There appear to be local gradients in signaling substances from neoplastic tissue to plasma that may provide new understanding of tumor biology. The development of sensitive proteomic technologies has made TIF a valuable source for tumor specific proteins and biomarker candidates. Potential biomarkers will appear locally in high concentrations in tumors and may eventually be found diluted in the plasma. Access to TIF that reliably reflects the local tumor microenvironment enables identification of substances that can be used in early detection and monitoring of disease.

Identification of proteins responsible for adriamycin resistance in breast cancer cells using proteomics analysis

Chemoresistance is a poor prognostic factor in breast cancer and is a major obstacle to the successful treatment of patients receiving chemotherapy. However, the precise mechanism of resistance remains unclear. In this study, a pair of breast cancer cell lines, MCF-7 and its adriamycin-resistant counterpart MCF-7/ADR was used to examine resistance-dependent cellular responses and to identify potential therapeutic targets. We applied nanoflow liquid chromatography (nLC) and tandem mass tags (TmT) quantitative mass spectrometry to distinguish the differentially expressed proteins (DEPs) between the two cell lines. Bioinformatics analyses were used to identify functionally active proteins and networks. 80 DEPs were identified with either up- or down-regulation. Basing on the human protein-protein interactions (PPI), we have retrieved the associated functional interaction networks for the DEPs and analyzed the biological functions. Six different signaling pathways and most of the DEPs strongly linked to chemoresistance, invasion, metastasis development, proliferation, and apoptosis. The identified proteins in biological networks served to resistant drug and to select critical candidates for validation analyses by western blot. The glucose-6-phosphate dehydrogenase (G6PD), gamma-glutamyl cyclotransferase (GGCT), isocitrate dehydrogenase 1 (NADP+,soluble)(IDH1), isocitrate dehydrogenase 2 (NADP+,mitochondrial) (IDH2) and glutathione S-transferase pi 1(GSTP1), five of the critical components of GSH pathway, contribute to chemoresistance.

From pathways to networks: connecting dots by establishing protein-protein interaction networks in signaling pathways using affinity purification and mass spectrometry

Signal transductions are the basis of biological activities in all living organisms. Studying the signaling pathways, especially under physiological conditions, has become one of the most important facets of modern biological research. During the last decade, MS has been used extensively in biological research and is proven to be effective in addressing important biological questions. Here, we review the current progress in the understanding of signaling networks using MS approaches. We will focus on studies of protein-protein interactions that use affinity purification followed by MS approach. We discuss obstacles to affinity purification, data processing, functional validation, and identification of transient interactions and provide potential solutions for pathway-specific proteomics analysis, which we hope one day will lead to a comprehensive understanding of signaling networks in humans.

Identification of proteins involved in human sperm motility using high-throughput differential proteomics

Mammalian sperm motility is a prerequisite for in vivo fertilization, and alterations in this parameter are commonly observed in infertile males. However, we still do not have a complete understanding of the molecular mechanisms controlling it. The aim of this study was to identify proteins involved in human sperm motility deficiency by using TMT protein labeling and LC-MS/MS. Two complementary approaches were used: comparison between sperm samples differing in motility (asthenozoospermic versus normozoospermic) and comparison between sperm subpopulations of fractionated normozoospermic samples differing in motility (non-migrated versus migrated). LC-MS/MS resulted in the identification of 1157 and 887 proteins in the first and second approaches, respectively. Remarkably, similar proteomic alterations were detected in the two experiments, with 80 proteins differentially expressed in the two groups of samples and 93 differentially expressed in the two groups of subpopulations. The differential proteins were analyzed by GO, cellular pathways, and clustering analyses and resulted in the identification of core deregulated proteins and pathways associated with sperm motility dysfunction. These included proteins associated with energetic metabolism, protein folding/degradation, vesicle trafficking, and the cytoskeleton. Contrary to what is usually accepted, the outcomes support the hypothesis that several metabolic pathways (notably, mitochondrial-related ones) contribute toward regulating sperm motility.

High-throughput sperm differential proteomics suggests that epigenetic alterations contribute to failed assisted reproduction

STUDY QUESTION

Are there quantitative alterations in the proteome of normozoospermic sperm samples that are able to complete IVF but whose female partner does not achieve pregnancy?

