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Effect of unfolded protein response on the immune infiltration and prognosis of transitional cell bladder cancer.

ABSTRACT: Background: Bladder cancer (BC) is one of the most common human malignancies worldwide. Previous researches have shown that the unfolded protein response (UPR) pathway could contribute to the tumorigenesis of BC. However, the role of UPR in the immune infiltration, progression, and prognosis of BC is unclear.Methods: The GSVA and ssGSEA methods were used for assessing the UPR score and immune cells infiltration score in three BC public datasets, respectively. The relationship between the UPR pathway and clinicopathological characteristics was analyzed by the Kruskal-Wallis, Wilcox test, and log-rank test. The association of the UPR pathway with various tumor-infiltrating immune cells was evaluated with the correlation analysis. Univariate Cox regression analysis was performed to identify risk factors significantly associated with prognosis. The predictive models were built based on risk factors and visualized with nomograms. The performance of our models was evaluated with the calibration curve, Harrell's concordance index (c-index), and receiver operating characteristic (ROC) analysis.Results: We found that the UPR pathway and many UPR-related genes were significantly associated with the pathologic grade, tumor type, and invasive progression of transitional cell bladder cancer (TCBC), and a high UPR score predicted a poor prognosis in patients. The UPR score was positively correlated with the infiltration abundance of many tumor immune cells in TCBC. Besides, we constructed predictive models based on the UPR score, and good performance was observed, with c-indexes ranging from 0.74 to 0.87.Conclusions: Our study proved that the UPR pathway may have an important impact on the progression, prognosis, and tumor immune infiltration in TCBC, and the models we built may provide effective and reliable guides for prognosis assessment and treatment decision-making for TCBC patients.

SUBMITTER: Yan X

PROVIDER: S-EPMC8253203 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundOncogenic metabolic reprogramming contributes to tumor growth and immune evasion. The intertumoral metabolic heterogeneity and interaction of distinct metabolic pathways may determine patient outcomes. In this study, we aim to determine the clinical and immunological significance of metabolic subtypes according to the expression levels of genes related to glycolysis and cholesterol-synthesis in bladder cancer (BCa).MethodsBased on the median expression levels of glycolytic and cholesterogenic genes, patients were stratified into 4 subtypes (mixed, cholesterogenic, glycolytic, and quiescent) in an integrated cohort including TCGA, GSE13507, and IMvigor210. Clinical, genomic, transcriptomic, and tumor microenvironment characteristics were compared between the 4 subtypes.ResultsThe 4 metabolic subtypes exhibited distinct clinical, molecular, and genomic patterns. Compared to quiescent subtype, mixed subtype was more likely to be basal tumors and was significantly associated with poorer prognosis even after controlling for age, gender, histological grade, clinical stage, and molecular phenotypes. Additionally, mixed tumors harbored a higher frequency of RB1 and LRP1B copy number deletion compared to quiescent tumors (25.7% vs. 12.7 and 27.9% vs. 10.2%, respectively, both adjusted P value< 0.05). Furthermore, aberrant PIK3CA expression level was significantly correlated with those of glycolytic and cholesterogenic genes. The quiescent subtype was associated with lower stemness indices and lower signature scores for gene sets involved in genomic instability, including DNA replication, DNA damage repair, mismatch repair, and homologous recombination genes. Moreover, quiescent tumors exhibited lower expression levels of pyruvate dehydrogenase kinases 1-3 (PDK1-3) than the other subtypes. In addition, distinct immune cell infiltration patterns were observed across the 4 metabolic subtypes, with greater infiltration of M0/M2 macrophages observed in glycolytic and mixed subtypes. However, no significant difference in immunotherapy response was observed across the 4 metabolic subtypes.ConclusionThis study proposed a new metabolic subtyping method for BCa based on genes involved in glycolysis and cholesterol synthesis pathways. Our findings may provide novel insight for the development of personalized subtype-specific treatment strategies targeting metabolic vulnerabilities.

Project description:Pentatricopeptide repeat domain 1 (PTCD1) was reported to regulate mitochondrial metabolism and oxidative phosphorylation. However, the effect and mechanism of PTCD1 in the development of bladder urothelial carcinoma (BLCA) remain unclear. The databases from The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) were used to analyze the expression changes, clinical features, and prognostic values of PTCD1. A nomogram was built to predict the prognostic outcomes of BLCA cases. The potential genes interacting with PTCD1 were explored by Weighted Gene Coexpression Network Analysis (WGCNA). The estimation of associations between PTCD1 and tumor mutations, tumor immunities, and m6A methylations was performed. The study found that the gradual decrease of PTCD1 expression was observed with the increase of stage and grade. Low PTCD1 expression was greatly correlated with higher pathological stage, N stage, and poor prognosis in TCGA cohorts; interestingly, low-grade BLCA cases all exhibited high expression of PTCD1. HPA database analysis implied that the expression of PTCD1 protein in BLCA was lower than that in normal bladder tissue, and the protein expression of PTCD1 in high-grade BLCA was lower than that in low-grade BLCA. Multivariate Cox regression analysis indicated that PTCD1 may serve as an independent factor influencing prognosis of BLCA. Mechanistically, PTCD1 played a regulatory role in BLCA progression through multiple tumor-related pathways containing PI3K-Akt signaling, ECM-receptor interaction, oxidative phosphorylation, and extracellular matrix organization. WGCNA reported that PTCD1 had a strong positive correlation with POLR2J, ZNHT1, ATP5MF, PDAP1, BUD31, and COPS6. Besides, the mRNA expression of PTCD1 was negatively associated with immune cells' infiltrations, immune functions, and checkpoints, especially with some m6A methylation regulators in BLCA. In sum, downregulation of PTCD1 expression may be involved in the development of BLCA and remarkably correlated with poor prognosis. Meantime, it showed an influence in immune cell infiltration and may serve as an agreeable prognostic indicator in BLCA.

Project description: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.

Project description:Breast cancer represents the number one cause of cancer-associated mortality globally. The most aggressive molecular subtype is triple negative breast cancer (TNBC), of which limited therapeutic options are available. It is well known that breast cancer prognosis and tumor sensitivity toward immunotherapy are dictated by the tumor microenvironment. Breast cancer gene expression profiles were extracted from the METABRIC dataset and two TNBC clusters displaying unique immune features were identified. Activated immune cells formed a large proportion of cells in the high infiltration cluster, which correlated to a good prognosis. Differentially expressed genes (DEGs) extracted between two heterogeneous subtypes were used to further explore the underlying immune mechanism and to identify prognostic biomarkers. Functional enrichment analysis revealed that the DEGs were predominately related to some processes involved in activation and regulation of innate immune signaling. Using network analysis, we identified two modules in which genes were selected for further prognostic investigation. Validation by independent datasets revealed that CXCL9 and CXCL13 were good prognostic biomarkers for TNBC. We also performed comparisons between the above two genes and immune markers (CYT, APM, TILs, and TIS), as well as cell checkpoint marker expressions, and found a statistically significant correlation between them in both METABRIC and TCGA datasets. The potential of CXCL9 and CXCL13 to predict chemotherapy sensitivity was also evaluated. We found that the CXCL9 and CXCL13 were good predictors for chemotherapy and their expressions were higher in chemotherapy-responsive patients in contrast to those who were not responsive. In brief, immune infiltrate characterization on TNBC revealed heterogeneous subtypes with unique immune features allowed for the identification of informative and reliable characteristics representative of the local immune tumor microenvironment and were potential candidates to guide the management of TNBC patients.

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Effect of unfolded protein response on the immune infiltration and prognosis of transitional cell bladder cancer.

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