Current gene therapy最新文献

Introduction: Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent malignancy of the pancreas, and the incidence of this disease is approximately equivalent to the mortality rate. Immunotherapy has made a remarkable breakthrough in numerous cancers, while its efficacy in PDAC remains limited due to the immunosuppressive microenvironment. Immunotherapy efficacy is highly correlated with the abundance of immune cells, particularly cytotoxic T cells. Therefore, molecular classifier is needed to identify relatively hot tumors that may benefit from immunotherapy.

Method: In this study, we carried out a transcriptome analysis of 145 pancreatic tumors to define the underlying immune regulatory mechanism driving the PDAC immunosuppressive microenvironment. The immune subtype was identified by consensus clustering, and the underlying PDAC immune activation mechanism was thoroughly examined using single sample gene set enrichment analysis (ssGSEA). Area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the accuracy of the molecular classifier in differentiating immunological subgroups of PDAC.5.

Result: The protein level of molecular classifier was verified by immunohistochemistry in human PDAC tissue. Immune-hot tumors displayed higher levels of immune cell infiltration and immune checkpoint, in line with enriched immune escape pathways. Hematopoietic cell signal transducer (HCST), a molecular classifier used to differentiate immunological subtypes of PDAC, has shown a substantial link with the expression levels of cytotoxic markers, such as CD8A and CD8B. At the single cell level, we found that HCST was predominantly expressed in CD8T cells. By immunohistochemistry and survival analysis, we further demonstrated the prognostic value of HCST in PDAC.

Conclusion: We identified HCST as a molecular classifier to distinguish PDAC immune subtypes, which may be useful for early diagnosis and targeted therapy of PDAC.

Despite tremendous advancements in knowledge, diagnosis, and availability of both traditional and innovative treatments, pancreatic cancer remains a dangerous disease with a high death rate and dismal prognosis. The traditional strategy in adjuvant and palliative settings is still cytotoxic chemotherapy predicated on the purine derivative gemcitabine; nevertheless, there is an increasing need for new medicines that target the primary molecular pathways and pathophysiological abnormalities implicated. There is now just a tiny amount of evidence of therapeutic benefit when the targeted drug erlotinib is added to the conventional gemcitabine treatment. In preclinical and clinical trials, novel medications targeting mTOR, NF-κB, and proteasome, including the enzyme histone deacetylase, are currently being studied alongside the well-established monoclonal antibody treatments and small-molecule protein tyrosine kinase inhibitors. These novel medications may change the negative natural progression of this illness in conjunction with gene therapy and immunotherapy, both of which are undergoing clinical study. In this regard, leveraging miRNA manipulation to combat cancer is appealing due to its promise to deliver personalized treatment tailored to an individual's distinct gene or miRNA expression profile. Preclinical studies involving animals have showcased the effectiveness of miRNA-based therapies, with several of these treatments now progressing into human clinical trials for various malignancies and other medical conditions. This review describes the important developments of targeted therapeutics that are associated with pancreatic cancer and the discoveries which can help in dealing with this fatal malignancy in a more significant manner.

RNA modifications play crucial roles in immune system development and function, with dynamic changes essential for diverse cellular processes. Innovative profiling technologies are invaluable for understanding the significance of these modifications in immune cells, both in healthy and diseased states. This review explores the utility of such technologies in uncovering the functions of RNA modifications and their impact on immune responses. Additionally, it delves into the mechanisms through which aberrant RNA modifications influence the tumor microenvironments immune milieu. Despite significant progress, several outstanding research questions remain, highlighting the need for further investigation into the molecular mechanisms underlying RNA modification's effects on immune function in various contexts.

Lung cancer is a leading cause of mortality worldwide. Immunotherapy has emerged as a potentially effective strategy, as traditional medicines have shown minimal success. This review investigates the current state of immunotherapy for lung cancer treatment, focusing on its mechanisms, clinical applications, strategies, and future directions. This study focuses on the different characteristics of non-small and small-cell lung cancer to emphasize the need for targeted treatment strategies. In non-small cell lung cancer, immune checkpoint inhibitors that target PD-1, PDL1, and CTLA-4 have shown a strong therapeutic benefit and increased survival rates. The complex interactions among tumor cells, immune cells, and the tumor microenvironment significantly impact the outcome of immunotherapy. The determination of predicting biomarkers and conquering resistance requires an understanding of the tumor microenvironment. This study addresses a range of immunotherapeutic strategies, such as immune modulators, monoclonal antibodies, and cancer vaccines. The combination approaches are being explored to enhance treatment effectiveness and address resistance mechanisms that integrate immunotherapy with other modalities. Despite advancements, challenges still exist. The identification of reliable biomarkers, regulating immune- related adverse effects, and the overcoming of limitations in treating metastatic disease require more investigation. Future research directions should include exploring the immune microenvironment, developing personalized treatment strategies based on tumor profiles, and integrating new technologies for patient screening. Immunotherapy holds immense potential to modify lung cancer treatment and enhance clinical results.

