Unveiling the therapeutic potential and leukemia risk of PD-166866 in sepsis via an integrated computational-experimental strategy.

Ferritin heavy chain 1 (FTH1) is abnormally expressed in various cancers, but its role and mechanism in endometrial cancer (EC) remain unclear. This study aims to explore the clinical significance, biological functions and potential inhibitor of FTH1 in EC. The expression, prognosis and clinical correlation of FTH1 in EC were analyzed using TIMER, GEO, kaplan-meier plotter and UALCAN databases. Virtual screening and molecular docking were conducted for identifying potential inhibitors of FTH1. In vitro experiments were conducted using human EC cells HEC-1A and RL95-2. Cell proliferation, cell cycle and apoptosis were detected by CCK-8 assay and flow cytometry. The level of reactive oxygen species (ROS) was detected by using the DCFH-DA probe. The levels of malondialdehyde (MDA) and glutathione (GSH) were detected using the corresponding test kits. Western blot was used to detect the expression level of FTH1, AKT and p-AKT. FTH1 was highly expressed in EC tissues and was associated with a shorter overall survival time of patients. Functional enrichment analysis revealed that FTH1 was mainly involved in the iron homeostasis and ferroptosis pathways. FTH1 knockdown inhibits the proliferation of EC cells, induces cell cycle arrest at the G0/G1 phase and triggers cell apoptosis. In EC cells with FTH1 knockdown, the levels of ROS and MDA were significantly increased, accompanied by a decrease in GSH levels. Furthermore, morin had a high binding affinity with FTH1, which also inhibited the malignant phenotypes of EC cells. Morin triggered ferroptosis of EC cells by down-regulating FTH1 expression and inhibiting the PI3K/AKT pathway. FTH1 is a potential prognostic biomarker and therapeutic target for EC. Morin induces ferroptosis of EC cells by regulating FTH1-PI3K/AKT axis, providing a new candidate drug and theoretical basis for the treatment of EC.

Ovarian Cancer is a leading cause of mortality among women globally, primarily due to lack of specific and sensitive early-stage diagnostic tools. This study aims to identify hub genes associated with recurrent, late-stage, and metastatic tumors as potential prognostic biomarkers and drug targets. Gene expression data from eight National Center for Biotechnology Information (NCBI)-Gene Expression Omnibus (GEO) datasets were categorized by recurrence, tumor-stage, and metastasis. Differential gene expression and enrichment analyses were performed. Hub genes were identified by protein-protein interaction networks and validated by the University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), GEPIA2, pROC, and Kaplan-Meier plotter databases. Genetic alterations, immune cell infiltration, miRNA prediction, and drug-gene interactions were assessed using cBioPortal, CIBERSORTx, Encyclopedia of RNA Interactomes (ENCORI), and Drug-Gene Interaction Database (DGIdb), respectively. Eight hub genes (FN1, COL1A1, COL1A2, COL3A1, POSTN, LUM, IGF1, and CXCL8) were identified, with COL1A2 common across all tumor categories. Note that 19.6% of cases showed mutations in these genes, primarily COL3A1. Overexpression of most hub genes and reduced expression of CXCL8 correlated with worse survival outcomes. COL1A1 and FN1 showed strong diagnostic ability. Late-stage tumors showed elevated M2 macrophages and neutrophils. hsa-miR-29a-3p, hsa-miR-29b-3p, and hsa-miR-29c-3p were identified as the most interactive miRNAs. Ocriplasmin and pamidronate were identified as potential therapeutics. Our findings highlight the therapeutic relevance of these hub genes and identify them as potential drug targets and prognostic biomarkers in ovarian cancer.

Paeoniflorigenone (PAG) is a bioactive compound found in the root of moutan cortex. It has demonstrated anti-cancer effects, although the specific mechanism of action remains unclear. The objective of this study was to investigate the pharmacological mechanisms of PAG in the treatment of bladder cancer using transcriptomics and molecular docking. PAG-associated targets were gathered using SuperPred, SEA, SwissTargetPrediction, and PharmMapper. Bladder cancer-related targets were obtained from TCGA databases. The intersection of drug-disease targets was determined using the Venny tool. Metascape database was employed for GO and KEGG enrichment analysis of the common targets in drug-disease interaction. The STRING database and Cytoscape 3.9.0 were utilized to construct a PPI network of the overlapping targets. Molecular docking analysis was performed using AutoDockTools. Further analysis of the core targets was carried out using TCGA, HPA, Kaplan-Meier Plotter, and TIMER databases. A total of 50 potential targets for the treatment of bladder cancer by PAG were found, and among them, MMP1, MMP7, MMP9, MMP13, MMP14, JUN, TGFBR2, PRSS1, and TOP2A were determined as the core targets. KEGG and GO analysis results indicated that PAG treatment primarily involves response to oxidative stress, MAPK signaling pathway, and IL-17 signaling pathway in bladder cancer. Molecular docking results demonstrated that the binding energies between PAG and the core targets were all below - 5kJ/mol, indicating a spontaneous binding of PAG to the core targets. These findings were further confirmed through analysis of mRNA expression levels, protein expression levels, prognostic values, and immune infiltration. It was initially discovered that PAG exerts its therapeutic effects on bladder cancer by targeting multiple pathways and multiple targets. This finding will enhance our comprehension of the potential mechanism by which PAG combats bladder cancer, and it will serve as a theoretical foundation for future research endeavors.

