Metabolomics-Based Discovery of Small Molecule Biomarkers in Serum Associated with Dengue Virus Infections and Disease Outcomes

Background

Epidemic dengue fever (DF) and dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS) are overwhelming public health capacity for diagnosis and clinical care of dengue patients throughout the tropical and subtropical world. The ability to predict severe dengue disease outcomes (DHF/DSS) using acute phase clinical specimens would be of enormous value to physicians and health care workers for appropriate triaging of patients for clinical management. Advances in the field of metabolomics and analytic software provide new opportunities to identify host small molecule biomarkers (SMBs) in acute phase clinical specimens that differentiate dengue disease outcomes.

Methodology/Principal Findings

Exploratory metabolomic studies were conducted to characterize the serum metabolome of patients who experienced different dengue disease outcomes. Serum samples from dengue patients from Nicaragua and Mexico were retrospectively obtained, and hydrophilic interaction liquid chromatography (HILIC)-mass spectrometry (MS) identified small molecule metabolites that were associated with and statistically differentiated DHF/DSS, DF, and non-dengue (ND) diagnosis groups. In the Nicaraguan samples, 191 metabolites differentiated DF from ND outcomes and 83 differentiated DHF/DSS and DF outcomes. In the Mexican samples, 306 metabolites differentiated DF from ND and 37 differentiated DHF/DSS and DF outcomes. The structural identities of 13 metabolites were confirmed using tandem mass spectrometry (MS/MS). Metabolomic analysis of serum samples from patients diagnosed as DF who progressed to DHF/DSS identified 65 metabolites that predicted dengue disease outcomes. Differential perturbation of the serum metabolome was demonstrated following infection with different DENV serotypes and following primary and secondary DENV infections.

Conclusions/Significance

These results provide proof-of-concept that a metabolomics approach can be used to identify metabolites or SMBs in serum specimens that are associated with distinct DENV infections and disease outcomes. The differentiating metabolites also provide insights into metabolic pathways and pathogenic and immunologic mechanisms associated with dengue disease severity.     

