Metabolic Understanding of the Genetic Dysregulation in the Tumor Microenvironment of Kidney Renal Clear Cell Carcinoma.
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ABSTRACT:
SUBMITTER: Xie J
PROVIDER: S-EPMC8794690 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe tumor microenvironment (TME) is a complex and evolving environment, and the tumor immune microenvironment in kidney renal clear cell carcinoma (KIRC) has a strong suppressive profile. This study investigates the potential prognostic role and value of genes of the tumor microenvironment in KIRC.MethodsThe transcriptome sequencing data of 530 cases and 39 cases of KIRC and the corresponding clinical prognosis information were downloaded from TCGA data and GEO data, respectively, and TME-related gene expression profiles were extracted. A prognostic signature was constructed and evaluated using univariate Cox regression analysis and LASSO regression analysis. Gene set enrichment analysis (GSEA) was used to obtain the biological process of gene enrichment in patients with high and low-risk groups.ResultsA prognostic signature consisting of eight TME-related genes (LRFN1, CSF1, UCN, TUBB2B, SERPINF1, ADAM8, ABCB4, CCL22) was constructed. Kaplan-Meier survival analysis yielded significantly lower survival times for patients in the high-risk group than in the low-risk group, and the AUC values for the ROC curves of this prognostic signature were essentially greater than 0.7, and univariate and multifactorial Cox regression analyses indicated that the risk score was independent risk factors for KIRC prognosis. GSEA analysis showed that immune-related biological processes were enriched in the high-risk group and that risk values were strongly associated with multiple immune cell scores and immune checkpoint-related genes (PDCD1, CTLA4).ConclusionsThe prognostic signature can accurately predict the prognosis of KIRC patients, which may provide new ideas for future precision immunotherapy of KIRC.
| S-EPMC9290677 | biostudies-literature
Project description:Background: Tumor microenvironment (TME) plays indisputable role in the progression of cancers. Immune cell infiltration (ICI) in TME was related to the prognosis of tumor patients. In this paper, we identified the pattern of immune-related ICI subtypes based on the TME immune infiltration pattern. Methods: The data from kidney renal clear cell carcinoma data (KIRC) was downloaded from the TCGA database. The distinct ICI subtypes were identified using CIBERSORT and ESTIMATE algorithms. The gene subgroups were identified based on DEGs in ICI subtypes. The single sample gene set enrichment analysis (ssGSEA) was used to ascertain the ICI score. Kaplan-Meier curve with log-rank test was conducted to analyze the survival probability of patients with KIRC in different subtypes. Results: The patients with high ICI scores exhibited a longer survival time and lower expression of checkpoint-related and immune activity-related genes. The high ICI score clusters were positively related to TMB. The patients in the low TMB subgroups have a favorable prognosis. The prediction ICI score did not affect the TMB status, and the low TMB subgroups + low/high ICI score subgroups exhibited better survival. Conclusion: In all, the tumor immune microenvironment, ICI score, and TMB were important determinants of KIRC patients’ survival outcomes. The TMB + ICI score may be a potential biomarker for predicting the prognosis of patients and for targeted immunotherapies to treating KIRC.
