Systems biology approaches toward autosomal dominant polycystic kidney disease (ADPKD)

Human iPSC-derived renal collecting duct organoid model cystogenesis in ADPKD

In autosomal dominant polycystic kidney disease (ADPKD), renal cyst lesions predominantly arise from collecting ducts (CDs). However, relevant CD cyst models using human cells are lacking. Although previous reports have generated in vitro renal tubule cyst models from human induced pluripotent stem cells (hiPSCs), therapeutic drug candidates for ADPKD have not been identified. Here, by establishing expansion cultures of hiPSC-derived ureteric bud tip cells, an embryonic precursor that gives rise to CDs, we succeed in advancing the developmental stage of CD organoids and show that all CD organoids derived from PKD1-/- hiPSCs spontaneously develop multiple cysts, clarifying the initiation mechanisms of cystogenesis. Moreover, we identify retinoic acid receptor (RAR) agonists as candidate drugs that suppress in vitro cystogenesis and confirm the therapeutic effects on an ADPKD mouse model in vivo. Therefore, our in vitro CD cyst model contributes to understanding disease mechanisms and drug discovery for ADPKD.

Identification of key pharmacological components and targets for Aidi injection in the treatment of pancreatic cancer by UPLC-MS, network pharmacology, and in vivo experiments

BACKGROUND

Pancreatic cancer is one of the most lethal cancers worldwide. Aidi injection (ADI) is a representative antitumor medication based on Chinese herbal injection, but its antitumor mechanisms are still poorly understood.

MATERIALS AND METHODS

In this work, the subcutaneous xenograft model of human pancreatic cancer cell line Panc-1 was established in nude mice to investigate the anticancer effect of ADI in vivo. We then determined the components of ADI using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS) and explored the possible molecular mechanisms against pancreatic cancer using network pharmacology.

RESULTS

In vivo experiments, the volume, weight, and degree of histological abnormalities of implanted tumors were significantly lower in the medium and high concentration ADI injection groups than in the control group. Network pharmacology analysis identified four active components of ADI and seven key targets, TNF, VEGFA, HSP90AA1, MAPK14, CASP3, P53 and JUN. Molecular docking also revealed high affinity between the active components and the target proteins, including Astragaloside IV to P53 and VEGFA, Ginsenoside Rb1 to CASP3 and Formononetin to JUN.

CONCLUSION

ADI could reduce the growth rate of tumor tissue and alleviate the structural abnormalities in tumor tissue. ADI is predicted to act on VEGFA, P53, CASP3, and JUN in ADI-mediated treatment of pancreatic cancer.

Integrative network pharmacology and experimental verification to reveal the anti-inflammatory mechanism of ginsenoside Rh4

Inflammation is an innate immune response to infection, and it is the main factor causing bodily injury and other complications in the pathological process. Ginsenoside Rh4 (G-Rh4), a minor ginsenoside of Panax ginseng C. A. Meyer and Panax notoginseng, has excellent pharmacological properties. However, many of its major pharmacological mechanisms, including anti-inflammatory actions, remain unrevealed. In this study, network pharmacology and an experimental approach were employed to elucidate the drug target and pathways of G-Rh4 in treating inflammation. The potential targets of G-Rh4 were selected from the multi-source databases, and 58 overlapping gene symbols related to G-Rh4 and inflammation were obtained for generating a protein–protein interaction (PPI) network. Molecular docking revealed the high affinities between key proteins and G-Rh4. Gene ontology (GO) and pathway enrichment analyses were used to analyze the screened core targets and explore the target–pathway networks. It was found that the JAK-STAT signaling pathway, TNF signaling pathway, NF-κB signaling pathway, and PI3K-Akt signaling pathway may be the key and main pathways of G-Rh4 to treat inflammation. Additionally, the potential molecular mechanisms of G-Rh4 predicted from network pharmacology analysis were validated in RAW264.7 cells. RT-PCR, Western blot, and ELISA analysis indicated that G-Rh4 significantly inhibited the production of pro-inflammatory cytokines such as TNF-α, IL-6, and IL-1β, as well as inflammation-related enzymes in lipopolysaccharide (LPS)-stimulated RAW264.7 cells. Moreover, in vitro experiments evaluated that Ginsenoside Rh4 exerts anti-inflammatory effects via the NF-κB and STAT3 signaling pathways. It is believed that our study will provide the basic scientific evidence that G-Rh4 has potential anti-inflammatory effects for further clinical studies.

