Novel tumor marker discovery of gastrointestinal cancers using various proteomic approaches

Cancer has been the disease with the highest cause of death for a decade. This is partly due to the lack of ideal tumor markers for early diagnosis, which causes cancer found at the advanced stage where no curative treatment is available. Therefore, development of tumor markers with higher sensitivity and specificity is waiting to emerge. The ideal source for the tumor markers are serum, plasma or urine samples that are routinely used as clinical laboratory test. They contain a number of proteins that could be useful for cancer diagnosis. Recent advances in proteomic technology made it possible to identify the low abundant proteins in the clinical samples and thus extensive efforts are now attempted to search for the tumor markers across the country. There are two prominent types of proteomic approaches, 2D gel-based (2DE) and MS/MS based approach. 2DE is favorable to analyze relatively high moleculer weight proteins (MW > 20kD) and MS is superior to detect low molecular proteins or peptides. In this article, we introduce our recent studies on tumor marker discovery using various proteomic approaches and will discuss future application for cancer     

泛素及其类似物的蛋白质组学研究进展

作为蛋白质的翻译后修饰,泛素及其类似物(ubiquitin-like modifiers,Ubls)对底物的修饰被认为是真核细胞内一种重要的调节机制。根据以往的研究表明,泛素/ubls与各种各样的底物蛋白形成共价结合以后,通过介导蛋白质降解、改变蛋白质的细胞定位、改变蛋白质的酶活性、改变蛋白质之间的相互作用等影响这些底物的功能与活性。可以想象,通过影响成百上千的不同底物蛋白,泛素和Ubls在各个细胞生理活动中都发挥着重要的调节作用。运用蛋白质组学的方法对泛素/Ubls进行研究,可以发现更多新的泛素和ubls的底物,帮助人们从整体水平上了解泛素/Ubls这个复杂的修饰系统。而利用质谱技术精确的鉴定泛素/Ubls在底物上的修饰位点则为进一步研究修饰发生的分子机制,以及对底物蛋白功能的影响提供了明确的线索和方向。到目前为止,已有越来越多的科学家们对泛素/Ubls修饰的蛋白质组学感兴趣并致力于这方面的研究,取得了很大进展。本文对泛素及Ubls的蛋白质组学研究进展进行了归纳和总结。     

Genomics-based approaches to gene discovery in innate immunity

Summary: The completion of draft sequences of the human and mouse genomes offers many opportunities for gene discovery in the field of immunology through the application of the methods of computational genomics. One arm of the innate immune system includes the antimicrobial peptides that protect multicellular organisms from a diverse spectrum of microorganisms. The β‐defensins comprise an important family of mammalian antimicrobial peptides. To better define the β‐defensin gene family, we developed an approach to search genomic databases for conserved motifs present in the β‐defensin family using HMMER, a computational search tool based on hidden Markov models (HMMs), in combination with the basic local alignment search tool. The approach was first used to identify candidate second‐exon coding regions, and later applied to finding associated first exons. This strategy discovered 28 new human and 43 new mouse β‐defensin genes in five syntenic chromosomal regions. Within each syntenic cluster, the gene sequences and organization were similar, suggesting that each cluster pair arose from a common ancestor and was retained because of conserved functions. These findings demonstrate an important proof‐of‐principle for a genome‐wide search strategy to identify genes with conserved structural motifs. Such an approach may be readily adopted to address other questions of relevance to immunology.     

Comprehensive phenotyping and biological marker discovery

There is an enormous unmet need for biological markers to characterize disease type, status, progression, and response to therapy. We are developing and applying an integrated bioanalytical platform and clinical research program to facilitate comprehensive differential phenotyping of patient samples and enable the discovery of biomarkers. The platform employs high-throughput, quantitative analysis for the characterization of thousands of parameters including cell populations, cell-surface antigen density, soluble proteins and soluble low molecular weight biomolecules, from small-volume biological samples in a clinical research laboratory-like setting.     

