Renal cell carcinoma (RCC) is the most common form of kidney cancer, known for its immune evasion and resistance to chemotherapy. Evidence indicates that the SARS-CoV-2 virus may worsen outcomes for RCC patients, as well as patients with diminished renal function. Evidence suggests that the SARS-CoV-2 virus may exacerbate outcomes in RCC patients and those with impaired renal function. This study explored the unidirectional effects of RCC cells and the SARS-CoV-2 spike protein (S protein) on human renal proximal tubule epithelial cells (RPTECs) using a microphysiological approach. We co-cultured RCC cells (Caki-1) with RPTEC and exposed them to the SARS-CoV-2 S protein under dynamic 3D conditions. The impact on metabolic activity, gene expression, immune secretions, and S protein internalization was evaluated. The SARS-CoV-2 S protein was internalized by RPTEC but poorly interacted with RCC cells. RPTECs exposed to RCC cells and the S protein exhibited upregulated expression of genes involved in immunogenic pathways, particularly those related to antigen processing and presentation via the major histocompatibility complex I (MHCI). Additionally, increased TNF-α secretion suggested a pro-inflammatory response. Metabolic shifts toward glycolysis were observed in RCC co-culture, while the presence of the S protein led to minor changes. The presence of RCC cells amplified the immune-modulatory effects of the SARS-CoV-2 S protein on the renal epithelium, potentially exacerbating renal inflammation and fostering tumor-supportive conditions. These findings suggest that COVID-19 infections can impact renal function in the presence of kidney cancer.

The tricellular tight junctions are crucial for the regulation of paracellular flux at tricellular junctions, where tricellulin (MARVELD2) and angulins (ILDR1, ILDR2, or LSR) are localized. The role of ILDR2 in podocytes, specialized epithelial cells in the kidney, is still unknown. We investigated the role of ILDR2 in glomeruli and its influence on blood filtration. Western blots, single-cell RNA sequencing (scRNA-seq), and superresolution microscopy showed a strong expression of ILDR2 in podocytes that colocalized with the podocyte-specific claudin CLDN5. Co-immunoprecipitation revealed that ILDR2 interacts with CLDN5. In glomerulopathies, induced by nephrotoxic serum and by desoxycorticosterone acetate (DOCA)-salt heminephrectomy, ILDR2 was strongly up-regulated. Furthermore, Ildr2 knockout mice exhibited glomerular hypertrophy and decreased podocyte density. However, they did not develop effacement of podocyte foot processes or proteinuria. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis of isolated glomeruli showed an increase in matrix proteins, such as fibronectin and collagens. This suggests a protective role of ILDR2 in glomerulopathies.

The Explainable Modular Neural Network (XModNN) enables the identification of biomarkers, facilitating the classification of diseases and clinical parameters in transcriptomic datasets. The modules within XModNN represent specific pathways or genes of a functional hierarchy. The incorporation of biological insights into the architectural design reduced the number of parameters. This is further reinforced by the weighted multi-loss progressive training, which enables successful classification with a reduced number of replicates. The combination of this workflow with layer-wise relevance propagation ensures a robust post hoc explanation of the individual module contribution. Two use cases were employed to predict sex and neuroblastoma cell states, demonstrating that XModNN, in contrast to standard statistical approaches, results in a reduced number of candidate biomarkers. Moreover, the architecture enables the training on a limited number of examples, attaining the same performance and robustness as support vector machine and random forests. The integrated pathway relevance analysis improves a standard gene set overrepresentation analysis, which relies solely on gene assignment. Two crucial genes and three pathways were identified for sex classification, while 26 genes and six pathways are highly important to discriminate adrenergic-mesenchymal cell states in neuroblastoma cancer.

Identifying effective drugs for focal segmental glomerulosclerosis (FSGS) treatment holds significant importance. Our high-content drug screening on zebrafish larvae relies on nitroreductase/metronidazole (NTR/MTZ)-induced podocyte ablation to generate FSGS-like injury. A crucial factor for successful drug screenings is minimizing variability in injury induction. For this, we introduce nifurpirinol (NFP) as a more reliable prodrug for targeted podocyte depletion. NFP showed a 2.3-fold increase in efficiency at concentrations 1,600-fold lower compared with MTZ-mediated injury induction. Integration into the screening workflow validated its suitability for the high-content drug screening. The presence of crucial FSGS hallmarks, such as podocyte foot process effacement, proteinuria, and activation of parietal epithelial cells, was observed. After the isolation of the glomeruli from the larvae, we identified essential pathways by proteomic analysis. This study shows that NFP serves as a highly effective prodrug to induce the FSGS-like disease in zebrafish larvae and is well-suited for a high-content drug screening to identify new candidates for the treatment of FSGS.NEW & NOTEWORTHY This research investigated the use of nifurpirinol in nanomolar amounts as a prodrug to reliably induce focal segmental glomerulosclerosis (FSGS)-like damage in transgenic zebrafish larvae. Through proteomic analysis of isolated zebrafish glomeruli, we were further able to identify proteins that are significantly regulated after the manifestation of FSGS. These results are expected to expand our knowledge of the pathomechanism of FSGS.

In actual pandemic situations like COVID-19, it is important to understand the influence of single mitigation measures as well as combinations to create most dynamic impact for lockdown scenarios. Therefore we created an agent-based model (ABM) to simulate the spread of SARS-CoV-2 in an abstract city model with several types of places and agents. In comparison to infection numbers in Germany our ABM could be shown to behave similarly during the first wave. In our model, we implemented the possibility to test the effectiveness of mitigation measures and lockdown scenarios on the course of the pandemic. In this context, we focused on parameters of local events as possible mitigation measures and ran simulations, including varying size, duration, frequency and the proportion of events. The majority of changes to single event parameters, with the exception of frequency, showed only a small influence on the overall course of the pandemic. By applying different lockdown scenarios in our simulations, we could observe drastic changes in the number of infections per day. Depending on the lockdown strategy, we even observed a delayed peak in infection numbers of the second wave. As an advantage of the developed ABM, it is possible to analyze the individual risk of single agents during the pandemic. In contrast to standard or adjusted ODEs, we observed a 21% (with masks) / 48% (without masks) increased risk for single reappearing participants on local events, with a linearly increasing risk based on the length of the events.