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ORIGINAL RESEARCH

A New Risk Score Model Based on Pyrogenic Signatures for the Prediction of Survival and Immune Microenvironment Features in Lung Adenocarcinoma

, , ORCID Icon, &
Pages 2323-2336 | Received 16 Mar 2023, Accepted 17 May 2023, Published online: 08 Jun 2023
 

Abstract

Purpose

Lung adenocarcinoma (LUAD) accounts for about 40–50% of all lung cancer cases with poor prognoses. Pyroptosis plays important roles in tumor development and anti-tumor processes. This study aims to investigate the prognostic value of pyroptosis-related genes in survival and tumor immune microenvironment (TIME) in LUAD.

Patients and Methods

Three datasets were collected, of which 59 normal samples and 513 LUAD samples as experimental group, 163 LUAD samples for validation analysis, and 43 non-small cell lung cancer (NSCLC) samples included in the immunotherapy cohort. A total of 33 pyrolysis-related genes were included in univariate Cox regression analysis. Five pyroptosis-related genes, including NLRC4, NLRP1, NOD1, PLCG1 and CASP9 were screened using Lasso to construct a pyroptosis-related risk score model. Functional enrichment and immune microenvironment analyses were performed. Another 5 tissue samples of LUAD patients were collected for qRT-PCR validation.

Results

According to the median risk score, the samples were divided into high-risk group and low-risk group, and the immune cell infiltration in the low-risk group was significantly higher than that in the high-risk group. Then, a nomogram was established based on clinical characteristics and risk score, which demonstrated high accuracy in 1-year OS. The risk score was significantly correlated with overall survival, immune-cell infiltration, and tumor mutation burden (TMB). qRT-PCR results showed that the expression of pyroptosis-related genes in tissues of LUAD patients was consistent with the trend in the experimental group.

Conclusion

The risk score model may predict the overall survival of LUAD patients with good accuracy. Our results also demonstrate effectiveness in evaluating the response to immunosuppressive therapy, and may help improve the overall prognosis and treatment outcome of LUAD.

Abbreviations

LUAD, lung adenocarcinoma; TIME, tumor immune microenvironment; NSCLC, non-small cell lung cancer; TMB, tumor mutation burden; GSDMD, gasdermin D; TCGA, the Cancer Genome Atlas; GEO, Gene Expression Omnibus; ROC, receiver operating characteristic; TF, transcription factor; ssGSEA, single sample gene set enrichment analysis; GSVA, gene set variation analysis; FDR, false discovery rate; FC, fold change; TMB, tumour mutation burden; GO, gene ontology; PCA, principal components analysis.

Data Sharing Statement

All data generated or analyzed during this study are included in this published article.

Ethics Approval and Consent to Participate

The study was conducted in accordance with the Declaration of Helsinki and the obtained tissue sample was approved by the ethics committee of the First Affiliated Hospital of Dalian Medical University. The informed consent was obtained from each patient and their families for clinical data use and publication.

Consent for Publication

The subjects gave written informed consent for the publication of any associated data and accompanying images.

Acknowledgments

Lei Zhao and Longfei Wang are Co-first authors. Chundong Gu and Jinna Wang are Co-corresponding authors.

Disclosure

All authors declare that they have no conflict of interest.

Additional information

Funding

There is no funding to report.