Phosphoprotein secretome of tumor cells as a source of candidates for breast cancer biomarkers in plasma

Roles of Post-Translational Modifications of Transcription Factors Involved in Breast Cancer Hypoxia

BC is the most commonly diagnosed cancer and the second leading cause of cancer death among women worldwide. Cellular stress is a condition that leads to disrupted homeostasis by extrinsic and intrinsic factors. Among other stressors, hypoxia is a driving force for breast cancer (BC) progression and a general hallmark of solid tumors. Thus, intratumoral hypoxia is an important determinant of invasion, metastasis, treatment failure, prognosis, and patient mortality. Acquisition of the epithelial-mesenchymal transition (EMT) phenotype is also a consequence of tumor hypoxia. The cellular response to hypoxia is mainly regulated by the hypoxia signaling pathway, governed by hypoxia-inducible factors (HIFs), mainly HIF1α. HIFs are a family of transcription factors (TFs), which induce the expression of target genes involved in cell survival and proliferation, metabolic reprogramming, angiogenesis, resisting apoptosis, invasion, and metastasis. HIF1α cooperates with a large number of other TFs. In this review, we focused on the crosstalk and cooperation between HIF1α and other TFs involved in the cellular response to hypoxia in BC. We identified a cluster of TFs, proposed as the HIF1α-TF interactome, that orchestrates the transcription of target genes involved in hypoxia, due to their post-translational modifications (PTMs), including phosphorylation/dephosphorylation, ubiquitination/deubiquitination, SUMOylation, hydroxylation, acetylation, S-nitrosylation, and palmitoylation. PTMs of these HIF1α-related TFs drive their stability and activity, degradation and turnover, and the bidirectional translocation between the cytoplasm or plasma membrane and nucleus of BC cells, as well as the transcription/activation of proteins encoded by oncogenes or inactivation of tumor suppressor target genes. Consequently, PTMs of TFs in the HIF1α interactome are crucial regulatory mechanisms that drive the cellular response to oxygen deprivation in BC cells.

Bio-Pathological Functions of Posttranslational Modifications of Histological Biomarkers in Breast Cancer

Proteins are the most common types of biomarkers used in breast cancer (BC) theranostics and management. By definition, a biomarker must be a relevant, objective, stable, and quantifiable biomolecule or other parameter, but proteins are known to exhibit the most variate and profound structural and functional variation. Thus, the proteome is highly dynamic and permanently reshaped and readapted, according to changing microenvironments, to maintain the local cell and tissue homeostasis. It is known that protein posttranslational modifications (PTMs) can affect all aspects of protein function. In this review, we focused our analysis on the different types of PTMs of histological biomarkers in BC. Thus, we analyzed the most common PTMs, including phosphorylation, acetylation, methylation, ubiquitination, SUMOylation, neddylation, palmitoylation, myristoylation, and glycosylation/sialylation/fucosylation of transcription factors, proliferation marker Ki-67, plasma membrane proteins, and histone modifications. Most of these PTMs occur in the presence of cellular stress. We emphasized that these PTMs interfere with these biomarkers maintenance, turnover and lifespan, nuclear or subcellular localization, structure and function, stabilization or inactivation, initiation or silencing of genomic and non-genomic pathways, including transcriptional activities or signaling pathways, mitosis, proteostasis, cell-cell and cell-extracellular matrix (ECM) interactions, membrane trafficking, and PPIs. Moreover, PTMs of these biomarkers orchestrate all hallmark pathways that are dysregulated in BC, playing both pro- and/or antitumoral and context-specific roles in DNA damage, repair and genomic stability, inactivation/activation of tumor-suppressor genes and oncogenes, phenotypic plasticity, epigenetic regulation of gene expression and non-mutational reprogramming, proliferative signaling, endocytosis, cell death, dysregulated TME, invasion and metastasis, including epithelial-mesenchymal/mesenchymal-epithelial transition (EMT/MET), and resistance to therapy or reversal of multidrug therapy resistance. PTMs occur in the nucleus but also at the plasma membrane and cytoplasmic level and induce biomarker translocation with opposite effects. Analysis of protein PTMs allows for the discovery and validation of new biomarkers in BC, mainly for early diagnosis, like extracellular vesicle glycosylation, which may be considered as a potential source of circulating cancer biomarkers.

Phosphoproteomics changes due to allograft-induced stress responses of Pinctada fucata martensii

Protein phosphorylation modifications are post-translational modifications (PTMs) that play important roles in signal transduction and immune regulation. Implanting a spherical nucleus into a recipient shellfish is critical in marine pearl aquaculture. Protein phosphorylation may be important in the immune responses of Pinctada fucata martensii after nucleus implantation, but their involvement in regulation remains unclear. Here, phosphoproteomics of P. f. martensii gill tissues was conducted 12 h after nuclear implantation using label-free data-independent acquisition (DIA) with LC-MS/MS. Among the 4024 phosphorylated peptides with quantitative information, 181 were up-regulated and 148 were down-regulated. Functional enrichment analysis of these differentially expressed phosphorylated proteins (DEPPs) revealed significant enrichment in functions related to membrane trafficking, exosomes, cytoskeleton, and signal transduction mechanisms. Further, 16 conserved motifs were identified among the DEPPs, including the RSphP, SphP, RSphA, RSphE, PTphP, and ATphP motifs that were significantly conserved, and which may be related to specific kinase recognition. Parallel response monitoring (PRM) analysis validated the abundances of 12 DEPPs from the proteomics, indicating that the phosphoproteomics analyses were robust. 12 DEPPs were selected from the proteomics results through Quantitative real-time PCR (qPCR) technology, and verification analysis was conducted at the gene level. The study suggests that kinases such as MAPKs, Akt, and CK2 may regulate the phosphorylation of related proteins following nuclear implantation. Furthermore, the important signaling pathways of Rap 1, IL-17A, and NF-κB, which are influenced by phosphorylated or dephosphorylated proteins, are found to be involved in this response. Overall, this study revealed the protein phosphorylation responses after nucleus implantation in P. f. martensii, helping to elucidate the characteristics and mechanisms of immune regulation responses in P. f. martensii, in addition to promoting a further understanding of protein phosphorylation modification functions in P. f. martensii.

