Identification of metastasis drivers of triple-negative breast cancer (TNBC) is a multifaceted challenge. Here, we identified TATA-box binding protein associated factor 7 (TAF7) as a candidate to modulate TNBC metastasis. TAF7 exhibited high expression in metastatic TNBC patients, and its elevated expression showed a negative correlation with overall survival in TNBC patients. The knockdown of TAF7 suppressed the migration and invasion of TNBC, suggesting TAF7 plays a role in the metastatic processes. Further, TAF7 was enhancing serum amyloid A1 (SAA1) transcription by binding to a specific motif in the SAA1 gene promoter. The elevated SAA1 in TNBC cells directly increased E-cadherin and N-cadherin phosphorylation thereby regulating cell adhesion. Mechanistically, TAF7 modulated cell invasion, migration, and lung metastasis through an SAA1-dependent manner in vitro and in vivo experiments. Taken together, it is likely that TAF7 could directly act on the SAA1 gene promoter, upregulating SAA1 and consequently promoting TNBC metastasis.

Bladder cancer (BLCA) is the most common malignancy of the urinary system and one of the most common cancers worldwide. This study seeks to examine the influence of angiogenesis-related genes (ARGs) linked to disulfidptosis on BLCA patients and to formulate a prognostic model for evaluating their prognosis and response to immunotherapy.

This study used sequencing data of BLCA in the Cancer Genome Atlas (TCGA) database. Unsupervised consensus clustering analysis, cox regression analysis, and least absolute shrinkage and selection operator (LASSO) regression analysis were used to screen hub genes and construct a related prognostic risk model. The receiver operating characteristic (ROC) curve and independent prognostic analysis were then used to verify the predictive performance of the signature genes. Clinical characteristics, immune status, and Tumor Mutation Burden (TMB) of the prognostic risk model were evaluated. The expression levels of model genes within standard bladder epithelial cell lines (SV-HUC-1) and bladder cancer cell lines (T24 and SW1710) were quantified through qRT-PCR.

The constructed prognostic risk model can be used as an independent risk indicator for BLCA and was validated in an external dataset. Immune cell infiltration analysis showed that CD8+T cells, Tregs and dendritic cells were significantly different between the two groups. A significant increase was observed in the Stromal score, Immune score and ESTIMATE score in the high-risk group compared with the low-risk group. The Immune Exclusion score and Tumor Immune Dysfunction and Exclusion (TIDE) score of the high-risk group were higher than those of the low-risk score group. Compared with the normal bladder epithelial cell line (SV-HUC-1), the expression levels of 2 model genes (COL5A2 and SCG2) in bladder cancer cell lines (T24 and SW1710) were significantly elevated.

This study helps us understand the characteristics of disulfidptosis-related subgroups. The characteristics of disulfidptosis-related ARGs may be used to evaluate the prognosis and immunotherapy response of BLCA patients.

Di-(2-ethylhexyl) phthalate (DEHP) is widely utilized as a plasticizer in industrial manufacturing to enhance the durability and flexibility of plastics. Studies have depicted that DEHP exposure may be associated with multiple cancers, including colorectal, liver and prostate cancer. However, the effects and underlying mechanisms of DEHP on bladder cancer progression remain unspecific. In this work, we explored the correlation between DEHP exposure and bladder cancer through comprehensive analysis. A total of 172 differentially expressed DEHP-related genes (DEDRGs) were screened based on the CTD and TCGA database. In addition, a new prognostic model related to DEHP was developed, which had excellent predictive power for bladder cancer prognoses. Molecular docking techniques were employed to assess the binding affinity of mono(2-ethylhexyl) phthalate (MEHP) to crucial proteins. Lastly, both in vitro and in vivo experiments, along with RNA sequencing, were conducted to elucidate the biological roles and mechanisms of MEHP in bladder cancer. Several new insights into the role of DEHP/MEHP in bladder cancer were given in this study, as well as an awareness of the association between environmental toxicants and cancer progression.

The persistent activation of the epidermal growth factor receptor (EGFR) leads to the activation of downstream oncogenic kinases and transcription factors, resulting in tumor progression and an increased resistance to cisplatin in bladder cancer (BC) cells. Lenvatinib, an oral multikinase inhibitor, has the potential to offer therapeutic benefits as an adjuvant treatment for BC patients. The investigation into its application in bladder cancer treatment is a valuable endeavor. The primary goal of this study is to confirm the effectiveness and mechanism of lenvatinib in inhibiting the progression of BC and enhancing the anticancer efficacy of cisplatin.

Three BC cell lines, namely, TSGH-8301, T24, and MB49, along with an MB49-bearing animal model, were utilized in this study.

In vitro experiments utilizing MTT assays demonstrated that lenvatinib sensitized BC cells to cisplatin, exhibiting a synergistic effect. Flow cytometry indicated apoptotic events and signaling, presenting that lenvatinib effectively induced apoptosis and triggered extrinsic/intrinsic apoptotic pathways. In vivo studies using a mouse model of BC confirmed the antitumor efficacy of lenvatinib, demonstrating significant tumor growth suppression without inducing toxicity in normal tissues. Western blotting analysis and immunohistochemistry stain revealed EGF-phosphorylated EGFR and EGFR-mediated ERK/P38/NF-κB signaling were suppressed by treatment with lenvatinib. In addition, lenvatinib also suppressed anti-apoptotic (MCL1, c-FLIP, and XIAP) and metastasis-related factors (Twist, Snail-1, ZEB-1, ZEB-2, and MMP9) and promoted epithelial markers (E-cadherin) while reducing mesenchymal markers (N-cadherin).

In conclusion, the induction of apoptosis and the inhibition of EGFR/ERK/P38/NF-κB signaling are correlated with lenvatinib's ability to hinder tumor progression and enhance the cytotoxic effects of cisplatin in bladder cancer. These findings underscore the potential of lenvatinib as a therapeutic option for bladder cancer, either as a standalone treatment or in combination with cisplatin.

This study aimed to investigate the role of m6A-related long non-coding RNAs (lncRNAs) in the prognosis and tumour microenvironment of head and neck squamous cell carcinoma (HNSCC).

497 samples from The Cancer Genome Atlas were analysed to identify m6A-related lncRNAs via correlation models. Tripartite regression models, Kaplan-Meier analysis and nomograms were then utilised to assess the prognostic significance of these lncRNAs. Tumour mutation burden and immune cell infiltration analyses were also performed. Moreover, m6A-related lncRNAs expression and relation with IGF2BP2 were confirmed by RT-qPCR.

The risk model revealed that high-risk scores predicted poorer survival outcomes. The area under ROC curves for predicting 1-, 3-, 5-year survival in the training set were 0.70, 0.68, and 0.64, respectively. Seven key m6A-related lncRNAs showed associations with immune checkpoint molecules, especially CTLA4 and PD-1. Finally, we found that knockdown of TUG1 repressed the expression of IGF2BP2.

Our results suggest that the m6A-related lncRNA risk model has potential clinical utility in predicting prognosis and immunotherapeutic responses in patients with HNSCC. Identification of candidate compounds for immunotherapy further emphasises the model's relevance in guiding treatment decisions for HNSCC.

