Identification of DNA damage and repair gene-related markers in pancreatic ductal adenocarcinoma by single-cell and bulk RNA sequencing.

Abstract

Background: The DNA damage response (DDR) has a major impact on the development and progression of pancreatic ductal adenocarcinoma (PDAC). Investigating biomarkers linked to the DDR may facilitate prognostic assessment and prediction of immunological characteristics for patients with PDAC.

Methods: The single-cell RNA sequencing (scRNA-seq) dataset GSE212966 was obtained from the GEO database, whereas the bulk RNA-seq data were sourced from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analyses were used to select genes to construct a prognostic risk model. Finally, the correlations of the model score with drug sensitivity, immunological checkpoints, and immune infiltration were assessed.

Results: We used 16 DDR marker genes to construct a predictive model. Furthermore, we established that the model had strong performance in both the training and validation cohorts. For PDAC, the model risk score served as an independent predictor of prognosis. There were notable differences in the proportions of the immune cells in the tumor microenvironment and drug sensitivity between the high and low risk score groups. The study confirmed that the risk score model is useful for predicting the immunotherapy response. Our experiments verified that knockdown of LY6D inhibits cell proliferation, promotes apoptosis and DNA damage.

Conclusion: Our creative integration of bulk RNA sequencing and scRNA-seq data allowed us to construct a DDR-related prognostic model. Our model can be used to predict the immunological features, treatment response and prognosis of PDAC with a relatively high degree of accuracy.