Gene expression profiling predicts clinical outcome of breast cancer

Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.     

Breast cancer-specific serum peptide profiles

Early detection of breast cancer is paramount to successful clinical therapy. Yet, early-stage breast cancer lacks specific symptoms or biomarkers. With the emerging of the mass spectrometric (MS)–based signatures as biomarkers, we investigated breast cancer-related serum profile pattern through class prediction and independent validation, and used Fourier transfer MS to identify breast cancer signature. We now show a distinctive serum peptide pattern that discriminates breast cancer from healthy controls with 93.2% sensitivity and 95.4% specificity. m/z 5901.70 and 4465.74 of ion fragment of FPA and alpha1-antichymotrypsin are found in the signatures that predominantly discriminate breast cancer from healthy individuals. These novel findings identify an MS-based serum peptide pattern of breast cancer that may have direct clinical utility in future. Contributed equally to this work Supported by National Natural Science Foundation of China (Grant No. 30321003) and National Key Basic Research and Development Program of China (Grant No. 2004CB518800)     

Prediction of multiple drug resistance phenotype in cancer cell lines using gene expression profiles and phylogenetic trees

When microarray gene expression data are used to predict multiple drug resistance (MDR) phenotypes for anticancer drugs, the normalization strategy and the quality of the selected signature genes are usually the main causes of inconsistency among different experiments. A stable statistical drug response prediction model is urgently required in oncology. In this study, the microarray gene expression data of multiple cancer cell lines with MDR was analyzed. For each probe-set, the expression value was defined as present/absent (1/0) and was classified into a gene set defined with protein domain organization (PDO). After employing the gene content method of phylogenetic analysis, a phylogenetic model (cell tree) for MDR phenotype prediction was built at the PDO gene set level. The results indicate that classification of cancer cell lines is predominantly affected by both the histopathological features and the MDR phenotype (paclitaxel and vinblastine). When applying this model to predict the MDR phenotype of independent samples, the phylogenetic model performs better than signature gene models. Although the utility of our procedure is limited due to sample heterogeneity, it still has potential application in MDR research, especially for hematological tumors or established cell lines.     

基于条件关联互补基因的乳腺癌预后分析

为了提高乳腺癌患者的生存率,改善病人的临床治疗效果,从分子机制上研究了乳腺癌的致病基因。首先对113个正常组织和1 109个癌症组织的表达量进行差异分析,然后对差异表达的基因采用条件联合分析方式对互补基因进行分组,并用逐步Cox回归挑选出一组基因拟合预后模型。研究结果显示:VWCE,SPDYC,CRYBG3,DEFB1,SEL1L2,NMNAT2 6个基因对患者生存率是有害的,AMZ1,GJB2,CXCL2,ALDOC 4个基因对患者生存率是有利的,最终确定10个基因的预后模型能够显著地将样本分为高风险组和低风险组,并且对乳腺癌患者5年和10年的生存率进行了预测,依赖时间的AUC值均可达0.7以上。所提方法能够利用基因与基因之间的关联性,很好地对高维数据进行降维,消除基因与基因之间的共线性问题,10个基因的预后模型可以对患者的临床预测提供帮助。     

基于SAM和GA／SVM的肿瘤基因表达谱分类算法

基因芯片技术在肿瘤分型分类的研究中得到了广泛的应用．为了处理肿瘤基因表达谱数据,建立肿瘤分类预测模型,文中采用基因表达差异显著性分析方法,支持向量机,遗传算法相结合的多步骤降维分类方法．采用该方法处理大肠癌和白血病数据集,筛选到基因数量较少并且分类准确度较高的特征基因子集．实验结果表明,文中的方法可以快速有效地筛选肿瘤特征基因,获得更好的分类效果．     

基于分子网络的癌症基因与非癌症基因的差异性分析

研究人类蛋白质相互作用网络中,癌症基因和非癌症基因在拓扑结构上的差异性,进而为潜在的癌症基因挖掘提供重要依据。首先利用多个数据库,构建一个较为全面的人类蛋白质相互作用(protein-protein interaction,PPI)网络,并搜集已知癌症基因;然后从PPI网络中抽取大量随机样本,并分别统计分析随机样本和已知癌症基因在节点度、节点介数和最大连接组件上的差异程度。得到了如下结果:(1)构建了一个较为全面的人类蛋白质相互作用网络;(2)获得乳腺癌已知癌症基因集;(3)已知癌症基因集和PPI网络随机样本在节点度、节点介数以及最大连接组件等拓扑结构属性上差异有显著性(P<2.2×10-16)。PPI网络的节点度、节点介数和最大连接组件等拓扑结构属性能够显著地区分癌症基因与非癌症相关基因,为新的未知癌症基因的发掘提供了重要考察依据。     