Aim: Lung adenocarcinoma (LUAD), the most prevalent subtype of non-small cell lung cancer (NSCLC), presents significant clinical challenges due to its high mortality and limited therapeutic options. The molecular heterogeneity and the development of therapeutic resistance further complicate treatment, underscoring the need for a more comprehensive understanding of its cellular and molecular characteristics. This study sought to delineate novel cellular subpopulations and molecular subtypes of LUAD, identify critical biomarkers, and explore potential therapeutic targets to enhance treatment efficacy and patient prognosis. Methods: An integrative multi-omics approach was employed to incorporate single-cell RNA sequencing (scRNA-seq), bulk transcriptomic analysis, and genome-wide association study (GWAS) data from multiple LUAD patient cohorts. Advanced computational approaches, including Bayesian deconvolution and machine learning algorithms, were used to comprehensively characterize the tumor microenvironment, classify LUAD subtypes, and develop a robust prognostic model. Results: Our analysis identified eleven distinct cellular subpopulations within LUAD, with epithelial cells predominating and exhibiting high mutation frequencies in Tumor Protein 53 (TP53) and Titin (TTN) genes. Two molecular subtypes of LUAD [consensus subtype (CS)1 and CS2] were identified, each showing distinct immune landscapes and clinical outcomes. The CS2 subtype, characterized by increased immune cell infiltration, demonstrated a more favorable prognosis and higher sensitivity to immunotherapy. Furthermore, a multi-omics-driven machine learning signature (MOMLS) identified ribonucleotide reductase M1 (RRM1) as a critical biomarker associated with chemotherapy response. Based on this model, several potential therapeutic agents targeting different subtypes were proposed. Conclusion: This study presents a comprehensive multi-omics framework for understanding the molecular complexity of LUAD, providing insights into cellular heterogeneity, molecular subtypes, and potential therapeutic targets. Differential sensitivity to immunotherapy among various cellular subpopulations was identified, paving the way for future immunotherapy-focused research.

Bladder cancer (BC) is a highly recurrent and invasive malignancy, with Mycobacterium bovis BCG serving as the primary immunotherapy, particularly for non-muscle-invasive bladder cancer (NMIBC). However, the mechanisms underlying BCG's antitumor effects and the potential of non-tuberculous mycobacteria like Mycobacterium brumae remain unclear. This study investigates the antitumor effects of M. bovis BCG and M. brumae on BC cell migration, invasion, and anchorage-independent growth. BC cell lines representing different stages of tumor differentiation were treated with either M. bovis BCG or M. brumae. Cell migration was assessed through wound healing and transwell assays, invasiveness by transwell invasion assays, MMP-9 production by gelatin zymography, and anchorage-independent growth via soft agar colony formation. Both mycobacteria inhibited individual cell migration across all BC lines, while collective migration was only reduced in intermediate-grade cells. Both treatments also reduced invasiveness, associated with decreased MMP-9 production. Furthermore, M. brumae inhibited anchorage-independent growth across all BC lines, while M. bovis BCG had a more selective effect, primarily inhibiting growth in high-grade cells. In conclusion, both mycobacteria reduce migration, invasion, and anchorage-independent growth of BC cells, with their effectiveness varying by species and tumor differentiation grade.

Bladder cancer treatments are highly aggressive and have strong side effects. Safer and more effective treatments are needed. In this study, Dibenzolium (DIB), a potent NADPH oxidase inhibitor, was evaluated for its anti-tumor effects. KK-47 (non-invasive), T24 and 5637 (invasive) cells were used in experiments. Cell proliferation, apoptosis and wound healing assays and western blotting were conducted. In addition, DIB was intratumorally administered to mice bearing KK-47, T24 and 5637 tumors, and tumor size and weight were observed over time. After removing tumors, immunohistochemistry (IHC) staining was conducted. Cell proliferation was significantly suppressed in all cell lines, and apoptotic cells increased in the KK-47 and T24 cell lines after DIB. Wound healing was suppressed in all cell lines by DIB. In KK-47 and T24, DIB increased the protein expression of the epithelial marker E-cadherin. In vivo, DIB safely suppressed tumor growth in all cell lines-bearing mice. Cleaved-Caspase-3 and E-cadherin expression increased in KK-47 and T24 tumors after DIB. In conclusion, DIB inhibited tumor growth by inducing apoptosis through the Caspase-3 pathway and reduced migration and invasion by suppressing epithelial mesenchymal transition (EMT) in bladder cancer similarly shown as our previous study of prostate cancer.

Bladder carcinoma (BLCA) represents a common urinary tract malignancy, characterized by aggressive behavior and high recurrence rates. The biological response regulation during tumor proliferation and metastasis is intimately associated with liquid-liquid phase separation (LLPS). For the purpose of enhancing early detection and treatment, this study employed transcriptomic data to examine the prognostic implications of LLPS-associated genes and formulate a predictive model. Clinical and transcriptomic data of bladder cancer patients were sourced from the GEO and TCGA databases. This study applied a clustering algorithm using non-negative matrix factorization (NMF) to classify samples, which were systematically compared based on their liquid-liquid phase separation characteristics. Prognostic models were developed using multivariate Cox regression and the Least Absolute Shrinkage Selection Operator (LASSO) algorithm to establish risk formulas for nine genes. The gene signature's validity was tested across the entire TCGA cohort (406 cases), the TCGA testing cohort (120 cases), and the external validation dataset GSE13507. The predictive accuracy of the signature system was assessed using receiver operating characteristic (ROC) and Kaplan-Meier curves. Additionally, decision curve analysis incorporating clinicopathological parameters and the genetic signature was employed to predict individual survival. This study identified two distinct molecular subtypes, C1 and C2. Patients with the C1 subtype exhibited significantly better prognoses than those with the C2 subtype. Low-risk group patients consistently showed superior prognoses compared to high-risk groups across the entire TCGA, GEO, and TCGA training cohorts. Furthermore, the LLPS-related gene model demonstrated prognostic value independent of other clinical traits. This study identifies LLPS-associated gene clusters and establishes an independent, accurate prognostic model for BLCA. The model holds potential for clinical application in BLCA prognosis assessment.

Anoikis and epithelial-mesenchymal transition (EMT) are pivotal in the distant metastasis of lung adenocarcinoma (LUAD). A detailed understanding of their interplay and the identification of key genes is vital for effective therapeutic strategies against LUAD metastasis.

Key prognostic genes related to anoikis and EMT were identified through univariate Cox regression analysis. We utilized ten machine learning algorithms to develop the Anoikis and EMT-Related Optimal Model (AEOM). The TCGA-LUAD dataset served as the training cohort, while six additional international multicenter LUAD datasets were employed as validation cohorts. The average concordance index (c-index) was used to evaluate model performance and identify the most effective model. Subsequent multi-omics analyses were conducted to explore differences in pathway enrichment, immune infiltration, and mutation landscapes between high and low AEOM groups. Experimental validation demonstrated that RHPN2, a key biomarker within the model, acts as an oncogene facilitating LUAD progression.

