Both RNA N6-methyladenosine (m6A) modification of SARS-CoV-2 and immune characteristics of the human body have been reported to play an important role in COVID-19, but how the m6A methylation modification of leukocytes responds to the virus infection remains unknown. Based on the RNA-seq of 126 samples from the GEO database, we disclosed that there is a remarkably higher m6A modification level of blood leukocytes in patients with COVID-19 compared to patients without COVID-19, and this difference was related to CD4+ T cells. Two clusters were identified by unsupervised clustering, m6A cluster A characterized by T cell activation had a higher prognosis than m6A cluster B. Elevated metabolism level, blockage of the immune checkpoint, and lower level of m6A score were observed in m6A cluster B. A protective model was constructed based on nine selected genes and it exhibited an excellent predictive value in COVID-19. Further analysis revealed that the protective score was positively correlated to HFD45 and ventilator-free days, while negatively correlated to SOFA score, APACHE-II score, and crp. Our works systematically depicted a complicated correlation between m6A methylation modification and host lymphocytes in patients infected with SARS-CoV-2 and provided a well-performing model to predict the patients’ outcomes.

Clear cell renal cell carcinoma (ccRCC) is one of the most common cancers in the world. Our aim is to identify prognostic biomarkers that contribute to the progression of early stage ccRCC and clarify the mechanism. Here, the mRNA microarray expression profile of ccRCC samples was obtained from Gene Expression Omnibus (GEO) (GSE68417). 62 differentially expressed genes (DEGs) were gained by R Studio, including 31 upregulated genes and 31 downregulated genes. Pathway enrichment analysis was performed in DAVID database. Then, the protein-protein interaction network was obtained through STRING database and visualized by Cytoscape. Subsequently, among the network, only inhibitor of DNA Binding 1 (ID1) was significant between low-grade and high-grade ccRCC patients in TCGA data set. After analysis of the corresponding clinical information in R Studio, it is shown that low ID1 expression correlated with poor survival, high probability of tumor metastasis, and relatively high serum calcium. Later, functional enrichment of ID1 in GeneMANIA uncovered that regulating DNA binding is a main characteristic of ID1 in ccRCC, which was validated by Kaplan-Meier curve of ID1 associated genes using KM plotter database and R Studio. Immune infiltration analysis performed by Tumor Immune Estimation Resource (TIMER) revealed that CD8+ T cells and macrophages were prognostic factors. Furthermore, Valproic acid was analyzed to be the most convinced target drug of ID1 identified by Comparative Toxicogenomics Database (CTD). Taken together, ID1, a biomarker of clinical outcome in early stage ccRCC patients, has the potential function of preventing deterioration in ccRCC progression and metastasis.

Clear cell renal cell carcinoma (ccRCC) is one of the most lethal urological malignancies with high tumor heterogeneity, and reliable biomarkers are still needed for its diagnosis and prognosis. WEE family kinases function as key regulators of the G2/M transition, have essential roles in maintaining cellular genomic stability and have the potential to be promising therapeutic targets in various tumors. However, the roles of WEE family kinases in ccRCC remain undetermined. In the present study, we first explored multiple public datasets and found that PKMYT1 was up-regulated in both RCC tumors and cell lines. Expression levels of PKMYT1 were highly associated with pathological stage and grade. Kaplan-Meier curves showed that high PKMYT1 expression was associated with lower overall survival and disease-free survival. Receiver operating characteristic curves revealed that the expression of PKMYT1 could better distinguish ccRCC from normal samples. Functional enrichment analysis demonstrated that cell cycle- related pathways and epithelial to mesenchymal transition (EMT) might be potential mechanisms of PKMYT1 in ccRCC tumorigenesis. Moreover, knockdown of PKMYT1 in vitro attenuated the proliferation, migration and invasion of RCC cell lines, promoted cell apoptosis and prevented the EMT phenotype in vitro . In conclusion, our study demonstrated that PKMYT1 has the potential to act as a diagnostic and prognostic biomarker for RCC patients. Targeting PKMYT1 may be considered as a new potential therapeutic method and direction in RCCs.

Background: Six2, a transcription factor, exerts an oncogenic role in clear cell renal cell carcinoma (ccRCC). Increased Six2 expression could enhance cancer metastasis. However, the regulatory mechanism of Six2 in promoting metastasis remains unclear. The purpose of this study is to analyze the regulatory pattern of Six2 and the potential role of Six2 in the tumor immune microenvironment. Materials and Methods: Firstly, transcriptional data in TCGA-KIRC cohorts was used to analyze the relationship between Six2 expression and clinical information. Secondly, we detect the association between Six2 and the tumor immune microenvironment in ccRCC. Then, we analyzed Six2-related differentially expressed genes (DEGs) and constructed a prognostic model using the Lasso-Cox algorithm by integrating Six2 ChIP data and co-expressed genes. Next, we analyzed the clinical significance and immunotherapy sensitivity of this model. Results: Six2 was overexpressed in RCC cells compared with normal kidney cells and upregulated Six2 was positively linked with clinical stage, grade, T stage, M stage, and poor survival. And Six2 was correlated with the remodeling of the tumor microenvironment. Potential downstream effectors and biological functions regulated by Six2 were identified using in silico analysis. Meanwhile, a risk model based on 8 Six2 target genes was established to classify ccRCC patients into high-and-low risk groups. This risk model showed a reliable ability to forecast the overall survival of ccRCC patients and predict the susceptibility to immunotherapy. Conclusions: Our findings provide a promising prognostic indicator for ccRCC patients and help better understand the transcriptional and immunological role of Six2 in ccRCC.

BackgroundSix2, a transcription factor, exerts an oncogenic role in clear cell renal cell carcinoma (ccRCC). Increased Six2 expression could enhance cancer metastasis. However, the regulatory action of Six2 remains unclear in cancer. The purpose of this study is to analyze the regulatory pattern and potential downstream effectors of Six2.MethodsFirstly, transcriptional data in TCGA-KIRC cohorts was used to analyze the relationship between Six2 expression and clinical information. Then, we analyzed Six2-related differentially expressed genes (DEGs) and constructed a prognostic model using the Lasso-Cox algorithm by integrating Six2 ChIP data and co-expressed genes. Next, we analyzed the clinical significance of this model and examined the DEGs between the high-and low-risk group. Finally, we intersected the GO and KEGG pathway results between Six2-related DEGs and risk-related DEGs to reveal biological functions in which Six2 is involved.ResultsSix2 was increased in RCC cells compared with normal kidney cells and upregulated Six2 was positively linked with clinical stage, M stage, and worse survival. Potential downstream effectors and biological functions regulated by Six2 were identified using in silico analysis. Meanwhile, a risk model based on 8 Six2 target genes was established to classify ccRCC patients into high-and-low groups. This risk model showed a reliable ability to forecast the overall survival of ccRCC patients. Shared enriched pathways were found between the Six2 high-and low-expression and risk groups, such as epithelial-to-mesenchymal transition, PI3K-Akt pathway, etc.ConclusionOur findings provide a promising prognostic indicator for ccRCC patients and help better understand the transcriptional role of Six2 in ccRCC.