An Introduction to Analytical Challenges, Approaches, and Applications in Mass Spectrometry-Based Secretomics

The active release of proteins into the extracellular space and the proteolytic cleavage of cell surface proteins are key processes that coordinate and fine-tune a multitude of physiological functions. The entirety of proteins that fulfill these extracellular tasks are referred to as the secretome and are of special interest for the investigation of biomarkers of disease states and physiological processes related to cell-cell communication. LC-MS-based proteomics approaches are a valuable tool for the comprehensive and unbiased characterization of this important subproteome. This review discusses procedures, opportunities, and limitations of mass spectrometry-based secretomics to better understand and navigate the complex analytical landscape for studying protein secretion in biomedical science.

PhosY-secretome profiling combined with kinase-substrate interaction screening defines active c-Src-driven extracellular signaling

c-Src tyrosine kinase is a renowned key intracellular signaling molecule and a potential target for cancer therapy. Secreted c-Src is a recent observation, but how it contributes to extracellular phosphorylation remains elusive. Using a series of domain deletion mutants, we show that the N-proximal region of c-Src is essential for its secretion. The tissue inhibitor of metalloproteinases 2 (TIMP2) is an extracellular substrate of c-Src. Limited proteolysis-coupled mass spectrometry and mutagenesis studies verify that the Src homology 3 (SH3) domain of c-Src and the P31VHP34 motif of TIMP2 are critical for their interaction. Comparative phosphoproteomic analyses identify an enrichment of PxxP motifs in phosY-containing secretomes from c-Src-expressing cells with cancer-promoting roles. Inhibition of extracellular c-Src using custom SH3-targeting antibodies disrupt kinase-substrate complexes and inhibit cancer cell proliferation. These findings point toward an intricate role for c-Src in generating phosphosecretomes, which will likely influence cell-cell communication, particularly in c-Src-overexpressing cancers.

Construction and validation of a prognostic model based on ten signature cell cycle-related genes for early-stage lung squamous cell carcinoma

BACKGROUND

We performed a bioinformatics analysis to screen for cell cycle-related differentially expressed genes (DEGs) and constructed a model for the prognostic prediction of patients with early-stage lung squamous cell carcinoma (LSCC).

METHODS

From a gene expression omnibus (GEO) database, the GSE157011 dataset was randomly divided into an internal training group and an internal testing group at a 1:1 ratio, and the GSE30219, GSE37745, GSE42127, and GSE73403 datasets were merged as the external validation group. We performed single-sample gene set enrichment analysis (ssGSEA), univariate Cox analysis, and difference analysis, and identified 372 cell cycle-related genes. Additionally, we combined LASSO/Cox regression analysis to construct a prognostic model. Then, patients were divided into high-risk and low-risk groups according to risk scores. The internal testing group, discovery set, and external verification set were used to assess model reliability. We used a nomogram to predict patient prognoses based on clinical features and risk values. Clinical relevance analysis and the Human Protein Atlas (HPA) database were used to verify signature gene expression.

RESULTS

Ten cell cycle-related DEGs (EIF2B1, FSD1L, FSTL3, ORC3, HMMR, SETD6, PRELP, PIGW, HSD17B6, and GNG7) were identified and a model based on the internal training group constructed. From this, patients in the low-risk group had a higher survival rate when compared with the high-risk group. Time-dependent receiver operating characteristic (tROC) and Cox regression analyses showed the model was efficient and accurate. Clinical relevance analysis and the HPA database showed that DEGs were significantly dysregulated in LSCC tissue.

CONCLUSION

Our model predicted the prognosis of early-stage LSCC patients and demonstrated potential applications for clinical decision-making and individualized therapy.

Disulfide bond and crosslinking analyses reveal inter-domain interactions that contribute to the rigidity of placental malaria VAR2CSA structure and formation of CSA binding channel

VAR2CSA, a multidomain Plasmodium falciparum protein, mediates the adherence of parasite-infected red blood cells to chondroitin 4-sulfate (C4S) in the placenta, contributing to placental malaria. Therefore, detailed understanding of VAR2CSA structure likely help developing strategies to treat placental malaria. The VAR2CSA ectodomain consists of an N-terminal segment (NTS), six Duffy binding-like (DBL) domains, and three interdomains (IDs) present in sequence NTS-DBL1x-ID1-DBL2x-ID2-DBL3x-DBL4ε-ID3-DBL5ε-DBL6ε. Recent electron microscopy studies showed that VAR2CSA is compactly organized into a globular structure containing C4S-binding channel, and that DBL5ε-DBL6ε arm is attached to the NTS-ID3 core structure. However, the structural elements involved in inter-domain interactions that stabilize the VAR2CSA structure remain largely not understood. Here, limited proteolysis and peptide mapping by mass spectrometry showed that VAR2CSA contains several inter-domain disulfide bonds that stabilize its compact structure. Chemical crosslinking-mass spectrometry showed that all IDs interact with DBL4ε; additionally, IDs interact with other DBL domains, demonstrating that IDs are the key structural scaffolds that shape the functional NTS-ID3 core. Ligand binding analysis suggested that NTS considerably restricts the C4S binding. Overall, our study revealed that inter-domain disulfide bonds and interactions between IDs and DBL domains contribute to the stability of VAR2CSA structural architecture and formation of C4S-binding channel.

