Tumor microenvironment-based drug discovery: a novel insight into bladder cancer immunotherapy.
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ABSTRACT:
SUBMITTER: Zheng XN
PROVIDER: S-EPMC8367065 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Immunotherapy is a potential way to save the lives of patients with bladder cancer, but it only benefits approximately 20% of them. A total of 4,028 bladder cancer patients were collected for this study. Unsupervised non-negative matrix factorization and the nearest template prediction algorithms were employed for the classification. We identified the immune and non-immune classes from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA-BLCA) training cohort. The 150 most differentially expressed genes between these two classes were extracted, and the classification reappeared in 20 validation cohorts. For the activated and exhausted subgroups, a stromal activation signature was assessed by the NTP algorithm. Patients in the immune class showed highly enriched signatures of immunocytes, while the exhausted subgroup also exhibited activated transforming growth factor (TGF)-β1, and cancer-associated extracellular matrix signatures. Patients in the immune-activated subgroup showed a lower genetic alteration and better overall survival. Anti-PD-1/PD-L1 immunotherapy was more beneficial for the immune-activated subgroup, while immune checkpoint blockade therapy plus a TGF-β inhibitor or an EP300 inhibitor might achieve greater efficacy for patients in the immune-exhausted subgroup. Novel immune molecular classifier was identified for the innovative immunotherapy of patients with bladder cancer.
| S-EPMC7900642 | biostudies-literature
Project description:Bacillus Calmette-Guerin (BCG) is the only FDA approved first line therapy for patients with nonmuscle invasive bladder cancer. The purpose of this study is to better understand the role of innate immune pathways involved in BCG immunotherapy against murine bladder tumor. We first characterized the immunological profile induced by the MB49 mouse urothelial carcinoma cell line. MB49 cells were not able to activate an inflammatory response (TNF-α, IL-6, CXCL-10 or IFN-β) after the stimulus with different agonists or BCG infection, unlike macrophages. Although MB49 cells are not able to induce an efficient immune response, BCG treatment could activate other cells in the tumor microenvironment (TME). We evaluated BCG intratumoral treatment in animals deficient for different innate immune molecules (STING-/-, cGAS-/-, TLR2-/-, TLR3-/-, TLR4-/-, TLR7-/-, TLR9-/-, TLR3/7/9-/-, MyD88-/-, IL-1R-/-, Caspase1/11-/-, Gasdermin-D-/- and IFNAR-/-) using the MB49 subcutaneous mouse model. Only MyD88-/- partially responded to BCG treatment compared to wild type (WT) mice, suggesting a role played by this adaptor molecule. Additionally, BCG intratumoral treatment regulates cellular infiltrate in TME with an increase of inflammatory macrophages, neutrophils and CD8+ T lymphocytes, suggesting an immune response activation that favors tumor remission in WT mice but not in MyD88-/-. The experiments using MB49 cells infected with BCG and co-cultured with macrophages also demonstrated that MyD88 is essential for an efficient immune response. Our data suggests that BCG immunotherapy depends partially on the MyD88-related innate immune pathway.
| S-EPMC8329301 | biostudies-literature
Project description:Due to the strong heterogeneity of bladder cancer (BC), there is often substantial variation in the prognosis and efficiency of immunotherapy among BC patients. For the precision treatment and assessment of prognosis, the subtyping of BC plays a critical role. Despite various subtyping methods proposed previously, most of them are based on a limited number of molecules, and none of them is developed on the basis of cell states. In this study, we construct a single-cell atlas by integrating single cell RNA-seq, RNA microarray, and bulk RNA-seq data to identify the absolute proportion of 22 different cell states in BC, including immune and nonimmune cell states derived from tumor tissues. To explore the heterogeneity of BC, BC was identified into four different subtypes in multiple cohorts using an improved consensus clustering algorithm based on cell states. Among the four subtypes, C1 had median prognosis and best overall response rate (ORR), which characterized an immunosuppressive tumor microenvironment. C2 was enriched in epithelial-mesenchymal transition/invasion, angiogenesis, immunosuppression, and immune exhaustion. Surely, C2 performed the worst in prognosis and ORR. C3 with worse ORR than C2 was enriched in angiogenesis and almost nonimmune exhaustion. Displaying an immune effective environment, C4 performed the best in prognosis and ORR. We found that patients with just an immunosuppressive environment are suitable for immunotherapy, but patients with an immunosuppressive environment accompanied by immune exhaustion or angiogenesis may resist immunotherapy. Furthermore, we conducted exploration into the heterogeneity of the transcriptome, mutational profiles, and somatic copy-number alterations in four subtypes, which could explain the significant differences related to cell states in prognosis and ORR. We also found that PD-1 in immune and tumor cells could both influence ORR in BC. The level of TGFβ in a cell state can be opposite to the overall level in the tissues, and the level in a specific cell state could predict ORR more accurately. Thus, our work furthers the understanding of heterogeneity and immunotherapy resistance in BC, which is expected to assist clinical practice and serve as a supplement to the current subtyping method from a novel perspective of cell states.
