Dataset Information

Construction of an m6A- and neutrophil extracellular traps-related lncRNA model to predict hepatocellular carcinoma prognosis and immune landscape.

ABSTRACT:

Purpose

To investigate the impact of N6-methyladenosine- (m6A) and neutrophil extracellular traps- (NETs) related lncRNAs (MNlncRNAs) on the prognosis of hepatocellular carcinoma (HCC).

Methods

We collected m6A and NETs-related genes from published studies. We identified the MNlncRNAs by correlation analysis. Cox regression and the least absolute selection operator (LASSO) method were used to select predictive MNlncRNAs. The expressions of predictive MNlncRNAs were detected by cell and tissue experiments. Survival, medication sensitivity, and immunological microenvironment evaluations were used to assess the model's prognostic utility. Finally, we performed cellular experiments to further validate the model's prognostic reliability.

Results

We obtained a total of 209 MNlncRNAs. 7 MNlncRNAs comprised the prognostic model, which successfully stratifies HCC patients, with the area under the curve (AUC) ranging from 0.7 to 0.8. In vitro tests confirmed that higher risk patients had worse prognosis. Risk score, immunological microenvironment, and immune checkpoint gene expression were all significantly correlated with each other in HCC. In the group at high risk, immunotherapy could be more successful. Cellular assays confirmed that HCC cells with high risk scores have a higher proliferation and invasive capacity.

Conclusion

The MNlncRNAs-related prognostic model aided in determining HCC prognosis, revealing novel therapeutic options, notably immunotherapy.

SUBMITTER: Zhan T

PROVIDER: S-EPMC10585104 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Construction of an m6A- and neutrophil extracellular traps-related lncRNA model to predict hepatocellular carcinoma prognosis and immune landscape.

Zhan Tian T Wang Wei W Guan Xiao X Bao Wei W Lu Na N Zhang Jianping J

Frontiers in immunology 20231005

<h4>Purpose</h4>To investigate the impact of N6-methyladenosine- (m6A) and neutrophil extracellular traps- (NETs) related lncRNAs (MNlncRNAs) on the prognosis of hepatocellular carcinoma (HCC).<h4>Methods</h4>We collected m6A and NETs-related genes from published studies. We identified the MNlncRNAs by correlation analysis. Cox regression and the least absolute selection operator (LASSO) method were used to select predictive MNlncRNAs. The expressions of predictive MNlncRNAs were detected by cel ...[more]

PMID: 37868992

Similar Datasets

Project description:BackgroundNeutrophil extracellular traps (NETs) were originally thought to be formed by neutrophils to trap invading microorganisms as a defense mechanism. Increasing studies have shown that NETs play a pivotal role in tumor progression and diffusion. In this case, transcriptome analysis provides an opportunity to unearth the association between NETs and clinical outcomes of patients with pan-cancer.MethodsThe transcriptome sequencing data of The Cancer Genome Atlas pan-cancer primary focus was obtained from UCSC Xena, and a 19-gene NETs score was then constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression model based on the expression levels of 69 NETs initial biomarkers we collected from multistudies. In addition, multiple datasets covering multiple cancer types from other databases were collected and used to validate the signature. Gene ontology enrichment analyses were used to annotate the functions of NETs-related pathways. Immunohistochemistry (IHC) was implemented to evaluate the role of NETs-related genes in clinical patients across types of tumors, including lung adenocarcinoma (n=58), colorectal carcinoma (n=93), kidney renal clear cell carcinoma (n=90), and triple-negative breast cancer (n=80).ResultsThe NETs score was calculated based on 19-NETs related genes according to the LASSO Cox model. The NETs score was considered a hazardous factor in most cancer types, with a higher score indicating a more adverse outcome. In addition, we found that NETs were significantly correlated to various malignant biological processes, such as the epithelial to mesenchymal transition (R=0.7444, p<0.0001), angiogenesis (R=0.5369, p<0.0001), and tumor cell proliferation (R=0.3835, p<0.0001). Furthermore, in IHC cohorts of a variety of tumors, myeloperoxidase, a gene involved in the model and a classical delegate of NETs formation, was associated with poor clinical outcomes.ConclusionsCollectively, these constitutive and complementary biomarkers represented the ability of NETs formation to predict the development of patients' progression. Integrative transcriptome analyses plus clinical sample validation may facilitate the biomarker discovery and clinical transformation.

Dataset Information

Construction of an m6A- and neutrophil extracellular traps-related lncRNA model to predict hepatocellular carcinoma prognosis and immune landscape.

Purpose

Methods

Results

Conclusion

Publications

Construction of an m6A- and neutrophil extracellular traps-related lncRNA model to predict hepatocellular carcinoma prognosis and immune landscape.

Similar Datasets

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