BA-ELISA方法检测乳腺癌患者血清p185蛋白

目的建立血清p185蛋白新的检测方法,评价血清p185蛋白在乳腺癌诊断中的意义.方法利用生物素化C-erbB-2单克隆抗体,建立血清p185蛋白BA-ELISA检测方法,并对乳腺癌、乳腺增生和正常对照血清进行p185蛋白检测,同时对组织进行p185免疫组化染色.结果乳腺癌血清p185蛋白与乳腺增生、正常对照相比差异显著(P<0.05),其中免疫组化阳性乳腺癌血清p185蛋白与乳腺增生、正常对照组相比有显著差异(P<0.01),而免疫组化阴性乳腺癌血清p185蛋白与其相比无显著差异(P>0.05);BA-ELISA方法检测血清p185蛋白的敏感度为43.3%,特异度为91.1%,准确度为74.4%.血清p185蛋白水平与乳腺组织p185蛋白表达高度相关(P<0.01).结论乳腺癌患者血清p185蛋白对乳腺癌具有诊断意义.血清p185蛋白与组织p185蛋白表达高度相关.     

用于手写签名识别的演化超网络

手写签名作为易被大众所接受的生物特征身份认证方式,已成为模式识别领域一个重要研究热点.针对现有手写签名存在易模仿难鉴定的问题,提出一种结合演化超网络模型的手写签名认证方法.为了平滑噪声,构造出可读性强的笔迹特征集,采用向量化和平滑采集点的方法对手写签名样本进行预处理,从而提取出位置和方向特征属性,采用演化超网络模型对签名进行学习和鉴定.为验证该方法的有效性,对20个签名用户分别采集了40个真实签名和20个伪造签名数据进行实验.实验结果表明,该方法对用户签名的误拒率(false rejection rate,FRR)为4.75％,误纳率(false acceptance rate,FAR)为3.75％,识别率(verification accuracy,VA)为95.75％.同时和其他传统的识别算法相比,具有更高的识别率.     

Serum microRNA-155 as a potential biomarker for breast cancer screening

MicroRNAs(miRs) have been shown to be differentially expressed in the serum of cancer patients and controls,and can thus be used as biomarkers for cancer screening.We detected the expression level of miR-155 in the serum of female breast cancer patients and healthy controls to investigate whether serum miR-155 could discriminate patients with early-stage breast cancer.Serum samples were collected from 20 female patients with newly diagnosed breast cancer and 10 healthy controls.Real-time quantitative PCR was used to detect the expression level of miR-155.The expression level of miR-155 was significantly increased in the serum of breast cancer patients compared with in the serum of normal controls.MiR-155 may be useful as a blood-based biomarker for breast cancer screening.     

人类乳腺癌的分子遗传学研究进展

乳腺癌发病机制非常复杂，其中涉及多种基因异常，包括易感基因、癌基因、抑癌基因等，对乳腺癌发生发展中这些基因异常的认识，是乳腺癌防治的关键。我们对近年来乳腺癌发病过程中分子遗传学的研究进展及乳腺癌相关基因的研究现状进行综述。     

缺乏核素示踪的早期乳腺癌前哨淋巴结活检方法临床研究

目的探讨应用亚甲蓝单示踪剂行缺乏核素示踪的早期乳腺癌前哨淋巴结活检(SLNB)的临床经验.方法收集行全乳切除手术或保乳手术的早期乳腺癌患者109例(0期12例,Ⅰ期27例,ⅡA期28例,ⅡB期10例)为研究对象,所有患者通过临床和影像学检查评估腋窝淋巴结阴性状态,对其行亚甲蓝示踪前哨淋巴结活检(SLNB)、非前哨淋巴结活检(Non-SLNB)和腋窝淋巴结清扫(ALND)的患者资料进行分析,所有前哨淋巴结(SLN)、非前哨淋巴结(Non-SLN)和腋窝淋巴结(ALN)均行病理学和免疫组化检查.结果 SLN检出率、假阴性率、准确性、阴性预测值分别为97.24%,6.9%,98.1%,97.5%.病理N分期的SLN检出率间比较差异具有统计学意义(P0.05).结论应用亚甲蓝单示踪法行SLNB能准确预测缺乏核素示踪的早期乳腺癌腋窝淋巴结状态,本研究入组的病例提示前哨淋巴结的检出率和准确率与乳腺癌的N分期相关.     