Discovery of Predictive Biomarkers for Litter Size in Boar Spermatozoa

Conventional semen analysis has been used for prognosis and diagnosis of male fertility. Although this tool is essential for providing initial quantitative information about semen, it remains a subject of debate. Therefore, development of new methods for the prognosis and diagnosis of male fertility should be seriously considered for animal species of economic importance as well as for humans. In the present study, we applied a comprehensive proteomic approach to identify global protein biomarkers in boar spermatozoa in order to increase the precision of male fertility prognoses and diagnoses. We determined that l-amino acid oxidase, mitochondrial malate dehydrogenase 2, NAD (MDH2), cytosolic 5′-nucleotidase 1B, lysozyme-like protein 4, and calmodulin (CALM) were significantly and abundantly expressed in high-litter size spermatozoa. We also found that equatorin, spermadhesin AWN, triosephosphate isomerase (TPI), Ras-related protein Rab-2A (RAB2A), spermadhesin AQN-3, and NADH dehydrogenase [ubiquinone] iron-sulfur protein 2 (NDUFS2) were significantly and abundantly expressed in low-litter size spermatozoa (>3-fold). Moreover, RAB2A, TPI, and NDUFS2 were negatively correlated with litter size, whereas CALM and MDH2 were positively correlated. This study provides novel biomarkers for the prediction of male fertility. To the best of our knowledge, this is the first work that shows significantly increased litter size using male fertility biomarkers in a field trial. Moreover, these protein markers may provide new developmental tools for the selection of superior sires as well as for the prognosis and diagnosis of male fertility.Prognosis and diagnosis of male fertility is a major concern in both animals and humans worldwide. In humans, about half of the fertility problems arise because of male factors. In addition, 50% of breeding system failures that are contributed by the sire lead to huge economic drawbacks in the animal industry (1 –5). Therefore, the development of new methods is needed to ensure more accurate prognosis and diagnosis of male fertility.Worldwide, artificial insemination (AI)¹ has been extensively performed in animal industries. Recent data revealed that more than 90% of the sows in Europe and the United States have been bred using AI during last three decades (6). The AI system sufficiently contributes to the achievement of high performance swine production through the selection of quality semen. Moreover, AI has been implemented extensively in swine industries for genetic up-grading (7, 8). However, the selection of high quality semen still depends on conventional sperm analyses such as the analysis of sperm morphology (9), motility (10), and sperm penetration assays (11, 12). Although these tests are commonly used to evaluate the male factor of fertility/infertility, the clinical value is still debated (13). Therefore, to evaluate the limits of conventional sperm analyses, the development of new methods to assess sperm function and fertility should be seriously considered for animal species of economic importance as well as for humans. Additionally, it is important to note that the optimization of sperm production will be possible when the methods to choose superior sires with greater efficiency become available. In this regard, the identification of global protein biomarkers using comprehensive proteomic tools represents a new method on the horizon that may facilitate the prediction of superior sires.Recently, several studies have reported that proteomics is an effective tool that has the potential to transform our understanding of spermatozoa (14 –16) by acquiring new biomarkers of male infertility and/or fertility. In addition, the development of mass spectrometry (MS) allows the potential identification of sperm proteins (17, 18). In fact, increased knowledge of the sperm proteome allows us to identify new molecular markers.In this study, we used high- and low-litter size boar spermatozoa to develop suitable biomarkers. First, sperm motility (%), motion characteristics, and capacitation status were evaluated by computer-assisted sperm analysis (CASA) and combined Hoechst 33258/chlortetracycline fluorescence assessment. Second, to find deferentially expressed proteins (>threefold) between high- and low-litter size boar spermatozoa, a 2-DE proteomic approach was applied following the identification of proteins by ESI-MS/MS and a MASCOT search. The 2-DE results were confirmed by a Western blot analysis that was performed with five commercially available antibodies. Third, to validate discovered markers for male fertility prediction, the expression levels of five proteins from 20 randomly selected boar spermatozoa with broad fertility ranges (i.e. litter size) were analyzed by enzyme-linked immunosorbent assay (ELISA), and the relationship between protein expression and male fertility was determined. Moreover, to represent the entire proteomic event, biological functions and interactions of the deferentially expressed proteins were schematized by a signaling pathway.     

Genome-Scale Discovery of DNA-Methylation Biomarkers for Blood-Based Detection of Colorectal Cancer

Background

There is an increasing demand for accurate biomarkers for early non-invasive colorectal cancer detection. We employed a genome-scale marker discovery method to identify and verify candidate DNA methylation biomarkers for blood-based detection of colorectal cancer.

Methodology/Principal Findings

We used DNA methylation data from 711 colorectal tumors, 53 matched adjacent-normal colonic tissue samples, 286 healthy blood samples and 4,201 tumor samples of 15 different cancer types. DNA methylation data were generated by the Illumina Infinium HumanMethylation27 and the HumanMethylation450 platforms, which determine the methylation status of 27,578 and 482,421 CpG sites respectively. We first performed a multistep marker selection to identify candidate markers with high methylation across all colorectal tumors while harboring low methylation in healthy samples and other cancer types. We then used pre-therapeutic plasma and serum samples from 107 colorectal cancer patients and 98 controls without colorectal cancer, confirmed by colonoscopy, to verify candidate markers. We selected two markers for further evaluation: methylated THBD (THBD-M) and methylated C9orf50 (C9orf50-M). When tested on clinical plasma and serum samples these markers outperformed carcinoembryonic antigen (CEA) serum measurement and resulted in a high sensitive and specific test performance for early colorectal cancer detection.

Conclusions/Significance

Our systematic marker discovery and verification study for blood-based DNA methylation markers resulted in two novel colorectal cancer biomarkers, THBD-M and C9orf50-M. THBD-M in particular showed promising performance in clinical samples, justifying its further optimization and clinical testing.     

