LIM domain only 7 negatively controls nonalcoholic steatohepatitis in the setting of hyperlipidemia.

BACKGROUND AND AIMS: Hyperlipidemia has been extensively recognized as a high-risk factor for NASH; however, clinical susceptibility to NASH is highly heterogeneous. The key controller(s) of NASH susceptibility in patients with hyperlipidemia has not yet been elucidated. Here, we aimed to reveal the key regulators of NASH in patients with hyperlipidemia and to explore its role and underlying mechanisms. APPROACH AND RESULTS: To identify the predominant suppressors of NASH in the setting of hyperlipidemia, we collected liver biopsy samples from patients with hyperlipidemia, with or without NASH, and performed RNA-sequencing analysis. Notably, decreased Lineage specific Interacting Motif domain only 7 (LMO7) expression robustly correlated with the occurrence and severity of NASH. Although overexpression of LMO7 effectively blocked hepatic lipid accumulation and inflammation, LMO7 deficiency in hepatocytes greatly exacerbated diet-induced NASH progression. Mechanistically, lysine 48 (K48)-linked ubiquitin-mediated proteasomal degradation of tripartite motif-containing 47 (TRIM47) and subsequent inactivation of the c-Jun N-terminal kinase (JNK)/p38 mitogen-activated protein kinase (MAPK) cascade are required for the protective function of LMO7 in NASH. CONCLUSIONS: These findings provide proof-of-concept evidence supporting LMO7 as a robust suppressor of NASH in the context of hyperlipidemia, indicating that targeting the LMO7-TRIM47 axis is a promising therapeutic strategy for NASH.

Unraveling neoantigen-associated genes in bladder cancer: An in-depth analysis employing 101 machine learning algorithms.

The therapeutic outcomes for bladder cancer (BLCA) remain suboptimal. Concurrently, there is a growing appreciation for the role of neoantigens in tumors. In this study, we explored the mechanisms underlying the involvement of neoantigen-associated genes in BLCA and their impact on prognosis. Our analysis incorporated both single-cell sequencing and bulk sequencing data sourced from publicly available databases. By employing a comprehensive set of 10 machine learning algorithms, we generated 101 algorithm combinations. The optimal combination, determined based on consistency indices, was utilized to construct a prognostic model comprising nine genes (CAPG, ACTA2, PDIA6, AKNA, PTMS, SNAP23, ID2, CD3G, SP140). Subsequently, we validated this model in an independent cohort, demonstrating its robust testing efficacy. Moreover, we explored the correlations between various clinical traits, model scores, and genes. Leveraging extensive public data resources, we conducted a drug sensitivity analysis to provide insights for targeted drug screening. Additionally, consensus clustering analysis and immune infiltration analysis were performed on bulk sequencing datasets and immunotherapy cohorts. These analyses yield valuable insights into the role of neoantigens in BLCA, guiding future research endeavors.

Machine learning-based integration develops a mitophagy-related lncRNA signature for predicting the progression of prostate cancer: a bioinformatic analysis.

Prostate cancer remains a complex and challenging disease, necessitating innovative approaches for prognosis and therapeutic guidance. This study integrates machine learning techniques to develop a novel mitophagy-related long non-coding RNA (lncRNA) signature for predicting the progression of prostate cancer. Leveraging the TCGA-PRAD dataset, we identify a set of four key lncRNAs and formulate a riskscore, revealing its potential as a prognostic indicator. Subsequent analyses unravel the intricate connections between riskscore, immune cell infiltration, mutational landscapes, and treatment outcomes. Notably, the pan-cancer exploration of YEATS2-AS1 highlights its pervasive impact, demonstrating elevated expression across various malignancies. Furthermore, drug sensitivity predictions based on riskscore guide personalized chemotherapy strategies, with drugs like Carmustine and Entinostat showing distinct suitability for high and low-risk group patients. Regression analysis exposes significant correlations between the mitophagy-related lncRNAs, riskscore, and key mitophagy-related genes. Molecular docking analyses reveal promising interactions between Cyclophosphamide and proteins encoded by these genes, suggesting potential therapeutic avenues. This comprehensive study not only introduces a robust prognostic tool but also provides valuable insights into the molecular intricacies and potential therapeutic interventions in prostate cancer, paving the way for more personalized and effective clinical approaches.