| S-EPMC9277187 | biostudies-literature
Project description:BackgroundDue to the different infiltration abundance of immune cells in tumor, the efficacy of immunotherapy varies widely among individuals. Recently, growing evidence suggested that cuproptosis has impact on cancer immunity profoundly. However, the comprehensive roles of cuproptosis-related genes in tumor microenvironment (TME) and in response to immunotherapy are still unclear.MethodsBased on 43 cuproptosis-related genes, we employed unsupervised clustering to identify cuproptosis-related patterns and single-sample gene set enrichment analysis algorithm to build a cuproptosis signature for individual patient's immune cell infiltration and efficacy of immune checkpoint blockade (ICB) evaluation. Then, the cuproptosis-related genes were narrowed down using univariate Cox regression model and least absolute shrinkage and selection operator algorithm. Finally, a cuproptosis risk score was built by random survival forest based on these narrowed-down genes.ResultsTwo distinct cuproptosis-related patterns were developed, with cuproptosis cluster 1 showing better prognosis and higher enrichment of immune-related pathways and infiltration of immune cells. For individual evaluation, the cuproptosis signature that we built could be used not only for predicting immune cell infiltration in TME but also for evaluating an individual's sensitivity to ICBs. Patients with higher cuproptosis signature scores exhibited more activated cancer immune processes, higher immune cell infiltration, and better curative efficacy of ICBs. Furthermore, a robust cuproptosis risk score indicated that patients with higher risk scores showed worse survival outcomes, which could be validated in internal and external validation cohorts. Ultimately, a nomogram which combined the risk score with the prognostic clinical factors was developed, and it showed excellent prediction accuracy for survival outcomes.ConclusionDistinct cuproptosis-related patterns have significant differences on prognosis and immune cell infiltration in kidney renal clear cell carcinoma (KIRC). Cuproptosis signature and risk score are able to provide guidance for precision therapy and accurate prognosis prediction for patients with KIRC.
| S-EPMC9540508 | biostudies-literature
Project description:BackgroundKidney renal clear cell carcinoma (KIRC) affects the genitourinary system. Although treatment of KIRC in early stages can be highly successful, this type of cancer is difficult to detect until later stages of disease that are less easily treatable. Previous studies have focused on tumor cells, but have ignored the contributions of the tumor microenvironment.MethodsWe analyzed KIRC gene expression data from The Cancer Genome Atlas with the ESTIMATE algorithm to identify differentially expressed genes. Through protein-protein interaction network analysis, we identified clusters and picked genes from the clusters for further analysis. Differential expression, Kaplan-Meier, and univariate Cox analyses were used to select prognostic biomarkers. Gene Set Enrichment Analysis (GSEA) and Tumor Immune Estimation Resource (TIMER) analysis were used to explore the immune characteristics of these genes as biomarkers.ResultsThrough the ESTIMATE algorithm and other system biology tools, TNFSF13B was identified as a prognostic biomarker. TNFSF13B is highly expressed in tumors, and high expression of TNFSF13B leads to poor prognosis. Further GSEA and TIMER analysis revealed that the expression of TNFSF13B was related to the immune signaling pathway and lymphocyte infiltration. Our findings strongly suggest that TNFSF13B may be a potential biomarker or target related to the tumor microenvironment for KIRC.
| S-EPMC7333652 | biostudies-literature
Project description:Previous studies have demonstrated that direct targeting of interstitial cancer-associated fibroblasts (CAF) and tumor fibrosis alone seemed to be an unpromising treatment option for malignant tumors. Therefore, it is necessary to further explore the mechanism of the influence of collagen and tumor fibrosis on the biological behavior of malignant tumors. The current study aimed to explore the effect of intratumor fibrosis on the prognosis of renal clear cell carcinoma (ccRCC) and its mechanism. With the bioinformatic analysis of The Cancer Genome Atlas (TCGA) database (n = 537), the study showed that high Collagen type I α 1 (COL1A1) mRNA expression indicated the poor prognosis of ccRCC patients compared with low expression ones. We further used the Two-photon-excited fluorescence (TPEF)/second harmonic generation (SHG) microscopy to determine the intratumor fibrosis of 68 patients with surgical resection of ccRCC and confirmed that a high fibrosis level in the tumor was associated with a poor prognosis compared with patients with low expression (Progression-Free Survival: p = 0.030). We further measured the protein chips of 640 cytokines in ccRCC specimens and found that several cytokines, including prolactin (PRL), were associated with the degree of fibrosis in the tumor, as confirmed by the prolactin receptor (PRLR) immunohistochemical method. In addition, the study showed that PRLR expression decreased significantly in the ccRCC compared with adjacent normal tissue (p < 0.05). Our research shows that low expression of PRLR predicted the poor survival of the patient. We used the Cell Counting Kit-8 experiment, the transwell and the plate clone formation assay to evaluate the role of PRL in the 7860 and the ACHN cell lines. We found that PRL promoted ccRCC cell proliferation and migration. JAK-STAT3 activation was found in the high prolactin expression group by mass spectrum analysis. This study delineated the fibrosis-based tumor microenvironment characteristics of ccRCC. PRL/PRLR may be involved in the fibrosis process and are essential prognostic risk factors for ccRCC.
