An EMT-related gene signature for the prognosis of human bladder cancer

Intersecting pathways: The role of hybrid E/M cells and circulating tumor cells in cancer metastasis and drug resistance

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.

Characterization of the stem cell landscape and identification of a stemness-associated prognostic signature in bladder cancer

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.

A novel grading approach predicts worse outcomes in stage pT1 non-muscle-invasive bladder cancer

OBJECTIVE

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.

PATIENTS AND METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

LRP1 induces anti-PD-1 resistance by modulating the DLL4-NOTCH2-CCL2 axis and redirecting M2-like macrophage polarisation in bladder cancer

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.

Prediction of immunotherapy response of bladder cancer with a pyroptosis-related signature indicating tumor immune microenvironment

Background

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.

Methods

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.

Results

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.

Conclusion

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

Exploring the mystery of colon cancer from the perspective of molecular subtypes and treatment

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.

Predicting bladder cancer survival with high accuracy: insights from MAPK pathway-related genes

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.

PESSA: A web tool for pathway enrichment score-based survival analysis in cancer

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.

Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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

A "One Arrow Three Eagle" Strategy to Improve CM-272 Primed Bladder Cancer Immunotherapy

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.

Identification of FLRT2 as a key prognostic gene through a comprehensive analysis of TMB and IRGPs in BLCA patients

Introduction

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.

Methods and results

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.

Discussion

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.

Prognostic and chemotherapeutic response prediction by proliferation essential gene signature: Investigating POLE2 in bladder cancer progression and cisplatin resistance

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.

Identifying OGN as a Biomarker Covering Multiple Pathogenic Pathways for Diagnosing Heart Failure: From Machine Learning to Mechanism Interpretation

BACKGROUND

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

METHODS

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.

RESULTS

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.

CONCLUSIONS

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

Update on Epithelial-Mesenchymal Plasticity in Cancer Progression

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.

Molecular map of cGAS-STING pathway-related genes in bladder cancer: the perspective toward immune microenvironment and prognosis

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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

Urinary Microbiome Dysbiosis and Immune Dysregulations as Potential Diagnostic Indicators of Bladder Cancer

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.

Single-cell Sequencing Data Reveals Aggressive CD68-type Macrophages and Prognostic Models in Bladder Cancer

BACKGROUND

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

METHODS

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.

RESULTS

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.

CONCLUSION

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.

A Pyroptosis-Related Gene Signature Predicts Prognosis and Tumor Immune Microenvironment in Colorectal Cancer

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.

A review of Glycogen Synthase Kinase-3 (GSK3) inhibitors for cancers therapies

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.

Classification of bladder cancer based on immune cell infiltration and construction of a risk prediction model for prognosis

OBJECTIVES

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

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

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.

POLR3G promotes EMT via PI3K/AKT signaling pathway in bladder cancer

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.

Prognostic significance and immunoinfiltration analysis of genes associated with epithelial-mesenchymal transition and energy metabolism in bladder urothelial carcinoma

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

The Emerging Roles and Mechanisms of PAQR3 in Human Cancer: Pathophysiology and Therapeutic Implications

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.

Construction of a prediction model for prognosis of bladder cancer based on the expression of ion channel-related genes

OBJECTIVES

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

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

SMC1A facilitates gastric cancer cell proliferation, migration, and invasion via promoting SNAIL activated EMT

BACKGROUND

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).

MATERIALS AND METHODS

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.

RESULTS

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.

CONCLUSION

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.

CCNB1 is involved in bladder cancer pathogenesis and silencing CCNB1 decelerates tumor growth and improves prognosis of bladder cancer

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.

A comprehensive analysis of FBN2 in bladder cancer: A risk factor and the tumour microenvironment influencer

Bladder cancer (BLCA) is a common and difficult-to-manage disease worldwide. Most common type of BLCA is urothelial carcinoma (UC). Fibrillin 2 (FBN2) was first discovered while studying Marfan syndrome, and its encoded products are associated with elastin fibres. To date, the role of FBN2 in BLCA remains unclear. The authors first downloaded data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The patients were divided into high FBN2 expression and low FBN2 expression groups, and the survival curve, clinical characteristics, tumour microenvironment (TME), and immune cell differences were analysed between the two groups. Then, the differentially expressed genes (DEGs) were filtered, and functional enrichment for DEGs was performed. Finally, chemotherapy drug susceptibility analysis based on the high and low FBN2 groups was conducted. The authors found upregulated expression of FBN2 in BLCA and proved that FBN2 could be an independent prognostic factor for BLCA. TME analysis showed that the expression of FBN2 affects several aspects of the TME. The upregulated expression of FBN2 was associated with a high stromal score, which may lead to immunosuppression and be detrimental to immunotherapy. In addition, the authors found that NK cells resting, macrophage M0 infiltration, and other phenomena of immune cell infiltration appeared in the high expression group of FBN2. The high expression of FBN2 was related to the high sensitivity of some chemotherapy drugs. The authors systematically investigated the effects and mechanisms of FBN2 on BLCA and provided a new understanding of the role of FBN2 as a risk factor and TME influencer in BLCA.