The AEOM displayed superior prognostic predictive performance for LUAD patients, outperforming numerous previously published LUAD signatures. Biologically, the AEOM was notably associated with immune features; the high AEOM group exhibited decreased immune activity and a tendency towards immune-cold tumors, as well as a higher tumor mutational burden (TMB). Subgroup analysis revealed that the low AEOM + high TMB group had the most favorable prognosis. The high AEOM group was primarily enriched in cell cycle-related pathways, promoting cancer cell proliferation. RHPN2, a crucial gene within the AEOM (correlation = 0.85, P < 0.05), was linked to poorer prognosis in LUAD patients with elevated RHPN2 expression. Further in vitro experiments showed that RHPN2 modulates LUAD cell proliferation and invasion.

The AEOM provides a robust prognostic model for LUAD, uncovering critical immune and biological pathways, with RHPN2 identified as a key oncogenic driver. These findings offer valuable insights for targeted therapies and enhanced patient outcomes.

This study aimed to explore the Liquid-liquid phase separation (LLPS)-related genes associated with the prognosis of bladder cancer (BCa) and assess the potential application of LLPS-related prognostic signature for predicting prognosis in BCa patients.

Clinical information and transcriptome data of BCa patients were extracted from the Cancer Genome Atlas-BLCA (TCGA-BLCA) database and the GSE13507 database. Furthermore, 108 BCa patients who received treatment at our institution were subjected to a retrospective analysis. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an LLPS-related prognostic signature for BCa. The CCK8, wound healing and Transwell assays were performed.

Based on 62 differentially expressed LLPS-related genes (DELRGs), three DELRGs were screened by LASSO analysis including kallikrein-related peptidase 5 (KLK5), monoacylglycerol O-acyltransferase 2 (MOGAT2) and S100 calcium-binding protein A7 (S100A7). Based on three DELRGs, a novel LLPS-related prognostic signature was constructed for individualized prognosis assessment. Kaplan-Meier curve analyses showed that LLPS-related prognostic signature was significantly correlated with overall survival (OS) of BCa. ROC analyses demonstrated the LLPS-related prognostic signature performed well in predicting the prognosis of BCa patients in the training group (the area under the curve (AUC) = 0.733), which was externally verified in the validation cohort 1 (AUC = 0.794) and validation cohort 2 (AUC = 0.766). Further experiments demonstrated that inhibiting KLK5 could affect the proliferation, migration, and invasion of BCa cells.

In this study, a novel LLPS-related prognostic signature was successfully developed and validated, demonstrating strong performance in predicting the prognosis of BCa patients.

Cancer metastasis and therapy resistance are intricately linked with the dynamics of Epithelial-Mesenchymal Transition (EMT) and Circulating Tumor Cells (CTCs). EMT hybrid cells, characterized by a blend of epithelial and mesenchymal traits, have emerged as pivotal in metastasis and demonstrate remarkable plasticity, enabling transitions across cellular states crucial for intravasation, survival in circulation, and extravasation at distal sites. Concurrently, CTCs, which are detached from primary tumors and travel through the bloodstream, are crucial as potential biomarkers for cancer prognosis and therapeutic response. There is a significant interplay between EMT hybrid cells and CTCs, revealing a complex, bidirectional relationship that significantly influences metastatic progression and has a critical role in cancer drug resistance. This resistance is further influenced by the tumor microenvironment, with factors such as tumor-associated macrophages, cancer-associated fibroblasts, and hypoxic conditions driving EMT and contributing to therapeutic resistance. It is important to understand the molecular mechanisms of EMT, characteristics of EMT hybrid cells and CTCs, and their roles in both metastasis and drug resistance. This comprehensive understanding sheds light on the complexities of cancer metastasis and opens avenues for novel diagnostic approaches and targeted therapies and has significant advancements in combating cancer metastasis and overcoming drug resistance.

Bladder cancer (BC) is very common among cancers of urinary system. It was usually categorized into two types: non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC). NMIBC and MIBC groupings are heterogeneous and have different characteristics.

The study was aimed to find some hub genes and related signal pathways which might be engaged in the progression of BC and to investigate the relationship with clinical stages and its prognostic significance.

GSE37317 datasets were acquired from Gene Expression Omnibus (GEO) database. GEO2R on-line tool was selected to screen the differentially expressed genes (DEGs) of the two different types of BC. Then, Gene Ontology (GO) enrichment and KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of these DEGs were conducted. A protein-protein interaction (PPI) network was employed to help us screen hub genes and find significant modules. Finally, we made analysis of gene expression and survival curve by GEPIA and Kaplan-Meier plotter database.

224 DEGs were screened in total, with 110 showing increased expression and 114 demonstrating decreased expression. GO and KEGG pathway enrichment analysis showed that DEGs were mostly involved in collagen fibril organization, extracellular matrix (ECM) structural constituent, bHLH transcription factor binding, AGE-RAGE signaling pathway and TGF-beta signaling pathway. Only 3 hub genes (DCN, JUN, THBS1) displayed significantly higher expression compared to those in the healthy controls. These hub genes were also strongly related to clinical stages as well as overall survival (OS) of BC patients.

Taken together, most of hub genes involved in the progression of BC were related to ECM and EMT. In addition, 3 hub genes (DCN, JUN, THBS1) were strongly related with clinical stages and OS of BC patients. This study can enhance our comprehension of the progression of NMIBC and identify novel potential targets for MIBC.

It is accepted that cancer stem cells (CSCs) are key to the occurrence, progression, drug resistance, and recurrence of bladder cancer (BLCA). Here, we aimed to characterize the landscapes of CSCs and investigate the biological and clinical signatures based on a prognostic model constructed by genes associated with CSCs. The malignant epithelial cells were discovered and sorted into six clusters through single cell analysis. C2 was identified as the CSCs. The signaling involved in the interactions between C2, cancer-associated fibroblasts (CAFs), and immune cells mainly consisted of MK, THBS, ANGPTL, VISFATIN, JAM, and ncWNT pathways. The CSC-like prognostic index (CSCLPI) constructed by the random survival forest was a reliable risk factor for BLCA and had a stable and powerful effect on predicting the overall survival of patients with BLCA. The level of CAFs was higher among patients with higher CSCLPI scores, suggesting that CAFs play a significant role in regulating biological characteristics. The CSCLPI-developed survival prediction nomogram has the potential to be applied clinically to predict the 1-, 2-, 3-, and 5-year overall survival of patients with BLCA. The CSCLPI can be used for prognostic prediction and drug treatment evaluation in the clinic.

To develop a prognostically relevant scoring system for stage pT1 non-muscle-invasive bladder cancer (NMIBC) incorporating tumour budding, growth pattern and invasion pattern because the World Health Organisation grading system shows limited prognostic value in such patients.

The tissue specimens and clinical data of 113 patients with stage pT1 NMIBC who underwent transurethral resection of bladder tumour were retrospectively investigated. Tumour budding, and growth and invasion patterns were evaluated and categorised into two grade groups (GGs). GGs and other clinical and histopathological variables were investigated regarding recurrence-free survival (RFS), progression-free survival (PFS), cancer-specific survival (CSS) and overall survival (OS) using univariable and multivariable Cox regression analyses.

