Optimally Configured Optical Fiber Near-Field Enhanced Plasmonic Resonance Immunoprobe for the Detection of Alpha-Fetoprotein.

The detection of trace biomarkers is an important supplementary approach for early screening and diagnoses of tumors. An optical fiber near-field enhanced plasmonic resonance immunoprobe is developed for the detection of the hepatocellular carcinoma biomarker, i.e., the alpha-fetoprotein. Generic principles based on dispersion models and finite element analysis (FEA) models are developed to realize the optimized configuration of spectral characteristics of the immunoprobe. Dispersion models provide theoretical guidance for the design of the multilayer sensing structure from the perspective of the ray optics theory. FEA models provide theoretical guidance for the selection of coating materials from the perspective of the self-defined dielectric constant ratio, i.e., the ratio of the real part to the imaginary part. The optimized configuration of the antibody coupling further improves the biosensing performance of the immunoprobe. The limit of detection (LOD) can reach down to 0.01 ng mL-1 , which is one order of magnitude lower than those relevant reported works. Such a low LOD can more effectively avoid the accuracy degradation of detection results due to measurement errors. Human serum samples have also been detected, with the good precision achieved. This work shows promising prospects in applications of label-free, low-cost, rapid, and convenient early screening of tumors.

Ubiquitination-mediated molecular pathway alterations in human lung squamous cell carcinomas identified by quantitative ubiquitinomics.

Abnormal ubiquitination is extensively associated with cancers. To investigate human lung cancer ubiquitination and its potential functions, quantitative ubiquitinomics was carried out between human lung squamous cell carcinoma (LSCC) and control tissues, which characterized a total of 627 ubiquitin-modified proteins (UPs) and 1209 ubiquitinated lysine sites. Those UPs were mainly involved in cell adhesion, signal transduction, and regulations of ribosome complex and proteasome complex. Thirty three UPs whose genes were also found in TCGA database were significantly related to overall survival of LSCC. Six significant networks and 234 hub molecules were obtained from the protein-protein interaction (PPI) analysis of those 627 UPs. KEGG pathway analysis of those UPs revealed 47 statistically significant pathways, and most of which were tumor-associated pathways such as mTOR, HIF-1, PI3K-Akt, and Ras signaling pathways, and intracellular protein turnover-related pathways such as ribosome complex, ubiquitin-mediated proteolysis, ER protein processing, and proteasome complex pathways. Further, the relationship analysis of ubiquitination and differentially expressed proteins shows that ubiquitination regulates two aspects of protein turnover - synthesis and degradation. This study provided the first profile of UPs and molecular networks in LSCC tissue, which is the important resource to insight into new mechanisms, and to identify new biomarkers and therapeutic targets/drugs to treat LSCC.

Preparation of Mitochondria from Ovarian Cancer Tissues and Control Ovarian Tissues for Quantitative Proteomics Analysis.

Ovarian cancer is a common gynecologic cancer with high mortality but unclear molecular mechanism. Most ovarian cancers are diagnosed in the advanced stage, which seriously hampers therapy. Mitochondrial changes are a hallmark of human ovarian cancers, and mitochondria are the centers of energy metabolism, cell signaling, and oxidative stress. In-depth insights into the changes of the mitochondrial proteome in ovarian cancers compared to control ovarian tissue will benefit in-depth understanding of the molecular mechanisms of ovarian cancer, and the discovery of effective and reliable biomarkers and therapeutic targets. An effective mitochondrial preparation method coupled with an isobaric tag for relative and absolute quantification (iTRAQ) quantitative proteomics are presented here to analyze human ovarian cancer and control mitochondrial proteomes, including differential-speed centrifugation, density gradient centrifugation, quality assessment of mitochondrial samples, protein digestion with trypsin, iTRAQ labeling, strong cation exchange fractionation (SCX), liquid chromatography (LC), tandem mass spectrometry (MS/MS), database analysis, and quantitative analysis of mitochondrial proteins. Many proteins have been successfully identified to maximize the coverage of the human ovarian cancer mitochondrial proteome and to achieve the differentially expressed mitochondrial protein profile in human ovarian cancers.