NFYA transcriptionally activates GPX4 inhibiting ferroptosis in colorectal cancer.

Renal cell carcinoma (RCC) is the most prevalent form of renal malignancy accounting for around 3% of all adult malignancies. Although new targeted medications are continually being developed, they are not able to treat all patients. Thus, a comprehensive investigation of the mode of progression and biomolecular mechanism of renal cancer is a need to identify its novel targets for better diagnostics and treatment strategies. We aim to identify the potential biomarkers of renal cancer, infer the cellular processes and pathways influenced by renal cancer, using in silico methods. We analysed three profiles of gene expression (GSE168845, GSE66270 and GSE781) from Gene Expression Omnibus (GEO) database to investigate possible treatment targets for RCC. Differentially expressed genes (DEGs) between RC and normal renal tissues were found using the GEO2R web program. Gene Ontology (GO) and KEGG pathway enrichment analysis were carried out using the Enrichr web-based tool. The DEGs were then organized into a protein-protein network using the STRING database tool. From an interaction network of multiple genes, we filtered the critical hub genes using the CytoHubba application of Cytoscape. To verify the predictive-value of the hub genes, we performed survival-analysis using a renal cancer database by plotting the Kaplan-Meier plots. We identified a set of 30 DEGs (24 upregulated genes and 6 downregulated genes). Most of the DEGs were active in signaling and transportation mechanisms. The PPI network and Cytohubba results revealed ten critical hub genes including UMOD, SLC34A1, SLC22A6, SLC12A1, RHCG, NPHS2, KCNJ1, G6PC, FABP1 and ALB. The Kaplan-Meier plotter database confirmed that few genes enhanced the chances of survival, while others decreased them and some genes had no effect on RC patient survival. The identification of DEGs and the enrichment of their biological functions/key pathways offers more precise information about RC and allows identification of crucial biomarkers which will aid future research and help in efficient therapeutic strategies.

Succinylation has been shown to promote lung cancer development, but its mechanism remains incompletely understood. KAT2A, a succinyltransferase, acts as an oncogene in multiple cancers, but its role in mediating lung cancer progression is unclear. This study aimed to investigate the mechanism by which KAT2A regulates lung cancer progression via succinylation. KAT2A expression was analyzed using UALCAN, GEPIA, and Kaplan-Meier Plotter databases, and validated in lung cancer cell lines and patient-derived tissues. Quantitative real-time PCR, Cell Counting Kit-8 (CCK-8), EdU staining, and flow cytometry were performed to assess KAT2A's role in lung cancer cell proliferation and apoptosis. KAT2A's target proteins were predicted using LinkedOmics and STRING databases. Additionally, invivo xenograft models were established to evaluate the effect of KAT2A knockdown on tumor growth. Results indicated that KAT2A expression was significantly elevated in lung cancer cells and tissues and was associated with poor prognosis. KAT2A knockdown inhibited proliferation and promoted apoptosis in lung cancer cells, whereas MYC overexpression reversed these effects. Mechanistically, KAT2A knockdown downregulated MYC by reducing succinylation at K370 and K386 residues. Mutation of these sites abrogated the proliferative effect of MYC overexpression and restored apoptotic activity. Furthermore, invivo experiments demonstrated that KAT2A knockdown inhibited tumor growth and reduced MYC succinylation. Our findings demonstrate that KAT2A functions as an oncogene in lung cancer by enhancing MYC succinylation. This study identifies KAT2A as a promising therapeutic target for lung cancer.

