An exfoliation and enrichment strategy results in improved transcriptional profiles when compared to matched formalin fixed samples

<p>Abstract</p> <p>Background</p> <p>Identifying the influence formalin fixation has on RNA integrity and recovery from clinical tissue specimens is integral to determining the utility of using archival tissue blocks in future molecular studies. For clinical material, the current gold standard is unfixed tissue that has been snap frozen. Fixed and frozen tissue however, both require laser capture microdissection to select for a specific cell population to study. The recent development of a sampling method capable of obtaining a viable, enriched cell population represents an alternative option in procuring cells from clinical material for molecular research purposes. The expression profiles of cells obtained by using this procurement approach, in conjunction with the profiles from cells laser capture microdissected from frozen tissue sections, were compared to the expression profiles from formalin fixed cells to determine the influence fixation has on expression profiles in clinical material.</p> <p>Methods</p> <p>Triplicate samples of non-neoplastic colonic epithelial cells were recovered from a hemicolectomy specimen using three different procurement methods from the same originating site: 1) an exfoliation and enrichment strategy 2) laser capture microdissection from formalin fixed tissue and 3) laser capture microdissection from frozen tissue. Parameters currently in use to assess RNA integrity were utilized to assess the quality of recovered RNA. Additionally, an expression microarray was performed on each sample to assess the influence each procurement technique had on RNA recovery and degradation.</p> <p>Results</p> <p>The exfoliation/enrichment strategy was quantitatively and qualitatively superior to tissue that was formalin fixed. Fixation negatively influenced the expression profile of the formalin fixed group compared to both the frozen and exfoliated/enrichment groups.</p> <p>Conclusion</p> <p>The exfoliation/enrichment technique represents a superior alternative in tissue procurement and RNA recovery relative to formalin fixed tissue. None of the deleterious effects associated with formalin fixation are encountered in the exfoliated/enriched samples because of the absence of its use in this protocol. The exfoliation/enrichment technique also represents an economical alternative that will yield comparable results to cells enriched by laser capture microdissection from frozen tissue sections.</p

Inferring the conservative causal core of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.</p> <p>Results</p> <p>In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from <it>E. coli </it>that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.</p> <p>Conclusions</p> <p>For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.</p

Bagging Statistical Network Inference from Large-Scale Gene Expression Data

Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository

Inferring the conservative causal core of gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically.</p> <p>Results</p> <p>In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from <it>E. coli </it>that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently.</p> <p>Conclusions</p> <p>For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.</p

A Relative Variation-Based Method to Unraveling Gene Regulatory Networks

Gene regulatory network (GRN) reconstruction is essential in understanding the functioning and pathology of a biological system. Extensive models and algorithms have been developed to unravel a GRN. The DREAM project aims to clarify both advantages and disadvantages of these methods from an application viewpoint. An interesting yet surprising observation is that compared with complicated methods like those based on nonlinear differential equations, etc., methods based on a simple statistics, such as the so-called -score, usually perform better. A fundamental problem with the -score, however, is that direct and indirect regulations can not be easily distinguished. To overcome this drawback, a relative expression level variation (RELV) based GRN inference algorithm is suggested in this paper, which consists of three major steps. Firstly, on the basis of wild type and single gene knockout/knockdown experimental data, the magnitude of RELV of a gene is estimated. Secondly, probability for the existence of a direct regulation from a perturbed gene to a measured gene is estimated, which is further utilized to estimate whether a gene can be regulated by other genes. Finally, the normalized RELVs are modified to make genes with an estimated zero in-degree have smaller RELVs in magnitude than the other genes, which is used afterwards in queuing possibilities of the existence of direct regulations among genes and therefore leads to an estimate on the GRN topology. This method can in principle avoid the so-called cascade errors under certain situations. Computational results with the Size 100 sub-challenges of DREAM3 and DREAM4 show that, compared with the -score based method, prediction performances can be substantially improved, especially the AUPR specification. Moreover, it can even outperform the best team of both DREAM3 and DREAM4. Furthermore, the high precision of the obtained most reliable predictions shows that the suggested algorithm may be very helpful in guiding biological experiment designs

