AI Article Synopsis

  • Lung cancer, specifically adenocarcinoma (LUAD), is a leading cancer worldwide with significant new cases and death rates, necessitating improved survival prediction methods.
  • DNA methylation, an important epigenetic mechanism, is linked to cancer development and requires further investigation for its prognostic potential in LUAD.
  • The study analyzed data from TCGA and GEO databases to identify differentially methylated genes and develop a prognostic model, ultimately assessing survival rates and potential drug applications related to LUAD.

Article Abstract

Background: One of the most prevalent cancers in the world is lung cancer, with adenocarcinoma (LUAD) making up a significant portion of cases. According to the National Cancer Institute (NCI), there are new cases and fatality rates per 100,000 individuals as follows: New instances of lung and bronchial cancer occur annually at a rate of 50.0 per 100,000 persons. The yearly death rate for men and women is 35.0 per 100,000. DNA methylation is one of the earliest discovered and widely studied epigenetic regulatory mechanisms, and its abnormality is closely related to the occurrence and development of cancer. However, the prognostic value of DNA methylation and LUAD needs to be further explored to improve the survival prediction of LUAD patients.

Methods: The transcriptome data and clinical data of LUAD were downloaded from TCGA and GEO databases, and the Illumina Human Methylation450 array (450k array) data were downloaded from the TCGA database. Firstly, the intersection of the expressed genes of the two databases is corrected, the differential analysis is performed, and the methylation data is evaluated by the MethylMix package to obtain differentially methylated genes. Independent prognostic genes were screened out using univariate and multivariate Cox regression analysis, and a methylation prognostic model was developed using univariate Cox analysis and validated with the GSE30219 dataset in the GEO database. Survival analysis between methylation high-risk and low-risk groups was performed and a methylation-based gene prognostic model was constructed. Finally, the prediction of potential drugs associated with the LUAD gene signature using Drug Sensitivity Genomics in Cancer (GDSC).

Results: In this study, a total of 555 samples from the TCGA database and 307 samples from GSE30219 were included, and a total of 24 differential methylation driver genes were identified. Univariate and multivariate Cox regression analyzes were used to screen out independent prognostic genes, involving 2 genes: CFTR, PKIA. Survival analysis was different between the methylation high-risk group and the low-risk group, the CFTR high methylation group and the low methylation group were poor, and the opposite was true for PKIA.

Conclusions: Our study revealed that the methylation status of CFTR and PKIA can serve as potential prognostic biomarkers and therapeutic targets in lung cancer.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10466921PMC
http://dx.doi.org/10.1186/s13023-023-02807-1DOI Listing

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