Background: Metabolic disorders are significant risk factors for liver cancer, particularly Hepatocellular Carcinoma (HCC). However, the molecular genetic basis of metabolic reprogramming in the liver remains largely uncertain.

Objective: This study aimed to investigate some novel prognostic biomarkers in HCC by using proteogenomic and transcriptomic analysis and explore the potential role of specific prognostic genes in HCC.

Methods: Here, we have presented a proteogenomic analysis of 10 pairs of HCC. Protein co-expression and pathway analysis were performed to investigate the biological characteristics of HCC. Protein and mRNA expression profiles of multi-cohorts were integrated to detect novel prognostic protein markers of HCC. The carcinogenic roles of candidate prognostic markers were further evaluated by MTS assay, colony formation, monolayer wound healing assay, and xenograft models.

Results: A total of 2086 proteins with significantly different expressions were detected in HCC. Pathways related to oncogenic signaling and insulin-related metabolism have been found to be dysregulated and differentially regulated in HCC. We have identified the novel prognostic biomarkers, KIF5B, involved in liver metabolic reprogramming. The biomarkers were identified using multivariable COX regression analysis from two independent proteomic datasets (Fudan Cohort and our recruited cohort) and the TCGA mRNA database. Both the protein and mRNA up-regulation of KIF5B have been found to be associated with a poor clinical outcome in HCC. Insulin activated the protein expression of KIF5B in HCC. Knocking out KIF5B expression by sgRNA decreased the protein expression of FASN and SCD1 and the intracellular triglyceride concentration. Silencing KIF5B suppressed HCC cell proliferation and colony formation in vitro, as well as HCC growth in xenograft models.

Conclusion: Our findings have suggested KIF5B protein to function as a novel prognostic biomarker in HCC. KIF5B expression has been found to activate the AKT/mTOR pathway and reprogram triglyceride metabolism, leading to HCC development. Targeting KIF5B may be an effective strategy in the clinical treatment of HCC.

Glioblastoma is a malignant manifestation of a solid brain tumour with a very dismal prognosis due to an overall median survival of 14 months. The currently administered Standard treatment plan, the STUPP regimen, is not very effective in tackling this neoplasia. A major concern that affects the development of new drug formulations, specifically for Glioma, is the inherent sub-clonal heterogeneity, which includes the dynamic and intricate nature of the Tumour Microenvironment (TME). Targeting the cellular niche using personalized medication for glioma specifically gene therapy, seems to be promising, with most studies in preclinical models yielding optimistic results. This paper analyses the great headways made in glioma gene therapy in the last 10 years while looking into different therapeutic strategies. That said, certain challenges do plague the clinical use of gene therapy which have been highlighted in the hopes that future researchers will address these concerns and further propel gene therapy in its journey from the Lab to the bedside.

Introduction: Lung cancer stands as one of the most prevalent malignant neoplasms, with microRNAs (miRNAs) playing a pivotal role in the modulation of gene expression, impacting cancer cell proliferation, invasion, metastasis, immune escape, and resistance to therapy.

Methods: The intricate role of miRNAs in lung cancer underscores their significance as biomarkers for early detection and as novel targets for therapeutic intervention. Traditional approaches for the identification of miRNAs related to lung cancer, however, are impeded by inefficiencies and complexities.

Results: In response to these challenges, this study introduced an innovative deep-learning strategy designed for the efficient and precise identification of lung cancer-associated miRNAs. Through comprehensive benchmark tests, our method exhibited superior performance relative to existing technologies.

Conclusion: Further case studies have also confirmed the ability of our model to identify lung cancer- associated miRNAs that have undergone biological validation.

