GMP-compliant extracellular vesicles derived from umbilical cord mesenchymal stromal cells: manufacturing and pre-clinical evaluation in ARDS treatment.

BACKGROUND AIMS: Extracellular vesicles (EVs) represent a new axis of intercellular communication that can be harnessed for therapeutic purposes, as cell-free therapies. The clinical application of mesenchymal stromal cell (MSC)-derived EVs, however, is still in its infancy and faces many challenges. The heterogeneity inherent to MSCs, differences among donors, tissue sources, and variations in manufacturing conditions may influence the release of EVs and their cargo, thus potentially affecting the quality and consistency of the final product. We investigated the influence of cell culture and conditioned medium harvesting conditions on the physicochemical and proteomic profile of human umbilical cord MSC-derived EVs (hUCMSC-EVs) produced under current good manufacturing practice (cGMP) standards. We also evaluated the efficiency of the protocol in terms of yield, purity, productivity, and expression of surface markers, and assessed the biodistribution, toxicity and potential efficacy of hUCMSC-EVs in pre-clinical studies using the LPS-induced acute lung injury model. METHODS: hUCMSCs were isolated from a cord tissue, cultured, cryopreserved, and characterized at a cGMP facility. The conditioned medium was harvested at 24, 48, and 72 h after the addition of EV collection medium. Three conventional methods (nanoparticle tracking analysis, transmission electron microscopy, and nanoflow cytometry) and mass spectrometry were used to characterize hUCMSC-EVs. Safety (toxicity of single and repeated doses) and biodistribution were evaluated in naive mice after intravenous administration of the product. Efficacy was evaluated in an LPS-induced acute lung injury model. RESULTS: hUCMSC-EVs were successfully isolated using a cGMP-compliant protocol. Comparison of hUCMSC-EVs purified from multiple harvests revealed progressive EV productivity and slight changes in the proteomic profile, presenting higher homogeneity at later timepoints of conditioned medium harvesting. Pooled hUCMSC-EVs showed a non-toxic profile after single and repeated intravenous administration to naive mice. Biodistribution studies demonstrated a major concentration in liver, spleen and lungs. HUCMSC-EVs reduced lung damage and inflammation in a model of LPS-induced acute lung injury. CONCLUSIONS: hUCMSC-EVs were successfully obtained following a cGMP-compliant protocol, with consistent characteristics and pre-clinical safety profile, supporting their future clinical development as cell-free therapies.

In silico approaches for drug repurposing in oncology: a scoping review.

Introduction: Cancer refers to a group of diseases characterized by the uncontrolled growth and spread of abnormal cells in the body. Due to its complexity, it has been hard to find an ideal medicine to treat all cancer types, although there is an urgent need for it. However, the cost of developing a new drug is high and time-consuming. In this sense, drug repurposing (DR) can hasten drug discovery by giving existing drugs new disease indications. Many computational methods have been applied to achieve DR, but just a few have succeeded. Therefore, this review aims to show in silico DR approaches and the gap between these strategies and their ultimate application in oncology. Methods: The scoping review was conducted according to the Arksey and O'Malley framework and the Joanna Briggs Institute recommendations. Relevant studies were identified through electronic searching of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We included peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between 1 January 2003, and 31 December 2021. Results: We identified 238 studies for inclusion in the review. Most studies revealed that the United States, India, China, South Korea, and Italy are top publishers. Regarding cancer types, breast cancer, lymphomas and leukemias, lung, colorectal, and prostate cancer are the top investigated. Additionally, most studies solely used computational methods, and just a few assessed more complex scientific models. Lastly, molecular modeling, which includes molecular docking and molecular dynamics simulations, was the most frequently used method, followed by signature-, Machine Learning-, and network-based strategies. Discussion: DR is a trending opportunity but still demands extensive testing to ensure its safety and efficacy for the new indications. Finally, implementing DR can be challenging due to various factors, including lack of quality data, patient populations, cost, intellectual property issues, market considerations, and regulatory requirements. Despite all the hurdles, DR remains an exciting strategy for identifying new treatments for numerous diseases, including cancer types, and giving patients faster access to new medications.

Hedgehog components are overexpressed in a series of liver cancer cases.

