Explore the vast range of titles available.

The advent of micro-physiological systems (MPS) in biomedical research has enabled the introduction of more complex and relevant physiological into in vitro models. The recreation of complex morphological features in three-dimensional environments can recapitulate otherwise absent dynamic interactions in conventional models. In this study we developed an advanced in vitro Renal Cell Carcinoma (RCC) that mimics the interplay between healthy and malignant renal tissue. Based on the TissUse Humimic platform our model combines healthy renal proximal tubule epithelial cells (RPTEC) and RCC. Co-culturing reconstructed RPTEC tubules with RCC spheroids in a closed micro-perfused circuit resulted in significant phenotypical changes to the tubules. Expression of immune factors revealed that interleukin-8 (IL-8) and tumor necrosis factor-alfa (TNF-α) were upregulated in the non-malignant cells while neutrophil gelatinase-associated lipocalin (NGAL) was downregulated in both RCC and RPTEC. Metabolic analysis showed that RCC prompted a shift in the energy production of RPTEC tubules, inducing glycolysis, in a metabolic adaptation that likely supports RCC growth and immunogenicity. In contrast, RCC maintained stable metabolic activity, emphasizing their resilience to external factors. RNA-seq and biological process analysis of primary RTPTEC tubules demonstrated that the 3D tubular architecture and MPS conditions reverted cells to a predominant oxidative phosphorylate state, a departure from the glycolytic metabolism observed in 2D culture. This dynamic RCC co-culture model, approximates the physiology of healthy renal tubules to that of RCC, providing new insights into tumor-host interactions. Our approach can show that an RCC-MPS can expand the complexity and scope of pathophysiology and biomarker studies in kidney cancer research.

Kidney cancer and chronic kidney disease are two renal pathologies with very different clinical management strategies and therapeutical options. Nonetheless, the cellular and molecular mechanisms underlying both conditions are closely related. Renal physiology is adapted to operate with a limited oxygen supply, making the kidney remarkably equipped to respond to hypoxia. This tightly regulated response mechanism is at the heart of kidney cancer, leading to the onset of malignant cellular phenotypes. Although elusive, the role of hypoxia in chronic kidney diseases is emerging as related to fibrosis, a pivotal factor in decaying renal function. The present review offers a perspective on the common biological traits shared between kidney cancer and chronic kidney disease and the available and prospective therapies for both conditions.

Patients with metastatic clear cell renal cell carcinoma (ccRCC) are frequently treated with tyrosine kinase inhibitors (TKI) such as sunitinib. It inhibits angiogenic pathways by mainly targeting the receptors of VEGF and PDGF. In ccRCC, angiogenesis is characterized by the inactivation of the von Hippel-Lindau gene (VHL) which in turn leads to the induction of HIF1α target genes such as CA9 and VEGF. Furthermore, the angiogenic phenotype of ccRCC is also reflected by endothelial markers (CD31, CD34) or other tumor-promoting factors like Ki67 or survivin. Tissue microarrays from primary tumor specimens of 42 patients with metastatic ccRCC under sunitinib therapy were immunohistochemically stained for selected markers related to angiogenesis. The prognostic and predictive potential of theses markers was assessed on the basis of the objective response rate which was evaluated according to the RECIST criteria after 3, 6, 9 months and after last report (12-54 months) of sunitinib treatment. Additionally, VHL copy number and mutation analyses were performed on DNA from cryo-preserved tumor tissues of 20 ccRCC patients. Immunostaining of HIF-1α, CA9, Ki67, CD31, pVEGFR1, VEGFR1 and -2, pPDGFRα and -β was significantly associated with the sunitinib response after 6 and 9 months as well as last report under therapy. Furthermore, HIF-1α, CA9, CD34, VEGFR1 and -3 and PDGRFα showed significant associations with progression-free survival (PFS) and overall survival (OS). In multivariate Cox proportional hazards regression analyses high CA9 membrane staining and a response after 9 months were independent prognostic factors for longer OS. Frequently observed copy number loss and mutation of VHL gene lead to altered expression of VHL, HIF-1α, CA9, and VEGF. Immunoexpression of HIF-1α, CA9, Ki67, CD31, pVEGFR1, VEGFR1 and -2, pPDGFRα and -β in the primary tumors of metastatic ccRCC patients might support the prediction of a good response to sunitinib treatment.

Renal cell carcinoma (RCC) comprises a heterogenous group of tumors. Traditionally, papillary RCC (pRCC) is associated with a favorable outcome compared to clear cell RCC (ccRCC), while other series report equivalent or worse prognosis. In this paper we comparatively evaluate outcome of pRCC versus ccRCC in two large multi-institutional databases (cohort study), including distribution of pRCC subtypes 1 and 2. Retrospective data of 1,943 surgically treated pRCC patients from 17 European/ North American centers between 1984-2015 were compared to 5,600 ccRCC patients from a database comprising 11 European/ North American centers (1984-2011). Median follow-up was 64.6 months. Differences between pRCC, subtypes, and ccRCC were compared with t-tests, Chi^2-tests, and exact Fisher tests. Cancer-specific mortality was analyzed with cumulative incidence curves and Cox cause-specific hazard models. The robustness of our results was examined with sensitivity analyses. We present that cancer-specific mortality rates and variables as stage, lymph node, and distant metastasis differ significantly between groups. Furthermore, we demonstrate that patients with non-metastatic pRCC had a significantly better cancer-specific mortality (HR 0.76, p = 0.007), when compared to ccRCC. Additionally, pRCC type 2 versus ccRCC exhibited no difference in cancer-specific mortality (HR 0.9, p = 0.722), whereas pRCC type 1 versus ccRCC displayed a risk of death reduced by 69% (p = 0.044). Taken together, outcome of pRCC versus ccRCC varies significantly in non-metastatic disease. Furthermore, pRCC type 2 exhibited no difference in cancer-specific mortality, whereas pRCC type 1 displayed a significantly reduced risk of death. Consequently, there is urgent need to respect histopathological entities and their subtypes, when assigning follow-up or targeted therapy to RCC patients.

