HIF1A predicts the efficacy of anti-PD-1 therapy in advanced clear cell renal cell carcinoma.
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ABSTRACT:
SUBMITTER: Guo T
PROVIDER: S-EPMC9530654 | biostudies-literature | 2022 Sep
REPOSITORIES: biostudies-literature
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HIF1A predicts the efficacy of anti-PD-1 therapy in advanced clear cell renal cell carcinoma.
Guo Tuanjie T Wang Tao T Zhang Jian J Chen Siteng S Wang Xiang X
Translational oncology 20220930
Immunotherapy for cancer has become a revolutionary treatment, with the progress of immunological research on cancer. Cancer patients have also become more diversified in drug selection. Individualized medical care of patients is more important in the era of precision medicine. For advanced clear cell renal cell carcinoma (ccRCC) patients, immunotherapy and targeted therapy are the two most important treatments. The development of biomarkers for predicting the efficacy of immunotherapy or target ...[more]
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Project description:Immunotherapy has greatly improved the survival time and quality of life of patients with renal cell carcinoma, but the benefits are limited to a small portion of patients. There are too few new biomarkers that can be used to identify molecular subtypes of renal clear cell carcinoma and predict survival time with anti-PD-1 treatment. Single-cell RNA data of clear cell renal cell carcinoma (ccRCC) treated with anti-PD-1 were obtained from public databases, then 27,707 high-quality CD4 + T and CD8 + T cells were obtained for subsequent analysis. Firstly, genes set variation analysis and CellChat algorithm were used to explore potential molecular pathway differences and intercellular communication between the responder and non-responder groups. Additionally, differentially expressed genes (DEGs) between the responder and non-responder groups were obtained using the "edgeR" package, and ccRCC samples from TCGA-KIRC (n = 533) and ICGA-KIRC (n = 91) were analyzed by the unsupervised clustering algorithm to recognize molecular subtypes with different immune characteristics. Finally, using univariate Cox analysis, least absolute shrinkage and selection operator (Lasso) regression, and multivariate Cox regression, the prognosis model of immunotherapy was established and verified to predict the progression-free survival of ccRCC patients treated with anti-PD-1. At the single cell level, there are different signal pathways and cell communication between the immunotherapy responder and non-responder groups. In addition, our research also confirms that the expression level of PDCD1/PD-1 is not an effective marker for predicting the response to immune checkpoint inhibitors (ICIs). The new prognostic immune signature (PIS) enabled the classification of ccRCC patients with anti-PD-1 therapy into high- and low-risk groups, and the progression-free survival times (PFS) and immunotherapy responses were significantly different between these two groups. In the training group, the area under the ROC curve (AUC) for predicting 1-, 2- and 3-year progression-free survival was 0.940 (95% CI: 0.894-0.985), 0.981 (95% CI: 0.960-1.000), and 0.969 (95% CI: 0.937-1.000), respectively. Validation sets confirm the robustness of the signature. This study revealed the heterogeneity between the anti-PD-1 responder and non-responder groups from different angles and established a robust PIS to predict the progression-free survival of ccRCC patients receiving immune checkpoint inhibitors.
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Project description:BackgroundClear cell renal cell carcinoma (ccRCC) has the highest morbidity among renal cell carcinoma (RCC) subtypes. While existing clinical pharmacological intervention strategies have achieved certain efficacy, challenges including inevitable drug resistance and intricate immune heterogeneity of ccRCC continue to hinder their biomedical application. Therefore, developing novel immunotherapeutic agents and identifying patients who can gain the greatest benefits from these therapies are urgent issues.MethodsTo address these challenges, mRNA expression profile and clinical data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. These data were integrated and randomly allocated into training and test sets. Immune-related differentially expressed genes (IRDEGs) were used to construct an immune-related gene prognostic index (IRGPI). Both prognostic performance metrics and immune phenotyping were employed to evaluate the effectiveness of the model. Furthermore, model IRDEGs (mIRDEGs) in two risk subgroups were leveraged to select potential therapeutic compounds. Afterwards, network pharmacology and molecular docking techniques were used to elucidate the anti-cancer mechanisms of Zebularine (Zeb). Finally, the anti-cancer efficacy of Zeb was validated through in vivo and in vitro experiments.ResultsOur constructed IRGPI exhibited superior prognostic performance. The drug screening revealed Zeb potentially targets the PI3K-Akt signaling pathway to exert its anti-cancer effects. Subsequent experimental validation corroborated these theoretical findings.ConclusionThis study presents a prognostic model to evaluate immune cell infiltration and predict the prognosis of ccRCC patients. The identified small molecule compound provides a novel therapeutic avenue for treating ccRCC patients.
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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.
