Prognostic value of COL10A1 and its correlation with tumor-infiltrating immune cells in urothelial bladder cancer: A comprehensive study based on bioinformatics and clinical analysis validation.

Bladder cancer (BLCA) is one of the most lethal diseases. COL10A1 is secreted small-chain collagen in the extracellular matrix associated with various tumors, including gastric, colon, breast, and lung cancer. However, the role of COL10A1 in BLCA remains unclear. This is the first research focusing on the prognostic value of COL10A1 in BLCA. In this research, we aimed to uncover the association between COL10A1 and the prognosis, as well as other clinicopathological parameters in BLCA. We obtained gene expression profiles of BLCA and normal tissues from the TCGA, GEO, and ArrayExpress databases. Immunohistochemistry staining was performed to investigate the protein expression and prognostic value of COL10A1 in BLCA patients. GO and KEGG enrichment along with GSEA analyses were performed to reveal the biological functions and potential regulatory mechanisms of COL10A1 based on the gene co-expression network. We used the "maftools" R package to display the mutation profiles between the high and low COL10A1 groups. GIPIA2, TIMER, and CIBERSORT algorithms were utilized to explore the effect of COL10A1 on the tumor immune microenvironment. We found that COL10A1 was upregulated in the BLCA samples, and increased COL10A1 expression was related to poor overall survival. Functional annotation of 200 co-expressed genes positively correlated with COL10A1 expression, including GO, KEGG, and GSEA enrichment analyses, indicated that COL10A1 was basically involved in the extracellular matrix, protein modification, molecular binding, ECM-receptor interaction, protein digestion and absorption, focal adhesion, and PI3K-Akt signaling pathway. The most commonly mutated genes of BLCA were different between high and low COL10A1 groups. Tumor immune infiltrating analyses showed that COL10A1 might have an essential role in recruiting infiltrating immune cells and regulating immunity in BLCA, thus affecting prognosis. Finally, external datasets and biospecimens were used, and the results further validated the aberrant expression of COL10A1 in BLCA samples. In conclusion, our study demonstrates that COL10A1 is an underlying prognostic and predictive biomarker in BLCA.

Wang X ，Bai Y ，Zhang F ，Li D ，Chen K ，Wu R ，Tang Y ，Wei X ，Han P ... -  《Frontiers in Immunology》

TEAD4 functions as a prognostic biomarker and triggers EMT via PI3K/AKT pathway in bladder cancer.

The distant metastasis is the primary cause of cancer morbidity and mortality for bladder cancer (BLCA) paitents. All the recommended therapy for it largely depends on how far the cancer has invaded. It has been confirmed that epithelial to mesenchymal transition (EMT) is the leading reason for the BLCA metastasis which makes BLCA difficult to cure. The aim of the present study is to identify the BLCA-related genes that can be used as the new prognostic biomarker and treatment target, and to investigate the functional mechanisms of TEAD4 in EMT dysregulation. The "limma" R package was used to identify the differentially expressed genes (DEGs) between the normal and the tumor samples from TCGA BLCA and GTEx databases. Kaplan-Meier and UniCox analysis were used to filter DEGs with prognostic value in BLCA. Step muti-Cox analysis was used to construct a prognostic risk score model based on clinical phenotype characters. Gene set enrichment analysis (GSEA) was performed to explore the possible molecular mechanisms affecting the prognosis in BLCA. Unsupervised hierarchical clustering analysis was performed to evaluate the effects of EMT process on the prognosis. Single-sample GSEA (ssGSEA) was used to calculate the correlation betweeen the expression of DEGs and EMT enrichment scores. TEAD4 expression and its association with pathological grading and survival were appraised in samples from TCGA dataset and BLCA tissue microarray. Colony formation assays and CCK8 assays were performed to study the changes in BLCA cell proliferation when the TEAD4 levels was down- or up-regulated in BLCA cells. Transwell and wound healing assays were utilized to analyze the impact of TEAD4 on the invasion and metastasis of the BLCA cells. Western Blot was carried out to detect the changes of EMT-related markers and the active molecules involved in PI3K/AKT signaling in BLCA cells. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was conducted on the genes related to TEAD4 expression. 740Y-P (activator of PI3K/AKT pathway) and LY294002 (inhibitor of PI3K/AKT pathway) were applied to evaluate the contribution of PI3K/AKT signaling pathway in the EMT of BLCA cells. To examine the in vivo effect of TEAD4 on tumor metastasis, we designed a metastatic nude-mouse model by tail vein injection of TEAD4-knockdown BLCA cells. And PET/CT imaging was used to assess the extent of lung metastases. A total of 1592 DEGs were recognized, among which 4 DEGs have been identified as independent prognostic factors for BLCA, such as FASN, IGFL2, PLOD1 and TEAD4. TCGA BLCA samples were divided into significantly different low- and high-risk groups according to the median risk score; GSEA analysis showed that HALLMARK EMT pathway was the top enriched gene signature when compared high-risk and low-risk groups, which was also verified by unsupervised cluster analysis. EMT signature-derived ssGSEA scores demonstrated that TEAD4 had the most positive correlation with EMT process. In addition, TEAD4 expression was upregulated in TCGA BLCA samples and correlated with pT stage, tumor stage and tumor grade. Functional studies showed that TEAD4 knockdown via lentiviral TEAD4 shRNA inhibited cell migration and invasion in vitro and in vivo, with the reduced expression of EMT related markers in BLCA cell lines; the migration and invasion of TEAD4 knockdown cells could be restored by ectopic expression of TEAD4. Meanwhile, KEGG enrichment analysis of genes related to TEAD4 expression showed that enrichment was significantly related to PI3K/AKT pathway. The pathway inhibitor LY294002 blocked the TEAD4-induced enhancement of migration and invasion as well as the expression EMT-related markers, whereas the agonist 740Y-P rescued the decreased migration, invasion and EMT induced by TEAD4 knockdown. TEAD4 is closely correlated with poor prognosis in BLCA and mediates its metastasis through regulating EMT via PI3K/AKT pathway, proving that TEAD4 is not only an effective biomarker for predicting the prognosis but also a great potential target for treatment of metastatic BLCA.

