BACKGROUND:Cervical cancer is a major global health challenge and requires the exploration of novel treatment strategies. Immune checkpoint inhibitors, particularly those targeting Programmed Death 1 (PD-1) and Programmed Death-Ligand 1 (PD-L1), have emerged as promising therapeutic agents in oncology. This study aimed to evaluate the efficacy and safety of these inhibitors in the treatment of cervical cancer. METHODS:A comprehensive literature search was conducted across PubMed, Embase, Web of Science, Scopus, the Cochrane Library, and the China National Knowledge Infrastructure to identify studies published up to November 1, 2024. A total of 26 relevant studies were included, including 21 Non-Randomized Controlled Trials (Non-RCTs) and 5 Randomized Controlled Trials (RCTs). The analysis primarily evaluated the efficacy and safety of PD-1/PD-L1 inhibitors in patients with advanced cervical cancer. The primary outcomes included the objective response rate, disease control rate, progression-free survival, overall survival, and adverse events. Non-RCTs and RCTs were evaluated using ROBINS-I and ROB 2, respectively. Data analysis and visualization were performed using STATA 17.0 and GraphPad. This study has been registered with PROSPERO (registration number CRD42024510357). RESULTS:Therapeutic outcomes indicated that the objective response rate in patients with cervical cancer was 44.30% (95% CI 31.06%-57.93%), and the disease control rate was 63.05% (95% CI 51.67%-73.78%). The complete response, partial response, stable disease, and progressive disease rates were 12.58% (95% CI 6.46%-20.13%), 26.87% (95% CI 19.92%-34.40%), 17.95% (95% CI 12.50%-24.07%), and 27.61% (95% CI 17.68%-38.71%), respectively. The median PFS was 6.22 months (95% CI 3.86-8.59), with 6- and 12-month PFS rates of 58.93% (95% CI 47.78%-69.65%) and 45.20% (95% CI 32.73%-57.96%), respectively. The median OS was 14.81 months (95% CI 8.45-21.16), with 6- and 12-month OS rates of 86.57% (95% CI 80.92%-91.42%) and 70.34% (95% CI 61.47%-78.53%), respectively. Regarding safety, the incidence of treatment-related adverse events was 83.24% (95% CI 73.93%-90.94%), serious adverse events was 25.71% (95% CI 15.33%-37.58%), adverse drug reactions was 71.57% (95% CI 57.61%-83.78%), and immunerelated adverse events was 34.26% (95% CI 27.11%-41.76%). Common treatment-related adverse events included anemia, diarrhea, nausea, and leukopenia. CONCLUSION:The findings indicate that immune checkpoint inhibitors represent a potentially effective treatment option for patients with cervical cancer; however, their safety profile warrants careful consideration. Combination therapies involving PD-1 inhibitors appear to improve efficacy while maintaining manageable safety.
INTRODUCTION:Metabolic reprogramming facilitates survival in Acute Myeloid Leukemia (AML), but the molecular checkpoints governing ammonia tolerance remain unclear. This study aimed to investigate the role of the TRH/TRHR axis in AML ammonia tolerance and identify potential therapeutic interventions. METHODS:Ammonia Metabolism-Related Genes (AMRGs) were initially identified, and core prognostic genes were screened using 101 combinations of 10 machine learning algorithms. The optimal drug combination was derived by using the Biological Factor-Regulated Neural Network (BFReg- NN) model, followed by molecular docking. A risk signature was constructed and evaluated using survival analysis, time-dependent Receiver Operating Characteristic (ROC) curves, calibration curves, Decision Curve Analysis (DCA), and Cox regression. By systematically assessing ammonia levels, cell proliferation, apoptosis, and ROS accumulation, alongside functional rescue and genetic validation experiments, we elucidated the underlying mechanisms of ammonia tolerance in AML and validated the therapeutic efficacy of the screened drugs. RESULTS:A total of 6 core prognostic genes (TRH, TCIRG1, CXCL10, RUFY4, GPR12, CCR5) were screened out through machine learning. The BFReg-NN model predicted imiquimod and itraconazole as the optimal drug combination. The constructed risk model demonstrated moderate prognostic predictive ability. An abnormal "high ammonia and low TRH" state in AML was identified. Exogenous TRH treatment significantly reversed ammonia tolerance, suppressed AML cell proliferation, increased ROS accumulation, and promoted AML cell death. Combination treatment with imiquimod and itraconazole significantly inhibited AML cell proliferation and promoted apoptosis, with TRH/TRHR signaling playing an important role. Additional validation in THP-1 cells and TRHR knockdown experiments further supported the involvement of TRH/TRHR signaling. DISCUSSION:Collectively, AML cells demonstrate a state of high ammonia tolerance. Our findings suggest that the TRH-TRHR axis may serve as an ammonia metabolism-related checkpoint in AML and indicate that the imiquimod-itraconazole regimen represents a potential therapeutic strategy for targeting ammonia tolerance in AML. CONCLUSION:AML cells exhibit a state of high ammonia tolerance associated with reduced TRH expression. Our study suggested that TRH/TRHR signaling is involved in regulating ammonia tolerance in AML.