Novel and Unique Diagnostic Biomarkers for Bacillus anthracis Infection

A search for bacterium-specific biomarkers in peripheral blood following infection with Bacillus anthracis was carried out with rabbits, using a battery of specific antibodies generated by DNA vaccination against 10 preselected highly immunogenic bacterial antigens which were identified previously by a genomic/proteomic/serologic screen of the B. anthracis secretome. Detection of infection biomarkers in the circulation of infected rabbits could be achieved only after removal of highly abundant serum proteins by chromatography using a random-ligand affinity column. Besides the toxin component protective antigen, the following three secreted proteins were detected in the circulation of infected animals: the chaperone and protease HtrA (BA3660), an NlpC/P60 endopeptidase (BA1952), and a protein of unknown function harboring two SH3 (Src homology 3) domains (BA0796). The three proteins could be detected in plasma samples from infected animals exhibiting 10³ to 10⁵ CFU/ml blood and also in standard blood cultures at 3 to 6 h post-bacterial inoculation at a bacteremic level as low as 10³ CFU/ml. Furthermore, the three biomarkers appear to be present only in the secretome of B. anthracis, not in those of the related pathogens B. thuringiensis and B. cereus. To the best of our knowledge, this is the first report of direct detection of B. anthracis-specific proteins, other than the toxin components, in the circulation of infected animals.The gram-positive spore-forming bacterium Bacillus anthracis is the causative agent of anthrax, a rare fatal disease which is initiated, in its most severe form, by inhalation of spores. Due to the severity of the disease, the ease of respiratory infection, and the extreme resistance of the spores to unfavorable environmental conditions, B. anthracis is considered a potential biological warfare agent (for a review, see references 8, 10, 35, 56, and 62), and in recent years, the need for novel reliable diagnostic approaches, improved vaccination strategies, novel therapeutic targets, and a better understanding of the pathogenesis of anthrax has been widely acknowledged.Inhaled B. anthracis spores are taken up by alveolar macrophages and germinate into vegetative bacilli which eventually invade the bloodstream, where they multiply massively and secrete toxins and virulence factors. Anthrax is toxinogenic in the sense that the bacterial binary exotoxin is necessary for the onset of the disease (54), yet other factors may be required for the colonization and expansion of bacteria in the host (15, 18, 31, 32, 37, 46, 65, 66, 70, 83). The toxin is composed of the following three proteins: protective antigen (PA), which mediates binding to the receptor on target cells and internalization of the toxin components (14, 74); lethal factor, a zinc protease targeting several mitogen-activated protein kinases (52); and edema factor (EF), a calmodulin-dependent adenylate cyclase (55, 57). The genes encoding the three exotoxin components are located on the native virulence plasmid pXO1. Genes encoding proteins with functions involved in the synthesis of the second major B. anthracis virulence determinant, an immunologically inert polyglutamyl capsule that protects bacteria from phagocytosis, are located on a second native virulence plasmid, pXO2 (56).In humans, the initial symptoms of inhalation anthrax are nonspecific and reminiscent of influenza-like upper respiratory tract infections. The second stage is characterized by high fever, respiratory failure, dyspnea, and shock. Unless patients are treated promptly, death occurs within 24 h of the onset of the second stage, preceded by massive bacteremia (27, 34, 73, 76). The mandatory treatment for anthrax is based on administration of antibiotics (17, 76), yet study of the disease in animal models has clearly established that the time of antibiotic administration postinfection is crucial for the effectiveness of the treatment, strongly supporting the importance of rapid diagnosis (2, 47, 48). At present, due to the severity of the disease and its rapid progression, treatment is administered to each person with confirmed contact with contaminated areas (76).Early accurate diagnosis of anthrax is complicated by the rarity of the disease and the nonspecific nature of the symptoms. Microbiologic identification of anthrax is based on the nonhemolytic nature of the typically white-gray colonies and the rod morphology of the gram-positive nonmotile bacilli detected in clinical samples or blood cultures (16, 19, 30, 73, 78). Immunofluorescence and immunohistochemistry targeted to bacterial proteins are not routinely conducted. Later in the course of the disease, seroconversion in response to the various components of the toxin may serve only as a retrospective confirmation of initial exposure. With the advent of genetic methodologies, B. anthracis in cultures inoculated with clinical and forensic samples can be detected specifically and accurately by PCR, usually designed to amplify genes located on the native virulence plasmids (30). Recently, the use of PA as a disease biomarker was suggested, owing to the presence of this protein in detectable amounts in the circulation of infected animals (53, 71). EF and lethal factor can be detected in the circulation only at later stages of infection (30).In recent years, the search for novel biomarkers of disease, including bacterial infections, has exploited the approach of global biological inspection based on functional genomic or proteomic studies (64, 85). We previously documented such global surveys, combined with a serological study of B. anthracis (5, 6, 20, 21, 22, 38, 39), for identification of vaccine and diagnostic marker candidates among extracellular (secreted or membranal) proteins. These studies indeed revealed a list of proteins that can serve as potential biomarkers, based on their immunogenicity (which probes their in vivo expression), abundance under various culture conditions, and functional relatedness to infection. In the present study, the search was extended by directly addressing the presence of bacterial secreted proteins in the circulation of B. anthracis-infected rabbits, using specific antibodies generated by DNA vaccination against the previously selected immunogenic proteins. Visualization of bacterial proteins in the circulation of infected animals was achieved only following depletion of highly abundant serum proteins by an affinity chromatography protocol. The search enabled the successful detection, in addition to PA, of three secreted proteins uniquely expressed by B. anthracis, i.e., HtrA (BA3660), the BA1952 endopeptidase, and a protein of unknown function (BA0796). All of these proteins are potential virulence-related factors. This is the first communication of the presence of B. anthracis secreted proteins other than the bacterial toxin in the circulation of infected animals, and their identification strongly supports the validity of the reductional screening approach for selection of disease biomarkers.     

