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外周血单个核细胞差异基因表达分析揭示了一种用于早期检测胰腺癌的新方法。

Differential gene expression analysis of peripheral blood mononuclear cells reveals novel test for early detection of pancreatic cancer.

机构信息

Eppley Institute for Research in Cancer and Allied Diseases, University of Nebraska Medical Center, Omaha, NE 68198, USA.

出版信息

Cancer Biomark. 2011;11(1):1-14. doi: 10.3233/CBM-2012-0260.

Abstract

BACKGROUND

We sought to validate global microarray results indicating the differential expression of 383 genes in Peripheral Blood Mononuclear Cells (PBMCs) from patients with pancreatic cancer (PC) and to further evaluate their PC diagnostic potential.

METHODS AND MATERIALS

In total, 177 patients were recruited (47 healthy controls (HC), 35 chronic pancreatitis (CP) patients, and 95 PC patients). PBMC expressions of six genes from our previous study (ANXA3, ARG1, CA5B, F5, SSBP2, and TBC1D8) along with four new genes (MIC1, NGAL, MUC1, and MUC16) were analyzed using multiplex Q-RT PCR.

RESULTS

Differential expressions of 5 of the 6 genes previously identified by PBMC microarray were validated in this study. Multivariate models for PBMC gene expression were attempted to determine if any combination was diagnostically superior to CA19-9 alone. We found that addition of PBMC CA5B, F5, SSBP2, and MIC1 expression levels to CA19-9 significantly improved CA19-9's diagnostic abilities when comparing resectable PC to CP patients (p=0.023).

CONCLUSIONS

Results of our previous study were validated, indicating reproducibility of PC-associated PBMC expression profiling. We identified a score-based model that can differentiate resectable PC from CP better than CA19-9, potentiating that PBMC differential expression analysis may offer a novel tool for early PC diagnosis.

摘要

背景

我们旨在验证全基因组芯片结果表明胰腺癌(PC)患者外周血单个核细胞(PBMC)中 383 个基因的差异表达,并进一步评估其在 PC 诊断中的潜力。

方法和材料

共招募了 177 名患者(47 名健康对照(HC)、35 名慢性胰腺炎(CP)患者和 95 名 PC 患者)。使用多重 Q-RT-PCR 分析了我们之前研究中的六个基因(ANXA3、ARG1、CA5B、F5、SSBP2 和 TBC1D8)以及四个新基因(MIC1、NGAL、MUC1 和 MUC16)在 PBMC 中的表达。

结果

本研究验证了 PBMC 微阵列先前鉴定的 6 个基因中的 5 个的差异表达。尝试构建 PBMC 基因表达的多变量模型,以确定任何组合是否优于 CA19-9 单独用于诊断。我们发现,在 CA19-9 比较可切除性 PC 与 CP 患者时,将 PBMC CA5B、F5、SSBP2 和 MIC1 表达水平添加到 CA19-9 中显著提高了 CA19-9 的诊断能力(p=0.023)。

结论

我们之前研究的结果得到了验证,表明 PC 相关 PBMC 表达谱具有可重复性。我们确定了一种基于评分的模型,可以比 CA19-9 更好地区分可切除性 PC 与 CP,这表明 PBMC 差异表达分析可能为早期 PC 诊断提供一种新的工具。

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