Background: Colorectal cancer (CRC), a prevalent malignancy of the gastrointestinal tract, ranks among the leading causes of cancer-related morbidity and mortality. Its clinical course is marked by high fatality and poor prognosis. Elucidating the mechanisms underlying CRC initiation and recurrence is therefore critical for identifying novel therapeutic targets. Methods: This study incorporated two datasets, TCGA-CRC and GSE17537. A total of 84 glutamine metabolism-related genes (GMRGs) were identified, and differential expression analysis was conducted using the TCGA-CRC dataset. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to determine gene modules most strongly associated with GMRG scores. Single-cell RNA sequencing (scRNA-seq) was utilized to characterize key cellular clusters and to identify differentially expressed genes (DEGs) between high and low glutamine metabolism (GM) groups. Overlapping GMRGs were visualized using the ggVennDiagram package in R. A CRC risk prediction model was developed through Cox proportional hazards and LASSO regression analyses, with performance evaluated by ROC curves. Cell type enrichment across 64 immune and stromal populations was assessed via xCell, and intergroup differences were tested using the Wilcoxon rank-sum test. TIDE scores were used to estimate immunotherapy responsiveness, while oncoPredict facilitated drug sensitivity profiling. PCOLCE2 expression in CRC was validated by RT-qPCR and Western blotting. Its functional role was examined through CCK-8 assays, invasion and migration tests, flow cytometry, and glutamate quantification. Results: ScRNA-seq analysis identified two key cell populations and 437 DEGs associated with GM status. WGCNA pinpointed the MEgreen module as most significantly correlated with GMRG scores, encompassing 1075 genes. Integration of DEGs, module genes, and GM-related DEGs yielded 60 candidate genes for downstream analysis. A GMRG-based prognostic model comprising six genes (SRPX, CXCL1, GPX3, PCOLCE2, CLU, SEMA3E) demonstrated strong predictive performance. Prognostic gene expression correlated with immune and stromal infiltration patterns, as indicated by Spearman correlation analysis. The high-risk group exhibited diminished predicted response to immunotherapy (TIDE scores). Drug sensitivity analysis identified four compounds-Dasatinib-51, WH-4-023-56, TWS-119-366, and LDN-193189-478-with elevated efficacy in high-risk CRC cases. PCOLCE2 expression was significantly reduced in CRC tissues. Functional assays revealed that PCOLCE2 knockdown did not substantially affect cell proliferation but significantly impaired invasion and migration in CRC cells, increased apoptosis, and suppressed both glutamine uptake and glutamate production-highlighting its oncogenic role. Conclusion: Six GMRGs-SRPX, CXCL1, GPX3, PCOLCE2, CLU, and SEMA3E-were identified as key components of a robust prognostic model for CRC. These findings offer valuable insights into CRC pathogenesis and potential therapeutic strategies. Notably, this study provides the first evidence implicating PCOLCE2 as a tumor-promoting factor in CRC.

BACKGROUND:The clinical comorbidity of diabetes mellitus (DM) and gastric cancer (GC) presents a significant healthcare challenge, as these two conditions often synergistically promote disease progression. Although Epimedium is known for its anti-tumor and metabolic regulatory properties, the precise molecular mechanism by which it intervenes in the DM-GC comorbidity remains poorly understood. METHODS:We integrated transcriptomic datasets of DM and GC to identify common differentially expressed genes (DEGs). Machine learning algorithms, enhanced by SHapley Additive exPlanations (SHAP) analysis, were utilized to isolate core genes within both disease contexts. These candidates were then intersected with the predicted targets of Epimedium. To refine the targets, single-cell RNA sequencing (scRNA-seq) analysis was performed to evaluate cell-specific expression patterns. Additionally, CCK-8, Western blot, and qPCR assays were conducted in human HGC-27 cells to validate the therapeutic efficacy of Epimedium in vitro. RESULTS:Eight common DEGs were identified, leading to the selection of GABRA1 and IGHG1 as primary hub genes. scRNA-seq analysis revealed that IGHG1 was significantly overexpressed in GC tissues compared to normal tissues, particularly within the B-cell population, whereas GABRA1 showed insufficient expression levels for further analysis. In cellular verification, HGC-27 cell viability was significantly inhibited by Epimedium in a dose-dependent manner, with a half-maximal inhibitory concentration (IC50) of 632.3 μg/ml. Furthermore, the expression of IGHG1 was markedly downregulated at both the transcriptional and translational levels following Epimedium treatment. CONCLUSIONS:Our findings identify IGHG1 as a critical molecular bridge in the DM-GC comorbidity. Epimedium exerts potent anti-tumor effects by targeting and downregulating IGHG1 expression. This study provides a novel therapeutic strategy and a robust theoretical basis for the treatment of patients suffering from concurrent diabetes and gastric cancer.