Interdependent Regulation of Polycystin Expression Influences Starvation-Induced Autophagy and Cell Death

Autosomal dominant polycystic kidney disease (ADPKD) is mainly caused by deficiency of polycystin-1 (PC1) or polycystin-2 (PC2). Altered autophagy has recently been implicated in ADPKD progression, but its exact regulation by PC1 and PC2 remains unclear. We therefore investigated cell death and survival during nutritional stress in mouse inner medullary collecting duct cells (mIMCDs), either wild-type (WT) or lacking PC1 (PC1KO) or PC2 (PC2KO), and human urine-derived proximal tubular epithelial cells (PTEC) from early-stage ADPKD patients with PC1 mutations versus healthy individuals. Basal autophagy was enhanced in PC1-deficient cells. Similarly, following starvation, autophagy was enhanced and cell death reduced when PC1 was reduced. Autophagy inhibition reduced cell death resistance in PC1KO mIMCDs to the WT level, implying that PC1 promotes autophagic cell survival. Although PC2 expression was increased in PC1KO mIMCDs, PC2 knockdown did not result in reduced autophagy. PC2KO mIMCDs displayed lower basal autophagy, but more autophagy and less cell death following chronic starvation. This could be reversed by overexpression of PC1 in PC2KO. Together, these findings indicate that PC1 levels are partially coupled to PC2 expression, and determine the transition from renal cell survival to death, leading to enhanced survival of ADPKD cells during nutritional stress.

Metabolic Reprogramming and Reconstruction: Integration of Experimental and Computational Studies to Set the Path Forward in ADPKD

Metabolic reprogramming is a key feature of Autosomal Dominant Polycystic Kidney Disease (ADPKD) characterized by changes in cellular pathways occurring in response to the pathological cell conditions. In ADPKD, a broad range of dysregulated pathways have been found. The studies supporting alterations in cell metabolism have shown that the metabolic preference for abnormal cystic growth is to utilize aerobic glycolysis, increasing glutamine uptake and reducing oxidative phosphorylation, consequently resulting in ADPKD cells shifting their energy to alternative energetic pathways. The mechanism behind the role of the polycystin proteins and how it leads to disease remains unclear, despite the identification of numerous signaling pathways. The integration of computational data analysis that accompanies experimental findings was pivotal in the identification of metabolic reprogramming in ADPKD. Here, we summarize the important results and argue that their exploitation may give further insights into the regulative mechanisms driving metabolic reprogramming in ADPKD. The aim of this review is to provide a comprehensive overview on metabolic focused studies and potential targets for treatment, and to propose that computational approaches could be instrumental in advancing this field of research.

TWEAK Signaling Pathway Blockade Slows Cyst Growth and Disease Progression in Autosomal Dominant Polycystic Kidney Disease

BACKGROUND

In autosomal dominant polycystic kidney disease (ADPKD), cyst development and enlargement lead to ESKD. Macrophage recruitment and interstitial inflammation promote cyst growth. TWEAK is a TNF superfamily (TNFSF) cytokine that regulates inflammatory responses, cell proliferation, and cell death, and its receptor Fn14 (TNFRSF12a) is expressed in macrophage and nephron epithelia.

METHODS

To evaluate the role of the TWEAK signaling pathway in cystic disease, we evaluated Fn14 expression in human and in an orthologous murine model of ADPKD. We also explored the cystic response to TWEAK signaling pathway activation and inhibition by peritoneal injection.