The Bladder Tumor Microenvironment Components That Modulate the Tumor and Impact Therapy

The tumor microenvironment (TME) is complex and involves many different cell types that seemingly work together in helping cancer cells evade immune monitoring and survive therapy. The advent of single-cell sequencing has greatly increased our knowledge of the cell types present in the tumor microenvironment and their role in the developing cancer. This, coupled with clinical data showing that cancer development and the response to therapy may be influenced by drugs that indirectly influence the tumor environment, highlights the need to better understand how the cells present in the TME work together. This review looks at the different cell types (cancer cells, cancer stem cells, endothelial cells, pericytes, adipose cells, cancer-associated fibroblasts, and neuronal cells) in the bladder tumor microenvironment. Their impact on immune activation and on shaping the microenvironment are discussed as well as the effects of hypertensive drugs and anesthetics on bladder cancer.

Comprehensive analysis of the role of a four-gene signature based on EMT in the prognosis, immunity, and treatment of lung squamous cell carcinoma

Epithelial-mesenchymal transition (EMT), a biological process through which epithelial cells transform into mesenchymal cells, contributes to tumor progression and metastasis. However, a comprehensive analysis of the role of EMT-related genes in Lung squamous cell carcinoma (LUSC) is still lacking. In this study, data were downloaded from available databases, including The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The association between differentially expressed EMT-related genes (EMT-RDGs) and LUSC prognosis, drug sensitivity, mutation, and immunity was analyzed using bioinformatics methods. In the results, Lasso and univariate Cox regression analyses identified four EMT-RDGs that were differentially expressed, and used to establish a prognostic model capable of distinguishing between high- and low-risk groups. Then, prognostic factors were identified by multivariate Cox regression analysis and used to construct a nomogram. The high-risk group had a significantly poorer prognosis than the low-risk group. The tumor immune environment was significantly different between the two groups, with the low-risk group exhibiting a better response to immunotherapy. In addition, the half-maximal inhibitory concentration prediction indicating that the constructed model could effectively predict sensitivity to chemotherapy. This study provides new reference for further exploration of new clinical therapeutic strategies for LUSC.

Epigenetic regulation of hybrid epithelial-mesenchymal cell states in cancer

Epithelial-to-mesenchymal transition (EMT) is a process by which cells lose their epithelial characteristics and gain mesenchymal phenotypes. In cancer, EMT is thought to drive tumor invasion and metastasis. Recent efforts to understand EMT biology have uncovered that cells undergoing EMT attain a spectrum of intermediate "hybrid E/M" states, which exist along an epithelial-mesenchymal continuum. Here, we summarize recent studies characterizing the epigenetic drivers of hybrid E/M states. We focus on the histone-modification writers, erasers, and readers that assist or oppose the canonical hybrid E/M transcription factors that modulate hybrid E/M state transitions. We also examine the role of chromatin remodelers and DNA methylation in hybrid E/M states. Finally, we highlight the challenges of targeting hybrid E/M pharmacologically, and we propose future directions that might reveal the specific and targetable mechanisms by which hybrid E/M drives metastasis in patients.

Bibliometric analysis of the association between drinking water pollution and bladder cancer

Background

Bladder cancer has become an increasingly intractable health problem worldwide. Long-term drinking water pollution is known to promote its occurrence. This study aimed to analyze the research status, hot spots, and future trends of drinking water pollution and bladder cancer through extensive bibliometric examination to provide reference data for better prevention and management of bladder cancer.

Methods

The Scopus database developed by Elsevier was browsed for articles that met the predefined criteria using the search terms related to drinking water and bladder cancer. Included articles were further evaluated by year of publication, subject category, institution, article type, source journal, authors, co-authorship networks, and text mining of titles by R software packages tm, ggplot2 and VOSviewer software.

Results

In total, 687 articles were selected after a comprehensive literature search by the Scopus database, including 491 research articles, 98 review articles, 26 conference papers, 23 letters and 49 other documents. The total number of articles published showed an upward trend. The United States has the largest number of published articles (345 articles), institutions (7/10) and funding sponsors (top 5). The journal with the most publications was Environmental Health Perspectives, with 46 published. The highest number of citations up to 2330 times for a single article published in 2007 on the journal of Mutation Research. Professor Cantor K.P. was the highest number of publications with 35 articles and Smith A.H. was the most cited author with the number of citations reaching 6987 times overall and 225 times per article. The most frequent keywords excluding the search subject were "arsenic", "chlorination", "trihalomethane", and "disease agents".