Colon adenocarcinoma (COAD) is a common malignancy with substantial morbidity and mortality, and the identification of new therapeutic targets remains essential for improving patient outcomes. In this study, we investigated SHC SH2-domain binding protein 1 (SHCBP1) in COAD through two complementary components with distinct evidentiary scopes. The first component comprised expression profiling, prognostic and methylation analyzes, bioinformatic characterization, and functional validation in vitro and in vivo. The second component comprised exploratory computational analyses, including predicted interaction network analysis and structure-based virtual screening. Public databases were used to analyze SHCBP1 expression, prognosis, and promoter methylation status. Co-expression and functional enrichment analyses were performed to explore the biological context of SHCBP1. In vitro and in vivo experiments were then conducted to evaluate the effects of SHCBP1 knockdown on tumor growth. SHCBP1 was significantly upregulated in COAD and was associated with poor patient prognosis. Promoter hypomethylation may contribute to its increased expression. Bioinformatic analyses suggested that SHCBP1 is associated with DNA replication and cell-cycle-related pathways. Experimental studies demonstrated that SHCBP1 knockdown suppressed cell proliferation and tumor growth. In the exploratory computational component, predicted interaction network analysis and virtual screening prioritized several in silico candidate interactions and two compounds with favorable predicted binding scores. These computational findings require independent biochemical and cellular validation. Overall, our findings suggest that SHCBP1 may represent a candidate biomarker associated with COAD proliferation and unfavorable prognosis, as well as a putative molecular target that warrants further validation.

Purpose: Inflammatory bowel disease (IBD) can severely disrupt intestinal health, leading to chronic inflammation. Betulinic acid (BHA) has demonstrated anti‐inflammatory and antioxidant properties. This study aims to explore the mechanism by which BHA alleviates colitis through the regulation of the key circadian gene REV‐ERBα (NR1D1) in a DSS‐induced colitis mouse model. Methods: The study first utilized in vivo experiments to establish a mouse model of colitis induced by DSS, investigating the effect of BHA in alleviating colitis through the regulation of NR1D1. Subsequently, an inflammatory model was established at the cellular level using CCD841 cells treated with 100 ng/mL LPS to explore the regulatory mechanism of BHA on colitis. Results: Our results indicate that oral administration of BHA effectively alleviates colitis symptoms, as shown by reduced disease activity index and histopathological scores. Notably, we found that BHA improves intestinal inflammation in DSS‐induced mice by downregulating VDAC1/NF‐κB. In addition, in vitro experiments demonstrate that the anti‐inflammatory effects of BHA are closely related to the NR1D1 gene. Conclusion: Our findings demonstrate the potential of BHA as a preventive and therapeutic agent for IBD.