AimAsporin (ASPN) was shown to be highly expressed in gastric cancer. The purpose of this study was to investigate the relationship between ASPN expression and invasion, migration, macrophage M2 polarization and prognosis of gastric cancer.MethodsASPN expression in tumor and normal tissues was analyzed using TIMER, GEPIA, and HPA databases. Its clinical prognostic value was evaluated using Kaplan-Meier plotter and GEPIA databases. The association of ASPN with clinicopathological parameters was explored using the cBioPortal datasets. The TIMER and Aclbi databases were used to assess the relationship between ASPN and tumor immune infiltration, and TIMER and GEPIA were used to analyze correlations with immune infiltrate gene markers. Immunohistochemistry detected ASPN protein in 436 gastric cancer tissues and analyzed its correlation with clinicopathological parameters and prognosis. Transwell assays were used to assess ASPN's impact of ASPNs on the migration and invasion of HGC27 and AGS gastric cancer cells. GSEA was used to investigate cellular mechanisms associated with ASPN expression. The possible regulatory pathways of ASPN that promote M2 macrophage polarization were analyzed using RNA-seq.ResultsASPN expression was elevated in 51.8% of gastric cancer cases and was correlated with poor survival rates, higher tumor stage, and histologic grade. It is significantly linked to the presence of various immune cells and markers, particularly monocytes/macrophages and regulatory T (Treg) cells. High ASPN expression is associated with multiple cancer-related pathways. ASPN upregulation is linked to the Lauren classification, differentiation, invasion depth, lymph node and distant metastasis, and TNM staging. Patients with low ASPN expression had a 5-year survival rate of 53.8% compared to 28.8% for those with high expression. Overexpression of ASPN upregulates migration and invasion of AGS and HGC-27 cells. TIMER database analysis indicated that ASPN was positively correlated with M2 macrophage markers (such as CD163) but not with M1 markers. ASPN upregulation in gastric cancer is closely associated with M2 macrophage polarization and a poor prognosis. KEGG pathway analysis revealed that increased ASPN levels are significantly associated with the neutrophil extracellular trap (NETs) pathway.ConclusionsASPN is highly expressed in gastric cancer and is associated with poor prognosis by promoting invasion and migration and inducing macrophage M2 polarization.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12885-025-15196-4.

BackgroundCCR5 is a chemokine receptor involved in immune regulation and tumor progression. Its role in predicting therapy response in breast cancer remains unclear.MethodsWe evaluated CCR5 protein expression in a clinical cohort of 66 breast cancer patients treated with NAC, assessing its association with pathological complete response (pCR). Prognostic relevance was validated in the Kaplan–Meier Plotter database. We further investigated CCR5’s predictive value in a cohort receiving chemo-immunotherapy (GSE173839). Immune-related transcriptional features were assessed via GSEA and deconvolution analysis. The structural impact of the V131I CCR5 variant was explored using AlphaFold modeling, molecular dynamics simulations, and AI-based protein stability prediction.ResultsHigh CCR5 expression was associated with reduced pCR rates in the NAC cohort (OR = 0.06, P = 0.012) and with poorer RFS, particularly in HER2-negative subtypes (P = 0.009). In contrast, CCR5-high tumors in the chemo-immunotherapy cohort exhibited significantly higher pCR rates (OR = 2.5, P = 0.046), suggesting a suppressed yet immune-infiltrated microenvironment potentially responsive to immune reactivation. GSEA analysis and immune cell infiltration profiling indicate a coexistence of immune activation and immunosuppression. Structural modeling of the V131I variant suggested increased conformational flexibility and reduced stability of CCR5, implying a potential sensitivity to subtle structural perturbations.ConclusionOur study supports a dual regulatory hypothesis, in which CCR5 expression may influence immune dynamics and therapeutic response, while its structural stability may serve as a potential modulatory factor. This hypothesis-generating observation suggests that CCR5 could represent a potential prognostic and predictive biomarker, particularly in NAC-refractory or immune-inflamed breast cancers.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12672-025-04189-1.

BackgroundThe clinicopathologic and prognostic significance of T-cell lymphoma invasion and metastasis 2 (TIAM2) in hepatocellular carcinoma (HCC) remains unclear.MethodsTIAM2 expression was detected immunohistochemically in matched HCC and adjacent liver (AL) specimens from 168 patients with radical resection. The correlations between TIAM2 and clinicopathologic parameters, overall and disease-free survival were evaluated. The expression, prognostic value and genomic alterations of TIAM2 gene were explored in the online publicly available databases.ResultsTIAM2 was significantly overexpressed in HCC tissues, compared with AL tissues (P < 0.001). Its expression in multiple tumors was also statistically higher than that in solitary ones (P = 0.017). Moreover, TIAM2 overexpression was univariately associated with poor overall and disease-free survival (P = 0.0066 and 0.0060). In multivariate Cox regression analysis, TIAM2 overexpression was one of significant determinants of both overall and disease-free survival. In the Ualcan and Kaplan-Meier Plotter databases, overexpression and prognostic power of TIAM2 gene in HCC was confirmed, while its genetic alterations included mutation, amplification and deep deletion in the cBioPortal database. Some known tumor-related genes, such as FGD6, FGFR2 and FZD1, were strongly related to TIAM2 gene.ConclusionsTIAM2 overexpression closely correlated with tumor multiplicity and poor prognosis in resected HCC, thus being a potential therapeutic target.