Conclusion

This study is the first systematic bibliometric study of the literature publications on drinking water pollution and bladder cancer. It offers an overall and intuitive understanding of this topic in the past few years, and points out a clear direction research hotspots and reveals the trends for further in-depth study in future.

YTHDF1 Promotes Bladder Cancer Cell Proliferation via the METTL3/YTHDF1-RPN2-PI3K/AKT/mTOR Axis

N6-methyladenosine (m6A) is the most common mRNA modification and it plays a critical role in tumor progression, prognoses and therapeutic response. In recent years, more and more studies have shown that m6A modifications play an important role in bladder carcinogenesis and development. However, the regulatory mechanisms of m6A modifications are complex. Whether the m6A reading protein YTHDF1 is involved in the development of bladder cancer remains to be elucidated. The aims of this study were to determine the association between METTL3/YTHDF1 and bladder cancer cell proliferation and cisplatin resistance to explore the downstream target genes of METTL3/YTHDF1 and to explore the therapeutic implications for bladder cancer patients. The results showed that the reduced expression of METTL3/YTHDF1 could lead to decreased bladder cancer cell proliferation and cisplatin sensitivity. Meanwhile, overexpression of the downstream target gene, RPN2, could rescue the effect of reduced METTL3/YTHDF1 expression on bladder cancer cells. In conclusion, this study proposes a novel METTL3/YTHDF1-RPN2-PI3K/AKT/mTOR regulatory axis that affects bladder cancer cell proliferation and cisplatin sensitivity.

Incidence and prognostic nomogram for resected non-small cell neuroendocrine tumor: A population-based respective study in China and the SEER database

Background

Pulmonary neuroendocrine tumors, including small cell lung cancer (SCLC) and non-small cell neuroendocrine tumor (NSCLC-NET), have obvious heterogeneity. The comparison between SCLC and NSCLC-NET, and prognostic nomogram of resected NSCLC-NET have not been performed.

Methods

We retrieved data from SEER database. The incidence and prognostic factors were compared between SCLC and NSCLC-NET. By Cox regression, we constructed prognostic nomogram of resected NSCLC-NET. The nomogram was evaluated by ROC, calibration plot and decision curve analysis (DCA) and compared with 8th TNM staging system. A Chinese cohort was used for external validation.

Results

The age-adjusted incidence of SCLC declined after 1991 but the incidence of NSCLC-NET continuously rose. Patients with typical carcinoid had the best prognosis in both overall survival and lung cancer specific survival, followed by atypical carcinoid, large cell neuroendocrine tumor and SCLC after operation. Patients receiving sleeve resection in NSCLC-NET had longer survival but segmental resection was more recommended in SCLC. High-smoking index was associated with worse overall survival in both SCLC and NSCLC-NET. Histological subtype, age, surgery type, N, M stage and chemotherapy were independent prognostic factors and used to construct prognostic nomogram of resected NSCLC-NET. The nomogram performed well with good discrimination, calibration and clinical usefulness, which was validated by a Chinese cohort (1, 3, 5-year AUC: SEER cohort 0.873, 0.901, 0.875; Chinese cohort 0.867, 0.892, 0.874). Compared to the 8th staging system, the nomogram had higher C-index (0.87 vs 0.728, P < 0.001), clinical usefulness, increasing AUC value over time and improved 68%.

Conclusion

The prognostic nomogram of resected NSCLC-NET performed better than the 8th TNM staging system. It may have certain value in risk stratification and survival prediction of patients with resected NSCLC-NET and help clinicians to take measures for high-risk patients in advance.

Noncoding RNAs as a potential biomarker for the prognosis of bladder cancer: a systematic review and meta-analysis

OBJECTIVE

The relationship between noncoding RNAs and the prognosis of bladder cancer (BC) is still controversial. The purpose of this study is to evaluate the relationship between noncoding RNAs and prognosis by meta-analysis.

METHODS

Comprehensive retrieval of PubMed, Embase, the Cochrane Library, the Web of Science, CNKI, and WanFang databases is related to the correlation between noncoding RNAs and the prognosis of BC. Data were extracted, and the literature quality was evaluated. STATA16.0 served for the meta-analysis.