This research aimed to determine genes associated with M1 TAMs (tumour-associated macrophages) and to develop an M1 TAMs-related signature for predicting GC (Gastric cancer)'s prognosis and therapeutic effect. Based on the GC dataset in TCGA, we constructed a prognostic signature using M1 TAMs-related genes and validated it using data from the GEO dataset. To evaluate the predictive power of the signature, the survival curves, ROC curves, Cox regression analysis, nomograms and calibration curves were constructed. Differences in immune infiltration, immunotherapy response, and chemotherapy sensitivity between the two risk groups were also analysed. Furthermore, by jointly using the string database and Cytoscape software, we identified the hub gene that differed between the two risk groups. In the end, the expression and function of the identified hub gene were validated using fresh tissue specimens and GC cell lines. A six-gene risk signature was developed based on M1 TAMs-related genes. Furthermore, the ROC curve, nomogram, calibration plot of the nomogram and Cox regression analysis confirmed M1 TAMs co-expressed genes have a strong predictive performance of the six-gene risk signature. Immune infiltration analysis and the TIDE algorithm indicated that low-risk GC patients may be more suitable for immunotherapy. Finally, fibronectin 1 (FN1), the hub gene with the highest degree of interaction between high- and low-risk groups, indicated a significant correlation with survival differences in GC. Functional analysis demonstrated that FN1 promotes GC cell proliferation, invasion, migration and EMT. The risk signature of six M1 TAMs co-expressed genes can be used to evaluate the prognosis and treatment efficacy of patients with GC, providing a basis for selecting new therapies for patients. The FN1 gene is the hub gene with predictive value in this signature, and it is upregulated in GC and functions as an oncogene.

Background and Objectives: This study aims to identify novel genetic targets in thyroid cancer (TC) by conducting a comprehensive analysis of microarray datasets and investigating the genetic factors that drive TC development. By uncovering these factors, we provide valuable insights for future research and treatment. Methods: We performed a meta-analysis of three TC datasets from the GEO database, including data from 100 healthy controls and 220 TC samples. These datasets were processed using R, fol-lowed by batch correction and differential expression analysis. We then conducted DEG, eQTL, MR, GSEA, GO, and KEGG analyses to identify gene-disease associations. Results: Validation of the target genes confirmed their significant roles in TC pathogenesis and progression. Specifically, gene expression analysis revealed 42 upregulated genes and 42 downregulated genes in TC samples. To explore the role of these genes further, we applied Mendelian randomization (MR) analysis, which identified four co-expressed genes-LAMP5, MTSS1, CEACAM1, and PRDX6-that were strongly associated with TC. These genes are involved in various biological processes, including macrophage activation and neural system modulation. Additionally, cell type-specific analysis revealed a unique immune cell landscape in TC, emphasizing the critical role of immune responses in disease progression. Notably, the MR findings were validated by variance analysis in the validation cohort, further strengthening the reliability of our results. Conclusion: This evidence not only validates our methodological approach but also reveals new mechanisms underlying TC pathogenesis, paving the way for targeted therapeutic interventions. Our findings offer significant insights into the molecular mechanisms of TC and highlight the potential for targeted therapies.

The cell proliferation protein 123 (CDC123) is involved in the synthesis of the eukaryotic initiation factor 2 (eIF2), which regulates eukaryotic translation. Although CDC123 is considered a candidate oncogene in breast cancer, its expression and role in Hepatocellular Carcinoma (HCC) remain unknown. Herein, we obtained the CDC123 RNA-seq and clinical prognostic data from the TCGA database. The mRNA level revealed that CDC123 was highly expressed in HCC patients, and Kaplan -Meier analysis implied better prognoses in HCC patients with low CDC123 expression (P < 0.001). The multivariate Cox analysis revealed that the CDC123 level was an independent prognostic factor (P < 0.001). We further confirmed a high CDC123 expression in HCC cell lines. Additionally, we found that CDC123 knockdown in HCC cell lines significantly inhibited cellular proliferation, invasion, and migration. Moreover, CDC123 was co -expressed with the CDK5 Regulatory Subunit -Associated Protein 1 Like 1 (CDKAL1), whose mRNA level was decreased after silencing CDC123. Therefore, we hypothesized that CDC123 promotes HCC progression by regulating CDKAL1.

