# Development and validation of a prognostic model based on endoplasmic reticulum stress-related lncRNAs in breast cancer

## TL;DR

This study develops a prognostic model using six endoplasmic reticulum stress-related lncRNAs to predict survival and outcomes in breast cancer patients.

## Contribution

The study introduces a novel six-lncRNA risk model based on endoplasmic reticulum stress-related genes for breast cancer prognosis.

## Key findings

- The six-lncRNA model showed strong survival prediction with AUC values of 0.702, 0.707, and 0.676 at 1, 3, and 5 years.
- High-risk patients had significantly poorer overall survival compared to low-risk patients.
- LMNTD2-AS1 knockdown reduced breast cancer cell proliferation, migration, and invasion.

## Abstract

Breast cancer (BC), recognized as the most prevalent malignant tumor among women, has emerged as a critical global public health concern. Increasing evidence indicates that long non-coding RNAs (lncRNAs) are essential regulators in the initiation, development, and progression of BC, influencing tumor biology through diverse molecular mechanisms. Despite these advances, the specific prognostic significance of endoplasmic reticulum (ER) stress (ERS)-related lncRNAs in BC remains largely unexplored, and no comprehensive study has yet been reported in this context.

In this study, we utilized high-throughput BC data from the TCGA database to identify ERS-related lncRNAs that are strongly associated with patient survival and prognosis. Based on these findings, we developed a risk model consisting of six ERS-related lncRNAs within the TCGA cohort, which demonstrated independent prognostic value for BC patients. We further examined the association of this model with clinical outcomes, the tumor microenvironment (TME), immune cell infiltration, and the predictive potential of immune checkpoint expression. In addition, we conducted functional analyses to explore the signaling pathways and biological processes regulated by ERS-related lncRNAs, providing new insights into their role in BC progression and prognosis.

The prognostic model constructed from six ERS-related lncRNAs demonstrated strong predictive performance, with AUC values of 0.702, 0.707, and 0.676 for estimating survival at 1, 3, and 5 years, respectively. Kaplan-Meier survival analyses further revealed that patients in the high-risk group exhibited significantly poorer overall survival (OS) compared to those in the low-risk group. Gene set enrichment analysis (GSEA) indicated that the prognostic model may be functionally linked to pathways involving the extracellular matrix (ECM) and focal adhesions. Among the six ERS-related lncRNAs, LMNTD2-AS1 was selected for functional validation, and experimental results demonstrated that its knockdown suppressed the proliferation, migration, and invasion abilities of breast cancer cells.

Overall, our ERS-related lncRNA risk signature not only provides valuable prognostic insights but may also serve as a potential therapeutic target and biomarker to improve the management and treatment strategies for BC patients.