Osteosarcoma (OS) is the most common form of primary bone malignancy, characterized by the production of osteoid tissue and contributing significantly to cancer-related mortality in both pediatric and adult populations. The etiology of OS remains multifactorial, involving genetic predispositions, environmental exposures, and complex molecular alterations. Despite advances in surgery and chemotherapy, therapeutic outcomes remain suboptimal due to the high propensity for metastasis and chemoresistance. This review explores recent insights into the genomic landscape of OS, with a focus on the regulatory roles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) in tumor initiation, progression, and therapy resistance. We further examine emerging strategies that target these non-coding RNAs as potential therapeutic agents or biomarkers for diagnosis and prognosis. Ultimately, this review emphasizes the need for innovative RNA-based approaches to improve the clinical management and survival outcomes of osteosarcoma patients.
BACKGROUND:Extensive clinical evidence has identified metastasis-associated colon cancer 1 (MACC1) as a pivotal cancer-promoting gene that actively fuels the advancement of neoplasms. However, the upstream transcriptional regulators of MACC1 and the specific posttranscriptional mechanisms involving N6-methyladenosine (m6A) modification that govern its expression remain largely undefined. This study aims to elucidate the regulatory network controlling MACC1 expression and its impact on colorectal cancer (CRC) progression. METHODS:MACC1 expression and its potential regulators were systematically analyzed using public databases, including GEPIA, TCGA, and TIMER2, alongside clinical tissue samples and cell lines (SW480, HCT-116, and SW620). Functional experiments were conducted to assess cell viability, proliferation, invasion, and ferroptosis. These methodological approaches encompassed chromatin immunoprecipitation (ChIP), RNA immunoprecipitation (RIP), methylated RNA immunoprecipitation (MeRIP), as well as dual-luciferase reporter systems. Furthermore, in vivo validation was performed using a nude mouse xenograft model. RESULTS:MACC1 was significantly upregulated in CRC tissues and cell lines, and its high expression correlated with an unfavorable prognosis. Functional assays revealed that silencing MACC1 inhibited CRC cell proliferation and invasion while inducing ferroptosis. Mechanistically, RNA binding protein 15 (RBM15) was identified as a key m6A methyltransferase component that stabilized MACC1 mRNA in an insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1)- dependent manner. Furthermore, zinc finger and BTB domain-containing 33 (ZBTB33) was found to transcriptionally activate RBM15 by binding to its promoter region. Knockdown of RBM15 inhibited CRC cell invasion and proliferation and induced ferroptosis; these effects were notably reversed by MACC1 overexpression. Moreover, ZBTB33 silencing inhibited the key malignant phenotypes of CRC cells and induced ferroptosis by regulating RBM15. Further, RBM15 depletion suppressed tumor growth, which was attenuated by the restoration of MACC1. DISCUSSION:Our study unveils a novel ZBTB33/RBM15/MACC1 signaling axis that drives CRC progression. Clinically, these findings not only deepen the understanding of m6A-mediated posttranscriptional regulation in CRC but also identify this axis as a promising therapeutic target for overcoming ferroptosis resistance and improving patient outcomes. CONCLUSION:These findings uncover a novel ZBTB33/RBM15/MACC1 regulatory axis in CRC, where ZBTB33 transcriptionally activates RBM15 to enhance MACC1 mRNA stability, ultimately suppressing ferroptosis and promoting tumor progression.
INTRODUCTION:Osteoarthritis (OA) is a whole-joint disease involving coordinated changes in subchondral bone, Bone Marrow Mesenchymal Stem cells (BM-MSCs), and synovium. This study aimed to identify BM-MSC-associated and OA-related candidate biomarkers and evaluate their potential diagnostic and immune-related relevance. METHODS:The scRNA-seq dataset GSE147287 was used to construct an OA subchondral bonemarrow atlas, identify BM-MSC populations, perform BM-MSC sub-clustering, and derive BMMSC co-expression modules and hub genes using hdWGCNA. Three synovial transcriptomic datasets (GSE55457, GSE55235, and GSE55584) were integrated as the training cohort after datasetspecific log2 (expression + 1) transformation and ComBat correction, whereas GSE12021 was processed independently as an external validation cohort. BM-MSC hub genes were intersected with OA-related synovial DEGs and further prioritized using LASSO, SVM-RFE, and XGBoost. A combined four-gene model was constructed using Firth's penalized logistic regression. Diagnostic performance was evaluated by ROC analysis, cellular expression was validated in IL-1β-stimulated hBMSCs by qRT-PCR, and immune-cell and Hallmark pathway correlations were assessed using ssGSEA and Spearman analysis with Benjamini-Hochberg correction. RESULTS:The single-cell atlas contained nine major cell types, and BM-MSC sub-clustering identified four transcriptionally distinct subclusters. Cross-tissue integration yielded 35 BM-MSCassociated and OA-related candidate genes, from which EFEMP2, CTSO, SPRY1, and NFIC were selected. In the training cohort, the