BACKGROUND:Hepatocellular carcinoma (HCC) exhibits a high degree of invasiveness and is closely associated with rapid disease progression. Multiple lines of evidence indicate a strong correlation between anoikis resistance and tumor progression, invasion, and metastasis. Nevertheless, the classification of anoikis in HCC and the investigation of novel biological target mechanisms in this context continue to pose challenges, requiring further exploration. METHODS:Combined with HCC samples from TCGA, GEO and ICGC databases, cluster analysis was conducted on anoikis genes, revealing novel patterns among different subtypes. Significant gene analysis of different gene subtypes was performed using WCGNA. The anoikis prognostic risk model was established by Lasso-Cox. Go, KEGG, and GSEA were applied to investigate pathway enrichment primarily observed in risk groups. We compared the disparities in immune infiltration, TMB, tumor microenvironment (TME), and drug sensitivity between the two risk groups. RT-qPCR and Western blotting were performed to validate the expression levels of SLCO4C1 in HCC. The biological functions of SLCO4C1 in HCC cells were assessed through various experiments, including CCK8 assay, colony formation assay, invasion migration assay, wound healing assay, and flow cytometry analysis. RESULTS:HCC was divided into 2 anoikis subtypes, and the subtypeB had a better prognosis. An anoikis prognostic model based on 12 (COPZ2, ACTG2, IFI27, SPP1, EPO, SLCO4C1, RAB26, STC2, RAC3, NQO1, MYCN, HSPA1B) risk genes is important for survival and prognosis. Significant differences were observed in immune cell infiltration, TME, and drug sensitivity analysis between the risk groups. SLCO4C1 was downregulated in HCC. SLCO4C1 downregulation promoted the proliferation, invasion, migration, and apoptosis of HCC cells. The tumor-suppressive role of SLCO4C1 in HCC has been confirmed. CONCLUSIONS:Our study presents a novel anoikis classification method for HCC that reveals the association between anoikis features and HCC. The anoikis feature is a critical biomarker bridging tumor cell death and tumor immunity. In this study, we provided the first evidence of SLCO4C1 functioning as a tumor suppressor in HCC.

BackgroundThis study aims to develop a risk prediction model for multidrug-resistant bacterial and fungal infections in patients with gastrointestinal fistulas during the perioperative period.MethodsA retrospective cohort study was conducted at Anhui No. 2 Provincial People’s Hospital from January 2022 to July 2024. We analyzed the distribution, resistance patterns, and mechanisms of multidrug resistance. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. A nomogram was constructed based on these risk factors, and its performance was evaluated using calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA).ResultsA total of 266 patients were included, with 157 (59.02%) testing positive for multidrug-resistant infections. We isolated 329 pathogenic strains: 84 Gram-positive (25.53%), 215 Gram-negative (65.35%), and 30 fungal strains (9.11%). The most common isolate was Klebsiella pneumoniae (57 strains, 17.33%). Patients were divided into a training cohort (n = 177) and a validation cohort (n = 89). Multivariate analysis identified six key indicators: secondary surgery, length of hospital stay, preoperative white blood cell (WBC) count, preoperative neutrophil count, postoperative WBC count, and postoperative C-reactive protein (CRP) levels. The nomogram demonstrated excellent predictive ability, with an area under the curve (AUC) of 0.905 in the training cohort and 0.793 in the validation cohort. Calibration curves indicated high consistency between predicted probabilities and observed values. DCA confirmed the clinical utility of the nomogram.ConclusionOur study shows that multidrug-resistant infections in patients with gastrointestinal fistulas are predominantly caused by Gram-negative bacilli, especially carbapenem-resistant Enterobacteriaceae. Key risk factors include secondary surgery and various blood count parameters. The developed nomogram provides robust predictive accuracy, aiding healthcare providers in implementing targeted infection prevention strategies.

Background A two-way relationship exists between type 2 diabetes (T2DM) and human nonalcoholic steatohepatitis (NASH). Several diabetic NASH models have the disadvantages of long cycles or inconsistent with the actual incidence of human disease, which would be costly and time-consuming to investigate disease pathogenesis and develop drugs. Therefore, there is an urgent need to establish a diabetic NASH mouse model. Methods The combination between Fructose-palmitate-cholesterol diet (FPC) and Streptozotocin (STZ) (FPC+STZ) was used to construct diabetic NASH mouse model. The in vivo effects of silencing acid-sensitive Ion Channel 1a (ASIC1a) were examined with an adeno-associated virus 9 (AAV9) carrying ASIC1a short hairpin RNA (shRNA) in FPC+STZ model. Results The mice fed with FPC for 12 weeks had insulin resistance, hyperinsulinemia, lipid accumulation, and increased hepatic levels of inflammatory factors. However, it still did not develop remarkable liver fibrosis. Most interestingly, noticeable fibrotic scars were observed in the liver of mice from FPC+STZ group. Furthermore, insulin therapy significantly ameliorated FPC+STZ-induced NASH-related liver fibrosis, indicating that hyperglycemia is of great significance in NASH development and progression. Importantly, ASIC1a was found to be involved in the pathogenesis of diabetic NASH as demonstrated that silencing ASIC1a in HSCs significantly ameliorated FPC+STZ-induced NASH fibrosis. Mechanistically, ASIC1a interacted with Poly Adp-adenosine ribose polymerase (PARP1) to promote HSC activation by inducing autophagy. Conclusion A FPC diet combined with an injection of STZ induces a diabetic NASH mouse model in a shorter period. Targeting ASIC1a may provide a novel therapeutic target for the treatment of diabetic NASH.