SUMMARY ANSWER

Normozoospermic sperm samples with different IVF outcomes (pregnancy versus no pregnancy) differed in the levels of at least 66 proteins.

WHAT IS KNOWN ALREADY

The analysis of the proteome of sperm samples with distinct fertilization capacity using low-throughput proteomic techniques resulted in the detection of a few differential proteins. Current high-throughput mass spectrometry approaches allow the identification and quantification of a substantially higher number of proteins.

STUDY DESIGN, SIZE, DURATION

This was a case-control study including 31 men with normozoospermic sperm and their partners who underwent IVF with successful fertilization recruited between 2007 and 2008.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Normozoospermic sperm samples from 15 men whose female partners did not achieve pregnancy after IVF (no pregnancy) and 16 men from couples that did achieve pregnancy after IVF (pregnancy) were included in this study. To perform the differential proteomic experiments, 10 no pregnancy samples and 10 pregnancy samples were separately pooled and subsequently used for tandem mass tags (TMT) protein labelling, sodium dodecyl sulphate-polyacrylamide gel electrophoresis, liquid chromatography tandem mass spectrometry (LC-MS/MS) identification and peak intensity relative protein quantification. Bioinformatic analyses were performed using UniProt Knowledgebase, DAVID and Reactome. Individual samples (n = 5 no pregnancy samples; n = 6 pregnancy samples) and aliquots from the above TMT pools were used for western blotting.

MAIN RESULTS AND THE ROLE OF CHANCE

By using TMT labelling and LC-MS/MS, we have detected 31 proteins present at lower abundance (ratio no pregnancy/pregnancy < 0.67) and 35 at higher abundance (ratio no pregnancy/pregnancy > 1.5) in the no pregnancy group. Bioinformatic analyses showed that the proteins with differing abundance are involved in chromatin assembly and lipoprotein metabolism (P values < 0.05). In addition, the differential abundance of one of the proteins (SRSF protein kinase 1) was further validated by western blotting using independent samples (P value < 0.01).

LIMITATIONS, REASONS FOR CAUTION

For individual samples the amount of recovered sperm not used for IVF was low and in most of the cases insufficient for MS analysis, therefore pools of samples had to be used to this end.

WIDER IMPLICATIONS OF THE FINDINGS

Alterations in the proteins involved in chromatin assembly and metabolism may result in epigenetic errors during spermatogenesis, leading to inaccurate sperm epigenetic signatures, which could ultimately prevent embryonic development. These sperm proteins may thus possibly have clinical relevance.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the Spanish Ministry of Economy and Competitiveness (Ministerio de Economia y Competividad; FEDER BFU 2009-07118 and PI13/00699) and Fundación Salud 2000 SERONO13-015. There are no competing interests to declare.

Colorectal cancer candidate biomarkers identified by tissue secretome proteome profiling

Colorectal cancer (CRC) is a major health problem. Biomarkers associated with molecular changes in cancer cells can aid early detection, diagnosis, prognosis, therapy selection, and disease monitoring. Tumor tissue secretomes are a rich source of candidate biomarkers. To identify CRC protein biomarkers, secretomes of four pairs of human CRC tissue and patient-matched normal colon tissue samples, and secretomes of five CRC cell lines were analyzed by GeLC-MS/MS. Subsequent data analysis was based on label-free spectral counting, Ingenuity Pathway Analysis, Secretome/SignalP, STRING and Cytoscape, resulting in 2703 protein identifications in the tissue secretomes, of which 409 proteins were significantly more present in CRC samples than in controls. Biomarker selection of 76 candidates was based on consistent and abundant over-representation in cancer- compared to control-secretomes, and presumed neoplastic origin. Overlap analysis with previously obtained datasets revealed 21 biomarkers suited for early detection of CRC. Immunohistochemistry confirmed overexpression in CRC of one candidate marker (MCM5). In conclusion, a human reference dataset of 76 candidate biomarkers was identified for which we illustrate that combination with existing pre-clinical datasets allows pre-selection of biomarkers for blood- or stool-based assays to support clinical management of CRC. Further dedicated validation studies are required to demonstrate their clinical applicability.

