【作者】 刘海波；

【导师】 李晓娜；

【作者基本信息】 中国医科大学 ， 生物医学工程（专业学位）， 2021， 硕士

【摘要】 研究目的:近年来,随着精准医疗的快速发展,乳腺癌在诊断、治疗、预后等多个方面的总体水平都有了较大的提升,可是有关三阴性乳腺癌预后的问题却依旧困扰着医学家们。尽管科研人员对其做了大量的研究,但是三阴性乳腺癌的预后并未得到明显改善。根据柳叶刀等权威期刊的相关报道,2020年全球乳腺癌的新增病例人数为226万例。乳腺癌已被认定为女性中发病率最高的恶性肿瘤,其中,三阴性乳腺癌(TNBC)约占全部乳腺癌的16%,它是一种雌激素受体、孕激素受体和ERBB2基因指标均显示为阴性的乳腺癌亚型,其预后效果一直比其它乳腺癌亚型要差,治疗选择亦非常有限。本研究旨在对传统生物信息学方法的创新性应用,从多组学角度在多个乳腺癌预后指标中挖掘出三阴性乳腺癌的生物标志物,以更加精准的辅助临床治疗和预后评估。研究方法:本研究应用的基因数据主要来自美国国立生物技术信息中心(NCBI)创建并维护的GEO基因数据库、美国国家癌症研究所(NCI)和美国国家人类基因组研究所(NHGRI)共同创建的TCGA基因数据库。本研究应用的生物材料是在中国医科大学第一附属医院收集的60例三阴性乳腺癌患者的病变组织。我们对GEO基因数据库的两个数据集(GSE25055、GSE25065)进行基因数据挖掘,并使用PPI、WGCNA等相关生物信息学技术在多个乳腺癌临床预后指标中找到了与三阴性乳腺癌预后显著相关的hub基因。最后,我们使用ONCOMINE、TCGA和K-M ploter等多个基因数据库和免疫组化实验对hub基因进行了验证。结果:从GEO数据集中共提取了178例三阴性乳腺癌患者的基因及临床数据。然后,对提取的所有基因进行单因素生存分析,得到976个P值小于0.05的响应基因。通过对WGCNA的创新性应用,最终,我们从乳腺癌的多个临床预后指标中获取了5个与三阴性乳腺癌预后高度相关的hub基因。通过ONCOMINE、TCGA等多个基因数据库和免疫组化实验的验证,这5个hub基因(NCAPG、CCNB1、ESPL1、TRIP13、NCAPH)在三阴性乳腺癌中均表现出显著的表达差异性。结论:综上所述,通过对传统生物信息学方法的创新性应用,我们从GEO数据集中得到的5个与三阴性乳腺癌预后相关的hub基因(NCAPG、CCNB1、ESPL1、TRIP13、NCAPH)经多基因数据库和生物实验验证,这5个hub基因在三阴性乳腺癌中确实表现出非常显著的表达差异性,并且它们与多个临床预后指标高度相关。所以,本研究认为这5个hub基因极有可能是三阴性乳腺癌的新靶点。更多还原

【Abstract】 Objective: In recent years,with the rapid development of precision medicine,the overall level of breast cancer in diagnosis,treatment,prognosis and many other aspects has improved greatly,but the problems related to the prognosis of triple negative breast cancer still plague medical practitioners.Although researchers have done a lot of research on it,the prognosis of triple negative breast cancer has not improved significantly.According to relevant reports from authoritative journals such as the lancet,there were 2.26 million new cases of breast cancer worldwide in 2020.Breast cancer has been identified as the most frequently occurring malignancy in women,among which,triple negative breast cancer(TNBC),which accounts for approximately 16% of all breast cancers,is a subtype of breast cancer that shows negative genetic indicators for estrogen receptor,progesterone receptor and erb B2,and has a poor prognostic effect than other subtypes of breast cancer,with very limited therapeutic options.This study aims at innovative applications of traditional bioinformatics methods to mine biomarkers of triple negative breast cancer among multiple breast cancer prognostic indicators from a multi omics perspective for more precise adjuvant clinical treatment and prognosis assessment.Methods: The genetic data applied in this study were obtained mainly from the geo gene database created and maintained by the National Center for Biotechnology Information(NCBI),and the TCGA Gene Database Co created by the National Cancer Institute(NCI)and the National Human Genome Research Institute(NHGRI).The biomaterials applied in this study were the lesion tissues of 60 triple negative breast cancer patients collected at the First Affiliated Hospital of China Medical University.We performed gene data mining from two datasets(GSE25055,GSE25065)of the geo database and derived hub genes that were significantly associated with triple negative breast cancer prognostic indicators in multiple breast cancer clinical prognostic indicators using relevant bioinformatics techniques such as PPI and WGCNA.We then validated the hub genes using several gene databases and immunohistochemistry experiments including ONCOMINE,TCGA and K-M ploter.Results: A total of 178 sample cases of triple negative breast cancer patients were extracted from the geo dataset.Then,univariate survival analysis was performed on all the genes extracted,resulting in 976 significant genes with p-values less than0.05.Through innovative application of WGCNA,ultimately,we obtained five hub genes that were highly associated with triple negative breast cancer from multiple clinical prognostic indicators.Through ONCOMINE,TCGA and other gene databases and immunohistochemical experiments,the 5 hub genes(NCAPG,CCNB1,ESPL1,TRIP13,NCAPH)showed significant differences in three negative breast cancer.Conclusions: In summary,through innovative application of traditional bioinformatics methods,we mined five hub genes(NCAPG,CCNB1,ESPL1,TRIP13,NCAPH)associated with triple negative breast cancer prognosis,which were verified by multiple databases and biological experiments,showed indeed very significant expression differences in triple negative breast cancer,and they were associated with multiple clinical prognosis Indicators are highly correlated.So,we think that these 5 hub genes are highly likely to be novel targets for triple negative breast cancer.更多还原