Phosphorylation of IGFBP-3 by Casein Kinase 2 Blocks Its Interaction with Hyaluronan, Enabling HA-CD44 Signaling Leading to Increased NSCLC Cell Survival and Cisplatin Resistance

Cisplatin is a platinum agent used in the treatment of non-small cell lung cancer (NSCLC). Much remains unknown regarding the basic operative mechanisms underlying cisplatin resistance in NSCLC. In this study, we found that phosphorylation of IGFBP-3 by CK2 (P-IGFBP-3) decreased its binding to hyaluronan (HA) but not to IGF-1 and rendered the protein less effective at reducing cell viability or increasing apoptosis than the non-phosphorylated protein with or without cisplatin in the human NSCLC cell lines, A549 and H1299. Our data suggest that blocking CD44 signaling augmented the effects of cisplatin and that IGFBP-3 was more effective at inhibiting HA-CD44 signaling than P-IGFBP-3. Blocking CK2 activity and HA-CD44 signaling increased cisplatin sensitivity and more effectively blocked the PI3K and AKT activities and the phospho/total NFκB ratio and led to increased p53 activation in A549 cells. Increased cell sensitivity to cisplatin was observed upon co-treatment with inhibitors targeted against PI3K, AKT, and NFκB while blocking p53 activity decreased A549 cell sensitivity to cisplatin. Our findings shed light on a novel mechanism employed by CK2 in phosphorylating IGFBP-3 and increasing cisplatin resistance in NSCLC. Blocking phosphorylation of IGFBP-3 by CK2 may be an effective strategy to increase NSCLC sensitivity to cisplatin.

Fam20C Regulates Bone Resorption and Breast Cancer Bone Metastasis through Osteopontin and BMP4

Fam20C is a kinase that generates the majority of secreted phosphoproteins and regulates biomineralization. However, its potential roles in bone resorption and breast cancer bone metastasis are unknown. Here we show that Fam20C in the myeloid lineage suppresses osteoclastogenesis and bone resorption, during which, osteopontin (OPN) is the most abundant phosphoprotein secreted in a Fam20C-dependent manner. OPN phosphorylation by Fam20C decreased OPN secretion, and OPN neutralization reduced Fam20C deficiency-induced osteoclast differentiation and bone metastasis. In contrast, Fam20C in breast cancer cells promoted bone metastasis by facilitating the phosphorylation and secretion of BMP4, which in turn enhanced osteoclastogenesis. Mutation of the BMP4 phosphorylation site elevated BMP4 lysosomal degradation and reduced BMP4 secretion. In breast cancer cells, BMP4 depletion or treatment with a BMP4 signaling inhibitor diminished osteoclast differentiation and bone metastasis and abolished Fam20C-mediated regulation of these processes. Collectively, this study discovers distinct roles for Fam20C in myeloid cells and breast cancer cells and highlights OPN and BMP4 as potential therapeutic targets for breast cancer bone metastasis. SIGNIFICANCE: Osteoclastogenesis and bone metastasis are suppressed by myeloid-derived Fam20C, but enhanced by breast cancer-associated Fam20C, uncovering novel Fam20C functions and new therapeutic strategies via targeting Fam20C substrates OPN and BMP4.

Detection of Human Cholangiocarcinoma Markers in Serum Using Infrared Spectroscopy

Simple Summary

Cholangiocarcinoma is a form of liver cancer that is found, predominantly, in Thailand. Due to the non-specific symptoms and laboratory investigation, it is difficult to rule out cholangiocarcinoma from other liver conditions. Here, we demonstrate the development of a diagnostic tool for cholangiocarcinoma, based on the ATR-FTIR analyses of sera, coupled with multivariate analyses and machine learning tools to obtain a better specificity. The innovative approach that shows highly promising results for this otherwise difficult to diagnose cancer.

Abstract

Cholangiocarcinoma (CCA) is a malignancy of the bile duct epithelium. Opisthorchis viverrini infection is a known high-risk factor for CCA and in found, predominantly, in Northeast Thailand. The silent disease development and ineffective diagnosis have led to late-stage detection and reduction in the survival rate. Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) is currently being explored as a diagnostic tool in medicine. In this study, we apply ATR-FTIR to discriminate CCA sera from hepatocellular carcinoma (HCC), biliary disease (BD) and healthy donors using a multivariate analysis. Spectral markers differing from healthy ones are observed in the collagen band at 1284, 1339 and 1035 cm⁻¹, the phosphate band (vsPO2−) at 1073 cm⁻¹, the polysaccharides band at 1152 cm⁻¹ and 1747 cm⁻¹ of lipid ester carbonyl. A Principal Component Analysis (PCA) shows discrimination between CCA and healthy sera using the 1400–1000 cm⁻¹ region and the combined 1800—1700 + 1400–1000 cm⁻¹ region. Partial Least Square-Discriminant Analysis (PLS-DA) scores plots in four of five regions investigated, namely, the 1400–1000 cm⁻¹, 1800–1000 cm⁻¹, 3000–2800 + 1800–1000 cm⁻¹ and 1800–1700 + 1400–1000 cm⁻¹ regions, show discrimination between sera from CCA and healthy volunteers. It was not possible to separate CCA from HCC and BD by PCA and PLS-DA. CCA spectral modelling is established using the PLS-DA, Support Vector Machine (SVM), Random Forest (RF) and Neural Network (NN). The best model is the NN, which achieved a sensitivity of 80–100% and a specificity between 83 and 100% for CCA, depending on the spectral window used to model the spectra. This study demonstrates the potential of ATR-FTIR spectroscopy and spectral modelling as an additional tool to discriminate CCA from other conditions.