RESULTS

1. CircRNAs: High circ-ZFR expression led to poor overall survival (OS) of BC. 2. LncRNAs: Low lnc-GAS5 expression predicted poor OS of BC, high lnc-TUG1 expression predicted poor OS of BC. 3. MiRNAs: High miR-21 expression predicted poor OS of BC, high miR-222 expression led to poor OS of BC, high miR-155 expression predicted poor progression-free survival (PFS) of BC, high miR-143 expression caused poor PFS of BC, low miR-214 expression could result in poor recurrence-free survival (RFS) of BC.

CONCLUSIONS

High circ-ZFR, lnc-TUG1, miR-222, and miR-21 expressions were correlated with poor OS of BC; high miR-155 and miR-143 expression predicted poor PFS of BC; low lnc-GAS5 expression predicted poor OS of BC; low miR-214 expression predicted poor RFS of BC.

High expression of ABCF1 is an independent predictor of poor prognosis in bladder cancer

ABCF1, a member of the ATP-binding cassette (ABC) transporter family, is involved in the malignant progression of tumors. However, the role of ABCF1 in bladder cancer is poorly understood. In our study, we explored the differential expression of ABCF1 in bladder cancer and normal bladder tissues based on bioinformatic analysis and immunohistochemical results. GSEA was performed to ascertain the potential related signaling pathways of ABCF1. The relationship between ABCF1 expression and bladder cancer progression was analyzed using the GSE13507 dataset. In addition, the differential expression of ABCF1 in the cell lines was verified by quantitative real-time polymerase chain reaction (qRT‒PCR) and Western blotting. ABCF1 was upregulated in bladder cancer, and the high expression of ABCF1 was closely related to sex (P = 0.00056), grade (P = 0.00049), T stage (P = 0.00007), and N stage (P = 0.0076). High expression of ABCF1 was correlated with poor overall survival in bladder cancer patients (P < 0.001). In addition, univariate and multivariate Cox regression analyses showed that high ABCF1 expression was an independent factor for poor prognosis in bladder cancer patients. Therefore, ABCF1 expression is closely related to the progression of bladder cancer and can be used as a potential indicator of poor prognosis and a therapeutic target for bladder cancer.

Prediction of immune infiltration and prognosis for patients with urothelial bladder cancer based on the DNA damage repair-related genes signature

Objectives

To analyze the correlations between the expression and effect of DNA damage repair genes and the immune status and clinical outcomes of urothelial bladder cancer (BLCA) patients. In addition, we evaluate the efficacy and value of utilizing the DNA damage repair genes signature as a prognosis model for BLCA.

Methods

Two subtype groups (C1 and C2) were produced based on the varied expression of DNA damage repair genes. Significantly differentiated genes and predicted enriched gene pathways were obtained between the two subtypes. Seven key genes were obtained from the DNA damage repair-related genes and a 7-gene signature prognosis model was established based on the key genes. The efficacy and accuracy of this model in prognosis prediction was evaluated and verified in two independent databases. Also, the difference in biological functions, drug sensitivity, immune infiltration and affinity between the high-risk group and low-risk group was analyzed.

Results

The DNA damage repair gene signature could significantly differentiate the BLCA into two molecular subgroups with varied genetic expression and enriched gene pathways. Seven key genes were screened out from the 232 candidate genes for prognosis prediction and a 7-gene signature prognosis model was established based on them. Two independent patient cohorts (TCGA cohort and GEO cohort) were utilized to validate the efficacy of the prognosis model, which demonstrated an effective capability to differentiate and predict the overall survival of BLCA patients. Also, the high-risk group and low-risk group derived from the 7-gene model exhibited significantly differences in drug sensitivity, immune infiltration status and biological pathways enrichment.

Conclusions

Our established 7-gene signature model based on the DNA damage repair genes could serve as a novel prognosis predictive tool for BLCA. The differentiation of BLCA patients based on the 7-gene signature model may be of great value for the appropriate selection of specific chemotherapy agents and immune-checkpoint blockade therapy administration.

Urinary Eubacterium sp. CAG:581 Promotes Non-Muscle Invasive Bladder Cancer (NMIBC) Development through the ECM1/MMP9 Pathway

BACKGROUND

Increasing evidence points to the urinary microbiota as a possible key susceptibility factor for early-stage bladder cancer (BCa) progression. However, the interpretation of its underlying mechanism is often insufficient, given that various environmental conditions have affected the composition of urinary microbiota. Herein, we sought to rule out confounding factors and clarify how urinary Eubacterium sp. CAG:581 promoted non-muscle invasive bladder cancer (NMIBC) development.

