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. 2024 Jun 10;16(11):9972-9989.
doi: 10.18632/aging.205911. Epub 2024 Jun 10.

Disulfidptosis-related lncRNAs signature predicting prognosis and immunotherapy effect in lung adenocarcinoma

Affiliations

Disulfidptosis-related lncRNAs signature predicting prognosis and immunotherapy effect in lung adenocarcinoma

Suifeng Hong et al. Aging (Albany NY). .

Abstract

Purpose: Lung adenocarcinoma (LUAD) is a prevalent malignant tumor worldwide, with high incidence and mortality rates. However, there is still a lack of specific and sensitive biomarkers for its early diagnosis and targeted treatment. Disulfidptosis is a newly identified mode of cell death that is characteristic of disulfide stress. Therefore, exploring the correlation between disulfidptosis-related long non-coding RNAs (DRGs-lncRNAs) and patient prognosis can provide new molecular targets for LUAD patients.

Methods: The study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines.

Results: A total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line.

Conclusions: The prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.

Keywords: disulfidptosis; drug sensitivity; long non-coding RNAs; lung adenocarcinoma; prognosis model.

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Conflict of interest statement

CONFLICTS OF INTEREST: The authors declare no conflicts of interest related to this study. The authors report no proprietary or commercial interest in any product mentioned or concept discussed in this article.

Figures

Figure 1
Figure 1
The flowchart of this study.
Figure 2
Figure 2
Expression of DRG-lncRNAs in LUAD. DRG-lncRNAs, disulfidptosis-related long non-coding RNAs. Abbreviation: LUAD; lung adenocarcinoma.
Figure 3
Figure 3
Construction of the disulfidptosis-related prognostic signature. (A) 10 DRG-lncRNAs significantly correlated with the survival prognosis of LUAD patients. (B) LASSO regression based on optimal parameter (lambda) construction model. (C) LASSO regression coefficient curve. (D) Multivariate Cox regression analysis of DRG-lncRNA with prognostic significance. (E, F) The Kaplan-Meier curve shows different OS and PFS between the low-risk and high-risk groups. (G) A heatmap shows the differential expression of DRG-lncRNAs in the high-risk and low-risk groups. (H) The risk curve of the training group is reordered by disulfidptosis related signature and the scatter plot of the sample survival overview. The green and red dots represent survival and death, respectively. (I) The risk curve of the test group is reordered by disulfidptosis related signature and the scatter plot of the sample survival overview. The green and red dots represent survival and death, respectively. Abbreviations: DRG-lncRNAs: disulfidptosis-related long non-coding RNAs; LUAD: lung adenocarcinoma; LASSO: least absolute shrinkage and selection operator; OS: overall survival; PFS: progression-free survival.
Figure 4
Figure 4
Clinical features and evaluation of the prognostic ability. (A, B) The univariate and multivariate Cox regression analysis of risk scores, age, gender, grade, stage. (C) One- three- and five-year AUC in the risk score. (D, E) Clinical prognosis analysis of LUAD patients with low- and high scores among stage. Abbreviations: AUC: area under curve; LUAD: lung adenocarcinoma.
Figure 5
Figure 5
Functional enrichment analysis of DRG-lncRNAs. (AC) GO and KEGG enrichment analysis of DRG-lncRNAs. (D) Pathways of enrichment of highly and lowly expressed genes in the high-risk group. (E) Pathways of enrichment of highly and lowly expressed genes in the low-risk group. Abbreviations: DRG-lncRNAs: disulfidptosis-related long non-coding RNAs; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes.
Figure 6
Figure 6
The correlation between DRG-lncRNAs and immune cell infiltration. (A) Results of differences in stromal cell score, immune cell score, and comprehensive score among LUAD patients under different risk groups. (B) Immune response heatmaps for high-risk and low-risk groups based on CIBERSORT, CIBERSORT ABS, XCELL, MCPcounter, QUANTISEQ, EPIC, and TIMER algorithms. (C) Abundances of infiltrating immune cells between high-risk and low-risk groups. (D) Differential expression of immune function scores between high-risk and low-risk groups. Abbreviations: DRG-lncRNAs: disulfidptosis-related long non-coding RNAs; LUAD: lung adenocarcinoma; TME: tumor microenvironment.
Figure 7
Figure 7
Mutation analysis of the DRG-lncRNAs based on the risk score model. (A, B) The waterfall diagram shows the genes that most frequently undergo somatic mutations under different risk groups. (C) The difference in tumor mutation burden between high- and low-risk score groups. (D) Kaplan-Meier curves of high and low TMB groups. (E) Kaplan-Meier curves of four groups classified by risk score and TMB. Abbreviations: DRG-lncRNAs: disulfidptosis-related long non-coding RNAs; TMB: tumor mutational burden; H: high; L: low.
Figure 8
Figure 8
Analysis of chemotherapeutic drugs sensitivity. (AE) Chemotherapeutic drugs sensitivity analysis of Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin in the low-risk and high-risk groups.
Figure 9
Figure 9
Relative DRG-lncRNAs expression levels in LUAD cell lines. (AE) The mRNA expression level of AL365181.2, AL606489.1, SNHG12, GSEC, and AC090559.1 in LUAD cell lines (A549 and PC9) and the human bronchial epithelial cell line (HBE). Abbreviations: DRG-lncRNAs: disulfidptosis-related long non-coding RNAs; LUAD: lung adenocarcinoma. **P < 0.01, ***P < 0.001.

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