Drew Janice E, Farquharson Andrew J, Mayer Claus Dieter, Vase Hollie F, Coates Philip J, Steele Robert J, Carey Francis A
Metabolic Health, Rowett Institute of Nutrition and Health, University of Aberdeen, Aberdeen, AB21 9SB, Scotland.
Biomathematics and Statistics Scotland, University of Aberdeen, Aberdeen, AB21 9SB, Scotland.
PLoS One. 2014 Nov 25;9(11):e113071. doi: 10.1371/journal.pone.0113071. eCollection 2014.
Cancers exhibit abnormal molecular signatures associated with disease initiation and progression. Molecular signatures could improve cancer screening, detection, drug development and selection of appropriate drug therapies for individual patients. Typically only very small amounts of tissue are available from patients for analysis and biopsy samples exhibit broad heterogeneity that cannot be captured using a single marker. This report details application of an in-house custom designed GenomeLab System multiplex gene expression assay, the hCellMarkerPlex, to assess predictive gene signatures of normal, adenomatous polyp and carcinoma colon tissue using archived tissue bank material. The hCellMarkerPlex incorporates twenty-one gene markers: epithelial (EZR, KRT18, NOX1, SLC9A2), proliferation (PCNA, CCND1, MS4A12), differentiation (B4GANLT2, CDX1, CDX2), apoptotic (CASP3, NOX1, NTN1), fibroblast (FSP1, COL1A1), structural (ACTG2, CNN1, DES), gene transcription (HDAC1), stem cell (LGR5), endothelial (VWF) and mucin production (MUC2). Gene signatures distinguished normal, adenomatous polyp and carcinoma. Individual gene targets significantly contributing to molecular tissue types, classifier genes, were further characterised using real-time PCR, in-situ hybridisation and immunohistochemistry revealing aberrant epithelial expression of MS4A12, LGR5 CDX2, NOX1 and SLC9A2 prior to development of carcinoma. Identified gene signatures identify aberrant epithelial expression of genes prior to cancer development using in-house custom designed gene expression multiplex assays. This approach may be used to assist in objective classification of disease initiation, staging, progression and therapeutic responses using biopsy material.
癌症表现出与疾病发生和进展相关的异常分子特征。分子特征可改善癌症筛查、检测、药物开发以及为个体患者选择合适的药物治疗方案。通常,患者可用于分析的组织量非常少,且活检样本表现出广泛的异质性,无法通过单一标志物来捕捉。本报告详细介绍了一种内部定制设计的GenomeLab系统多重基因表达分析方法——hCellMarkerPlex,该方法用于使用存档组织库材料评估正常、腺瘤性息肉和结肠癌组织的预测基因特征。hCellMarkerPlex包含21个基因标志物:上皮细胞(EZR、KRT18、NOX1、SLC9A2)、增殖(PCNA、CCND1、MS4A12)、分化(B4GANLT2、CDX1、CDX2)、凋亡(CASP3、NOX1、NTN1)、成纤维细胞(FSP1、COL1A1)、结构(ACTG2、CNN1、DES)、基因转录(HDAC1)、干细胞(LGR5)、内皮细胞(VWF)和粘蛋白产生(MUC2)。基因特征可区分正常、腺瘤性息肉和癌组织。使用实时PCR、原位杂交和免疫组织化学进一步表征了对分子组织类型有显著贡献的单个基因靶点(分类基因),揭示了在癌发生之前MS4A12、LGR5、CDX2、NOX1和SLC9A2的异常上皮表达。所确定的基因特征通过内部定制设计的基因表达多重分析方法,识别出癌症发生之前基因的异常上皮表达。这种方法可用于协助使用活检材料对疾病的起始、分期、进展和治疗反应进行客观分类。