PPM1A suppresses the proliferation and invasiveness of RCC cells via Smad2/3 signaling inhibition

Sphingosine kinase 1 regulates lipid metabolism to promote progression of kidney renal clear cell carcinoma

PURPOSE

To detect the expression of sphingosine kinase 1 (SPHK1) in clear cell renal cell carcinoma (ccRCC) and explore its biological role in the occurrence and development of ccRCC through regulation of fatty acid metabolism.

METHODS

Using the Cancer Genome Atlas database, SPHK1 expression and its clinical significance were detected in clear cell renal cell carcinoma. Immunohistochemistry was performed to detect SPHK1 expression in RCC samples in our hospital. The connection between the SPHK1 levels and clinicopathological features of patients was assessed. Nile Red was used to detect fatty acids in cells. Cell Counting Kit-8 and 5-ethynyl-2'-deoxyuridine assays were performed to determine the effect of SPHK1 on renal cell viability and proliferation, respectively. Additionally, the effects of SPHK1 on the proliferation and metastasis of ccRCC were studied using wound healing and Transwell assays. Fatty acids were added exogenously in recovery experiments and western blotting was performed to determine the effect of SPHK1 on fatty acid metabolism in ccRCC. Finally, the effects of SPHK1 on tumor growth were investigated in a xenograft model.

RESULTS

Bioinformatics analysis revealed that SPHK1 expression was upregulated in kidney RCC. OverSPHK1 expression was associated with poor prognosis for ccRCC patients. High SPHK1 expression was detected in human ccRCC. SPHK1 expression was related to clinicopathological features, such as tumor size and Furman grade. Additionally, cell proliferation, migration, and invasion were inhibited in ccRCC cells with low SPHK1 expression. In rescue experiments, proliferation, migration, and invasion were restored. In vivo, reduced SPHK1 levels correlated with lower expression of fatty acid synthase, stearoyl-CoA desaturase 1, and acetyl CoA carboxylase, and slowed tumor growth.

CONCLUSIONS

SPHK1 is abnormally overexpressed in human ccRCC. Patients with ccRCC may benefit from treatments that target SPHK1, which may also serve as a prognostic indicator.

A three-snoRNA signature: SNORD15A, SNORD35B and SNORD60 as novel biomarker for renal cell carcinoma

BACKGROUND

Accumulating evidence has confirmed the role of snoRNAs in a variety of cancer, but rare in renal cell carcinoma (RCC). This study aims to clarify the role of snoRNAs in RCC tumorigenesis and their potential as novel tumor biomarkers.

MATERIALS AND METHODS

The snoRNA expression matrix was obtained from the public TCGA and SNORic databases. SNORD15A, SNORD35B and SNORD60 were selected and validated by qPCR, then analyzed combined with related clinical factors using T-test and ROC curve.

RESULTS

All three snoRNAs: SNORD15A, SNORD35B and SNORD60 were significantly upregulated in cancer tissues compared to adjacent tissues from TCGA or FFPE detection. These three snoRNAs were also increased in urinary sediment (US) of RCC as well as the early-stage RCC patients compared with the healthy controls. In addition, RNase stability experiments confirmed their stable existence in US. Meanwhile, the ROC curve shows that SNORD15A, SNORD35B and SNORD60 could effectively distinguish RCC (AUC = 0.7421) and early-stage RCC (AUC = 0.7465) from healthy individuals.

CONCLUSION

SNORD15A, SNORD35B and SNORD60 were upregulated in tissues and US of RCC, serving as novel potential biomarkers for RCC diagnosis.

Expression of gasdermin D in clear cell renal cell carcinoma and its effect on its biological function

Background

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma, which suffers from the lack of diagnosis and treatment methods, and many patients cannot be diagnosed at first time. Gasdermin D (GSDMD) is involved in inflammatory reactions and pyroptosis and is considered a potential therapeutic target. This paper's aim is to elucidate the expression of GSDMD in clear cell renal cell carcinoma and its value for treatment and prognosis, as well as its impact on the biological function of clear cell renal cell carcinoma.

Method

The Cancer Genome Atlas (TCGA) database was used to compare the expression of GSDMD in tumor and normal tissues, analyze its correlation with cancer stage and overall survival time, and establish receiver operating characteristic (ROC) curve, which was confirmed by the Gene Expression Omnibus (GEO) database and immunohistochemical staining of clinical samples and PCR and Western blotting (WB) of cell lines. The relationship between GSDMD and patient prognosis and staging was analyzed using TCGA database and validated using clinical sample data. Differentially expressed genes (DEGs) and epithelial-mesenchymal transition (EMT)-related genes of GSDMD were screened by TCGA database. Protein-protein interaction (PPI) of GSDMD was constructed by GeneMANIA and STRING, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were analyzed by the Metascape database. Then, R software was used to analyze the immune cell infiltration, immune microenvironment score, and tumor mutational burden (TMB) analysis of GSDMD high- and low-expression groups in TCGA database. GSDMD lentivirus was used to transfect 769-P cells to construct stable upregulated and downregulated transfected cell lines. PCR was used to verify the expression differences of differentially expressed genes between the high- and low-expression groups of GSDMD; then, MTT, flow apoptosis, and Transwell were used to detect the proliferation, apoptosis, invasion, and migration of the transfected cells.

