# Nucleic acid-sensing-related gene signature in predicting prognosis and treatment efficiency of small cell lung cancer patients

## TL;DR

This study identifies a gene signature linked to nucleic acid sensing that predicts survival and treatment response in small cell lung cancer patients.

## Contribution

A novel 7-gene nucleic acid-sensing-related risk model is developed for predicting prognosis and treatment response in small cell lung cancer.

## Key findings

- The 7NAS risk model is an independent prognostic index for small cell lung cancer patients.
- Low-risk patients show an immune-activated tumor microenvironment with higher infiltration of immune cells.
- Low-risk patients may respond better to chemotherapy and immunotherapy.

## Abstract

Nucleic acid-sensing (NAS) pathways could induce innate and adaptive immune responses. However, rare evidence exhibited how the core genes of the NAS pathways affected the immune response and prognosis of small cell lung cancer (SCLC) patients.

We conducted a comprehensive bioinformatic analysis based on the RNA profiles of 114 SCLC patients, including 79 from cBioPortal, 21 from GSE30219, and 14 from our sequencing data. The multiplex immunohistochemistry (mIHC) was used to characterize the role of NAS related genes in the tumor microenvironment (TME) of SCLC.

A prognostic model (7NAS risk model) was constructed based on 7 NAS-related genes which was demonstrated as an independent prognostic index. The low-risk group was identified to have a better prognosis and an immune-activated microenvironment in both the public datasets and our dataset. Intriguingly, mIHC data showed that CD45+ immune cells, CD8+ T lymphocytes, and CD68+ macrophages were prevalently enriched in low-risk SCLC patients and positively correlated with IRF1 expression. Additionally, Patients in the low-risk group might have superior responses to chemotherapy and immunotherapy.

Conclusively, this study created a new risk model based on genes associated with NAS pathways which could predict the prognosis and response of treatment in patients with SCLC.