Construction of a circRNA-miRNA-mRNA ceRNA regulatory network identifies RNAs and genes linked to human ovarian clear cell carcinoma.

Ovarian cancer (OC) is a leading cause of cancer-related mortality among females worldwide. Lysine demethylase 6A (KDM6A) plays a crucial role in multiple physiological and pathological processes. However, its role in ovarian carcinogenesis remains unclear. The expression of KDM6A and survival analysis in OC were assessed utilizing GEPIA and Kaplan-Meier plotter databases. The expression of KDM6A was evaluated immunohistochemically in tissue samples from 55 OC patients. The CCK-8, Colony formation, and Transwell assays were employed to assess the ability of OC cells in proliferation, migration, and invasion. Lung metastasis and subcutaneous tumor models were used to evaluate the function of KDM6A in vivo. RNA sequencing, Western blot, and quantitative polymerase chain reaction were conducted to investigate the molecular functions of KDM6A. A chromatin immunoprecipitation assay was employed to determine the effects of KDM6A on the promoters of ubiquitin-like protein interferon-stimulated gene 15 (ISG-15). KDM6A expression was downregulated in OC and associated with poor progression-free survival and overall survival. KDM6A inhibits OC cell proliferation, migration, and invasion in vitro. Xenograft models have also confirmed the antitumor role of KDM6A in OC growth and metastasis. The mechanistic study demonstrated that KDM6A exerted an antitumor effect in a histone-demethylase-dependent manner by epigenetically activating ISG-15 transcription. KDM6A, a functional tumor suppressor, is frequently downregulated in OC. The KDM6A-ISG-15 axis is critical in restraining OC malignancy and may serve as a potential molecular target for novel therapies.

Claudins (CLDNs), key components of tight junctions, are dysregulated in various cancers. However, the roles and therapeutic potential of specific CLDN family members-particularly CLDN6, CLDN9, and CLDN10-in ovarian cancer (OC) remain incompletely defined. To address this gap, we conducted a comprehensive analysis of the CLDN family to identify novel diagnostic and prognostic biomarkers as well as potential therapeutic targets for OC. Gene expression profiles and corresponding clinical data from The Cancer Genome Atlas ovarian cancer cohort (TCGA-OV) and two Gene Expression Omnibus (GEO) datasets (GSE18520, GSE26712) were analyzed. Differential expression of CLDN genes between OC and normal tissues was evaluated using R with appropriate bioinformatics packages (e.g., limma). Logistic regression models were employed to calculate odds ratios (ORs), and receiver operating characteristic (ROC) curves were generated across all datasets to identify consistently dysregulated CLDNs associated with OC. Prognostic hazard ratios (HRs) for these CLDNs were extracted from the Kaplan-Meier Plotter (KM Plotter) database and synthesized using a random-effects model to assess their associations with overall survival. Intersection analysis was performed to identify CLDNs exhibiting both significant differential expression and prognostic significance. Candidate targets underwent comprehensive validation, including single-cell RNA sequencing (scRNA-seq) to characterize cell-type-specific expression patterns. Notably, Key findings regarding CLDN6 were further validated by immunohistochemistry (IHC) on an independent tissue microarray (TMA), as well as functional assays in OC cell lines following siRNA-mediated knockdown. These included transwell invasion, wound healing (scratch) test, and measurements of mitochondrial depolarization, reactive oxygen species (ROS) accumulation, cell cycle arrest, and apoptosis. CLDN6, CLDN9, and CLDN10 were consistently and significantly upregulated in OC compared to normal tissues across all datasets. Single-cell RNA sequencing revealed that CLDN6 and CLDN10 were predominantly expressed in malignant epithelial cell subsets, a pattern associated with aggressive tumor phenotypes. Meta-analysis of HRs showed that HR >1 in CLDN6 and HR <1 in CLDN10. Although CLDN10 is highly expressed in tumor cells, its hazard ratio (HR) is less than 1, and the underlying mechanism of this gene remains unclear. Experiments have confirmed that CLDN6 is closely associated with tumor invasion. Computational analysis, meta-analysis, and single-cell data collectively confirm that only CLDN6 is a clearly defined gene closely associated with tumor progression, a finding subsequently validated by experimental results. Notably, the combined signature comprising CLDN6, CLDN9, and CLDN10 exhibited superior diagnostic performance, with higher area under the curve (AUC) values in ROC analysis, compared to individual CLDNs or established OC biomarkers such as carbohydrate antigen 125 (CA125), human epididymis 4 (HE4), carcinoembryonic antigen (CEA), and alpha-fetoprotein (AFP). The signature also showed enhanced prognostic discrimination, as indicated by time-dependent ROC analysis. Protein overexpression of these targets was validated by IHC and Western blot. Functional assays further demonstrated that siRNA-mediated knockdown of CLDN6 significantly inhibited the proliferation of OC cells, promoted cell apoptosis, increased production of ROS, induced G1 phase arrest, inhibited cell invasion and migration in vitro. Furthermore, western blot analysis identified that knockdown of CLDN6 repressed the Wnt/β-catenin pathway. Nude mice experiments indicated that CLDN6 knockdown in OC cells dramatically suppresses the tumor growth and lung metastasis in vivo. CLDN6, CLDN9, and CLDN10 are critically involved in the pathogenesis and progression of OC. A biomarker panel combining these three claudins demonstrates superior diagnostic and prognostic performance compared to individual markers and established clinical biomarkers such as CA125 and HE4. Notably, functional evidence indicates that CLDN6 plays a pivotal role in regulating malignant phenotypes, highlighting its potential as a novel therapeutic target. These findings collectively support the clinical utility of the CLDN6/9/10 axis as both a non-invasive biomarker signature and a promising avenue for targeted intervention in ovarian cancer.