"Huntington's disease" (HD) is an autosomal dominant hereditary neurodegenerative disease characterized by defects in efferent striatal neurons, cortical neurons, and the basal ganglia. The pathogenesis of HD is still unclear, and there is currently no curative therapy for this disorder. This review emphasizes the potential beneficial effects of various neurotrophic factors in HD. PubMed, Web of Science, Embase, and google scholar databases were used to search for all studies on the efficacy of neurotrophic factors in HD. Several gene therapy strategies have been employed to treat HD, including gene therapy with a variety of neuroprotective factors. Moreover, a wide variability of gene therapy approaches such as a neurotrophin, has shown promising results for both prevention and neuroprotection in HD, which may be due to their potential to prevent neuronal cell death or decrease neurodegeneration, thereby promoting the growth of innovative axons, dendrites, and synapses leading to improvement of HD. Neurotrophic factors may be suitable as neuroprotective therapy agents in HD. Therefore, substantial research on gene therapy should be conducted to provide better treatment options for HD in the future.

Introduction: Antimicrobial peptides (AMPs), unlike antibiotics, are encoded in genomes. AMPs are exported from the cell after expression and translation. In the case of bacteria, the exported peptides target other microbes to give the producing bacterium a competitive edge. While AMPs are sought after for their similar antimicrobial activity to traditional antibiotics, it is difficult to predict which combinations of amino acids will confer antimicrobial activity. Many computer algorithms have been designed to predict whether a sequence of amino acids will exhibit antimicrobial activity, but the vast majority of validated AMPs in databases are still of eukaryotic origin. This defies common sense since the vast majority of life on Earth is prokaryotic.

Methods: The antimicrobial peptide pipeline, presented here, is a bacteria-centric AMP predictor that predicts AMPs by taking design inspiration from the sequence properties of bacterial genomes with the intention to improve the detection of naturally occurring bacterial AMPs. The pipeline integrates multiple concepts of comparative biology to search for candidate AMPs at the primary, secondary, and tertiary peptide structure levels.

Results: Results showed that the antimicrobial peptide pipeline identifies known AMPs that are missed by state-of-the-art AMP predictors and that the pipeline yields more AMP candidates from real bacterial genomes than from fake genomes, with the rate of AMP detection being significantly higher in the genomes of six nosocomial pathogens than in the fake genomes.

Conclusion: This bacteria-centric AMP pipeline enhances the detection of bacterial AMPs by incorporating sequence properties unique to bacterial genomes. It complements existing tools, addressing gaps in AMP detection and providing a promising avenue for discovering novel antimicrobial peptides.

Background: The global prevalence of rheumatoid arthritis (RA) is on the rise. Numerous studies have demonstrated the potential of stem cell-based therapies in RA treatment. Experimental evidence suggests that preconditioning enhances the regenerative capabilities of stem cells compared to their unconditioned counterparts.

Objective: This study aimed to evaluate whether adipose-derived stem cells (ADSCs) preconditioned with green tea epigallocatechin gallate (EGCG) and miR-92a exhibit superior therapeutic effects in RA compared to unconditioned ADSCs.

Methods: Both in vitro and in vivo models were employed. In the cellular model, ADSCs were preconditioned with EGCG and miR-92a. In the animal model, male Wistar rats were used, and RA was induced using the collagen-induced arthritis (CIA) model. Following RA induction, the animals were divided into six groups: Sham (healthy rats), RA (RA-induced rats), RA+ADSC (RA-induced rats receiving unconditioned ADSCs), RA+E-ADSC (RA-induced rats receiving EGCGpreconditioned ADSCs), RA+mic-ADSC (RA-induced rats receiving miR-92a mimicpreconditioned ADSCs), and RA+inh-ADSC (RA-induced rats receiving miR-92a inhibitorpreconditioned ADSCs).

Results: In the cellular model, preconditioning with EGCG and miR-92a activated the CXCR4/p- Akt signaling pathway, thereby enhancing ADSC viability. In the animal model, RA induction caused several joint pathologies, including hind paw swelling, disrupted bone metabolism, immune cell infiltration, increased expression of IL-17, KLF4, and IL-6, as well as cartilage degradation. While transplantation of unconditioned ADSCs modestly improved these pathological features, the administration of E-ADSCs and mic-ADSCs significantly ameliorated these conditions in RA rats. Conversely, the therapeutic effects of E-ADSCs and mic-ADSCs were attenuated by the transplantation of inh-ADSCs.

Conclusion: The therapeutic effects of E-ADSCs and mic-ADSCs in RA were strongly associated with the modulation of the KLF4/IL-17/MMP-2 axis. These findings suggest that ADSCs preconditioned with EGCG and miR-92a hold considerable clinical promise for the treatment of RA.