| S-EPMC8446447 | biostudies-literature
Project description:Background: M7G modification is extremely vital for the development of many cancers, especially tumor immunity. M7G modification is a novel functional regulator of miRNA, and the researches on m7G-related miRNAs in kidney renal clear cell carcinoma (KIRC) are still insufficient. This research aims to establish a risk signature on the foundation of m7G-associated miRNAs, which can precisely forecast the prognosis of KIRC patients. Methods: Transcriptome data and clinical data used in this study come from The Cancer Genome Atlas database. Our team utilized univariable Cox, Lasso and multivariable Cox analyses to construct a m7G-associated miRNAs risk signature that can forecast the prognosis of KIRC patients. Kaplan-Meier method, time-dependent receiver operating characteristic (ROC) curve, and the independent analysis of risk signatures were employed to verify the predictability and accuracy of the risk signature. Subsequently, based on CIBERSORT, ESTIMATE and ssGSEA algorithms, we speculated the potential impact of the proposed risk signature on tumor immune microenvironment. Ultimately, by virtue of the risk signature and tumor immunity, the hub genes affecting the prognosis of KIRC patients were screened out. Results: Our team established and verified a prognostic signature comprising 7 m7G-associated miRNAs (miR-342-3p, miR-221-3p, miR-222-3p, miR-1277-3p, miR-6718-5p, miR-1251-5p, and miR-486-5p). The results of the Kaplan-Meier survival analysis revealed that the prognosis of KIRC sufferers in the high-risk group was often unsatisfactory. The accuracy of the prediction ability of the risk signature was verified by calculating the area under the ROC curve. Univariate-multivariate Cox analyses further showed that this risk signature could be utilized as an independent prognosis-related biomarker for KIRC sufferers. The results of the immune analysis revealed that remarkable diversities existed in immune status and tumor microenvironment between high-risk and low-risk groups. On the foundation of the proposed risk signature and other clinical factors, a nomogram was established to quantitatively forecast the survival of KIRC sufferers at 1, 3 and 5 years. Conclusion: Based on m7G-related miRNAs, a risk signature was successfully constructed, which could precisely forecast the prognosis of sufferers and guide personalized immunotherapy for KIRC patients.
| S-EPMC9263547 | biostudies-literature
Project description:The incidence of kidney renal clear cell carcinoma (KIRC) is rising worldwide, and the prognosis is poor. Cuproptosis is a new form of cell death that is dependent on and regulated by copper ions. The relationship between cuproptosis and KIRC remains unclear. In the current study, changes in cuproptosis-related genes (CRGs) in TCGA-KIRC transcriptional datasets were characterized, and the expression patterns of these genes were analyzed. We identified three main molecular subtypes and discovered that multilayer CRG changes were associated with patient clinicopathological traits, prognosis, elesclomol sensitivity, and tumor microenvironment (TME) cell infiltration characteristics. Then, a CRG score was created to predict overall survival (OS). The CRG score was found to be strongly linked to the TME. These findings may help elucidate the roles of CRGs in KIRC, potentially enhancing understanding of cuproptosis and supporting the development of more effective immunotherapy strategies.
