The Downregulation of Prognosis- and Immune Infiltration-Related Gene CYFIP2 Serves as a Novel Target in ccRCC

CA9, CYFIP2 and LGALS3BP-A Novel Biomarker Panel to Aid Prognostication in Glioma

Brain cancer is a devastating and life-changing disease. Biomarkers are becoming increasingly important in addressing clinical issues, including in monitoring tumour progression and assessing survival and treatment response. The goal of this study was to identify prognostic biomarkers associated with glioma progression. Discovery proteomic analysis was performed on a small cohort of astrocytomas that were diagnosed as low-grade and recurred at a higher grade. Six proteins were chosen to be validated further in a larger cohort. Three proteins, CA9, CYFIP2, and LGALS3BP, were found to be associated with glioma progression and, in univariate analysis, could be used as prognostic markers. However, according to the results of multivariate analysis, these did not remain significant. These three proteins were then combined into a three-protein panel. This panel had a specificity and sensitivity of 0.7459 for distinguishing between long and short survival. In silico data confirmed the prognostic significance of this panel.

Downregulation of RNA binding protein 47 predicts low survival in patients and promotes the development of renal cell malignancies through RNA stability modification

RNA binding proteins (RBPs) are crucial for cell function, tissue growth, and disease development in disease or normal physiological processes. RNA binding motif protein 47 (RBM47) has been proven to have anti-tumor effects on many cancers, but its effect is not yet clear in renal cancer. Here, we demonstrated the expression and the prognostic role of RBM47 in public databases and clinical samples of clear cell renal carcinoma (ccRCC) with bioinformatics analysis. The possible mechanism of RBM47 in renal cancer was verified by gene function prediction and in vitro experiments. The results showed that RBM47 was downregulated in renal cancers when compared with control groups. Low RBM47 expression indicated poor prognosis in ccRCC. RBM47 expression in renal cancer cell lines was reduced significantly when compared to normal renal tubular epithelial cells. Epithelial-mesenchymal transition (EMT) and transforming growth factor-β signaling pathway was associated with RBM47 in ccRCC by Gene set enrichment analysis. RBM47 expression had a positive correlation with e-cadherin, but a negative correlation with snail and vimentin. RBM47 overexpression could repress the migration, invasion activity, and proliferation capacity of renal cancer cells, while RBM47 inhibition could promote the development of the malignant features through EMT signaling by RNA stability modification. Therefore, our results suggest that RBM47, as a new molecular biomarker, may play a key role in the cancer development of ccRCC.

Cuproptosis in ccRCC: key player in therapeutic and prognostic targets

Background

Classical biomarkers have been used to classify clear cell renal cell carcinoma (ccRCC) patients in a variety of ways, and emerging evidences have indicated that cuproptosis is closely related to mitochondrial metabolism, thereby accelerating the development and progression of ccRCC. Nevertheless, the specific relationship between cuproptosis and the prognosis and treatment of ccRCC remains unclear.

Methods

We comprehensively integrated several ccRCC patient datasets into a large cohort. Following that, we systematically analyzed multi-omics data to demonstrate the differences between two cuproptosis clusters.

Results

We identified two cuproptosis clusters in ccRCC patients. Among the two clusters, cluster 1 patients showed favorable prognosis. We then confirmed the significant differences between the two clusters, including more typical cancer hallmarks were enriched in cluster 2 patients; cluster 2 patients were more susceptible to develop mutations and had a lower level of gistic score and mRNAsi. Importantly, both Tumor Immune Dysfunction and Exclusion analysis and subclass mapping algorithm showed that cuproptosis 1 patients were more susceptible to be responded to immunotherapy. In addition, a prognostic signature was successfully developed and also showed prominent predictive power in response to immunotherapy.

Conclusion

As a result of our findings, we were able to classify ccRCC patients according to cuproptosis in a novel way. By constructing the cuproptosis clusters and developing the signature, patients with ccRCC could have a more accurate prognosis prediction and better immunotherapy options.