Molecular pathological approaches to human tumor immunology

Research on human tumor immunology has greatly advanced in the past two decades. Many immunogenic tumor antigens have been identified, and some of these antigens entered in clinical trials. Consequently, it has been shown that these antigens can inhibit tumor growth in patients to some extent, indicating that they act as potent immunogenic therapeutic vaccines in cancer patients with malignancies originating from various tissues. These patients had antigen‐specific cytotoxic T‐lymphocyte (CTL) responses when assessed on tetramer, enzyme‐linked immunospot (ELISPOT), T‐cell clonotype and CTL induction efficiency. Thus, it has become clear that human tumor vaccines can evoke clinical and immunological anti‐tumor responses in patients. The tumor regression effects of tumor vaccines, however, are generally low, and it is obvious that current vaccination protocols are generally too weak to provide substantial and satisfactory clinical benefits. This means that other drastic and more potent clinical and immunological protocols are required in cancer immunotherapy. To find such efficient protocols the basic immunological and biological properties of cancers must be investigated. In the present review the identification of human tumor antigens recognized on CTL and the clinical trials are introduced. Next, the most recent analysis of human cancer‐initiating cell (cancer stem cell)‐associated antigens is described. These antigens might be able to act as ‘universal, general and fundamental’ tumor antigens. Also present is the authors' recent study for increasing cross‐presentation efficiency in dendritic cells and subsequent enhancement of human leukocyte antigen (HLA)‐class I‐restricted peptide antigenicity by using HSP90 and ORP150 molecular chaperones that act as endogenous Toll‐like receptor ligands. In addition to the aforementioned manipulation of the positive loop of tumor immunity, it is necessary to regulate and intervene in the negative loop. In particular, the potential of the expression of HLA class I molecule regulation by epigenetic mechanisms will be discussed. Finally, the type of basic and clinical tumor immunology research highly required currently, and in the very near future, are described.     

Model-based approaches to biomarker discovery and evaluation: a multidisciplinary integrated review

The most common use of any mathematical or statistical model in physiology, pathophysiology, or therapy evaluation is to organize all relevant components characterizing the system behavior into a rigorously testable framework. This approach is widely applied both to the study of complex homeostatic paradigms involving endogenous substances and to the evaluation of the kinetics and dynamics of xenobiotics such as toxicants and drugs. In either case, one seeks a quantitative framework of the system that is consistent with known physiology and pharmacology and is "compatible" (in some meaningful sense) with all available data. The models are then evaluated and subjected to identifiability and validity tests and can then be used to estimate unknown parameters of interest, to make predictions about system behavior, to simulate previously unobserved behavior in response to a putative perturbation, and to aid in further experimental design. In a broader context, however, the focus and ultimate goal of this set of methodologies (whether this is explicitly stated or not) lies in understanding the mechanisms of physiology and pathophysiology and measuring the effect of therapeutic interventions through the accurate quantification of biomarkers of interest. In this review, we attempt to bring together under this comprehensive framework more than four decades of investigation on modeling and simulation in the life sciences (in particular, we will concentrate on the areas of pharmacology, physiology, and bioengineering). We demonstrate that such modeling approaches, when appropriately designed and evaluated, have significant potential and can be used to understand the multiple factors of disease progression and response to therapeutic interventions, the most likely causes of variability in population and individual responses to therapy, and the most appropriate timing of treatment administration. Lastly, they may allow estimation and prediction of significant outcomes in feasibility and clinical studies.     

Forward genetics in mammalian cells: functional approaches to gene discovery.

Definitive proof of function in biological systems requires genetic analysis. Only when the loss of a particular protein corresponds to the loss of a specific function can one be sure that the protein truly affects the function. Changing the pattern of gene expression through random mutagenesis or by introducing expression libraries, followed by selection of mutant or variant cells and identification of a missing or overexpressed protein, has the power to reveal or confirm the roles of specific components of signaling pathways and to provide mutant cell lines and cDNA reagents to be used in defining detailed mechanisms through structure-function analyses. These examples of forward genetics contrast with reverse genetic approaches, where the function of a known gene product is explored by knockout or replacement. Here we review a broad range of techniques that have been used to alter gene expression randomly in mammalian cells, with examples of specific discoveries that have resulted from these applications of forward genetics.     