新基因BP1抗体制备及其在乳腺癌表达的初步观察

为了探讨新同源盒基因BP 1在乳腺癌的表达,运用生物信息学方法设计19肽,合成并偶联到大分子载体KLH上制成人工免疫原,制备兔抗BP 1多克隆抗体IgG.蛋白印迹方法检测BP 1在乳腺癌细胞系M CF 7、M DA-M B-231细胞均有表达:免疫组织化学结果显示,BP 1蛋白在乳腺癌的表达率显著高于癌旁组织,在雌激素受体阴性肿瘤的表达率高于雌激素受体阳性组。BP 1基因的异常表达参与了乳腺癌的发生,是一种新的乳腺癌分子标志物.     

Metallothionein gene cluster is split by chromosome 16 rearrangements in myelomonocytic leukaemia

The metallothioneins (MTs) are a family of proteins of low relative molecular mass which bind heavy-metal ions. MTs exist in several molecular forms (MT-I, MT-II) and are encoded by a multi-gene family containing at least 14 closely related genes and pseudogenes. These proteins function in the regulation of trace-metal metabolism, the storage of these ions in the liver, and as a protective mechanism against heavy-metal toxicity. Somatic cell hybridization has shown that most MT genes, including the functional MT genes (MT1A, MT1B, MT2A), lie on human chromosome 16. Using in situ hybridization, we have now localized the MT genes to band q22 of chromosome 16. This chromosomal band is also a breakpoint in two specific rearrangements, the inv(16)(p13q22) and t(16; 16)(p13;q22) rearrangements, found in a subgroup of patients with acute myelomonocytic leukaemia (AMML). Hybridization of a MT probe to malignant cells from two patients with an inv(16) showed labelled sites on both arms of the inverted chromosome, indicating that the breakpoint at 16q22 splits the MT gene cluster. Similar results were obtained when this probe was hybridized to metaphase cells from two patients with a t(16; 16). These results suggest that the MT genes or their regulatory regions may function as an 'activating' sequence for an as yet unidentified cellular gene located at 16p13.     

ACE基因多态性与异常体液型乳腺癌的易感性

 为探讨血管紧张素转换酶(ACE)基因插入/缺失(I/D)多态性与新疆汉族人群乳腺癌的相关性, 按维吾尔医将乳腺癌患者分为4 种体液型, 采用聚合酶链式反应(PCR)技术对新疆汉族139 例乳腺癌患者和72 例正常对照组ACE 基因I/D 多态性进行检测, 比较各组间等位基因和基因型频率分布的差异。结果显示, 异常黏质乳腺癌患者组II 基因型频率(P=0.018)和I 等位基因频率(P=0.004)都显著高于正常对照组;异常黏液质乳腺癌患者组I 等位基因频率显著高于异常黑胆质乳腺癌患者组(P=0.012)。由此得出, ACE 基因I 等位基因和II 基因型可能增加新疆汉族维吾尔医异常黏液质型乳腺癌的发病风险。     

基于改进LightGBM的室内指纹定位算法

针对室内定位算法在定位时所用时间较长和定位精度较低的问题,提出了一种基于改进LightGBM算法的室内定位算法。该算法首先针对指纹库中的数据进行预处理,通过KNN算法去除异常点和离群点,降低环境噪声干扰,提高数据可靠性。接下来,将样本集划分为训练集和测试集,使用LightGBM算法对进行建模。同时,使用遗传算法调整LightGBM算法中的参数,并根据适应度函数寻找最优参数,得到LightGBM+GA坐标预测模型。最后,根据优化后的参数建立预测模型实现坐标预测。实验结果表明,该算法在WiFi定位的精度上较与XGBoost算法提高0.1m,相较于GBDT算法提高0.19m,在定位时间上,LightGBM+GA算法比GBDT算法快5.10s,比XGBoost算法快5.97s,具有较好的实用性。     