CYFIP2 serves as a prognostic biomarker and correlates with tumor immune microenvironment in human cancers

BACKGROUND

The mechanisms whereby CYFIP2 acts in tumor development and drives immune infiltration have been poorly explored. Thus, this study aimed to identifying the role of CYFIP2 in tumors and immune response.

METHODS

In this study, we first explored expression patterns, diagnostic role and prognostic value of CYFIP2 in cancers, particularly in lung adenocarcinoma (LUAD). Then, we performed functional enrichment, genetic alterations, DNA methylation analysis, and immune cell infiltration analysis of CYFIP2 to uncover its potential mechanisms involved in immune microenvironment.

RESULTS

We found that CYFIP2 significantly differentially expressed in different tumors including LUAD compared with normal tissues. Furthermore, CYFIP2 was found to be significantly correlated with clinical parameters in LUAD. According to the diagnostic and survival analysis, CYFIP2 may be employed as a potential diagnostic and prognostic biomarker. Moreover, genetic alterations revealed that mutation of CYFIP2 was the main types of alterations in different cancers. DNA methylation analysis indicated that CYFIP2 mRNA expression correlated with hypomethylation. Afterwards, functional enrichment analysis uncovered that CYFIP2 was involved in tumor-associated and immune-related pathways. Immune infiltration analysis indicated that CYFIP2 was significantly correlated with immune cells infiltration. In particular, CYFIP2 was strongly linked with immune microenvironment scores. Additionally, CYFIP2 exhibited a significant relationship with immune regulators and immune-related genes including chemokines, chemokines receptors, and MHC genes.

CONCLUSION

Our results suggested that CYFIP2 may serve as a prognostic cancer biomarker for determining prognosis and might be a promising therapeutic strategy for tumor immunotherapy.

Single-cell and transcriptome analysis reveals TAL cells in diabetic nephropathy

Diabetic nephropathy is a global public health concern with multifaceted pathogenesis, primarily involving hypertension. Excessive activation of AT1R has been strongly associated with hypertension onset and progression in diabetic nephropathy. This study aimed to conduct thick ascending limb cell single-cell and transcriptomic analysis in diabetic nephropathy, including screening for biological markers, cellular communication, and immune infiltration, to identify potential biomarkers and effective means for prevention and treatment. By using high-dimensional weighted gene co-expression network analysis, least absolute shrinkage and selection operator, machine learning, neural deconvolution, quasi-chronological analysis, non-negative matrix factorization clustering, and monocyte chemotactic protein-induced counter, we identified 7 potential thick ascending limb cell biomarkers for diabetic nephropathy and elucidated the bone morphogenetic protein pathway's regulation of thick ascending limb cells through podocyte epithelial cells and podocyte cells. The study also highlighted the role of COBL, PPARGC1A, and THSD7A in non-negative matrix factorization clustering and their relationship with thick ascending limb cell immunity in diabetic nephropathy. Our findings provide new insights and avenues for managing diabetic nephropathy, ultimately alleviating the burden on patients and society.

A Novel 7-Methylguanosine (m7G)-Related Gene Signature for Overall Survival Prediction in Patient with Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common pathology type of renal cancer that has an abysmal prognosis. Although a crucial role for 7-methylguanosine modification in cancer cell development has been reported, its role in ccRCC remains uncertain. This study was conducted to determine the efficacy of predictive biomarkers based on m7G-related genes in ccRCC. Firstly, we extracted clinical data and gene expression profiles of ccRCC patients from publicly accessible databases. It identified that 22 of the m7G-related 34 genes were related to overall survival, and 5 of the 22 genes were significantly expressed differently in tumor tissues. Based on Lasso regression analysis, five optimal genes (CYFIP2, EIF4A1, NUDT1, NUDT10, and NUDT4) were chosen to build a new predictive risk model in the TCGA cohort. Validation was carried out with the E-MTAB-1980 cohort. Then, a prognostic nomogram was erected, including the m7G-related gene risk score, age, histological grade, and stage status. Further studies and analysis showed that immune cell infiltration might be associated with the m7G-related risk genes. In addition, the relationship between gene expression and drug response was evaluated by the Pearson correlation test. Therefore, the risk signature with five selected m7G-related genes may be a promising prognostic biomarker and contribute to standardized prognostic assessment for ccRCC.

