Condensation of the β-cell secretory granule luminal cargoes pro/insulin and ICA512 RESP18 homology domain

Forsythoside B suppresses glioblastoma by upregulating the expression of PTPRN

Glioblastoma (IDH-wildtype) (GBM), the most common high-grade glioma, is a highly invasive and malignant tumor in the brain. Currently, there is no effective treatment for GBM, highlighting the urgent need to find novel therapeutic drugs. Forsythoside B (FB), as a phenylethanoid glycosides compound extracted from Forsythia suspensa, has shown pharmacological functions such as anti-inflammation and anti-bacteria. However, its effects and mechanisms in GBM remain unclear. By performing several in vitro assays, we found that FB suppressed the proliferation of GBM cells in dose- and time-dependent manners. Furthermore, FB arrested the cell cycle at the G1/S phase and induced apoptosis in GBM cells. FB also significantly inhibited GBM cells migration. Mechanistically, RNA sequencing results showed that FB treatment remarkably upregulated the expression of PTPRN (a protein-coding gene that plays an important role in the progression of various cancers) in GBM cells. Consistent with this finding, PTPRN expression was downregulated in GBM samples from the Chinese Glioma Genome Atlas (CGGA) and other databases. Knockdown of PTPRN partially restored the inhibitory effects of FB on GBM cells, whereas, overexpression of PTPRN enhanced FB-induced suppression of GBM cell growth and migration. Finally, we found that FB slowed down the growth of tumor in a GBM orthotopic mice model through upregulating PTPRN expression in vivo, with no significant toxicity to other organs. Taken together, these results suggest that FB exerts its anticancer effects on GBM via increasing the expression of PTPRN, which may provide a potential new therapeutic strategy for the treatment of GBM.

Bioinformatic analysis constructs an optimal prognostic index for survival-related variables (OPISV) based on whole-genome expression data in Glioblastoma

PURPOSE

Using clinical information and transcriptomic sequencing data from glioblastoma (GBM) patients in the TCGA database to perform gene-by-gene analysis that is aligned with individual patient characteristics and develop an optimal prognostic index of survival-related variables (OPISV) through iterative machine learning techniques to predict the prognosis of GBM patients.

STUDY DESIGN

The TCGA dataset was utilized as the training dataset, while two GEO datasets served as independent validation cohorts. Initially, survival analysis (p < 0.001***), differential gene expression analysis (p < 0.05*), and univariate Cox regression analysis (p < 0.05*) were employed to identify genes that are highly correlated with patient prognosis and exhibit significant differences in survival status. Subsequently, incorporating the non-excludable variable of age, a multivariate Cox regression analysis was performed in a stepwise manner to construct the OPISV. Finally, logistic and LASSO regressions were used to validate the association between the identified genes and patient survival. The OPISV performance is evaluated and its potential mechanisms are explored.

RESULTS

Age, CTSD, PTPRN, PTPRN2, NSUN5, DNAJC30 and SOX21 emerged as the optimal variables through multivariate Cox regression iterations. Further analysis characterized Age, PTPRN and DNAJC30 as independent prognostic risk factors for constructing OPISV, which is validated with external GEO datasets and GEPIA database. In OPISV_high populations, significantly upregulated GABAergic synapse function was exposed. Differential genes identified from gene clustering of the GABAergic synapse pathway and gene module highly correlated with GABAergic synapse in the WGCNA analysis are pointing unequivocally to the glioma progress.

CONCLUSION

OPISV is feasible for predicting patient survival, as it may serve as a potential mechanism underlying the involvement of GABAergic synapses in the progression of GBM.

Protein Tyrosine Phosphatase Receptors N and N2 Control Pituitary Melanotroph Development and POMC Expression

The neuroendocrine marker genes Ptprn and Ptprn2 encode protein tyrosine phosphatase receptors N and N2, 2 members of protein tyrosine phosphatase receptors void of enzymatic activity, and whose function and mechanism of action have not been elucidated. To explore the role(s) of Ptprn and Ptprn2 on the hypothalamic-pituitary-adrenal axis, we used mice in which both genes were knocked out (DKO). The focus in this study was on corticotrophs and melanotrophs from the anterior and intermediate lobes of the pituitary gland, respectively. In both sexes, DKO caused an increase in the expression of the corticotroph/melanotroph genes Pomc and Tbx19 and the melanotroph-specific gene Pax7. We also found in vivo and in vitro increased synthesis and release of beta-endorphin, alpha-melanocyte-stimulating hormone, and ACTH in DKO mice, which was associated with increased serum corticosterone levels and adrenal mass. DKO also increased the expression of other melanotroph-specific genes, but not corticotroph-specific genes. The dopaminergic pathway in the hypothalamus and dopaminergic receptors in melanotrophs were not affected in DKO mice. However, hyperplasia of the intermediate lobe was observed in DKO females and males, accompanied by increased proopiomelanocortin immunoreactivity per cell. These results indicate that protein tyrosine phosphatase receptor type N contributes to hypothalamic-pituitary-adrenal function by being involved in processes governing postnatal melanotroph development and Pomc expression.

