SNHG6-centered RNA regulatory network links epithelial plasticity and apoptosis signaling in breast cancer.

Introduction
Regulatory interactions among long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs play an important role in epithelial plasticity and tumor progression in breast cancer. However, the network-level organization of these RNA-mediated regulatory interactions remains insufficiently characterized.

Methods
Candidate EMT-associated regulators were identified through integrative bioinformatic screening of GEO and TCGA-BRCA datasets together with curated interaction databases. Expression of selected coding and non-coding RNAs was quantified in 40 paired primary breast tumors and adjacent normal tissues using RT-qPCR. Correlation and partial-correlation analyses were applied to identify candidate lncRNA–miRNA–mRNA regulatory modules consistent with the competing endogenous RNA (ceRNA) framework. Network reconstruction and functional enrichment analyses were performed to characterize the regulatory architecture of the identified interactions.

Results
Correlation-based analysis identified several candidate ceRNA modules centered on the lncRNA SNHG6, including SNHG6–miR-200c-3p–CDH1 and SNHG6–miR-16-5p–CDH1 axes. In addition, a SNHG6–miR-16-5p–BCL2L11 module linked EMT-associated regulatory circuits with apoptosis signaling. Network reconstruction revealed a compact regulatory network in which SNHG6 connected two key miRNA regulators (miR-200c-3p and miR-16-5p) with EMT- and stemness-associated genes including CDH1, SOX4, BMI1, and BCL2L11. Functional enrichment analysis highlighted biological processes related to epithelial differentiation and stem cell regulation and identified cancer-associated pathways including Hippo signaling, cadherin signaling, and apoptosis-related pathways.

Conclusions
These findings identify an SNHG6-centered RNA regulatory network linking epithelial plasticity, stemness-associated transcriptional programs, and apoptosis-related signaling in breast cancer and suggest candidate regulatory axes for future functional validation.

This work was supported by the Russian Science Foundation grant no. 24-75-00159.