AUCs were 0.890 (95% CI, 0.792-0.989) for EFEMP2, 0.896 (95% CI, 0.802-0.990) for CTSO, 0.892 (95% CI, 0.797-0.987) for SPRY1, and 0.769 (95% CI, 0.630-0.908) for NFIC. In GSE12021, the corresponding AUCs were 0.867 (95% CI, 0.698-1.000), 0.922 (95% CI, 0.801-1.000), 0.922 (95% CI, 0.797-1.000), and 0.856 (95% CI, 0.674-1.000), respectively. The combined four-gene model achieved AUCs of 0.998 (0.993-1.000) in the training cohort and 1.000 (1.000-1.000) in GSE12021. qRT-PCR confirmed the upregulation of EFEMP2 and CTSO and the downregulation of SPRY1 and NFIC in IL-1β-stimulated hBMSCs. After Benjamini- Hochberg correction, no immune-cell or Hallmark pathway correlations remained statistically significant, although several moderate exploratory trends were observed. DISCUSSION:EFEMP2, CTSO, SPRY1, and NFIC represent BM-MSC-associated and OA-related candidate biomarkers. These findings provide a hypothesis-generating framework for characterizing OA-related stromal states and developing future tissue-fitness or patient-stratification tools, but further clinical and tissue-specific validation is required. CONCLUSION:EFEMP2, CTSO, SPRY1, and NFIC were identified as BM-MSC-associated and OArelated candidate biomarkers. These findings provide a hypothesis-generating framework for characterizing OA-related stromal states and developing future tissue-state assessment or patientstratification tools, although further tissue-specific and clinical validation is required.
Background: Biomanufacturing of adeno-associated virus (AAV) involves multiple processes. The most common approach is triple transfection (TT) of Human Embryonic Kidney 293 (HEK-293) cells with three plasmids: one providing the gene of interest (GOI plasmid, or cisplasmid), one providing the AAV Rep and Cap genes (RepCap plasmid, or trans-plasmid), and a helper plasmid providing critical adenoviral genes (Helper). Another method uses Herpes Simplex Virus (HSV) as a helper virus, in combination with HSV GOI and HSV RepCap plasmids, to produce AAVs, typically in HEK-293 cells. Objective: Using AAV9 as a model capsid, we aimed to determine whether there are differences in selected quality attributes of the final purified AAV9 product across manufacturing platforms. results: For all comparisons, each AAV9 product will be called AAV9-HSV or AAV-TT. It was shown that AAV9-HSV contained molecular weight protein impurities (p=0.0004, ****) and a lower full-to-empty ratio. Mass and %VP ratio differences for each AAV9 capsid were not significant. Methods: A range of biophysical characterization assays was used to assess the reproducibility of the following attributes: hydrodynamic radius, charge heterogeneity, full-to-empty ratio, purity, and molecular weight of the final purified AAV9 from each platform. Results: For all comparisons, each AAV9 product is designated as either AAV9-HSV or AAV9- TT. AAV9-HSV exhibited molecular weight protein impurities relative to AAV9-TT (p = 0.0004, ****) and a lower full-to-empty ratio. Differences in mass and VP ratio for each AAV9 capsid were not statistically significant. conclusion: Specifics to where those differences could have arisen during the manufacturing of each were not investigated and a single lot of each was used. Discussion: The biophysical characterization assays provided information indicating tight overall comparability between platforms, with some variability observed. Conclusions: A single lot of AAV9 from each process was used for all comparisons; a larger sample size is recommended for future validation. Functional assessments, including process steps during manufacturing and biological assays, were not performed and could be explored in future studies to further validate these exploratory findings.
Abstract: Diabetes causes several health risks, including cardiovascular disease, renal failure, neuropathy, and retinopathy. Traditional pharmacological techniques have concentrated on singletarget treatment, but they typically fail to address diabetes pathophysiology pathways. Diabetes disrupts complex signaling, gene expression, and metabolic networks, which our multi-target strategy can better manage. Network pharmacology, a novel systems biology method, targets several biochemical processes and components simultaneously for an effective treatment. It uses bioinformatics, genetics, and computer modeling to explain how the drug-target interactions and predict pharmacological effects on different disease pathways. This method has been used to implement biological networks to uncover therapeutic compounds that affect inflammation, oxidative stress, insulin resistance, and vascular dysfunction molecular targets. Berberine, curcumin, ginseng and many other botanicals can affect many pathways, treating diabetes' metabolic dysfunction and its effects. Network pharmacology helps in medication repurposing, combination therapy development and speeding successful treatments. Determining synergistic effects among drugs or natural ingredients can enhance diabetes treatment. Network pharmacology is intriguing, but it needs good clinical trials to prove its safety and usefulness. In conclusion, network pharmacology can create multi-target medicines to tackle the complex nature of diabetic and their complications, potentially improving and personalizing treatment.
