Klett Hagen, Fuellgraf Hannah, Levit-Zerdoun Ella, Hussung Saskia, Kowar Silke, Küsters Simon, Bronsert Peter, Werner Martin, Wittel Uwe, Fritsch Ralph, Busch Hauke, Boerries Melanie
Institute of Molecular Medicine and Cell Research, University of Freiburg, Freiburg, Germany.
German Cancer Research Center, Heidelberg, Germany.
Front Genet. 2018 Apr 5;9:108. doi: 10.3389/fgene.2018.00108. eCollection 2018.
Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic.
晚期诊断和全身扩散是导致胰腺导管腺癌(PDAC)预后始终较差的主要原因。因此,迫切需要开发PDAC的诊断生物标志物,以改善临床中的患者分层和治疗结果。通过研究肿瘤组织和非肿瘤组织的独立PDAC患者队列的转录组,我们通过一种新颖的、普遍适用的荟萃分析,鉴定出81个调控显著的基因。利用共表达值进行一致性聚类,揭示了四个不同的聚类,其基因分别源自外分泌/内分泌胰腺、基质细胞和肿瘤细胞。基于TCGA数据库,三个聚类与PDAC患者的生存率密切相关,这突出了所鉴定基因的预后潜力。结合生存影响信息和荟萃分析中的稳健性,我们提取了一个包含17个基因的子集进行进一步验证。我们发现,该子集不仅能在新鲜冷冻以及福尔马林固定石蜡包埋样本中区分PDAC与非肿瘤组织和基质,还能检测胰腺前驱病变并甄别出胰腺炎样本。此外,该分类器在TCGA数据库中能区分PDAC与其他癌症。另外,我们使用qPCR在转录水平上对PDAC患者的分类器进行了实验验证,并通过免疫组化对三种蛋白质(AHNAK2、LAMC2、TFF1)以及使用基于ELISA的血浆蛋白质检测对两种分泌蛋白(TFF1、SERPINB5)在蛋白质水平上进行了应用示例。总之,我们提出了一种新颖的、稳健的PDAC诊断和预后基因特征,未来在临床上具有潜在的适用性。