Fig 1: miR-223-3p targets and modulates SORBS1. A Differential expression of GC-related mRNA by analysis in TCGA-STAD; B The intersection between results predicted by 3 databases (Targetscan, miRDB, mirDIP) and the differential genes; C The correlation between miR-223-3p and potential target genes analyzed by ENCORI (p = 2.41e-19); D SORBS1 expression in normal gastric mucosa cells and GC cells (at logarithmic phase) (n = 3; p = 0.0002; p < 0.0001; p = 0.001); E The binding sites of miR-223-3p and SORBS1 predicted by miRDB database; F Targeted relationship between miR-223-3p and SORBS1 verified by dual-luciferase reporter gene detection (n = 3; p = 0.0092); G Interaction between miR-223-3p and SORBS1 verified by RIP (n = 3; p < 0.0001; p < 0.0001, n = 3; p < 0.0001; p < 0.0001); H SORBS1 level in each transfection group after 48-h transfection (n = 3; p = 0.0367; p < 0.001, n = 3; p = 0.0024; p = 0.0017); I The protein expression level of SORBS1 in each transfection group after 48-h transfection (n = 3; p = 0.0303; p = 0.0124, n = 3; p = 0.0011; p = 0.0073). *p < 0.05; **p < 0.01; ***p < 0.001
Fig 2: Event-based splicing analysis highlights potential RBPMS-dependent events downstream of MYOCD. The output from our rMATS analysis was overlapped with genes found to undergo Rbpms-dependent splicing in rat cells in a previous study [35]. A Genes from the overlap of these datasets. For confirmation of true splicing events, we used event-specific primers and PCR. Amplicons were separated on agarose gels (B, n = 5–6). Events are ordered by absolute change in percent spliced in (PSI). C Compiled data from panel B. TPM1, known to undergo SMC specific splicing, was represented in many categories in the rMATS analysis, showing increased usage of exon 2 and reduced usage of exon 3 (D). In panel E, TPM1 protein variants were examined by western blotting showing bands at 36 and 33 kDa that increased relative to other bands. Quantification is included in the bar graph on the right. Panel F shows western blotting for SORBS1. At least five SORBS1 protein species were detected and quantified (right)
Fig 3: miR-223-3p in MVs derived from CAFs promotes malignant progression of GC in vivo. A Appearance pictures and weight of subcutaneous tumor masses of mice (n = 5; p < 0.0001; p < 0.0001); B Volume and growth of subcutaneous tumor masses of transplanted mice in the 3 groups (n = 5; p = 0.0013; p = 0.0196); C miR-223-3p and SORBS1levels in cancer tissue of 3 groups of mice (n = 3; p < 0.0001; p = 0.0001, p = 0.0002; p = 0.0001); D Expression level of Ki-67 in tumor tissue of transplanted mice detected by IHC; E The expression levels of EMT-related proteins and SORBS1 in the tumor tissue of transplanted mice (n = 3; p = 0.0002; p = 0.0001, p = 0.0005; p = 0.0001, p = 0.0034; p = 0.0002). *p < 0.05; **p < 0.01; ***p < 0.001
Fig 4: Risk score independent of the prognostic analysis. (A) Univariate Cox analysis showing the hazard ratio of each candidate prognosis-related lipid metabolism DEG in predicting overall survival in BRCA from the training set. (B) Multivariate Cox regression analysis of 2 prognostic genes. (C) Survival analysis of SDC1. (D) Survival analysis of SORBS1. (E) The distribution of risk score and survival status of the training set-BRCA patients in the high- and low-risk groups. (F) Survival analysis of the high- and low-risk groups in the training set. (G) ROC curve showing the moderate accuracy of the constructed prognostic model of BRCA from the training set. (H) The distribution of ROC analysis of the two-gene signature in the testing set. (I) The distribution of Kaplan-Meier survival analysis of the two-gene signature in the testing set. (J) The distribution of risk score and survival status analysis of the two-gene signature in the testing set. (K) The distribution of ROC analysis of the two-gene signature in the GSE20685 dataset. (L) The distribution of Kaplan-Meier survival analysis of the two-gene signature in the GSE20685 dataset. (M) The distribution of risk score and survival status analysis of the two-gene signature in the GSE20685 dataset.
Fig 5: miR-223-3p regulates the proliferation, migration and invasion of GC cells by targeting SORBS1. A miR-223-3p and SORBS1expression in each transfection group after 48 h transfection (BGC-823 cells: n = 3; p = 0.0017; p < 0.001, p < 0.001; p < 0.001, AGS cells: p = 0.0025; p = 0.0017, p = 0.0003; p = 0.0004); B SORBS1 expression in each transfection group after 48-h transfection (n = 3; p = 0.0003; p = 0.0002, n = 3; p = 0.0002; p = 0.0014); C The cell activity of each transfection group (n = 3; p = 0.0014; p = 0.0051, n = 3; p = 0.0014; p = 0.0187); D The ability of cell colony formation in each transfection group (n = 3; p = 0.0015; p = 0.0158, n = 3; p = 0.0098; p = 0.0004); E, F The cell migration and invasion in each transfection group (migration: n = 3; p = 0.0085; p = 0.0073, n = 3; p = 0088; p = 0.0138, invasion: n = 3; p = 0.0073; p = 0.0093, n = 3; p = 0.0002; p < 0.0001). G, H Cell apoptosis and cell cycle in each transfection group (apoptosis: n = 3; p < 0.0001; p < 0.0001, p = 0.0001; p = 0.0001, cell cycle: n = 3; p = 0.0370; p = 0.0225, p = 0.0085; p = 0.0217). *p < 0.05; **p < 0.01; ***p < 0.001
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