The integration of two tumour budding groups, two growth patterns, and two invasion patterns yielded an unfavourable GG (n = 28; 24.7%) that had a high impact on oncological outcomes. The unfavourable GG was identified as an independent RFS and OS predictor (P = 0.004 and P = 0.046, respectively) and linked to worse PFS (P = 0.001) and CSS (P = 0.001), irrespective of the European Association of Urology risk group. The unfavourable GG was associated with higher rates of BCG-unresponsive tumours (P = 0.006). Study limitations include the retrospective, single-centre design, diverse therapies and small cohort.

We present a morphology-based grading system for stage pT1 NMIBC that correlates with disease aggressiveness and oncological patient outcomes. It therefore identifies a highest risk group of stage pT1 NMIBC patients, who should be followed up more intensively or receive immediate radical cystectomy. The grading incorporates objective variables assessable on haematoxylin and eosin slides and immunohistochemistry, enabling an easy-to-use low-cost approach that is applicable in daily routine. Further studies are needed to validate and confirm these results.

The tumour microenvironment (TME) drives bladder cancer (BLCA) progression. Targeting the TME has emerged as a promising strategy for BLCA treatment in recent years. Furthermore, checkpoint blockade therapies are only beneficial for a minority of patients with BLCA, and drug resistance is a barrier to achieving significant clinical effects of anti-programmed cell death protein-1 (PD-1)/programmed death protein ligand-1 (PD-L1) therapy. In this study, higher low-density lipoprotein receptor-related protein 1 (LRP1) levels were related to a poorer prognosis for patients with various cancers, including those with higher grades and later stages of BLCA. Enrichment analysis demonstrated that LRP1 plays a role in the epithelial-mesenchymal transition (EMT), NOTCH signalling pathway, and ubiquitination. LRP1 knockdown in BLCA cells delayed BLCA progression both in vivo and in vitro. Furthermore, LRP1 knockdown suppressed EMT, reduced DLL4-NOTCH2 signalling activity, and downregulated M2-like macrophage polarisation. Patients with BLCA and higher LRP1 levels responded weakly to anti-PD-1 therapy in the IMvigor210 cohort. Moreover, LRP1 knockdown enhanced the therapeutic effects of anti-PD-1 in mice. Taken together, our findings suggest that LRP1 is a potential target for improving the efficacy of anti-PD-1/PD-L1 therapy by preventing EMT and M2-like macrophage polarisation by blocking the DLL4-NOTCH2 axis.

Although prognostic models based on pyroptosis-related genes (PRGs) have been constructed in bladder cancer (BLCA), the comprehensive impact of these genes on tumor microenvironment (TME) and immunotherapeutic response has yet to be investigated.

Based on expression profiles of 52 PRGs, we utilized the unsupervised clustering algorithm to identify PRGs subtypes and ssGSEA to quantify immune cells and hallmark pathways. Moreover, we screened feature genes of distinct PRGs subtypes and validated the associations with immune infiltrations in tissue using the multiplex immunofluorescence. Univariate, LASSO, and multivariate Cox regression analyses were employed to construct the scoring scheme.

Four PRGs clusters were identified, samples in cluster C1 were infiltrated with more immune cells than those in others, implying a favorable response to immunotherapy. While the cluster C2, which shows an extremely low level of most immune cells, do not respond to immunotherapy. CXCL9/CXCL10 and SPINK1/DHSR2 were identified as feature genes of cluster C1 and C2, and the specimen with high CXCL9/CXCL10 was characterized by more CD8 + T cells, macrophages and less Tregs. Based on differentially expressed genes (DEGs) among PRGs subtypes, a predictive model (termed as PRGs score) including five genes (CACNA1D, PTK2B, APOL6, CDK6, ANXA2) was built. Survival probability of patients with low-PRGs score was significantly higher than those with high-PRGs score. Moreover, patients with low-PRGs score were more likely to benefit from anti-PD1/PD-L1 regimens.

PRGs are closely associated with TME and oncogenic pathways. PRGs score is a promising indicator for predicting clinical outcome and immunotherapy response.

The molecular categorization of colon cancer patients remains elusive. Gene set enrichment analysis (GSEA), which investigates the dysregulated genes among tumor and normal samples, has revealed the pivotal role of epithelial-to-mesenchymal transition (EMT) in colon cancer pathogenesis. In this study, we employed multi-clustering method for grouping data, resulting in the identification of two clusters characterized by varying prognostic outcomes. These two subgroups not only displayed disparities in overall survival (OS) but also manifested variations in clinical variables, genetic mutation, and gene expression profiles. Using the nearest template prediction (NTP) method, we were able to replicate the molecular classification effectively within the original dataset and validated it across multiple independent datasets, underscoring its robust repeatability. Furthermore, we constructed two prognostic signatures tailored to each of these subgroups. Our molecular classification, centered on EMT, hold promise in offering fresh insights into the therapy strategies and prognosis assessment for colon cancer.

The mitogen-activated protein kinase (MAPK) pathway plays a critical role in tumor development and immunotherapy. Nevertheless, additional research is necessary to comprehend the relationship between the MAPK pathway and the prognosis of bladder cancer (BLCA), as well as its influence on the tumor immune microenvironment. To create prognostic models, we screened ten genes associated with the MAPK pathway using COX and least absolute shrinkage and selection operator (LASSO) regression analysis. These models were validated in the Genomic Data Commons (GEO) cohort and further examined for immune infiltration, somatic mutation, and drug sensitivity characteristics. Finally, the findings were validated using The Human Protein Atlas (HPA) database and through Quantitative Real-time PCR (qRT-PCR). Patients were classified into high-risk and low-risk groups based on the prognosis-related genes of the MAPK pathway. The high-risk group had poorer overall survival than the low-risk group and showed increased immune infiltration compared to the low-risk group. Additionally, the nomograms built using the risk scores and clinical factors exhibited high accuracy in predicting the survival of BLCA patients. The prognostic profiling of MAPK pathway-associated genes represents a potent clinical prediction tool, serving as the foundation for precise clinical treatment of BLCA.

The activation levels of biologically significant gene sets are emerging tumor molecular markers and play an irreplaceable role in the tumor research field; however, web-based tools for prognostic analyses using it as a tumor molecular marker remain scarce. We developed a web-based tool PESSA for survival analysis using gene set activation levels. All data analyses were implemented via R. Activation levels of The Molecular Signatures Database (MSigDB) gene sets were assessed using the single sample gene set enrichment analysis (ssGSEA) method based on data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), The European Genome-phenome Archive (EGA) and supplementary tables of articles. PESSA was used to perform median and optimal cut-off dichotomous grouping of ssGSEA scores for each dataset, relying on the survival and survminer packages for survival analysis and visualisation. PESSA is an open-access web tool for visualizing the results of tumor prognostic analyses using gene set activation levels. A total of 238 datasets from the GEO, TCGA, EGA, and supplementary tables of articles; covering 51 cancer types and 13 survival outcome types; and 13,434 tumor-related gene sets are obtained from MSigDB for pre-grouping. Users can obtain the results, including Kaplan-Meier analyses based on the median and optimal cut-off values and accompanying visualization plots and the Cox regression analyses of dichotomous and continuous variables, by selecting the gene set markers of interest. PESSA (https://smuonco.shinyapps.io/PESSA/ OR http://robinl-lab.com/PESSA) is a large-scale web-based tumor survival analysis tool covering a large amount of data that creatively uses predefined gene set activation levels as molecular markers of tumors.