METHODS

Differentially abundant urinary microbiota of 51 NMIBC patients and 47 healthy controls (as Cohort 1) were first determined by metagenomics analysis. Then, we modeled the coculture of NMIBC organoids with candidate urinary Eubacterium sp. CAG:581 in anaerobic conditions and explored differentially expressed genes of these NMIBC tissues by RNA-Seq. Furthermore, we dissected the mechanisms involved into Eubacterium sp. CAG:581 by inducing extracellular matrix protein 1 (ECM1) and matrix metalloproteinase 9 (MMP9) upregulation. Finally, we used multivariate Cox modeling to investigate the clinical relevance of urinary Eubacterium sp. CAG:581 16S ribosomal RNA (16SrRNA) levels to the prognosis of 406 NMIBC patients (as Cohort 2).

RESULTS

Eubacterium sp. CAG:581 infection accelerated the proliferation of NMIBC organoids (p < 0.01); ECM1 and MMP9 were the most upregulated genes induced by the increased colony forming units (CFU) gradient of Eubacterium sp. CAG:581 infection via phosphorylating ERK1/2 in NMIBC organoids of Cohort 1. Excluding the favorable impact of potential contributing factors, the ROC curve of Cohort 2 manifested its 3-year AUC value as 0.79 and the cut-off point of Eubacterium sp. CAG:581 16SrRNA as 10.3 (delta CT value).

CONCLUSION

Our evidence suggests that urinary Eubacterium sp. CAG:581 promoted NMIBC progression through the ECM1/MMP9 pathway, which may serve as the promising noninvasive diagnostic biomarker for NMIBC.

Tumor microenvironment and epithelial-mesenchymal transition in bladder cancer: Cytokines in the game?

Bladder cancer (BlCa) is a highly immunogenic cancer. Bacillus Calmette-Guérin (BCG) is the standard treatment for non-muscle invasive bladder cancer (NMIBC) patients and, recently, second-line immunotherapies have arisen to treat metastatic BlCa patients. Understanding the interactions between tumor cells, immune cells and soluble factors in bladder tumor microenvironment (TME) is crucial. Cytokines and chemokines released in the TME have a dual role, since they can exhibit both a pro-inflammatory and anti-inflammatory potential, driving infiltration and inflammation, and also promoting evasion of immune system and pro-tumoral effects. In BlCa disease, 70-80% are non-muscle invasive bladder cancer, while 20-30% are muscle-invasive bladder cancer (MIBC) at the time of diagnosis. However, during the follow up, about half of treated NMIBC patients recur once or more, with 5-25% progressing to muscle-invasive bladder cancer, which represents a significant concern to the clinic. Epithelial-mesenchymal transition (EMT) is one biological process associated with tumor progression. Specific cytokines present in bladder TME have been related with signaling pathways activation and EMT-related molecules regulation. In this review, we summarized the immune landscape in BlCa TME, along with the most relevant cytokines and their putative role in driving EMT processes, tumor progression, invasion, migration and metastasis formation.

Prognostic value of genes related to cancer-associated fibroblasts in lung adenocarcinoma

BACKGROUND

Although it has been established that cancer-associated fibroblasts (CAFs) facilitate tumor development, the relationship between CAFs and the prognosis of patients with lung adenocarcinoma (LUAD) has not been extensively explored.

OBJECTIVE

This study was formulated to investigate the prognostic value of CAF-related genes in LUAD.

METHODS

Differential analysis was carried out with TCGA-LUAD dataset as the training set. By overlapping differentially expressed genes (DEGs) with genes associated with CAF, CAF-related DEGs specific to LUAD were obtained. A prognostic risk model was constructed by Lasso and Cox regression analysis, and samples were grouped according to median risk score. The efficacy of the model was accessed through survival curve and receiver operating characteristic curve (ROC) analyses, with the validation set for verification. Risk score combined with clinical factors was utilized for Cox analysis to verify the independence of the model, and a nomogram was drawn. GSEA was performed on different risk groups. Immunologic infiltration and tumor mutational burden were assessed in different risk groups.

RESULTS

Eleven feature genes including DLGAP5, KCNE2, UPK2, NPAS2, ARHGAP11A, ANGPTL4, ANLN, DKK1, SMUG1, C16orf74, and ACAD8 were identified, based on which a prognostic model was constructed. Risk score could predict the prognosis of LUAD patients and could be an independent prognostic factor for LUAD patients. GSEA outcomes displayed significant enrichment of genes in the high-risk group in the P53 SIGNALING PATHWAY. In comparison to the low-risk group, the high-risk group exhibited a decreased degree of immune infiltration and an elevated level of tumor mutational burden.

CONCLUSION

An 11-gene model was constructed based on CAF-related genes to predict LUAD prognosis. This model represented an independent prognostic factor for LUAD.

An Overview of Epithelial-to-Mesenchymal Transition and Mesenchymal-to-Epithelial Transition in Canine Tumors: How Far Have We Come?