Inhibition of FSTL3 abates the proliferation and metastasis of renal cell carcinoma via the GSK-3β/β-catenin signaling pathway

Renal cell carcinoma (RCC) is a lethal malignancy of the genitourinary system. Follistatin-like 3 (FSTL3), which mediates cell differentiation and growth, acts as a biomarker of tumors and participates in cancer development and progression. Presently, the FSTL3’s functions in RCC were investigated. Quantitative reverse transcription PCR (qRT-PCR), Western Blot, and enzyme linked immunosorbent assay (ELISA) were conducted to verify FSTL3 expression in RCC tissues and cell lines. BrdU assay and CCK8 experiment were made to monitor cell proliferation. Transwell was implemented to examine the invasion of the cells. Flow cytometry analyzed cell apoptosis, and Western Blot evaluated the protein levels of E-cadherin, Twist, and Slug. In the meantime, the protein profiles of the GSK-3β, β-catenin, and TGF-β signaling pathways were ascertained. Moreover, the Xenograft tumor model was constructed in nude mice for measuring tumor growth in vivo. The statistics showed that FSTL3 presented an overexpression in RCC, and patients with a lower expression of FSTL3 manifested a better prognosis. Down-regulated FSTL3 hampered the proliferation, invasion, EMT, and tumor growth of RCC cells and caused cell apoptosis. On the contrary, FSTL3 overexpression enhanced the malignant behaviors of RCC cells. Furthermore, FSTL3 knockdown bolstered GSK-3β, suppressed β-catenin, and reduced BMP1-SMAD pathway activation. Inhibited β-catenin substantially mitigated FSTL3-mediated promoting functions in RCC. In short, FSTL3 functions as an oncogene in RCC by modulating the GSK-3β/β-catenin signaling pathway.

Phosphorylated Osteopontin Secreted from Cancer Cells Induces Cancer Cell Motility

Osteopontin (OPN) plays a pivotal role in cancer cell invasion and metastasis. Although OPN has a large number of phosphorylation sites, the functional significance of OPN phosphorylation in cancer cell motility remains unclear. In this study, we attempted to investigate whether phosphorylated OPN secreted from cancer cells affect cancer cell migration. Quantitative PCR and Western blot analyses revealed that MDA-MB435S, A549, and H460 cells highly expressed OPN, whereas the OPN expression levels in H358, MIAPaca-2, and Panc-1 cells were quite low or were not detected. Compared with the cancer cell lines with a low OPN expression, the high OPN-expressing cancer cell lines displayed a higher cell migration, and the cell migration was suppressed by the anti-OPN antibody. This was confirmed by the OPN overexpression in H358 cancer cells with a low endogenous OPN. Phos-tag ELISA showed that phosphorylated OPN was abundant in the cell culture media of A549 and H460 cells, but not in those of MDA-MB435S cells. Moreover, the A549 and H460 cell culture media, as well as the MDA-MB435S cell culture media with a kinase treatment increased cancer cell motility, both of which were abrogated by phosphatase treatment or anti-OPN antibodies. These results suggest that phosphorylated OPN secreted from cancer cells regulates cancer cell motility.

Molecular architecture and domain arrangement of the placental malaria protein VAR2CSA suggests a model for carbohydrate binding

VAR2CSA is the placental-malaria-specific member of the antigenically variant Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) family. It is expressed on the surface of Plasmodium falciparum-infected host red blood cells and binds to specific chondroitin-4-sulfate chains of the placental proteoglycan receptor. The functional ∼310 kDa ectodomain of VAR2CSA is a multidomain protein that requires a minimum 12-mer chondroitin-4-sulfate molecule for specific, high affinity receptor binding. However, it is not known how the individual domains are organized and interact to create the receptor-binding surface, limiting efforts to exploit its potential as an effective vaccine or drug target. Using small angle X-ray scattering and single particle reconstruction from negative-stained electron micrographs of the ectodomain and multidomain constructs, we have determined the structural architecture of VAR2CSA. The relative locations of the domains creates two distinct pores that can each accommodate the 12-mer of chondroitin-4-sulfate, suggesting a model for receptor binding. This model has important implications for understanding cytoadherence of infected red blood cells and potentially provides a starting point for developing novel strategies to prevent and/or treat placental malaria.

Phosphoproteomic strategies in cancer research: a minireview

Understanding the cellular processes is central to comprehend disease conditions and is also true for cancer research. Proteomic studies provide significant insight into cancer mechanisms and aid in the diagnosis and prognosis of the disease. Phosphoproteome is one of the most studied complements of the whole proteome given its importance in the understanding of cellular processes such as signaling and regulations. Over the last decade, several new methods have been developed for phosphoproteome analysis. A significant amount of these efforts pertains to cancer research. The current use of powerful analytical instruments in phosphoproteomic approaches has paved the way for deeper and sensitive investigations. However, these methods and techniques need further improvements to deal with challenges posed by the complexity of samples and scarcity of phosphoproteins in the whole proteome, throughput and reproducibility. This review aims to provide a comprehensive summary of the variety of steps used in phosphoproteomic methods applied in cancer research including the enrichment and fractionation strategies. This will allow researchers to evaluate and choose a better combination of steps for their phosphoproteome studies.

The potential of cystatin C as a predictive biomarker in breast cancer

INTRODUCTION

Breast cancer (BCa) is the leading cause of cancer-related deaths among women. Numerous efforts are being directed toward identifying novel tissue and/or circulating molecular markers that may help clinicians in detecting early-stage BCa patients and in providing an accurate estimation of the prognosis and prediction of response to clinical treatments. In this setting, emerging evidence has indicated Cystatin C (Cyst C), as the most potent endogenous inhibitor of cysteine cathepsins, as a possible useful marker in the clinical management of BCa patients.

AREAS COVERED

This review analyzes the results of emerging studies underpinning a potential clinical role of Cyst C, as additional marker in BCa.

EXPERT OPINION

Cyst C expression levels have been reported to be altered in tumor tissues and/or in biological fluids of BCa patients. Furthermore, clinical evidence has highlighted a significant correlation between altered Cyst C levels in tumor tissues and/or biological fluids and some clinco-biological parameters of BCa progression. These findings provide evidence for a potential clinical use of Cyst C as a novel marker to improve the clinical and therapeutic management of BCa patients and as a gauge for better clarifying the role of cysteine proteinases in the various steps of BCa progression.

