申请人:AGENCY FOR SCIENCE, TECHNOLOGY AND RESEARCH
公开号:US20160222458A1
公开(公告)日:2016-08-04
We describe a method of assigning a grade to a breast tumour, which grade is indicative of the aggressiveness of the tumour, the method comprising detecting the expression of a gene selected from the genes set out in Table D0 (6g-TAGs) or Table D1 (SWS Classifier 0). We also describe methods of treating patients having a high aggressiveness tumour or a low aggressiveness tumour, by identifying the aggressiveness tumour by obtaining, from a sample of a histological Grade 2 tumour isolated from the patient, gene expression data of BRRN1, AURKA, MELK, PRR11, CENPW and E2F1; assigning a grade to the tumour by applying a class prediction algorithm to the gene expression data, wherein a Grade 3 tumour is classified as a high aggressiveness tumour and a Grade 1 tumour is classified as a low aggressiveness tumour; and specifically treating the patient accordingly.
我们描述了一种将乳腺肿瘤分级的方法,该等级表明肿瘤的侵袭性,该方法包括检测来自表D0(6g-TAGs)或表D1(SWS Classifier 0)中所选基因的表达。我们还描述了治疗高侵袭性肿瘤或低侵袭性肿瘤的方法,通过从患者分离的组织学2级肿瘤样本中获取BRRN1,AURKA,MELK,PRR11,CENPW和E2F1的基因表达数据来确定侵袭性肿瘤;通过将类别预测算法应用于基因表达数据来对肿瘤进行分级,其中3级肿瘤被分类为高侵袭性肿瘤,1级肿瘤被分类为低侵袭性肿瘤;并相应地治疗患者。