Distant metastasis is a major cause of treatment failure in nasopharyngeal carcinoma (NPC) patients. Cell surface proteins represent attractive targets for cancer diagnosis or therapy. However, the cell surface proteins associated with NPC metastasis are poorly understood. To identify potential therapeutic targets for NPC metastasis, we isolated cell surface proteins from two isogenic NPC cell lines, 6-10B (low metastatic) and 5-8F (highly metastatic), through cell surface biotinylation. Stable isotope labeling by amino acids in cell culture (SILAC) based proteomics was applied to comprehensively characterize the cell surface proteins related with the metastatic phenotype. We identified 294 differentially expressed cell surface proteins, including the most upregulated protein myoferlin (MYOF), two receptor tyrosine kinases(RTKs) epidermal growth factor receptor (EGFR) and ephrin type-A receptor 2 (EPHA2) and several integrin family molecules. These differentially expressed proteins are enriched in multiple biological pathways such as the FAK-PI3K-mTOR pathway, focal adhesions, and integrin-mediated cell adhesion. The knockdown of MYOF effectively suppresses the proliferation, migration and invasion of NPC cells. Immunohistochemistry analysis also showed that MYOF is associated with NPC metastasis. We experimentally confirmed, for the first time, that MYOF can interact with EGFR and EPHA2. Moreover, MYOF knockdown could influence not only EGFR activity and its downstream epithelial–mesenchymal transition (EMT), but also EPHA2 ligand-independent activity. These findings suggest that MYOF might be an attractive potential therapeutic target that has double effects of simultaneously influencing EGFR and EPHA2 signaling pathway. In conclusion, this is the first study to profile the cell surface proteins associated with NPC metastasis and provide valuable resource for future researches.
The emergence of omics technologies over the last decade has helped in advancement of research and our understanding of complex diseases like brain cancers. However, barring genomics, no other omics technology has been able to find utility in clinical settings. The recent advancements in mass spectrometry instrumentation have resulted in proteomics technologies becoming more sensitive and reliable. Targeted proteomics, a relatively new branch of mass spectrometry-based proteomics has shown immense potential in addressing the shortcomings of the standard molecular biology-based techniques like Western blotting and Immunohistochemistry. In this study we demonstrate the utility of Multiple reaction monitoring (MRM), a targeted proteomics approach, in quantifying peptides from proteins like Apolipoprotein A1 (APOA1), Apolipoprotein E (APOE), Prostaglandin H2 D-Isomerase (PTGDS), Vitronectin (VTN) and Complement C3 (C3) in cerebrospinal fluid (CSF) collected from Glioma and Meningioma patients. Additionally, we also report transitions for peptides from proteins – Vimentin (VIM), Cystatin-C (CST3) and Clusterin (CLU) in surgically resected Meningioma tissues; Annexin A1 (ANXA1), Superoxide dismutase (SOD2) and VIM in surgically resected Glioma tissues; and Microtubule associated protein-2 (MAP-2), Splicing factor 3B subunit 2 (SF3B2) and VIM in surgically resected Medulloblastoma tissues. To our knowledge, this is the first study reporting the use of MRM to validate proteins from three types of brain malignancies and two different bio-specimens. Future studies involving a large cohort of samples aimed at accurately detecting and quantifying peptides of proteins with roles in brain malignancies could potentially result in a panel of proteins showing ability to classify and grade tumors. Successful application of these techniques could ultimately offer alternative strategies with increased accuracy, sensitivity and lower turnaround time making them translatable to the clinics.
The mammary gland is a unique apocrine gland made up of a branching network of ducts that end in alveoli. It is an ideal system to study the molecular mechanisms associated with cell proliferation, differentiation, and oncogenesis. MFG-E8, also known as Lactadherin, is a vital glycoprotein related to the milk fat globule membrane and initially identified to get secreted in bovine milk. Our previous report suggests that a high level of MFG-E8 is indicative of high milk yield in dairy animals. Here, we showed that MFG-E8 controls the cell growth and morphology of epithelial cells through a network of regulatory transcription factors. To understand the comprehensive action, we downregulated its expression in MECs by MFG-E8 specific shRNA. We generated a knockdown proteome profile of differentially expressed proteins through a quantitative iTRAQ experiment on a high-resolution mass spectrometer (Q-TOF). The downregulation of MFG-E8 resulted in reduced phagocytosis and cell migration ability, whereas it also leads to more lifespan to knockdown vis-a-vis healthy cells, which is confirmed through BrdU, MTT, and Caspase 3/7. The bioinformatics analysis revealed that MFG-E8 knockdown perturbs a large number of intracellular signaling, eventually leading to cessation in cell growth. Based on the directed network analysis, we found that MFG-E8 is activated by CX3CL1, TP63, and CSF2 and leads to the activation of SOCS3 and CCL2 for the regulation of cell proliferation. We further proved that the depletion of MFG-E8 resulted in activated cytoskeletal remodeling by MFG-E8 knockdown, which results in the activation of three independent pathways ZP4/JAK-STAT5, DOCK1/STAT3, and PIP3/AKT/mTOR. Overall, this study suggests that MFG-E8 expression in mammary epithelial cells is an indication of intracellular deterioration in cell health. To date, to the best of our knowledge, this is the first study that explores the downstream targets of MFG-E8 involved in the regulation of mammary epithelial cell health.
