Effect of CHST11, a novel biomarker, on the biological functionalities of clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor, and the role of carbohydrate sulfotransferase 11 (CHST11) in this cancer remains unclear. Here, by using bioinformatics methods, we comprehensively analyzed the relationship between CHST11 and clinical significance, immune infiltration, functional enrichment, m6A methylation, and protein-protein interaction networks. We found that CHST11 expression was significantly higher in ccRCC samples than in normal tissues. Additionally, CHST11 levels correlated with the clinicopathological features of ccRCC patients and functioned as a prognostic factor for patient survival. Functional analysis revealed the involvement of CHST11 in metabolic pathways. Immune infiltration and m6A methylation analysis suggested the association of CHST11 with immune cell abundance in the tumor microenvironment and specific methylation patterns in ccRCC. The in vitro analysis of the clinical samples and ccRCC cell lines demonstrated that the overexpression of CHST11 promotes ccRCC cell proliferation, migration, and invasion, while its suppression has the opposite effect. Thus, CHST11 may play a remarkable role in the occurrence and progression of ccRCC. Functionally, CHST11 promotes the aggressiveness of ccRCC cells. These findings provide insights into the role of CHST11 in ccRCC progression.Registry and the Registration No. of the study/trial: No. 2021K034.

A novel necroptosis-related long noncoding RNA model for predicting clinical features, immune characteristics, and therapeutic response in clear cell renal cell carcinoma.

Background: Necroptosis is an immune-related cell death pathway involved in the regulation of the tumor microenvironment (TME). Here, we aimed to explore the role of necroptosis in clear cell renal cell carcinoma (ccRCC) and construct a necroptosis-related lncRNA (NRL) model to assess its potential association with clinical characteristics and immune status. Methods: Gene expression profiles and clinical data for ccRCC patients were obtained from the Cancer Genome Atlas (TCGA). Pearson's correlation, univariate Cox, and least absolute shrinkage and selection operator analyses were used to develop an NRL model. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to determine the prognostic value of the NRL model. The clinical information was used to assess the diagnostic value of the NRL model. The TME, immune function, immune cell infiltration, and immune checkpoints associated with the NRL model risk score were studied using the ESTIMATE, GSEA, ssGSEA, and CIBERSORT algorithms. The immunophenoscore (IPS) and half-maximal inhibitory concentration (IC50) were used to compare the efficacies of immunotherapy and chemotherapy based on the NRL model. Finally, in vitro assays were performed to confirm the biological roles of NRLs. Results: A total of 18 necroptosis-related genes and 285 NRLs in ccRCC were identified. A four-NRL model was constructed and showed good performance in the diagnosis and prognosis of ccRCC patients. The ESTIMATE scores, tumor mutation burden, and tumor stemness indices were significantly correlated with NRL model risk score. Immune functions such as chemokine receptors and immune receptor activity showed differences between different risk groups. The infiltration of immunosuppressive cells such as Tregs was higher in high-risk patients than in low-risk patients. High-risk patients were more sensitive to immunotherapy and some chemotherapy drugs, such as sunitinib and temsirolimus. Finally, the expression of NRLs included in the model was verified, and knocking down these NRLs in tumor cells affected cell proliferation, migration, and invasion. Conclusion: Necroptosis plays an important role in the progression of ccRCC. The NRL model we constructed can be used to predict the clinical characteristics and immune features of ccRCC patients.

ALDOB represents a potential prognostic biomarker for patients with clear cell renal cell carcinoma.

