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Clear cell renal cell carcinoma (ccRCC) characterized by a tumor thrombus (TT) extending into the inferior vena cava (IVC) generally indicates poor prognosis. Nevertheless, the risk for tumor recurrence after nephrectomy and thrombectomy varies. An applicable and accurate prediction system to select ccRCC patients with TT of the IVC (ccRCC/TT) at high risk after nephrectomy is urgently needed, but has not been established up to now. To our knowledge, a possible role of microRNAs (miRs) for the development of ccRCC/TT or their impact as prognostic markers in ccRCC/TT has not been explored yet. Therefore, we analyzed the expression of the previously described onco-miRs miR-200c, miR-210, miR-126, miR-221, let-7b, miR-21, miR-143 and miR-141 in a study collective of 74 ccRCC patients. Using the expression profiles of these eight miRs we developed classification systems that accurately differentiate ccRCC from non-cancerous renal tissue and ccRCC/TT from tumors without TT. In the subgroup of 37 ccRCC/TT cases we found that miR-21, miR-126, and miR-221 predicted cancer related death (CRD) accurately and independently from other clinico-pathological features. Furthermore, a combined risk score based on the expression of miR-21, miR-126 and miR-221 was developed and showed high sensitivity and specificity to predict cancer specific survival (CSS) in ccRCC/TT. Using the combined risk score we were able to classify ccRCC/TT patients correctly into high and low risk cases. The risk stratification by the combined risk score (CRS) will benefit from further cohort validation and might have potential for clinical application as a molecular prediction system to identify high- risk ccRCC/TT patients.
The treatment of high-risk prostate cancer (HRPCa) is a tremendous challenge for uro-oncologists. The identification of predictive moleculobiological markers allowing risk assessment of lymph node metastasis and systemic progression is essential in establishing effective treatment. In the current study, we investigate the prognostic potential of miR-205 in HRPCa study and validation cohorts, setting defined clinical endpoints for both. We demonstrate miR-205 to be significantly down-regulated in over 70% of the HRPCa samples analysed and that reconstitution of miR-205 causes inhibition of proliferation and invasiveness in prostate cancer (PCa) cell lines. Additionally, miR-205 is increasingly down-regulated in lymph node metastases compared to the primary tumour indicating that miR-205 plays a role in migration of PCa cells from the original location into extraprostatic tissue. Nevertheless, down-regulation of miR-205 in primary PCa was not correlated to the synchronous presence of metastasis and failed to predict the outcome for HRPCa patients. Moreover, we found a tendency for miR-205 up-regulation to correlate with an adverse outcome of PCa patients suggesting a pivotal role of miR-205 in tumourigenesis. Overall, we showed that miR-205 is involved in the development and metastasis of PCa, but failed to work as a useful clinical biomarker in HRPCa. These findings might have implications for the use of miR-205 as a prognostic or therapeutic target in HRPCa.
Background
Renal cell carcinoma (RCC) is marked by high mortality rate. To date, no robust risk stratification by clinical or molecular prognosticators of cancer-specific survival (CSS) has been established for early stages. Transcriptional profiling of small non-coding RNA gene products (miRNAs) seems promising for prognostic stratification. The expression of miR-21 and miR-126 was analysed in a large cohort of RCC patients; a combined risk score (CRS)-model was constructed based on expression levels of both miRNAs.
Methods
Expression of miR-21 and miR-126 was evaluated by qRT-PCR in tumour and adjacent non-neoplastic tissue in n = 139 clear cell RCC patients. Relation of miR-21 and miR-126 expression with various clinical parameters was assessed. Parameters were analysed by uni- and multivariate COX regression. A factor derived from the z-score resulting from the COX model was determined for both miRs separately and a combined risk score (CRS) was calculated multiplying the relative expression of miR-21 and miR-126 by this factor. The best fitting COX model was selected by relative goodness-of-fit with the Akaike information criterion (AIC).