| S-EPMC8864284 | biostudies-literature
Project description:Immunotherapy has been a milestone for muscle-invasive bladder cancer (MIBC), but only a small portion of patients can benefit from it. Therefore, it is crucial to develop a robust individualized immune-related signature of MIBC to identify patients potentially benefiting from immunotherapy. The current study identified patients from the Cancer Genome Atlas (TCGA) and immune genes from the ImmPort database, and used improved data analytical methods to build up a 45 immune-related gene pair signature, which could classify patients into high-risk and low-risk groups. The signature was then independently validated by a Gene Expression Omnibus (GEO) dataset and IMvigor210 data. The subsequent analysis confirmed the worse survival outcomes of the high-risk group in both training (p < 0.001) and validation cohorts (p = 0.018). A signature-based risk score was proven to be an independent risk factor of overall survival (p < 0.001) and could predict superior clinical net benefit compared to other clinical factors. The CIBERSORT algorithm revealed the low-risk group had increased CD8+ T cells plus memory-activated CD4+ T-cell infiltration. The low-risk group also had higher expression of PDCD1 (PD-1), CD40, and CD27, and lower expression of CD276 (B7-H3) and PDCD1LG2 (PD-L2). Importantly, IMvigor210 data indicated that the low-risk group had higher percentage of "inflamed" phenotype plus less "desert" phenotype, and the survival outcomes were significantly better for low-risk patients after immunotherapy (p = 0.014). In conclusion, we proposed a novel and promising prognostic immune-related gene pair (IRGP) signature of MIBC, which could provide us a panoramic view of the tumor immune microenvironment of MIBC and independently identify MIBC patients who might benefit from immunotherapy.
| S-EPMC8664435 | biostudies-literature
Project description:BackgroundBladder cancer (BLCA) is prone to metastasis and has poor prognosis with unsatisfactory treatment responsiveness. Disulfidptosis is a recently discovered, novel mode of cell death that is closely associated with human cancers. However, a comprehensive analysis of the relationship between disulfidptosis and BLCA is lacking. Therefore, this study aimed to explore the potential effect of disulfidptosis on BLCA and identify a biomarker for evaluating the prognosis and immunotherapy of patients with BLCA.Material and methodsWe acquired BLCA RNA sequencing data from The Cancer Genome Atlas Urothelial Bladder Carcinoma (TCGA-BLCA) cohort (containing 19 normal samples and 409 tumor samples) and the GES39281 cohort (containing 94 tumor samples) which were used for external validation of the signature. Initially, we performed unsupervised consensus clustering to explore disulfidptosis-related subgroups. We then conducted functional enrichment analysis on these subgroups to gain insights into their biological significance and evaluate their immunotherapy response and chemotherapy sensitivity. Next, we conducted Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression to construct a prognostic signature in the TCGA training set for prognosis-related differentially expressed genes (DEGs) in the disulfidptosis-related subgroups. Subsequently, we used a receiver operating characteristic (ROC) curve and independent prognostic analysis to validate the predictive performance of the signature in the TCGA testing and the GES39281 cohorts. Finally, we explored the therapeutic value of this signature in patients with BLCA, in terms of immunotherapy and chemotherapy.ResultIn this study, we obtained two subgroups: DRG-high (238 samples) and DRG-low (160 samples). The DRG-high group exhibited a poor survival rate compared to the DRG-low group and had a significant association with tumor grade, stage, and metastasis. Additionally, several pathways related to cancer and the immune system were enriched in the high-DRG group. Moreover, the DRG-high group exhibited higher expression of PD1 and CTLA4 and had a better response to immunotherapy in patients with both PD1 and CTLA4 positivity. Conversely, the DRG-high group was more sensitive to common chemotherapeutic agents. A prognostic signature was created, consisting of COL5A1, DIRAS3, NKG7, and POLR3G and validated as having a robust predictive capability. Patients in the low-risk-score group had more immune cells associated with tumor suppression and better immunotherapy outcomes.ConclusionThis study contributes to our understanding of the characteristics of disulfidptosis-related subgroups in BLCA. Disulfidptosis-related signatures can be used to assess the prognosis and immunotherapy of patients with BLCA.