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Project description:ADAPTeR is a prospective, phase II study of nivolumab (anti-PD-1) in 15 treatment-naive patients (115 multiregion tumor samples) with metastatic clear cell renal cell carcinoma (ccRCC) aiming to understand the mechanism underpinning therapeutic response. Genomic analyses show no correlation between tumor molecular features and response, whereas ccRCC-specific human endogenous retrovirus expression indirectly correlates with clinical response. T cell receptor (TCR) analysis reveals a significantly higher number of expanded TCR clones pre-treatment in responders suggesting pre-existing immunity. Maintenance of highly similar clusters of TCRs post-treatment predict response, suggesting ongoing antigen engagement and survival of families of T cells likely recognizing the same antigens. In responders, nivolumab-bound CD8+ T cells are expanded and express GZMK/B. Our data suggest nivolumab drives both maintenance and replacement of previously expanded T cell clones, but only maintenance correlates with response. We hypothesize that maintenance and boosting of a pre-existing response is a key element of anti-PD-1 mode of action.
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Project description:This study investigates the roles of RUVBL1 and HIF1A in ccRCC development and explores their clinical significance as prognostic biomarkers. mRNA and protein expressions were analyzed using TCGA data and an institutional tissue cohort, respectively. Correlations with clinicopathological parameters and patient outcomes were assessed. TCGA data revealed significantly elevated RUVBL1 mRNA expression in ccRCC tissues, associated with advanced histological grade, T stage, lymph node metastasis, and clinical stage. High RUVBL1 mRNA expression correlated with inferior overall survival and served as an adverse prognostic factor. Similarly, HIF1A mRNA expression was significantly higher in ccRCC tissues, correlating with worse overall survival and acting as an adverse prognostic factor for treatment outcomes. Simultaneous evaluation of RUVBL1 and HIF1A mRNA expression demonstrated enhanced prognostic capacity, surpassing the predictive power of individual markers. Immunohistochemical staining confirmed substantial upregulation of both RUVBL1 and HIF-1α proteins in ccRCC tissues. Furthermore, high expression of both RUVBL1 and HIF-1α proteins was significantly associated with shorter patient survival time. Our findings underscore the significance of RUVBL1 and HIF-1α as potential prognostic markers in ccRCC, paving the way for further research to translate these insights into clinically relevant applications.
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Project description:BACKGROUND:Although clear cell renal cell carcinoma (ccRCC) is well known as a highly immunogenic tumor, only a small subset of patients could benefit from current immunotherapy, which might be due to the heterogeneity of immune microenvironment in ccRCC. So, it is meaningful to explore novel immunotherapy or combination therapy for improving therapeutic efficacy. HHLA2, a newly discovered B7 family member, is prevalently expressed in numerous tumors, including ccRCC. This study aimed to investigate the prognostic impact of HHLA2/PD-L1 co-expression and its relationship with tumor-infiltrating lymphocytes (TILs). METHODS:The expression levels of HHLA2, PD-L1, CD8, and CD4 in cancer tissues from cases (206 in the training cohort and 197 in the validation cohort) with surgically resectable primary ccRCC were evaluated by immunohistochemistry. RESULTS:The positive rates of HHLA2 were much higher than those of PD-L1 in ccRCC tissues. HHLA2-positive expression was significantly associated with necrosis, microvascular invasion, advanced Fuhrman nuclear, and TNM stage and indicated a shorter progression-free survival (PFS) and overall survival (OS) in both cohorts. Moreover, patients with HHLA2/PD-L1 co-expression suffered the highest risk of disease progression and death by a significant margin. Besides, HHLA2/PD-L1 co-expression was significantly associated with a high density of CD8+ and CD4+ TILs. Notably, a new immune classification, based on HHLA2/PD-L1 co-expression and TILs, successfully stratified PFS and OS, especially in patients with TILs positivity. CONCLUSIONS:The expression of HHLA2 is more frequent than PD-L1 in ccRCC. HHLA2/PD-L1 co-expression had an adverse impact on the prognoses of patients with ccRCC; this finding provides a rationale for combination immunotherapy with anti-HHLA2 and PD-L1 blockage for patients with ccRCC in the future.
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Project description:BackgroundRecently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC).MethodsWe used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC.ResultThrough LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0-21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2-7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9-10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871.ConclusionsOur study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.
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Project description:The most common subtype of renal cell carcinoma is clear cell renal cell carcinoma (ccRCC). While localized ccRCC can be cured with surgery, metastatic disease has a poor prognosis. Recently, immunotherapy has emerged as a promising approach for advanced ccRCC. This review provides a comprehensive overview of the evolving immunotherapeutic landscape for metastatic ccRCC. Immune checkpoint inhibitors (ICIs) like PD-1/PD-L1 and CTLA-4 inhibitors have demonstrated clinical efficacy as monotherapies and in combination regimens. Combination immunotherapies pairing ICIs with antiangiogenic agents, other immunomodulators, or novel therapeutic platforms such as bispecific antibodies and chimeric antigen receptor (CAR) T-cell therapy are areas of active research. Beyond the checkpoint blockade, additional modalities including therapeutic vaccines, cytokines, and oncolytic viruses are also being explored for ccRCC. This review discusses the mechanisms, major clinical trials, challenges, and future directions for these emerging immunotherapies. While current strategies have shown promise in improving patient outcomes, continued research is critical for expanding and optimizing immunotherapy approaches for advanced ccRCC. Realizing the full potential of immunotherapy will require elucidating mechanisms of response and resistance, developing predictive biomarkers, and rationally designing combination therapeutic regimens tailored to individual patients. Advances in immunotherapy carry immense promise for transforming the management of metastatic ccRCC.
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