Innovating the Concept and Practice of Two-Dimensional Gel Electrophoresis in the Analysis of Proteomes at the Proteoform Level.

Two-dimensional gel electrophoresis (2DE) is an important and well-established technical platform enabling extensive top-down proteomic analysis. However, the long-held but now largely outdated conventional concepts of 2DE have clearly impacted its application to in-depth investigations of proteomes at the level of protein species/proteoforms. It is time to popularize a new concept of 2DE for proteomics. With the development and enrichment of the proteome concept, any given "protein" is now recognized to consist of a series of proteoforms. Thus, it is the proteoform, rather than the canonical protein, that is the basic unit of a proteome, and each proteoform has a specific isoelectric point (pI) and relative mass (Mr ). Accordingly, using 2DE, each proteoform can routinely be resolved and arrayed according to its different pI and Mr . Each detectable spot contains multiple proteoforms derived from the same gene, as well as from different genes. Proteoforms derived from the same gene are distributed into different spots in a 2DE pattern. High-resolution 2DE is thus actually an initial level of separation to address proteome complexity and is effectively a pre-fractionation method prior to analysis using mass spectrometry (MS). Furthermore, stable isotope-labeled 2DE coupled with high-sensitivity liquid chromatography-tandem MS (LC-MS/MS) has tremendous potential for the large-scale detection, identification, and quantification of the proteoforms that constitute proteomes.

Quantitative Analysis of Ubiquitinated Proteins in Human Pituitary and Pituitary Adenoma Tissues.

Protein ubiquitination is an important post-translational modification that is associated with multiple diseases, including pituitary adenomas (PAs). Protein ubiquitination profiling in human pituitary and PAs remains unknown. Here, we performed the first ubiquitination analysis with an anti-ubiquitin antibody (specific to K-ε-GG)-based label-free quantitative proteomics method and bioinformatics to investigate protein ubiquitination profiling between PA and control tissues. A total of 158 ubiquitinated sites and 142 ubiquitinated peptides in 108 proteins were identified, and five ubiquitination motifs were found. KEGG pathway network analysis of 108 ubiquitinated proteins identified four statistically significant signaling pathways, including PI3K-AKT signaling pathway, hippo signaling pathway, ribosome, and nucleotide excision repair. R software Gene Ontology (GO) analysis of 108 ubiquitinated proteins revealed that protein ubiquitination was involved in multiple biological processes, cellular components, and molecule functions. The randomly selected ubiquitinated 14-3-3 zeta/delta protein was further analyzed with Western blot, and it was found that upregulated 14-3-3 zeta/delta protein in nonfunctional PAs might be derived from the significantly decreased level of its ubiquitination compared to control pituitaries, which indicated a contribution of 14-3-3 zeta/delta protein to pituitary tumorigenesis. These findings provided the first ubiquitinated proteomic profiling and ubiquitination-involved signaling pathway networks in human PAs. This study offers new scientific evidence and basic data to elucidate the biological functions of ubiquitination in PAs, insights into its novel molecular mechanisms of pituitary tumorigenesis, and discovery of novel biomarkers and therapeutic targets for effective treatment of PAs.

Multiomics-Based Signaling Pathway Network Alterations in Human Non-functional Pituitary Adenomas.

