Development Of Biomarkers For Diagnosis Research Articles

Exploring the Potential Role of Oligodendrocyte-Associated PIP4K2A in Alzheimer's Disease Complicated with Type 2 Diabetes Mellitus via Multi-Omic Analysis.

Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are two common diseases that affect the elderly population worldwide. The identification of common genes associated with AD and T2DM holds promise for potential biomarkers and intriguing pathogenesis of these two complicated diseases. This study utilized a comprehensive approach by integrating transcriptome data from multiple cohorts, encompassing both AD and T2DM. The analysis incorporated various data types, including blood and tissue samples as well as single-cell datasets, allowing for a detailed assessment of gene expression patterns. From the brain region-specific single-cell analysis, PIP4K2A, which encodes phosphatidylinositol-5-phosphate 4-kinase type 2 alpha, was found to be expressed mainly in oligodendrocytes compared to other cell types. Elevated levels of PIP4K2A in AD and T2DM patients' blood were found to be associated with key cellular processes such as vesicle-mediated transport, negative regulation of autophagosome assembly, and cytosolic transport. The identification of PIP4K2A's potential roles in the cellular processes of AD and T2DM offers valuable insights into the development of biomarkers for diagnosis and therapy, especially in the complication of these two diseases.

Omics sciences and precision medicine in melanoma.

This article provides an overview of the application of omics sciences in melanoma research. The name omics sciences refers to the large-scale analysis of biological molecules like DNA, RNA, proteins, and metabolites. In the course of this review, we have adopted a focu-sed research strategy, meticulously selecting the most pertinent and emblematic articles related to the topic. Our methodology included a systematic examination of the scientific literature to guarantee a thorough and precise synthesis of the existing sources. With the advent of high-throughput technologies, omics have become an essential tool for understanding the complexity of melanoma. In this article, we discuss the different omics approaches used in melanoma research, including genomics, transcriptomics, proteomics, and metabolomics. We also highlight the major findings and insights gained from these studies, including the identification of new therapeutic targets and the development of biomarkers for diagnosis and prognosis. Finally, we discuss the challenges and future directions in omics-based melanoma research, including the integration of multiple omics data and the development of personalized medicine approaches. Overall, this article emphasizes the importance of omics science in advancing our understanding of melanoma and its potential for improving patient outcomes.

Identification of potential biomarkers for diagnosis of syphilis from the cerebrospinal fluid based on untargeted metabolomic analysis.

The infection rate of syphilis continues to rise globally, and the difficulty in diagnosis of neurosyphilis promptly needs to be resolved. More specific and sensitive diagnostic markers for latent syphilis and neurosyphilis should be found. Here the metabolic profiles of 88 cerebrospinal fluid samples from syphilis patients and controls were analyzed by LC/MS-based untargeted metabolomics. In total, 272 metabolites based on 3937 features obtained in ESI- mode and 252 metabolites based on 3799 features in ESI+ mode were identified. The experimental process was evaluated by principal component analysis, partial least squares discriminant analysis, and hierarchical cluster analysis. A clear separation between latent syphilis and neurosyphilis was found. Levels of lipid and linoleic acid metabolites, such as 9-oxo-octadecadienoic acid and 9,10,13-trihydroxyoctadecenoic acid, were increased in syphilis patients. In patients with neurosyphilis, significant changes in levels of 5-hydroxy-L-tryptophan (5-HTP) and acetyl-N-formyl-5-methoxykynurenamine (AFMK) in the tryptophan-kynurenine pathway were also detected. Only one metabolite, theophylline, differed significantly between symptomatic and asymptomatic neurosyphilis patients. Additionally, KEGG analysis revealed significant enrichment of tryptophan metabolism pathways, indicating a high correlation between tryptophan metabolism and syphilis symptoms. Levels of linoleic acid metabolites, 5-HTP, AFMK and theophylline were significantly altered in different patients. The role of these differential metabolites in the development of syphilis is worthy of further exploration. Our results may promote the development of biomarkers for diagnosis of latent syphilis from neurosyphilis, and for that of asymptomatic neurosyphilis from symptomatic neurosyphilis in the future.

