Abstract
BackgroundAccumulating evidences demonstrated tumor microenvironment (TME) of bladder cancer (BLCA) may play a pivotal role in modulating tumorigenesis, progression, and alteration of biological features. Currently we aimed to establish a prognostic model based on TME-related gene expression for guiding clinical management of BLCA.MethodsWe employed ESTIMATE algorithm to evaluate TME cell infiltration in BLCA. The RNA-Seq data from The Cancer Genome Atlas (TCGA) database was used to screen out differentially expressed genes (DEGs). Underlying relationship between co-expression modules and TME was investigated via Weighted gene co-expression network analysis (WGCNA). COX regression and the least absolute shrinkage and selection operator (LASSO) analysis were applied for screening prognostic hub gene and establishing a risk predictive model. BLCA specimens and adjacent tissues from patients were obtained from patients. Bladder cancer (T24, EJ-m3) and bladder uroepithelial cell line (SVHUC1) were used for genes validation. qRT-PCR was employed to validate genes mRNA level in tissues and cell lines.Results365 BLCA samples and 19 adjacent normal samples were selected for identifying DEGs. 2141 DEGs were identified and used to construct co-expression network. Four modules (magenta, brown, yellow, purple) were regarded as TME regulatory modules through WGCNA and GO analysis. Furthermore, seven hub genes (ACAP1, ADAMTS9, TAP1, IFIT3, FBN1, FSTL1, COL6A2) were screened out to establish a risk predictive model via COX and LASSO regression. Survival analysis and ROC curve analysis indicated our predictive model had good performance on evaluating patients prognosis in different subgroup of BLCA. qRT-PCR result showed upregulation of ACAP1, IFIT3, TAP1 and downregulation of ADAMTS9, COL6A2, FSTL1,FBN1 in BLCA specimens and cell lines.ConclusionsOur study firstly integrated multiple TME-related genes to set up a risk predictive model. This model could accurately predict BLCA progression and prognosis, which offers clinical implication for risk stratification, immunotherapy drug screen and therapeutic decision.
Highlights
Accumulating evidences demonstrated tumor microenvironment (TME) of bladder cancer (BLCA) may play a pivotal role in modulating tumorigenesis, progression, and alteration of biological features
Non-muscle invasive bladder cancer (NMIBC) patients usually have a good prognosis, approximately 70% of NMIBC cases will have a recurrence in the first year after initial diagnosis, and nearly 10–50% of NMIBC will progress to muscle invasive bladder cancer (MIBC) that is featured with higher grade and poorer prognosis [3]
ESTIMATE scores and stromal scores are significantly correlated with BLCA subtypes ESTIMATE algorithm (Estimation of Stromal and Immune cells in Malignant Tumors using Expression data) is a tool for predicting the presence of immune/stromal cells infiltration and tumor purity in tumor tissue based on single sample gene set enrichment analysis
Summary
Accumulating evidences demonstrated tumor microenvironment (TME) of bladder cancer (BLCA) may play a pivotal role in modulating tumorigenesis, progression, and alteration of biological features. A growing body of emerging evidences raise the awareness in cancer research community that tumor microenvironment (TME) may play a pivotal role in carcinogenesis, immune evasion and treatment response [4,5,6,7]. Makito et al [11] found that both recurrence-free survival (RFS) and progression-free survival (PFS) dramatically shortened with regulatory T cells (Treg) and tumorassociated macrophages (TAM) increasing in the tumorenriched area after intravesical BCG therapy, implying immune cell infiltration could be an effective tool to evaluate immunotherapy response
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