Background: Stem cells characterized by self-renewal and therapeutic resistance play crucial roles in bladder cancer (BLCA). However, the genes modulating the maintenance and proliferation of BLCA stem cells are still unclear. In this study, we aimed to characterize the expression of stem cell-related genes in BLCA. Methods: The mRNA expression-based stemness index (mRNAsi) of The Cancer Genome Atlas (TCGA) was evaluated and corrected by tumor purity. Corrected mRNAsi were further analyzed with regard to muscle-invasive bladder cancer molecular subtypes, survival analysis, pathological staging characteristics, and outcomes after primary treatment. Next, weighted gene co-expression network analysis was used to find modules of interest and key genes. Functional enrichment analysis was performed to functionally annotate the modules and key genes. The expression levels of key genes in all cancers were validated using Oncomine and Gene Expression Omnibus (GEO) database containing molecular subtypes in BLCA. Protein interaction networks were used to identify upstream genes, and the relationships between genes were analyzed at the protein and transcription levels. Findings: mRNAsi was significantly upregulated in cancer tissues. Corrected mRNAsi in BLCA increased as tumor stage increased, with T3 having the highest stem cell characteristics. Lower corrected mRNAsi scores had better overall survival and treatment outcome. The modules of interest and key genes were determined based on topological overlap measurement clustering results and the inclusion criteria. For 13 key genes ( AURKA, BUB1B, CDCA5, CDCA8, KIF11, KIF18B, KIF2C, KIFC1, KPNA2, NCAPG, NEK2, NUSAP1 , and RACGAP1 ), enriched gene ontology terms related to cell proliferation (e.g., mitotic nuclear division, spindle, and microtubule binding) were determined. Their expression did not differ according to the pathological stages of BLCA, and these genes were clearly overexpressed in many types of cancers. In GEO database, the expression levels of 13 key genes were higher in basal subtype with the highest stem cell characteristics than in luminal and its subtypes. AURKB and PLK1 may be regulated upstream of other key genes, and the key genes were found to be strongly correlated with each other and with upstream genes. Interpretation: The 13 key genes identified in this study were found to play important roles in the maintenance of BLCA stem cells. Controlling the upstream genes AURKB and PLK1 may have applications in the treatment of BLCA. These genes may act as therapeutic targets for inhibiting the stemness characteristics of BLCA.

Background: Bladder urothelial cancer (BLCA) treatment using immune checkpoint inhibitors (IMCIs) can result in long-lasting clinical benefits. However, only a fraction of patients respond to such treatment. In this study, we aimed to identify the relationships between immune cell infiltration levels (ICILs) and IMCIs and identify markers for ICILs.Methods: ICILs were estimated based on single-sample gene set enrichment analysis. The response rates of different ICILs to IMCIs were calculated by combining the ICILs of molecular subtypes in BLCA with the response rates of different molecular subtypes of IMvigor 210 trials to a programmed cell death ligand-1 inhibitor. Weighted gene co-expression network analysis was used to identify modules of interest with ICILs. Functional enrichment analysis was performed to functionally annotate the modules. Screening of key genes and unsupervised clustering were used to identify candidate biomarkers. Tumor IMmune Estimation Resource was used to validate the relationships between the biomarkers and ICILs. Finally, we verified the expression of key genes in molecular subtypes of different response rates for IMCIs.Findings: The basal squamous subtype and luminal infiltrated subtype, which showed low response rates for IMCIs, had the highest levels of immune infiltration. The neuronal subtypes, which showed the highest response rates to IMCIs, had low ICILs. The modules of interest and key genes were determined based on topological overlap measurement, clustering results, and inclusion criteria. Modules highly correlated with ICILs were mainly enriched in immune responses and epithelial–mesenchymal transition. After screening the key genes in the modules, five candidate biomarkers (CD48, SEPT1, ACAP1, PPP1R16B, and IL16) were selected by unsupervised clustering. The key genes were inversely associated with tumor purity and were mostly expressed in the basal squamous subtype and luminal infiltrated subtypes.Interpretation: Patients with high ICILs may benefit the least from treatment with IMCIs. Five key genes could predict ICILs in BLCA, and their high expression suggested that the response rate to IMCIs may decrease.