Abstract: Alzheimer's disease (AD) represents a significant healthcare challenge, requiring innovative treatment strategies. This review examines gene therapy as a promising approach for targeting fundamental biological pathways involved in the development and progression of AD. Focusing on the genetic and molecular underpinnings of the disease, the paper highlights pathological indicators such as beta-amyloid plaques and neurofibrillary tangles. It explores the rationale for gene therapy, emphasizing the manipulation of genes implicated in amyloid processing, tau protein regulation, and neuroinflammation. The analysis critically evaluates the effectiveness of various gene therapy interventions in mitigating cognitive decline, reducing neurodegeneration, and altering disease progression. Furthermore, the long-term safety profiles and potential adverse effects associated with gene therapies are discussed, including immune responses and therapeutic limitations. The conclusion synthesizes current findings, identifies research gaps, and proposes future directions for the advancement of gene therapy as a viable and sustainable strategy for treating Alzheimer's disease.
Introduction/Objective: The tumor suppressor miR-30d-3p is upregulated under hypoxic conditions, suggesting a functional role in tumor progression. This study aimed to determine the association between miR-30d-3p and junction-mediating and regulatory protein (JMY) and to examine their effects on proliferation, cell cycle, migration, and apoptosis in A549 cells cultured under both normoxic and hypoxic conditions. Methods: Cell proliferation and migration were analyzed using real-time cell analysis (RTCA). Flow cytometry was employed to assess cell-cycle distribution and apoptosis. The expression levels of miR-30d-3p, JMY, and related genes under different oxygen conditions were determined using quantitative RT-PCR. Results: Under hypoxia, miR-30d-3p expression increased 6.1-fold. JMY mRNA expression also rose approximately twofold following miR-30d-3p inhibitor transfection under normoxia. The miR- 30d-3p mimic increased the G1 population (62% vs. 49.2% in controls) and reduced migration by 48.4% under normoxia, while also inducing apoptosis. Under hypoxia, the miR-30d-3p inhibitor caused a slight rise in sub-G1/G1 phases at 72 h and reduced proliferation by 56.9%. Discussion: miR-30d-3p exhibited oxygen-dependent effects, acting as a tumor suppressor under normoxia but showing altered behavior under hypoxia. Hypoxia-related HIF-1α stabilization and metabolic adaptation contributed to growth inhibition and modified cellular responses to miR-30d- 3p. Increased JMY levels following miR-30d-3p inhibition support a regulatory miR-30d- 3p/JMY/p53 axis influencing proliferation, cell cycle, and migration. Conclusion: These findings suggest that A549 cells are sensitive to changes in miR-30d-3p expression under normoxic and hypoxic conditions; however, its effects on cellular processes differ depending on oxygen availability. Thus, miR-30d-3p may represent a potential therapeutic target for non-small cell lung cancer (NSCLC) and could pave the way for innovative approaches to cancer diagnosis and treatment.
INTRODUCTION:Cardiovascular diseases continue to be the leading cause of death worldwide. Traditional medicines relieve symptoms and slow the advancement of the disease, but fail to fix genetic problems at their roots. Cardiovascular science has dramatically changed thanks to advancements in genome editing tools, such as CRISPR/Cas9 and its successor technologies. These types of genome editing tools enable researchers and physicians to precisely and programmatically manipulate specific genetic loci related to cardiovascular diseases, offering hope for developing new curative therapies. METHODS:This article is based on a complete review of peer-reviewed literature published between 2020 and 2025. A systematic search of databases (PubMed, Web of Science, Scopus, and others) for literature using the keywords (genome editing; CRISPR/Cas9; base editing; prime editing; cardiovascular disease; cardiomyopathy; atherosclerosis; etc.) was completed. RESULTS:CRISPR/Cas9 makes it easy and fast to create genetically modified cardiac model organisms to evaluate pathogenic variation. Using base editing is an effective way to perform precise single- nucleotide corrections, particularly with respect to PCSK9 targeting and its association with long-lasting reductions in LDL cholesterol levels in humans. Prime editing extends this capability to complex mutations, including RBM20 in dilated cardiomyopathy. Early-stage clinical trials targeting transthyretin amyloidosis demonstrate the feasibility of in vivo genome editing. Secondgeneration cardiotropic AAV vectors and lipid nanoparticles continue to improve cardiac delivery and safety profiles. DISCUSSION:Genome editing shifted cardiovascular research from associative genetics toward causal intervention. Next-generation editors reduce double-strand break-associated risks, enhancing clinical suitability. Still remaining challenges include efficient delivery in a tissue-specific manner, off-target effects, immunity, and ethical considerations related to permanent genomic modification. CONCLUSION:Genome editing is a paradigm-shifting development within the field of cardiology that promises a long-term genetic remedy. Yet further optimization and development within genome editing and its guidelines will be important for making such a paradigm shift successful.