Liver cancers, including hepatocellular carcinoma (HCC), are the sixth most common cancer and the third leading cause of cancer-related death worldwide, representing a global public health problem. This study evaluated nine patients with HCC. Six of the cases involved hepatic explants, and three involved hepatic segmentectomy for tumor resection. Eight out of nine tumors were HCC, with one being a combined hepatocellular-cholangiocarcinoma tumor. Conventional markers of hepatocellular differentiation (Hep Par-1, arginase, pCEA, and glutamine synthetase) were positive in all patients, while markers of hepatic precursor cells (CK19, CK7, EpCAM, and CD56) were negative in most patients, and when positive, they were detected in small, isolated foci. Based on in silico analysis of HCC tumors from The Cancer Genome Atlas database, we found that Hedgehog (HH) pathway components (GLI1, GLI2, GLI3 and GAS1) have high connectivity values (module membership > 0.7) and are strongly correlated with each other and with other genes in biologically relevant modules for HCC. We further validated this finding by analyzing the gene expression of HH components (PTCH1, GLI1, GLI2 and GLI3) in our samples through qPCR, as well as by immunohistochemical analysis. Additionally, we conducted a chemosensitivity analysis using primary HCC cultures treated with a panel of 18 drugs that affect the HH pathway and/or HCC. Most HCC samples were sensitive to sunitinib. Our results offer a comprehensive view of the molecular landscape of HCC, highlighting the significance of the HH pathway and providing insight into focused treatments for HCC.

Assessing the Clinical Impact of the SARS-CoV-2 Gamma Variant on Intensive Care Unit Admissions: Insights from a Reference Hospital in Northeastern Brazil.

The global challenge posed by the prolonged COVID-19 pandemic underscores the critical need for ongoing genomic surveillance to identify emerging variants and formulate effective public health strategies. This retrospective observational study, conducted in a reference hospital in Northeast Brazil and comprising 2116 cases, employed PCR genotyping together with epidemiological data to elucidate the impact of the Gamma variant during its emergence, revealing distinct patterns in hospitalization rates, severity of illness, and outcomes. The study emphasizes the challenges posed by the variant, particularly an increased tendency for ICU admissions and respiratory support, especially among adults aged 18 to 59 without comorbidities. Laboratory analyses further demonstrate elevated inflammatory, coagulation, and hepatic markers in the Gamma variant cohort, suggesting a more severe systemic response. Despite limitations, including a retrospective approach and single-institution data, the study underscores the importance of ongoing genomic surveillance. Overall, this research contributes valuable insights into the impact of the Gamma variant on COVID-19 dynamics, advocating for continued research and surveillance to inform effective public health strategies regarding evolving viral variants.

In silico approaches for drug repurposing in oncology: Protocol for a scoping review of existing evidence.

Drug repurposing has been applied in the biomedical field to optimize the use of existing drugs, leading to a more efficient allocation of research resources. In oncology, this approach is particularly interesting, considering the high cost related to the discovery of new drugs with therapeutic potential. Computational methods have been applied to predict associations between drugs and their targets. However, drug repurposing has not always been promising and its efficiency has yet to be proven. Therefore, the present scoping review protocol was developed to screen the literature on how in silico strategies can be implemented in drug repurposing in oncology. The scoping review will be conducted according to the Arksey and O'Malley framework (2005) and the Joanna Briggs Institute recommendations. We will search the PubMed/MEDLINE, Embase, Scopus, and Web of Science databases, as well as the grey literature. We will include peer-reviewed research articles involving in silico strategies applied to drug repurposing in oncology, published between January 1, 2003, and December 31, 2021. Data will be charted and findings described according to review questions. We will report the scoping review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review guidelines (PRISMA-ScR).

Studying effects of different protonation states of His11 and His102 in ribose-5-phosphate isomerase of Trypanosoma cruzi: an example of cooperative behavior.

The Trypanosoma cruzi ribose-5-phosphate isomerase B (TcRpiB) is a crucial piece in the pentose phosphate pathway and thus is a potential drug target for treatment of Chagas' disease. TcRpiB residues, such as Cys69, Asp45, Glu149 and Pro47, have confirmed their roles in substrate recognition, catalytic reaction and binding site conformation. However, the joint performance of His11 and His102, in the D-ribose-5-phosphate (R5P) in the catalysis is not well understood. In this work, we probed the influence of different protonation states of His11 and His102 on the behavior of the ligand R5P using molecular dynamics simulations, network analysis and thermodynamic integration. Simulations revealed that a protonated His11 combined with a neutral His102 (His11+‒His102) was able to stabilize the ligand R5P in the binding site. Moreover, calculated relative free energy differences showed that when protonated His11 was coupled to a neutral His102 an exergonic process takes place. On the other hand, neutral His11 combined with a protonated His102 (His11‒His102+), sampled conformations that resembled the catalyzed product D-ribulose-5-phosphate (Ru5P). Network analysis also demonstrated some peculiarities for these systems with some negatively correlated nodes in the binding site for His11‒His102+, and exclusive suboptimal paths for His11+‒His102. Therefore, the combined approach presented in this paper proposes two suitable protonation states for the TcRpiB catalytic mechanism, where an extra proton in either histidines might favor R5P binding or influence isomerization reaction to Ru5P. Our results may guide further in silico drug discovery studies. Communicated by Ramaswamy H. Sarma.