BackgroundBreast cancer (BC) is the most frequently diagnosed malignancy in women, contributing to high morbidity and mortality rates. Dysregulation of Extra Spindle Pole Bodies Like 1 (ESPL1), a mitotic regulator essential for chromosomal segregation, is frequently upregulated in cancers. However, the mechanisms underlying ESPL1 overexpression and its prognostic relevance in BC remain unclear.MethodsThe study performed the data mining of The Cancer Genome Atlas (TCGA) using various web-based computational tools, including TIMER 2.0, UALCAN, FIREHOSE, TISIDB, GEPIA2, OncoDB, TCGA Portal, TCGAnalyzeR v1.0, bc-GenExMiner v5.0, TNMplot, and DriverDBv4 to compare ESPL1 expression in tumor vs. normal tissues across pan-cancer and BC subtypes. The Kaplan-Meier (KM) Plotter database was used to determine the association between ESPL1 expression and the survival outcomes of BC patients. miRNet, TACCO, and CancerMIRNome databases were used to analyze miRNAs correlated with ESPL1, while lncRNAs were analyzed using the Enrichr database. For experimental validation, ESPL1 expression level was analyzed in BC tumor and adjacent normal tissue collected from BC patients.ResultsWe found that ESPL1 gene was significantly overexpressed in tumors, metastatic tissues, and circulating tumor cells, with tumor samples showing an overall 4-fold increase in expression compared to adjacent normal tissue of BC patients. Furthermore, BC patients with high ESPL1 expression exhibited shorter overall survival (OS), disease-free survival (DFS), and relapse-free survival (RFS) compared to patients with low expression. Tumors from ER-negative and PR-negative BC patients exhibited elevated expression levels of both ESPL1 and the transcription factor E2F8. Moreover, increased levels of ESPL1 and E2F8 were positively correlated with lncRNA TMPO-AS1, while negatively correlated with hsa-let-7b-5p. Notably, the 3′ untranslated region (3′UTR) of ESPL1 showed strong binding sites for hsa-let-7b-5p. We also identified Hesperidin as a high affinity ESPL1 binders, suggesting novel therapeutic candidates targeting this oncogenic network.