INTRODUCTION:Rheumatoid Arthritis (RA) is a common autoimmune disease. The Basement Membrane (BM) plays a critical structural role in tissues such as the kidneys and joints, and is often implicated in immune-related diseases. This study aims to explore the complex interactions between RA and the BM, and to identify potential diagnostic biomarkers. METHODS:The data used in this study were sourced from the Gene Expression Omnibus (GEO) database. We screened Differentially Expressed Genes (DEGs) related to BM by comparing RA tissue with normal tissue. Consensus clustering analysis was performed based on the features of the BM in RA tissue samples. Functional enrichment analyses, including Gene Ontology (GO) and KEGG pathway analysis, were performed on genes common to the different clusters. Three machine learning algorithms were used to screen for biomarkers, including LASSO, Random Forest (RF), and Support Vector Machine Recursive Feature Elimination (SVM-RFE). The screening results were validated using the GSE77298 dataset and confirmed via qRT-PCR. In addition, molecular docking technology was applied to predict the binding potential between Schisandrin (SCH) and the candidate biomarkers SEL1L3 and SLAMF8. RESULTS:By integrating RA transcriptome data with BM-related genes, we identified two BMassociated molecular subtypes of RA, both of which exhibit distinct immune cell infiltration characteristics. By further implementing a combination of LASSO, RF, and SVM-RFE, SEL1L3 and SLAMF8 were identified as candidate diagnostic biomarkers. In the external validation set (GSE77298) and qRT-PCR experiments, both exhibited significant upregulation in RA tissue and excellent diagnostic efficacy. The AUC of SEL1L3 and SLAMF8 was 0.987 and 0.970, respectively, and molecular docking suggests that SCH binds stably to both. DISCUSSION:The research results indicate that molecular changes related to BM may play an important role in the pathogenesis of RA, particularly through immune regulation and tissue remodeling. Identifying different subtypes of BM-related RA highlights the heterogeneity of RA and may help improve disease classification and personalized diagnosis. SEL1L3 and SLAMF8 can serve as promising biomarkers for early RA detection and provide new insights into BM-related immune mechanisms. CONCLUSION:SEL1L3 and SLAMF8 are the first BM-associated RA diagnostic markers identified, providing new targets for early RA diagnosis and investigation of its molecular mechanisms.
INTRODUCTION:Myofibroblasts play a critical role in the progression of hepatocellular carcinoma (HCC), a major subtype of primary liver cancer. METHODS:Bulk RNA-seq data were analyzed to identify core genes of relevant cell subpopulations. Next, cell clustering was performed based on public scRNA-seq data of HCC. Using the R package CellChat, receptor-ligand communication networks between myofibroblasts and other cell subtypes were characterized. Hub genes within HCC myofibroblast subpopulations were screened via hdWGCNA. Subsequently, differentially expressed genes (DEGs) from the bulk analysis were intersected with these hub genes. Machine learning algorithms were employed to select key genes to construct a nomogram. Finally, correlations in immune cell infiltration were analyzed. RESULTS:Six major cell subpopulations were identified from the scRNA-seq data, with prominent crosstalk observed between myofibroblasts and hepatocytes. Using hdWGCNA, 10 myofibroblastassociated co-expression modules were obtained, five of which were identified as functionally key modules. By intersecting the module hub genes with HCC-related DEGs, 15 overlapping genes were obtained. From these, four key genes were ultimately selected by machine learning algorithms: plasmalemma vesicle-associated protein (PLVAP), retinol binding protein 7 (RBP7), NADH dehydrogenase (Ubiquinone) 1 Alpha subcomplex subunit 4-like 2 (NDUFA4L2), and tropomyosin 2 (Beta) (TPM2). A nomogram integrating 6 imaging-histological features and PLVAP expression exhibited robust prediction capacity. All gene expressions were positively correlated with the infiltration of regulatory T cells (Tregs) and macrophage M0 and negatively correlated with the infiltration of neutrophils and monocytes. DISCUSSION:Myofibroblasts participate in extensive intercellular crosstalk in the HCC microenvironment, suggesting the potential value of myofibroblast-related biomarkers in HCC therapy. CONCLUSION:In this study, hub genes associated with myofibroblast programs in HCC were identified using scRNA-seq and hdWGCNA.
INTRODUCTION:As an engulfment adapter for apoptotic clearance, GULP1 is related to tumor progression, but its role in ovarian cancer (OVCA) remains unclear. METHODS:GULP1 expression, copy number variations (CNVs), and their correlations were analyzed using datasets collected from The Cancer Genome Atlas (TCGA)-OVCA and the Gene Expression Profiling Interactive Analysis (GEPIA). Gene set enrichment analysis (GSEA), immune infiltration assessment, and drug sensitivity prediction were conducted to identify pathways enriched by GULP1 and to explore its potential association with drug sensitivity. The binding affinity of candidate drugs to GULP1 was evaluated through molecular docking. Finally, cellular assays were performed to explore the biological functions of GULP1 in OVCA cells. RESULTS:GULP1 was downregulated in OVCA, particularly in advanced stages. The GULP1 expression was associated with enrichment of hypoxia, EMT, angiogenesis, and TGFβ signaling, which were correlated with immune evasion. LFM-A13 demonstrated binding affinity for GULP1 (ΔG = -5.85 kcal/mol). Overexpression of GULP1 inhibited migration and invasion of A2780 and SK-OV-3 cells. Conversely, GULP1 knockdown exerted the opposite effects. DISCUSSION:This study explored the role of GULP1 in OVCA and analyzed its correlation with the immune microenvironment and key pathways. Molecular docking predicted LFM-A13 as a potential therapeutic agent for OVCA; however, its efficacy remains to be clinically verified. CONCLUSION:The current findings reveal GULP1 as a novel biomarker for OVCA progression and immune escape, highlighting its role in modulating the tumor microenvironment (TME). Targeting GULP1 with LFM-A13 may offer a potential strategy for OVCA precision therapy.