| S-EPMC10864973 | biostudies-literature
Project description:Although immunotherapy has revolutionized bladder cancer (BLCA) therapy, only few patients demonstrate durable clinical benefits due to the heterogeneity. Emerging evidence has linked pyroptosis to shaping tumor microenvironment (TME) and predicting therapy response. However, the relationship between pyroptosis and immunotherapy response in BLCA remains elusive. In this study, we performed a comprehensive bioinformatic analysis to dissect the role of pyroptosis in BLCA. Differentially expressed pyroptosis-related genes (DEPRGs) between tumor and normal tissues were identified using publicly available datasets. Kaplan-Meier analysis was performed to screen for DEPRGs associated with survival. Consensus clustering was used for BLCA subtyping. TME characteristics were evaluated by CIBERSORT, ESTIMATE and immune checkpoint genes (ICGs). Following univariate COX regression and LASSO analyses with pyroptosis-related DEGs, the risk model and nomogram were constructed with TCGA dataset and validated in the GEO dataset. Furthermore, therapeutic responses in high- and low-risk groups were compared using TIDE and GDSC databases. Two pyroptosis-related subtypes (Cluster 1 and 2) were identified based on expression patterns of GSDMA and CHMP4C. Bioinformatic analyses showed that cluster 1 had poor survival, more M0/M1/M2 macrophages, higher immune/stromal/ESTIMATE scores, and higher expression levels of ICGs. A 15-gene signature for predicting prognosis could classify patients into high- and low-risk groups. Furthermore, the correlation of risk scores with TIDE score and IC50 showed that patients in low-risk group were more sensitive to immunotherapy, whereas patients in high-risk group could better benefit from chemotherapy. Our study identified two novel pyroptosis-related subtypes and constructed a risk model, which can predict the prognosis, improve our understanding the role of PRGs in BLCA, and guide chemotherapy and immunotherapy.
| S-EPMC9744904 | biostudies-literature
Project description: Not available
| S-EPMC10497934 | biostudies-literature
Project description:ObjectiveHypoxia, which can considerably affect the tumor microenvironment, hinders the use of immunotherapy in bladder cancer (BLCA). Therefore, we aimed to identify reliable hypoxia-related biomarkers to guide clinical immunotherapy in BLCA.MethodsUsing data downloaded from TCGA-BLCA cohort, we determined BLCA subtypes which divide 408 samples into different subtypes. Tumor immune infiltration levels of two clusters were quantified using ssGSEA, MCPcounter, EPIC, ESTIMATE, and TIMER algorithms. Next, we constructed a hypoxia score based on the expression of hypoxia-related genes. The IMvigor210 cohort and SubMap analysis were used to predict immunotherapeutic responses in patients with different hypoxia scores. Hub genes were screened using cytoscape, immunohistochemistry (IHC), and multispectral immunofluorescence were used to detect the spatial distribution of immune markers.ResultsPatients with BLCA were categorized into cluster1 (n = 227) and Cluster2 (n = 181). Immune infiltration and expression of immune markers were higher in Cluster1. Immune infiltration was also more obvious in the high-hypoxia score group which related to a better predicted response to immunotherapy. IHC, and multispectral immunofluorescence confirmed the importance of TLR8 in immune infiltration and immune phenotype.ConclusionsBLCA subtype can evaluate the infiltration of immune cells in the tumor microenvironment of different patients. Hypoxia score in this study could effectively predict immunotherapeutic responses in patients with BLCA. TLR8 may be a potential target for clinical immunotherapy.
