根据蛋白质互作网络预测前列腺癌相关蛋白质的细致功能

对于功能部分已知的前列腺癌相关蛋白质,提出了一种基于Gent Ontology的功能特异的子网构建方法来细化其功能注释。结果显示该方法能够以很高的精确率为前列腺癌相关蛋白质预测更为精细的功能。预测的相关蛋白质的功能对于指导实验研究前列腺癌的分子机制具有重要的价值。     

根据蛋白质互作网络预测乳腺癌相关蛋白质的细致功能

乳腺癌是最为常见的恶性肿瘤之一。已有的关于乳腺癌相关蛋白质的功能注释比较宽泛, 制约了乳腺癌的后续研究工作。对于已知部分功能的乳腺癌相关蛋白质, 提出了一种结合Gene Ontology功能先验知识和蛋白质互作的方法, 通过构建功能特异的局部相互作用网络来预测乳腺癌相关蛋白质的细致功能。结果显示该方法能够以很高的精确率为乳腺癌相关蛋白质预测更为精细的功能。预测的相关蛋白质的功能对于指导实验研究乳腺癌的分子机制具有重要的价值。     

基于贝叶斯网络和相互作用可信度的蛋白质功能预测方法

蛋白质功能注释是后基因组时代研究的核心内容之一,基于蛋白质相互作用网络的蛋白质功能预测方法越来越受到研究者们的关注.提出了一种基于贝叶斯网络和蛋白质相互作用可信度的蛋白质功能预测方法.该方法在功能预测过程中为待注释的蛋白质建立贝叶斯网络预测模型,并充分考虑了蛋白质相互作用的可信度问题.在构建的芽殖酵母数据集上的三重交叉验证测试表明,在功能预测过程中考虑蛋白质可信度能够有效地提高功能预测的性能.与现有一些算法相比,该方法能够给出令人满意的预测效果.     

基于相互作用的蛋白质功能预测

蛋白质功能预测是后基因时代研究的热点问题。基于相互作用的蛋白质功能预测方法目前应用比较广泛,但是当"伙伴蛋白质"(interacting partners)数目k较小时,其预测准确率不高。从蛋白质相互作用网络入手,结合"小世界网络"特性,有效解决了k较小时预测准确率不高的问题。对酵母(Saccharomyces cerevisiae)蛋白质的相互作用网络进行预测,当k≤4时其预测准确率比相同条件下的GO(global optimization)方法有一定提高。实验结果表明:该方法能够有效的应用于伙伴蛋白质数目较小时的蛋白质功能预测。     

计算方法在蛋白质相互作用研究中的应用

计算方法在蛋白质相互作用研究的各个阶段扮演了一个重要的角色。对此,作者将从以下几个方面对计算方法在蛋白质相互作用及相互作用网络研究中的应用做一个概述：蛋白质相互作用数据库及其发展;数据挖掘方法在蛋白质相互作用数据收集和整合中的应用;高通量方法实验结果的验证;根据蛋白质相互作用网络预测和推断未知蛋白质的功能;蛋白质相互作用的预测。     

结合蛋白质互作与基因表达谱信息大范围预测蛋白质的精细功能

GESTs(gene expression similarity and taxonomy similarity)是结合基因表达相似性和基因功能分类体系Gene Ontology (GO)中的功能概念相似性测度进行功能预测的新方法. 将此预测算法推广应用于蛋白质互相作用数据, 并提出了几种在蛋白质互作网络中为功能待测蛋白质筛选邻居的方法. 与已有的其它蛋白质功能预测方法不同, 新方法在学习过程中自动地从功能分类体系中的各个功能类中选择最合适的尽可能具体细致的功能类, 利用注释于其相近功能类中的互作邻居蛋白质支持对此具体功能类的预测. 使用MIPS提供的酵母蛋白质互作信息与一套基因表达谱数据, 利用特别针对GO体系结构层次特点设计的3种测度, 评价对GO知识体系中的生物过程分支进行蛋白质功能预测的效果. 结果显示, 利用文中的方法, 可以大范围预测蛋白质的精细功能. 此外, 还利用此方法对2004年底Gene Ontology上未知功能的蛋白质进行预测, 其中部分预测结果在2006年4月发布的SGD注释数据中已经得到了证实.     

蛋白质相互作用研究进展

蛋白质行使功能时,需要与其他蛋白质或者其他分子相互作用才能完成.在蛋白质相互作用水平上研究蛋白质对理解蛋白质功能、疾病与进化具有重要的意义.就蛋白质相互作用的预测、常用的蛋白质相互作用数据库以及蛋白质相互作用网络的研究进行了介绍.     