A novel copper-dependent mode of death, cuproptosis, has been newly identified. This study developed a cuproptosis score (CS) based on the cuproptosis model to analyse the association of CS with prognosis, immune cell infiltration, drug sensitivity and immunotherapy response in hepatocellular carcinoma (HCC) patients. A typing model of cuproptosis was constructed based on the expression of 19 cuproptosis-related genes (CRGs). A total of 485 samples were divided into high scoring group (HSG) and low scoring group (LSG) according to CS, and the drug sensitivity and responsiveness to immunotherapy were evaluated by combining the immunophenotype score (IPS), oncoPredict, the tumour immune dysfunction and rejection (TIDE). The use of weighted gene coexpression network analysis (WGCNA) identified key prognostic genes for cuproptosis. Western blotting was used to detect the expression level of the key gene. The CRG key gene glutaminase (GLS) is highly expressed in HCC, and patients with high expression of GLS have a poorer prognosis. Furthermore, cell function experiments, such as proliferation, migration and invasion assays, confirmed that GLS knockdown significantly changed the incidence and progression of HCC. This study suggests that new biological markers associated with cuproptosis can be used in the clinical diagnosis of HCC patients to predict prognosis and therapeutic targets.

Background: Cuproptosis, as a recently discovered type of programmed cell death, occupies a very important role in hepatocellular carcinoma (HCC) and provides new methods for immunotherapy; however, the functions of cuproptosis in HCC are still unclear.Methods: We first analyzed the transcriptome data and clinical information of 526 HCC patients using multiple algorithms in R language and extensively described the copy number variation, prognostic and immune infiltration characteristics of cuproptosis related genes (CRGs). Then, the hub CRG related genes associated with prognosis through LASSO and Cox regression analyses and constructed a prognostic prediction model including multiple molecular markers and clinicopathological parameters through training cohorts, then this model was verified by test cohorts. On the basis of the model, the clinicopathological indicators, immune infiltration and tumor microenvironment characteristics of HCC patients were further explored via bioinformation analysis. Then, We further explored the key gene biological function by single-cell analysis, cell viability and transwell experiments. Meantime, we also explored the molecular docking of the hub genes.Results: We have screened 5 hub genes associated with HCC prognosis and constructed a prognosis prediction scoring model. And the model results showed that patients in the high-risk group had poor prognosis and the expression levels of multiple immune markers, including PD-L1, CD276 and CTLA4, were higher than those patients in the low-risk group. We found a significant correlation between risk score and M0 macrophages and memory CD4+ T cells. And the single-cell analysis and molecular experiments showed that BEX1 were higher expressed in HCC tissues and deletion inhibited the proliferation, invasion and migration and EMT pathway of HCC cells. Finally, it was observed that BEX1 could bind to sorafenib to form a stable conformation.Conclusion: The study not only revealed the multiomics characteristics of CRGs in HCC but also constructed a new high-accuracy prognostic prediction model. Meanwhile, BEX1 were also identified as hub genes that can mediate the cuproptosis of hepatocytes as potential therapeutic targets for HCC.