BIOLOGICAL SIGNIFICANCE

Tissue secretome proteomes are a rich source of candidate biomarkers. Several secretome proteome datasets have been obtained from pre-clinical in vitro and in vivo colorectal cancer (CRC) model systems, yielding promising CRC biomarkers obtained under well-defined experimentally controlled conditions. However, which of these biomarker proteins are actually secreted by human CRC samples was not known. To our knowledge, this is the first study that directly compares secretome proteomes from clinically relevant human CRC tissues to patient-matched normal colon tissues. We identified 76 human CRC protein biomarkers that may facilitate blood-based or stool-based assay development to support clinical management of CRC. Overlap analysis with datasets from well-defined pre-clinical studies helps to determine what clinical application suits these human CRC biomarkers best, i.e. early detection, diagnosis, prognosis, therapy selection, and/or disease monitoring of CRC. This is demonstrated for a CRC mouse model dataset, revealing 21 human CRC biomarkers suited for early detection of CRC.

Omic-profiling in breast cancer metastasis to bone: implications for mechanisms, biomarkers and treatment

Despite well-recognised advances in breast cancer treatment, there remain substantial numbers of patients who develop metastatic disease, of which up to 70% involves spread to bone, resulting in skeletal complications which have a major negative impact on mortality and quality of life. Bisphosphonates and newer bone-targeted agents have reduced the prevalence of skeletal complications, yet there remains significant unmet clinical need, particularly for the development of more specific therapies for the prevention and treatment of metastatic bone disease, for the prediction of risk of its development in individual patients and for the prediction of response to treatments. Modern 'omic' strategies can potentially make a major contribution to meeting this need. Technological advances in the field of nucleic acid sequencing, mass spectrometry and metabolic profiling have driven progress in genomics, transcriptomics (functional genomics), proteomics and metabolomics. This review appraises the recent application of these approaches to studies of breast cancer metastasis (particularly to bone), with a focus on understanding how omic approaches may lead to new therapeutic options and to novel biomarker molecules or molecular signatures with potential value in clinical practise. The increasingly recognised need for rigorous sample quality control and both pre-clinical and clinical validation to meet the ultimate goals of clinical utility and patient benefit is discussed. Future directions of omic driven research in breast cancer metastasis are considered, in particular micro-RNAs and their role in the post-transcriptional regulation of gene function and the possible role of cancer-stem cells and epigenetic modifications in the development of distant metastases.

Increased WD-repeat containing protein 1 in interstitial fluid from ovarian carcinomas shown by comparative proteomic analysis of malignant and healthy gynecological tissue

We aimed to identify differentially expressed proteins in interstitial fluid from ovarian cancer employing multiple fractioning and high resolution mass spectrometry-based proteomic analysis, and asked whether specific proteins that may serve as biomarker candidates or therapeutic targets could be identified. High throughput proteomics was conducted on immunodepleted and fractioned interstitial fluid from pooled samples of ovarian carcinomas, using endometrial carcinomas and healthy ovarian tissue as controls. Differential analysis revealed the up-regulation of extracellular proteasomes in tumor interstitial fluid compared to the healthy control. Moreover, a number of differentially expressed proteins in interstitial fluid from ovarian carcinomas compared with control tissues were identified. Detection of proteasome 20S related proteins in TIF compared to IF from healthy tissue indicates that the 20S proteasome can have a role in the tumor microenvironment. Six selected proteins, CEACAM5, FREM2, MUC5AC, TFF3, PYCARD and WDR1, were independently validated in individual tumor lysates from ovarian carcinomas by multiple reaction monitoring initiated detection and sequence analysis, Western blot and/or selected reaction monitoring. Quantification of specific proteins revealed substantial heterogeneity between individual samples. Nevertheless, WD repeat-containing protein 1 was confirmed as being significantly overexpressed in interstitial fluid from ovarian carcinomas compared to healthy ovarian tissue by Orbitrap analysis of individual native interstitial fluid from ovarian and endometrial carcinomas and healthy ovarian tissue. We suggest that this protein should be explored as a therapeutic target in ovarian carcinomas. This article is part of a Special Issue entitled: An Updated Secretome.