Time-resolved proteome and transcriptome of paraquat-induced pulmonary fibrosis

BackgroundsPulmonary fibrosis (PF) is a pathological state presenting at the progressive stage of heterogeneous interstitial lung disease (ILD). The current understanding of the molecular mechanisms involved is incomplete. This clinical toxicology study focused on the pulmonary fibrosis induced by paraquat (PQ), a widely-used herbicide. Using proteo-transcriptome analysis, we identified differentially expressed proteins (DEPs) derived from the initial development of fibrosis to the dissolved stage and provided further functional analysis. MethodsWe established a mouse model of progressive lung fibrosis via intratracheal instillation of paraquat. To acquire a comprehensive and unbiased understanding of the onset of pulmonary fibrosis, we performed time-series proteomics profiling (iTRAQ) and RNA sequencing (RNA-Seq) on lung samples from paraquat-treated mice and saline control. The biological functions and pathways involved were evaluated through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway analysis. Correlation tests were conducted on comparable groups 7 days and 28 days post-exposure. Differentially expressed proteins and genes following the same trend on the protein and mRNA levels were selected for validation. The functions of the selected molecules were identified in vitro. The protein level was overexpressed by transfecting gene-containing plasmid or suppressed by transfecting specific siRNA in A549 cells. The levels of endothlial-mesenchymal transition (EMT) markers, including E-cadherin, vimentin, FN1, and α-SMA, were determined via western blot to evaluate the fibrotic process. ResultsWe quantified 1358 DEPs on day 7 and 426 DEPs on day 28 post exposure (Fold change >1.2; Q value < 0.05). The top 5 pathways – drug metabolism-cytochrome P450, metabolism of xenobiotics by cytochrome P450, complement and coagulation cascades, chemical carcinogenesis, protein digestion and absorption — were involved on both day 7 and day 28. Several pathways, including tight junction, focal adhesion, platelet activation, and ECM-receptor interaction, were more enriched on day 28 than on day 7. Integrative analysis of the proteome and transcriptome revealed a moderate correlation of quantitative protein abundance ratios with RNA abundance ratios (Spearman R = 0.3950 and 0.2477 on days 7 and 28, respectively), indicating that post-transcriptional regulation plays an important role in lung injury and repair. Western blot identified that the protein expressions of FN1, S100A4, and RBM3 were significantly upregulated while that of CYP1A1, FMO3, and PGDH were significantly downregulated on day 7. All proteins generally recovered to baseline on day 28. qPCR showed the mRNA levels of Fn1, S100a4, Rbm3, Cyp1a1, Fmo3, and Hpgd changed following the same trend as the levels of their respective proteins. Further, in vitro experiments showed that RBM3 was upregulated while PGDH was downregulated in an EMT model established in human lung epithelial A549 cells. RBM3 overexpression and PGDH knockout could both induce EMT in A549 cells. RBM3 knockout or PGDH overexpression had no reverse effect on EMT in A549 cells. ConclusionsOur proteo-transcriptomic study determined the proteins responsible for fibrogenesis and uncovers their dynamic regulation from lung injury to repair, providing new insights for the development of biomarkers for diagnosis and treatment of fibrotic diseases.

Determination of Genetic and Epigenetic Modifications-Related Prognostic Biomarkers of Breast Cancer: Genome High-Throughput Data Analysis.

The high heterogeneity of breast cancer (BRCA) makes it more challenging to interpret the genetic variation mechanisms involved in BRCA pathogenesis and prognosis. Areas with high DNA methylation (such as CpG islands) were accompanied by copy number variation (CNV), and these genomic variations affected the level of DNA methylation. In this study, we characterized intertumor heterogeneity and analyzed the effects of CNV on DNA methylation and gene expression. In addition, we performed a Genetic Set Enrichment Analysis (GSEA) to identify key pathways for changes between patients with low and high expression of genes. Our analysis found two key genes, namely, HPDL and SOX17. The protein expressed by HPDL is 4-hydroxyphenylpyruvate dioxygenase-like protein, which has dioxygenase activity. SOX17 is a transcription factor that can inhibit Wnt signaling, promote the degradation of activated CTNNB1, and participate in cell proliferation. Our analysis found that the CNV of HPDL and SOX17 is not only related to the patient's prognosis, but also related to gene methylation and expression levels affecting the patient's survival time. Among them, the high-methylation, low-expression HPDL and SOX17 showed poor prognosis. And the addition of two copies of SOX17 is associated with a lower survival rate, while a decrease in the copy number of HPDL also suggests a poor prognosis. This study provided an effective bioinformatics basis for further exploration of molecular mechanisms related to BRCA and assessment of patient prognosis, but the development of biomarkers for diagnosis and treatment still requires further clinical data validation.

