Research Paper Volume 15, Issue 15 pp 7741—7759

The expression and prognostic value of disulfidptosis progress in lung adenocarcinoma

Lina Ni1, *, , Huizhen Yang1, *, , Xiaoyu Wu1, , Kejin Zhou1, , Sheng Wang1, ,

  • 1 Department of Respiratory, Jinhua Guangfu Cancer Hospital, Jinhua, Zhejiang 321200, China
* Equal contribution

Received: April 6, 2023       Accepted: July 18, 2023       Published: August 7, 2023
How to Cite

Copyright: © 2023 Ni et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Disulfidptosis is a new cell death model caused by accumulating intracellular disulfides bonding to actin cytoskeleton proteins. This study aimed to investigate the expression and prognostic value of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD). The data of expression profiles and scRNA-seq were collected from TCGA and GEO databases. The different expressions of DRGs between normal and LUAD tissues were compared. The LASSO analysis and multivariate Cox regression analysis were utilized to develop a DRGs model for the prognosis evaluation in LUAD. The model’s predictive accuracy was evaluated with the area under the receiver operating characteristic curve (AUC) and C-index. Survival analysis, univariate and multivariate Cox regression analysis were used to assessing the predictive value of the DRGs model. ScRNA-seq data were analyzed with “Seurat” and “Monocle 2” packages. There were significant differences in 22 DRGs between normal and tumor tissues. A model with five DRGs (ACTB, FLNB, NCKAP1, SLC3A2, SLC7A11) was constructed. The AUC and C-index of the model were significantly higher than that based on clinical parameters. Survival analysis, univariate and multivariate Cox regression analysis demonstrated risk score was an independent prognostic predictor. In the scRNA-seq study, we identified 14 clusters and 11 cell types. Clusters 2, 8, and 13 were annotated into Epithelial cells. SLC7A11 and SLC3A2, NCKAP1 and FLNB, ACTB expressed most abundantly in Epithelial cells, Endothelial cells, Naive CD4 T, respectively. We explored the expression of DRGs in LUAD and constructed a predictive DRGs model, which was stable and reliable for predicting LUAD prognosis.


AUC: The area under the curve; C-index: concordance index; DRGs: Disulfidptosis-related genes; FDR: False discovery rate; GEO: Gene Expression Omnibus; GSEA: Gene set enrichment analysis; HR: Hazard ratio; IPS value: immunophenoscore value; LASSO: Least absolute shrinkage and selection operator; LC: Lung cancer; LUAD: Lung adenocarcinoma; OS: overall survival; PCA: Principal component analysis; RNA-seq: RNA sequencing; ROC: Receiver operating characteristic curve; ScRNA-seq: Single-cell RNA sequencing; ssGSEA: Single-sample gene set enrichment analysis; TCGA: The Cancer Genome Atlas; TIICs: Tumor-infiltrating immune cells; TMB: Tumor mutational burden; t-SNE: t-Stochastic Neighbor Embedding.