Historically, pre-clinical and clinical studies in human medicine have provided new insights, pushing forward the contemporary knowledge. The new results represented a motivation for investigators in specific fields of veterinary medicine, who addressed the same research topics from different perspectives in studies based on experimental and spontaneous animal disease models. The study of different pheno-genotypic contexts contributes to the confirmation of translational models of pathologic mechanisms. This review provides an overview of EMT and MET processes in both human and canine species. While human medicine rapidly advances, having a large amount of information available, veterinary medicine is not at the same level. This situation should provide motivation for the veterinary medicine research field, to apply the knowledge on humans to research in pets. By merging the knowledge of these two disciplines, better and faster results can be achieved, thus improving human and canine health.

A tumor microenvironment preoperative nomogram for prediction of lymph node metastasis in bladder cancer

Background

Growing evidence suggests that tumor metastasis necessitates multi-step microenvironmental regulation. Lymph node metastasis (LNM) influences both pre- and post-operative bladder cancer (BLCA) treatment strategies. Given that current LNM diagnosis methods are still insufficient, we intend to investigate the microenvironmental changes in BLCA with and without LNM and develop a prediction model to confirm LNM status.

Method

"Estimation of Stromal and Immune cells in Malignant Tumors using Expression data" (ESTIMATE) algorithm was used to characterize the tumor microenvironment pattern of TCGA-BLCA cohort, and dimension reduction, feature selection, and StrLNM signature construction were accomplished using least absolute shrinkage and selection operator (LASSO) regression. StrLNM signature was combined with the genomic mutation to establish an LNM nomogram by using multivariable logistic regression. The performance of the nomogram was evaluated in terms of calibration, discrimination, and clinical utility. The testing set from the TCGA-BLCA cohort was used for internal validation. Moreover, three independent cohorts were used for external validation, and BLCA patients from our cohort were also used for further validation.

Results

The StrLNM signature, consisting of 22 selected features, could accurately predict LNM status in the TCGA-BLCA cohort and several independent cohorts. The nomogram performed well in discriminating LNM status, with the area under curve (AUC) of 75.1% and 65.4% in training and testing datasets from the TCGA-BLCA cohort. Furthermore, the StrLNM nomogram demonstrated good calibration with p >0.05 in the Hosmer-Lemeshow goodness of fit test. Decision curve analysis (DCA) revealed that the StrLNM nomogram had a high potential for clinical utility. Additionally, 14 of 22 stably expressed genes were identified by survival analysis and confirmed by qPCR in BLCA patient samples in our cohort.

Conclusion

In summary, we developed a nomogram that included an StrLNM signature and facilitated the preoperative prediction of LNM status in BLCA patients.

A risk score for the prognosis prediction of the muscle-invasive bladder cancer patients who received gemcitabine plus cisplatin chemotherapy

To develop an individualized gene-based risk score to predict the prognosis of muscle-invasive bladder cancer (MIBC) patients who received GC regimens. We downloaded transcriptome profiling data and clinical information from the Cancer Genome Atlas (TCGA) database. We identified 1854 survival-associated genes and then constructed the risk score based on six special genes selected from the survival-associated genes. We divided patients into high-risk and low-risk groups according to the median risk score. High-risk patients have significantly poorer overall survival than low-risk patients (log-rank test chi-square = 38.08, p = 7e-10, C-index = 0.785, se = 0.032). The risk score was evaluated by Kaplan-Meier survival curve, time-dependent ROC curves, and C-index. Multivariate Cox regression and nomogram suggested that the risk score was an independent prognostic indicator. Gene set enrichment analysis indicated that the survival-associated genes were significantly enriched in immune-related terms. Among six special genes, CHPF2, TRAV26-2, and BTF3P12 were found to be immune-related genes. In conclusion, our risk score provided an indicator to predict the prognosis of MIBC patients who received GC regimens and potential immunotherapeutic targets for MIBC.

Prognostic values of the immune microenvironment-related non-coding RNA IGF2BP2-AS1 in bladder cancer