Non-functional pituitary adenoma (NFPA) seriously affects hypothanamus-pituitary-target organ axis system, with a series of molecule alterations in the multiple levels of genome, transcriptome, proteome, and post-translational modifications, and those molecules mutually interact in a molecular-network system. Meta analysis coupled with IPA pathway-network program was used to comprehensively analyze nine sets of documented NFPA omics data, including NFPA quantitative transcriptomics data [280 differentially expressed genes (DEGs)], NFPA quantitative proteomics data [50 differentially expressed proteins (DEPs)], NFPA mapping protein data (218 proteins), NFPA mapping protein nitration data (9 nitroproteins and 3 non-nitrated proteins), invasive NFPA quantitative transriptomics data (346 DEGs), invasive NFPA quantitative proteomics data (57 DEPs), control mapping protein data (1469 proteins), control mapping protein nitration data (8 nitroproteins), and control mapping phosphorylation data (28 phosphoproteins). A total of 62 molecular-networks with 861 hub-molecules and 519 canonical-pathways including 54 cancer-related canonical pathways were revealed. A total of 42 hub-molecule panels and 9 canonical-pathway panels were identified to significantly associate with tumorigenesis. Four important molecular-network systems, including PI3K/AKT, mTOR, Wnt, and ERK/MAPK pathway-systems, were confirmed in NFPAs by PTMScan experiments with altered expression-patterns and phosphorylations. Nineteen high-frequency hub-molecules were also validated in NFPAs with PTMScan experiment with at least 2.5-fold changes in expression or phosphorylation, including ERK, ERK1/2, Jnk, MAPK, Mek, p38 MAPK, AKT, PI3K complex, p85, PKC, FAK, Rac, Shc, HSP90, NFκB Complex, histone H3, AP1, calmodulin, and PLC. Furthermore, mTOR and Wnt pathway-systems were confirmed in NFPAs by immunoaffinity Western blot analysis, with significantly decreased expression of PRAS40 and increased phosphorylation levels of p-PRAS40 (Thr246) in mTOR pathway in NFPAs compared to controls, and with the decreased protein expressions of GSK-3ß and GSK-3ß, significantly increased phosphorylation levels of p-GSK3α (Ser21) and p-GSK3ß (Ser9), and increased expression level of ß-catenin in Wnt pathway in NFPAs compared to controls. Those findings provided a comphrensive and large-scale pathway network data for NFPAs, and offer the scientific evidence for insights into the accurate molecular mechanisms of NFPA and discovery of the effective biomarkers for diagnosis, prognosis, and determination of therapeutic targets.

Quantitative Analysis of Proteome in Non-functional Pituitary Adenomas: Clinical Relevance and Potential Benefits for the Patients.

Background: Non-functional pituitary adenoma (NFPA) is a common tumor that occurs in the pituitary gland, and generally without any symptoms at its early stage and without clinical elevation of hormones, which is commonly diagnosed when it grows up to compress its surrounding tissues and organs. Currently, the pathogenesis of NFPA has not been clarified yet. It is necessary to investigate molecular alterations in NFPA, and identify reliable biomarkers and drug therapeutic targets for effective treatments. Methods: Tandem mass tags (TMT)-based quantitative proteomics was used to identify and quantify proteins in NFPAs. GO and KEGG enrichment analyses were used to analyze the identified proteins. Differentially expressed genes (DEGs) between NFPA and control tissues were obtained from GEO datasets. These two sets of protein and gene data were analyzed to obtain overlapped molecules (genes; proteins), followed by further GO and KEGG pathway analyses of these overlapped molecules, and molecular network analysis to obtain the hub molecules with Cytoscape. Two hub molecules (SRC and AKT1) were verified with Western blotting. Results: Totally 6076 proteins in NFPA tissues were identified, and 3598 DEGs between NFPA and control tissues were identified from GEO database. Overlapping analysis of 6076 proteins and 3598 DEGs obtained 1088 overlapped molecules (DEGs; proteins). KEGG pathway analysis of 6076 proteins obtained 114 statistically significant pathways, including endocytosis, and spliceosome signaling pathways. KEGG pathway analysis of 1088 overlapped molecules obtained 52 statistically significant pathways, including focal adhesion, cGMP-PKG pathway, and platelet activation signaling pathways. These pathways play important roles in cell energy supply, adhesion, and maintenance of the tumor microenvironment. According to the association degree in Cytoscape, ten hub molecules (DEGs; proteins) were identified, including GAPDH, ALB, ACACA, SRC, ENO2, CALM1, POTEE, HSPA8, DECR1, and AKT1. Western-blotting analysis confirmed the upregulated expressions of SRC and PTMScan experiment confirmed the increased levels of pAKT1, in NFPAs compared to controls. Conclusions: This study established the large-scale quantitative protein profiling of NFPA tissue proteome. It offers a basis for subsequent in-depth proteomics analysis of NFPAs, and insight into the molecular mechanism of NFPAs. It also provided the basic data to discover reliable biomarkers and therapeutic targets for NFPA patients.