OBJECTIVE:To devise a bioactive surface functionalization approach for 3D-printed Ti- 6Al-4V scaffolds that influences macrophage polarization towards the pro-reparative M2 phenotype, therefore enhancing immunomodulation and facilitating good implant-soft tissue integration. METHODS:Porous Ti-6Al-4V scaffolds were produced by selective laser melting and then covered with a polydopamine-multi-element-doped hydroxyapatite-type I collagen (PDA-mHA-Col I) composite. The scaffolds' physicochemical characteristics were characterized. Murine RAW264.7 macrophages were cocultured with uncoated (T) or coated (TPMC) scaffolds. Cell viability, proliferation, apoptosis, adhesion, and polarization were assessed via CCK-8 tests, EdU staining, flow cytometry, phalloidin staining, ELISA, and qRT-PCR. The NF-κB, PI3K/Akt, and STAT6 signaling pathways were examined using Western blotting and targeted inhibitors. RESULTS:The PDA-mHA-Col I coating improved surface hydrophilicity while maintaining mechanical characteristics. XPS verified effective collagen immobilization, exhibiting a surface nitrogen concentration of 13.03%. The coating demonstrated stability after 7 days in PBS, retaining a nitrogen content of 11.74% and negligible titanium exposure. In comparison to the T group, the TPMC scaffold markedly enhanced macrophage adhesion, proliferation, and spreading, while diminishing apoptosis. It prompted M2 polarization, as shown by reduced expression of M1 markers (iNOS, CD86) and pro-inflammatory cytokines (TNF-α, IL-6), with elevated expression of M2 markers (Arg-1, CD206) and anti-inflammatory cytokines (IL-10, TGF-β1). The TPMC scaffold suppressed the phosphorylation of NF-κB p65 while simultaneously activating PI3K/Akt and STAT6 signaling pathways. The inhibition of PI3K or STAT6 somewhat mitigated the increase of M2 markers. DISCUSSION:The coating created a pro-healing milieu by inhibiting inflammatory signals and stimulating pro-reparative pathways, thus tackling a significant obstacle in oral and maxillofacial bone repair. CONCLUSIONS:The PDA-mHA-Col I composite coating facilitates macrophage M2 polarization by concurrently inhibiting NF-κB and activating PI3K/Akt/STAT6 signaling, presenting a viable immunomodulatory approach for oral and maxillofacial bone restoration.
INTRODUCTION:Osteoporosis (OP) and osteoarthritis (OA) are two skeletal disorders characterized by disrupted bone homeostasis. Transplantation of bone marrow mesenchymal stem cells (BM-MSCs) has emerged as a promising therapeutic strategy for both conditions; however, the precise molecular mechanisms mediating their beneficial effects remain poorly defined. METHODS:The GSE147287 dataset containing scRNA-seq data from BM-MSCs from OA and OP patients was obtained. Dimensionality reduction and cell clustering were performed using the Seurat R package, pseudotime trajectory analysis was carried out with the Monocle 2 package, and transcription factor (TF)-target gene regulatory networks were inferred using the GENIE3 R package. RT-qPCR quantified mRNA levels in a rat OP model, which was established via bilateral ovariectomy. RESULTS:Nine distinct BM-MSC subtypes were classified. OP samples had higher osteocytes and neutrophils and lower macrophages, chondroblasts, monocytes, and plasma B cells than OA samples. Chondroblasts (4 clusters), 2/3 linked to autophagy, may drive OA-to-OP progression. Osteoblasts (the largest OP-OA difference) showed reduced osteoblast differentiation, downregulated Wnt pathway genes, and upregulated ossification genes in late stages. In the rat model, CAT, CHRDL1, RUNX1, ETS1, FOXO3, and TAL1 were dysregulated. DISCUSSION:OP and OA exhibit distinct BM-MSC lineage heterogeneity. OA-to-OP progression involves enhanced oxidative phosphorylation and reduced autophagy. Downregulated RUNX1 (inhibiting NF-κB/IL-6) and Wnt pathway in OP were consistent with previous findings, showing the potential to serve as biomarkers for predicting disease progression and therapy response. CONCLUSION:This study preliminarily examined BM-MSC lineage heterogeneity in OP and OA, clarifying the dynamic development, transcriptional regulation, and biological functions of chondrocytes and osteoblasts in these two bone diseases.