Bladder cancer can range from noninvasive to invasive tumors. When non-muscle invasive bladder cancer (NMIBC) recurs, patients could endure long-term invasive malignancies with a high disease-specific death rate. Immune escape frequently results in tumor development, metastases, unfavorable prognosis, and failure of immunotherapy. Based on the median immune score, this study used ESTIMATE scores to evaluate 411 bladder cancer cases from TCGA-BLCA. Two hundred two ncRNAs were differentially expressed in two groups, where 29 candidates appeared to be associated with the overall survival of bladder cancer patients. LASSO algorithm was performed to establish the risk score model of 13-ncRNA. Risk scores were computed for cases in the training set, validation set, and TCGA-BLCA set; Poor prognosis in cases with higher risk scores was based on the training set, validating set, and TCGA-BLCA set. Among the 13 ncRNAs, IGF2BP2-AS1, MAGF-AS1, ARHGAP5-AS1, and LINC00942 were significantly correlated with the overall survival of bladder cancer patients. Pearson's correlation analysis based on TCGA-BLCA identified 2093, 3107, 386, and 936 mRNAs co-expressed with IGF2BP2-AS1, MAGF-AS1, ARHGAP5-AS1, and LINC00942, respectively. Conclusively, the 13 ncRNA signature exhibited a feasible predictive prognostic value for bladder cancer patients. IGF2BP2-AS1 expression was higher in bladder cancer tissues and significantly correlated to immune-related factors, suggesting that IGF2BP2-AS1 represents a promising immune-related target for treating bladder cancer patients.

Fucoidan from Sargassum hemiphyllum inhibits the stemness of cancer stem cells and epithelial-mesenchymal transitions in bladder cancer cells

A variety of anticancer activities have been established for fucoidan from brown algae, whereas whether cancer stem cells (CSCs) are inhibited by sulfated polysaccharides is unexplored. In this study, fucoidan extracted from Sargassum hemiphyllum was showed heat stable and might tolerate 140 °C treatment. Fucoidan did not exhibit cytotoxicity in 5637 and T24 bladder cancer cells. After fucoidan treatment, the stress fibers were aggregated into thick and abundant underneath the plasma membrane and getting around the cells, and the structure of F-actin showed a remarkable change in the filopodial protrusion in T24 and 5637 cells. Using culture inserts, transwell assays and time lapse recordings showed that fucoidan inhibited cell migration. In the epithelial-mesenchymal transition (EMT), fucoidan downregulated the expression of vimentin, a mesenchymal marker, and upregulated the expression of E-cadherin, an epithelial marker. Additionally, the transcription levels of Snail, Slug, Twist1, Twist2, MMP2 and MMP9 were significantly decreased by fucoidan, indicating EMT suppression. CSCs are implicated in tumor initiation, metastatic spread, drug resistance and tumor recurrence. Our results showed that fucoidan inhibited stemness gene expression and sphere formation in bladder CSCs. For the first time, our findings demonstrated that fucoidan inhibits CSC formation and provides evidence as potential anticancer therapy.

Characterization of Epithelial-Mesenchymal Transition Identifies a Gene Signature for Predicting Clinical Outcomes and Therapeutic Responses in Bladder Cancer

Purpose. The complex etiological variables and high heterogeneity of bladder cancer (BC) make prognostic prediction challenging. We aimed to develop a robust and promising gene signature using advanced machine learning methods for predicting the prognosis and therapy responses of BC patients. Methods. The single-sample gene set enrichment analysis (ssGSEA) algorithm and univariable Cox regression were used to identify the primary risk hallmark among the various cancer hallmarks. Machine learning methods were then combined with survival and differential gene expression analyses to construct a novel prognostic signature, which would be validated in two additional independent cohorts. Moreover, relationships between this signature and therapy responses were also identified. Functional enrichment analysis and immune cell estimation were also conducted to provide insights into the potential mechanisms of BC. Results. Epithelial-mesenchymal transition (EMT) was identified as the primary risk factor for the survival of BC patients (HR=1.43, 95% CI: 1.26-1.63). A novel EMT-related gene signature was constructed and validated in three independent cohorts, showing stable and accurate performance in predicting clinical outcomes. Furthermore, high-risk patients had poor prognoses and multivariable Cox regression analysis revealed this to be an independent risk factor for patient survival. CD8+ T cells, Tregs, and M2 macrophages were found abundantly in the tumor microenvironment of high-risk patients. Moreover, it was anticipated that high-risk patients would be more sensitive to chemotherapeutic drugs, while low-risk patients would benefit more from immunotherapy. Conclusions. We successfully identified and validated a novel EMT-related gene signature for predicting clinical outcomes and therapy responses in BC patients, which may be useful in clinical practice for risk stratification and individualized treatment.