Chronic alcohol consumption is a major risk factor for alcoholic steatohepatitis (ASH). Previous studies have shown that direct injury of hepatocytes is the key factor in its occurrence and development. However, our study shows that the role of Kupffer cells in ASH cannot be ignored. We isolated Kupffer cells from the livers of ASH mice and found that alcohol consumption induced Kupffer cell pyroptosis and increased the release of interleukin‐1β (IL‐1β). Furthermore, we screened the related m6A enzyme methyltransferase‐like 3 (METTL3) from liver Kupffer cells, and found that silencing METTL3 alleviated inflammatory cytokine eruption by Kupffer cell pyroptosis in ASH mice. In vitro, we silenced METTL3 with lentivirus in BMDMs and RAW264.7 cells and confirmed that METTL3 could reduce pyroptosis by influencing the splicing of pri‐miR‐34A. Together, our results revealed a critical role of KC pyroptosis in ASH and highlighted the mechanism by which METLL3 relieves cell pyroptosis, which could be a promising therapeutic strategy for ASH.

BACKGROUND:Macrophage infiltration in the tumor microenvironment participates in the regulation of tumor progression. Previous studies have found that Notch signaling pathway is involved in regulating the progression of colorectal cancer (CRC), however, the specific mechanism is still unclear.METHODS:The correlation between Notch signaling pathway and macrophage infiltration was investigated in TCGA database and verified in clinical samples of patients with CRC using immunohistochemistry. Gene Set Enrichment Analysis was used to find out genes related to Notch3 expression. Colony formation assay, and flow cytometry were utilized to test tumor growth and immune cell infiltration in vitro and in vivo.RESULTS:Using bioinformatics analysis and clinical sample validation, we found that Notch3 was highly expressed in colon tumor tissues compared to adjacent normal tissues, and it participated in regulating the recruitment of macrophages to the tumor microenvironment. Furthermore, we found that the Notch3 expression was positively correlated with the expression of macrophage recruitment-related cytokines in colon tumor tissues. Finally, we demonstrated that depletion of Notch3 had no significant effect on the growth of colon tumor cells in vitro, while, attenuated the growth of colon cancer tumors in vivo. Simultaneous, immunosuppressive cells, macrophages and myeloid-derived suppressor cell (MDSC) infiltration were dramatically reduced in the tumor microenvironment.CONCLUSION:Our study illustrated that Notch3 could facilitate the progression of CRC by increasing the infiltration of macrophages and MDSCs to promote the immunosuppressive tumor microenvironment. Targeting Notch3 specifically is a potentially effective treatment for CRC.

Background:Cellular senescence occurs throughout life and can play beneficial roles in a variety of physiological processes, including embryonic development, tissue repair, and tumor suppression. However, the relationship between cellular senescence-related genes (CSRGs) and immunotherapy in esophageal carcinoma (ECa) remains poorly defined.Methods:The data set used in the analysis was retrieved from TCGA (Research Resource Identifier (RRID): SCR_003193), GEO (RRID: SCR_005012), and CellAge databases. Data processing, statistical analysis, and diagram formation were conducted in R software (RRID: SCR_001905) and GraphPad Prism (RRID: SCR_002798). Based on CSRGs, we used the TCGA database to construct a prognostic signature for ECa and then validated it in the GEO database. The predictive efficiency of the signature was evaluated using receiver operating characteristic (ROC) curves, Cox regression analysis, nomogram, and calibration curves. According to the median risk score derived from CSRGs, patients with ECa were divided into high- and low-risk groups. Immune infiltration and immunotherapy were also analyzed between the two risk groups. Finally, the hub genes of the differences between the two risk groups were identified by the STRING (RRID: SCR_005223) database and Cytoscape (RRID: SCR_003032) software.Results:A six-gene risk signature (DEK, RUNX1, SMARCA4, SREBF1, TERT, and TOP1) was constructed in the TCGA database. Patients in the high-risk group had a worse overall survival (OS) was disclosed by survival analysis. As expected, the signature presented equally prognostic significance in the GSE53624 cohort. Next, the Area Under ROC Curve (AUC=0.854) and multivariate Cox regression analysis (HR=3.381, 2.073-5.514, P<0.001) also proved that the risk signature has a high predictive ability. Furthermore, we can more accurately predict the prognosis of patients with ECa by nomogram constructed by risk score. The result of the TIDE algorithm showed that ECa patients in the high-risk group had a greater possibility of immune escape. At last, a total of ten hub genes (APOA1, MUC5AC, GC, APOA4, AMBP, FABP1, APOA2, SOX2, MUC8, MUC17) between two risk groups with the highest interaction degrees were identified. By further analysis, four hub genes (APOA4, AMBP, FABP1, and APOA2) were related to the survival differences of ECa.Conclusions:Our study reveals comprehensive clues that a novel signature based on CSRGs may provide reliable prognosis prediction and insight into new therapy for patients with ECa.

