Laboratory of Virology, Medical School, University of Crete, Crete, Greece.
PLoS One. 2011 Apr 4;6(4):e18135. doi: 10.1371/journal.pone.0018135.
Current diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays.
Our goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays.
METHODOLOGY/PRINCIPAL FINDINGS: BC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways.
CONCLUSIONS/SIGNIFICANCE: The identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers.
目前，膀胱癌（BC）的诊断和治疗已经取得了很大的进展，这得益于微阵列技术的应用。
我们的目标是利用微阵列技术，鉴定具有临床相关性的 BC 亚类之间的常见差异表达（DE）基因。
方法/主要发现：对 BC 样本和对照样本（包括实验和公开数据集）进行全基因组微阵列分析。我们根据组织学对样本进行分组，并单独鉴定每个样本中的 DE 基因，以及每个肿瘤组中的 DE 基因。采用双重分析策略。首先，分析实验样本并得出结论；然后，将实验集与公开的微阵列数据集相结合，并进一步分析以寻找常见的 DE 基因。实验数据集同时确定了 831 个在所有肿瘤样本中均差异表达的基因。此外，与 5 个正常组织相比，所有 10 个 BC 样本中同时有 33 个基因上调和 85 个基因下调。层次聚类根据组织学将肿瘤组分为不同的亚群。对所有基因和所有样本进行 K-均值聚类，以及对肿瘤组进行聚类，共得到 49 个聚类。对所有样本中常见的 DE 基因进行 K-均值聚类，得到 24 个聚类。基于 PCA，基因表现出不同的差异表达模式。YY1 和 NFκB 是调节鉴定出的 DE 基因表达的最常见转录因子之一。第 1 号染色体包含 32 个 DE 基因，其次是第 2 号和第 11 号染色体，分别包含 25 个和 23 个 DE 基因，第 21 号染色体的 DE 基因数量最少。GO 分析显示，在常见下调的 DE 基因中，运输和结合基因占主导地位；在上调的 DE 基因中，RNA 代谢和加工基因占主导地位；在下调的 T1 级-III 肿瘤和上调的 T2/T3 级-III 肿瘤的 DE 基因中，细胞通讯和信号转导基因占主导地位。整合所有微阵列平台的样本揭示了 17 个常见的 DE 基因（BMP4、CRYGD、DBH、GJB1、KRT83、MPZ、NHLH1、TACR3、ACTC1、MFAP4、SPARCL1、TAGLN、TPM2、CDC20、LHCGR、TM9SF1 和 HCCS），其中 4 个参与了许多途径。
结论/意义：鉴定不同组织学的 BC 样本之间的常见 DE 基因，可以为发现新的潜在标志物提供进一步的见解。