Molecular biomarkers in diagnosis of bladder cancer

Rapid development of genomic studies has led to development of new molecular biomarkers for diagnosis of primary and recurrent forms of bladder cancer. The study objective is to evaluate the current status of molecular biomarkers for diagnosis of recurrence and/or progression of bladder cancer and possibilities of their clinical use. A search of literature published in the last several years in the Pubmed and MedLine databases was performed. The obtained data was analyzed, sensitivity, specificity, positive and negative prognostic value were determined. The requirements for quality and characteristics of molecular biomarkers vary significantly depending on a specific case. The clinical role of urine biomarkers in observation of patients with nonmuscle invasive bladder cancer remains uncertain. Assays approved by the U.S. Food and Drug Administration do not demonstrate desired sensitivity and specificity which leads to their limited use. Currently, commercial assays of urine biomarkers are not sufficiently studied which predetermines further search for the optimal method of early diagnosis of bladder cancer. Multicenter clinical studies will allow to determine the place of each molecular biomarker in clinical practice.

Are There Any Biomarkers for Pedophilia and Sexual Child Abuse? A Review.

The use of biomarkers in medicine is a common and valuable approach in several clinical fields. Understanding the relationship between measurable biological processes and clinical outcomes not only is indispensable in the face of understanding physiological processes in healthy as well as in diseased organisms but also for understanding and evaluating treatment effects. Therefore, also in the context of forensic psychiatry, biomarkers and their potentially beneficial effects are of growing interest. The objective of this review is to examine if there are biomarkers that may serve as a tool to support diagnostic process, treatment evaluation, and risk assessment of pedophilic individuals and child sexual offenders. In the first part, we present an overview of the current neurobiological, as well as physiological and psychophysiological approaches to characterize pedophilia and child sexual offending. Secondly, we discuss and evaluate the impact of these approaches on the development of biomarkers for diagnosis, therapy, and risk assessment in pedophilic subjects and child sexual offenders. We conclude that a lot of research has already enhanced our neurobiological knowledge about pedophilia and child sexual offending. Although there surely exist promising parameters and approaches, in our view currently none of these is ready yet to serve as a clinically applicable diagnostic, response, or predictive biomarker for pedophilia and child sexual offending. Therefore, further work remains to be done. The development of a composite diagnostic biomarker to assess deviant sexual interest, combining several measures like functional magnetic resonance imaging, electroencephalogram, eye tracking, and behavioral approaches seems to be most promising. A valid and reliable measurement of deviant sexual interest, insensitive to manipulations could significantly support clinical diagnostic process. Similarly, regarding therapy evaluation and risk assessment, a composite biomarker to assess inhibitory control functions seems to be promising. Furthermore, the application of the Research Domain Criteria-approach, a new approach for investigating and classifying mental disorders, offers the possibility to take research to a new level.

Integration of multi-omics data to mine cancer-related gene modules.

The identification of cancer-related genes is a major research goal, with implications for determining the pathogenesis of cancer and identifying biomarkers for early diagnosis and treatment. In this study, by integrating multi-omics data, including gene expression, DNA copy number variation, DNA methylation, transcription factors, miRNA, and lncRNA data, we propose a method for mining cancer-related genes based on network models. First, using random forest-based feature selection method multi-omics data are integrated to identify key regulatory factors that affect gene expression, and then genome-wide regulatory networks are constructed. Next, by comparing the regulatory networks of key candidate genes in variant samples and non-variant samples, a differential expression regulatory network is generated. The differential network contains a collection of abnormal regulatory genes of key candidate genes. Then, by introducing the functional similarity as a distance metric for gene sets, a density-based clustering method is used to mine gene modules related to cancer. We applied this method to LUSC (lung squamous cell carcinoma) and mined cancer-related gene modules composed of 20 genes. GO function and KEGG pathway analyses indicated that the modules were closely related to cancer. A survival analysis was used to verify that the excavated gene modules can effectively distinguish between high- and low-risk groups. Overall, these results suggest that the proposed method can be used to identify cancer-related gene modules, providing a basis for the development of biomarkers for diagnosis and treatment.

