Multi-Layered Analysis of TGF-β Signaling and Regulation via DNA Methylation and microRNAs in Astrocytic Tumors

Abstract

Astrocytic tumors are a heterogeneous group of glial neoplasms characterized by marked differences in biological behavior and patient prognosis. Transforming growth factor-beta (TGF-β) signaling plays a pivotal role in astrocytoma pathogenesis; however, the extent and mechanisms of its epigenetic regulation remain poorly understood. This study aimed to investigate how promoter methylation and microRNA-mediated mechanisms regulate key genes within the TGF-β signaling pathway across various astrocytoma grades. Tumor tissue samples from 65 patients with WHO grade II-IV astrocytomas were analyzed using Affymetrix gene expression and microRNA microarrays. Promoter methylation of TGF-β signaling genes was assessed using methylation-specific polymerase chain reaction (MSP). Gene expression was validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR), and protein levels were quantified using enzyme-linked immunosorbent assay (ELISA). MicroRNA targets were predicted using bioinformatic tools, and survival analyses were conducted using Kaplan-Meier and Cox regression models. Six genes-SMAD1, SMAD3, SKIL, BMP2, SMAD4, and MAPK1-showed significant upregulation in high-grade tumors (fold change > 5.0, p < 0.05), supported by RT-qPCR and protein-level data. Promoter hypomethylation and reduced expression of regulatory microRNAs (e.g., hsa-miR-145-5p targeting SMAD3) were more common in higher-grade tumors. Protein-protein interaction analysis indicated strong functional interconnectivity among the overexpressed genes. High protein levels of SMAD1, SMAD3, and SKIL were significantly associated with shorter overall survival (p < 0.001). This multi-level analysis reveals that astrocytic tumor progression involves epigenetic derepression and microRNA-mediated dysregulation of TGF-β signaling. Elevated expression of SMAD1, SMAD3, and SKIL emerged as strong prognostic indicators, underscoring their potential as biomarkers and therapeutic targets in astrocytic tumors.

Keywords: DNA methylation; MAPK1; SMAD proteins; TGF-β signaling; astrocytic tumors; epigenetic regulation; gene expression profiling; glioma; microRNA; prognostic biomarkers.

Figure 1

Quantitative expression analysis of six TGF-β-associated mRNAs using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Data represent mean ± standard deviation (SD) from three independent experiments (n = 3). Statistical significance was evaluated using one-way ANOVA with post hoc testing. Asterisk indicates statistically significant differences compared to G2 (p < 0.05). SKIL, SKI-like proto-oncogene; BMP2, bone morphogenetic protein 2; SMAD1, SMAD family member 1; SMAD3, SMAD family member 3; SMAD4, SMAD family member 4; MAPK1, mitogen-activated protein kinase 1 (ERK2).

Figure 2

Frequency of promoter methylation in TGF-β signaling-related genes (SKIL, SMAD1, SMAD3, SMAD4, BMP2, and MAPK1) across astrocytic tumor grades (G2, G3, and G4). Methylation status was assessed using methylation-specific PCR (MSP) and interpreted in a binary manner (methylated vs. unmethylated). The histogram-like representation reflects the number of unmethylated cases per gene and grade, indicating a trend toward promoter hypomethylation with increasing tumor grade.

Figure 3

Interaction network of selected proteins generated using the STRING database.

Figure 4

Kaplan–Meier survival curves for overall survival stratified by protein expression levels of (A) SKIL, (B) SMAD1, (C) SMAD3, (D) SMAD4, (E) BMP2, and (F) MAPK1 in patients with astrocytic tumors. X-axis: survival time (months). Y-axis: cumulative survival probability. Red lines indicate high expression; black lines indicate low expression. Number of patients at risk is displayed for all time points below each survival curve to improve transparency and interpretability.