Adenovirus expressing nc886, an anti-interferon and anti-apoptotic non-coding RNA, is an improved gene delivery vector.

Recombinant adenovirus (rAdV) vector is the most promising vehicle to deliver an exogenous gene into target cells and is preferred for gene therapy. Exogenous gene expression from rAdV is often too inefficient to induce phenotypic changes and the amount of administered rAdV must be very high to achieve a therapeutic dose. However, it is often hampered because a high dose of rAdV is likely to induce cytotoxicity by activating immune responses. nc886, a 102-nucleotide non-coding RNA that is transcribed by RNA polymerase III, acts as an immune suppressor and a facilitator of AdV entry into the nucleus. Therefore, in this study, we have constructed an rAdV expressing nc886 (AdV:nc886) to explore whether AdV:nc886 overcomes the aforementioned drawbacks of conventional rAdV vectors. When infected into mouse cell lines and mice, AdV:nc886 expresses a sufficient amount of nc886, which suppresses the induction of interferon-stimulated genes and apoptotic pathways triggered by AdV infection. As a result, AdV:nc886 is less cytotoxic and produces more rAdV-delivered gene products, compared with the parental rAdV vector lacking nc886. In conclusion, this study demonstrates that the nc886-expressing rAdV could become a superior gene delivery vehicle with greater safety and higher efficiency for in vivo gene therapy.

Inhibition of Amyloid-ß (Aß)-Induced Cognitive Impairment and Neuroinflammation in CHI3L1 Knockout Mice through Downregulation of ERK-PTX3 Pathway.

Several clinical studies reported that the elevated expression of Chitinase-3-like 1 (CHI3L1) was observed in patients suffering from a wide range of diseases: cancer, metabolic, and neurological diseases. However, the role of CHI3L1 in AD is still unclear. Our previous study demonstrated that 2-({3-[2-(1-Cyclohexen-1-yl)ethyl]-6,7-dimethoxy-4-oxo-3,4-dihydro-2-quinazolinyl}culfanyl)-N-(4-ethylphenyl)butanamide, a CHI3L1 inhibiting compound, alleviates memory and cognitive impairment and inhibits neuroinflammation in AD mouse models. In this study, we studied the detailed correlation of CHI3L1 and AD using serum from AD patients and using CHI3L1 knockout (KO) mice with Aß infusion (300 pmol/day, 14 days). Serum levels of CHI3L1 were significantly elevated in patients with AD compared to normal subjects, and receiver operating characteristic (ROC) analysis data based on serum analysis suggested that CHI3L1 could be a significant diagnostic reference for AD. To reveal the role of CHI3L1 in AD, we investigated the CHI3L1 deficiency effect on memory impairment in Aß-infused mice and microglial BV-2 cells. In CHI3L1 KO mice, Aß infusion resulted in lower levels of memory dysfunction and neuroinflammation compared to that of WT mice. CHI3L1 deficiency selectively inhibited phosphorylation of ERK and IκB as well as inhibition of neuroinflammation-related factors in vivo and in vitro. On the other hand, treatment with recombinant CHI3L1 increased neuroinflammation-related factors and promoted phosphorylation of IκB except for ERK in vitro. Web-based gene network analysis and our results showed that CHI3L1 is closely correlated with PTX3. Moreover, in AD patients, we found that serum levels of PTX3 were correlated with serum levels of CHI3L1 by Spearman correlation analysis. These results suggest that CHI3L1 deficiency could inhibit AD development by blocking the ERK-dependent PTX3 pathway.

Identification of signature gene set as highly accurate determination of metabolic dysfunction-associated steatotic liver disease progression.

BACKGROUND/AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. METHODS: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. RESULTS: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. CONCLUSION: We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.