Protein condensates in the the secretory pathway: Unraveling biophysical interactions and function

The emergence of phase separation phenomena among macromolecules has identified biomolecular condensates as fundamental cellular organizers. These condensates concentrate specific components and accelerate biochemical reactions without relying on membrane boundaries. Although extensive studies have revealed a large variety of nuclear and cytosolic membraneless organelles, we are witnessing a surge in the exploration of protein condensates associated with the membranes of the secretory pathway, such as the endoplasmic reticulum and the Golgi apparatus. This review focuses on protein condensates in the secretory pathway and discusses their impact on the organization and functions of this cellular process. Moreover, we explore the modes of condensate-membrane association and the biophysical and cellular consequences of protein condensate interactions with secretory pathway membranes.

Candidate Biomarkers for Targeting in Type 1 Diabetes; A Bioinformatic Analysis of Pancreatic Cell Surface Antigens

OBJECTIVE

Type 1 diabetes (T1Ds) is an autoimmune disease in which the immune system invades and destroys insulin-producing cells. Nevertheless, at the time of diagnosis, about 30-40% of pancreatic beta cells are healthy and capable of producing insulin. Bi-specific antibodies, chimeric antigen receptor regulatory T cells (CAR-Treg cells), and labeled antibodies could be a new emerging option for the treatment or diagnosis of type I diabetic patients. The aim of the study is to choose appropriate cell surface antigens in the pancreas tissue for generating an antibody for type I diabetic patients.

MATERIALS AND METHODS

In this bioinformatics study, we extracted pancreas-specific proteins from two large databases; the Human Protein Atlas (HPA) and Genotype-Tissue Expression (GTEx) Portal. Pancreatic-enriched genes were chosen and narrowed down by Protter software for the investigation of accessible extracellular domains. The immunohistochemistry (IHC) data of the protein atlas database were used to evaluate the protein expression of selected antigens. We explored the function of candidate antigens by using the GeneCards database to evaluate the potential dysfunction or activation/hyperactivation of antigens after antibody binding.

RESULTS

The results showed 429 genes are highly expressed in the pancreas tissue. Also, eighteen genes encoded plasma membrane proteins that have high expression in the microarray (GEO) dataset. Our results introduced four structural proteins, including NPHS1, KIRREL2, GP2, and CUZD1, among all seventeen candidate proteins.

CONCLUSION

The presented antigens can potentially be used to produce specific pancreatic antibodies that guide CARTreg, bi-specific, or labeling molecules to the pancreas for treatment, detection, or other molecular targeted therapy scopes for type I diabetes.

Protein nanocondensates: the next frontier

Over the past decade, myriads of studies have highlighted the central role of protein condensation in subcellular compartmentalization and spatiotemporal organization of biological processes. Conceptually, protein condensation stands at the highest level in protein structure hierarchy, accounting for the assembly of bodies ranging from thousands to billions of molecules and for densities ranging from dense liquids to solid materials. In size, protein condensates range from nanocondensates of hundreds of nanometers (mesoscopic clusters) to phase-separated micron-sized condensates. In this review, we focus on protein nanocondensation, a process that can occur in subsaturated solutions and can nucleate dense liquid phases, crystals, amorphous aggregates, and fibers. We discuss the nanocondensation of proteins in the light of general physical principles and examine the biophysical properties of several outstanding examples of nanocondensation. We conclude that protein nanocondensation cannot be fully explained by the conceptual framework of micron-scale biomolecular condensation. The evolution of nanocondensates through changes in density and order is currently under intense investigation, and this should lead to the development of a general theoretical framework, capable of encompassing the full range of sizes and densities found in protein condensates.

Condensation of the β-cell secretory granule luminal cargoes pro/insulin and ICA512 RESP18 homology domain

ICA512/PTPRN is a receptor tyrosine-like phosphatase implicated in the biogenesis and turnover of the insulin secretory granules (SGs) in pancreatic islet beta cells. Previously we found biophysical evidence that its luminal RESP18 homology domain (RESP18HD) forms a biomolecular condensate and interacts with insulin in vitro at close-to-neutral pH, that is, in conditions resembling those present in the early secretory pathway. Here we provide further evidence for the relevance of these findings by showing that at pH 6.8 RESP18HD interacts also with proinsulin-the physiological insulin precursor found in the early secretory pathway and the major luminal cargo of β-cell nascent SGs. Our light scattering analyses indicate that RESP18HD and proinsulin, but also insulin, populate nanocondensates ranging in size from 15 to 300 nm and 10e2 to 10e6 molecules. Co-condensation of RESP18HD with proinsulin/insulin transforms the initial nanocondensates into microcondensates (size >1 μm). The intrinsic tendency of proinsulin to self-condensate implies that, in the ER, a chaperoning mechanism must arrest its spontaneous intermolecular condensation to allow for proper intramolecular folding. These data further suggest that proinsulin is an early driver of insulin SG biogenesis, in a process in which its co-condensation with RESP18HD participates in their phase separation from other secretory proteins in transit through the same compartments but destined to other routes. Through the cytosolic tail of ICA512, proinsulin co-condensation with RESP18HD may further orchestrate the recruitment of cytosolic factors involved in membrane budding and fission of transport vesicles and nascent SGs.