Radiomics and radiogenomics of primary liver cancers.

Concurrent advancements in imaging and genomic biomarkers have created opportunities to identify non-invasive imaging surrogates of molecular phenotypes. In order to develop such imaging surrogates radiomics and radiogenomics/imaging genomics will be necessary; there has been consistent progress in these fields for primary liver cancers. In this article we evaluate the current status of the field specifically with regards to hepatocellular carcinoma and intrahepatic cholangiocarcinoma, highlighting some of the up and coming results that were presented at the annual Radiological Society of North America Conference in 2017. There are an increasing number of studies in this area with a bias towards quantitative feature measurement, which is expected to benefit reproducibility of the findings and portends well for the future development of biomarkers for diagnosis, prognosis, and treatment response assessment. We review some of the advancements and look forward to some of the exciting future applications that are anticipated as the field develops.

De novo assembly and transcriptome analysis of the Pinus densiflora response to pine wilt disease in nature

Pine trees have economically and ecologically important roles. However, since the beginning of the twentieth century, a large number of trees have been seriously damaged by pine wilt disease (PWD). Although many studies have been conducted into blocking the spread of PWD, relatively few studies have been performed to examine the transcriptional responses of pine trees to the pine wood nematode (PWN). Here, we performed de novo assembly and analysis of the Pinus densiflora transcriptome by next-generation sequencing (NGS), to identify transcriptional responses that are related to the PWD infection. We identified that 586 of 71,003 assembled unigenes were differentially expressed after PWD infection. Gene ontology analysis showed that biological process terms related to defense responses (response to oxygen containing compound, response to jasmonic acid, response to biotic stimulus, cinnamic acid biosynthetic process, etc.) were significantly enriched in the DEGs after PWD infection. Our results suggested that jasmonic acid signaling is important in controlling defense response against PWD infection and is finely tuned by coordinated expression of positive and negative regulators. These findings contribute to our understanding of the transcriptional responses of P. densiflora to PWN, and could facilitate the development of biomarkers for diagnosis of PWD.

Identification of Shared Molecular Signatures Indicate the Susceptibility of Endometriosis to Multiple Sclerosis

Women with endometriosis (EMS) appear to be at a higher risk of developing other autoimmune diseases predominantly multiple sclerosis (MS). Though EMS and MS are evidently diverse in their phenotype, they are linked by a common autoimmune condition or immunodeficiency which could play a role in the expansion of endometriosis and possibly increase the risk of developing MS in women with EMS. However, the common molecular links connecting EMS with MS are still unclear. We conducted a meta-analysis of microarray experiments focused on EMS and MS with their respective controls. The GEO2R web application discovered a total of 711 and 1516 genes that are differentially expressed across the experimental conditions in EMS and MS, respectively with 129 shared DEGs between them. The functional enrichment analysis of DEGs predicts the shared gene expression signatures as well as the overlapping biological processes likely to infer the co-occurrence of EMS with MS. Network based meta-analysis unveiled six interaction networks/crosstalks through overlapping edges between commonly dysregulated pathways of EMS and MS. The PTPN1, ERBB3, and CDH1 were observed to be the highly ranked hub genes connected with disease-related genes of both EMS and MS. Androgen receptor (AR) and nuclear factor-kB p65 (RelA) were observed to be the most enriched transcription factor in the upstream of shared down-regulated and up-regulated genes, respectively. The two disease sample sets compared through crosstalk interactions between shared pathways revealed commonly up- and down-regulated expressions of 10 immunomodulatory proteins as probable linkers between EMS and MS. This study pinpoints the number of shared genes, pathways, protein kinases, and upstream regulators that may help in the development of biomarkers for diagnosis of MS and endometriosis at the same time through improved understanding of shared molecular signatures and crosstalk.