Prognosis Risk Model Based on Necroptosis-Related Signature for Bladder Cancer

Background: Bladder cancer(BLCA) is the ninth most common cancer. In recent years, necroptosis was found to be related to the occurrence and development of tumors. In this study, we aimed to construct a model based on a necroptosis-related signature to evaluate the potential prognostic application in BLCA. Methods: A total of 67 necroptosis-related genes were used to select the ideal cluster numbers, and it was found that there were four necroptosis-related patterns. Then, we compared the gene expression levels among all of the groups and established a necroptosis-related prognostic model. We made the following enrichment analysis of function and built a novel scoring system, the NEC score, to evaluate the state of necroptosis according to the expression level of necroptosis-related genes. Results: A total of 67 necroptosis-related genes were used to define four distinct necroptosis-related patterns: NEC cluster1–4. Each NEC cluster exhibited different patterns of survival and immune infiltration. Based on univariate Cox regression analyses and least absolute shrinkage and selection operator (Lasso) regression, 14 necroptosis-related genes were established to develop the NEC score. Patients were divided into two groups based on the NEC score. Patients in the high NEC score group had a significantly poorer overall survival than those in the low NEC score group. We further confirmed the correlation of clinical characteristics, as well as the immunotherapy outcome, with the NEC score, and confirmed the potential of the NEC score to be an independent prognostic factor. Furthermore, we compared the expression levels of eight potential biomarker genes between our own BLCA tissues and para-carcinoma tissue. Conclusion: We developed a novel NEC score that has a potential prognostic value in BLCA patients and may help personalized immunotherapy counselling.

A novel cuproptosis-related lncRNA signature predicts the prognosis and immune landscape in bladder cancer

Background

Bladder cancer (BLCA) is one of the deadliest diseases, with over 550,000 new cases and 170,000 deaths globally every year. Cuproptosis is a copper-triggered programmed cell death and is associated with the prognosis and immune response of various cancers. Long non-coding RNA (lncRNA) could serve as a prognostic biomarker and is involved in the progression of BLCA.

Methods

The gene expression profile of cuproptosis-related lncRNAs was analyzed by using data from The Cancer Genome Atlas. Cox regression analysis and least absolute shrinkage and selection operator analysis were performed to construct a cuproptosis-related lncRNA prognostic signature. The predictive performance of this signature was verified by ROC curves and a nomogram. We also explored the difference in immune-related activity, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE), and drug sensitivity between the high- and low-risk groups.

Results

We successfully constructed a cuproptosis-related lncRNA prognostic signature for BLCA including eight lncRNAs (RNF139-AS1, LINC00996, NR2F2-AS1, AL590428.1, SEC24B-AS1, AC006566.1, UBE2Q1-AS1, and AL021978.1). Multivariate Cox analysis suggested that age, clinical stage, and risk score were the independent risk factors for predicting prognosis of BLCA. Further analysis revealed that this signature not only had higher diagnostic efficiency compared to other clinical features but also had a good performance in predicting the 1-year, 3-year, and 5-year overall survival rate in BLCA. Notably, BLCA patients with a low risk score seemed to be associated with an inflamed tumor immune microenvironment and had a higher TMB level than those with a high risk score. In addition, patients with a high risk score had a higher TIDE score and a higher half maximal inhibitory concentration value of many therapeutic drugs than those with a low risk score.

Conclusion

We identified a novel cuproptosis-related lncRNA signature that could predict the prognosis and immune landscape of BLCA.

A novel focal adhesion-related risk model predicts prognosis of bladder cancer —— a bioinformatic study based on TCGA and GEO database

Background

Bladder cancer (BLCA) is the ninth most common cancer globally, as well as the fourth most common cancer in men, with an incidence of 7%. However, few effective prognostic biomarkers or models of BLCA are available at present.

Methods

The prognostic genes of BLCA were screened from one cohort of The Cancer Genome Atlas (TCGA) database through univariate Cox regression analysis and functionally annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The intersecting genes of the BLCA gene set and focal adhesion-related gene were obtained and subjected to the least absolute shrinkage and selection operator regression (LASSO) to construct a prognostic model. Gene set enrichment analysis (GSEA) of high- and low-risk patients was performed to explore further the biological process related to focal adhesion genes. Univariate and multivariate Cox analysis, receiver operating characteristic (ROC) curve analysis, and Kaplan–Meier survival analysis (KM) were used to evaluate the prognostic model. DNA methylation analysis was presented to explore the relationship between prognosis and gene methylation. Furthermore, immune cell infiltration was assessed by CIBERSORT, ESTIMATE, and TIMER. The model was verified in an external GSE32894 cohort of the Gene Expression Omnibus (GEO) database, and the Prognoscan database presented further validation of genes. The HPA database validated the related protein level, and functional experiments verified significant risk factors in the model.

Results

VCL, COL6A1, RAC3, PDGFD, JUN, LAMA2, and ITGB6 were used to construct a prognostic model in the TCGA-BLCA cohort and validated in the GSE32894 cohort. The 7-gene model successfully stratified the patients into both cohorts’ high- and low-risk groups. The higher risk score was associated with a worse prognosis.

Conclusions

The 7-gene prognostic model can classify BLCA patients into high- and low-risk groups based on the risk score and predict the overall survival, which may aid clinical decision-making.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10264-5.