蛋白质表面氨基酸特性研究进展

分布在蛋白质分子表面的暴露于溶剂的氨基酸所具有的一些特性对蛋白质的折叠和聚合过程、蛋白质一蛋白质相互作用以及蛋白质的功能具有重要影响。本文分析了蛋白质表面氨基酸在疏水性、保守性、静电势及结构方面的一些特性,阐述了近年来国际上利用这些特性对蛋白质一蛋白质相互作用界面进行预测的方法,最后介绍了几款预测蛋白质表面氨基酸的软件。     

蛋白质表面氨基酸特性研究进展

分布在蛋白质分子表面的暴露于溶剂的氨基酸所具有的一些特性对蛋白质的折叠和聚合过程、蛋白质-蛋白质相互作用以及蛋白质的功能具有重要影响。本文分析了蛋白质表面氨基酸在疏水性、保守性、静电势及结构方面的一些特性,阐述了近年来国际上利用这些特性对蛋白质-蛋白质相互作用界面进行预测的方法,最后介绍了几款预测蛋白质表面氨基酸的软件。     

真核蛋白质的亚细胞位点预测研究进展

研究真核蛋白质的亚细胞位点是了解真核蛋白质功能,深入研究蛋白质相关信号通路内在机制的基础。同时,可以为了解 疾病发病机制及为新药研发提供帮助。因此,研究真核蛋白质的亚细胞位点意义十分重大。随着基因组测序的完成,真核蛋白质 序列信息增长迅速,为真核蛋白质亚细胞位点的研究提出了更多的挑战。传统的实验法难以满足蛋白质信息量迅速增长的需求。 而采用生物信息学手段处理大规模数据的计算预测方法,可在较短时间内获得大量真核蛋白质亚细胞位点信息,弥补了实验法 的不足。因此,运用计算预测法预测真核蛋白质的亚细胞位点成为生物信息学领域的研究热点之一。本文主要从提取真核蛋白质 的特征信息、计算预测方法及预测效果的评价三个方面,介绍近年来真核蛋白质亚细胞位点预测的研究进展。     

Search for the tumor-associated proteins of oral squamous cell carcinoma collected in Taiwan using proteomics strategy

Squamous cell carcinoma (SCC) accounts for more than 90% of malignant tumors of the oral cavity. In Taiwan, oral squamous cell carcinoma (OSCC) is among the most frequent malignancies, largely due to betal quid chewing. Despite the recent improvement in treatment results, the long-term outcome of OSCC generally remains poor, especially for those with advanced diseases. It is therefore desirable to identify potential biomarkers that may aid in risk stratification and perhaps the development of therapeutic targets. In this study, we exploited two-dimensional gel electrophoresis (2-DE) coupled with mass spectrometry to compare the proteome maps of 10 OSCC specimens with their adjacent nontumorous epithelia to identify differentially expressed proteins. Comparative proteomics indicated that 17 proteins were differentially expressed in OSCC with 11 up-regulated and 6 down-regulated proteins. These deregulated proteins participated in cytoskeletal functions, cell signaling, antiapoptosis, angiogenesis, lipid metabolism, drug metabolism, and protein translation/turnover. They were all associated with tumor development in various cancers. Among the dys-regulated proteins, the immunoexpression of three proteins including nicotinamide N-methyltransferase, apolipoprotein AI, and 14-3-3 zeta were evaluated in 38 OSCCs of testing cohort to confirm the proteomics data. Subsequently, the expression of 14-3-3 zeta, as the most relevant to OSCC progression determined by testing cohort, was further assessed in 80 OSCCs of independent validation cohort to identify the clinical relevance of its expression. By this comprehensive study, we identified 14-3-3 zeta as the only prognosticator of local recurrence-free survival (LRFS) and also an independently predicted factor of disease-specific survival (DSS).     

Identification of PRDX4 and P4HA2 as metastasis-associated proteins in oral cavity squamous cell carcinoma by comparative tissue proteomics of microdissected specimens using iTRAQ technology

