Comprehensive Analysis of Molecular Characteristics, Clinical Signifificance, and Cancer Immune Interactions of Patients by Anoikis-Related Genes in LUAD Combined with Single-cell Data
Weijie Yu, Zhoulin Miao, Julaiti Ainiwaer, Bingzhang QiaoiD, Kawuli JumaiiD, Ilyar SheyhidiniD
Abstract
BackgroundLung adenocarcinoma(LUAD) is the most prevalent subtype of lung cancer today. There is a close relationship between Anoikis related genes(ARGs) and tumor prognosis, drug susceptibility, and tumor microenvironment(TME). MethodWe calculated differential expression genes using downloaded Anoikis genes and selected genes of prognostic value. Consensus clustering analysis was used and characterized between different clusters. Differences between the different groups were also explored. Risk scores and Nomogram with predictive prognostic functions were established. Immune status and drug sensitivity were also assessed between different risk groups. Single-cell data were downloaded to compare the expression profiles of selected genes, and immunohistochemical results of selected genes were also downloaded to corroborate the reliability of the manuscript. ResultTwo clusters were identified on the basis of related gene expression. We analyzed the survival time, functional enrichment between the two groups and found significant differences between the two clusters. Significant relationships were found between the different clusters and clinical variables. group B had a significantly lower KM curve than group A, as well as a significant enrichment in multiple tumor functions. A risk score with prognostic value was established. The risk score was found to have a high predictive value for prognosis and was an independent prognostic factor. Combined with clinical variables, a Nomogram was established and found to be an accurate predictor of patient prognosis. There were significant differences in immune status between the different risk groups. Patients in the low-risk group were significantly better treated than those in the high-risk group. Finally single cell data confirmed the expression of the selected genes. Also, the immunohistochemical results helped us to confirm the selected genes have increased expression in tumor tissue. ConclusionIn conclusion, this paper reveals the role of ARGs and immune status, drug susceptibility, and prediction of prognosis in LUAD. Also, an accurate prognostic prediction model was established based on genetic.
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