Classification and Immunotherapy Assessment of Lung Adenocarcinoma Based on Coagulation-Related Genes

Abstract

Introduction: This study on lung adenocarcinoma (LUAD), a common lung cancer subtype with high mortality. Aims: This study focuses on how tumor cell interactions affect immunotherapy responsiveness. Methods: Using public databases, we used non-negative matrix factorization clustering method, ssGSEA, CIBERSORT algorithm, immunophenotype score, survival analysis, protein–protein interaction network method to analyze gene expression data and coagulation-related genes. Results: We divided LUAD patients into three coagulation-related subgroups with varying immune characteristics and survival rates. A cluster of three patients, having the highest immune infiltration and survival rate, also showed the most potential for immunotherapy. We identified five key genes influencing patient survival using a protein–protein interaction network. Conclusion: This research offers valuable insights for forecasting prognosis and immunotherapy responsiveness in LUAD patients, helping to inform clinical treatment strategies.

Keywords::

• clustering analysis
• cMAP database
• coagulation factor
• immunity
• lung adenocarcinoma

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.futuremedicine.com/doi/suppl/10.2217/pme-2023-0094

Author contributions

Y Zhou contributed to the study design. W Fan conducted the literature search. S Zhong and J Yang acquired the data. Y Zhong wrote the article. J Zhou performed data analysis. G Huang revised the article. All authors read and approved the final manuscript.

Financial disclosure

The authors have no financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Conflict of interest disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Availability of data and materials

The data and materials in the current study are available from the corresponding author on reasonable request.