BACKGROUND:Autism Spectrum Disorder (ASD) is a highly heterogeneous neurodevelopmental condition. Single-cell RNA sequencing (scRNA-seq) has revealed transcriptional disruptions, particularly in interneurons, yet their subtypes and molecular signatures remain poorly understood. METHODS:It was analyzed scRNA-seq data from the human Prefrontal Cortex (PFC). Key cell types were identified using Scissor and ROGUE methods, followed by secondary clustering for subtype annotation. A signature matrix was established using CIBERSORTx to deconvolute the bulk transcriptomes and estimate cell type-specific proportions. Differential subtype proportions between ASD and control samples were compared to identify key cell subtypes. Differentially Expressed Genes (DEGs) from both the key subtype and bulk data were intersected to determine subtypespecific biomarkers, which were further assessed via molecular docking. RESULTS:Interneurons were identified as the most heterogeneous cell population in ASD-affected PFC and were further categorized into five subtypes. A signature matrix was then developed with CIBERSORTx to reflect the proportion of each cell type and subtype. Among the cell subtypes, synaptic membrane-integrating interneurons (SMI-IN) emerged as the key subtypes, which exhibited notable distinctions between the ASD and control samples. Furthermore, five potential biomarkers (PRELID2, MYO1B, LRCH2, LIFR, and RERG) were identified from the SMI-IN subtype. Finally, quercetin and coumestrol were predicted as potential therapeutic compounds targeting these biomarkers. Nevertheless, as all findings were obtained via computational analysis, further cellular and clinical experiments are required to validate these identified biomarkers and candidate compounds. DISCUSSION:This study focused on interneurons and identified SMI-IN as a key cell subtype and its potential biomarkers (PRELID2, MYO1B, LRCH2, LIFR, and RERG). CONCLUSION:The present findings provided new insights for ASD intervention.
INTRODUCTION:A comprehensive study of Cell-In-Cell (CIC) structures in stomach adenocarcinoma (STAD) may facilitate the development of therapeutic strategies. METHODS:Enrichment analysis was conducted using ssGSEA. WGCNA was used to identify hub genes, and Differentially Expressed Genes (DEGs) were screened by the DESeq2 package. Gene selected by both LASSO regression (glmnet package) and SVM-RFE algorithms (e1071 package) were intersected to develop a diagnostic model for STAD using the rms package. Immune infiltration of STAD samples was analyzed using CIBERSORT and ESTIMATE algorithms. Single-cell data were processed by Seurat package. Cell subpopulations were identified using the FindClusters function, and their marker genes were subsequently determined by FindAllMarkers, followed by in vitro functional validation. RESULTS:Five genes (MSR1, PDGFRB, COL8A1, PLA2G7, and FCGR3A) with AUC > 0.8 were identified as potential biomarkers for STAD and combined into a five-gene diagnostic model. Immune infiltration analysis showed that these genes were associated with T-cell and macrophage infiltration. Among the ten cell types identified by single-cell analysis, the five biomarkers were found to be highly expressed specifically in macrophages and fibroblasts. In vitro functional assays confirmed that these markers were upregulated in HGC-27 and AGS cells, and that MSR1 regulated STAD cell proliferation, migration, and invasion. DISCUSSION:The five biomarkers, which showed a specifically high expression in macrophages and fibroblasts, were closely associated with heterotypic CIC formation. Further analysis suggested that these biomarkers contributed to STAD pathogenesis, potentially via immune, stromal, and metabolic crosstalk. These findings help clarify the interactions between CIC biology and the STAD tumorimmune microenvironment. CONCLUSIONS:The five biomarkers provide valuable insights for the early screening, diagnosis, and treatment of STAD.
INTRODUCTION:Members of the Homeobox (HOX) gene family, particularly HOXCs, may be implicated in the development and prognosis of prostate cancer (PCa), but the specific mechanisms remain unclear. METHODS:The clinical and transcriptomic data from TCGA-PRAD and GSE70770 were collected to examine the impact of HOXC family members on progression-free survival (PFS) in PCa. Meanwhile, the mechanisms of HOXC family members in PCa and their relationship with patients' prognosis were systematically investigated by performing survival analysis, enrichment analysis, and COX regression analysis. This study also developed a prognostic model. Additionally, a qPCR assay was conducted to determine the mRNA level of HOXC family members in PCa cells. RESULTS:Upregulated expressions of HOXC4, HOXC5, HOXC12, and HOXC13 in PCa tissues were found to be correlated with a worse prognosis. A prognostic model incorporating HOXC4 expression level, T stage, and Gleason score was constructed, exhibiting excellent performance in predicting 1-, 3-, and 5-year PFS (average AUC > 0.7). Enrichment analysis showed that HOXC4, which was highly expressed in PCa cells, may be involved in the progression and invasion of PCa through pathways such as oxidative phosphorylation, PLK1 signaling, cell cycle, and DNA methylation. Further, ssGSEA showed that HOXC4 may affect immune cell infiltration in PCa tumors. DISCUSSION:HOXC4 was related to immune cell infiltration and pathway activation in PCa and confirmed to be a risk factor for the cancer prognosis. However, the specific molecular mechanisms of HOXC4 in PCa development still require further investigation. CONCLUSION:The HOXC4-based prognostic model may be an effective tool for assessing the prognosis of PCa patients.