Background: Previous studies have shown that aldolase B (ALDOB) might play controversial roles in multiple types of cancer, which could act as a cancer-promoting factor or a cancer-inhibiting factor depending on the subtype of the cancer. However, the role of ALDOB in clear cell renal cell carcinoma (ccRCC) patients has not been clearly elucidated. Therefore, this study aimed to comprehensively explore the expression level, prognostic value, functional enrichment, immune infiltration, and N6-methyladenosine (m6A) modification of ALDOB in ccRCC patients. Methods: A total of 1,070 ccRCC tissues and 409 normal tissues from the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) database, and the ArrayExpress database were enrolled to evaluate the expression level and prognostic value of ALDOB in ccRCC. The Kaplan-Meier survival curves and the Log-Rank test were performed to assess the prognostic value. The univariate and multivariate Cox regression analysis were used to identify the independent prognostic predictors in ccRCC patients. In addition, R version 4.2.0 with its suitable packages were used to perform the functional enrichment analysis, immune infiltration analysis, and m6A methylation analysis. Statistical significance was set at the P value <0.05. Results: The expression level of ALDOB was significantly down-regulated in ccRCC compared to normal tissue, and the ALDOB expression level was noticeably correlated with T stage, M stage, and histologic grade of patients with ccRCC. The survival analysis revealed that ALODB was the independent predictor of overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) of ccRCC patients. In addition, the functional enrichment analysis showed that ALDOB and its related genes were mainly involved in the metabolism and metabolic pathways of multiple substances, including glycolysis, gluconeogenesis, and fatty acid degradation. Finally, the immune infiltration analysis and the m6A methylation analysis suggested that ALDOB was closely correlated with the infiltration abundance of immune cells and stromal cells in the tumor microenvironment and several types of m6A regulators in ccRCC. Conclusions: As a potential prognostic biomarker for patients with ccRCC, downregulation of ALDOB was closely associated with the clinicopathological features, poor prognosis, immune infiltration, and m6A modification in ccRCC patients.

Development and validation of a novel 5 cuproptosis-related long noncoding RNA signature to predict diagnosis, prognosis, and drug therapy in clear cell renal cell carcinoma.

Background: Cuproptosis has been reported as a new form of cell death. However, its potential mechanism of action in clear cell renal cell carcinoma (ccRCC) remains unclear. Therefore, we systematically clarified the role of cuproptosis in ccRCC and aimed to develop a novel signature of cuproptosis-related long noncoding RNAs (lncRNA) (CRLs) to assess the clinical characteristics of ccRCC patients. Methods: Gene expression, copy number variation, gene mutation, and clinical data for ccRCC were obtained from The Cancer Genome Atlas (TCGA). CRL signature was constructed with least absolute shrinkage and selection operator (LASSO) regression analysis. The clinical diagnostic value of the signature was verified by clinical data. The prognostic value of the signature was detected by Kaplan-Meier analysis and receiver operating characteristic (ROC) curve. The prognostic value of the nomogram was evaluated by calibration curves, ROC curves, and decision curve analysis (DCA). Gene set enrichment analysis (GSEA), single sample GSEA (ssGSEA) and cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm were used to analyze the differences of immune function and immune cell infiltration among different risk groups. Prediction of clinical treatment differences in populations with different risks and susceptibilities was completed with R package (The R Foundation of Statistical Computing). Verification of key lncRNA expression was performed by quantitative real-time polymerase chain reaction (qRT-PCR). Results: The cuproptosis-related genes were extensively dysregulated in ccRCC. A total of 153 differentially expressed prognostic CRLs were identified in ccRCC. Furthermore, a 5-lncRNA signature (AC015912.3, AC026401.3, AC103706.1, AC134312.5, and EMX2OS) were obtained that showed good performance in the diagnosis and prognosis of ccRCC. The nomogram could more accurately predict overall survival (OS). Immune functions such as T-cell and B-cell receptor signaling pathways showed differences between different risk groups. Clinical treatment value analysis showed that the signature may be able to effectively guide immunotherapy and target therapy. In addition, qRT-PCR results showed significant differences in the expression of key lncRNAs in ccRCC. Conclusions: Cuproptosis plays an important role in the progression of ccRCC. The 5-CRL signature can guide the prediction of clinical characteristics and tumor immune microenvironment of ccRCC patients.

Isl1 promotes gene transcription through physical interaction with Set1/Mll complexes.

Histone H3 lysine 4 (H3K4) methylation is generally recognized as a prominent marker of gene activation. While Set1/Mll complexes are major methyltransferases that are responsible for H3K4 methylation, the mechanism of how these complexes are recruited into the target gene promotor is still unclear. Here, starting with an affinity purification-mass spectrometry approach, we have found that Isl1, a highly tissue-specific expressed LIM/homeodomain transcription factor, is physically associated with Set1/Mll complexes. We then show that Wdr5 directly binds to Isl1. And this binding is likely mediated by the homeodomain of Isl1. Functionally, using mouse ß-cell and human neuroblastoma tumor cell lines, we show that both Wdr5 binding and H3K4 methylation level at promoters of some Isl1 target genes are significantly reduced upon depletion of Isl1, suggesting Isl1 is required for efficient locus-specific H3K4 methylation. Taken together, our results establish a critical role of Set1/Mll complexes in regulating the target gene expression of Isl1.