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A genomic instability-derived risk index predicts clinical outcome and immunotherapy response for clear cell renal cell carcinoma.

ABSTRACT: This study aims to originate agenomic instability-derived risk index (GIRI) for prognostic analysis of clear cell renal cell carcinoma (ccRCC) and explore the mutation characteristics, immune characteristics, and immunotherapy response defined by GIRI. Differentially expressed genome instability-associated genes were obtained from the genomic unstable (GU) group and the genomic stable (GS) group. Rigorous screening conditions were assigned to the screening of hub genes, which were then used to generate the GIRI through multivariate Cox regression analysis. The selected samples were assigned to the high-risk group or the low-risk group based on the median GIRI. Possible reasons for the prognostic differences in risk subgroups were explored from the aspects of mutation profiles, immune profiles, immunomodulators, and biological pathway activities. The possibility of immunotherapy response was predicted by Tumor Immune Dysfunction and Exclusion analysis results. The prediction of drugs that might reverse the expression profiles of the risk subgroups was discovered through theonnectivity Map (CMap). High-risk populations manifested poor overall survival than low-risk populations and were characterized by elevated cumulative mutation counts and tumor mutation burden. Also, high-risk populations had higher immune scores, immunomodulator (PD-1, CTLA4, LAG3, and TIGIT) expression, and genomic instability-related pathway activities, and were more likely to reap benefits from immunotherapy. Besides, we predicted several drugs (PI3K inhibitor, ATPase inhibitor, and phenylalanyl tRNA synthetase inhibitor) targeting risk subgroups. The well established GIRI was an effective cancer biomarker for predicting ccRCC prognosis and provided apotential reference value for identifying immunotherapy response.

SUBMITTER: Wu S

PROVIDER: S-EPMC8806326 | 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:BackgroundClear cell renal cell carcinoma (ccRCC) is a kind of frequently diagnosed cancer, leading to high death rate in patients. Genomic instability (GI) is regarded as playing indispensable roles in tumorigenesis and impacting the prognosis of patients. The aberrant regulation of long non-coding RNAs (lncRNAs) is a main cause of GI. We combined the somatic mutation profiles and expression profiles to identify GI derived lncRNAs (GID-lncRNAs) in ccRCC and developed a GID-lncRNAs based risk signature for prognosis prediction and medication guidance.MethodsWe decided cases with top 25% cumulative number of somatic mutations as genomically unstable (GU) group and last 25% as genomically stable (GS) group, and identified differentially expressed lncRNAs (GID-lncRNAs) between two groups. Then we developed the risk signature with all overall survival related GID-lncRNAs with least absolute shrinkage and selection operator (LASSO) Cox regression. The functions of the GID-lncRNAs were partly interpreted by enrichment analysis. We finally validated the effectiveness of the risk signature in prognosis prediction and medication guidance.ResultsWe developed a seven-lncRNAs (LINC00460, AL139351.1, AC156455.1, AL035446.1, LINC02471, AC022509.2, and LINC01606) risk signature and divided all samples into high-risk and low-risk groups. Patients in high-risk group were in more severe clinicopathologic status (higher tumor grade, pathological stage, T stage, and more metastasis) and were deemed to have less survival time and lower survival rate. The efficacy of prognosis prediction was validated by receiver operating characteristic analysis. Enrichment analysis revealed that the lncRNAs in the risk signature mainly participate in regulation of cell cycle, DNA replication, material metabolism, and other vital biological processes in the tumorigenesis of ccRCC. Moreover, the risk signature could help assess the possibility of response to precise treatments.ConclusionOur study combined the somatic mutation profiles and the expression profiles of ccRCC for the first time and developed a GID-lncRNAs based risk signature for prognosis predicting and therapeutic scheme deciding. We validated the efficacy of the risk signature and partly interpreted the roles of the seven lncRNAs composing the risk signature in ccRCC. Our study provides novel insights into the roles of genomic instability derived lncRNAs in ccRCC.

Project description:BackgroundClear cell carcinoma of the kidney is a common urological malignancy characterized by poor patient prognosis and treatment outcomes. Modulation of vasculogenic mimicry in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects.MethodsWe downloaded the data from renal clear cell carcinoma samples and vasculogenic mimicry-related genes to establish a new vasculogenic mimicry-related index (VMRI) using a machine learning approach. Based on VMRI, patients with renal clear cell carcinoma were divided into high VMRI and low VMRI groups, and patients' prognosis, clinical features, tumor immune microenvironment, chemotherapeutic response, and immunotherapeutic response were systematically analyzed. Finally, the function of CDH5 was explored in renal clear cell carcinoma cells.ResultsVMRI can be used for prognostic and immunotherapy efficacy prediction in a variety of cancers, which consists of four vasculogenic mimicry-related genes (CDH5, MMP9, MAPK1, and MMP13), is a reliable predictor of survival and grade in patients with clear cell carcinoma of the kidney and has been validated in multiple external datasets. We found that the high VMRI group presented higher levels of immune cell infiltration, which was validated by pathological sections. We performed molecular docking prediction of vasculogenic mimicry core target proteins and identified natural small molecule drugs with the highest affinity for the target protein. Knockdown of CDH5 inhibited the proliferation and migration of renal clear cell carcinoma.ConclusionsThe VMRI identified in this study allows for accurate prognosis assessment of patients with renal clear cell carcinoma and identification of patient populations that will benefit from immunotherapy, providing valuable insights for future precision treatment of patients with renal clear cell carcinoma.

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A genomic instability-derived risk index predicts clinical outcome and immunotherapy response for clear cell renal cell carcinoma.

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