Chi M ，Liu J ，Mei C ，Shi Y ，Liu N ，Jiang X ，Liu C ，Xue N ，Hong H ，Xie J ，Sun X ，Yin B ，Meng X ，Wang B ... -  《JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH》

LIG1 is a novel marker for bladder cancer prognosis: evidence based on experimental studies, machine learning and single-cell sequencing.

Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the precise involvement of LIG1 in BLCA remains elusive. This pioneering investigation delves into the uncharted territory of LIG1's impact on BLCA. Our primary objective is to elucidate the intricate interplay between LIG1 and BLCA, alongside exploring its correlation with various clinicopathological factors. We retrieved gene expression data of para-carcinoma tissues and bladder cancer (BLCA) from the GEO repository. Single-cell sequencing data were processed using the "Seurat" package. Differential expression analysis was then performed with the "Limma" package. The construction of scale-free gene co-expression networks was achieved using the "WGCNA" package. Subsequently, a Venn diagram was utilized to extract genes from the positively correlated modules identified by WGCNA and intersect them with differentially expressed genes (DEGs), isolating the overlapping genes. The "STRINGdb" package was employed to establish the protein-protein interaction (PPI) network.Hub genes were identified through the PPI network using the Betweenness Centrality (BC) algorithm. We conducted KEGG and GO enrichment analyses to uncover the regulatory mechanisms and biological functions associated with the hub genes. A machine-learning diagnostic model was established using the R package "mlr3verse." Mutation profiles between the LIG1^high and LIG1^low groups were visualized using the BEST website. Survival analyses within the LIG1^high and LIG1^low groups were performed using the BEST website and the GENT2 website. Finally, a series of functional experiments were executed to validate the functional role of LIG1 in BLCA. Our investigation revealed an upregulation of LIG1 in BLCA specimens, with heightened LIG1 levels correlating with unfavorable overall survival outcomes. Functional enrichment analysis of hub genes, as evidenced by GO and KEGG enrichment analyses, highlighted LIG1's involvement in critical function such as the DNA replication, cellular senescence, cell cycle and the p53 signalling pathway. Notably, the mutational landscape of BLCA varied significantly between LIG1high and LIG1low groups.Immune infiltrating analyses suggested a pivotal role for LIG1 in immune cell recruitment and immune regulation within the BLCA microenvironment, thereby impacting prognosis. Subsequent experimental validations further underscored the significance of LIG1 in BLCA pathogenesis, consolidating its functional relevance in BLCA samples. Our research demonstrates that LIG1 plays a crucial role in promoting bladder cancer malignant progression by heightening proliferation, invasion, EMT, and other key functions, thereby serving as a potential risk biomarker.

Song DM ，Shen T ，Feng K ，He YB ，Chen SL ，Zhang Y ，Luo WF ，Han L ，Tong M ，Jin Y ... -  《Frontiers in Immunology》

Exploring the Shared Gene Signatures and Molecular Mechanisms between Bladder Urothelial Carcinoma and Metabolic Syndrome.