A new mode of cell death, disulfidptosis, has been discovered. Clinical prognostic significance of disulfidptosis related pattern in hepatocellular carcinoma(HCC). In this study, a risk score model was established based on disulfidptosis model to analyze the role of risk score in clinical prognosis, immune cell infiltration, drug sensitivity and immunotherapy response. Disulfidptosis subtype were constructed based on the transcriptional profiles of 15 disulfidptosis-related genes(DRGs). All 601 samples were defined as high risk group(HRG) and low risk group(LRG) based on the disulfidptosis risk score. Drug sensitivity and response to immunotherapy were calculated by immunophenotypic score(IPS), tumor prediction, tumor immune dysfunction and rejection(TIDE). RT-qPCR was used to determine the mRNA level of disulfidptosis prognostic gene. Risk groups was identified as potential predictors of immune cell infiltration, drug sensitivity, and immunotherapy responsiveness. HRG may benefit from immunotherapy. Classification is very effective in predicting the prognosis and therapeutic effect of patients, and provides a reference for accurate individualized treatment. This study suggests that new biomarkers related to Disulfidptosis can be used in clinical diagnosis of liver cancer to predict prognosis and treatment targets.

BACKGROUND:miR-29-3p, an important tumor suppressor, with inhibitory effects in multiple cancers that have been studied. Its exact molecular function is in HCC, however, still not been explored clearly. The purpose of our study is to make certain how miR-29c-3p affects HCC through TPX2.MATERIALS AND METHODS:Expression profile data of miR-29c-3p and TPX2 were acquired and downloaded from the TCGA database, and the respective differential expression was verified by qPCR and immunohistochemistry. The StarBase and dual luciferase reporter confirmed TPX2 targeting miR-29c-3p. Their effects on the biological functions of Hep3B and HepG2 were investigated by cellular assays.RESULTS:miR-29-3p was found to be significantly down-regulated in HCC, and the miR-29-3p low expression group had a poor prognosis. Overexpression of miR-29-3p was detrimental to invasion and migration ability of HCC cells and promoted their apoptosis. We identified miR-29c-3p targeting TPX2 by predictive analysis. TPX2 was significantly upregulated in HCC, and patients with high TPX2 expression had a poor prognosis. TPX2 knockdown partially counteracted the promoting effect of miR-29-3p inhibition on hepatocellular carcinoma cells, and its effect on hepatocellular carcinoma cell biology was similar to miR-29c-3p overexpression.CONCLUSION:miR-29c, a key gene regulating HCC, is lowly expressed in HCC, its overexpression can remarkably inhibit the biological function of tumor cells. miR-29c can perform this function by regulating the expression of TPX2.

Hepatic stellate cells (HSCs) serve a pivotal role in the formation and degradation of the extracellular matrix during liver fibrosis. Inonotsuoxide B is a tetracyclic triterpenoid that can be extracted from Inonotus obliquus and has been previously reported to inhibit the growth of liver and gastric cancer cells. However, its effect on liver fibrosis remain poorly understood. Therefore, in the present study, the potential antiproliferative effects of inonotsuoxide B on HSCs was investigated. Initially, cells were divided into the following five groups: Control; platelet-derived growth factor (PDGF)-BB (10 ng/ml); and PDGF-BB + inonotsuoxide B (5, 10 and 20 µg/ml) groups. Inonotsuoxide B treatment (5, 10 and 20 µg/ml) was revealed to reverse PDGF-BB-induced HSC proliferation. Furthermore, the protein expression of α-smooth-muscle actin (α-SMA) and type I collagen was significantly decreased in the inonotsuoxide B (10 and 20 µg/ml) groups compared with the PDGF-BB group. Inonotsuoxide B (5, 10 and 20 µg/ml) was also revealed to suppress PDGF-BB-induced α-SMA mRNA expression and activation of the PI3K/AKT and ERK signaling pathways in HSCs. These findings suggest that inonotsuoxide B suppresses the proliferation and activation of HSCs by inhibiting the PI3K/AKT and ERK1/2 signaling pathways.

