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Glycogen Metabolism Predicts the Efficacy of Immunotherapy for Urothelial Carcinoma.

ABSTRACT: Urothelial cancer (UC) is one of the common refractory tumors and chemotherapy is the primary treatment for it. The advent of immune checkpoint inhibitors (ICI) has facilitated the development of treatment strategies for UC patients. To screen out UC patients sensitive to ICI, researchers have proposed that PD-L1, tumor mutation burden and TCGA molecular subtypes can be used as predictors of ICI efficacy. However, the performance of these predictors needs further validation. We need to identify novel biomarkers to screen out UC patients sensitive to ICI. In our study, we collected the data of two clinical cohorts: the ICI cohort and the TCGA cohort. The result of the multivariate Cox regression analysis showed that glycogen metabolism score (GMS) (HR = 1.26, p = 0.017) was the negative predictor of prognosis for UC patients receiving ICI treatment. Low-GMS patients had a higher proportion of patients achieving complete response or partial response to ICI. After the comparison of gene mutation status between high-GMS and low-GMS patients, we identified six genes with significant differences in mutation frequencies, which may provide new directions for potential drug targets. Moreover, we analyzed the immune infiltration status and immune-related genes expression between high-GMS and low-GMS patients. A reduced proportion of tumor-associated fibroblasts and elevated proportion of CD8⁺ T cells can be observed in low-GMS patients while several immunosuppressive molecules were elevated in the high-GMS patients. Using the sequencing data of the GSE164042 dataset, we also found that myeloid-derived suppressor cell and neutrophil related signature scores were lower in α-glucosidase knockout bladder carcinoma cells when compared to the control group. In addition, angiogenesis, classic carcinogenic pathways, immunosuppressive cells related pathways and immunosuppressive cytokine secretion were mainly enriched in high-GMS patients and cell samples from the control group. Finally, we suspected that the combination treatment of ICI and histone deacetylase inhibitors may achieve better clinical responses in UC patients based on the analysis of drug sensitivity data. In conclusion, our study revealed the predictive value of GMS for ICI efficacy of UC patients, providing a novel perspective for the exploration of new drug targets and potential treatment strategies.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC8424112 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Clear cell renal cell carcinoma (ccRCC) constitutes the commonest kidney malignancy. Immunogenic cell death (ICD) is a type of regulated cell death (RCD), which sufficiently activates adaptive immunity. However, ICD's involvement in cancer development is unclear, as well as the associations of ICD effectors with ccRCC prognosis. Methods: RNA-sequencing expression profiles of ccRCC in The Cancer Genome Atlas (TCGA) and normal samples in Gene Expression Omnibus (GEO) were comprehensively investigated. Consensus clustering analysis was employed to determine subgroup members linked to ICD-related genes. Functional enrichment analysis was utilized for the examination of TLR4's biological role, and in vitro cellular assays were utilized for further confirmation. We also used Kaplan-Meier (KM) and Cox regression analyses to assess TLR4's prognostic value. Finally, "CIBERSORT" was employed for immune score evaluation. Results: The associations of ICD effectors with ccRCC prognosis were examined based on TCGA, and 12 genes showed upregulation in ccRCC tissue specimens. Meanwhile, ccRCC cases with upregulated ICD-related genes had increased overall survival. Among these ICD-related genes, TLR4 was selected for subsequent analysis. TLR4 was upregulated in ccRCC samples and independently predicted ccRCC. TLR4 also enhanced the proliferative, migratory and invasive abilities in cultured ccRCC cells. Moreover, TLR4 had close relationships with immune checkpoints and infiltrated immune cells. ccRCC cases with elevated TLR4 expression had prolonged overall survival, suggesting a prognostic value for TLR4. Finally, a pan-cancer analysis demonstrated TLR4 had differential expression in various malignancies in comparison with normal tissue samples. Conclusions: This study revealed prognostic values for ICD-associated genes, particularly TLR4, and experimentally validated the inducing effects of TLR4 on ccRCC progression in vitro. We also demonstrated the associations of TLR4 with immune cell infiltration, providing a novel strategy for prognostic evaluation and a novel therapeutic target in ccRCC.

Project description:Objective: Resistance to immune checkpoint inhibitors (ICIs) has been a massive obstacle to ICI treatment in metastatic urothelial carcinoma (MUC). Recently, increasing evidence indicates the clinical importance of the association between hypoxia and immune status in tumor patients. Therefore, it is necessary to investigate the relationship between hypoxia and prognosis in metastatic urothelial carcinoma. Methods: Transcriptomic and clinical data from 348 MUC patients who underwent ICI treatment from a large phase 2 trial (IMvigor210) were investigated in this study. The cohort was randomly divided into two datasets, a training set (n = 213) and a testing set (n = 135). Data of hypoxia-related genes were downloaded from the molecular signatures database (MSigDB), and screened by univariate and multivariate Cox regression analysis to construct a prognosis-predictive model. The robustness of the model was evaluated in two melanoma cohorts. Furthermore, an external validation cohort, the bladder cancer cohort, from the Cancer Genome Atlas (TCGA) database, was t used to explore the mechanism of gene mutation, immune cell infiltration, signaling pathway enrichment, and drug sensitivity. Results: We categorized patients as the high- or low- risk group using a four-gene hypoxia risk model which we constructed. It was found that patients with high-risk scores had significantly worse overall survival (OS) compared with those with low-risk scores. The prognostic model covers 0.71 of the area under the ROC curve in the training set and 0.59 in the testing set, which is better than the survival prediction of MUC patients using the clinical characteristics. Mutation analysis results showed that deletion mutations in RB1, TP53, TSC1 and KDM6A were correlated with hypoxic status. Immune cell infiltration analysis illustrated that the infiltration T cells, B cells, Treg cells, and macrophages was correlated with hypoxia. Functional enrichment analysis revealed that a hypoxic microenvironment activated inflammatory pathways, glucose metabolism pathways, and immune-related pathways. Conclusion: In this investigation, a four-gene hypoxia risk model was developed to evaluate the degree of hypoxia and prognosis of ICI treatment, which showed a promising clinical prediction value in MUC. Furthermore, the hypoxia risk model revealed a close relationship between hypoxia and the tumor immune microenvironment.

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Glycogen Metabolism Predicts the Efficacy of Immunotherapy for Urothelial Carcinoma.

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