Using statistical and knowledge-based approaches for literature-based discovery

The explosive growth in biomedical literature has made it difficult for researchers to keep up with advancements, even in their own narrow specializations. While researchers formulate new hypotheses to test, it is very important for them to identify connections to their work from other parts of the literature. However, the current volume of information has become a great barrier for this task and new automated tools are needed to help researchers identify new knowledge that bridges gaps across distinct sections of the literature. In this paper, we present a literature-based discovery system called LitLinker that incorporates knowledge-based methodologies with a statistical method to mine the biomedical literature for new, potentially causal connections between biomedical terms. We demonstrate LitLinker’s ability to capture novel and interesting connections between diseases and chemicals, drugs, genes, or molecular sequences from the published biomedical literature. We also evaluate LitLinker’s performance by using the information retrieval metrics of precision and recall.     

Need for sustainable approaches in antileishmanial drug discovery

Leishmaniasis is a neglected parasitic disease for which the current antileishmania therapeutics are hampered by drug toxicity, high cost, need for parenteral administration, increasing treatment failure rates, and emergence of drug resistance. The R&D pipeline had run fairly dry for several years, but fortunately some new drug candidates are now under (pre)clinical development. Identification of novel drugs will nevertheless remain essential to adequately sustain and improve effective disease control in the future. In this review, a package of standard and accessible R&D approaches is discussed with expansion to some alternative strategies focusing on parasite–host and vector–host interactions.

     

Molecular epidemiologic approaches to urinary tract infection gene discovery in uropathogenic Escherichia coli

Urinary tract infection (UTI) is one of the most frequently acquired bacterial infections. The vast majority of UTIs are caused by a large, genetically heterogeneous group of Escherichia coli. This genetic diversity has hampered identification of UTI-related genes. A three-step experimental strategy was used to identify genes potentially involved in E. coli UTI transmission or virulence: epidemiologic pairing of a UTI-specific strain with a fecal control, differential cloning to isolated UTI strain-specific DNA, and epidemiologic screening to identify sequences among isolated DNAs that are associated with UTI. The 37 DNA sequences initially isolated were physically located all over the tester strain genome. Only two hybridized to the total DNA of the sequenced E. coli K-12 strain; eight sequences were present significantly more frequently in UTI isolates than in fecal isolates. Three of the eight sequences matched to genes for multidrug efflux proteins, usher proteins, and pathogenicity island insertion sites, respectively. Using population characteristics to direct gene discovery and evaluation is a productive strategy applicable to any system.     

Proteomic strategies and challenges in tumor metastasis research

The rapidly evolving field of proteomics offers new approaches to understanding the pathogenesis of cancer and metastatic disease. Although numerous tumor markers have been identified with different genomic methods in the past, most are either not specific or sensitive enough to be used in routine clinical setting. The rationale for proteomic profiling is based on the fact that proteins represent the dynamic state of the cells, reflecting pathophysiological changes in the disease more accurately than genomic and epigenetic alterations. Emerging proteomic techniques allow simultaneous assessment of a large number of proteins at one time. The study of protein profiles in complex systems, such as plasma, serum or tissues of cancer patients is likely to become valuable for monitoring the response of patients during treatment or for detecting recurrence of the disease.     

Proteomics approaches to identify tumor antigen directed autoantibodies as cancer biomarkers

The identification of autoantibodies to tumor cell proteins by proteomics approaches has great potential impact on cancer biomarker discovery. The humoral immune response represents a form of biological amplification of signals that are otherwise weak due to very low concentrations of antigen, especially in the early stages of cancers. In addition, proteomics can detect immunoreactivity directed against protein post-translational modifications. Two-dimensional gel based Western blots, protein antigen microarrays, and multiplex ELISA reactions have been applied by our group to antigen based biomarker detection and validation. The latter two are based on liquid-phase separations that are suitable for automation. This work has resulted in the identification of numerous cancer biomarker candidates. Large clinical studies are currently planned to establish their value in early cancer diagnosis.     

肿瘤分子标记物检测的进展

在肿瘤的发生过程中，血清中某些肿瘤标志物的升高与肿瘤密切相关。因此，检测肿瘤标记物在对肿瘤的筛选、诊断和判断预后中扮演着重要的角色。肿瘤标志物的研究进行了许多年，并且有大量的文献报道，但是真正能够用于临床的肿瘤标志物的数量还相当有限。目前已经确定与肿瘤相关的肿瘤标志物有癌胚抗原（CEA）、糖抗原（CA19-9）、癌抗原（CA125）、甲胎蛋白（AFP）、前列腺特异抗原（PSA）、CA15-3、人绒毛膜促性腺激素（hCG）等，