Identification of genomic instability related lncRNA signature with prognostic value and its role in cancer immunotherapy in pancreatic cancer

Background: Increasing evidence suggested the critical roles of lncRNAs in the maintenance of genomic stability. However, the identification of genomic instability-related lncRNA signature (GILncSig) and its role in pancreatic cancer (PC) remains largely unexplored. Methods: In the present study, a systematic analysis of lncRNA expression profiles and somatic mutation profiles was performed in PC patients from The Cancer Genome Atlas (TCGA). We then develop a risk score model to describe the characteristics of the model and verify its prediction accuracy. ESTIMATE algorithm, single-sample gene set enrichment analysis (ssGSEA), and CIBERSORT analysis were employed to reveal the correlation between tumor immune microenvironment, immune infiltration, immune checkpoint blockade (ICB) therapy, and GILncSig in PC. Results: We identified 206 GILnc, of which five were screened to develop a prognostic GInLncSig model. Multivariate Cox regression analysis and stratified analysis revealed that the prognostic value of the GILncSig was independent of other clinical variables. Receiver operating characteristic (ROC) analysis suggested that GILncSig is better than the existing lncRNA-related signatures in predicting survival. Additionally, the prognostic performance of the GILncSig was also found to be favorable in patients carrying wild-type KRAS, TP53, and SMAD4. Besides, a nomogram exhibited appreciable reliability for clinical application in predicting the prognosis of patients. Finally, the relationship between the GInLncSig model and the immune landscape in PC reflected its application value in clinical immunotherapy. Conclusion: In summary, the GILncSig identified by us may serve as novel prognostic biomarkers, and could have a crucial role in immunotherapy decisions for PC patients.