Dataset Information

Fibroblast Common Serum Response Signature-Related Classification Affects the Tumour Microenvironment and Predicts Prognosis in Bladder Cancer.

ABSTRACT: Abnormal oncogenic signatures provide important clues regarding cancer prognosis and treatment. We analysed the variations in 189 oncogenic signature gene sets between normal and tumourous tissues from The Cancer Genome Atlas (TCGA) and found that the "CSR_LATE_UP" signature was the most upregulated oncogenic signature gene set in bladder cancer. Next, we developed a common serum response (CSR) risk score (CRS) model based on fibroblast CSR genes and systematically analysed the correlations of these genes or the CRSs with survival, previously reported molecular subtypes, clinicopathological features, cancer signalling pathways, chemotherapeutic responses, and the tumour microenvironment using TCGA and validation cohorts. The CRS could predict the malignant phenotype, chemotherapeutic efficacy, immune invasion, and disease prognosis. Inflammatory signalling pathways (e.g., inflammatory response, TNFA signalling via NFƘB, IFNα response, and IL2-STAT5 signalling) were markedly upregulated in patients with high CRS. Notably, the CSR-related gene ANLN was positively correlated with CD8⁺ immune cell infiltration, PD-L1 expression, and sensitivity to PD-L1 inhibitors and could thus provide guidance for clinical immunotherapy. This study highlights the crucial role of the CSR signature in bladder cancer and provides a CRS model for accurate predictions of the disease prognosis and chemotherapy and immunotherapy responses.

SUBMITTER: Yang X

PROVIDER: S-EPMC9606836 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Fibroblast Common Serum Response Signature-Related Classification Affects the Tumour Microenvironment and Predicts Prognosis in Bladder Cancer.

Yang Xiangchou X Zhou Yangyang Y Huang Linjing L Lin Shang S Ye Haihao H Shan Yujuan Y

Oxidative medicine and cellular longevity 20221019

Abnormal oncogenic signatures provide important clues regarding cancer prognosis and treatment. We analysed the variations in 189 oncogenic signature gene sets between normal and tumourous tissues from The Cancer Genome Atlas (TCGA) and found that the "CSR_LATE_UP" signature was the most upregulated oncogenic signature gene set in bladder cancer. Next, we developed a common serum response (CSR) risk score (CRS) model based on fibroblast CSR genes and systematically analysed the correlations of t ...[more]

PMID: 36312898

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Project description:Background: Tumor necrosis factor (TNF) family members play vital roles in cancer development and antitumor immune responses. However, the expression patterns, prognostic values, and immunological characteristics of TNF members in bladder carcinoma (BLCA) remain unclear. Methods: The training cohort, TCGA-BLCA, was downloaded from The Cancer Genome Atlas; another two Gene Expression Omnibus datasets (GSE13507 and GSE32894) and the Xiangya cohort (RNA-sequencing cohort collected from our hospital) were used as the external validation cohort. The least absolute shrinkage and selection operator (LASSO) algorithm and cross-validation were used to screen variables. Cox regression model and random survival forest (RSF) were used to develop the risk score, respectively. Then, we systematically correlated the TNF risk score with the tumor microenvironment (TME) cell infiltration, molecular subtypes of BLCA, and the potential value for predicting the efficacy of immunotherapy. Results: We developed two TNF-based patterns, named TNF cluster 1 and TNF cluster 2. TNF cluster 1 exhibited poorer survival outcome and an inflamed TME characteristic compared with TNF cluster 2. We then filtered out 196 differentially expressed genes between the two TNF clusters and applied the LASSO algorithm and cross-validation to screen out 22 genes to build the risk score. For risk score, we found that RSF exhibited higher efficacy than the Cox regression model, and we chose the risk score developed by RSF for the following analysis. BLCA patients in the higher risk score group showed significantly poorer survival outcomes. Moreover, these results could be validated in the external validation cohorts, including the GSE13507, GSE32894, and Xiangya cohorts. Then, we systematically correlated the risk score with TME cell infiltration and found that it was positively correlated with the infiltration of a majority of immune cells. Also, a higher risk score indicated a basal subtype of BLCA. Notably, the relationship between risk score, TME cell infiltration, and molecular subtypes could be validated in the Xiangya cohort. Conclusion: We developed and validated a robust TNF-based risk score, which could predict prognostic outcomes, TME, and molecular subtypes of BLCA. However, the value of risk score predicting the efficacy of immunotherapy needs further research.

Project description:BackgroundGastric cancer (GC) is one of the most common cancers, with a wide range of symptoms and outcomes. Cancer-associated fibroblasts (CAFs) are newly identified in the tumor microenvironment (TME) and associated with GC progression, prognosis, and treatment response. A novel CAF-associated prognostic model is urgently needed to improve treatment strategies.MethodsThe detailed data of GC samples were downloaded from The Cancer Genome Atlas (TCGA), GSE62254, GSE26253, and GSE84437 datasets, then obtained 18 unique CAF-related genes from the research papers. Eight hundred eight individuals with GC were classified as TCGA or GSE84437 using consensus clustering by the selected CAF-related genes. The difference between the two subtypes revealed in this study was utilized to create the "CAF-related signature score" (CAFS-score) prognostic model and validated with the Gene Expression Omnibus (GEO) database.ResultsWe identified two CAF subtypes characterized by high and low CAFS-score in this study. GC patients in the low CAFS-score group had a better OS than those in the high CAFS-score group, and the cancer-related malignant pathways were more active in the high CAFS-score group, compared to the low CAFS-score group. We found that there was more early TNM stage in the low CAFS-score subgroup, while there was more advanced TNM stage in the high CAFS-score subgroup. The expression of TMB was significantly higher in the low CAFS-score subgroup than in the high CAFS-score subgroup. A low CAFS-score was linked to increased microsatellite instability-high (MSI-H), mutation load, and immunological activation. Furthermore, the CAFS-score was linked to the cancer stem cell (CSC) index as well as chemotherapeutic treatment sensitivity. The patients in the high CAFS-score subgroup had significantly higher proportions of monocytes, M2 macrophages, and resting mast cells, while plasma cells and follicular helper T cells were more abundant in the low-risk subgroup. The CAFS-score was also highly correlated with the sensitivity of chemotherapeutic drugs. The low CAFS-score group was more likely to have an immune response and respond to immunotherapy. We developed a nomogram to improve the CAFS-clinical score's usefulness.ConclusionThe CAFS-score may have a significant role in the TME, clinicopathological characteristics, prognosis, CSC, MSI, and drug sensitivity, according to our investigation of CAFs in GC. We also analyzed the value of the CAFS-score in immune response and immunotherapy. This work provides a foundation for improving prognosis and responding to immunotherapy in patients with GC.

Dataset Information

Fibroblast Common Serum Response Signature-Related Classification Affects the Tumour Microenvironment and Predicts Prognosis in Bladder Cancer.

Publications

Fibroblast Common Serum Response Signature-Related Classification Affects the Tumour Microenvironment and Predicts Prognosis in Bladder Cancer.

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