Up-Regulation of FSTL3, Regulated by lncRNA DSCAM-AS1/miR-122-5p Axis, Promotes Proliferation and Migration of Non-Small Cell Lung Cancer Cells

Background

Follistatin-like 3 (FSTL3) binds and inactivates activin, a growth factor with cell growth and differentiation. Previous studies reported that it is overexpressed in invasive breast cancers, and its expression and function in non-small cell lung cancer (NSCLC) remain unclear.

Materials and Methods

Immunohistochemistry was employed to probe the expression of FSTL3 in NSCLC tissues. Real-time PCR (RT-PCR) was applied to detect the expression of lncRNA DSCAM-AS1 and miR-122-5p. A549 cells and H1299 cells were used as cell models. The biological influence of FSTL3 on cells was studied using CCK-8 assay, wound healing assay and transwell assay in vitro, respectively. In vivo subcutaneous xenotransplanted tumor model and tail vein injection model in mice were also constructed to validate the roles of FSTL3. Interactions between miR-122-5p and FSTL3, DSCAM-AS1 and miR-122-5p were determined by bioinformatics analysis, RT-PCR, and dual-luciferase reporter assay.

Results

FSTL3 and DSCAM-AS1 were remarkably up-regulated in NSCLC samples, and miR-122-5p was down-regulated. FSTL3 was associated with worse prognosis of NSCLC patients. FSTL3 knockdown markedly inhibited the viability, migration and invasion of NSCLCs in vitro and in vivo. DSCAM-AS1 could down-regulate miR-122-5p via sponging it, and FSTL3 was a target gene of miR-122-5p.

Conclusion

Taken together, our study identified that FSTL3 was a new oncogene of NSCLC, which was regulated by DSCAM-AS1 and miR-122-5p. These findings suggested that FSTL3, DSCAM-AS1 and miR-122-5p might serve as a new valuable therapeutic target for NSCLC.

LC-MS/MS analysis of the dog serum phosphoproteome reveals novel and conserved phosphorylation sites: Phosphoprotein patterns in babesiosis caused by Babesia canis, a case study

Phosphorylation is the most commonly studied protein post-translational modification (PTM) in biological systems due to its importance in controlling cell division, survival, growth, etc. Despite the thorough research in phosphoproteomics of cells and tissues there is little information on circulating phosphoproteins. We compared serum from 10 healthy dogs and 10 dogs affected by B. canis-caused babesiosis with no organ dysfunctions by employing gel-free LC-MS/MS analysis of individual samples and tandem mass tag (TMT) label-based quantitative analyses of pools, both supported by phosphopeptide enrichment. Results showed a moderate number of phosphorylated proteins (50-55), with 89 phosphorylation sites not previously published for dogs although a number of them matched phosphorylation sites found in mammalian orthologs. Three phosphopeptides showed significant variation in babesiosis-affected dog sera compared to controls: Serum amyloid A (SAA) phosphorylated at serine 101 (up-regulation), kininogen 1 phosphorylated at threonine 326, and fibrinogen α phosphorylated at both threonine 20 and serine 22 (down-regulation). 71.9% of the detected phosphorylated sites were phosphoserine, 16.8% phosphothreonine and only 11.2% phosphotyrosine residues. TMT label-based quantitative analysis showed α-2-HS-glycoprotein / Fetuin A to be the most abundant phosphoprotein (50-70% of all phosphoproteins) followed by kininogen-1 (10-20%). The alterations of phosphorylated proteins observed in canine babesiosis caused by Babesia canis suggest new insights into the largely neglected role of extracellular protein phosphorylation in health and disease, encouraging urgent further research on this area. To the best of our knowledge the present study represents the first attempt to characterize canine serum phosphoproteome.

Phosphotyrosine profiling of human cerebrospinal fluid

Background

Cerebrospinal fluid (CSF) is an important source of potential biomarkers that affect the brain. Biomarkers for neurodegenerative disorders are needed to assist in diagnosis, monitoring disease progression and evaluating efficacy of therapies. Recent studies have demonstrated the involvement of tyrosine kinases in neuronal cell death. Thus, neurodegeneration in the brain is related to altered tyrosine phosphorylation of proteins in the brain and identification of abnormally phosphorylated tyrosine peptides in CSF has the potential to ascertain candidate biomarkers for neurodegenerative disorders.

Methods

In this study, we used an antibody-based tyrosine phosphopeptide enrichment method coupled with high resolution Orbitrap Fusion Tribrid Lumos Fourier transform mass spectrometer to catalog tyrosine phosphorylated peptides from cerebrospinal fluid. The subset of identified tyrosine phosphorylated peptides was also validated using parallel reaction monitoring (PRM)-based targeted approach.

Results

To date, there are no published studies on global profiling of phosphotyrosine modifications of CSF proteins. We carried out phosphotyrosine profiling of CSF using an anti-phosphotyrosine antibody-based enrichment and analysis using high resolution Orbitrap Fusion Lumos mass spectrometer. We identified 111 phosphotyrosine peptides mapping to 66 proteins, which included 24 proteins which have not been identified in CSF previously. We then validated a set of 5 tyrosine phosphorylated peptides in an independent set of CSF samples from cognitively normal subjects, using a PRM-based targeted approach.

Conclusions

The findings from this deep phosphotyrosine profiling of CSF samples have the potential to identify novel disease-related phosphotyrosine-containing peptides in CSF.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9205-1) contains supplementary material, which is available to authorized users.

The crucial role of multiomic approach in cancer research and clinically relevant outcomes

Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different "omics" technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.

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.