Aptamer-Based Detection of Disease Biomarkers in Mouse Models for Chagas Drug Discovery

Drug discovery initiatives, aimed at Chagas treatment, have been hampered by the lack of standardized drug screening protocols and the absence of simple pre-clinical assays to evaluate treatment efficacy in animal models. In this study, we used a simple Enzyme Linked Aptamer (ELA) assay to detect T. cruzi biomarker in blood and validate murine drug discovery models of Chagas disease. In two mice models, Apt-29 ELA assay demonstrated that biomarker levels were significantly higher in the infected group compared to the control group, and upon Benznidazole treatment, their levels reduced. However, biomarker levels in the infected treated group did not reduce to those seen in the non-infected treated group, with 100% of the mice above the assay cutoff, suggesting that parasitemia was reduced but cure was not achieved. The ELA assay was capable of detecting circulating biomarkers in mice infected with various strains of T. cruzi parasites. Our results showed that the ELA assay could detect residual parasitemia in treated mice by providing an overall picture of the infection in the host. They suggest that the ELA assay can be used in drug discovery applications to assess treatment efficacy in-vivo.     

Plasma miRNAs as Diagnostic and Prognostic Biomarkers for Ovarian Cancer

Background

Most (70%) epithelial ovarian cancers (EOCs) are diagnosed late. Non-invasive biomarkers that facilitate disease detection and predict outcome are needed. The microRNAs (miRNAs) represent a new class of biomarkers. This study was to identify and validate plasma miRNAs as biomarkers in EOC.

Methodology/Principal Findings

We evaluated plasma samples of 360 EOC patients and 200 healthy controls from two institutions. All samples were grouped into screening, training and validation sets. We scanned the circulating plasma miRNAs by TaqMan low-density array in the screening set and identified/validated miRNA markers by real-time polymerase chain reaction assay in the training set. Receiver operating characteristic and logistic regression analyses established the diagnostic miRNA panel, which were confirmed in the validation sets. We found higher plasma miR-205 and lower let-7f expression in cases than in controls. MiR-205 and let-7f together provided high diagnostic accuracy for EOC, especially in patients with stage I disease. The combination of these two miRNAs and carbohydrate antigen-125 (CA-125) further improved the accuracy of detection. MiR-483-5p expression was elevated in stages III and IV compared with in stages I and II, which was consistent with its expression pattern in tumor tissues. Furthermore, lower levels of let-7f were predictive of poor prognosis in EOC patients.