Recent cancer studies have found that the netrin family of proteins plays vital roles in the development of some cancers. However, the functions of the many variants of these proteins in cancer remain incompletely understood. In this work, we used the most comprehensive database available, including more than 10000 samples across more than 30 tumor types, to analyze the six members of the netrin family. We performed comprehensive analysis of genetic change and expression of the netrin genes and analyzed epigenetic and pathway relationships, as well as the correlation of expression of these proteins with drug sensitivity. Although the mutation rate of the netrin family is low in pan-cancer, among the tumor patients with netrin mutations, the highest number are Uterine Corpus Endometrial Carcinoma patients, accounting for 13.6% of cases (54 of 397). Interestingly, the highest mutation rate of a netrin family member is 38% for NTNG1 (152 of 397). Netrin proteins may participate in the development of endocrine-related tumors and sex hormone-targeting organ tumors. Additionally, the participation of NTNG1 and NTNG2 in various cancers shows their potential for use as new tumor markers and therapeutic targets. this analysis provides a broad molecular perspective of this protein family and suggests some new directions for the treatment of cancer. Cytokines, growth factors, angiogenic factors, and extracellular proteases are secreted to the outside of the cell to produce biological functions 1. These secreted proteins participate in the immune regulation of chronic inflammation 2,3 and the occurrence of lipid metabolism diseases 4 , but also play important roles in tumor invasion, metastasis, immunity, and drug resistance 5-8. For example, CD317 and EGFR are secreted proteins that are potential diagnostic markers for non-small cell lung cancer 9. CD63 is secreted by melanoma into the blood and can be used as a protein marker 10. HGF inhibits the treatment of RAF inhibitors of BRAF mutant melanoma 11. The netrins are neuroguiding factors with axonal guiding function, and are similar to laminin in structure. Netrins were first discovered in C. elegans in 1990 12 , and this family of proteins includes the secreted proteins Netrin-1 (NTN1), Netrin-3 (NTN3), Netrin-4 (NTN4), and Netrin-5 (NTN5). The secreted proteins have a common domain structure, with an N-terminal laminin repeat (Laminin N-terminal), three cysteine-rich EGF modules (V-1, V-2, and V-3), and a positively charged C-terminal domain (NTR) 13. The netrin family also includes two membrane-binding proteins, Netrin-G1 (NTNG1) and Netrin-G2 (NTNG2) 14. Although these proteins also have Laminin N-terminal and Laminin EGF domains, their ends have different functions due to GPI 15. The major binding receptors of the secreted netrin proteins are DCC and UNC5 homologue family UNC5A-D, which are both dependent receptors. Netrin binding to a receptor promotes cell survival, proliferation, and differentiation, and without netrin binding, the receptor induces apoptosis 16,17....

Background: Cancer-associated fibroblasts (CAFs) are mainly involved in cancer progression and treatment failure. However, the specific signature of CAFs and their related clinicopathological parameters in renal cell carcinoma (RCC) remain unclear. Here, methods to recognize gene signatures were employed to roughly assess the infiltration of CAFs in RCC, based on the data from The Cancer Genome Atlas (TCGA). Weighted Gene Coexpression Network Analysis (WGCNA) was used to cluster transcriptomes and correlate with CAFs to identify the gene signature. Single-cell and cell line sequencing data were used to verify the expression specificity of the gene signature in CAFs. The gene signature was used to evaluate the infiltration of CAFs in each sample, and the clinical significance of each key gene in the gene signature and CAFs was analyzed. We observed that the CAF infiltration was higher in kidney cancer and advanced tumor stage and grade than in normal tissues. The seven key genes of the CAF gene signature identified using WGCNA showed high expression of CAF-related characteristics in the cell clustering landscape and fibroblast cell lines; these genes were found to be associated with extracellular matrix function, collagen synthesis, cell surface interaction, and adhesion. The high CAF infiltration and the key genes were verified from the TCGA and Gene Expression Omnibus data related to the advanced grade, advanced stage, and poor prognosis of RCC. In summary, our findings indicate that the clinically significant gene signature may serve as a potential biomarker of CAFs in RCC, and the infiltration of CAFs is associated with the pathological grade, stage, and prognosis of RCC.