Identification of potential tissue-specific cancer biomarkers and development of cancer versus normal genomic classifiers

Machine learning techniques for cancer prediction and biomarker discovery can hasten cancer detection and significantly improve prognosis. Recent “OMICS” studies which include a variety of cancer and normal tissue samples along with machine learning approaches have the potential to further accelerate such discovery. To demonstrate this potential, 2,175 gene expression samples from nine tissue types were obtained to identify gene sets whose expression is characteristic of each cancer class. Using random forests classification and ten-fold cross-validation, we developed nine single-tissue classifiers, two multi-tissue cancer-versus-normal classifiers, and one multi-tissue normal classifier. Given a sample of a specified tissue type, the single-tissue models classified samples as cancer or normal with a testing accuracy between 85.29% and 100%. Given a sample of non-specific tissue type, the multi-tissue bi-class model classified the sample as cancer versus normal with a testing accuracy of 97.89%. Given a sample of non-specific tissue type, the multi-tissue multi-class model classified the sample as cancer versus normal and as a specific tissue type with a testing accuracy of 97.43%. Given a normal sample of any of the nine tissue types, the multi-tissue normal model classified the sample as a particular tissue type with a testing accuracy of 97.35%. The machine learning classifiers developed in this study identify potential cancer biomarkers with sensitivity and specificity that exceed those of existing biomarkers and pointed to pathways that are critical to tissue-specific tumor development. This study demonstrates the feasibility of predicting the tissue origin of carcinoma in the context of multiple cancer classes.

Proteomic profiling of the cancer cell secretome: informing clinical research

INTRODUCTION

Cancer represents one of the major causes of human deaths. Identification of proteins as biomarkers for early detection of cancer and therapeutic targets for cancer treatment are important issues in precision medicine. Secretome of cancer cells represents the collection of proteins secreted or shed from cancer cells. Proteomic profiling of the cancer cell secretome has been proven to be a convenient and efficient way to discover cancer biomarker and/or therapeutic targets. Areas covered: There have been numerous reviews describing the history and application of secretome analysis in cancer biomarker/therapeutic target research. The present review focuses on the technological advancement for profiling low-molecular-mass proteins in secretome, the latest information regarding the new candidate biomarkers and molecular mechanisms discovered on the basis of cancer cell secretome analysis, as well as the previously discovered candidate biomarkers that enter into clinical trials. Expert commentary: Current technologies for protein sample preparation/separation and MS-based protein identification have allowed in-depth analysis of cancer cell secretome. Future efforts should focus on the comprehensiveness of cancer cell secretome, meta-analysis of different secretome datasets and integrated analysis via combining other omics datasets, as well as the incorporation of MS-based biomarker verification pipeline into both preclinical studies and clinical trials.

Systematic network-based discovery of a Fam20C inhibitor (FL-1607) with apoptosis modulation in triple-negative breast cancer

Family with sequence similarity 20, member C (Fam20C) is a physiological Golgi casein kinase that phosphorylates multiple secreted proteins. Recently, it has been reported that Fam20C can be identified as a novel kinase target for therapeutic development. Thus, inhibition of Fam20C will be a potential therapeutic strategy to prevent tumor cell progression and metastasis. In our study, based upon the systems-biology network, molecular modeling and molecular dynamics (MD) simulations, we discovered a novel Fam20C inhibitor (FL-1607) with potent anti-proliferative effects on triple-negative breast cancer (TNBC) cells. Subsequently, we found that this Fam20C inhibitor could induce apoptosis and inhibit cell migration in MDA-MB-468 cells. Together, these findings would provide a new clue to the exploration of more novel Fam20C inhibitors for future TNBC therapy.

Extracellular Protein Phosphorylation, the Neglected Side of the Modification

The very existence of extracellular phosphorylation has been questioned for a long time, although casein phosphorylation was discovered a century ago. In addition, several modification sites localized on secreted proteins or on extracellular or lumenal domains of transmembrane proteins have been catalogued in large scale phosphorylation analyses, though in most such studies this aspect of cellular localization was not considered. Our review presents examples when additional analyses were performed on already public data sets that revealed a wealth of information about this "neglected side" of the modification. We also sum up accumulated knowledge about extracellular phosphorylation, including the discovery of Golgi-residing kinases and the special difficulties encountered in targeted analyses. We hope future phosphorylation studies will not ignore the existence of phosphorylation outside of the cell, and further discoveries will shed more light on its biological role.

Multivariate models from RNA-Seq SNVs yield candidate molecular targets for biomarker discovery: SNV-DA

BACKGROUND

It has recently been shown that significant and accurate single nucleotide variants (SNVs) can be reliably called from RNA-Seq data. These may provide another source of features for multivariate predictive modeling of disease phenotype for the prioritization of candidate biomarkers. The continuous nature of SNV allele fraction features allows the concurrent investigation of several genomic phenomena, including allele specific expression, clonal expansion and/or deletion, and copy number variation.

RESULTS

The proposed software pipeline and package, SNV Discriminant Analysis (SNV-DA), was applied on two RNA-Seq datasets with varying sample sizes sequenced at different depths: a dataset containing primary tumors from twenty patients with different disease outcomes in lung adenocarcinoma and a larger dataset of primary tumors representing two major breast cancer subtypes, estrogen receptor positive and triple negative. Predictive models were generated using the machine learning algorithm, sparse projections to latent structures discriminant analysis. Training sets composed of RNA-Seq SNV features limited to genomic regions of origin (e.g. exonic or intronic) and/or RNA-editing sites were shown to produce models with accurate predictive performances, were discriminant towards true label groupings, and were able to produce SNV rankings significantly different from than univariate tests. Furthermore, the utility of the proposed methodology is supported by its comparable performance to traditional models as well as the enrichment of selected SNVs located in genes previously associated with cancer and genes showing allele-specific expression. As proof of concept, we highlight the discovery of a previously unannotated intergenic locus that is associated with epigenetic regulatory marks in cancer and whose significant allele-specific expression is correlated with ER+ status; hereafter named ER+ associated hotspot (ERPAHS).

CONCLUSION

The use of models from RNA-Seq SNVs to identify and prioritize candidate molecular targets for biomarker discovery is supported by the ability of the proposed method to produce significantly accurate predictive models that are discriminant towards true label groupings. Importantly, the proposed methodology allows investigation of mutations outside of exonic regions and identification of interesting expressed loci not included in traditional gene annotations. An implementation of the proposed methodology is provided that allows the user to specify SNV filtering criteria and cross-validation design during model creation and evaluation.