The lncRNA SNHG3 regulates energy metabolism of ovarian cancer by an analysis of mitochondrial proteomes.

BACKGROUND: Malignant tumors are heterogeneous diseases characterized by different metabolic phenotypes. These were revealed by Warburg effect and reverse Warburg effect phenotypes. However, the molecular mechanism remains largely unknown. METHODS: Isobaric tag for relative and absolute quantification (iTRAQ) proteomics was used to identify mitochondrial differentially expressed proteins (DEPs) of ovarian cancers relative to controls, followed by bioinformatic analysis. The molecular profiling of long non-coding RNAs (lncRNAs) was also investigated by searching the dataset of the Cancer Genome Atlas (TCGA) consisting of 419 ovarian cancer patients. RESULTS: A total of 1198 mitochondrial DEPs were identified by iTRAQ quantitative proteomics. Bioinformatic analysis of those DEPs showed that cancer cells exhibited an increased dependence on Kreb's cycle and oxidative phosphorylation, with some related upregulated proteins. Moreover, TCGA analysis showed lncRNA SNHG3 was not only related to ovarian cancer survival, but also energy metabolism. Interestingly, integrated analysis of the results of GSEA analysis and Starbase 2.0 found that SNHG3 was related to energy metabolism by regulating miRNAs and EIF4AIII, and those molecules had target sites with PKM, PDHB, IDH2, and UQCRH in the glycolysis, Kreb's cycle, and oxidative phosphorylation (OXPHOS) pathways. Furthermore, SNHG3 might be associated with drug resistance. CONCLUSION: The results derived from TCGA data and mitochondrial DEPs data are consistent with the Warburg and reverse Warburg effects that cancer cells mainly rely on glycolysis and oxidative phosphorylation to produce energy. Also, this integrated lncRNA-miRNA-mRNA and lncRNA-binding protein-mRNA signatures might have important merit for insights into molecular mechanisms and clinical implications in ovarian cancer.

Identification of the proteomic variations of invasive relative to non-invasive non-functional pituitary adenomas.

The incomplete surgery section of invasive non-functional pituitary adenomas (NFPAs) carries the increased risks of complications and requires adjuvant radiotherapy and medications. It is necessary to clarify the molecular mechanisms and markers of invasiveness to guide the management of NFPA patients. The study aimed to proteomic variations of invasive and non-invasive NFPAs and sought the protein markers for invasive NFPAs. Invasive (n = 4) and non-invasive (n = 4) NFPA tissues were analyzed (n = 3-5/each tissue) with 2DE and PDQuest software. Twenty-four high-resolution 2DE gels were quantitatively compared to determine differentially expressed proteins (DEPs) between invasive and non-invasive NFPAs. Approximately 1200 protein spots were detected in each 2DE map, and 103 differential spots (64 upregulated and 39 downregulated) were identified. Among those 103 differential spots, 57 DEPs (30 upregulated and 27 downregulated) were characterized with peptide mass fingerprint and MS/MS. Gene-ontology (GO) and ingenuity pathway analyses of those DEPs revealed pathway networks including mitochondrial dysfunction, oxidative stress, mitogen-activated protein kinase signaling abnormality, TR/RXR activation, proteolysis abnormality, ketogenesis and ketolysis, cyclin-dependent kinase C signaling abnormality, and amyloid processing that were significantly associated with invasive characteristics of invasive NFPA. Those data demonstrate that proteomic variations exist between invasive and non-invasive NFPAs. 2DE-based comparative proteomics is an effective approach to identify proteomic variations and pathway network variations. Those findings will serve as a basis to understand the molecular mechanisms of invasive NFPAs and to discover protein markers to effectively manage patients with invasive NFPAs.