Cervical lymph node metastasis represents the major prognosticator for oral cavity squamous cell carcinoma (OSCC). Here, we used an iTRAQ-based quantitative proteomic approach to identify proteins that are differentially expressed between microdissected primary and metastatic OSCC tumors. The selected candidates were examined in tissue sections via immunohistochemistry, and their roles in OSCC cell function investigated using RNA interference. Seventy-four differentially expressed proteins in nodal metastases, including PRDX4 and P4HA2, were identified. Immunohistochemical analysis revealed significantly higher levels of PRDX4 and P4HA2 in tumor cells than adjacent non-tumor epithelia (P < 0.0001 and P < 0.0001, respectively), and even higher expression in the 31 metastatic tumors of lymph nodes, compared to the corresponding primary tumors (P = 0.060 and P = 0.002, respectively). Overexpression of PRDX4 and P4HA2 was significantly associated with positive pN status (P = 0.048 and P = 0.021, respectively). PRDX4 overexpression was a significant prognostic factor for disease-specific survival in both univariate and multivariate analyses (P = 0.034 and P = 0.032, respectively). Additionally, cell migration and invasiveness were attenuated in OEC-M1 cells upon in vitro knockdown of PRDX4 and P4HA2 with specific interfering RNA. Novel metastasis-related prognostic markers for OSCC could be identified by our approach.     

Identification of novel prognostic indicators for oral squamous cell carcinoma based on proteomics and metabolomics

BackgroundThe low 5-year survival rate of oral squamous cell carcinoma (OSCC) suggests that new prognostic indicators need to be identified to aid the clinical management of patients.MethodsSaliva samples from OSCC patients and healthy controls were collected for proteomic and metabolomic sequencing. Gene expressed profiling was downloaded from TCGA and GEO databases. After the differential analysis, proteins with a significant impact on the prognosis of OSCC patients were screened. Correlation analysis was performed with metabolites and core proteins were identified. Cox regression analysis was utilized to stratify OSCC samples based on core proteins. The prognostic predictive ability of the core protein was then evaluated. Differences in infiltration of immune cells between the different strata were identified.ResultsThere were 678 differentially expressed proteins (DEPs), 94 intersected DEPs among them by intersecting with differentially expressed genes in TCGA and GSE30784 dataset. Seven core proteins were identified that significantly affected OSCC patient survival and strongly correlated with differential metabolites (R² > 0.8). The samples were divided into high- and low-risk groups according to median risk score. The risk score and core proteins were well prognostic factor in OSCC patients. Genes in high-risk group were enriched in Notch signaling pathway, epithelial mesenchymal transition (EMT), and angiogenesis. Core proteins were strongly associated with the immune status of OSCC patients.ConclusionsThe results established a 7-protein signatures with the hope of early detection and the capacity for risk assessment of OSCC patient prognosis. Further providing more potential targets for the treatment of OSCC.     

Suppression of OSCC malignancy by oral glands derived-PIP identified by iTRAQ combined with 2D LC-MS/MS

Oral squamous cell carcinoma (OSCC) is the most common malignancy in head and neck cancer and a global cause of cancer-related death. Due to the poor survival rates associated with OSCC, there is a growing need to develop novel technologies and predictive biomarkers to improve disease diagnosis. The identification of new cellular targets in OSCC tumors will benefit such developments. In this study, isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics analysis combined with 2-dimensional liquid chromatography and tandem mass spectrometry (2D LC-MS/MS) were used to identify differentially expressed proteins (DEPs) between tumor and normal tissues. Of the DEPs detected, the most significantly downregulated protein in OSCC tissue was prolactin-inducible protein (PIP). Clonogenic and 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) experiments showed that the proliferation capacity of OSCC cells overexpressing PIP decreased due to cell cycle arrest at the G0/G1 checkpoint. Wound-healing and transwell assay further showed that PIP overexpression also reduced the migration and invasion of OSCC cells. Immunohistochemistry (IHC) was used to analyze the expression in OSCC, indicating that PIP may be secreted by glandular cells and have an inhibitory effect on OSCC cells to produce. In western blot analysis, silencing studies confirmed that PIP mediates these effects through the AKT/mitogen-activated protein kinase (MAPK) signaling axis in OSCC cells. Taken together, this study reveals PIP as a key mediator of OSCC cell growth, migration, and invasion through its effect on AKT/MAPK signaling.     

Identification of cancer hallmark‐associated gene and lncRNA cooperative regulation pairs and dictate lncRNA roles in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Numerous cancers share ten common traits (“hallmarks”) that govern the transformation of normal cells into cancer cells. Long non‐coding RNAs (lncRNAs) are important factors that contribute to tumorigenesis. However, very little is known about the cooperative relationships between lncRNAs and cancer hallmark‐associated genes in OSCC. Through integrative analysis of cancer hallmarks, somatic mutations, copy number variants (CNVs) and expression, some OSCC‐specific cancer hallmark‐associated genes and lncRNAs are identified. A computational framework to identify gene and lncRNA cooperative regulation pairs (GLCRPs) associated with different cancer hallmarks is developed based on the co‐expression and co‐occurrence of mutations. The distinct and common features of ten cancer hallmarks based on GLCRPs are characterized in OSCC. Cancer hallmark insensitivity to antigrowth signals and self‐sufficiency in growth signals are shared by most GLCRPs in OSCC. Some key GLCRPs participate in many cancer hallmarks in OSCC. Cancer hallmark‐associated GLCRP networks have complex patterns and specific functions in OSCC. Specially, some key GLCRPs are associated with the prognosis of OSCC patients. In summary, we generate a comprehensive landscape of cancer hallmark‐associated GLCRPs that can act as a starting point for future functional explorations, the identification of biomarkers and lncRNA‐based targeted therapy in OSCC.     

