Jiang Zhiyang, Pan Jiadong, Lu Jiahui, Mei Jie, Xu Rui, Xia Dandan, Yang Xuejing, Wang Huiyu, Liu Chaoying, Xu Junying, Ding Junli
Department of General Surgery, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Department of Gastroenterology, Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Front Pharmacol. 2022 Oct 13;13:1025921. doi: 10.3389/fphar.2022.1025921. eCollection 2022.
It has been well-defined that tumor-infiltrating lymphocytes (TILs) play critical roles in pancreatic cancer (PaCa) progression. This research aimed to comprehensively explore the composition of TILs in PaCa and their potential clinical significance. A total of 178 samples from the TCGA and 63 samples from the GSE57495 dataset were enrolled in our study. ImmuCellAI was applied to calculate the infiltrating abundance of 24 immune cell types in PaCa and further survival analysis revealed the prognostic values of TILs in PaCa. Moreover, the Hallmark enticement analysis of differentially expressed genes (DEGs) between low- and high-risk groups was performed as well. Immunohistochemistry staining was used to evaluate NEUROD1 expression. As result, different kinds of TILs had distinct infiltrating features. In addition, Specific TILs subsets had notable prognostic values in PaCa. We further established a 6-TILs signature to assess the prognosis of PaCa patients. Kaplan-Meier and Cox regression analyses both suggested the significant prognostic value of the signature in PaCa. Based on the prognostic signature, we screened a great deal of potential prognostic biomarkers and successfully validated NEUROD1 as a novel prognostic biomarker in PaCa. Overall, the current study illuminated the immune cells infiltrating the landscape in PaCa and identified a TILs-dependent signature and NEUROD1 for prognostic prediction in PaCa patients.
肿瘤浸润淋巴细胞(TILs)在胰腺癌(PaCa)进展中发挥关键作用,这一点已得到明确。本研究旨在全面探究PaCa中TILs的组成及其潜在的临床意义。我们的研究纳入了来自TCGA的178个样本和来自GSE57495数据集的63个样本。应用ImmuCellAI计算PaCa中24种免疫细胞类型的浸润丰度,进一步的生存分析揭示了TILs在PaCa中的预后价值。此外,还对低风险和高风险组之间的差异表达基因(DEGs)进行了特征引诱分析。采用免疫组织化学染色评估NEUROD1表达。结果显示,不同类型的TILs具有不同的浸润特征。此外,特定的TILs亚群在PaCa中具有显著的预后价值。我们进一步建立了一个6-TILs特征来评估PaCa患者的预后。Kaplan-Meier分析和Cox回归分析均表明该特征在PaCa中具有显著的预后价值。基于该预后特征,我们筛选了大量潜在的预后生物标志物,并成功验证NEUROD1为PaCa中的一种新型预后生物标志物。总体而言,当前研究阐明了浸润PaCa的免疫细胞格局,并确定了一种依赖TILs的特征以及用于预测PaCa患者预后的NEUROD1。