RESULTS

Meta-analysis of published animal-model data of cystic disease reveals mRNA upregulation of several components of the TWEAK signaling pathway. We also observed that TWEAK and Fn14 were overexpressed in mouse ADPKD kidney cysts, and TWEAK was significantly high in urine and cystic fluid from patients with ADPKD. TWEAK administration induced cystogenesis and increased cystic growth, worsening the phenotype in a murine ADPKD model. Anti-TWEAK antibodies significantly slowed the progression of ADPKD, preserved renal function, and improved survival. Furthermore, the anti-TWEAK cystogenesis reduction is related to decreased cell proliferation-related MAPK signaling, decreased NF-κB pathway activation, a slight reduction of fibrosis and apoptosis, and an indirect decrease in macrophage recruitment.

CONCLUSIONS

This study identifies the TWEAK signaling pathway as a new disease mechanism involved in cystogenesis and cystic growth and may lead to a new therapeutic approach in ADPKD.

Forecast of the outbreak of COVID-19 using artificial neural network: Case study Qatar, Spain, and Italy

The present study illustrates the outbreak prediction and analysis on the growth and expansion of the COVID-19 pandemic using artificial neural network (ANN). The first wave of the pandemic outbreak of the novel Coronavirus (SARS-CoV-2) began in September 2019 and continued to March 2020. As declared by the World Health Organization (WHO), this virus affected populations all over the globe, and its accelerated spread is a universal concern. An ANN architecture was developed to predict the serious pandemic outbreak impact in Qatar, Spain, and Italy. Official statistical data gathered from each country until July 6th was used to validate and test the prediction model. The model sensitivity was analyzed using the root mean square error (RMSE), the mean absolute percentage error and the regression coefficient index R2, which yielded highly accurate values of the predicted correlation for the infected and dead cases of 0.99 for the dates considered. The verified and validated growth model of COVID-19 for these countries showed the effects of the measures taken by the government and medical sectors to alleviate the pandemic effect and the effort to decrease the spread of the virus in order to reduce the death rate. The differences in the spread rate were related to different exogenous factors (such as social, political, and health factors, among others) that are difficult to measure. The simple and well-structured ANN model can be adapted to different propagation dynamics and could be useful for health managers and decision-makers to better control and prevent the occurrence of a pandemic.

Increased kynurenine-to-tryptophan ratio in the serum of patients infected with SARS-CoV2: An observational cohort study

Immune dysregulation is a hallmark of patients infected by SARS-CoV2 and the balance between immune reactivity and tolerance is a key determinant of all stages of infection, including the excessive inflammatory state causing the acute respiratory distress syndrome. The kynurenine pathway (KP) of tryptophan (Trp) metabolism is activated by pro-inflammatory cytokines and drives mechanisms of immune tolerance. We examined the state of activation of the KP by measuring the Kyn:Trp ratio in the serum of healthy subjects (n = 239), and SARS-CoV2-negative (n = 305) and -positive patients (n = 89). Patients were recruited at the Emergency Room of St. Andrea Hospital (Rome, Italy). Kyn and Trp serum levels were assessed by HPLC/MS-MS. Compared to healthy controls, both SARS-CoV2-negative and -positive patients showed an increase in the Kyn:Trp ratio. The increase was larger in SARS-CoV2-positive patients, with a significant difference between SARS-CoV2-positive and -negative patients. In addition, the increase was more prominent in males, and positively correlated with age and severity of SARS-CoV2 infection, categorized as follows: 1 = no need for intensive care unit (ICU); 2 ≤ 3 weeks spent in ICU; 3 ≥ 3 weeks spent in ICU; and 4 = death. The highest Kyn:Trp values were found in SARS-CoV2-positive patients with severe lymphopenia. These findings suggest that the Kyn:Trp ratio reflects the level of inflammation associated with SARS-CoV2 infection, and, therefore, might represent a valuable biomarker for therapeutic intervention.