乳腺癌相关转移基因的研究进展

目的综述肿瘤转移基因在乳腺癌中的研究进展。方法采用文献回顾的方法,对目前国内外肿瘤转移基因在乳腺癌中的研究状况加以分析与综述。结果肿瘤转移基因与乳腺癌的发生、转移及预后相关。结论对肿瘤转移基因的深入研究有助于进一步深化对乳腺癌生物学行为的认识,为肿瘤转移的分子诊断和基因治疗提供新的思路。     

基于随机矩阵理论分析乳腺癌基因网络

利用随机矩阵理论分析乳腺癌基因微阵列数据,得到乳腺癌基因共表达网络,找出乳腺癌基因共表达网络中重要的增殖模块和免疫模块,并预测基因PMSCL1与乳腺癌细胞的增殖、侵袭及迁移有关,基因CCAN2与乳腺癌细胞的有丝分裂有关,基因SCYA5与乳腺癌细胞的免疫应答有关,基因PRC1、RAB31、INHBA可作为乳腺癌的靶向基因.     

维医异常黑胆质证与肿瘤患者血浆脂肪酸含量变化的相关性

 从脂肪酸代谢水平阐释“异病同证”、“同证同理”等维医基础理论的科学性以及探讨不同肿瘤异常黑胆质证患者体内脂肪酸代谢变化。肿瘤病异常黑胆质证患者122 例,其中包括食管癌患者25例、肠癌患者20 例、肺癌患者33 例、乳腺癌患者20 例和胃癌患者24 例;另选35例健康志愿者为对照组;采用气相色谱法（gas chromatography,GC）对患者血浆进行10 种脂肪酸的定量检测;对患者与健康对照组之间的不同脂肪酸含量的差异性采用SPSS 16.0 软件进行独立样本的t 检验。结果显示,肉豆蔻酸在食管癌、肠癌、肺癌、乳腺癌和胃癌异常黑胆质证患者体内的含量均明显升高,这是本研究中所有肿瘤患者共同的特点;食管癌异常黒胆质证患者体内棕油酸、油酸、花生酸和DHA 含量明显升高,而亚油酸、花生四烯酸含量明显降低;肠癌异常黑胆质证患者体内棕榈酸和油酸含量明显升高;肺癌异常黑胆质证患者体内棕油酸、棕榈酸、油酸和花生酸含量明显升高,而亚油酸含量明显降低;乳腺癌异常黑胆质证患者体内棕油酸、棕榈酸、油酸、花生酸和EPA 含量明显升高,而硬脂酸和花生四烯酸含量明显降低;胃癌异常黑胆质证患者体内的棕油酸和DHA 含量明显升高,而亚油酸、EPA 和花生四烯酸含量明显降低。由此得出,不同病种肿瘤异常黑胆质证患者血浆脂肪酸代谢特点有共性,也有明显的差异性。     

TRIM24 links a non-canonical histone signature to breast cancer

Recognition of modified histone species by distinct structural domains within 'reader' proteins plays a critical role in the regulation of gene expression. Readers that simultaneously recognize histones with multiple marks allow transduction of complex chromatin modification patterns into specific biological outcomes. Here we report that chromatin regulator tripartite motif-containing 24 (TRIM24) functions in humans as a reader of dual histone marks by means of tandem plant homeodomain (PHD) and bromodomain (Bromo) regions. The three-dimensional structure of the PHD-Bromo region of TRIM24 revealed a single functional unit for combinatorial recognition of unmodified H3K4 (that is, histone H3 unmodified at lysine 4, H3K4me0) and acetylated H3K23 (histone H3 acetylated at lysine 23, H3K23ac) within the same histone tail. TRIM24 binds chromatin and oestrogen receptor to activate oestrogen-dependent genes associated with cellular proliferation and tumour development. Aberrant expression of TRIM24 negatively correlates with survival of breast cancer patients. The PHD-Bromo of TRIM24 provides a structural rationale for chromatin activation through a non-canonical histone signature, establishing a new route by which chromatin readers may influence cancer pathogenesis.