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The role of cancer-associated fibroblasts (CAFs) has been thoroughly investigated in tumour microenvironments but not in bladder urothelial carcinoma (BLCA). The cell fraction of CAFs gradually increased with BLCA progression. Weighted gene coexpression network analysis (WGCNA) revealed a specific gene expression module of CAFs that are relevant to cancer progression and survival status. Fifteen key genes of the module were consistent with a fibroblast signature in single-cell RNA sequencing, functionally related to the extracellular matrix, and significant in survival analysis and tumour staging. A comparison of the luminal-infiltrated versus luminal-papillary subtypes and fibroblast versus urothelial carcinoma cell lines and immunohistochemical data analysis demonstrated that the key genes were specifically expressed in CAFs. Moreover, these genes are highly correlated with previously reported CAF markers. In summary, CAFs play a major role in the progression of BLCA, and the 15 key genes act as BLCA-specific CAF markers and can predict CAF changes. WGCNA can, therefore, be used to sort CAF-specific gene set in cancer tissues. K E Y W O R D S bladder cancer, cancer-associated fibroblast, marker, tumour microenvironment, weighted gene co-expression network analysis 1 | INTRODUCTION Bladder urothelial carcinoma (BLCA) is one of the leading causes of cancer-related death worldwide, with a 5-year survival rate of only 5% in patients with metastases (Antoni et al., 2017). BLCA with local and distant metastases remains an urgent challenge for researchers. Most cancers exhibit epithelial abnormalities and mutations in transformed cells. Over the past 20 years, this scenario has evolved, and the matrix has been shown to act as a driver of the tumourigenic process and promote cancer progression (Gascard & Tlsty, 2016). Cancer-associated fibroblasts (CAFs) are the main components of the tumour microenvironment (TME), and they appear in the matrix surrounding cancer. Biochemical crosstalk between cancer cells and CAFs and the mechanical remodelling of the stromal extracellular matrix (ECM) by CAFs are important factors in tumour cell migration and invasion (Erdogan & Webb, 2017; Valkenburg, de Groot, & Pienta, 2018). However, the current understanding of the interplay between CAFs and TME in BLCA is limited. High-throughput data from a large number of patient samples reveal the pathogenesis of and mechanisms underlying various cancers. In combination with weighted gene co-expression network analysis (WGCNA), the search for highly co-expressed key genes or hub genes is also common in tumour progression (Giulietti et al.,

Background The RUNX family of transcription factors plays an important regulatory role in tumor development. Although the importance of RUNX in certain cancer types is well known, the pan-cancer landscape remains unclear. Materials and Methods Data from The Cancer Genome Atlas (TCGA) provides a pan-cancer overview of the RUNX genes. Hence, herein, we performed a pan-cancer analysis of abnormal RUNX expression and deciphered the potential regulatory mechanism. Specifically, we used TCGA multi-omics data combined with multiple online tools to analyze transcripts, genetic alterations, DNA methylation, clinical prognoses, miRNA networks, and potential target genes. Results RUNX genes are consistently overexpressed in esophageal, gastric, pancreatic, and pan-renal cancers. The total protein expression of RUNX1 in lung adenocarcinoma, kidney renal clear cell carcinoma (KIRC), and uterine corpus endometrial carcinoma (UCEC) is consistent with the mRNA expression results. Moreover, increased phosphorylation on the T14 and T18 residues of RUNX1 may represent potential pathogenic factors. The RUNX genes are significantly associated with survival in pan-renal cancer, brain lower-grade glioma, and uveal melanoma. Meanwhile, various mutations and posttranscriptional changes, including the RUNX1 D96 mutation in invasive breast carcinoma, the co-occurrence of RUNX gene mutations in UCEC, and methylation changes in the RUNX2 promoter in KIRC, may be associated with cancer development. Finally, analysis of epigenetic regulator co-expression, miRNA networks, and target genes revealed the carcinogenicity, abnormal expression, and direct regulation of RUNX genes. Conclusions We successfully analyzed the pan-cancer abnormal expression and prognostic value of RUNX genes, thereby providing potential biomarkers for various cancers. Further, mutations revealed via genetic alteration analysis may serve as a basis for personalized patient therapies.

Renal cell carcinoma (RCC) is difficult to cure once it progresses and metastasizes. Runt-related transcription factor 2 (RUNX2) is associated with the development or progression of various cancers, but its role in RCC remains unclear. The expression of RUNX2 is not only aberrantly increased in ccRCC, but also is increased with increasing tumor stage and pathological grade. The prognosis of patients with tumors expressing RUNX2, which was revealed to be highly expressed in survival analysis, was significantly worse. Gene set enrichment analysis revealed that the RUNX2-mediated epithelial-mesenchymal transition (EMT) pathway promoted tumor progression. In vitro, knockdown of RUNX2 inhibited the proliferation, migration, and invasion of RCC, with related proteins in the EMT pathway exhibiting corresponding changes. RUNX2 regulated EMT in RCC to promote tumor progression.