Identification of Wnt/β-Catenin- and Autophagy-Related lncRNA Signature for Predicting Immune Efficacy in Pancreatic Adenocarcinoma

SIMPLE SUMMARY: Pancreatic adenocarcinoma (PAAD) is a devastating malignant tumor with a dismal prognosis. How to evaluate the prognosis efficiently is urgently needed for PAAD patients. Both activated autophagy and Wnt/β-catenin signaling pathway were reported to show significant relevancy with PAAD. This study aimed to identify the potential prognosis factor based on autophagy and Wnt/β-catenin related genes in PAAD. We identified 45 prognostic genes significantly associated with the overall survival of PAAD patients. Then a prognosis model was constructed according to six warlncRNAs (LINC01347, CASC8, C8orf31, LINC00612, UCA1, and GUSBP11). In conclusion, our results provide a basis for the pathogenesis of PAAD, including the cross-talk between autophagy and the Wnt/β-catenin signaling pathway, and reveal a prognostic indicator with the potential of the efficacy of prognosis and immunotherapeutic responses in PAAD patients. ABSTRACT: Pancreatic cancer is one of the tumors with a poor prognosis. Therefore, it is significant and urgent to explore effective biomarkers for risk stratification and prognosis prediction to promote individualized treatment and prolong the survival of patients with PAAD. In this study, we identified Wnt/β-catenin- and autophagy-related long non-coding RNAs (lncRNAs) and demonstrated their role in predicting immune efficacy for PAAD patients. The univariate and multivariate Cox proportional hazards analyses were used to construct a prognostic risk model based on six autophagy- and Wnt/β-catenin-related lncRNAs (warlncRNAs): LINC01347, CASC8, C8orf31, LINC00612, UCA1, and GUSBP11. The high-risk patients were significantly associated with poor overall survival (OS). The receiver operating characteristic (ROC) curve analysis was used to assess the predictive accuracy of the prognostic risk model. The prediction efficiency was supported by the results of an independent validation cohort. Subsequently, a prognostic nomogram combining warlncRNAs with clinical indicators was constructed and showed a good predictive efficiency for survival risk stratification. Furthermore, functional enrichment analysis demonstrated that the signature according to warlncRNAs is closely linked to malignancy-associated immunoregulatory pathways. Correlation analysis uncovered that warlncRNAs’ signature was considerably associated with immunocyte infiltration, immune efficacy, tumor microenvironment score, and drug resistance.