Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a broadly expressed lncRNA involved in many aspects of cellular processes. To further delineate the underlying molecular mechanism, we employed a high-throughput strategy to characterize the interacting proteins of MALAT1 by combining RNA pull-down, quantitative proteomics, bioinformatics, and experimental validation. Our approach identified 127 potential MALAT1-interacting proteins and established a highly connected MALAT1 interactome network consisting of 788 connections. Gene ontology annotation and network analysis showed that MALAT1 was highly involved in five biological processes: RNA processing; gene transcription; ribosomal proteins; protein degradation; and metabolism regulation. The interaction between MALAT1 and depleted in breast cancer 1 (DBC1) was validated using RNA pull-down and RNA immunoprecipitation. Further mechanistic studies reveal that MALAT1 binding competes with the interaction between sirtuin1 (SIRT1) and DBC1, which then releases SIRT1 and enhances its deacetylation activity. Consequently, the deacetylation of p53 reduces the transcription of a spectrum of its downstream target genes, promotes cell proliferation and inhibits cell apoptosis. Our results uncover a novel mechanism by which MALAT1 regulates the activity of p53 through the lncRNA–protein interaction.
Background: Numerous metabolic parameters can be changed during hemodialysis in the end-stage renal disease (ESRD) caused by systemic diseases, such as diabetes mellitus, hypertension. Some ocular parameters also can be variable due to the changes after hemodialysis. This study evaluates the effects of ocular parameters, including best-corrected visual acuity (BCVA), intraocular pressure (IOP), central macular thickness (CMT), subfoveal choroidal thickness (SFCT), retinal arteriolar caliber (RAC), retinal venular calibre (RVC), in ESRD patients following hemodialysis. Materials and methods: Two-hundred and two ESRD patients were recruited resulting in 404 eyes evaluations. All patients underwent hemodialysis in the Dialysis Unit of the Second Hospital of Tianjin Medical University. BCVA, CMT, IOP, SFCT, RAC and RVC were evaluated before and after hemodialysis. Systemic parameters were collected such as age, body weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), duration of hemodialysis, body weight changes, high density lipoprotein cholesterol (HDLC), low density lipoprotein cholesterol (LDLC), very low density lipoprotein cholesterol (VLDLC), glycosylated hemoglobin (HbA1c). Results: The causes of ESRD patients included chronic glomerulonephritis ( n = 65), diabetes mellitus ( n = 60), hypertensive nephrosclerosis ( n = 37), and other causes ( n = 40). In our study, BCVA ( p = .817), CMT ( p = .252) and IOP ( p = .978) did not significantly change after hemodialysis. SFCT significantly decreased from 254.29 ± 69.36 μm to 235.54 ± 659.90 μm ( p = .002) following hemodialysis. SFCT changes were significantly correlated with SBP ( p = .042) and body weight changes ( p = .044). The RAC and RVC were dilated significantly ( p = .033, p = .007). RVC changes were correlated with baseline DBP ( p = .003), HDLC ( p = .009), LDLC ( p = .004) and changes in DBP ( p = .037) and body weight ( p = .001). Conclusion: Hemodialysis can affect various ocular parameters including SFCT, RAC and RVC, which changed significantly following hemodialysis. Whereas BCVA, IOP and CMT did not change after hemodialysis in ESRD patients. The systemic compensatory mechanisms of the changes in SBP, DBP, body weight following hemodialysis need further study.
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