The aim of this study was to investigate the common gene signatures and potential molecular mechanisms of bladder urothelial carcinoma (BLCA) and metabolic syndrome (MS). Transcriptome data for BLCA and MS were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was utilized to identify co-expression networks associated with BLCA and MS, and five hub genes were further screened and validated using logistic least absolute shrinkage and selection operator (LASSO) regression models and receiver operating characteristic (ROC) curve, and external dataset for validation. The relationship between the hub genes and the clinicopathological characteristics and prognosis of BLCA patients was explored in the GEO and The Cancer Genome Atlas (TCGA)-BLCA cohorts, respectively. Differences in the immune microenvironment of BLCA and MS were analyzed using the database CIBERSORT and the R package "ssGSEA", and the correlation between hub genes and tumor microenvironment, immune score and targeted drugs was analyzed with the help of the TCGA-BLCA cohort. Finally, BLCA single-cell RNA (scRNA) data were used to analyze the expression levels of the hub genes in various cell types of BLCA and molecular mechanisms. Five hub genes were screened by WGCNA and LASSO regression analysis, namely AP2-associated protein kinase 1 (AAK1), ATP-binding cassette subfamily F member 2 (ABCF2), Mitochondrial ribosomal protein L42 (MRPL42), La-related protein 3 (SSB) and TATA-box binding protein-associated factor 10 (TAF10). Analyzed in the GEO and TCGA-BLCA cohorts, we found that the hub genes (TAF10 and ABCF2) were closely associated with the clinicopathological characteristics and prognosis of BLCA patients. In CIBERSORT, we discovered that the hub genes are closely linked to the immune microenvironment, immune score, and especially with dendritic cells (DCs). In the single-cell RNA sequencing (scRNA-seq) analysis of BLCA, we identified that SSB was significantly differentially expressed in BLCA and normal bladder tissues and that it plays an important role in the development of BLCA. The interaction of BLCA with MS may be associated with several cancer pathways being activated and identified TAF10 and ABCF2 as potential biomarkers and therapeutic targets for patients with BLCA and MS.

Li C ，Wan Z ，Deng Q ，Li Z ，Wang Y ... -  《ARCHIVOS ESPANOLES DE UROLOGIA》

Comprehensive Analysis Identified ETV7 as a Potential Prognostic Biomarker in Bladder Cancer.

The tumor microenvironment (TME) plays a crucial role in the initiation and progression of cancer. Bladder cancer (BLCA) is a malignant tumor of the genitourinary system. Its heterogeneity results in significant differences in the prognosis of patients. To date, this is still a huge challenge for clinical treatment. In recent years, more and more evidence showed that dysregulation of transcription factors (TFs) plays an important role in tumor progression, invasion, and metastasis. Unfortunately, the role of TFs on the tumor microenvironment in bladder cancer is unclear. The original data of BLCA and corresponding adjacent tissues were obtained from The Cancer Genome Atlas (TCGA) database. TFs were downloaded from the Animal Transcription Factor DataBase (Animal TFDB). Intersection analysis was used to obtain TFs that were differentially expressed between tumor and adjacent tissues. Gene Set Cancer Analysis (GSCALite) and CIBERSORT software were used to reveal the key differentially expressed TFs (DE-TFs). Subsequently, UALCAN and Human Protein Atlas (HPA) databases were used to disclose the expression of key DE-TFs in BLCA. The K-M curve divulged the relationship between the key DE-TFs and the patient's overall survival (OS), and the univariate and multivariate Cox regression analyses were conducted to explore independent prognostic factors. The cluster profiler package and Gene Set Enrichment Analysis (GSEA) were used for functional enrichment of genes related to the key DE-TFs. Finally, CIBERSORT software analyzed the immune landscape of BLCA. We obtained a total of 117 BLCA-related DE-TFs. Among them, ETV7 was identified as the key DE-TFs due to its association with the autophagy activation pathway and various immune cells in cancer. Online databases of UALCAN and HPA indicated that ETV7 was overexpressed in tumors and negatively correlated with tumor severity. The K-M curve showed that the OS of patients with high expression of ETV7 was poor, which indicated that it was an independent prognostic factor. Functional enrichment of 87 DEGs between ETV7-high and -low expression groups indicated that it was closely related to the immune response and the functions of a variety of immune cells. Finally, CIBERSORT results proved that the high and low expression of ETV7 also caused significant differences in the tumor immune microenvironment of patients. Overall, we proved that the transcription factor ETV7 was a novel prognostic factor, which may improve the individualized outcome prediction in BLCA by regulating the tumor immune microenvironment.

Li H ，Zhang Y ，Zheng S 《-》