INTRODUCTION:Intrahepatic cholangiocarcinoma (iCCA) is characterized by heterogeneity and poor survival. It remains unclear how telomere maintenance programs influence the prognosis and immune microenvironment in iCCA, and clinically applicable, telomere‑anchored transcriptomic tools are currently lacking. METHODS:Transcriptomes and survival data from TCGA-CHOL, GSE107943, and E-MTAB-6389 cohorts were integrated (n=135). Telomere maintenance gene (TMG) scores were calculated using GSVA and subsequently used for WGCNA module identification. Functional enrichment was analyzed with clusterProfiler (FDR-adjusted P < 0.05). A prognostic model was constructed using univariate Cox and LASSO-Cox regression analyses, and validated by Kaplan-Meier (KM) curve and time-dependent ROC. Immune features were inferred by MCPcounter, CIBERSORT, and ssGSEA algorithms. Drug sensitivity was predicted by pRRophetic, and the resulting IC50 estimates were then correlated with the RiskScore. RESULTS:The TMG score was inversely correlated with the ESTIMATE score (Spearman ρ=-0.2439, P=0.0044). WGCNA identified a TMG-associated module enriched for cellcycle/ mitotic and microtubule functions. Three key TMGs (PTTG1, TSPYL5, PLLP) were integrated to develop a RiskScore that can consistently stratify overall survival (OS) in both the integrated set and all external cohorts, demonstrating a robust accuracy for 1-, 3-, and 5-year prognostic prediction. High-RiskScore tumors exhibited reduced immune infiltration across multiple deconvolution frameworks. The RiskScore was negatively correlated with predicted IC50 for several agents (e.g., pyrimethamine, GNF-2, NSC-87877, CGP-082996, KIN001-135), suggesting higher drug sensitivity in high-risk cases. DISCUSSION:We identified a three-gene, telomere-related risk score for iCCA, which can effectively predict patients' survival and distinguish immune-cold, high-proliferation phenotypes. Potential targeted drugs for high-risk patients were predicted and supported by mechanistic validation. CONCLUSION:A compact telomere-anchored three-gene RiskScore was developed to predict the prognosis, immune contexture, and therapy sensitivity for iCCA.
BACKGROUND:In advanced Prostate Cancer (PCa), metastatic spread and the inevitable emergence of enzalutamide resistance represent major clinical hurdles. Although apolipoprotein L3 (APOL3) is linked to oncogenesis, its precise mechanistic role in PCa progression and antiandrogen resistance, particularly its regulation of the STAT3-DAB2IP axis, remains largely unexplored. METHODS:Publicly available clinical datasets were analyzed to evaluate APOL3 expression and its prognostic value. The functional consequences of modulating APOL3 and DAB2IP levels were assessed using in vitro and in vivo PCa models, including an established enzalutamide-resistant cell line (C4-2R). Mechanistic insights into cellular proliferation, motility, angiogenesis, and drug response were derived from RNA sequencing, reciprocal co-immunoprecipitation (Co-IP), and dual-targeting phenotypic assays. RESULTS:APOL3 is significantly upregulated in PCa, strongly correlating with elevated Gleason scores, advanced stage, TP53 mutational status, and poor prognosis. Functionally, APOL3 promotes PCa proliferation, metastasis, and angiogenesis. Mechanistically, APOL3 sustains STAT3 phosphorylation and suppresses the tumor suppressor DAB2IP. Notably, Co-IP assays revealed a direct, bidirectional physical interaction between APOL3 and DAB2IP. Furthermore, we discovered that elevated APOL3 drives enzalutamide resistance not by enhancing classical Androgen Receptor (AR) activity, but by directly binding the Glucocorticoid Receptor (GR). This APOL3-GR complex activates a bypass signaling pathway entirely independent of the AR. While restoring DAB2IP resensitized cells to enzalutamide, it triggered a compensatory upregulation of APOL3. Consequently, concurrent APOL3 knockdown and DAB2IP overexpression yielded a powerful synergistic effect, profoundly dismantling malignant phenotypes, suppressing pro-metastatic markers (p-STAT3, VEGF, SNAIL, MMP2), and restoring enzalutamide sensitivity. DISCUSSION:These findings establish APOL3 as a central driver of prostate cancer metastasis and enzalutamide resistance. APOL3 drives these aggressive phenotypes by directly binding and suppressing DAB2IP to sustain oncogenic STAT3 signaling, and by activating an AR-independent bypass pathway through its physical interaction with the Glucocorticoid Receptor (GR). The enrichment of APOL3 in TP53-mutated and resistant tumors underscores its critical role in tumor plasticity. Consequently, synergistically co-targeting APOL3 alongside DAB2IP restoration represents a highly promising therapeutic strategy to overcome adaptive antiandrogen resistance and halt metastatic progression. CONCLUSION:APOL3 is a central driver of PCa aggressiveness and enzalutamide resistance, functioning via the direct modulation of the DAB2IP/STAT3 axis and the activation of the GR bypass pathway. Cotargeting APOL3 alongside DAB2IP restoration represents a highly promising, synergistic therapeutic strategy to circumvent adaptive resistance and halt metastatic progression in advanced castration-resistant prostate cancer.