| S-EPMC9299088 | biostudies-literature
Project description:BackgroundIt is well known that chronic inflammation can promote the occurrence and progression of cancer. As a type of proinflammatory death, pyroptosis can recast a suitable microenvironment to promote tumor growth. However, the potential role of pyroptosis in clear cell renal cell carcinoma (ccRCC) remains unclear.MethodsThe transcriptome expression profile and mutation profile data of ccRCC with clinical characteristics included in this study were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering was used for clustering. Gene set enrichment analysis (GSEA) analysis were applied to evaluate the biological mechanisms. Single sample gene set enrichment analysis (ssGSEA) was applied for evaluating the proportion of various immune infiltrating cells. The ESTIMATE algorithm was involved to compute the immune microenvironment scores.ResultsAmong the 17 pyroptosis regulators, a total of 15 pyroptosis regulators were differential expressed between tumor and normal tissues, in which 12 of them emerged strong correlations with prognoses. According to the pyroptosis components, the ccRCC patients were divided into four pyroptosis subtypes with different clinical, molecular, and pathway characteristics. Compared with other clusters, cluster B showed the pyroptosis heat phenotype, while cluster D represented the pyroptosis cold phenotype with poor overall survival. In addition, we performed principal component analysis (PCA) on the differential genes between clusters to construct the pyroptosis index. Furthermore, the pyroptosis index was significantly correlated with survival in different tumor mutation statuses and different grades and stages. Besides, the expression of pyroptosis-related regulators was related to the infiltration of immune cells and the expression of immune checkpoints, among which AIM2 was considered as the most significant immune-related pyroptosis regulator. Ultimately, we found that AIM2 was related to the immune activation pathway and was significantly overexpressed in tumor tissues.ConclusionThis study revealed that pyroptosis regulators and pyroptosis index played an important role in the development and prognoses of ccRCC. Moreover, AIM2 can be used as a predictor of the response of immunotherapy. Assessing the pyroptosis patterns may help evaluate the tumor status and guide immunotherapy strategies.
| S-EPMC8766752 | biostudies-literature
Project description:Increasing evidence suggests the essential regulation of RNA N6-methyladenosine (m6A) modification in carcinogenesis and immune response. Nevertheless, the potential impacts of these modifications on the tumor microenvironment (TME) immune cell infiltration characteristics in clear-cell renal cell carcinoma (ccRCC) remain unclear. Utilizing a consensus clustering algorithm, we determined three m6A modification patterns and identified three m6A-related gene clusters among 569 ccRCC samples, which were associated with different biological functions and clinical outcomes. Thereafter, the m6A score was constructed using m6A-associated signature genes to accurately exploit the m6A modification patterns within individual tumors. The m6A score was further demonstrated to be noticeably related to ccRCC prognosis. In addition, the m6A score was found to be strongly correlated with tumor mutational burden (TMB), microsatellite instability, immune infiltration, immune checkpoint expression, and immunotherapy response, which was also validated in the pan-cancer analyses. Our findings thoroughly elucidated that m6A modification contributes to tumor microenvironment immune-infiltrating characteristics and prognosis in ccRCC. Assessing the m6A modification patterns of individual patients with ccRCC will offer novel insights into TME infiltration and help develop more effective treatment strategies.
| S-EPMC9068873 | biostudies-literature
Project description:Kidney cancer encompasses a range of primary cancers, such as clear cell renal cell carcinoma (ccRCC) and papillary renal cell carcinoma (pRCC). Our knowledge about the tumor microenvironment (TME) of kidney cancer is still limited. Therefore, we comprehensively assessed the TME of kidney cancers (including ccRCC and pRCC) using the ESTIAMTE, and CIBERSORT algorithms, and conducted distinct functional and correlation analyses with data from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Gene Expression Omnibus (GEO), Connectivity map and CellMiner database. Next, we identified two immune-related hub genes, IGLL5 and IL2RA, which play essential roles in the TME as well as on survival in ccRCC and pRCC. Furthermore, ccRCC and pRCC samples from our medical center were collected to verify the clinical application value of these two immune-related genes. A specific enrichment analysis of immune cells related to IGLL5 and IL2RA was also conducted in two types of renal cell cancer. Based on selected genes, we predicted the drug response and uncovered novel drug candidate for RCC treatment. Considering the unfavorable outcomes of kidney cancer and emerging interest in TME-targeted treatments, our results may offer insights into immune-related molecular mechanisms and possible targets to control the kidney cancer.
| S-EPMC8650138 | biostudies-literature