bims-lorfki 2022-01-16 papers

Issue of 2022‒01‒16
four papers selected by
Nikita Dewani
Max Delbrück Centre for Molecular Medicine

Pathol Res Pract. 2021 Dec 05. pii: S0344-0338(21)00395-2. [Epub ahead of print]229 153734

Long non-coding RNA MEG8 induced by PLAG1 promotes clear cell renal cell carcinoma through the miR-495-3p/G3BP1 axis.

Clear cell renal cell carcinoma (ccRCC) is recognized as one of the most lethal malignancies among the urological system, with constantly increasing mortality. While the molecular mechanisms underlying ccRCC progression are still poorly understood, the molecular and functional role of lncRNA in multiple diseases has been well demonstrated. In this study, we hypothesized that lncRNA MEG8 might participate in ccRCC development. At first, we found that MEG8 expression was increased in ccRCC tumor tissues and cells. Next, we demonstrated that MEG8 knockdown suppressed cell viability, migration, and invasion in vitro and inhibited tumor growth in vivo. Subsequently, we utilized bioinformatics analysis, ChIP, and luciferase assays, and we found that PLAG1 could transcriptionally regulate MEG8 in ccRCC cells. Furthermore, MEG8 promoted G3BP1 expression to aggravate ccRCC tumorigenic properties through sponging miR-495-3p. Our study identified a novel PLAG1/MEG8/miR-495-3p/G3BP1 network in ccRCC development, which might be a promising direction for developing new diagnoses or therapeutic agents for ccRCC.

Keywords: Clear cell renal cell carcinoma; G3BP1; LncRNA MEG8; MiR-495–3p; PLAG1

DOI: https://doi.org/10.1016/j.prp.2021.153734

Appl Biochem Biotechnol. 2022 Jan 11.

A Novel MIR503HG/miR-497-5p/CCL19 Axis Regulates High Glucose-Induced Cell Apoptosis, Inflammation, and Fibrosis in Human HK-2 Cells.

Danping Zhang, Xiaoxiao Chen, Dan Zheng.

Long non-coding RNAs (lncRNAs) play crucial roles in the development of diabetic nephropathy (DN). Here, we explored the activity and mechanism of MIR503 host gene (MIR503HG) in high glucose (HG)-evoked cytotoxicity in HK-2 cells. MIR503HG, microRNA (miR)-497-5p, and C-C motif chemokine ligand 19 (CCL19) were quantified by quantitative real-time PCR (qRT-PCR) and western blot. The direct relationship between miR-497-5p and MIR503HG or CCL19 was confirmed by dual-luciferase reporter and RNA immunoprecipitation (RIP) assays. Cell viability and apoptosis were evaluated by XTT assay and flow cytometry, respectively. Our data showed that MIR503HG was overexpressed in HG-stimulated HK-2 cells. Knockdown of MIR503HG alleviated HG-evoked cell apoptosis, inflammation, and fibrosis in HK-2 cells. Mechanistically, MIR503HG regulated miR-497-5p expression via a binding site. MIR503HG depletion reduced HG-evoked cell apoptosis, inflammation, and fibrosis in HK-2 cells by up-regulating miR-497-5p. Moreover, miR-497-5p directly targeted and suppressed CCL19. MiR-497-5p-mediated suppression of CCL19 relieved HG-induced cell apoptosis, inflammation, and fibrosis in HK-2 cells. Furthermore, MIR503HG regulated CCL19 expression via miR-497-5p competition. Our findings identify a new MIR503HG/miR-497-5p/CCL19 network in the regulating HG-evoked cell apoptosis, inflammation, and fibrosis in HK-2 cells.

Keywords: CCL19; High glucose; MIR503HG; miR-497-5p

DOI: https://doi.org/10.1007/s12010-021-03776-6

Int J Gen Med. 2022 ;15 207-222

A Novel Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Patients with Papillary Renal Cell Carcinoma.

Ruijie Dang, Meiling Jin, Jingzhu Nan, Xuege Jiang, Zheng He, Fang Su, Diangeng Li.

Purpose: Papillary renal cell carcinoma (PRCC) is a common renal cell carcinoma. Recent studies have reported that ferroptosis is involved in the occurrence and development of tumors. Long non-coding RNAs can be used as independent biomarkers for the diagnosis and prognosis of a variety of tumors.Methods: Gene expression profile and clinical information of patients with PRCC were obtained from The Cancer Genome Atlas (TCGA) database. Lasso penalized Cox regression and univariate Cox regression analysis were utilized for model construction. The Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Immune cell infiltration and immune function were compared between the high-risk and low-risk groups. Chemotherapy sensitivity analysis was also performed.
Results: We constructed a prognostic signature consisting of 15 ferroptosis-related lncRNAs. The K-M curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the lncRNA signature was 0.930, exhibiting robust prognostic capacity. The high-risk group had a greater degree of immune cell infiltration than the low-risk group. Significant differences in inflammation promotion, parainflammation, and type I IFN response were noted between the low-risk and high-risk groups (p < 0.01). The expression levels of immune checkpoints including CD80, IDO1, and LAG3 were significantly higher in the high-risk group than in the low-risk group (p < 0.05). Chemotherapy sensitivity analysis showed that MNX1-AS1, ZFAS1, MIR4435-2HG, and ADAMTS9-AS1 were significantly correlated with the sensitivity of some chemotherapy drugs (p < 0.05).
Conclusion: We demonstrated that a ferroptosis-related lncRNA prognostic signature could be a novel biomarker for PRCC.

Keywords: PRCC; ferroptosis; long non-coding RNA; prognostic signature

DOI: https://doi.org/10.2147/IJGM.S341034

Oxid Med Cell Longev. 2022 ;2022 3617775

Establishment of a Prognostic Prediction and Drug Selection Model for Patients with Clear Cell Renal Cell Carcinoma by Multiomics Data Analysis.

Aimin Jiang, Yewei Bao, Anbang Wang, Wenliang Gong, Xinxin Gan, Jie Wang, Yi Bao, Zhenjie Wu, Bing Liu, Juan Lu, Linhui Wang.

Methods: This study was based on the multiomics data (including mRNA, lncRNA, miRNA, methylation, and WES) of 258 ccRCC patients from TCGA database. Firstly, we screened the feature values that had impact on the prognosis and obtained two subtypes. Then, we used 10 algorithms to achieve multiomics clustering and conducted pseudotiming analysis to further validate the robustness of our clustering method, based on which the two subtypes of ccRCC patients were further subtyped. Meanwhile, the immune infiltration was compared between the two subtypes, and drug sensitivity and potential drugs were analyzed. Furthermore, to analyze the heterogeneity of patients at the multiomics level, biological functions between two subtypes were compared. Finally, Boruta and PCA methods were used for dimensionality reduction and cluster analysis to construct a renal cancer risk model based on mRNA expression.Results: A prognosis predicting model of ccRCC was established by dividing patients into the high- and low-risk groups. It was found that overall survival (OS) and progression-free interval (PFI) were significantly different between the two groups (p < 0.01). The area under the OS time-dependent ROC curve for 1, 3, 5, and 10 years in the training set was 0.75, 0.72, 0.71, and 0.68, respectively.
Conclusion: The model could precisely predict the prognosis of ccRCC patients and may have implications for drug selection for ccRCC patients.

DOI: https://doi.org/10.1155/2022/3617775