基于线性微分方程模型和k-means聚类研究乳腺癌转移相关基因调控通路

目的通过线性微分方程模型和k-means聚类方法初步探索性研究乳腺癌转移相关基因表达调控通路和预测其生物学意义。方法选择30例伴有淋巴结转移的乳腺癌组织及其相应淋巴结转移癌组织的基因表达谱芯片的比较结果,通过线性微分方程模型和k-means聚类分析乳腺癌转移相关基因表达调控通路。结果比较伴有淋巴结转移的乳腺癌组织和其相应淋巴结转移癌组织,分析筛选了27个表达差异基因,提出GRP基因、BPAG1基因、SFRP2基因间的乳腺癌转移相关调控通路存在的假设。结论初步表明乳腺癌转移的形成是与多基因异常引起基因调控通路异常致使细胞恶性转化相关,利用多种生物信息学手段分析乳腺癌转移相关基因表达调控通路及其生物学意义具有一定的应用价值。

Genetic regulatory pathway of gene related breast cancer metastasis: primary study by linear differential model and k-means clustering

Objective To investigate the potential genetic regulatory pathway of gene related breast cancer metastasis. Methods Microarray technique was used to identify the gene expression profile and to screen the differential expression genes in breast cancer with special emphasis on the metastasis factors. A gene chip was available, obtained from the surgical samples, including breast cancer primary tissues and metastasis tissues, of 30 female patients with breast cancer at different clinical stages. Then potential genetic regulatory pathway of gene related breast cancer metastasis was analyzed with a linear differential model and k-means clustering. Results Twenty-seven differential expression genes were identified. It was suggested that the potential regulatory pathway of gene related to breast cancer metastasis is made up of GRP, BPAG1, and SFRF2 genes. Conclusion The metastasis of breast cancer is related to the cancerization caused by the abnormal expression of multiple genes. It is reliable to analyze the Genetic regulatory pathway of gene related breast cancer metastasis by using multiple bio-informatic measures.