Conclusions/Significance

Our findings indicate that plasma miR-205 and let-7f are biomarkers for ovarian cancer detection that complement CA-125; let-7f may be predictive of ovarian cancer prognosis.     

Cancer Proteomics and the Elusive Diagnostic Biomarkers

Despite progress in genomic and proteomic technology and applications, the validation of cancer biomarkers of use as clinical early detection diagnostics has remained elusive. As described in this brief viewpoint, there are now recognized to be many types of clinical biomarkers and proteomic analyses, particularly when combined with other ‘omic analyses, have been effective in many such biomarker identifications. However, in the area of early diagnosis of cancers, the problems associated with the conversion from identification to diagnostic have largely not been overcome. Notably, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI), has been particularly successful in refining the analytical steps needed to tackle this challenging issue and has provided positive insight into how to solve many of the underlying problems. The potential for developing clinical diagnostics for early detection of highly lethal cancers and possible new therapeutic strategies through proteomic analyses, as seen through these CPTAC successes, is more promising than ever.     

人肺鳞癌组织的血清蛋白质组学的比较分析

采用以肿瘤免疫学与蛋白质组学(proteomics)研究技术有机地结合为基础的血清蛋白质组学研究体系(serologicproteomeanalysis ,SERPA)筛选肺癌分子标志物.对10例人肺鳞癌组织,应用双向凝胶电泳(two dimensionalelectrophoresis ,2 DE)技术对同一肺鳞癌组织的细胞总蛋白同时进行电泳后获得3张相同的凝胶,其中一块2 DE凝胶经银染显色作为平行胶,其余两块2 DE凝胶经电转膜将凝胶中的蛋白质转至硝酸纤维素(NC)膜上,然后分别与肺癌患者的自身血清以及正常对照血清进行Western印迹分析,获取Western印迹反应图谱.经计算机图像分析识别差异反应的蛋白质,然后与平行胶比较找出相应的差异反应蛋白质点.获得了分辨率较高的人肺鳞癌组织与患者的自身血清以及正常对照血清的Western印迹反应图谱;图像分析共识别36±8个差异反应的蛋白质;在平行胶上找到了匹配的差异反应蛋白质点.对2 0个差异蛋白质点进行了肽质指纹图分析,鉴定出14个与细胞生长增殖、细胞代谢、细胞周期调控、信号转导等有关的肺鳞癌相关抗原.通过血清蛋白质组技术对肺鳞癌组织进行的研究,建立了分辨率较高的人肺鳞癌组织与患者的自身血清以及正常血清的Western印迹反应图谱,成功鉴定14个肺鳞癌相关抗原,为进一步筛选用于肺鳞癌诊断、治疗和预后评估     

Discovery and Validation of New Potential Biomarkers for Early Detection of Colon Cancer

Background

Accurate detection of characteristic proteins secreted by colon cancer tumor cells in biological fluids could serve as a biomarker for the disease. The aim of the present study was to identify and validate new serum biomarkers and demonstrate their potential usefulness for early diagnosis of colon cancer.

Methods

The study was organized in three sequential phases: 1) biomarker discovery, 2) technical and biological validation, and 3) proof of concept to test the potential clinical use of selected biomarkers. A prioritized subset of the differentially-expressed genes between tissue types (50 colon mucosa from cancer-free individuals and 100 normal-tumor pairs from colon cancer patients) was validated and further tested in a series of serum samples from 80 colon cancer cases, 23 patients with adenoma and 77 cancer-free controls.

Results

In the discovery phase, 505 unique candidate biomarkers were identified, with highly significant results and high capacity to discriminate between the different tissue types. After a subsequent prioritization, all tested genes (N = 23) were successfully validated in tissue, and one of them, COL10A1, showed relevant differences in serum protein levels between controls, patients with adenoma (p = 0.0083) and colon cancer cases (p = 3.2e-6).

Conclusion

We present a sequential process for the identification and further validation of biomarkers for early detection of colon cancer that identifies COL10A1 protein levels in serum as a potential diagnostic candidate to detect both adenoma lesions and tumor.

Impact

The use of a cheap serum test for colon cancer screening should improve its participation rates and contribute to decrease the burden of this disease.     

Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study

Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.     