Background: Owing to the heterogeneity displayed by hepatocellular carcinoma (HCC) and the complexity of tumor microenvironment (TME), it is noted that the long-term effectiveness of the cancer therapy poses a severe clinical challenge. Hence, it is essential to categorize and alter the treatment intervention decisions for these tumors. Materials and methods: “ConsensusClusterPlus” tool was used for developing a secure molecular classification system that was based on the cuproptosis-linked gene expression. Furthermore, all clinical properties, pathway characteristics, genomic changes, and immune characteristics of different cell types involved in the immune pathways were also assessed. Univariate Cox regression and the least absolute shrinkage and selection operator (Lasso) analyses were used for designing the prognostic risk model associated with cuproptosis. Results: Three cuproptosis-linked subtypes (clust1, clust2, and clust3) were detected. Out of these, Clust3 showed the worst prognosis, followed by clust2, while Clust1 showed the best prognosis. Three subtypes had significantly different enrichment in pathways related to Tricarboxylic Acid (TCA) cycle, cell cycle, and cell senescence (p < 0.01). The clust3 subtype with poor prognosis had a low “ImmuneScore” and low immune cell infiltration, and the three subtypes had significant differences in the antigen processing and presentation pathway of the macrophages. Clust1 had a low TIDE score and was sensitive to immunotherapy. Then, according to the prognosis-related genes of cuproptosis, a prognosis risk model related to cuproptosis was constructed, containing seven genes (KIF2C, PTTG1, CENPM, CDC20, CYP2C9, SFN, and CFHR3). “High” group had a higher TIDE score compared to the TIDE score value shown by the “Low” group, which benefited less from immunotherapy, whereas the “High” group patients were more sensitive to the conventional drugs. Finally, the prognosis risk model related to cuproptosis was combined with clinical pathological characteristics to further improve the prognostic model and survival prediction. Conclusion: Three new molecular subgroups based on cuproptosis-linked genes were revealed, and a cuproptosis-related prognostic risk model comprising seven genes was established in this study, which could assist in predicting the prognosis and identifying the patients benefit from immunotherapy.

Abstract Background Pyroptosis-related long noncoding RNAs (lncRNAs) (PRLs) are closely related to gastric cancer (GC). However, However, the mechanism of its role in GC has not been elaborated. This study deeply analyzed the potential role of PRL in GC. Methods A PRLs coexpression network was constructed via GC data from the TCGA dataset. Cox analysis was used to determine the prognosis related PRLs. QRT–PCR was used for quantitative verification. LASSO analysis and multivariate Cox analysis were used to construct the prognosis model of PRLs and calculate the risk score of each sample. The clinical characteristics, prognosis and tumor microenvironment (TME) of different risk groups were analyzed. Finally, we constructed a ceRNA network of lncRNA miRNA/mRNA and five histone modification modes (H3K27ac, H3K4me1, H3K17me3, H3K4me3, and H3K9me3). Results We obtained seven PRLs and constructed a prognostic model. In addition, we also drew a highly accurate nomogram to predict the prognosis of GC. The expression of lncRNAs AP000695.1 and AC087301.1 was significantly different between GC tissues and normal tissues. The immune function and TME also changed in different risk groups. We found the sub-networks of miRNAs and target genes related to AP000695.1 and AC243964.3. And we also found that the AC007277.1 enhancer region H3K27ac, H3K4me1, H3K4me3 levels increased. Conclusion This study revealed the clinical features, prognosis and tumor microenvironment of PRL in gastric cancer, and further explored its potential role in GC. This study revealed the clinical characteristics, prognosis and tumor microenvironment of PRLs in GC. The potential role in GC was discussed, which provided a new theoretical basis and ideas for immunotherapy of GC.