Characterization of protein-interaction networks in tumors

<p>Abstract</p> <p>Background</p> <p>Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be formally represented as graphs, and approximating PINs as undirected graphs allows the network properties to be characterized using well-established graph measures.</p> <p>This paper outlines features of PINs derived from 29 studies on differential gene expression in cancer. For each study the number of differentially regulated genes was determined and used as a basis for PIN construction utilizing the Online Predicted Human Interaction Database.</p> <p>Results</p> <p>Graph measures calculated for the largest subgraph of a PIN for a given differential-gene-expression data set comprised properties reflecting the size, distribution, biological relevance, density, modularity, and cycles. The values of a distinct set of graph measures, namely <it>Closeness Centrality</it>, <it>Graph Diameter</it>, <it>Index of Aggregation</it>, <it>Assortative Mixing Coefficient</it>, <it>Connectivity</it>, <it>Sum of the Wiener Number</it>, <it>modified Vertex Distance Number</it>, and <it>Eigenvalues </it>differed clearly between PINs derived on the basis of differential gene expression data sets characterizing malignant tissue and PINs derived on the basis of randomly selected protein lists.</p> <p>Conclusion</p> <p>Cancer PINs representing differentially regulated genes are larger than those of randomly selected protein lists, indicating functional dependencies among protein lists that can be identified on the basis of transcriptomics experiments. However, the prevalence of hub proteins was not increased in the presence of cancer. Interpretation of such graphs in the context of robustness may yield novel therapies based on synthetic lethality that are more effective than focusing on single-action drugs for cancer treatment.</p

Integrative Bioinformatics Analysis of Proteins Associated with the Cardiorenal Syndrome

The cardiorenal syndrome refers to the coexistence of kidney and cardiovascular disease, where cardiovascular events are the most common cause of death in patients with chronic kidney disease. Both, cardiovascular as well as kidney diseases have been extensively analyzed on a molecular level, resulting in molecular features and associated processes indicating a cross-talk of the two disease etiologies on a pathophysiological level. In order to gain a comprehensive picture of molecular factors contributing to the bidirectional interplay between kidney and cardiovascular system, we mined the scientific literature for molecular features reported as associated with the cardiorenal syndrome, resulting in 280 unique genes/proteins. These features were then analyzed on the level of molecular processes and pathways utilizing various types of protein interaction networks. Next to well established molecular features associated with the renin-angiotensin system numerous proteins involved in signal transduction and cell communication were found, involving specific molecular functions covering receptor binding with natriuretic peptide receptor and ligands as well known example. An integrated analysis of identified features pinpointed a protein interaction network involving mediators of hemodynamic change and an accumulation of features associated with the endothelin and VEGF signaling pathway. Some of these features may function as novel therapeutic targets

Proteomic-biostatistic integrated approach for finding the underlying molecular determinants of hypertension in human plasma

Despite advancements in lowering blood pressure, the best approach to lower it remains controversial because of the lack of information on the molecular basis of hypertension. We, therefore, performed plasma proteomics of plasma from patients with hypertension to identify molecular determinants detectable in these subjects but not in controls and vice versa. Plasma samples from hypertensive subjects (cases; n=118) and controls (n=85) from the InGenious HyperCare cohort were used for this study and performed mass spectrometric analysis. Using biostatistical methods, plasma peptides specific for hypertension were identified, and a model was developed using least absolute shrinkage and selection operator logistic regression. The underlying peptides were identified and sequenced off-line using matrix-assisted laser desorption ionization orbitrap mass spectrometry. By comparison of the molecular composition of the plasma samples, 27 molecular determinants were identified differently expressed in cases from controls. Seventy percent of the molecular determinants selected were found to occur less likely in hypertensive patients. In cross-validation, the overall R(2) was 0.434, and the area under the curve was 0.891 with 95% confidence interval 0.8482 to 0.9349, P&lt;0.0001. The mean values of the cross-validated proteomic score of normotensive and hypertensive patients were found to be -2.007±0.3568 and 3.383±0.2643, respectively, P&lt;0.0001. The molecular determinants were successfully identified, and the proteomic model developed shows an excellent discriminatory ability between hypertensives and normotensives. The identified molecular determinants may be the starting point for further studies to clarify the molecular causes of hypertension

Linking the ovarian cancer transcriptome and immunome

<p>Abstract</p> <p>Background</p> <p>Autoantigens have been reported in a variety of tumors, providing insight into the interplay between malignancies and the immune response, and also giving rise to novel diagnostic and therapeutic concepts. Why certain tumor-associated proteins induce an immune response remains largely elusive.</p> <p>Results</p> <p>This paper analyzes the proposed link between increased abundance of a protein in cancerous tissue and the increased potential of the protein for induction of a humoral immune response, using ovarian cancer as an example. Public domain data sources on differential gene expression and on autoantigens associated with this malignancy were extracted and compared, using bioinformatics analysis, on the levels of individual genes and proteins, transcriptional coregulation, joint functional pathways, and shared protein-protein interaction networks. Finally, a selected list of ovarian cancer-associated, differentially regulated proteins was tested experimentally for reactivity with antibodies prevalent in sera of ovarian cancer patients.</p> <p>Genes reported as showing differential expression in ovarian cancer exhibited only minor overlap with the public domain list of ovarian cancer autoantigens. However, experimental screening for antibodies directed against antigenic determinants from ovarian cancer-associated proteins yielded clear reactions with sera.</p> <p>Conclusion</p> <p>A link between tumor protein abundance and the likelihood of induction of a humoral immune response in ovarian cancer appears evident.</p

