Albumin Expands Albumin Reabsorption Capacity in Proximal Tubule Epithelial Cells through a Positive Feedback Loop between AKT and Megalin

Renal proximal tubule cells (PTECs) act as urine gatekeepers, constantly and efficiently avoiding urinary protein waste through receptor-mediated endocytosis. Despite its importance, little is known about how this process is modulated in physiologic conditions. Data suggest that the phosphoinositide-3-kinase (PI3K)/protein kinase B (AKT) pathway regulates PTEC protein reabsorption. Here, we worked on the hypothesis that the physiologic albumin concentration and PI3K/AKT pathway form a positive feedback loop to expand endocytic capacity. Using LLC-PK1 cells, a model of PTECs, we showed that the PI3K/AKT pathway is required for megalin recycling and surface expression, affecting albumin uptake. Inhibition of this pathway stalls megalin at EEA1+ endosomes. Physiologic albumin concentration (0.01 mg/mL) activated AKT; this depends on megalin-mediated albumin endocytosis and requires previous activation of PI3K/mTORC2. This effect is correlated to the increase in albumin endocytosis, a phenomenon that we refer to as “albumin-induced albumin endocytosis”. Mice treated with L-lysine present decreased albumin endocytosis leading to proteinuria and albuminuria associated with inhibition of AKT activity. Renal cortex explants obtained from control mice treated with MK-2206 decreased albumin uptake and promoted megalin internalization. Our data highlight the mechanism behind the capacity of PTECs to adapt albumin reabsorption to physiologic fluctuations in its filtration, avoiding urinary excretion.

A Positive Feedback Loop Between Gastric Cancer Cells and Tumor-associated Macrophage Induces Malignancy Progression

Background: Hypoxia and inflammation tumor microenvironment (TME) play a crucial role in tumor development and progression. Although increased understanding of TME contributed to gastric cancer (GC) progression and prognosis, the direct interaction between macrophage and GC cells was not fully understood.Methods: Hypoxia and normoxia macrophage microarrays of GEO database was analyzed. The peripheral blood mononuclear cell acquired from the healthy volunteers. The expression of CXCL8 in GC tissues and cell lines was detected by quantitative reverse transcription PCR (qRT-PCR), western-blot, Elisa and immunofluorescence. Cell proliferation, migration, and invasion were evaluated by cell counting kit 8 (CCK8), colony formation, real-time imaging of cell migration and transwell. Luciferase reporter assays and chromatin immunoprecipitation were used to identify the interaction between transcription factor and target gene. Especially, a series of truncated and mutation reporter genes were applied to identify precise binding sites.The corresponding functions were verified in the complementation test and in vivo animal experiment.Results: Our results revealed that Hypoxia triggered macrophage secreted C-X-C Motif Chemokine Ligand 8 (CXCL8), which induced GC invasion and proliferation. This macrophage-induced GC progression was CXCL8 activated C-X-C Motif Chemokine Receptor 1/2 (CXCR1/2) on the GC cell membrane subsequently hyperactivated Janus kinase 1/ Signal transducer and activator of transcription 1 (JAK/STAT1) signaling pathway. Then, the transcription factor STAT1 directly led to the overexpression and secretion of Interleukin 10 (IL-10). Correspondingly, IL-10 induced the M2-type polarization of macrophages through the Nuclear Factor kappa B (NF-κB) pathway-dependent mechanism and continued to increase the expression and secretion of CXCL8 through the transcription factor Nuclear Factor Kappa B Subunit 1 (NFKB1, p50). It suggested a positive feedback loop between macrophage and GC. In clinical GC samples, increased CXCL8 predicted a patient's pessimistic outcome.Conclusion: Our work identified a positive feedback loop governing cancer cells and macrophage in GC that contributed to tumor progression and patient outcome.

The runaway evolution of SARS-CoV-2 leading to the highly evolved Delta strain

In new epidemics after the host shift, the pathogens may experience accelerated evolution driven by novel selective pressures. When the accelerated evolution enters a positive feedback loop with the expanding epidemics, the pathogen's runaway evolution may be triggered. To test this possibility in COVID-19, we analyze the extensive databases and identify 5 major waves of strains, one replacing the previous one in 2020-2021. The mutations differ entirely between waves and the number of mutations continues to increase, from 3-4 to 21-31. The latest wave is the Delta strain which accrues 31 new mutations to become highly prevalent. Interestingly, these new mutations in Delta strain emerge in multiple stages with each stage driven by 6-12 coding mutations that form a fitness group. In short, the evolution of SARS-CoV-2 from the oldest to the youngest wave, and from the earlier to the later stages of the Delta wave, is a process of acceleration with more and more mutations. The global increase in the viral population size (M(t), at time t) and the mutation accumulation (R(t)) may have indeed triggered the runaway evolution in late 2020, leading to the highly evolved Alpha and then Delta strain. To suppress the pandemic, it is crucial to break the positive feedback loop between M(t) and R(t), neither of which has yet to be effectively dampened by late 2021. New waves beyond Delta, hence, should not be surprising.

Positive feedback loop of HMGB1 and tumor-associated macrophages plays a key role in osteosarcoma metastasis

Background Numerous studies have demonstrated the important roles of tumor-associated macrophages (TAMs) in osteosarcoma metastasis. In osteosarcoma, higher levels of HMGB1 correlate with osteosarcoma progression. However, whether HMGB1 is involved in the polarization of M2 macrophages into M1 macrophages in osteosarcoma still remains largely unknown. Methods HMGB1 and CD206 mRNA expression was measured by qRT-PCR in osteosarcoma tissues and cells. HMGB1 and RAGE protein expression was measured by western blotting. Osteosarcoma migration was measured using a Transwell and wound-healing assay. Osteosarcoma invasion was measured using a Transwell assay. Macrophage subtypes were detected using flow cytometry. Results HMGB1 is aberrantly overexpressed in osteosarcoma, and positively correlates with the TNM III & IV stages, lymph node metastasis, and distant metastasis. Silencing HMGB1 inhibits migration, invasion, and metastasis-related proteins in osteosarcoma cells. Furthermore, the reduced HMGB1 expression in the conditioned media derived from osteosarcoma cells also induces the polarization of M2 TAMs to M1 TAMs. In addition, silencing HMGB1 inhibits the liver and lung metastases of osteosarcoma and reduces the expression of HMGB1, CD163, and CD206 in vivo experiments. HMGB1 regulates macrophage polarization through RAGE. Interestingly, the polarized M2 macrophages could induce osteosarcoma migration and invasion, which in turn results in activation of HMGB1 expression in osteosarcoma cells to form a positive feedback loop. Conclusions HMGB1 and M2 macrophages enhance osteosarcoma migration, invasion, and metastasis capability through positive feedback regulation. These findings reveal the significance of tumor cell and TAM interaction in the metastatic microenvironment.