Abstract PO2-01-08: Differential HOXB13 gene expression and promoter methylation analysis in breast cancer

Abstract Background: The Breast Cancer Index (BCI) is a gene expression-based signature comprising two functional biomarker panels: the Molecular Grade Index (MGI) and BCI (H/I), which is a ratio of the HOXB13 and IL17BR gene expression. Several studies have shown that BCI (H/I) is a predictive biomarker for extended adjuvant endocrine therapy benefit in hormone receptor-positive (HR+) early-stage breast cancer. Molecular mechanisms underlying endocrine responsiveness remain to be fully explored. The objective of this analysis is to evaluate the correlation between gene expression and methylation in breast cancer patients displaying different HOXB13 mRNA expression levels from The Cancer Genome Atlas (TCGA) project. Methods: Data from methylation microarrays and mRNA sequencing were examined in combination with clinical metadata from 1,095 TCGA breast cancer patients. After removing outliers, HR+ samples were ordered based on their HOXB13 expression levels and the top 10% of samples (HOXB13-high; n=95) and bottom 10% (HOXB13-low; n=95) were selected for further analysis. Differentially expressed genes (DEGs) were determined by comparing all protein-coding genes between the HOXB13-high and HOXB13-low sets, based on an absolute log-fold change above 2 and a Benjamini-Hochberg adjusted p-value threshold of 0.01. Among the subset of samples with matching methylation data (n=60 for the HOXB13-high group and n=48 for the HOXB13-low group), hypo-methylated and hyper-methylated differentially methylated probes (DMPs) were identified based on at least 10% change of β (i.e., average promoter methylation) and a Benjamini-Hochberg adjusted p-value threshold of 0.01. Motif and transcription factor (TF) enrichment analyses were identified at a minimum incidence of 10 and a lower boundary of 1.5 for the 95% confidence interval of the odds ratio. Results: Our analysis identified a total of 613 DEGs between the HOXB13-high and HOXB13-low groups. Gene ontology analysis of DEGs revealed a statistically significant enrichment of genes associated with PTK6 regulated cell cycle, oncogene-induced cellular senescence, and regulation of T cell activation. Analysis of protein-protein interactions of differentially expressed genes revealed differences in key biological processes including changes in cell cycle regulation, p53 pathway, and IL-17 signaling. A total of 5,295 hyper-methylated and 580 hypo-methylated DMPs were discovered when comparing HOXB13-high and HOXB13-low samples. Changes in global methylation patterns enabled classification of breast cancer samples with high or low HOXB13 expression with an accuracy of 0.90. Reconstruction of gene regulatory networks from DNA methylation and transcriptome profiles elucidated significant pairs of DMPs and differentially expressed genes. Specifically, a total of 197 differentially expressed genes were attributed to hyper-methylated DMPs, including genes involved in response to estrogen, activation of HOX genes during differentiation, and drug-mediated inhibition of CDK4/6 activity. Additionally, 8 differentially expressed genes were attributed to hypo-methylated DMPs and were associated with proteasomal protein catabolic processes. Lastly, motif analysis of transcriptional factors for the hyper-methylated DMPs revealed enrichment of binding motifs attributed to FOXA1, ESR1, XBR1, and FOXP1. Conclusion: A comprehensive and comparative analysis of mRNA expression levels and methylation patterns between TCGA breast cancer samples with high and low expression of HOXB13 revealed key signaling pathways and biological processes that may provide insights on the molecular mechanism of HOXB13 in the regulation of response to endocrine therapy in HR+ breast cancer. Citation Format: Natalia Siuliukina, Yi Zhang, Kai Treuner, Mark Pegram. Differential HOXB13 gene expression and promoter methylation analysis in breast cancer abstract. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-01-08.