Abstract 3490: Interrogation of small RNA-seq data for small noncoding RNA in human colon cancer

Abstract Genomic analysis of the human transcriptome has been made possible only in last decade by next generation sequencing (NGS). Recent advancements in NGS has further allowed us to look into small non-coding RNAs (sncRNAs) such as microRNAs (miRNAs), Piwi-interacting-RNAs (piRNAs), long non-coding RNAs (lncRNAs) &amp; small nuclear/nucleolar RNAs (sn/snoRNAs). Recently, the roles of sncRNAs in biological processes have been implicated in biomarker development for diagnosis, prognosis &amp;therapy. In the present study, 50 colon cancer patient’s small RNA sequencing raw data was downloaded from NIH bioproject (PRJNA266667; 7 TNM stage II &amp; 43 TNM stage III) which contained 27 female &amp; 23 male samples. 24 samples had metachronous metastasis (MM) &amp; 26 non-metachronous metastasis (NMM). The small RNA-seq data was analyzed using PartekFlow. In depth analysis showed aberrant expression of 48 miRNAs (all upregulated) in TNM-III vs TNM-II specimens &amp; 20 miRNAs (17 upregulated &amp; 3 downregulated) in MM vs NMM. Further investigation of dysregulated miRNA through pathway analysis confirmed that the majority of the miRNAs were involved in cancer signaling pathways. Analysis of piRNA found unusual expression of 60 piRNAs (57 upregulated &amp; 3 downregulated) in TNM-III vs TNM-II &amp; 31 piRNAs (28 upregulated &amp; 3 downregulated) in MM vs NMM. Further analysis of long non-coding RNAs, we found 77 lncRNAs were significantly expressed in TNM-III vs TNM-II &amp;18 lncRNAs in MM vs NMM. We also, investigated small nuclear/nucleolar RNAs (sn/snoRNAs), miscRNAs &amp; mtRNAs, we identified 37 snRNAs, 105 snoRNAs, 28 miscRNAs &amp; 5 mtRNAs in TNM-III vs TNM-II whereas 2 snRNAs, 11 snoRNAs, 57 miscRNAs &amp; 8 mtRNAs in MM vs NMM were identified. In summary, our comprehensive analysis on publicly available small RNA-seq data identified multiple small non-coding RNAs that need to be further explored for their use in the prognosis, diagnosis &amp; therapy of colon cancer. Citation Format: Srinivas V. Koduru, Angelique Nyinawabera, Dino J. Ravnic, Amit K. Tiwari. Interrogation of small RNA-seq data for small noncoding RNA in human colon cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3490. doi:10.1158/1538-7445.AM2017-3490

Abstract 4447: Analysis of small RNA-seq data for differential expression of small noncoding RNAs in human colorectal cancer

Abstract Background: Cancer is a major cause of deaths worldwide, despite improved healthcare and technologies. Recent advancements in genome sequencing have led to the rapid study of the whole transcriptome and small RNAs with their biological functions. Non-coding RNAs (ncRNAs) play an important role in biological processes that greatly impact biomarker development for diagnosis, prognosis, and therapy. Non-coding RNAs such as microRNAs (miRNA), Piwi-interacting-RNAs (piRNAs), small nuclear/nucleolar RNAs (sn/snoRNAs) have recently been studied to understand their biology and pathology. Results: In the present study, we used eight matched colorectal patient tissue samples (benign, tumor, and metastasis) small RNA sequencing data remapped for various small RNA annotation. We identified aberrant expression of 13 miRs in tumor and metastasis specimens [tumor vs benign group (19 miRs) and metastasis vs benign group (38 miRs)] of which five were upregulated, and eight were downregulated, during disease progression. We also investigated pathway analysis on abbarent expression of miRNAs, which showed majority of miRs involved in the colon other types of cancers. Further analysis of piRNAs revealed that six piRNAs in tumor vs benign and 24 in metastasis vs benign samples (commonly in both groups, only two piRNAs). Additionally, we examined other types of small RNAs [sn/snoRNAs, mt_rRNA, misc_RNA, nonsense mediated decay (NMD) and rRNA], we identified 15 in tumor vs benign and 104 metastasis vs benign and only four in commonly expressed. Conclusion: In summary, our results identified multiple sncRNAs during colorectal cancer progression which needs to be further validated and can be used for prognosis, diagnosis, and therapeutic potentials. Citation Format: Srinivas V. Koduru, Amit K. Tiwari, Sprague W. Hazard, Milind K. Mahajan, Dino J. Ravnic. Analysis of small RNA-seq data for differential expression of small noncoding RNAs in human colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4447. doi:10.1158/1538-7445.AM2017-4447

Review of recent molecular landscape knowledge of gastric cancer.