Cancer is one of the largest contributors to the burden of chronic disease in the world and is the second leading cause of death globally. It is associated with episodes of low-oxygen stress (hypoxia or ischemia/reperfusion) that promotes cancer progression and therapeutic resistance. Efforts have been made in the past using traditional proteomic approaches to decipher oxygen deprivation stress-related mechanisms of the disease initiation and progression and to identify key proteins as a therapeutic target for the treatment and prevention. Despite the potential benefits of proteomic in translational research for the discovery of new drugs, the therapeutic outcome with this approach has not met expectations in clinical trials. This is mainly due to the disease complexity which possess a multifaceted molecular pathology. Therefore, novel strategies to identify and characterize clinically important sets of modulators and molecular events for multi-target drug discovery are needed. Here, we review important past and current studies on proteomics in cancer with an emphasis on recent pioneered labeling approaches in mass spectrometry (MS)-based systematic quantitative analysis to improve clinical success. We also discuss the results of the selected innovative publications that integrate advanced proteomic technologies (e.g. MALDI-MSI, pSILAC/SILAC/iTRAQ/TMT-LC-MS/MS, MRM-MS) for comprehensive analysis of proteome dynamics in different biosystems, including cell type, cell species, and subcellular proteome (i.e. secretome and chromatome). Finally, we discuss the future direction and challenges in the application of these technological advancements in mass spectrometry within the context of cancer and hypoxia.
In view of the unsatisfactory treatment outcome of liver cancer under current treatment, where the mortality rate is high and the survival rate is poor, in this study we aimed to use RNA sequencing data to explore potential molecular markers that can be more effective in predicting diagnosis and prognosis of hepatocellular carcinoma. RNA sequencing data and corresponding clinical information were obtained from multiple databases. After matching with the apoptotic genes from the Deathbase database, 14 differentially expressed human apoptosis genes were obtained. Using univariate and multivariate Cox regression analyses, two apoptosis genes (BAK1 and CSE1L) were determined to be closely associated with overall survival (OS) in HCC patients. And subsequently experiments also validated that knockdown of BAK1 and CSE1L significantly inhibited cell proliferation and promoted apoptosis in the HCC. Then the two genes were used to construct a prognostic signature and diagnostic models. The high-risk group showed lower OS time compared to low-risk group in the TCGA cohort (P < 0.001, HR = 2.11), GSE14520 cohort (P = 0.003, HR = 1.85), and ICGC cohort (P < 0.001, HR = 4). And the advanced HCC patients showed higher risk score and worse prognosis compared to early-stage HCC patients. Moreover, the prognostic signature was validated to be an independent prognostic factor. The diagnostic models accurately predicted HCC from normal tissues and dysplastic nodules in the training and validation cohort. These results indicated that the two apoptosis-related signature effectively predicted diagnosis and prognosis of HCC and may serve as a potential biomarker and therapeutic target for HCC.
Multiple myeloma (MM) is a plasma cell-associated cancer and exists as the second most common hematological malignancy worldwide. Although researchers have been working on MM, a comprehensive quantitative Bone Marrow Interstitial Fluid (BMIF) and serum proteomic analysis from the same patients’ samples is not yet reported. The present study involves the investigation of alterations in the BMIF and serum proteome of MM patients compared to controls using multipronged quantitative proteomic approaches viz., 2D-DIGE, iTRAQ, and SWATH-MS. A total of 279 non-redundant statistically significant differentially abundant proteins were identified by the combination of three proteomic approaches in MM BMIF, while in the case of serum 116 such differentially abundant proteins were identified. The biological context of these dysregulated proteins was deciphered using various bioinformatic tools. Verification experiments were performed in a fresh independent cohort of samples using immunoblotting and mass spectrometry based SRM assays. Thorough data evaluation led to the identification of a panel of five proteins viz., haptoglobin, kininogen 1, transferrin, and apolipoprotein A1 along with albumin that was validated using ELISA in a larger cohort of serum samples. This panel of proteins could serve as a useful tool in the diagnosis and understanding of the pathophysiology of MM in the future.
Exosomes are directly involved in governing physiological and pathological processes of an organism by horizontal transfer of functional molecules (proteins, microRNA, etc.) from producing to receiving cells. We explored the relationship of proteins from plasma exosomes, and exosomes from the total blood of healthy females (HFs) and breast cancer patients (BCPs), with crucial steps of tumor progression: EMT, cell proliferation, invasion, cell migration, stimulation of angiogenesis, and immune response. A proteomic analysis of exosomes isolated from samples using ultrafiltration and ultracentrifugation was performed. Their nature has been verified using cryo-electron microscopy and flow cytometry. Bioinformatics analysis showed that 84% of common exosomal proteins were of cytoplasmic and vesicle origin. They perform functions of protein binding and signaling receptor binding, and facilitated the processes of the regulated exocytosis and vesicle-mediated transport. Half of the identified exosomal proteins from blood of HFs and BCPs are involved in crucial steps of the tumor progression: EMT, cell proliferation, invasion, cell migration stimulation of angiogenesis, and immune response. Moreover, we found that protein cargo of exosomes from HF total blood was enriched with proteins inhibiting EMT, cell migration, and invasion. Tumor diagnostic/prognostic protein markers accounted for 47% of the total composition of cell-surface-associated exosomes (calculated as the difference between the total blood exosomes and plasma exosomes) from BCP blood. Breast cancer-associated proteins were equally represented in the blood cell-surface-associated exosomes and in the plasma exosomes from BCPs. However, hyper-expressed proteins predominate in the blood cell-surface-associated exosomes as compared to the plasma exosomes (64 vs. 14%). Using breast cancer proteins data from the Human Protein Atlas (HPA) (www.proteinatlas.org/), three favorable (SERPINA1, KRT6B, and SOCS3), and one unfavorable (IGF2R) prognostic protein markers were found in the BCP total blood exosomes. Identified exosomal proteins from BCP blood can be recommended for further testing as breast cancer diagnostic/prognostic biomarkers or novel therapeutic targets.