The prevalence and mortality of bladder cancer (BLCA) present a significant medical challenge. While the function of senescence-related genes in tumor development is recognized, their prognostic significance in BLCA has not been thoroughly explored.

BLCA transcriptome datasets were sourced from the TCGA and GEO repositories. Gene groupings were determined through differential gene expression and non-negative matrix factorization (NMF) methodologies. Key senescence-linked genes were isolated using singular and multivariate Cox regression analyses, combined with lasso regression. Validation was undertaken with GEO database information. Predictive models, or nomograms, were developed by merging risk metrics with clinical records, and their efficacy was gauged using ROC curve methodologies. The immune response's dependency on the risk metric was assessed through the immune phenomenon score (IPS). Additionally, we estimated IC50 metrics for potential chemotherapeutic agents.

Reviewing 406 neoplastic and 19 standard tissue specimens from the TCGA repository facilitated the bifurcation of subjects into two unique clusters (C1 and C2) according to senescence-related gene expression. After a stringent statistical evaluation, a set of ten pivotal genes was discerned and applied for risk stratification. Validity tests for the devised nomograms in forecasting 1, 3, and 5-year survival probabilities for BLCA patients were executed via ROC and calibration plots. IC50 estimations highlighted a heightened responsiveness in the low-risk category to agents like cisplatin, cyclopamine, and sorafenib.

In summation, our research emphasizes the prospective utility of risk assessments rooted in senescence-related gene signatures for enhancing BLCA clinical oversight.

Immunotherapy using an immune-checkpoint blockade has significantly improved its therapeutic effects. CM-272, which is a novel epigenetic inhibitor of G9a, induces immunogenic cell death (ICD) for recovering the sensitivity to anti-PD-1 antibodies; however, the efficacy of CM-272 is greatly limited by promoting the transcription activity of HIF-1α to form a hypoxic environment. Here, a Fe3+ -based nanoscale metal-organic framework (MIL-53) is used to load CM-272 (ultra-high loading rate of 56.4%) for realizing an MIL-53@CM-272 nanoplatform. After entering bladder cancer cells, Fe3+ not only promotes the decomposition of H2 O2 into O2 for O2 -compensated sonodynamic therapy but reduces the high level of glutathione in the tumor microenvironment (TME) for enhancing reactive oxygen species, including ferroptosis and apoptosis. MIL-53 carriers can be degraded in response to the TME, accelerating the release of CM-272, which helps achieve the maximum effectiveness in an O2 -sufficient TME by attenuating drug resistance. Furthermore, MIL-53@CM-272 enhances dendritic cell maturation and synergistically combines it with an anti-programmed cell death protein 1 antibody during the study of immune-related pathways in the transcriptomes of bladder cancer cells using RNA-seq. This study presents the first instance of amalgamating nanomedicine with CM-272, inducing apoptosis, ferroptosis, and ICD to achieve the "one arrow three eagle" effect.

The tumor immune environment and immune-related genes are instrumental in the development, progression, and prognosis of bladder cancer (BLCA). This study sought to pinpoint key immune-related genes influencing BLCA prognosis and decipher their mechanisms of action.

We analyzed differentially expressed genes (DEGs) between high- and low- tumor mutational burden (TMB) groups. Subsequently, we constructed a reliable prognostic model based on immune-related gene pairs (IRGPs) and analyzed DEGs between high- and low-risk groups. A total of 22 shared DEGs were identified across differential TMB and IRGPs-derived risk groups in BLCA patients. Through univariate Cox and multivariate Cox analyses, we highlighted five genes - FLRT2, NTRK2, CYTL1, ZNF683, PRSS41 - significantly correlated with BLCA patient prognosis. Notably, the FLRT2 gene emerged as an independent prognostic factor for BLCA, impacting patient prognosis via modulation of macrophage infiltration in immune microenvironment. Further investigation spotlighted methylation sites - cg25120290, cg02305242, and cg01832662 - as key regulators of FLRT2 expression.

These findings identified pivotal prognostic genes in BLCA and illuminated the intricate mechanisms dictating patient prognosis. This study not only presents a novel prognostic marker but also carves out potential avenues for immunotherapy and targeted therapeutic strategies in BLCA. By demystifying the profound impact of immune-related genes and the tumor immune environment, this study augments the comprehension and prognostic management of bladder cancer.

Background: Bladder cancer (BLCA) is the most common genitourinary malignancy. Proliferation essential genes (PEGs) are crucial to the survival of cancer cells. This study aimed to build a PEG signature to predict BLCA prognosis and treatment efficacy. Methods: BLCA PEGs and differentially expressed PEGs were identified using DepMap and TCGA-BLCA datasets, respectively. Based on the prognostic analysis of the differentially expressed PEGs, a PEG model was constructed. Subsequently, we analyzed the relationship between the PEG signature and prognosis of BLCA patients as well as their response to chemotherapy. Finally, we performed random forest analysis to target and functional experiments to validate the most significant PEG which is associated with BLCA progression. CCK-8, invasion, migration, and chemosensitivity assays were performed to assess effects of gene knockdown on BLCA cell proliferation, invasion and migration abilities, and cisplatin chemosensitivity. Results: We screened 10 prognostic PEGs from 201 differentially expressed PEGs and used them to construct a PEG signature model. Patients with high PEG signature score (PEGs-high) exhibited worse OS and lower sensitivity to chemotherapy than those with PEGs-low. We also found significant correlations between the PEG score and previously defined BLCA molecular subtypes. This suggests that the PEG score may effectively predict the molecular subtypes which have distinct clinical outcomes. Random forest analysis revealed that POLE2 (DNA polymerase epsilon subunit 2) was the most significant PEG differentiating BLCA tissue and normal tissue. Bioinformatic analysis and an immunohistochemistry staining assay confirmed that POLE2 was significantly up-regulated in tumor tissues and was associated with poor survival in BLCA patients. Moreover, POLE2 knockdown inhibited the ability of cell clone formation, proliferation, invasion, immigration and IC50 of cisplatin. Conclusion: The PEG signature acts as a potential predictor for prognosis and chemotherapy response in BLCA patients. POLE2 is a key PEG and plays a remarkable role in promoting the malignant progression and cisplatin resistance of BLCA.

The pathophysiologic heterogeneity of heart failure (HF) necessitates a more detailed identification of diagnostic biomarkers that can reflect its diverse pathogenic pathways.

We conducted weighted gene and multiscale embedded gene co-expression network analysis on differentially expressed genes obtained from HF and non-HF specimens. We employed a machine learning integration framework and protein-protein interaction network to identify diagnostic biomarkers. Additionally, we integrated gene set variation analysis, gene set enrichment analysis (GSEA), and transcription factor (TF)-target analysis to unravel the biomarker-dominant pathways. Leveraging single-sample GSEA and molecular docking, we predicted immune cells and therapeutic drugs related to biomarkers. Quantitative polymerase chain reaction validated the expressions of biomarkers in the plasma of HF patients. A two-sample Mendelian randomization analysis was implemented to investigate the causal impact of biomarkers on HF.