Identification of a Novel Myc-Regulated Gene Signature for Patients with Kidney Renal Clear Cell Carcinoma

Given that myc was known to be a cancer-causing gene in several cancers including kidney renal clear cell carcinoma (KIRC). We aimed to construct myc-regulated genes (MRGs)-based prognostic signature. We obtained the mRNA expression and clinical data of KIRC from The Cancer Genome Atlas (TCGA) database and MRGs from the Molecular Signature Database (MSigDB). Then, a prognostic signature consisting of 8 MRGs (IRF9, UBE2C, YBX3, CDKN2B, CKAP2L, CYFIP2, FBLN5, and PDLIM7) was developed by differential expression analysis, cox regression analysis, and least absolute shrinkage and selection operator (lasso) analysis. Patients with KIRC were divided into high- and low-risk groups based on risk scores of MRGs-based signatures. Patients in the high-risk group showed inferior clinical characteristics and survival. In addition, the risk score was an independent prognostic factor for KIRC, and the risk score=based nomogram displayed satisfactory performance to predict the survival of KIRC. The MRGs-based signature is also correlated with immune cell infiltration and the mRNA expression of important immune checkpoints (IDO2, PDCD1, LAG3, FOXP3, and TIGIT). The tumor mutation burden (TMB) landscape between the high- and low-risk groups showed higher levels of TMB in the high-risk group than in the low-risk group and that higher levels of TMB predicted a poorer prognosis in KIRC. Furthermore, patients with KIRC in the high-risk group are more likely to experience immune escape. At last, we found patients with KIRC in the high-risk group were more sensitive to several chemotherapy drugs such as sunitinib, gefitinib, nilotinib, and rapamycin than patients with KIRC in the low-risk group. Our study successfully constructed and validated an MRGs-based signature that can predict clinical characteristics, prognosis, level of immune infiltration, and responsiveness to immunotherapy and chemotherapy drugs in patients with KIRC.

Molecular Subtyping Based on Cuproptosis-Related Genes and Characterization of Tumor Microenvironment Infiltration in Kidney Renal Clear Cell Carcinoma

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.

EA, Wang M, Yan H, Huang X, Zeng S, Zha D. Analysis and Experimental Validation of Rheumatoid Arthritis Innate Immunity Gene CYFIP2 and Pan-Cancer

Rheumatoid arthritis (RA) is a chronic, heterogeneous autoimmune disease. Its high disability rate has a serious impact on society and individuals, but there is still a lack of effective and reliable diagnostic markers and therapeutic targets for RA. In this study, we integrated RA patient information from three GEO databases for differential gene expression analysis. Additionally, we also obtained pan-cancer-related genes from the TCGA and GTEx databases. For RA-related differential genes, we performed functional enrichment analysis and constructed a weighted gene co-expression network (WGCNA). Then, we obtained 490 key genes by intersecting the significant module genes selected by WGCNA and the differential genes. After using the RanddomForest, SVM-REF, and LASSO three algorithms to analyze these key genes and take the intersection, based on the four core genes (BTN3A2, CYFIP2, ST8SIA1, and TYMS) that we found, we constructed an RA diagnosis. The nomogram model showed good reliability and validity after evaluation, and the ROC curves of the four genes showed that these four genes played an important role in the pathogenesis of RA. After further gene correlation analysis, immune infiltration analysis, and mouse gene expression validation, we finally selected CYFIP2 as the cut-in gene for pan-cancer analysis. The results of the pan-cancer analysis showed that CYFIP2 was closely related to the prognosis of patients with various tumors, the degree of immune cell infiltration, as well as TMB, MSI, and other indicators, suggesting that this gene may be a potential intervention target for human diseases including RA and tumors.

Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas

Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.