Relative quantification of biomarkers using mixed-isotope labeling coupled with MS

The identification and quantification of important biomarkers is a critical first step in the elucidation of biological systems. Biomarkers take many forms as cellular responses to stimuli and can be manifested during transcription, translation, and/or metabolic processing. Increasingly, researchers have relied upon mixed-isotope labeling (MIL) coupled with MS to perform relative quantification of biomarkers between two or more biological samples. MIL effectively tags biomarkers of interest for ease of identification and quantification within the mass spectrometer by using isotopic labels that introduce a heavy and light form of the tag. In addition to MIL coupled with MS, a number of other approaches have been used to quantify biomarkers including protein gel staining, enzymatic labeling, metabolic labeling, and several label-free approaches that generate quantitative data from the MS signal response. This review focuses on MIL techniques coupled with MS for the quantification of protein and small-molecule biomarkers.

Quantitative proteomics of auditory fear conditioning

Auditory fear conditioning is a well-characterized rodent learning model where a neutral auditory cue is paired with an aversive outcome to induce associative fear memory. The storage of long-term auditory fear memory requires long-term potentiation (LTP) in the lateral amygdala and de novo protein synthesis. Although many studies focused on individual proteins have shown their contribution to LTP and fear conditioning, non-biased genome-wide studies have only recently been possible with microarrays, which nevertheless fall short of measuring changes at the level of proteins. Here we employed quantitative proteomics to examine the expression of hundreds of proteins in the lateral amygdala in response to auditory fear conditioning. We found that various proteins previously implicated in LTP, learning and axon/dendrite growth were regulated by fear conditioning. A substantial number of proteins that were regulated by fear conditioning have not yet been studied specifically in learning or synaptic plasticity.

The cancer secretome, current status and opportunities in the lung, breast and colorectal cancer context

Despite major improvements on the knowledge and clinical management, cancer is still a deadly disease. Novel biomarkers for better cancer detection, diagnosis and treatment prediction are urgently needed. Proteins secreted, shed or leaking from the cancer cell, collectively termed the cancer secretome, are promising biomarkers since they might be detectable in blood or other biofluids. Furthermore, the cancer secretome in part represents the tumor microenvironment that plays a key role in tumor promoting processes such as angiogenesis and invasion. The cancer secretome, sampled as conditioned medium from cell lines, tumor/tissue interstitial fluid or tumor proximal body fluids, can be studied comprehensively by nanoLC-MS/MS-based approaches. Here, we outline the importance of current cancer secretome research and describe the mass spectrometry-based analysis of the secretome. Further, we provide an overview of cancer secretome research with a focus on the three most common cancer types: lung, breast and colorectal cancer. We conclude that the cancer secretome research field is a young, but rapidly evolving research field. Up to now, the focus has mainly been on the discovery of novel promising secreted cancer biomarker proteins. An interesting finding that merits attention is that in cancer unconventional secretion, e.g. via vesicles, seems increased. Refinement of current approaches and methods and progress in clinical validation of the current findings are vital in order to move towards applications in cancer management. This article is part of a Special Issue entitled: An Updated Secretome.

Quantitative proteomic analysis reveals that lipopolysaccharide induces mitogen-activated protein kinase-dependent activation in human microglial cells

Microglial cells act as the first and main form of active immune defense in the central nervous system related to inflammation and neurodegenerative disease. Lipopolysaccharide (LPS) induces many genes encoding inflammatory mediators, including cytokines such as tumor necrosis factor-α, interleukin-1β, (IL-1β), and IL-6, chemokines, and prostaglandins in microglial cells. Quantitative proteomics methods with isobaric chemical labeling using tandem mass tags and 2D-nano LC-ESI-MS/MS were used to systematically analyze proteomic changes in microglia responding to LPS stimulation. As a result, we found that the expression level of 21 proteins in human microglial cells changed after activation. Among those, one of the strong mitogen-activated protein kinase (MAPK) regulator proteins, CMPK1 was highly upregulated after LPS stimulation in human microglial cells. We detected and validated upregulation of MAPK including ERK1/2, p38, and SAPK/JNK by immunohistochemistry and Western blotting. NFκB, strong transcription factor of CMPK1, was translocated to the nucleus from the cytosol by high contents screening after LPS stimulation. Taken together, we conclude that MAPK signaling plays an important role in LPS-induced human microglial activation related to inflammatory response.