Secretome-based identification of Mac-2 binding protein as a potential oral cancer marker involved in cell growth and motility

Oral squamous cell carcinoma (OSCC) is the 11th most common cancer worldwide, and is associated with a high death rate. At present, there are no suitable markers for detecting and/or monitoring OSCC in body fluids/tissues. Here, we used 1D SDS-PAGE and MALDI-TOF MS to systematically analyze the secretomes of two OSCC cell lines (OEC-M1 and SCC4). The putative OSCC-related proteins identified in this analysis included the Mac-2 binding protein (Mac-2 BP), which was further found to be overexpressed in OSCC specimens and significantly elevated in the sera of OSCC patients compared to healthy controls. Finally, RNA interference-based knock-down of Mac-2 BP expression in OSCC cells revealed for the first time that Mac-2 BP is involved in regulating growth and motility of OSCC cells.     

Identification of Host-Immune Response Protein Candidates in the Sera of Human Oral Squamous Cell Carcinoma Patients

One of the most common cancers worldwide is oral squamous cell carcinoma (OSCC), which is associated with a significant death rate and has been linked to several risk factors. Notably, failure to detect these neoplasms at an early stage represents a fundamental barrier to improving the survival and quality of life of OSCC patients. In the present study, serum samples from OSCC patients (n = 25) and healthy controls (n = 25) were subjected to two-dimensional gel electrophoresis (2-DE) and silver staining in order to identify biomarkers that might allow early diagnosis. In this regard, 2-DE spots corresponding to various up- and down-regulated proteins were sequenced via high-resolution MALDI-TOF mass spectrometry and analyzed using the MASCOT database. We identified the following differentially expressed host-specific proteins within sera from OSCC patients: leucine-rich α2-glycoprotein (LRG), alpha-1-B-glycoprotein (ABG), clusterin (CLU), PRO2044, haptoglobin (HAP), complement C3c (C3), proapolipoprotein A1 (proapo-A1), and retinol-binding protein 4 precursor (RBP4). Moreover, five non-host factors were detected, including bacterial antigens from Acinetobacter lwoffii, Burkholderia multivorans, Myxococcus xanthus, Laribacter hongkongensis, and Streptococcus salivarius. Subsequently, we analyzed the immunogenicity of these proteins using pooled sera from OSCC patients. In this regard, five of these candidate biomarkers were found to be immunoreactive: CLU, HAP, C3, proapo-A1 and RBP4. Taken together, our immunoproteomics approach has identified various serum biomarkers that could facilitate the development of early diagnostic tools for OSCC.     

Saliva proteome profiling reveals potential salivary biomarkers for detection of oral cavity squamous cell carcinoma

Oral cavity squamous cell carcinoma (OSCC), which is frequently associated with poor prognosis and mortality, is a leading cause of cancer‐related death worldwide. Discovery of body fluid accessible biomarkers is needed to improve OSCC screening. To this end, we profiled proteomes of saliva from the healthy volunteers, the individuals with oral potentially malignant disorders (OPMD), and the OSCC patients by means of SDS‐PAGE coupled with LC‐MS/MS. In the control, the OPMD, and the OSCC groups, 958, 845, and 1030 salivary proteins were detected, respectively. With spectral counting‐based label‐free quantification, 22 overexpressed salivary proteins were identified in the OSCC group compared with the healthy controls and the OPMD individuals. Among them, resistin (RETN) was subjected to further validation with an independent cohort using ELISA. The data confirmed that the salivary RETN levels in the OSCC patients were significantly higher than that in the healthy or in the OPMD group. Moreover, the elevated levels of salivary RETN were highly correlated with late‐stage primary tumors, advanced overall stage, and lymph‐node metastasis. Our results not only reveal that profiling of saliva proteome is feasible for discovery of OSCC biomarkers, but also identify RETN as a potential salivary biomarker for OSCC detection.