急性胰腺炎不同病理类型基因表达谱差异的研究﹡

目的:联合应用cDNA微阵列和组织微阵列技术并采用计算机辅助处理技术研究正常胰腺组织、MAP、SAP之间基因表达谱,筛选出MAP与正常粘膜以及MAP与SAP之间的差异表达基因。方法:分别抽提正常胰腺组织、MAP和SAP组织的总RNA并纯化mRNA;将各mR-NA逆转录合成以Cy5和Cy3标记的cDNA一链做探针,分别混合后在3张含有4096条双点人类全长基因的芯片上进行杂交。用ScanArray 4000扫描芯片荧光信号图像,用GenePix Pro 3.0软件对扫描图像进行数字化处理和分析。结果3次杂交出现一致性显著异常,表达差异在2倍以上的基因有141条,其中表达上调的74条,表达下调的67条。结论通过基因表达谱差异的比较,提示MAP和SAP在基因水平存在差异,差异2倍以上的141个基因可能与AP的发生和发展以及相关早期炎症的启动和演化有关。

PROGRESS IN DNA CHIP TECHNOLOGY

DNA chip technology employs light- directed in situ oligonucleotide synthesis and/or DNA microarray printing device to produce arrays of large number of probes in the tiny surface of silicon substrates, which makes it possible that the gene detection be conducted efficiently with high speed and sensitivity. The DNA chip may take important part in genome research, gene diagnoses and so on.

Analysis of gene expression profile of aspermia using cDNA microarray

Objective: To identify the differential gene expression profiles between the normal and aspermia human testes utilizing cDNA microarray. Methods: cDNA probes were prepared by labeling mRNA of aspermia testes tissues with Cy5-dUTP and mRNA of normal testes tissues with Cy3-dUTP respectively through reverse transcription. The mixed cDNA probes were then hybridized with 4096 cDNA arrays (4096 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3000 scanner (General Scanning, Inc.). The values of Cy5-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Differentially expressed genes were screened according to the criterion that the absolute value of natural logarithm of the ratio of Cy5-dUTP to Cy3-dUTP was greater-than 2.0 or less-than 0.5. A randomly chosen gene RAP1A was studied by in situ hybridization to evaluate the accuracy of the results. Results: 623 differential expressed genes related to aspermia were found. There were 303 up-expressed genes and 320 down-expressed genes. A distinct up-expressed gene RAP1A was confirmed by in situ hybridization. Conclusions: Screening the differential gene expression profiles between the normal and aspermia human testis by cDNA microarray can be used in the study of aspermia-related genes and the further research due to its properties, RAP1A may play some roles in the development and progression of aspermia.

Identification of p63 expression in human lung cancer: analysis by complementary DNA and tissue microarray

Objective: To evaluate p63 expression at mRNA transcripts and protein levels in lung squamous cell cancer (SCC), adenocarcinoma, large cell lung cancer (LCLC) and small cell lung cancer (SCLC) and their matched metastatic tumors. The association between p63 expression and p63 locus at chromosomal 3q27 q29 was also investigated. Methods: p63 mRNA expression levels in a large series of lung cancers including SCC, adenocarcinoma, LCLC, SCLC and their matched metastatic tumors were analyzed by cDNA microarray technology. A tissue microarray from 150 primary lung cancer specimens was constructed and used for immunohistochemical detection of p63 protein expression. Chromosomal imbalances at the p63 locus in 70 primary lung cancers samples were studied by comparative genomic hybridization (CGH) technology. Results: mRNA levels were 10 fold in SCC compared to LCLC, SCLC, and adenocarcinoma. Interestingly, the mRNA expression of p63 in metastatic carcinomas was significantly higher than that in their matched primary tumors ( P <0 001). Immunohistochemistry demonstrated that p63 expression was 94.64% in SCC but only 1 79% in lung adenocarcinoma and 2 of 4 LCLC were positive staining. All the results in of SCLC were negative. There was a statistically significant difference for p63 positivity between pT1 tumors and those of higher stage ( P =0 035). The CGH results indicated that p63 locus at chromosomal 3q27 q29 was overrepresented in SCC. p63 immunopositivity correlated significantly with pronounced gains of the p63 locus at chromosomal 3q27 q29 (P=0.0001), indicating that strong expression of p63 in lung SCC correlated with increased gene amplification. Conclusion: p63 might play an important role not only in squamous differentiation of lung cancer but also in tumor development and progression.

A Network Partition Algorithm for Mining Gene Functional Modules of Colon Cancer from DNA Microarray Data

Computational analysis is essential for transforming the masses of microarray datainto a mechanistic understanding of cancer. Here we present a method for findinggene functional modules of cancer from microarray data and have applied it tocolon cancer. First, a colon cancer gene network and a normal colon tissue genenetwork were constructed using correlations between the genes. Then the modulesthat tended to have a homogeneous functional composition were identified by split-ting up the network. Analysis of both networks revealed that they are scale-free.Comparison of the gene functional modules for colon cancer and normal tissuesshowed that the modules’ functions changed with their structures.