基于网络分析的浸润性乳腺癌基因标志物研究

乳腺癌是一种机理复杂的疾病，通过临床表现很难在早期诊断乳腺癌病人的恶性程度，但是在细胞系层面具有明确区分标准。基于数据挖掘和基因网络的研究方法是诊断乳腺癌这种复杂疾病的有效手段之一。浸润性乳腺癌和非浸润性乳腺癌在病人的生存预后差异很大。本项目基于对临床数据进行深度的数据挖掘，建立浸润性乳腺癌和非浸润性乳腺癌的基因共表达网络。利用网络分析方法，通过比较浸润性乳腺癌和非浸润性乳腺癌细胞系中不同基因表达构建的网络来获取浸润性乳腺癌基因标志物。主要内容包括：（1）公共数据集GEO中乳腺癌细胞系基因组数据的收集和处理；（2）浸润性乳腺癌和非浸润性乳腺癌基因共表达网络的构建；（3）浸润性乳腺癌的特有基因共表达网络的建立与分析；（4）通过独立公共数据验证确定浸润性乳腺癌基因标志物；（5）对所得的浸润性乳腺癌基因标志物进行评估。本项目为乳腺癌的分类诊断提供一种新思路，为临床决策提供科学依据。

Breast cancer is a disease with complex mechanism. It is difficult to diagnose the malignancy of breast cancer patients in early stage through clinical manifestations, but there are clear criteria for differentiation at the cell line level. Based on data mining and gene network, research method is one of the effective means to diagnose this complex disease. Invasive breast cancer refers to a malignant tumor in which cancer cells have penetrated the basement membrane of breast ducts or lobular acini and invaded the stroma. Invasive breast cancer and non-invasive breast cancer have great differences in survival and prognosis. This project is based on in-depth data mining of clinical data to establish gene co-expression networks for invasive breast cancer and non-invasive breast cancer. By using of network analysis method, the gene markers of invasive breast cancer are obtained by comparing different gene expression networks in invasive and non-invasive breast cancer cell lines. The main contents include: (1) Collection and processing of genomic data of breast cancer cell lines in GEO dataset; (2) Construction of gene co-expression networks for invasive and non-invasive breast cancer; (3) Establishment and analysis of specific gene co-expression networks for invasive breast cancer; (4) Identification of invasive breast cancer gene markers through independent public data validation; (5) Assessment of the obtained invasive breast cancer gene markers. This project provides a new idea for the classification and diagnosis of breast cancer and scientific basis for clinical decision-making.