We first identified COL14A1, OGN, MFAP4, and SFRP4 as candidate biomarkers with robust diagnostic performance. We revealed that regulating biomarkers in HF pathogenesis involves TFs (BNC2, MEOX2) and pathways (cell adhesion molecules, chemokine signaling pathway, cytokine-cytokine receptor interaction, oxidative phosphorylation). Moreover, we observed the elevated infiltration of effector memory CD4+ T cells in HF, which was highly related to biomarkers and could impact immune pathways. Captopril, aldosterone antagonist, cyclopenthiazide, estradiol, tolazoline, and genistein were predicted as therapeutic drugs alleviating HF via interactions with biomarkers. In vitro study confirmed the up-regulation of OGN as a plasma biomarker of HF. Mendelian randomization analysis suggested that genetic predisposition toward higher plasma OGN promoted the risk of HF.

We propose OGN as a diagnostic biomarker for HF, which may advance our understanding of the diagnosis and pathogenesis of HF.

Epithelial-mesenchymal transition (EMT) is a cellular process by which epithelial cells lose their characteristics and acquire mesenchymal traits to promote cell movement. This program is aberrantly activated in human cancers and endows tumor cells with increased abilities in tumor initiation, cell migration, invasion, metastasis, and therapy resistance. The EMT program in tumors is rarely binary and often leads to a series of gradual or intermediate epithelial-mesenchymal states. Functionally, epithelial-mesenchymal plasticity (EMP) improves the fitness of cancer cells during tumor progression and in response to therapies. Here, we discuss the most recent advances in our understanding of the diverse roles of EMP in tumor initiation, progression, metastasis, and therapy resistance and address major clinical challenges due to EMP-driven phenotypic heterogeneity in cancer. Uncovering novel molecular markers and key regulators of EMP in cancer will aid the development of new therapeutic strategies to prevent cancer recurrence and overcome therapy resistance.

The cGAS-STING pathway emerges as a pivotal innate immune pathway with the potential to profoundly influence all facets of tumor initiation and progression. The prognostic significance and immunological role of cGAS-STING pathway-related genes (CRGs) in individuals diagnosed with bladder cancer (BLCA) have not yet been fully elucidated.

Performed unsupervised cluster analysis to identify distinct clusters. Utilizing LASSO and multivariate Cox regression analysis to construct a prognostic risk model. The IMvigor210, GSE13507 and GSE78220 cohorts were utilized to explore the potential value of risk score in immune therapy response and survival prediction.

A risk model was developed utilizing four CRGs in order to forecast the overall survival (OS) of BLCA patients. The risk score to be a standalone risk factor, which was further corroborated by the external validation set obtained from the GEO database (GSE13507). We established an integrated nomogram that combined risk scoring and clinical information, exhibiting commendable clinical practicality in predicting the overall survival period of BLCA patients. It is noteworthy that risk score could differentiate tumor microenvironments among different risk groups and individuals who were more responsive to immunotherapy in IMvigor210 and GSE13507 cohorts. In vitro experiments, we noted an up-regulation of IRF3 and IKBKB upon the activation of the cGAS-STING pathway. Conversely, the activation of the cGAS-STING pathway resulted in a down-regulation of POLR3G and CTNNB1.

CRG risk model shows promise as a potential stratification approach for bladder cancer patients.

There are a total of 82,290 new cases and 16,710 deaths estimated for bladder cancer in the United States in 2023. Currently, urine cytology tests are widely used for bladder cancer diagnosis, though they suffer from variable sensitivity, ranging from 45 to 97%. More recently, the microbiome has become increasingly recognized for its role in human diseases, including cancers. This study attempts to characterize urinary microbiome bladder cancer-specific dysbiosis to explore its diagnostic potential. RNA-sequencing data of urine samples from patients with bladder cancer (n = 18) and matched controls (n = 12) were mapped to bacterial sequences to yield species-level abundance approximations. Urine samples were analyzed at both the population and species level to reveal dysbiosis associated with bladder cancer. A panel of 35 differentially abundant species was discovered, which may be useful as urinary biomarkers for this disease. We further assessed whether these species were of similar significance in a validation dataset (n = 81), revealing that the genera Escherichia, Acinetobacter, and Enterobacter were consistently differentially abundant. We discovered distinct patterns of microbial-associated immune modulation in these samples. Several immune pathways were found to be significantly enriched with respect to the abundance of these species, including antigen processing and presentation, cytosolic DNA sensing, and leukocyte transendothelial migration. Differential cytokine activity was similarly observed, suggesting the urinary microbiome's correlation to immune modulation. The adherens junction and WNT signaling pathways, both implicated in the development and progression of bladder cancer, were also enriched with these species. Our findings indicate that the urinary microbiome may reflect both microbial and immune dysregulations of the tumor microenvironment in bladder cancer. Given the potential biomarker species identified, the urinary microbiome may provide a non-invasive, more sensitive, and more specific diagnostic tool, allowing for the earlier diagnosis of patients with bladder cancer.

The highly heterogeneous, complex pathological histology, and clinical phenotype in bladder cancer (BC) plague the prognostic management of BC to the present day.

This study was conducted using single-cell sequencing data from the gene expression omnibus (GEO) database (GSE135337). A descending, annotated analysis was performed to identify the cell types contributing to BC aggressiveness. BC cell sequencing data from The Cancer Genome Atlas (TCGA) database were then combined with univariate, least absolute shrinkage and selection operator (LASSO), multivariate COX regression analysis to identify biomarkers of BC prognosis to construct a BC. We identified biomarkers of BC prognosis to construct a prognostic risk guidance system for BC. The feedback of patients in different risk strata to immunotherapy was analyzed. Finally, the regulation of prognostic genes on cancer cell activity was verified in vitro by Western blot and cell counting kit-8 (CCK8) assays.

Macrophages specifically expressing CD68 in BC were the cell type with the highest AUCell score, and CD68 was the biomarker of Tumor-associated macrophages (TAMs). CD68 macrophages were potentially the critical cell type in the aggressive BC subtype. Through univariate, LASSO, multivariate COX-based regression analysis. CTSS, GMFG, ANXA5, GSN, SLC2A3, and FTL were authenticated as prognostic biomarkers (p < 0.05) and composed the Risk Score. Patients in the low-risk group showed an excellent survival advantage (p < 0.01) and immunotherapy feedback. Additionally, inhibition of GSN expression decreased EMT activity to inhibit bladder cancer cell viability.

In conclusion, this study provided feedback on the immune cell types associated with aggressiveness in BC. Importantly, a prognostic management system for BC was created based on the genes involved, providing more insight into the aggressive pathological phenotype as well as the prognosis of BC.