Gastric cancer (GC) is one of the most frequently diagnosed cancers worldwide and its prognosis remains dismal. One reason for poor outcomes of GC patients is that most are diagnosed when the cancer has already advanced. Novel biomarkers with high sensitivity and specificity are needed to diagnose GC in the early stage. In addition, to improve the outcome of patients with GC, patient stratification according to prognostic factors and sensitivity to chemo(radio)therapy are necessary. Appropriate follow-up criteria and individualized treatment will contribute to improvement in prognosis. Over the past decades, development of microarray and sequencing technology have coalesced to increase reports regarding epigenetic alterations that affect the character of malignancies including GC. These advances help our understanding of gastric carcinogenesis and have the possibility of improving the prognosis of GC by contributing to the optimization of therapeutic strategies. Further development of biomarkers for diagnosis and prognosis are desperately needed. Here, we enumerate and describe some GC-related molecules reported over the past few years that may be useful biomarkers.

Partnership between a historically black college and a community health and wellness center to engage African American men in community participatory research and the development of biomarkers of diabetic nephropathy

African American communities disproportionately bear the burden of complications of diabetes. Early intervention can significantly improve the prognosis. Progress in overcoming disparities has been partially impaired by mistrust between the African American community and researchers. For this reason, minority men are often underrepresented in biomedical research studies that serve as the basis for the development of biomarkers for diagnosis and therapeutics. Overcoming this disparity calls for the development of culturally sensitive approaches that leverage partnerships with health care providers in minority serving clinics. A unique level of trust exists between African American communities and Historically Black Colleges and Universities (HBCUs). HBCU's are thus in a unique position to develop partnerships with clinical researchers to increase participation of African American men in research to promote healthy living and develop biomarkers for diseases that disproportionately affect their communities. In the current study, North Carolina A&amp;T State University, one of the largest HBCU's in North Carolina, has partnered with the Cone Health Community Health and Wellness Center to build infrastructure to engage African American men in community participatory research. The research is designed to: (i) empower African American men to prevent and/or manage diabetes in order to prevent progression to complications, such as diabetic nephropathy and (ii) to increase collection of biological samples from African American men for biomarker development. Diabetic nephropathy (DN) is the most common complication of diabetes and is the leading cause of end stage renal disease. With the rising incidences of obesity, diabetes is becoming an epidemic in the African American community. While efforts are being made to develop biomarkers for early diagnosis of DN, participation of African American men in these studies has been minimal. By partnering with a community clinic that serves uninsured and underinsured patients, many of whom are from minority ethnic groups, we were able to engage diabetic African American men in biomedical research and collect biological samples for development of biomarkers of diabetic nephropathy. These samples will be subjected to proteomic and metabolomics analysis to identify biomarkers of diabetic nephropathy representative of the African American male population.Support or Funding InformationNIH/NIHMD #U54MD008621 Sub‐Award # HU‐14004NIH/NIHMD U54MD008621 Sub‐Award # HU‐150006

Cytokines as biomarkers in rheumatoid arthritis.

RA is a complex disease that develops as a series of events often referred to as disease continuum. RA would benefit from novel biomarker development for diagnosis where new biomarkers are still needed (even if progresses have been made with the inclusion of ACPA into the ACR/EULAR 2010 diagnostic criteria) and for prognostic notably in at risk of evolution patients with autoantibody-positive arthralgia. Risk biomarkers for rapid evolution or cardiovascular complications are also highly desirable. Monitoring biomarkers would be useful in predicting relapse. Finally, predictive biomarkers for therapy outcome would allow tailoring therapy to the individual. Increasing numbers of cytokines have been involved in RA pathology. Many have the potential as biomarkers in RA especially as their clinical utility is already established in other diseases and could be easily transferable to rheumatology. We will review the current knowledge's relation to cytokine used as biomarker in RA. However, given the complexity and heterogeneous nature of RA, it is unlikely that a single cytokine may provide sufficient discrimination; therefore multiple biomarker signatures may represent more realistic approach for the future of personalised medicine in RA.

