转录组数据的荟萃分析确定了一种新型的5基因胰腺癌分类器。
Meta-analysis of transcriptome data identifies a novel 5-gene pancreatic adenocarcinoma classifier.
作者信息
Bhasin Manoj K, Ndebele Kenneth, Bucur Octavian, Yee Eric U, Otu Hasan H, Plati Jessica, Bullock Andrea, Gu Xuesong, Castan Eduardo, Zhang Peng, Najarian Robert, Muraru Maria S, Miksad Rebecca, Khosravi-Far Roya, Libermann Towia A
机构信息
Department of Medicine, BIDMC Genomics, Proteomics, Bioinformatics and Systems Biology Center, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA.
Department of Pathology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, USA.
出版信息
Oncotarget. 2016 Apr 26;7(17):23263-81. doi: 10.18632/oncotarget.8139.
PURPOSE
Pancreatic ductal adenocarcinoma (PDAC) is largely incurable due to late diagnosis. Superior early detection biomarkers are critical to improving PDAC survival and risk stratification.
EXPERIMENTAL DESIGN
Optimized meta-analysis of PDAC transcriptome datasets identified and validated key PDAC biomarkers. PDAC-specific expression of a 5-gene biomarker panel was measured by qRT-PCR in microdissected patient-derived FFPE tissues. Cell-based assays assessed impact of two of these biomarkers, TMPRSS4 and ECT2, on PDAC cells.
RESULTS
A 5-gene PDAC classifier (TMPRSS4, AHNAK2, POSTN, ECT2, SERPINB5) achieved on average 95% sensitivity and 89% specificity in discriminating PDAC from non-tumor samples in four training sets and similar performance (sensitivity = 94%, specificity = 89.6%) in five independent validation datasets. This classifier accurately discriminated PDAC from chronic pancreatitis (AUC = 0.83), other cancers (AUC = 0.89), and non-tumor from PDAC precursors (AUC = 0.92) in three independent datasets. Importantly, the classifier distinguished PanIN from healthy pancreas in the PDX1-Cre;LSL-KrasG12D PDAC mouse model. Discriminatory expression of the PDAC classifier genes was confirmed in microdissected FFPE samples of PDAC and matched surrounding non-tumor pancreas or pancreatitis. Notably, knock-down of TMPRSS4 and ECT2 reduced PDAC soft agar growth and cell viability and TMPRSS4 knockdown also blocked PDAC migration and invasion.
CONCLUSIONS
This study identified and validated a highly accurate 5-gene PDAC classifier for discriminating PDAC and early precursor lesions from non-malignant tissue that may facilitate early diagnosis and risk stratification upon validation in prospective clinical trials. Cell-based experiments of two overexpressed proteins encoded by the panel, TMPRSS4 and ECT2, suggest a causal link to PDAC development and progression, confirming them as potential therapeutic targets.
目的
由于诊断较晚，胰腺导管腺癌（PDAC）大多无法治愈。优质的早期检测生物标志物对于提高PDAC患者的生存率和风险分层至关重要。
实验设计
对PDAC转录组数据集进行优化的荟萃分析，以识别和验证关键的PDAC生物标志物。通过qRT-PCR在显微切割的患者来源FFPE组织中检测5基因生物标志物panel的PDAC特异性表达。基于细胞的试验评估了其中两种生物标志物TMPRSS4和ECT2对PDAC细胞的影响。
结果
一个5基因的PDAC分类器（TMPRSS4、AHNAK2、POSTN、ECT2、SERPINB5）在四个训练集中区分PDAC与非肿瘤样本时，平均灵敏度达到95%，特异性达到89%，在五个独立验证数据集中表现相似（灵敏度 = 94%，特异性 = 89.6%）。该分类器在三个独立数据集中准确区分了PDAC与慢性胰腺炎（AUC = 0.83）、其他癌症（AUC = 0.89）以及PDAC前体与非肿瘤（AUC = 0.92）。重要的是，该分类器在PDX1-Cre;LSL-KrasG12D PDAC小鼠模型中区分了PanIN与健康胰腺。在PDAC的显微切割FFPE样本以及匹配的周围非肿瘤胰腺或胰腺炎样本中证实了PDAC分类器基因的差异表达。值得注意的是，敲低TMPRSS4和ECT2可降低PDAC在软琼脂中的生长和细胞活力，敲低TMPRSS4还可阻断PDAC的迁移和侵袭。
结论
本研究识别并验证了一种高度准确的5基因PDAC分类器，用于区分PDAC和早期前体病变与非恶性组织，这可能有助于在前瞻性临床试验中验证后实现早期诊断和风险分层。对该panel编码的两种过表达蛋白TMPRSS4和ECT2进行的基于细胞的实验表明它们与PDAC的发生和进展存在因果关系，证实它们为潜在的治疗靶点。
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