Pyroptosis is a programmed cell death, which garners increasing attention by relating to immune and therapy response. However, the role of pyroptosis in colorectal cancer (CRC) remains unclear. Our study mainly to explore the role of pyroptosis in CRC. The mRNA expression data and corresponding clinical information of CRC patients were achieved from The Cancer Genome Atlas (TCGA). Pyroptosis-related genes (PRGs) were identified using DESeq2 R package and biological function was analyzed using cluster Profiler R package. A PRGs-based prognosis model was constructed by a univariate Cox and LASSO regression analyses. Then, the affecting of risk signature to clinicopathological characteristics, immune status and infiltrated immune cells, immune checkpoint and chemotherapy sensitivity was analyzed. qRT-PCR and IHC were performed for the expression level of PRGs. Moreover, a nomogram predict model was constructed. Total 57 PRGs were identified between 500 CRC samples and 44 normal samples. Those PRGs mainly enriched in immune-related and pyroptosis-related pathways. GABRD, NADK, TMEM240, RER1, AGRN, UBE2J2, CALML6, PLCH2, TMEM88B have been identified as gene signature and a prognostic model was constructed and validated. CRC patients with high-risk score showed poor survival, high TMB score, high proportion of CD4 + memory T cells, common lymphoid progenitors, cancer associated fibroblasts, mast cells, and neutrophils. The immune checkpoint related genes, CD160, CD200R1, CD244, CD28, CD40LG, CD44, CD48, CD80, CD86, HHLA2, ICOS, IDO1, TIGIT, TNFRSF25, TNFRSF4, TNFRSF9, TNFSF15, TNFSF18 also increased in high-risk score group. CRC patients with high-risk score more sensitive to docetaxel and rapamycin but resistance to gemcitabine and mitomycin. Moreover, a predictive nomogram for 1-, 3-, 5-year for CRC patients was established and validated. In the study, a PRGs-based prognostic model and a predictive model were constructed. These models are effective and robust in prediction the 1-, 3-, and 5-year survival of CRC patients.

The intricate molecular pathways governing cancer development and progression have spurred intensive investigations into novel therapeutic targets. Glycogen Synthase Kinase-3 (GSK3), a complex serine/threonine kinase, has emerged as a key player with intricate roles in various cellular processes, including cell proliferation, differentiation, apoptosis, and metabolism. Harnessing GSK3 inhibitors as potential candidates for cancer therapy has garnered significant interest due to their ability to modulate key signalling pathways that drive oncogenesis. The review encompasses a thorough examination of the molecular mechanisms underlying GSK3's involvement in cancer progression, shedding light on its interaction with critical pathways such as Wnt/β-catenin, PI3K/AKT, and NF-κB. Through these interactions, GSK3 exerts influence over tumour growth, invasion, angiogenesis, and metastasis, rendering it an attractive target for therapeutic intervention. The discussion includes preclinical and clinical studies, showcasing the inhibitors efficacy across a spectrum of cancer types, including pancreatic, ovarian, lung, and other malignancies. Insights from recent studies highlight the potential synergistic effects of combining GSK3 inhibitors with conventional chemotherapeutic agents or targeted therapies, opening avenues for innovative combinatorial approaches. This review provides a comprehensive overview of the current state of research surrounding GSK3 inhibitors as promising agents for cancer treatment.

To classify bladder cancer based on immune cell infiltration score and to construct a prognosis assessment model of patients with bladder cancer.

The transcriptome data and clinical data of breast cancer patients were obtained from the The Cancer Genome Atlas (TCGA) database. Single sample gene set enrichment analysis was used to calculate the infiltration scores of 16 immune cells. The classification of breast cancer patients was achieved by unsupervised clustering, and the sensitivity of patients with different types to immunotherapy and chemotherapy was analyzed. The key modules significantly related to the infiltration of key immune cells were identified by weighted correlation network analysis (WGCNA), and the key genes in the modules were identified. A risk scoring model and a nomogram for prognosis assessment of bladder cancer patients were constructed and verified.

B cells, mast cells, neutrophils, T helper cells and tumor infiltrating lymphocytes were determined to be the key immune cells of bladder cancer. The patients were clustered into two groups (Cluster 1 ´ and Custer 2) based on immune cell infiltration scores. Compared with patients with Cluster 1 ´, patients with Cluster 2 were more likely to benefit from immunotherapy (P<0.05), and patients with Cluster 2 were more sensitive to Enbeaten, Docetaxel, Cyclopamine, and Akadixin (P<0.05). 35 genes related to key immune cells were screened out by WGCNA and 4 genes (GPR171, HOXB3, HOXB5 and HOXB6) related to the prognosis of bladder cancer were further screened by LASSO Cox regression. The areas under the ROC curve (AUC) of the bladder cancer prognosis risk scoring model based on these 4 genes to predict the 1-, 3- and 5-year survival of patients were 0.735, 0.765 and 0.799, respectively. The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1-, 3-, and 5-year overall survival of bladder cancer patients.

According to the immune cell infiltration score, bladder cancer patients can be classified. Furthermore, bladder cancer prognosis risk scoring model and nomogram based on key immune cell-related genes have high accuracy in predicting the prognosis of bladder cancer patients.

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

RNA Polymerase III Subunit G (POLR3G) promotes tumorigenesis, metastasis, cancer stemness, and chemoresistance of breast cancer and lung cancer; however, its biological function in bladder cancer (BLCA) remains unclear. Through bioinformatic analyses, we found that POLR3G expression was significantly elevated in BLCA tumor tissues and was associated with decreased survival. Multivariate Cox analysis indicated that POLR3G could serve as an independent prognostic risk factor. Our functional investigations revealed that POLR3G deficiency resulted in reduced migration and invasion of BLCA cells both in vitro and in vivo. Additionally, the expressions of EMT-related mesenchymal markers were also downregulated in POLR3G knockdown cells. Mechanistically, we showed that POLR3G could activate the PI3K/AKT signaling pathway. Inhibition of this pathway with LY294002 reduced the enhanced migration and invasion of BLCA cells induced by POLR3G overexpression, whereas the activation of this pathway using 740Y-P restored the abilities that were inhibited by POLR3G knockdown. Taken together, our findings suggested that POLR3G is a prognostic predictor for BLCA and promotes EMT of BLCA through activation of the PI3K/AKT signaling pathway.

Epithelial-mesenchymal transition (EMT) and aberrant energy metabolism are pivotal biological processes in tumor progression, significantly impacting tumor prognosis. However, the relationship between EMT, energy metabolism, and the immune microenvironment in bladder urothelial carcinoma (BLCA) remains inadequately understood.

Bladder cancer samples from The Cancer Genome Atlas were categorized into two groups via clustering analysis to elucidate disparities in expression, prognostic significance, and immune infiltration of genes associated with EMT and energy metabolism between these groups. Key genes associated with EMT and energy metabolism in BLCA were identified through Cox multifactorial regression analysis, immune infiltration analysis, etc. Subsequently, their prognostic significance in BLCA was validated.

Cluster analysis revealed significant differences in the expression of genes associated with EMT and energy metabolism between the two groups. Group 2 exhibited significantly improved overall survival and progression-free survival compared to Group 1. Chondroitin sulfate proteoglycan 4 (CSPG4) emerged as the most critical gene associated with EMT, energy metabolism, prognosis, and immune infiltration in BLCA. Immunohistochemical assays demonstrated differential expression of CSPG4 in bladder tumors and normal bladder tissues, with high CSPG4 expression correlating with a poorer BLCA prognosis. Furthermore, CSPG4 exhibited an association with the immune checkpoint molecule programmed death-1 (PD1) in BLCA.