Cystatin E/M suppresses legumain activity and invasion of human melanoma

<p>Abstract</p> <p>Background</p> <p>High activity of cysteine proteases such as legumain and the cathepsins have been shown to facilitate growth and invasion of a variety of tumor types. In breast cancer, several recent studies have indicated that loss of the cysteine protease inhibitor cystatin E/M leads to increased growth and metastasis. Although cystatin E/M is normally expressed in the skin, its role in cysteine protease regulation and progression of malignant melanoma has not been studied.</p> <p>Methods</p> <p>A panel of various non-melanoma and melanoma cell lines was used. Cystatin E/M and C were analyzed in cell media by immunoblotting and ELISA. Legumain, cathepsin B and L were analyzed in cell lysates by immunoblotting and their enzymatic activities were analyzed by peptide substrates. Two melanoma cell lines lacking detectable secretion of cystatin E/M were transfected with a cystatin E/M expression plasmid (pCST6), and migration and invasiveness were studied by a Matrigel invasion assay.</p> <p>Results</p> <p>Cystatin E/M was undetectable in media from all established melanoma cell lines examined, whereas strong immunobands were detected in two of five primary melanoma lines and in two of six lines derived from patients with metastatic disease. Among the four melanoma lines secreting cystatin E/M, the glycosylated form (17 kD) was predominant compared to the non-glycosylated form (14 kD). Legumain, cathepsin B and L were expressed and active in most of the cell lines, although at low levels in the melanomas expressing cystatin E/M. In the melanoma lines where cystatin E/M was secreted, cystatin C was generally absent or expressed at a very low level. When melanoma cells lacking secretion of cystatin E/M were transfected with pCST6, their intracellular legumain activity was significantly inhibited. In contrast, cathepsin B activity was not affected. Furthermore, invasion was suppressed in cystatin E/M over-expressing melanoma cell lines as measured by the transwell Matrigel assay.</p> <p>Conclusions</p> <p>These results suggest that the level of cystatin E/M regulates legumain activity and hence the invasive potential of human melanoma cells.</p

The representation of patient experience and satisfaction in physician rating sites. A criteria-based analysis of English- and German-language sites

<p>Abstract</p> <p>Background</p> <p>Information on patient experience and satisfaction with individual physicians could play an important role for performance measures, improved health care and health literacy. Physician rating sites (PRSs) bear the potential to be a widely available source for this kind of information. However, patient experience and satisfaction are complex constructs operationalized by multiple dimensions. The way in which PRSs allow users to express and rate patient experience and satisfaction could likely influence the image of doctors in society and the self-understanding of both doctors and patients. This study examines the extent to which PRSs currently represent the constructs of patient experience and satisfaction.</p> <p>Methods</p> <p>First, a systematic review of research instruments for measuring patient experience and satisfaction was conducted. The content of these instruments was analyzed qualitatively to create a comprehensive set of dimensions for patient experience and patient satisfaction. Second, PRSs were searched for systematically in English-language and German-language search engines of Google and Yahoo. Finally, we classified every structured question asked by the different PRS using the set of dimensions of patient experience and satisfaction.</p> <p>Results</p> <p>The qualitative content analysis of the measurement instruments produced 13 dimensions of patient experience and satisfaction. We identified a total of 21 PRSs. No PRSs represented all 13 dimensions of patient satisfaction and experience with its structured questions. The 3 most trafficked English-language PRS represent between 5 and 6 dimensions and the 3 most trafficked German language PRSs between 8 and 11 dimensions The dimensions for patient experience and satisfaction most frequently represented in PRSs included diversely operationalized ones such as <it>professional competence </it>and <it>doctor-patient relationship/support</it>. However, other less complex but nevertheless important dimensions such as <it>communication skills </it>and <it>information/advice </it>were rarely represented, especially in English-language PRSs.</p> <p>Conclusions</p> <p>Concerning the potential impact of PRSs on health systems, further research is needed to show which of the current operationalizations of patient experience and satisfaction presented in our study are establishing themselves in PRSs. Independently of this factual development, the question also arises whether and to what extent health policy can and should influence the operationalization of patient experience and satisfaction in PRSs. Here, the challenge would be to produce a set of dimensions capable of consensus from among the wide range of operationalizations found by this study.</p

Quantitative real-time RT-PCR validation of differential mRNA expression of SPARC, FADD, Fascin, COL7A1, CK4, TGM3, ECM1, PPL and EVPL in esophageal squamous cell carcinoma

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the most malignant tumors and typically presents at an advanced and rapidly fatal stage. To better understand the role of genetics in the etiology and prevention of ESCC and to identify potential susceptibility genes as well as early detection markers, we previously compared tumor and matched normal tissues from ESCC patients from a high-risk area of China using cDNA expression microarrays and identified 41 differentially-expressed genes (13 over-expressed and 28 under-expressed). METHODS: In the current study, we validated and quantitated differential mRNA expression in a sample of nine of these 41 genes, including four that were over-expressed (SPARC, FADD, Fascin, COL7A1), and five that were under-expressed (CK4, TGM3, ECM1, PPL, EVPL), in 75 new ESCC patients using quantitative Real-time RT-PCR and the 2(-ΔΔCT )method to examine both tumor and matched normal tissue. In addition, we examined expression patterns for these genes by selected demographic and clinical characteristics. RESULTS: Four previously over-expressed (tumor ≥2-fold normal) genes were all increased in the majority of new ESCC patients: SPARC was increased in 71% of patients, Fascin in 70%, FADD in 63%, and COL7A1 in 57%. Five previously under-expressed (tumor ≤0.5-fold normal) genes similarly showed decreased mRNA expression in two-thirds or more of patients: CK4 was decreased in 83% of patients, TGM3 in 77%, ECM1 in 73%, and PPL and EVPL in 67% each. In subset analyses, associations with age (for COL7A1), family history (for PPL and ECM1), and alcohol use (for SPARC and Fascin) were also noted. CONCLUSION: These data indicate that these nine genes have consistent differential mRNA expression, validating results of our previous cDNA array results, and affirming their potential role in the early detection of ESCC