Results

The results of bioinformatics analysis showed that the expression of GSDMD in clear cell renal cell carcinoma was significantly correlated with patient stage and overall survival, and the tumor with high expression of GSDMD had a worse stage and overall survival. GSDMD has some significance in the diagnosis of ccRCC. The results of EMT correlation analysis and enrichment analysis showed that GSDMD was correlated with genes and pathways related to invasion and metastasis of renal cell carcinoma. The subsequent immune cell infiltration analysis showed that there were many differences in the infiltration of immune cells between the high- and low-expression groups of GSDMD, such as naive B cells. The immune microenvironment score showed that the high-expression group had a lower proportion of stromal cells than the local expression group but had a higher proportion of immune cells. Through TMB, it was shown that the high-expression group had a higher mutation. The expression of GSDMD in renal cell carcinoma by immunohistochemistry and in vitro cell experiments was confirmed. According to the prognostic information of clinical patients, it was found that GSDMD was significantly correlated with TNM stage, Fuhrman grade, lymph node metastasis, gender, and smoking or not, and the prognosis of patients with high expression of GSDMD was worse. After that, we constructed stable transfection cell lines with high expression and knockdown through lentivirus transfection and verified the expression amount of differentially expressed genes by PCR, which is consistent with the results of TCGA database. Then, we confirmed that GSDMD is related to proliferation, invasion, migration, and apoptosis of ccRCC by MTT, flow apoptosis, and Transwell assay. The low expression of GSDMD inhibits the proliferation, invasion, and migration of tumors and enhances apoptosis and vice versa. Therefore, GSDMD can be used as a potential biological marker for the diagnosis and prognosis of ccRCC.

Establishment and Validation of a Machine Learning Prediction Model Based on Big Data for Predicting the Risk of Bone Metastasis in Renal Cell Carcinoma Patients

PURPOSE

Since the prognosis of renal cell carcinoma (RCC) patients with bone metastasis (BM) is poor, this study is aimed at using big data to build a machine learning (ML) model to predict the risk of BM in RCC patients.

METHODS

A retrospective study was conducted on 40,355 RCC patients in the SEER database from 2010 to 2017. LASSO regression and multivariate logistic regression analysis was performed to determine independent risk factors of RCC-BM. Six ML algorithm models, including LR, GBM, XGB, RF, DT, and NBC, were used to establish risk models for predicting RCC-BM. The prediction performance of ML models was weighed by 10-fold cross-validation.

RESULTS

The study investigated 40,355 patients diagnosed with RCC in the SEER database, where 1,811 (4.5%) were BM patients. Independent risk factors for BM were tumor grade, T stage, N stage, liver metastasis, lung metastasis, and brain metastasis. Among the RCC-BM risk prediction models established by six ML algorithms, the XGB model showed the best prediction performance (AUC = 0.891). Therefore, a network calculator based on the XGB model was established to individually assess the risk of BM in patients with RCC.

CONCLUSION

The XGB risk prediction model based on the ML algorithm performed a good prediction effect on BM in RCC patients.

A comprehensive overview of PPM1A: From structure to disease

PPM1A (magnesium-dependent phosphatase 1 A, also known as PP2Cα) is a member of the Ser/Thr protein phosphatase family. Protein phosphatases catalyze the removal of phosphate groups from proteins via hydrolysis, thus opposing the role of protein kinases. The PP2C family is generally considered a negative regulator in the eukaryotic stress response pathway. PPM1A can bind and dephosphorylate various proteins and is therefore involved in the regulation of a wide range of physiological processes. It plays a crucial role in transcriptional regulation, cell proliferation, and apoptosis and has been suggested to be closely related to the occurrence and development of cancers of the lung, bladder, and breast, amongst others. Moreover, it is closely related to certain autoimmune diseases and neurodegenerative diseases. In this review, we provide an insight into currently available knowledge of PPM1A, including its structure, biological function, involvement in signaling pathways, and association with diseases. Lastly, we discuss whether PPM1A could be targeted for therapy of certain human conditions.

lncRNA TSPEAR-AS2, a Novel Prognostic Biomarker, Promotes Oral Squamous Cell Carcinoma Progression by Upregulating PPM1A via Sponging miR-487a-3p