The study aimed to investigate the mechanism by which ginsenoside CK downregulates EZH2 to activate the dendritic cell-NK cell axis, promoting antitumor immunity in hepatocellular carcinoma (HCC). Potential targets of ginsenoside CK for HCC treatment were identified utilizing network pharmacology, followed by protein-protein interaction (PPI) network analysis, and GO and KEGG functional enrichment analyses. Differential expression analysis of HCC-related transcriptomic data from the GEO database (GSE84005) was conducted to identify key genes. The expression and prognostic relevance of key genes were verified utilizing the GEPIA and Kaplan-Meier Plotter databases. Molecular docking technology was used to study the binding characteristics of ginsenoside CK to key targets. The liver cancer samples were further grouped according to EZH2 expression, and co-expressed genes were screened and functionally annotated. The correlation between key gene expression and immune cell infiltration was analyzed utilizing the ssGSEA algorithm. Human HCC cell lines MHCC97 and Hep3B were cultured, and cell proliferation and colony formation were assessed utilizing CCK-8 and colony formation assays. Transwell migration and invasion assays evaluated changes in cell migration and invasion. Flow cytometry was employed to analyze cell apoptosis and cell cycle distribution. A xenograft mouse model was established to monitor tumor volume and body weight changes. Immunohistochemistry was used to assess Ki67 expression in tumor tissues, and flow cytometry measured the proportions of NK cells and dendritic cells in tumor tissues. qRT-PCR and Western blotting were performed to evaluate the expression levels of related factors. Network pharmacology analysis identified 114 potential targets of ginsenoside CK and 3991 potential targets of HCC, with 83 intersecting targets. GO and KEGG analyses indicated these targets were involved in phosphatidylinositol-mediated signaling, epithelial cell proliferation and migration, and regulation of MAP kinase activity, suggesting regulation through multiple immune-related signaling pathways in HCC. Transcriptomic analysis revealed that the core target EZH2 was highly expressed in HCC, and high expression correlated with poorer overall survival and relapse-free survival. Molecular docking confirmed that ginsenoside CK was stably bound to the active site of EZH2 (binding energy: -9.1 kcal/mol). Co-expression analysis showed that EZH2 was closely related to the cell cycle, p53 pathway and transcription factor E2F8/MYBL2. Immune infiltration analysis indicated that EZH2 negatively regulated the dendritic cell-NK cell axis, contributing to the remodeling of the tumor immune microenvironment. Invitro experiments demonstrated that ginsenoside CK downregulated EZH2, inhibiting HCC cell proliferation, migration, and invasion, while EZH2 overexpression reversed these inhibitory effects. Invivo experiments confirmed that ginsenoside CK suppressed tumor formation by downregulating EZH2, activating the dendritic cell-NK cell axis, and remodeling the tumor immune microenvironment. Ginsenoside CK inhibits EZH2, activating the dendritic cell-NK cell axis and remodeling the tumor immune microenvironment, thereby suppressing HCC cell activity and tumorigenicity.

Platinum-based compounds are commonly used as an initial treatment for colorectal cancer (CRC). However, the development of drug resistance in patients with CRC necessitates the administration of high drug concentrations during clinical treatment, thereby augmenting the toxicity of platinum-based compounds and increasing the mortality rate. STAG2 is a significantly associated drug-resistance gene in many cancers, but it has not been studied in colorectal cancer. Therefore, the present study aimed to investigate the role and drug sensitivity of the cisplatin-resistant gene STAG2. The effects of STAG2 on drug resistance and survival rates of patients with CRC were examined using the Genomics of Drug Sensitivity in Cancer (GDSC) and Kaplan-Meier (KM) plotter databases. Subsequently, a sh-STAG2-HT-29 cell line was generated using a knockdown test of STAG2, and the half-maximal inhibitory concentration (IC50) of the two cell lines was determined using a cell viability test. We then used various techniques, including the Cell Counting Kit-8 (CCK-8), plate cloning, 5-ethynyl-2'-deoxyuridine (EdU) fluorescence staining, flow cytometry for cell cycle detection, the scar assay, the Transwell invasion assay, and Annexin V-fluorescein isothiocyanate (FITC)/propidium iodide (PI) fluorescence staining for apoptosis detection, to investigate the functionality of the four subgroups of cancer cell lines. Additionally, Western blotting (WB) was used to identify the potential pathways associated with the observed functional alterations. Finally, the phenotype, tumor weight, mouse weight, tumor volume, and tumor tissue structure of the developed tumors were assessed using the subcutaneous tumor formation method. Database analysis indicated that STAG2 plays a role in facilitating drug resistance among individuals with CRC. Furthermore, mutations in this gene lead to increased sensitivity to cisplatin, and its overexpression was associated with an unfavorable prognosis. Following the successful development of STAG2 knockdown cells, differences in IC50 concentrations were observed between HT-29 and sh-STAG2-HT-29 cells. A treatment concentration of 10 μM cisplatin was selected, and the proliferation, migration, and invasion capabilities of cancer cells decreased after STAG2 knockdown. Additionally, the sensitivity of the cells to cisplatin therapy was increased, which was potentially mediated by the epithelial-mesenchymal transition (EMT) pathway. In mice, the tumorigenic potential of HT-29 cells was reduced by STAG2 knockdown, accompanied by a decrease in resistance to cisplatin therapy. STAG2 acts as a proto-oncogene in CRC, and its resistance to cisplatin therapy is more prominent. This study confirmed the role of STAG2 in CRC and provided a theoretical basis for the further development of STAG2 as an auxiliary criterion for determining dosage when patients are treated with platinum drugs.