Crucial considerations for pipelines to validate circulating biomarkers for breast cancer

Despite decades of progress in breast imaging, breast cancer remains the second most common cause of cancer mortality in women. The rapidly proliferative breast cancers that are associated with high relapse rates and mortality frequently present in younger women, in unscreened individuals, or in the intervals between screening mammography. Biomarkers exist for monitoring metastatic disease, such as CEA, CA27.29 and CA15-3, but there are no circulating biomarkers clinically available for early detection, prognosis, or monitoring for clinical relapse. There has been significant progress in the discovery of potential circulating biomarkers, including proteins, autoantibodies, nucleic acids, exosomes, and circulating tumor cells, but the vast majority of these biomarkers have not progressed beyond initial research discovery, and none have yet been approved for clinical use in early stage disease. Here, the authors review the crucial considerations of developing pipelines for the rapid evaluation of circulating biomarkers for breast cancer.

Site-specific O-Glycosylation Analysis of Human Blood Plasma Proteins

Site-specific glycosylation analysis is key to investigate structure-function relationships of glycoproteins, e.g. in the context of antigenicity and disease progression. The analysis, though, is quite challenging and time consuming, in particular for O-glycosylated proteins. In consequence, despite their clinical and biopharmaceutical importance, many human blood plasma glycoproteins have not been characterized comprehensively with respect to their O-glycosylation. Here, we report on the site-specific O-glycosylation analysis of human blood plasma glycoproteins. To this end pooled human blood plasma of healthy donors was proteolytically digested using a broad-specific enzyme (Proteinase K), followed by a precipitation step, as well as a glycopeptide enrichment and fractionation step via hydrophilic interaction liquid chromatography, the latter being optimized for intact O-glycopeptides carrying short mucin-type core-1 and -2 O-glycans, which represent the vast majority of O-glycans on human blood plasma proteins. Enriched O-glycopeptide fractions were subjected to mass spectrometric analysis using reversed-phase liquid chromatography coupled online to an ion trap mass spectrometer operated in positive-ion mode. Peptide identity and glycan composition were derived from low-energy collision-induced dissociation fragment spectra acquired in multistage mode. To pinpoint the O-glycosylation sites glycopeptides were fragmented using electron transfer dissociation. Spectra were annotated by database searches as well as manually. Overall, 31 O-glycosylation sites and regions belonging to 22 proteins were identified, the majority being acute-phase proteins. Strikingly, also 11 novel O-glycosylation sites and regions were identified. In total 23 O-glycosylation sites could be pinpointed. Interestingly, the use of Proteinase K proved to be particularly beneficial in this context. The identified O-glycan compositions most probably correspond to mono- and disialylated core-1 mucin-type O-glycans (T-antigen). The developed workflow allows the identification and characterization of the major population of the human blood plasma O-glycoproteome and our results provide new insights, which can help to unravel structure-function relationships. The data were deposited to ProteomeXchange PXD003270.

Casein kinases as potential therapeutic targets

INTRODUCTION

The conventional term 'casein kinase' (CK) denotes three classes of kinases - CK1, CK2 and Golgi-CK (G-CK)/Fam20C (family with sequence similarity 20, member C) - sharing the ability to phoshorylate casein in vitro, but otherwise unrelated to each other. All CKs have been reported to be implicated in human diseases, and reviews individually dealing with the druggability of CK1 and CK2 are available. Our aim is to provide a comparative analysis of the three classes of CKs as therapeutic targets.

AREAS COVERED

CK2 is the CK for which implication in neoplasia is best documented, with the survival of cancer cells often relying on its overexpression. An ample variety of cell-permeable CK2 inhibitors have been developed, with a couple of these now in clinical trials. Isoform-specific CK1 inhibitors that are expected to play a beneficial role in oncology and neurodegeneration have been also developed. In contrast, the pathogenic potential of G-CK/Fam20C is caused by its loss of function. Activators of Fam20C, notably sphingolipids and their analogs, may prove beneficial in this respect.

EXPERT OPINION

Optimization of CK2 and CK1 inhibitors will prove useful to develop new therapeutic strategies for treating cancer and neurodegenerative disorders, while the design of potent activators of G-CK/Fam20C will provide a new tool in the fields of bio-mineralization and hypophosphatemic diseases.

MicroRNA-485-5p suppresses cell proliferation and invasion in hepatocellular carcinoma by targeting stanniocalcin 2

Increasing evidences indicate that dys-regulation of MicroRNAs contributes to hepatocellular carcinoma. However, the roles of miR-485-5p in HCC are still largely unexplored. In the present study, our quantitative real-time PCR analysis found that miR-485-5p was significantly down-regulated in 50 pairs of human HCC tissues. Moreover, the reduced expression of miR-485-5p was significantly correlated with larger tumor size and more tumor number in patients with HCC. In vitro studies further showed that overexpression of miR-485-5p mimics could inhibit, while its antisense oligos promote cell proliferation and invasion. Results from the dual-luciferase reporter gene assays and western blot further showed that stanniocalcin 2 was a direct target of miR-485-5p. Therefore, our data suggest a novel role for miR-485-5p in the regulation of HCC progression.

A Single Kinase Generates the Majority of the Secreted Phosphoproteome

The existence of extracellular phosphoproteins has been acknowledged for over a century. However, research in this area has been undeveloped largely because the kinases that phosphorylate secreted proteins have escaped identification. Fam20C is a kinase that phosphorylates S-x-E/pS motifs on proteins in milk and in the extracellular matrix of bones and teeth. Here, we show that Fam20C generates the majority of the extracellular phosphoproteome. Using CRISPR/Cas9 genome editing, mass spectrometry, and biochemistry, we identify more than 100 secreted phosphoproteins as genuine Fam20C substrates. Further, we show that Fam20C exhibits broader substrate specificity than previously appreciated. Functional annotations of Fam20C substrates suggest roles for the kinase beyond biomineralization, including lipid homeostasis, wound healing, and cell migration and adhesion. Our results establish Fam20C as the major secretory pathway protein kinase and serve as a foundation for new areas of investigation into the role of secreted protein phosphorylation in human biology and disease.