Background

Long noncoding RNA (lncRNA) critically impacts the modulation of tumor developments and progressions. Our study is aimed at investigating the expressing patterns, clinical significance, and biological roles of lncRNA TSPEAR-AS2 (TSPEAR-AS2) in oral squamous cell carcinoma (OSCC). Material and Approach. The expressing states achieved by TSPEAR-AS2 were examined in OSCC specimens and cell lines by RT-PCR. The clinical significance of TSPEAR-AS2 was statistically analyzed. OSCC proliferating, invading, and migrating processes were examined with the use of wound healing assays, transwell, colony formation, and cell counting kit-8. Additionally, the downstream molecular mechanism of TSPEAR-AS2 in OSCC was explored.

Results

TSPEAR-AS2 was overexpressed in OSCC tumors and cells. High TSPEAR-AS2 was associated with advanced TNM stage. Patients with high TSPEAR-AS2 expression displayed a shorter disease-free survival and total survival of OSCC patients than those with low TSPEAR-AS2 expressing level. It was found that knockdown of TSPEAR-AS2 could inhibit the proliferating, invading, and migrating processes pertaining to OSCC cells. Luciferase reporter tests and RNA pull-down results revealed that TSPEAR-AS2 enhanced the expressions of PPM1A by regulating miR-487a-3p, and TSPEAR-AS2 could be adopted as a miR-487a-3p sponge to inhibit PPM1A expression.

Conclusion

Our study highlighted the significance of the TSPEAR-AS2/miR-487a-3p/PPM1A axis within OSCC progression and offered a novel biomarker and novel strategies for OSCC treatments.

CircMAPK9 promotes the progression of fibroblast-like synoviocytes in rheumatoid arthritis via the miR-140-3p/PPM1A axis

Background

Rheumatoid arthritis (RA) is a chronic inflammatory joint disease, and fibroblast-like synoviocytes (FLSs) are key effector cells in RA development. Mounting evidence indicates that circular RNAs (circRNAs) participate in the occurrence and development of RA. However, the precise mechanism of circRNA mitogen-activated protein kinase (circMAPK9) in the cell processes of FLSs has not been reported.

Methods

The expression levels of circMAPK9, microRNA-140-3p (miR-140-3p), and protein phosphatase magnesium-dependent 1A (PPM1A) were determined by quantitative real-time polymerase chain reaction (qRT-PCR) or western blot assay. Cell proliferation was examined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Cell apoptosis and cycle distribution were assessed by flow cytometry. Cell migration and invasion were tested by transwell assay. All the proteins were inspected by western blot assay. Inflammatory response was evaluated by enzyme-linked immunosorbent assay (ELISA). The interaction between miR-140-3p and circMAPK9 or PPM1A was verified by dual-luciferase reporter assay.

Results

CircMAPK9 and PPM1A were upregulated and miR-140-3p was downregulated in RA patients and FLSs from RA patients (RA-FLSs). CircMAPK9 silence suppressed cell proliferation, migration, invasion, inflammatory response, and promoted apoptosis in RA-FLSs. MiR-140-3p was a target of circMAPK9, and miR-140-3p downregulation attenuated the effects of circMAPK9 knockdown on cell progression and inflammatory response in RA-FLSs. PPM1A was targeted by miR-140-3p, and circMAPK9 could regulate PPM1A expression by sponging miR-140-3p. Furthermore, miR-140-3p could impede cell biological behaviors in RA-FLSs via targeting PPM1A.

Conclusion

CircMAPK9 knockdown might inhibit cell proliferation, migration, invasion, inflammatory response, and facilitate apoptosis in RA-FLSs via regulating miR-140-3p/PPM1A axis, offering a new mechanism for the comprehension of RA development and a new insight into the potential application of circMAPK9 in RA treatment.

Wnt signaling: An attractive target for periodontitis treatment

Periodontitis is the most common chronic inflammatory disease, and a leading cause of tooth loss. Characterized by resorption of alveolar process and destruction of periodontal ligaments, periodontitis can impact not only periodontal tissues but also systemic diseases, such as diabetes, cardiovascular diseases, and respiratory infections. Currently, it is a hotspot to manage destruction and gain regeneration of periodontal tissues. Increasing evidence indicates that the Wnt signaling plays an important role in homeostasis of periodontal tissues, functions of periodontal derived cells, and progression of periodontitis. Its molecule expressions were abnormal in periodontitis. As such, modulators targeting the Wnt signaling may be an adjuvant therapy for periodontitis treatment. This review elucidates the role of Wnt signaling and its molecules, with a view to develop a potential application of drugs targeting the Wnt signaling for periodontitis treatment.