PurposeThis study investigates the impact of the m1A regulator TRMT6 on prognosis and the tumor microenvironment in ovarian cancer.MethodsAn analysis of the TCGA database was conducted, supplemented by validation from clinical specimens (13 paired samples), to systematically evaluate the expression characteristics of 10 m1A regulators. The prognostic value was assessed using the Kaplan-Meier Plotter database and Cox regression analysis. Additionally, immunohistochemistry and the Log-rank test were employed to validate the impact of TRMT6 on the prognosis and clinicopathological characteristics of ovarian cancer patients. The ssGSEA algorithm and CIBERSORT were utilized to analyze the influence of TRMT6 on the tumor immune microenvironment. We performed single-gene differential analysis of TRMT6 in the TCGA ovarian cancer database using the DESeq2 package and constructed a ceRNA network.ResultsThree m1A regulators (TRMT10C, TRMT6, YTHDF1) were significantly overexpressed in cancer tissues (p < 0.01). Specifically, among these, TRMT6 and YTHDF1 were significantly associated with lower progression-free survival and overall survival (OS) (p < 0.01). Notably, TRMT6 emerged as an independent prognostic factor for predicting poor overall survival (HR = 2.74; 95% CI, 1.13 - 6.65; P = 0.026). TRMT6 expression had a significant correlation with the pathological stage. Furthermore, TRMT6 expression exhibited a significant negative correlation with eleven tumor-infiltrating immune cell types, including cytotoxic cells (p < 0.01). We also found that in ovarian cancer tissues with high expression of TRMT6, the enrichment scores of T cells gamma delta (p < 0.01) and Mast cells activated (p < 0.05) were significantly lower than those in tissues with low expression. HPSE2 has the most interaction nodes among mRNAs, hsa-miR-17-5p among miRNAs, and Lnc SNHG14 among lncRNAs in the ceRNA network.ConclusionThe findings suggest that the m1A regulator TRMT6 may drive ovarian cancer progression by promoting immune escape.

BackgroundDespite being the fourth leading cause of cancer deaths globally, advanced gastric cancer (GC) lacks effective therapeutic targets. While HER2-targeted therapy benefits a subset of patients, the role of its homolog ERBB4 remains controversial in GC pathogenesis and prognosis. This study aimed to examine the expression of ERBB4 in GC and explore whether it could serve as a new target for the biological therapy of GC.MethodsSequencing and clinical data on the ERBB4 gene in GC (tumor) tissues and adjacent non-cancerous (normal) tissues were downloaded from The Cancer Genome Atlas (TCGA) database. A differential expression analysis of the collected ERBB4 gene expression data was conducted. The ERBB4 expression profile in GC was obtained from the Human Protein Atlas (HPA) database. The association between ERBB4 expression and GC prognosis was analyzed using the Kaplan-Meier plotter. The relationship between ERBB4 gene methylation and stomach adenocarcinoma (STAD) was examined online by MEXPRESS visualization in TCGA database. The correlation between ERBB4 messenger RNA (mRNA) expression and methylation/copy number variations (CNVs) was also examined by Spearman correlation analysis. ERBB4 expression microarray data were obtained from the Kaplan-Meier plotter database, and the ERBB4 expression survival curve was plotted. A Cox regression model was established to conduct univariate and multivariate analyses of the risk factors affecting patient prognosis.ResultsCompared with adjacent non-cancerous tissues, ERBB4 mRNA and protein expression were significantly down-regulated in GC tissues. The mRNA expression level of the ERBB4 gene was affected by age, the sample type, and the risk of recurrence in GC patients. The abnormal amplification of ERBB4 was not correlated with its mRNA expression level. Additionally, there was a negative correlation between the methylation level and the mRNA expression of the ERBB4 gene. The Kaplan-Meier survival analysis revealed that patients with high ERBB4 expression had poor overall survival (OS) and progression-free survival (PFS) compared with those with low ERBB4 expression. The multivariate Cox regression analysis showed that ERBB4 was an independent prognostic factor for a poor prognosis in GC, but was not related to PFS.ConclusionsERBB4 is an independent prognostic factor for OS and may serve as a novel target for molecular therapy in GC.

