METTL3-mediated activation of Sonic Hedgehog signaling promotes breast cancer progression

Abstract

Introduction: Breast cancer represents a heterogeneous group of tumors characterized by diverse molecular and clinical features, driven by both genetic alterations and epigenetic regulation. Among these mechanisms, the Hedgehog (Hh) developmental pathway, particularly elevated levels of its ligand Sonic Hedgehog (SHH), has been implicated in breast cancer progression. Methyltransferase-like 3 (METTL3), the core catalytic component of the m6A methyltransferase complex, responsible for N6-methyladenosine (m6A) modification of mRNA, has shown a stronger prognostic relevance in regulating mRNA stability and cancer development than other m6A writers, erasers, or readers. Despite evidence suggesting that both SHH and METTL3 contribute to tumor growth in breast tissue, the functional relationship between these factors remains unclear. In this study, we investigated the potential of the METTL3-SHH axis in breast cancer progression to address this gap.

Methods: We have performed bioinformatic analyses by utilizing data from UALCAN, cBioPortal, and GEPIA platforms to comprehensively investigate the methylation patterns, gene expression levels, and mutation profiles of specific genes of interest. Expressions of METTL3 and components of the SHH signaling pathway were analyzed by qRT-PCR. Statistical analyses were performed by using Student's t-test, Spearman and Pearson coefficient (r) test, ANOVA test, and log-rank test.

Results: Analysis of 35 breast cancer patients of Bangladesh and gene expression data from The Cancer Genome Atlas (n = 1,021) database revealed METTL3 is overexpressed in breast cancer, and upregulation of METTL3 and downstream key components of the SHH signaling pathway (p < 0.05 vs. control) correlates significantly with worse patient outcomes (HR = 1.3). These findings suggest a possible regulatory mechanism linking METTL3-mediated m6A modification to SHH signaling in breast cancer progression. Elucidating this axis could provide novel insights into tumor biology and identify promising targets for epigenetic therapies.

Keywords: N6-methyladenosine (m6A); breast cancer; epigenetic regulation; methyltransferase like-3 (METTL3); sonic hedgehog developmental pathway.

FIGURE 1

Upregulation of METTL3 expression and its implications in breast cancer patients’ outcomes. (A) Oncoprint data summarizing the genomic alterations of methyltransferase complex genes (METTL3, METTL14, METTL16, WTAP, RBM15, and ZC3H15) in 1084 TCGA samples. Colored sections represent mutations, with moderate alterations observed in METTL3. Queried genes are altered in 2% of patients. (B) The heatmap provides a detailed view of gene expression (low to high) in individual samples, were altered in 242 (22%) of 1,084 samples. (C) Boxplot of METTL3 expression in tumor and normal samples. (D) cBioPortal analysis highlights significant expression differences between patients with METTL3 alterations and those without. (E) qRT-PCR of METTL3 expression in clinical samples (n = 35) compared to normal tissues. (F) Kaplan-Meier survival curve: patients are divided into two groups based on METTL3 expression levels: The low METTL3 expression group (black line) and the High METTL3 expression group (red line). (G) Experimental validation of METTL3 expression trends across clinical samples in a heatmap. For comparison between healthy and cancer cases, two-tailed unpaired t-tests were performed in GraphPad Prism, with significance determined at p < 0.05. Error bars represent the mean ± S.D. of the tissue samples. *p < 0.05 vs. control.

FIGURE 2

Sonic Hedgehog expression, methylation, and clinical significance in breast cancer. (A) TCGA data highlights SHH overexpression in breast cancer (BRCA). (B) qRT-PCR of SHH mRNA levels, which are significantly elevated in tumor tissues (n = 35) compared to controls. (C) 1% of Patients exhibited alterations in their mRNA expression, with the altered group showing higher expression of certain mRNAs than the unaltered group. (D) Correlation between METTL3 and SHH expression, Pearson and Spearman analyses were conducted in GraphPad Prism. (E) GEPIA analysis further explores the relationship between METTL3 and SHH. (F) Promoter methylation analysis: the Beta value indicates the level of DNA methylation, ranging from 0 (unmethylated) to 1 (fully methylated). Different beta value cut-offs have been considered to indicate hypermethylation [Beta value: 0.7–0.5] or hypomethylation [Beta value: 0.3–0.25]. (G) A scatter plot illustrating the relationship between SHH methylation and METTL3. (H) Survival analysis of breast cancer patients based on the Kaplan–Meier plotter database. p-values were calculated using a two-tailed Student’s t-test, with p < 0.05 considered statistically significant; ns = non-significant (p > 0.05). ***p < 0.001 vs. control.

FIGURE 3

Promoter hypermethylation reduced PTCH1 expression in breast cancer. (A) TCGA database analysis shows a significantly lower expression of PTCH1 in breast cancer tissues. (B) The cBioportal analysis of PTCH1 revealed a 5% alteration in expression, with some regions affected, while the surrounding unaltered areas exhibit a robust expression profile. (C) Experimental data showing increased PTCH1 expression in breast cancer (n = 35) compared to control tissues. (D) Methylation analysis supporting PTCH1 promoter hypermethylation in primary tumors. The gene in question is altered in 49 (5%) of the queried patients or samples. (E) Correlation of PTCH1 methylation and mRNA expression (Spearman: 0.23, Pearson: 0.27). This negative correlation suggests that hypomethylation leads to PTCH1 activation. (F) Correlation between PTCH1 mRNA and METTL3 mRNA. ***p < 0.001 vs. control.

FIGURE 4

SMO mRNA alteration is associated with PTCH1 and METTL3 expressions. (A) TCGA data analysis of breast cancer patients. (B) SMO mRNA expression alteration: the graph compares SMO mRNA expression between the altered and unaltered groups. (C) Co-expression analysis of PTCH1 and SMO. (D) Co-expression of METTL3 and SMO: the scatterplot shows a positive correlation between METTL3 and SMO mRNA. (E) Box plot compares SMO promoter methylation levels between normal tissue (n = 97) and primary tumor tissue (n = 793). (F) The relationship between METTL3 mRNA expression (x-axis) and SMO methylation levels (y-axis). (G) Experimental validation of SMO mRNA overexpression in tumor samples (n = 35) compared to control samples. (H) Correlation analysis between PTCH1 and SMO. (I) Co-expression between METTL3 and SMO expression. *p < 0.05 vs. control.

FIGURE 5

Expression and methylation pattern of GLI transcription factors: (A) Patterns of expression for the GLI family of genes—GLI1, GLI2, and GLI3. (B–D) The analysis of mRNA expression from cBioPortal. (E) Correlation of mRNA expression levels between the METTL3 and GLI family genes. (F–H) The boxplot compares promoter methylation of GLI, GLI2 and GLI3 genes in normal and primary breast cancer tissues. (I) Methylation patterns of GLI1 and GLI3. GLI2 does not show methylation data in the database. (J,K) The data represent the relationship between METTL3 expression and the methylation patterns of the GLI1 and GLI3 genes. (L) GLI1, GLI2, and GLI3 mRNA expression levels are measured in tumor (n = 35) and control samples by qRT-PCR. (M–O) The scatter plot showing the correlation of METTL3 and GLI genes in experimental data. ***p < 0.001 vs. control.