Endometrial Cancer: Molecular and Cellular Basis of Tumor Development, Novel Biomarkers and Therapeutic Agents, and Innovative Research Approaches

Endometrial Cancer: Molecular and Cellular Basis of Tumor Development, Novel Biomarkers and Therapeutic Agents, and Innovative Research Approaches

Medulla oblongata transcriptome changes during presymptomatic natural scrapie and their association with prion-related lesions

BackgroundThe pathogenesis of natural scrapie and other prion diseases is still poorly understood. Determining the variations in the transcriptome in the early phases of the disease might clarify some of the molecular mechanisms of the prion-induced pathology and allow for the development of new biomarkers for diagnosis and therapy. This study is the first to focus on the identification of genes regulated during the preclinical phases of natural scrapie in the ovine medulla oblongata (MO) and the association of these genes with prion deposition, astrocytosis and spongiosis.ResultsA custom microarray platform revealed that 86 significant probes had expression changes greater than 2-fold. From these probes, we identified 32 genes with known function; the highest number of regulated genes was included in the phosphoprotein-encoding group. Genes encoding extracellular marker proteins and those involved in the immune response and apoptosis were also differentially expressed. In addition, we investigated the relationship between the gene expression profiles and the appearance of the main scrapie-associated brain lesions. Quantitative Real-time PCR was used to validate the expression of some of the regulated genes, thus showing the reliability of the microarray hybridization technology.ConclusionsGenes involved in protein and metal binding and oxidoreductase activity were associated with prion deposition. The expression of glial fibrillary acidic protein (GFAP) was associated with changes in the expression of genes encoding proteins with oxidoreductase and phosphatase activity, and the expression of spongiosis was related to genes encoding extracellular matrix components or transmembrane transporters. This is the first genome-wide expression study performed in naturally infected sheep with preclinical scrapie. As in previous studies, our findings confirm the close relationship between scrapie and other neurodegenerative diseases.

Proteomics Annotation of Lipid Rafts Modified by Virus Infection

Lipid rafts are sphingolipid- and cholesterol-enriched membrane microdomains, which are involved in entry, assembly and budding of various types of viruses. Identification of rafts associated proteins modified by virus infection could therefore provide novel insights into the mechanisms of virus infection as well as the development of new biomarkers for diagnosis and drug development. Proteomic approaches, such as LC-ESI-MS/MS, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), two-dimensional difference gel electrophoresis (2D-DIGE), isotope-coded affinity tags (ICAT), Proteolytic ¹⁸O Labeling, isotope Tags for Relative and Absolute Quantification (iTRAQ), Stable Isotope Labeling with Amino acids in Cell culture (SILAC) and Multidimensional Protein Identification Technology (MudPIT), provide the large scale and unbiased platform to determine the dynamic profiles of the lipid rafts proteome. In this review, we summarized the research advance regarding modern proteomics analysis of host lipid rafts alterations in response to diverse virus infection.

Exploratory urinary metabolic biomarkers and pathways using UPLC-Q-TOF-HDMS coupled with pattern recognition approach

Metabolomics represents an emerging and powerful discipline concerned with the comprehensive analysis of small molecules and provides a powerful approach to discover biomarkers in biological systems. Recent development of biomarkers for diagnosis and therapeutic monitoring of liver-stagnation and spleen-deficiency syndrome (LSS)-type disease remains challenging. This study was undertaken to discover novel potential biomarkers for the non-invasive early diagnosis of human LSS. Urine samples which are potentially a rich source of metabolites were collected from patients with LSS, together with healthy control samples. Metabolite profiling was performed by ultra-performance liquid-chromatography/electrospray-ionization synapt high-definition mass spectrometry (UPLC-Q-TOF-HDMS) in conjunction with multivariate data analysis and ingenuity pathway analysis that were used to select the metabolites to be used for the non-invasive diagnosis of LSS. Twelve urinary differential metabolites contributing to the complete separation of LSS patients from matched healthy controls were identified involving several key metabolic pathways such as pentose and glucuronate interconversions, ascorbate, aldarate, cysteine, methionine, tyrosine, tryptophan, amino sugar and nucleotide sugar metabolism. More importantly, of the 12 differential metabolites, 4 metabolite markers, prolylhydroxyproline, L-homocystine, 2-octenoylcarnitine and α-N-phenylacetyl-L-glutamine, were effective for the diagnosis of human LSS, with an achieved sensitivity of 93.0%. These results demonstrate that robust metabolomics has the potential as a non-invasive strategy and promising screening tool to evaluate the potential of these metabolites in the early diagnosis of LSS patients and provides new insight into pathophysiological mechanisms.