A novel disulfidptosis-related LncRNA prognostic risk model: predicts the prognosis, tumor microenvironment and drug sensitivity in esophageal squamous cell carcinoma

Nov 28, 2024BMC gastroenterology

New RNA-based risk model predicts outcomes, tumor environment, and drug response in esophageal squamous cell cancer

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Abstract

A total of 155 significantly associated with were identified in esophageal squamous cell carcinoma (ESCC).

Nine lncRNAs were selected as having independent prognostic significance based on various regression analyses.
Differences in survival were observed between high-risk and low-risk groups according to the prognostic model.
Immune microenvironment characteristics, including immune infiltration, function, checkpoints, and drug sensitivity, varied significantly between risk groups.
Patients with high risk and high tumor mutation burden (TMB) had shorter survival compared to those classified as low risk and low TMB.
Real-time PCR analysis showed differential expression of DRG lncRNAs between ESCC cell lines and normal esophageal epithelial cell lines.

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BACKGROUND: is a newly discovered type of cell death that differs from apoptosis, necrosis, ferroptosis and other death modes and is closely related to the occurrence and progression of tumors. However, the predictive potential and biological characteristics of disulfidptosis-related (DRGs-lncRNAs) in esophageal squamous cell carcinoma (ESCC) are unclear.

METHODS: RNA transcriptome data, clinical information and mutation data for ESCC patients were obtained from The Cancer Genome Atlas (TCGA) database. Pearson correlation and Cox regression analyses were used to identify the DRGs-lncRNAs associated with overall survival (OS). LASSO regression analysis was used to construct the prognostic model. A nomogram was created to predict the prognosis of patients with ESCC. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were used to identify the signaling pathways associated with the model. TIMER, CIBERSORT, ESTIMATE and other methods were used to analyze immune infiltration, immune function, immune checkpoints and drug sensitivity. The tumor mutation burden (TMB) were assessed between different risk groups. Real-time polymerase chain reaction (RT‒PCR) was used to detect the expression of DRGs-lncRNAs in ESCC cell lines.

RESULTS: A total of 155 lncRNAs significantly associated with disulfidptosis were identified. Through univariate Cox regression analysis, LASSO regression analysis and multivariate Cox regression analysis, 9 lncRNAs with independent prognostic significance were selected, and a prognosis model was established. Survival analysis with the prognostic model revealed that there were obvious differences in survival between the high- and low-risk groups. Further analysis revealed that the immune microenvironment, immune infiltration, immune function, immune checkpoints, and drug sensitivity significantly differed between the high-risk and low-risk groups. Patients who exhibited both high risk and high tumor mutation burden (TMB) survived shorter, while those who fell into the low risk and low TMB categories survived longer. In addition, RT‒PCR analysis revealed differential expression of DRG lncRNAs between ESCC cell lines and esophageal epithelial cell lines.

CONCLUSIONS: We established a DRG-lncRNA prognostic model that can be used to predict the prognosis, tumor mutation burden, immune cell infiltration, and drug sensitivity of ECSS patients. The results of this study provide valuable insights into the understanding of ESCC and provide valuable assistance for the individualized treatment of ESCC patients.

Key numbers

0.891

AUC for 5-year survival

Area under the curve (AUC) for the 5-year survival prediction.

141

Patients included in the study

Total number of patients with complete follow-up information.

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A novel disulfidptosis-related LncRNA prognostic risk model: predicts the prognosis, tumor microenvironment and drug sensitivity in esophageal squamous cell carcinoma

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