Zuo Duo, Chen Yongzi, Zhang Xinwei, Wang Zhuozhi, Jiang Wenna, Tang Fan, Cheng Runfen, Sun Yi, Sun Lu, Ren Li, Liu Rui
Department of Clinical Laboratory, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Department of Tumor Cell Biology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Cancer Biol Med. 2021 Aug 17;19(7):1029-46. doi: 10.20892/j.issn.2095-3941.2020.0516.
The main reasons for the poor prognoses of pancreatic adenocarcinoma (PA) patients are rapid early-stage progression, advanced stage metastasis, and chemotherapy resistance. Identification of novel diagnostic and prognostic biomarkers of PA is therefore urgently needed.
Three mRNA microarray datasets were obtained from the Gene Expression Omnibus database to select differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for hub genes were performed using DAVID. Correlations between expression levels of hub genes and cancer-infiltrating immune cells were investigated by TIMER. Cox proportional hazard regression analyses were also performed. Serum hub genes were screened using the HPA platform and verified for diagnostic value using ELISAs.
We identified 59 hub genes among 752 DEGs. GO analysis indicated that these 59 hub genes were mainly involved in the defense response to viruses and the type I interferon signaling pathway. We also discovered that and were associated with immune cell infiltration in the PA microenvironment. Additionally, mRNA might be used as an independent risk factor for the prognoses of PA patients. Furthermore, the protein encoded by , which exists in peripheral blood, was validated as a potential diagnostic biomarker that distinguished PA patients from healthy controls (area under the curve: 0.902, 95% confidence interval: 0.819-0.961).
Our study suggested that and were associated with immune cell infiltration in the PA microenvironment, while mRNA expression might be an independent risk factor for the survival prognoses of PA patients. Moreover, ELISAs indicated that serum ISG15 could be a potential novel diagnostic biomarker for PA.
胰腺腺癌（PA）患者预后不良的主要原因是早期进展迅速、晚期转移和化疗耐药。因此，迫切需要鉴定PA的新型诊断和预后生物标志物。
从基因表达综合数据库中获取三个mRNA微阵列数据集，以选择差异表达基因（DEG）。使用DAVID对枢纽基因进行基因本体（GO）和京都基因与基因组百科全书通路富集分析。通过TIMER研究枢纽基因表达水平与癌症浸润免疫细胞之间的相关性。还进行了Cox比例风险回归分析。使用HPA平台筛选血清枢纽基因，并通过酶联免疫吸附测定（ELISA）验证其诊断价值。
我们在752个DEG中鉴定出59个枢纽基因。GO分析表明，这59个枢纽基因主要参与对病毒的防御反应和I型干扰素信号通路。我们还发现[具体基因1]和[具体基因2]与PA微环境中的免疫细胞浸润有关。此外，[具体基因3]mRNA可能用作PA患者预后的独立危险因素。此外，存在于外周血中的由[具体基因4]编码的蛋白质被验证为区分PA患者与健康对照的潜在诊断生物标志物（曲线下面积：0.902，95%置信区间：0.819 - 0.961）。
我们的研究表明，[具体基因1]和[具体基因2]与PA微环境中的免疫细胞浸润有关，而[具体基因3]mRNA表达可能是PA患者生存预后的独立危险因素。此外，ELISA表明血清ISG15可能是PA的一种潜在新型诊断生物标志物。
