Pancreatic ductal adenocarcinoma (PDAC) is regarded as a devastating malignant tumor and will rank the second leading cause of cancer deaths by 2030(33). The 5-year prognosis remains very poor, as up to 85% of cases present with either distant metastatic lesion or unresectable disease(34). Moreover, PDACs characteristic with a high intra- and inter-tumor heterogeneity, resulting in patients with the same clinical features exhibit distinct clinical outcomes and response to treatments(35). As the only predictive indicator utilized routinely in clinical application to forecast the survival and guide clinical management, the AJCC TNM staging fails to forecast the clinical outcome for patients with the same clinical stage (36). Thus, there is urgent need to exploit the novel and effective biomarkers for early diagnosis, treatment option, and survival evaluation to improve the prognosis for PDAC. In the past decades, more and more studies provided evidences to support that lncRNAs might play key roles in tumorigenesis, progression and invasion in PDAC(37–39).
According to previous researches, lncRNAs were reported as crucial regulators in regulating cancer immunity(13). A recent research from Mineo Marco et al reported that INCR1 knockdown can improve CAR T cell therapy via sensitizing tumor cells to cytotoxic T cell-mediated clearing (40). Another research showed encouraging potentiality for new clinical management decisions on the basis of epigenetic regulation targeting LncMALAT1, which can coordinate with the immune system(41). More and more evidences has strongly supported that immune-related lncRNAs may be novel disease biomolecules for cancer clinic treatment and possess valuable prognostic significance for survival(42, 43). Several immune‐related lncRNA signatures have been explored in some tumors, such as bladder cancer, breast cancer, and colon cancer(44–46). Nevertheless, the latent role of immune-correlated lncRNAs risk score model as a helpful predictive indicator needs further validated in cancer immune checkpoint therapy, especially in PDAC.
Here, our study assembled an immune-associated lncRNA signature and explored its predictive performance, as well as its role in immune cell infiltration and the assessment of responsiveness to immune checkpoint blockade treatment for PDAC patients. In our research, immune-associated lncRNAs were systematically identified through employing univariate Cox regression model as well as the biostatistics method. Subsequently, we employed LASSO algorithm analysis in lncRNA files derived from TCGA database, and final 5 significant immune-related lncRNAs were recognized. These five lncRNAs were included into developing the predictive risk score model. Subsequently, Kaplan–Meier curves, the timedependent ROC curves, and Cox regression analysis were employed to confirm the predictive performance of this immune-correlated lncRNAs risk score model, which can serve as an independent biomolecular indicator to forecast PDAC survival. Further validation was analyzed in both the internal testing group and combined cohort.
Subsequently, our pathway enrichment results suggested the latent impact of our immune-related lncRNA risk model on PDAC tumorigenesis and progression via chondrocyte development, keratinocyte proliferation, laminin binding and so on. Our results provide new evidence for strongly supporting that lncRNAs whose functions was still unclear may be novel biomarkers for predicting clinical outcomes in PDAC. Nonetheless, these findings require to be confirmed in further researches.
With the rise of immunotherapy, immune checkpoint blockade (ICB) treatment has markedly transformed anti-tumor immunopathological treatment (47–49). Preclinical research of immunotherapy for pancreatic cancer showed some promise, making it in the limelight(50). Its efficacy in treating patients with PDAC, however, is limited by its immunosuppressive microenvironment (51). Such biomolecules as immune checkpoint gene and tumor mutational burden cannot accurately forecast clinical outcomes from ICB treatment. Thus, exploiting biomolecular markers that can precisely forecast responsiveness to ICB is crucial to further advance precision immunotherapy(27, 52). Several studies reported that lncRNAs associated with immune reaction could forecast responsiveness to clinical treatment (53, 54). In this study, the association analyses shown that PDCD1, CD274, PDCD1LG2, CTLA-4, HAVCR2, and IDO1 were coexpressed. Besides, this immune‐correlated lncRNA risk score was significantly correlated with the ICB treatment target genes (i.e., PDCD1 and CTLA4). These findings indicated that this immune-related lncRNA risk score model may serve as a key part to measure the responsiveness to ICB treatment of PDAC patients. Recently, accumulating evidences have supported that numerous lncRNAs possess key roles in regulating immunity, such as immune cell infiltration, antigen presentation and so on(12, 13). Here, our results shown that this immune‐correlated lncRNAs risk model was markedly correlated with CD4 + T cells infiltration in PDAC, which indicated that as-constructed immune‐correlated lncRNA risk score model might serve as a key role in immune cell infiltration in PDAC.
Compared with published researches that investigated the lncRNA prognostic performance in PDAC, some superiorities of our research are as follows. First of all, our study is the first to explore the correlation between immune-related lncRNA signature and immune infiltration in PDAC. Besides, as far as we know, this research is the first to exploit immune-related lncRNAs signature which may precisely predict responsiveness to ICB in PDAC.