Results
RCC with and without miR-21 up- and miR-126 downregulation differed significantly in synchronous metastatic status and CSS. Upregulation of miR-21 and downregulation of miR-126 were independently prognostic. A combined risk score (CRS) based on the expression of both miRs showed high sensitivity and specificity in predicting CSS and prediction was independent from any other clinico-pathological parameter. Association of CRS with CSS was successfully validated in a testing cohort containing patients with high and low risk for progressive disease.
Conclusions
A combined expression level of miR-21 and miR-126 accurately predicted CSS in two independent RCC cohorts and seems feasible for clinical application in assessing prognosis.
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
Small bacterial regulatory RNAs (sRNAs) have been implicated in the regulation of numerous metabolic pathways. In most of these studies, sRNA-dependent regulation of mRNAs or proteins of enzymes in metabolic pathways has been predicted to affect the metabolism of these bacteria. However, only in a very few cases has the role in metabolism been demonstrated. Here, we performed a combined transcriptome and metabolome analysis to define the regulon of the sibling sRNAs NgncR_162 and NgncR_163 (NgncR_162/163) and their impact on the metabolism of Neisseria gonorrhoeae. These sRNAs have been reported to control genes of the citric acid and methylcitric acid cycles by posttranscriptional negative regulation. By transcriptome analysis, we now expand the NgncR_162/163 regulon by several new members and provide evidence that the sibling sRNAs act as both negative and positive regulators of target gene expression. Newly identified NgncR_162/163 targets are mostly involved in transport processes, especially in the uptake of glycine, phenylalanine, and branched-chain amino acids. NgncR_162/163 also play key roles in the control of serine-glycine metabolism and, hence, probably affect biosyntheses of nucleotides, vitamins, and other amino acids via the supply of one-carbon (C\(_1\)) units. Indeed, these roles were confirmed by metabolomics and metabolic flux analysis, which revealed a bipartite metabolic network with glucose degradation for the supply of anabolic pathways and the usage of amino acids via the citric acid cycle for energy metabolism. Thus, by combined deep RNA sequencing (RNA-seq) and metabolomics, we significantly extended the regulon of NgncR_162/163 and demonstrated the role of NgncR_162/163 in the regulation of central metabolic pathways of the gonococcus.
Staphylococcus aureus is a common cause of bacteremia that can lead to severe complications once the bacteria exit the bloodstream and establish infection in secondary organs. Despite its clinical relevance, little is known about the bacterial factors facilitating the development of these metastatic infections. Here, we used an S. aureus transposon mutant library coupled to transposon insertion sequencing (Tn-Seq) to identify genes that are critical for efficient bacterial colonization of secondary organs in a murine model of metastatic bloodstream infection. Our transposon screen identified a LysR-type transcriptional regulator (LTTR), which was required for efficient colonization of secondary organs such as the kidneys in infected mice. The critical role of LTTR in secondary organ colonization was confirmed using an isogenic mutant deficient in the expression of LTTR. To identify the set of genes controlled by LTTR, we used an S. aureus strain carrying the LTTR gene in an inducible expression plasmid. Gene expression analysis upon induction of LTTR showed increased transcription of genes involved in branched-chain amino acid biosynthesis, a methionine sulfoxide reductase, and a copper transporter as well as decreased transcription of genes coding for urease and components of pyrimidine nucleotides. Furthermore, we show that transcription of LTTR is repressed by glucose, is induced under microaerobic conditions, and required trace amounts of copper ions. Our data thus pinpoints LTTR as an important element that enables a rapid adaptation of S. aureus to the changing host microenvironment.
IMPORTANCE Staphylococcus aureus is an important pathogen that can disseminate via the bloodstream and establish metastatic infections in distant organs. To achieve a better understanding of the bacterial factors facilitating the development of these metastatic infections, we used in this study a Staphylococcus aureus transposon mutant library in a murine model of intravenous infection, where bacteria first colonize the liver as the primary infection site and subsequently progress to secondary sites such as the kidney and bones. We identified a novel LysR-type transcriptional regulator (LTTR), which was specifically required by S. aureus for efficient colonization of secondary organs. We also determined the transcriptional activation as well as the regulon of LTTR, which suggests that this regulator is involved in the metabolic adaptation of S. aureus to the host microenvironment found in secondary infection sites.