| S-EPMC10757107 | biostudies-literature
Project description:Background: The efficiency of immune checkpoint inhibitors (ICIs) in bladder cancer (BLCA) treatment has been widely validated; however, the tumor response to ICIs was generally low. It is critical and urgent to find biomarkers that can predict tumor response to ICIs. The tumor microenvironment (TME), which may play important roles to either dampen or enhance immune responses, has been widely concerned. Methods: The cancer genome atlas BLCA (TCGA-BLCA) cohort (n = 400) was used in this study. Based on the proportions of 22 types of immune cells calculated by CIBERSORT, TME was classified by K-means Clustering and differentially expressed genes (DEGs) were determined. Based on DEGs, patients were classified into three groups, and cluster signature genes were identified after reducing redundant genes. Then TMEscore was calculated based on cluster signature genes, and the samples were classified to two subtypes. We performed somatic mutation and copy number variation analysis to identify the genetic characteristics of the two subtypes. Correlation analysis was performed to explore the correlation between TMEscore and the tumor response to ICIs as well as the prognosis of BLCA. Results: According to the proportions of immune cells, two TME clusters were determined, and 1,144 DEGs and 138 cluster signature genes were identified. Based on cluster signature genes, samples were classified into TMEscore-high (n = 199) and TMEscore-low (n = 201) subtypes. Survival analysis showed patients with TMEscore-high phenotype had better prognosis. Among the 45 differentially expressed micro-RNAs (miRNAs) and 1,033 differentially expressed messenger RNAs (mRNAs) between the two subtypes, 16 miRNAs and 287 mRNAs had statistically significant impact on the prognosis of BLCA. Furthermore, there were 94 genes with significant differences between the two subtypes, and they were enriched in RTK-RAS, NOTCH, WNT, Hippo, and PI3K pathways. The Tumor Immune Dysfunction and Exclusion (TIDE) score of TMEscore-high BLCA was statistically lower than that of TMEscore-low BLCA. Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of TMEscore and tumor mutation burden (TMB) is 0.6918 and 0.5374, respectively. Conclusion: We developed a method to classify BLCA patients to two TME subtypes, TMEscore-high and TMEscore-low, and we found TMEscore-high subtype of BLCA had a good prognosis and a good response to ICIs.
| S-EPMC7957069 | biostudies-literature
Project description:BackgroundAlthough prognostic models based on pyroptosis-related genes (PRGs) have been constructed in bladder cancer (BLCA), the comprehensive impact of these genes on tumor microenvironment (TME) and immunotherapeutic response has yet to be investigated.MethodsBased on expression profiles of 52 PRGs, we utilized the unsupervised clustering algorithm to identify PRGs subtypes and ssGSEA to quantify immune cells and hallmark pathways. Moreover, we screened feature genes of distinct PRGs subtypes and validated the associations with immune infiltrations in tissue using the multiplex immunofluorescence. Univariate, LASSO, and multivariate Cox regression analyses were employed to construct the scoring scheme.ResultsFour PRGs clusters were identified, samples in cluster C1 were infiltrated with more immune cells than those in others, implying a favorable response to immunotherapy. While the cluster C2, which shows an extremely low level of most immune cells, do not respond to immunotherapy. CXCL9/CXCL10 and SPINK1/DHSR2 were identified as feature genes of cluster C1 and C2, and the specimen with high CXCL9/CXCL10 was characterized by more CD8 + T cells, macrophages and less Tregs. Based on differentially expressed genes (DEGs) among PRGs subtypes, a predictive model (termed as PRGs score) including five genes (CACNA1D, PTK2B, APOL6, CDK6, ANXA2) was built. Survival probability of patients with low-PRGs score was significantly higher than those with high-PRGs score. Moreover, patients with low-PRGs score were more likely to benefit from anti-PD1/PD-L1 regimens.ConclusionPRGs are closely associated with TME and oncogenic pathways. PRGs score is a promising indicator for predicting clinical outcome and immunotherapy response.
| S-EPMC11231188 | biostudies-literature