Transcriptional response in the unaffected kidney after contralateral hydronephrosis or nephrectomy

Transcriptional response in the unaffected kidney after contralateral hydronephrosis or nephrectomy.BackgroundUnilateral loss of kidney function is followed by compensatory contralateral growth. The early, genome-wide transcriptional response of the untouched kidney to unilateral ureteral obstruction (UUO) or unilateral nephrectomy is unknown.MethodsTwelve adult male Sprague-Dawley rats were subjected to UUO and twelve rats to unilateral nephrectomy. At time points 12, 24, and 72 hours after insult four rats each were sacrificed and the contralateral kidney harvested for genome-wide gene expression analysis, transcription factor analysis, and histomorphology.ResultsMicroarray studies revealed that the majority of differentially expressed transcripts were suppressed in UUO and unilateral nephrectomy compared to control kidneys. The function of these suppressed genes is predominantly growth inhibition and apoptosis suggesting a net pro-hypertrophic response. Insulin-like growth factor-2 (IGF-2)-binding protein was one of the few activated genes. We observed a distinctly different molecular signature between UUO and unilateral nephrectomy at the three time points investigated. The early response in UUO rats suggests a counterbalance to the nonfiltering kidney by activation of transport pathways such as the aquaporins. Unilateral nephrectomy kidneys, on the other hand, respond immediately to contralateral nephrectomy by activation of cell cycle regulators such as the cyclin family. Several genes with weakly defined function were found to be associated with either UUO or unilateral nephrectomy. Transcription factor analysis of the identified transcripts suggests common regulation at least of some of these genes. All kidneys showed normal histology.ConclusionRelease of growth inhibition by nephrectomy leads to immediate cell cycle activation after unilateral nephrectomy, whereas UUO kidneys counterbalance filtration failure by activation of several transporters

Baseline urinary metabolites predict albuminuria response to spironolactone in type 2 diabetes

The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in subjects with diabetic kidney disease, albeit with a large variability between individuals. Identifying novel biomarkers that predict response to therapy may help to tailor spironolactone therapy. We aimed to identify a set of metabolites for prediction of albuminuria response to spironolactone in subjects with type 2 diabetes. Systems biology molecular process analysis was performed a priori to identify metabolites linked to molecular disease processes and drug mechanism of action. Individual subject data and urine samples were used from 2 randomized placebo controlled double blind clinical trials (NCT01062763, NCT00381134). A urinary metabolite score was developed to predict albuminuria response to spironolactone therapy using penalized ridge regression with leave-one-out cross validation. Bioinformatic analysis identified a set of 18 metabolites linked to a diabetic kidney disease molecular model and potentially affected by spironolactone mechanism of action. Spironolactone reduced UACR relative to placebo by median -42% (25th to 75% percentile -65 to 6) and -29% (25th to 75% percentile -37 to -1) in the test and replication cohorts, respectively. In the test cohort, UACR reduction was higher in the lowest tertile of the baseline urinary metabolite score compared with middle and upper tertiles -58% (25th to 75% percentile -78 to 33), -28% (25th to 75% percentile -46 to 8), -40% (25th to 75% percentile -52% to 31), respectively, P= 0.001 for trend). In the replication cohort, UACR reduction was -54% (25th to 75% percentile -65 to -50), -41 (25th to 75% percentile -46% to 30), and -17% (25th to 75% percentile -36 to 5), respectively, P= 0.010 for trend). We identified a set of 18 urinary metabolites through systems biology to predict albuminuria response to spironolactone in type 2 diabetes. These data suggest that urinary metabolites may be used as a tool to tailor optimal therapy and move in the direction of personalized medicine

Is there decreasing public interest in renal transplantation? A Google trends TM analysis

Background and objectives: Renal transplantation is the preferred form of renal replacement therapy for the majority of patients with end stage renal disease (ESRD). The Internet is a key tool for people seeking healthcare-related information. This current work explored the interest in kidney transplantation based on Internet search queries using Google TrendsTM. Design, setting, participants, and measurements: We performed a Google TrendsTM search with the search term “kidney transplantation” between 2004 (year of inception) and 2018. We retrieved and analyzed data on the worldwide trend as well as data from the United Network for Organ Sharing (UNOS), the Organización Nacional de Trasplantes (ONT), the Eurotransplant area, and the National Health Service (NHS) Transplant Register. Google TrendsTM indices were investigated and compared to the numbers of performed kidney transplants, which were extracted from the respective official websites of UNOS, ONT, Eurotransplant, and the NHS. Results: During an investigational period of 15 years, there was a significant decrease of the worldwide Google TrendsTM index from 76.3 to 25.4, corresponding to an absolute reduction of −50.9% and a relative reduction by −66.7%. The trend was even more pronounced for the UNOS area (−75.2%), while in the same time period the number of transplanted kidneys in the UNOS area increased by 21.9%. Events of public interest had an impact on the search queries in the year of occurrence, as shown by an increase in the Google TrendsTM index by 39.2% in the year 2005 in Austria when a person of public interest received his second live donor kidney transplant. Conclusions: This study indicates a decreased public interest in kidney transplantation. There is a clear need to raise public awareness, since transplantation represents the best form of renal replacement therapy for patients with ESRD. Information should be provided on social media, with a special focus on readability and equitable access, as well as on web pages

Evaluation of the zucker diabetic fatty (ZDF) rat as a model for human disease based on urinary peptidomic profiles

Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level