ObjectivesTriple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC), characterized by poor clinical behaviors and outcomes. TMOD1 was reported as a downstream target of NF-κB contributing to the growth of cancer cells. However, it’s impacts on TNBC patients’ prognosis and treatment response remain unclear.MethodsThe prognostic value of TMOD1 was analyzed by data from the Kaplan–Meier database and verified through immunohistochemical evaluation from 190 TNBC patients in West China Hospital (WCH). Cell Counting Kit-8 assay, Transwell cell migration assay and Matrigel invasion assay were used for in vitro study. TNBC cells treated with gradient dosage of doxorubicin (Dox), paclitaxel (PTX), and 5-fluorouracil (5-FU) for chemotherapy sensitivity assay. The chemotherapy sensitivity of Dox in vivo was further confirmed by cell line-derived xenograft (CDX) model.ResultsTNBC patients with high TMOD1 expression had longer overall survival (OS) and recurrence-free survival (RFS) in both Kaplan–Meier plotter database and in cohort from WCH. In cellular functional study, overexpression of TMOD1 promoted TNBC cells’ proliferation, migration and invasion. It also enhanced TNBC sensitivity to Dox treatment both in vivo and in vitro.ConclusionsHigh TMOD1 expression in TNBC patients is associated with better prognosis. Although TMOD1 expression promotes TNBC cell proliferation, migration, and invasion, TMOD1 enhances the sensitivity to Dox therapy both in vivo and in vitro, which might contribute to improve the prognosis for TNBC patients.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12885-025-14961-9.

The relevance and clinical significance of p53 and PD-1/PD-L1 in urothelial carcinoma (UC) are still unknown. This study was to explore the expression, clinical significance, and correlation of p53, PD-1/PD-L1, as well as their associations with immune cells, immune checkpoints and immunotherapy in UC. The expression of p53 and PD-1/PD-L1 were analyzed by the tumor immune estimation resource (TIMER), SangerBox, Gene Expression Profiling Interactive Analysis (GEPIA) databases and immunohistochemistry. The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) and Kaplan-Meier plotter databases were used to examine the clinical and prognostic value of p53 and PD-1/PD-L1 in bladder cancer (BLCA). Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to analyze the potential mechanisms between p53, PD-1/PD-L1, and their co-expression genes and proteins identified through the GeneMANIA, STRING databases, and competitive endogenous RNA (ceRNA) network. The TIMER, GEPIA2, and An integrated repository portal for tumor-immune system interactions (TISIDB) databases were used to analyze the correlation of p53 and PD-1/PD-L1 expression with immune cell infiltration and immune cell gene markers in BLCA. Finally, the association between p53, PD-1/PD-L1 expression and immunotherapy checkpoint inhibitor (ICB), tumor mutation burden (TMB), tumour immune dysfunction and exclusion (TIDE) scores, and immunotherapy in TCGA-BLCA data was analyzed using the "Limma" package. Overall, p53 and PD-L1 expression were found to be significantly different between UC tissues and adjacent normal tissues, whereas no significant difference in PD-1 expression was observed. Pan-cancer survival analysis showed that p53, PD-1/PD-L1 were significantly associated with the prognosis of a variety of pan-cancers, including overall survival (OS) and relapse-free survival (RFS). However, further analysis also confirmed that only low PD-1 expression was associated with poorer OS and RFS in BLCA. In addition, p53 and PD-1/PD-L1 expression are closely related to adverse clinicopathological features. The correlation analysis between p53 and PD-1/PD-L1 showed a significant negative correlation between p53 and PD-1, while PD-1 was significantly positively correlated with PD-L1. Notably, p53 and PD-1/PD-L1 were found to be involved in the regulation of immune responses in GeneMANIA, STRING, ceRNA network, and functional enrichment analysis. Further analysis indicated that p53 and PD-1/PD-L1 were associated with specific immune cells and immune cell gene markers, which may partially affect UC prognosis due to the level of immune cell infiltration. Meanwhile, the correlation analysis of p53, PD-1/PD-L1 with ICB, TMB, TIDE scores and immunotherapy revealed that p53 had a better immunotherapeutic effect in PD-1 negative BLCA patients; Whereas, high PD-1/PD-L1 expression had a better immunotherapeutic effect regardless of CTLA4 and/or PD-1 positivity. As an immune gene or protein associated with PD-1/PD-L1, p53 is significantly negatively correlated with PD-1. High expression of p53 may inhibit PD-1 expression, further inhibiting the PD-1/PD-L1 axis to reduce immunosuppressive status. In addition, p53 may also block the formation of PD-1/PD-L1 resistance by inhibiting the polarization of TAMs and M2 macrophages. This work demonstrates the important role of p53 in PD-1/PD-L1 axis-based immunotherapy for UC patients, and p53 is expected to become a key target for breaking through the current status of immunotherapy.