Selenium (Se) is an essential trace element for selenoprotein biosynthesis. Selenoproteins have been implicated in cancer risk and tumor development. Selenoprotein P (SePP) serves as the major Se transport protein in blood and as reliable biomarker of Se status in marginally supplied individuals. Among the different malignancies, renal cancer is characterized by a high mortality rate. In this study, we aimed to analyze the Se status in renal cell cancer (RCC) patients and whether it correlates to cancer-specific mortality. To this end, serum samples of RCC patients (n = 41) and controls (n = 21) were retrospectively analyzed. Serum Se and SePP concentrations were measured by X-ray fluorescence and an immunoassay, respectively. Clinical and survival data were compared to serum Se and SePP concentrations as markers of Se status by receiver operating characteristic (ROC) curve and Kaplan-Meier and Cox regression analyses. In our patients, higher tumor grade and tumor stage at diagnosis correlated to lower SePP and Se concentrations. Kaplan-Meier analyses indicated that low Se status at diagnosis (SePP<2.4 mg/l, bottom tertile of patient group) was associated with a poor 5-year survival rate of 20% only. We conclude that SePP and Se concentrations are of prognostic value in RCC and may serve as additional diagnostic biomarkers identifying a Se deficit in kidney cancer patients potentially affecting therapy regimen. As poor Se status was indicative of high mortality odds, we speculate that an adjuvant Se supplementation of Se-deficient RCC patients might be beneficial in order to stabilize their selenoprotein expression hopefully prolonging their survival. However, this assumption needs to be rigorously tested in prospective clinical trials.

Startups searching for a business model face uncertainty. This research aims to demonstrates how B2B startups can use business experiments to discover and validate their business model's desirability quickly and cost-effectively. The research study follows a design science approach by focusing on two main steps: build and evaluate. We first created a B2B-Startup Experimentation Framework based on well-known earlier frameworks. After that, we applied the framework to the case of the German startup heliopas.ai. The framework consists of four steps (1) implementation of a measurement system, (2) hypothesis development and prioritization, (3) discovery, and (4) validation. Within its application, we conducted business experiments, including online and offline advertisements, as well as interviews. This research contributes in several ways to the understanding of how B2B-startups can use business experiments to discover and validate their business models: First, the designed B2B-Startup Experimentation Framework can serve as a guideline for company founders. Second, the results were used to improve the existing business model of the German B2B startup heliopas.ai. Finally, applying the framework allowed us to formulate design principles for creating business experiments. The design principles used in the study can be further tested in future studies.

Background Data on sequential therapy in patients with metastatic renal cell carcinoma (mRCC) and intrinsic resistance to receptor tyrosine kinase inhibitor (rTKI) treatment remains vague. Methods We retrospectively studied treatment characteristics and outcome of mRCC patients refractory to first rTKI therapy. Results Thirty-five mRCC patients (male, 18; female, 11) with primary resistance to first rTKI therapy (sunitinib, n = 28; sorafenib, n = 7) and a median treatment interval of 2.4 months (1 - 4.6) were identified. In 22 patients, progressive disease (PD) was determined by a new metastatic lesion. Of these, 16 patients received subsequent therapy with 12 patients remaining refractory and 4 patients achieving disease stabilization. In 13 patients continuous growth of existing metastatic lesions determined PD. Of these, 9 received sequential therapy with 6 achieving disease stabilization. Altogether, 25 patients were treated sequentially (rTKI: n = 15; mTOR-inhibitor: n = 10) and achieved a median PFS of 3.2 months (range, 1-16.6). Fifteen patients failed to respond to either line of therapy. Disease control was not associated with type of subsequent therapy. Median OS was 14.9 months (CI: 5.5-24.4). Conclusion Intrinsic resistance to rTKI is associated with a low chance of response to sequential therapy and a poor prognosis in mRCC patients.

PurposeBased on data retrieved from a comprehensive multicenter database, we externally validated a published postoperative nomogram for the prediction of disease-specific survival (DSS) in patients with papillary renal cell carcinoma (papRCC).MethodsA multicenter database containing data of 2325 patients with surgically treated papRCC was used as validation cohort. After exclusion of patients with missing data and patients included in the development cohort, 1372 patients were included in the final analysis. DSS-probabilities according to the nomogram were calculated and compared to actual DSS-probabilities. Subsequently, calibration plots and decision curve analyses were applied.ResultsThe median follow-up was 38 months (IQR 11.8–80.7). Median DSS was not reached. The c-index of the nomogram was 0.71 (95% CI 0.60–0.83). A sensitivity analysis including only patients operated after 1998 delivered a c-index of 0.84 (95% CI 0.77–0.92). Calibration plots showed slight underestimation of nomogram-predicted DSS in probability ranges below 90%: median nomogram-predicted 5-year DSS in the range below 90% was 55% (IQR 20–80), but the median actual 5-year DSS in the same group was 58% (95% CI 52–65). Decision-curve analysis showed a positive net-benefit for probability ranges between a DSS probability of 5% and 85%.ConclusionsThe nomogram performance was satisfactory for almost all DSS probabilities; hence it can be recommended for application in clinical routine and for counseling of patients with papRCC.