# Deciphering the prognostic role of endoplasmic reticulum stress in lung adenocarcinoma: integrating prognostic prediction and immunotherapy strategies

## TL;DR

This study explores how endoplasmic reticulum stress affects lung cancer outcomes and treatment, offering a new model to predict survival and guide therapy.

## Contribution

A novel ERS-associated signature (ERAS) is developed to predict LUAD patient outcomes and guide personalized treatment strategies.

## Key findings

- The ERAS model stratifies LUAD patients into high- and low-risk groups with distinct survival rates and treatment responses.
- High-ERAS patients show elevated tumor mutational burden and chemotherapy sensitivity but reduced immune response indicators.
- A nomogram was constructed to predict 1-, 3-, and 5-year survival rates for personalized patient management.

## Abstract

Endoplasmic reticulum stress (ERS) is a critical factor influencing lung adenocarcinoma (LUAD) progression and patient outcomes. In this study, we analyzed gene expression data from LUAD samples sourced from The Cancer Genomic Atlas and Gene Expression Omnibus databases. Utilizing advanced statistical methods including LASSO and Cox regression, we developed a ERS-associated signature (ERAS) based on ten ERS-related genes. This model stratified patients into high- and low-risk groups, with the high-risk group exhibiting decreased survival rates, elevated tumor mutational burden, and heightened chemotherapy sensitivity. Additionally, we observed lower immune and ESTIMATE scores in the high-ERAS group, indicating a potentially compromised immune response. Experimental validation through quantitative real-time polymerase chain reaction confirmed the utility of our model. Furthermore, we constructed a nomogram to predict 1-, 3-, and 5-year survival rates, providing clinicians with a valuable tool for personalized patient management. In conclusion, our study demonstrates the efficacy of the ERAS in identifying high-ERAS LUAD patients, offering promising implications for improved prognostication and treatment strategies.

The online version contains supplementary material available at 10.1007/s10238-024-01439-4.