Establish TIIC signature score based the machine learning fusion in bladder cancer.

BACKGROUND: Bladder cancer is a prevalent malignant tumor with high heterogeneity. Current treatments, such as transurethral resection of bladder tumor (TURBT) and intravesical Bacillus Calmette-Guérin (BCG) therapy, still have limitations, with approximately 30% of non-muscle-invasive bladder cancer (NMIBC) progressing to muscle-invasive bladder cancer (MIBC), and a substantial number of MIBC patients experiencing recurrence after surgery. Immunotherapy has shown potential benefits, but accurate prediction of its prognostic effects remains challenging. METHODS: We analyzed bladder cancer RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and used various machine learning algorithms to screen for feature RNAs related to tumor-infiltrating immune cells (TIICs) from single-cell data. Based on these RNAs, we established a TIIC signature score and evaluated its relationship with overall survival (OS) and immunotherapy response in bladder cancer patients. RESULTS: The study identified 171 TIIC-RNAs and selected 11 TIIC-RNAs with prognostic value through survival analysis. The TIIC signature score established using a machine learning fusion method was significantly associated with OS and showed good predictive performance in different datasets. Additionally, the signature score was negatively correlated with immunotherapy response, with patients with low TIIC feature scores showing better survival outcomes after immunotherapy. Further biological functional analysis revealed a close association between the TIIC signature score and immune regulation processes, cellular metabolism, and genetic variations. CONCLUSION: This study successfully constructed and validated an RNA signature scoring system based on tumor-infiltrating immune cell (TIIC) features, which can effectively predict OS and the effectiveness of immunotherapy in bladder cancer patients.

Disulfidptosis-related lncRNA signatures assess immune microenvironment and drug sensitivity in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is associated with a high mortality rate, where resistance to immunotherapy and chemotherapy plays a crucial role. A newly identified form of cell death called disulfidptosis shows promise, but its biological mechanism in HCC remains uncertain. In this study, a prognostic model was developed for Disulfidptosis-related long non-coding RNAs (DRLs) from 370 HCC patients sourced from TCGA-LIHC, utilizing five key features: AC026356.1, AC073254.1, PXN-AS1 expression, AC026412.3, and AC099066.2. High-risk HCC patients had lower survival, CD4+ T cell infiltration, and elevated immune checkpoint gene expression. Furthermore, based on the features of DRLs, HCC was classified into three subtypes. Notably, patients belonging to different subtypes demonstrated varying overall survival rates, immune cell infiltration patterns, and sensitivity to immune therapy. Moreover, the novel DRL AC026412.3 (HR = 40.207) emerged as the most significant prognostic factor, exhibiting high expression across all HCC cells. Elevated expression of AC026412.3 promoted HCC cell proliferation and induced resistance to gefitinib. In conclusion, we have discovered five DRLs and constructed a prognostic risk model. Our findings validate the correlation between DRL-related prognostic models, tumor subtypes, and the HCC immune microenvironment along with its implications for immunotherapy. Moreover, further investigation into the molecular mechanisms of key biomarkers like AC026412.3 in the future will contribute significantly to advancing our comprehension of HCC's pathogenesis and drug resistance mechanisms.

Targeting Neuraminidase 4 Attenuates Kidney Fibrosis in Mice.