Evaluating the effects of preanalytical variables on the stability of the human plasma proteome

High quality clinical biospecimens are vital for biomarker discovery, verification, and validation. Variations in blood processing and handling can affect protein abundances and assay reliability. Using an untargeted LC-MS approach, we systematically measured the impact of preanalytical variables on the plasma proteome. Time prior to processing was the only variable that affected the plasma protein levels. LC-MS quantification showed that preprocessing times <6h had minimal effects on the immunodepleted plasma proteome, but by 4 days significant changes were apparent. Elevated levels of many proteins were observed, suggesting that in addition to proteolytic degradation during the preanalytical phase, changes in protein structure are also important considerations for protocols using antibody depletion. As to processing variables, a comparison of single- vs double-spun plasma showed minimal differences. After processing, the impact ⩽3 freeze-thaw cycles was negligible regardless of whether freshly collected samples were processed in short succession or the cycles occurred during 14-17 years of frozen storage (-80 °C). Thus, clinical workflows that necessitate modest delays in blood processing times or employ different centrifugation steps can yield valuable samples for biomarker discovery and verification studies.

Identifying network biomarkers based on protein-protein interactions and expression data

Identifying effective biomarkers to battle complex diseases is an important but challenging task in biomedical research today. Molecular data of complex diseases is increasingly abundant due to the rapid advance of high throughput technologies. However, a great gap remains in identifying the massive molecular data to phenotypic changes, in particular, at a network level, i.e., a novel method for identifying network biomarkers is in pressing need to accurately classify and diagnose diseases from molecular data and shed light on the mechanisms of disease pathogenesis. Rather than seeking differential genes at an individual-molecule level, here we propose a novel method for identifying network biomarkers based on protein-protein interaction affinity (PPIA), which identify the differential interactions at a network level. Specifically, we firstly define PPIAs by estimating the concentrations of protein complexes based on the law of mass action upon gene expression data. Then we select a small and non-redundant group of protein-protein interactions and single proteins according to the PPIAs, that maximizes the discerning ability of cases from controls. This method is mathematically formulated as a linear programming, which can be efficiently solved and guarantees a globally optimal solution. Extensive results on experimental data in breast cancer demonstrate the effectiveness and efficiency of the proposed method for identifying network biomarkers, which not only can accurately distinguish the phenotypes but also provides significant biological insights at a network or pathway level. In addition, our method provides a new way to integrate static protein-protein interaction information with dynamical gene expression data.

Secreted pyruvate kinase M2 facilitates cell migration via PI3K/Akt and Wnt/β-catenin pathway in colon cancer cells

Pyruvate Kinase M2 (PKM2) is a key glycolytic enzyme, which highly expressed in tumor cells, and plays a pivotal role in the growth, survival and metabolism reprogramming of cancer cells. Besides the location of cytoplasm as a glycolytic enzyme and the location of nucleus as a protein kinase, extracellular PKM2 is present in serum and feces of tumor patients. However, little is known about the secretion of PKM2 and its significance in the progression of colon cancer. Here we demonstrated that PKM2 could be secreted from colon cancer cells, and purified PKM2 protein mimicing the secreted PKM2 was able to promote colon cancer cell migration. Moreover, PI3K/Akt and Wnt/β-catenin signaling were involved in secreted PKM2 induced colon cancer cell migration. The results reveal critical roles of secreted PKM2 in the progression of colon cancer, and indicate that PKM2 may be a therapeutic target for colon cancer.

Recent advances in proteomically subtyping pancreatic ductal adenocarcinomas and their potential clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a median overall survival of 6 months. Late diagnosis due to the absence of specific symptoms during disease development, in addition to extensive metastatic potential and resistance to chemotherapy and radiotherapy, are the most important reasons for short survival. Research efforts have therefore been focused on the development of early disease detection. However, the only US FDA-approved clinical biomarker, CA19-9, is considered inapplicable for screening and/or early detection of PDAC. The following editorial provides the reader with a short introduction to the topic of PDAC and gives focus to the current state of proteomic research in the field of PDAC biomarker discovery. This editorial also highlights the efforts made to subdivide this tumor entity and the potential clinical impact of patient stratification. Finally, the author provides opinions on the impact of proteomics to PDAC subtype stratification over the next 5 years.

Variation and quantification among a target set of phosphopeptides in human plasma by multiple reaction monitoring and SWATH-MS2 data-independent acquisition

Human plasma contains proteins that reflect overall health and represents a rich source of proteins for identifying and understanding disease pathophysiology. However, few studies have investigated changes in plasma phosphoproteins. In addition, little is known about the normal variations in these phosphoproteins, especially with respect to specific sites of modification. To address these questions, we evaluated variability in plasma protein phosphorylation in healthy individuals using multiple reaction monitoring (MRM) and SWATH-MS2 data-independent acquisition. First, we developed a discovery workflow for phosphopeptide enrichment from plasma and identified targets for MRM assays. Next, we analyzed plasma from healthy donors using an analytical workflow consisting of MRM and SWATH-MS2 that targeted phosphopeptides from 58 and 68 phosphoproteins, respectively. These two methods produced similar results showing low variability in 13 phosphosites from 10 phosphoproteins (CVinter < 30%) and high interpersonal variation of 16 phosphosites from 14 phosphoproteins (CVinter > 30%). Moreover, these phosphopeptides originate from phosphoproteins involved in cellular processes governing homeostasis, immune response, cell-extracellular matrix interactions, lipid and sugar metabolism, and cell signaling. This limited assessment of technical and biological variability in phosphopeptides generated from plasma phosphoproteins among healthy volunteers constitutes a reference for future studies that target protein phosphorylation as biomarkers.