EMT and energy metabolism exert pivotal influences on the immune microenvironment in BLCA. CSPG4 holds promise as a prognostic biomarker for patients with BLCA, offering valuable insights into potential immunotherapeutic strategies for this patient population.

Cancer was one of the common causes of death in the world, and it was increasing year by year. At present, Progestin and AdipoQ receptor family member 3 (PAQR3) was widely studied in cancer. It has been found that PAQR3 was down regulated in various cancers, such as the gastric cancer, osteosarcoma, glioma, hepatocellular carcinoma, acute lymphoblastic leukemia, laryngeal squamous cell carcinoma, esophageal cancer, breast cancer, non-small cell lung cancer, and colorectal cancer. The decreased expression of PAQR3 was associated with short overall survival and disease-free survival in patients with gastric cancer, hepatocellular carcinoma, laryngeal squamous cell carcinoma, esophageal cancer, breast cancer, and non-small cell lung cancer. PAQR3 could inhibit cancer progression by using the Ras/Raf/MEK/ERK, PI3/AKT, EMT and other mechanisms, and was negatively regulated by the miR-543, miR-15b-5p and miR-15b. The roles and signaling mechanisms of PAQR3, and the relationship between the expression of PAQR3 and prognosis in cancer progression are reviewed in this article, and provides new tumor marker and idea to guide cancer treatment.

To construct a prediction model for the prognosis of bladder cancer patients based on the expression of ion channel-related genes (ICRGs).

ICRGs were obtained from the existing researches. The clinical information and the expression of ICRGs mRNA in breast cancer patients were obtained from the Cancer Genome Atlas database. Cox regression analysis, minimum absolute shrinkage and selection operator regression analysis were used to screen breast cancer prognosis related genes, which were verified by immunohistochemistry and qRT-PCR. The risk scoring equation for predicting the prognosis of patients with bladder cancer was constructed, and the patients were divided into high-risk group and low-risk group according to the median risk score. Immune cell infiltration was compared between the two groups. Kaplan-Meier survival curve and receiver operating characteristic (ROC) curve were used to evaluate the accuracy and clinical application value of the risk scoring equation. The factors related to the prognosis of bladder cancer patients were analyzed by univariate and multivariate Cox regression, and a nomogram for predicting the prognosis of bladder cancer patients was constructed.

By comparing the expression levels of ICRGs in bladder cancer tissues and normal bladder tissues, 73 differentially expressed ICRGs were dentified, of which 11 were related to the prognosis of bladder cancer patients. Kaplan-Meier survival curve suggested that the risk score based on these 11 genes was negatively correlated with the prognosis of patients. The area under the ROC curve of the risk score for predicting the prognosis of patients at 1, 3 and 5 year was 0.634, 0.665 and 0.712, respectively. Stratified analysis showed that the ICRGs-based risk score performed well in predicting the prognosis of patients with American Joint Committee on Cancer (AJCC) stage Ⅲ-Ⅳ bladder cancer (P<0.05), while it had a poor value in predicting the prognosis of patients with AJCC stage Ⅰ-Ⅱ (P>0.05). There were significant differences in the infiltration of plasma cells, activated natural killer cells, resting mast cells and M2 macrophages between the high-risk group and the low-risk group. Cox regression analysis showed that risk score, smoking, age and AJCC stage were independently associated with the prognosis of patients with bladder cancer (P<0.05). The nomogram constructed by combining risk score and clinical parameters has high accuracy in predicting the 1, 3 and 5 year overall survival rate of bladder cancer patients.

The study shows the potential value of ICRGs in the prognostic risk assessment of bladder cancer patients. The constructed prognostic nomogram based on ICRGs risk score has high accuracy in predicting the prognosis of bladder cancer patients.

Structural maintenance of chromosomes protein 1 A (SMC1A) is a crucial subunit of the cohesion protein complex and plays a vital role in cell cycle regulation, genomic stability maintenance, chromosome dynamics. Recent studies demonstrated that SMC1A participates in tumorigenesis. This reseach aims to explore the role and the underlying mechanisms of SMC1A in gastric cancer (GC).

RT-qPCR and western blot were used to examine the expression levels of SMC1A in GC tissues and cell lines. The role of SMC1A on GC cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) were analyzed. Furthermore,the mechanism of SMC1A action was investigated.

SMC1A was highly expressed in GC tissues and cell lines. The high expression of SMC1A indicated the poor overall survival of GC patients from Kaplan-Meier Plotter. Enhancing the expression of SMC1A in AGS cells remarkably promoted cell proliferation in vitro and in vivo, migration and invasion, Conversely, knockdown of SMC1A in HGC27 cells inhibited cell proliferation, migration and invasion. Moreover, it's observed that SMC1A promoted EMT and malignant cell behaviors via regulating SNAIL.

Our study revealed that SMC1A promotes EMT process by upregulating SNAIL, which contributes to gastric cancer cell proliferation, migration and invasion. Therefore, targeting SMC1A may be a potential strategy to improve GC therapy.

In search of an effective therapeutic target for bladder urothelial carcinoma (BLCA), the present study aimed to investigate the expression of cyclin B1 (CCNB1) and its putative mechanism in BLCA. BLCA sequencing data from Gene Expression Omnibus and The Cancer Genome Atlas were used to analyze expression of CCNB1 mRNA and high CCNB1 expression had a poorer prognosis compared with those with low expression. Immunohistochemistry (IHC) samples collected from the Human Protein Atlas database were analyzed for CCNB1 protein expression. Short hairpin (sh) CCNB1-transfected BLCA T24 and 5637 cells were used to investigate the effects of CCNB1 and inhibit the proliferation, migration and invasion of BLCA cells, affect the cell cycle distribution and promote apoptosis of 5637 cells. A sh-CCNB1 BLCA chicken embryo chorioallantoic membrane (CAM) transplantation model was established to observe the impacts of sh-CCNB1 on the tumorigenesis of BLCA in vivo. Analysis of sequencing data showed that CCNB1 mRNA was significantly elevated in tumor and BLCA compared with normal tissues [standardized mean difference (SMD)=1.21; 95% CI: 0.26-2.15; I²=95.9%]. IHC indicated that CCNB1 protein was localized in the nucleus and cytoplasm and was significantly increased in BLCA tumor tissues. The in vitro tests demonstrated that proliferation of T24 and 5637 cells transfected with sh-CCNB1 was significantly inhibited and cell migration and invasion ability were significantly decreased. sh-CCNB1 decreased the percentage of T24 cells in G0/G1, 5637 cells in the G0/G1 phase and S phase and increased percentage of 5637 cells in the G2/M phase and increased early apoptosis of 5637 cells. The in vivo experiments demonstrated that the mass of transplanted tumors was significantly decreased compared with the control group following silencing of CCNB1. The present results suggested that CCNB1 was involve in the development and prognosis of BLCA and silencing of CCNB1 may be a promising targeted therapy for BLCA.