Despite significant progress in therapy, there remains a lack of substantial evidence regarding the molecular factors that lead to renal fibrosis. Neuraminidase 4 (NEU4), an enzyme that removes sialic acids from glycoconjugates, has an unclear role in chronic progressive fibrosis. Here, this study finds that NEU4 expression is markedly upregulated in mouse fibrotic kidneys induced by folic acid or unilateral ureter obstruction, and this elevation is observed in patients with renal fibrosis. NEU4 knockdown specifically in the kidney attenuates the epithelial-to-mesenchymal transition, reduces the production of pro-fibrotic cytokines, and decreases cellular senescence in male mice. Conversely, NEU4 overexpression exacerbates the progression of renal fibrosis. Mechanistically, NEU4254-388aa interacts with Yes-associated protein (YAP) at WW2 domain (231-263aa), promoting its nucleus translocation and activation of target genes, thereby contributing to renal fibrosis. 3,5,6,7,8,3',4'-Heptamethoxyflavone, a natural compound, is identified as a novel NEU4 inhibitor, effectively protecting mice from renal fibrosis in a NEU4-dependent manner. Collectively, the findings suggest that NEU4 may represent a promising therapeutic target for kidney fibrosis.

Protective effects and mechanisms of curcumin on podophyllotoxin toxicity in vitro and in vivo.

Podophyllotoxin (POD) is a naturally occurring lignan with pronounced antineoplastic and antiviral properties. POD binds to tubulin and prevents the formation of mitotic spindle. Although cases of overdose or accidental ingestion are quite often, no specific therapy is currently available to treat the POD intoxication. In the current investigation, the protective effects and mechanisms of curcumin (CUR) on podophyllotoxin toxicity were evaluated in vitro and in vivo. The results showed that CUR could protect POD-induced cytotoxicity by recovering the G2/M arrest and decrease the changes of membrane potential and microtubule structure in Vero cells. A significant decrease of mortality rates was observed in Swiss mice treated by intragastrical administration of POD+CUR as compared with POD alone. The POD+CUR group also exhibited decreases in plasma transaminases, alkaline phosphatase, lactate dehydrogenase, plasma urea, creatinine and malondialdehyde level but elevated superoxide dismutase and glutathione levels as compared to the POD group. Histological examination of the liver and kidney demonstrated less morphological changes in the treatment of POD+CUR as compared with POD alone. The mechanism of the protective effects might be due to the competitive binding of CUR with POD in the same colchicines binding site as revealed by the tubulin polymerization assay and the molecular docking analysis, and the antioxidant activity against the oxidative stress induced by POD. In summary, both in vitro and in vivo data indicated the promising role of CUR as a protective agent against the POD poisoning.

Fabrication of Stable and Self-Assembling Rapeseed Protein Nanogel for Hydrophobic Curcumin Delivery.

Food-dervied biopolymer nanogels have recently received considerable attention as favorable carrier systems for nutraceuticals and drugs. In the present study, new biocompatible and self-assembled acylated rapeseed protein isolate (ARPI)-based nanogels were fabricated for potential hydrophobic drug delivery by chemical acylation and heat-induced protein denaturation. The effects of the ARPI concentration, pH, heat temperature, and heat time on the physiochemical properties of self-assembled ARPI nanogels were investigated. The optimized ARPI nanogels were characterized by a hydrodiameter of 170 nm in size, spherical morphology, and light core-dark shell structure. In comparison to native rapeseed protein isolates and ARPI without the heat treatment, ARPI nanogels as a result of dual acylation and heat processes exhibited significantly altered spatial secondary and tertiary structures, increased surface hydrophobicity, and decreased free sulfhydryl contents of the protein. Such properties endow amphilic ARPI with the self-aggregating ability, resulting in the hydrophobic core with formations of covalent disulfide bonds and the hydrophilic shell with succinyl moieties exposed to the water side. Such a cross-linked structure allowed for ARPI nanogels to be resistant against a broad array of pH and ionic strength as well as lyophilization and dilution. ARPI nanogels demonstrated 95% encapsulation efficiency of hydrophobic compound curcumin and significantly increased its anticancer activity against multiple cancer cell lines.