Comparison of Diagnostic Accuracy of Biomarkers With Pooled Assessments

New biomarkers are frequently being developed in laboratory settings for the early diagnosis of diseases. However, the assay can be so expensive to assess in some cases that the evaluation of a large number of assays becomes unfeasible. Under this setting pooling biospecimens becomes an appealing alternative. In this paper, we present the methodology to allow for general pooling strategies and different data structures, which include balanced and unbalanced pooling cases. An estimate of the area under the ROC curve of a single biomarker with its asymptotic mean and variance is provided. Furthermore, we develop a test statistic for comparing the areas under the ROC curves of two biomarkers. The methods are illustrated with data from a study evaluating biomarkers for coronary heart disease.     

Quantitative Network Measures as Biomarkers for Classifying Prostate Cancer Disease States: A Systems Approach to Diagnostic Biomarkers

Identifying diagnostic biomarkers based on genomic features for an accurate disease classification is a problem of great importance for both, basic medical research and clinical practice. In this paper, we introduce quantitative network measures as structural biomarkers and investigate their ability for classifying disease states inferred from gene expression data from prostate cancer. We demonstrate the utility of our approach by using eigenvalue and entropy-based graph invariants and compare the results with a conventional biomarker analysis of the underlying gene expression data.     

Discovery of Novel Serum Biomarkers for Prenatal Down Syndrome Screening by Integrative Data Mining

Background

To facilitate the experimental search for novel maternal serum biomarkers in prenatal Down Syndrome screening, we aimed to create a set of candidate biomarkers using a data mining approach.

Methodology/Principal Findings

Because current screening markers are derived from either fetal liver or placental trophoblasts, we reasoned that new biomarkers can primarily be found to be derived from these two tissues. By applying a three-stage filtering strategy on publicly available data from different sources, we identified 49 potential blood-detectable protein biomarkers. Our set contains three biomarkers that are currently widely used in either first- or second-trimester screening (AFP, PAPP-A and fβ-hCG), as well as ten other proteins that are or have been examined as prenatal serum markers. This supports the effectiveness of our strategy and indicates the set contains other markers potentially applicable for screening.

Conclusions/Significance

We anticipate the set will help support further experimental studies for the identification of new Down Syndrome screening markers in maternal blood.     

Diagnostic Peptide Discovery: Prioritization of Pathogen Diagnostic Markers Using Multiple Features

The availability of complete pathogen genomes has renewed interest in the development of diagnostics for infectious diseases. Synthetic peptide microarrays provide a rapid, high-throughput platform for immunological testing of potential B-cell epitopes. However, their current capacity prevent the experimental screening of complete “peptidomes”. Therefore, computational approaches for prediction and/or prioritization of diagnostically relevant peptides are required. In this work we describe a computational method to assess a defined set of molecular properties for each potential diagnostic target in a reference genome. Properties such as sub-cellular localization or expression level were evaluated for the whole protein. At a higher resolution (short peptides), we assessed a set of local properties, such as repetitive motifs, disorder (structured vs natively unstructured regions), trans-membrane spans, genetic polymorphisms (conserved vs. divergent regions), predicted B-cell epitopes, and sequence similarity against human proteins and other potential cross-reacting species (e.g. other pathogens endemic in overlapping geographical locations). A scoring function based on these different features was developed, and used to rank all peptides from a large eukaryotic pathogen proteome. We applied this method to the identification of candidate diagnostic peptides in the protozoan Trypanosoma cruzi, the causative agent of Chagas disease. We measured the performance of the method by analyzing the enrichment of validated antigens in the high-scoring top of the ranking. Based on this measure, our integrative method outperformed alternative prioritizations based on individual properties (such as B-cell epitope predictors alone). Using this method we ranked 10 million 12-mer overlapping peptides derived from the complete T. cruzi proteome. Experimental screening of 190 high-scoring peptides allowed the identification of 37 novel epitopes with diagnostic potential, while none of the low scoring peptides showed significant reactivity. Many of the metrics employed are dependent on standard bioinformatic tools and data, so the method can be easily extended to other pathogen genomes.     

Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed.