不同ＥＲ状态乳腺癌组织Ｂｃｌ-２的表达及其临床意义

目的　分析不同ＥＲ状态的乳腺癌组织中Ｂｃｌ-２表达情况及其意义。方法　采用免疫组织化学方法检测１６０例浸润性乳腺癌组织中ＥＲ和Ｂｃｌ-２的表达情况,依据ＥＲ状态分为ＥＲ阳性和阴性组,分别比较Ｂｃｌ-２表达与临床病理特征的关系。结果　１６０例乳腺癌组织中ＥＲ阳性为７０例（４３.８％）,Ｂｃｌ-２阳性７４例（４６.３％）,Ｂｃｌ-２与ＥＲ表达呈正相关。ＥＲ阳性组中Ｂｃｌ-２表达与淋巴结转移少、组织学分级低及临床分期早显著相关,ＥＲ阴性组中Ｂｃｌ-２表达与上述临床病理特征均无关。结论　乳腺癌组织中存在Ｂｃｌ-２表达,其中ＥＲ阳性乳腺癌组织中Ｂｃｌ-２表达与临床病理特征有相关性。     

乳腺癌ER、PR与DAKO—M1关系的初步探讨

应用亲和酶标组化标记法和免疫组化ＡＢＣ法，测定１０６例乳腺癌组织中ＥＲ、ＰＲ和ＤＡＫＯ—Ｍ１水平。其阳性率分别为８３％、８１．１％和８０．２％。在８８例ＥＲ阴性乳腺癌中，ＰＲ阳性７６例，而１８例ＥＲ阴性乳腺癌中，ＰＲ阳性１０例。７９．２％乳腺癌ＥＲ和ＰＲ表达一致（ｐ＜０．０５）。在９８例ＥＲ和／或ＰＲ阳性乳腺癌中，８４例ＤＡＫＯ—Ｍ１阳性；而８例ＥＲ和ＰＲ阴性乳腺癌中，７例ＤＡＫＯ—Ｍ１阴性。８５．７％乳腺癌ＥＲ和／或ＰＲ和ＤＡＫＯ—Ｍ１表达一致（Ｐ＜０．０５）。ＥＲ、ＰＲ和ＤＡＫＯ—Ｍ１阳性率均随组织学分级增高而减低，其在癌组织学分级表达中均有显著意义（ｐ＜０．０１—０．００１）。结果提示，乳腺癌ＥＲ、ＰＲ和ＤＡＫＯ—Ｍ１水平，均可作为对乳腺癌患者治疗方案决策、判断其分化程度和预测预后的参考指标。     

100例乳腺癌雌激素和孕激素受体的测定和分析

目前临床医生根据对乳腺癌雌激素受体（ＥＲ）和孕激素受体（ＰＲ）测定来指导治疗方案。Ｗｉｔｌｉｆ综合文献报道ＥＲ和ＰＲ阳性时进行内分泌治疗有效率达７８％，而ＥＲ和ＰＲ阴性时仅１０％，有明显的差异性［１］。故对乳腺癌组织中ＥＲ和ＰＲ测定，有助于治疗方案的...     

三阴性乳腺癌的临床特点和生存分析

目的　回顾分析经免疫组化检测ＥＲ－、ＰＲ－和ＨＥＲ-２－乳腺癌（三阴性乳腺癌）的临床资料,探讨其临床特点和生存情况。方法　回顾分析我院２００１年１月～２００４年３月诊治的４１例三阴性乳腺癌患者的发病年龄、肿瘤大小、淋巴结转移情况、术后辅助治疗、肿瘤复发及生存情况。结果　４１例三阴性乳腺癌病例中,中位发病年龄４９岁,４３.６％的患者首诊时伴有淋巴结转移;可随访的３５例病例中,２７例接受了术后辅助治疗。中位随访时间５年,１、３、５年生存率分别为１００.０％、７４.０％和５７.０％,２０例出现了肿瘤复发和转移,内脏转移４０.０％,软组织转移２０.０％,骨转移６.０％。结论　三阴性乳腺癌首诊时淋巴结转移率高,复发后内脏及软组织转移率高,生存时间较短。     

维甲酸抑制乳腺癌细胞生长与维甲酸受体α相关性研究

研究维甲酸抑制乳腺癌细胞生长的作用卫ＥＲ关系的同时研究维甲酸作用与其自身受体之间的关系。细胞生长抑制实验，Ｎｏｒｔｈｅｒｎ杂交分析法及基因转染技术。发现ＥＲ阳性的乳腺癌细胞的生长能被维甲酸抑制，而ＥＲ阴性的乳腺癌细胞生长不被甲酸抑制而且被维甲酸抑制的ＥＲ阳性的乳腺癌细胞中维甲酸受体αｍＲＮＡ表达明显高天ＥＲ阴性的细胞。     

维甲酸抑制雌激素受体阳性乳腺癌细胞生长机制的研究

目的探讨雌激素受体的表达对维甲酸抑制乳腺癌细胞生长的影响和ＲＡＲα表达的变化。方法雌激素受体阴性的乳腺癌细胞株ＭＤＡ－ＭＢ－２３１细胞,采用分子生物学质粒转染技术,将ＥＲ阴性的乳腺癌细胞ＭＤＡ－ＭＤ－２３１转染成ＥＲ阳性细胞。结果发现ＥＲ转染后的细胞不仅ＲＡＲα的基础表达升高,而且ＲＡ能明显抑制该细胞的生长。同时还发现,无论是已确立的雌激素受体阳性的乳腺癌细胞株,还是雌激素受体转染后的细胞,雌激素都能明显刺激ＲＡＲα的表达。结论雌激素通过ＥＲ上调ＲＡＲα量的表达,在维甲酸对乳腺癌细胞生长的抑制中起着很重要的作用。     

１３６例三阴性乳腺癌的临床分析

目的　通过回顾分析三阴性乳腺癌病例资料,探讨三阴性乳腺癌的临床及预后情况。方法　收集ＥＲ、ＰＲ和ＨＥＲ-２均阴性的１３６例乳腺癌患者的临床资料,行Ｃｏｘ多元回归分析。结果　１３６例患者确诊时,中位年龄４７岁;有乳腺癌家族史者９例（６.６％）,浸润性导管癌１２４例（９１.２％）,Ｔ３分期以上２３例（１６.９％）,区域淋巴结阳性者６０例（４４.１％）。中位随访时间５９个月（３１～８６个月）,复发及转移患者４１例（３０１％）,死亡２４例;５年无病生存率（ＤＦＳ）和总生存率（ＯＳ）分别为６９.６％和８４.１％;术后复发转移,以肺内转移的发生率最高,其次是肝脏。术后中位复发时间为２６个月（５～６２个月）,复发后３年生存率为３５.２％。单因素分析显示,肿瘤大小、淋巴结转移数目、病理分期、辅助化疗周期数等与三阴性乳腺癌的预后有关。Ｃｏｘ多元回归分析显示,淋巴结转移数目是预测三阴性乳腺癌预后的独立因素。结论　三阴性乳腺癌具有发病年龄较轻、确诊时淋巴结转移率较高、临床分期较晚、术后早期复发率高、复发后生存时间短等特征,淋巴结转移数目为三阴性乳腺癌预后的独立指标。     

大剂量甲孕酮对进展期乳腺癌的治疗观察

我们应用大剂量甲孕酮（ＭＰＡ）治疗晚期乳腺癌病人１２例,效果满意,总结报告如下。１　临床资料１．１　一般资料　１２例病人均为女性,年龄３２～５７岁,平均４２岁,其中乳腺癌肺转移７例（其中４例伴癌性胸腔积液）,骨转移３例,局部复发２例。雌激素受体（ＥＲ）及孕激素受体（ＰＲ）均阳性６例,ＥＲ阳性、ＰＲ阴性４例,ＥＲ阴性、ＰＲ阳性１例,ＥＲ和ＰＲ均阴性１例。１．２　治疗方法　１２例病人在接受ＭＰＡ治疗前均应用ＴＡＭ及化疗３～２８个月,经观察效果不满意,改用ＭＰＡ５００ｍｇ,每日３次,连用３０天,改为Ｍ…     

Ｋｉ-６７、ＥＧＦＲ、ＨＥＲ-２和ｐ５３在乳腺癌中的表达及其相关性

目的　分析Ｋｉ-６７、ＥＧＦＲ、ＨＥＲ-２、ｐ５３在乳腺癌组织中的表达,并探讨其与乳腺癌临床病理特征之间的相关性。方法　用免疫组化法检测１３８例乳腺癌患者病理组织中Ｋｉ-６７、ＥＧＦＲ、ＨＥＲ-２和ｐ５３蛋白的表达,并结合临床病理特征进行相关性分析。结果　Ｋｉ-６７、ＥＧＦＲ、ＨＥＲ ２和ｐ５３在乳腺癌组织中的表达率依次为９１.３０％、１７.３９％、６２.３２％和２３.１９％,不同年龄组其表达均无统计学差异（Ｐ＞０.０５）。Ｋｉ-６７的表达与组织学分级、病理类型、肿块大小、淋巴结是否转移及分期显著相关（Ｐ＜０.０５）;ＥＧＦＲ表达与病理类型和ＥＲ状态显著相关（Ｐ＜０.０５）;ＨＥＲ ２表达与病理类型、组织学分级、淋巴结转移、远处转移及分期无相关性（Ｐ＞０.０５）;而ｐ５３表达与组织学分级、ＥＲ和ＰＲ状态呈显著相关（Ｐ＜０.０５）。ＥＲ和ＰＲ呈正相关;ＥＧＦＲ、ＨＥＲ-２、ｐ５３与ＥＲ均为负相关;ＨＥＲ-２和ＰＲ呈负相关;Ｋｉ-６７与ＥＧＦＲ、ＨＥＲ-２、ｐ５３、ＥＲ及ＰＲ之间均无相关性;ｐ５３与ＥＧＦＲ呈正相关;ＥＧＦＲ与ＨＥＲ-２呈负相关。结论　联合检测乳腺癌组织中ＥＧＦＲ、Ｋｉ-６７、ＨＥＲ-２和ｐ５３蛋白的表达能更清楚地了解乳腺癌的生物学行为,对乳腺癌的诊断、指导治疗及评价预后有重要的临床意义。     

表皮生长因子受体表达与乳腺癌激素受体水平和预后的关系

应用免疫组化ＡＢＣ方法研究７５例乳腺癌冰冻组织表皮生长因子受体（ＥＧＦＲ）的表达，结合临床资料和ＥＲ、ＰＲ测定结果进行分析，探讨ＥＧＦＲ表达与乳腺癌预后的关系。结果表明，ＥＧＦＲ阳性３０例（４０％），ＥＧＦＲ表达与肿瘤大小、腋淋巴结状况，临床分期和年龄无关，与ＥＲ、ＰＲ存在着显著的负相关（Ｐ＜０．００５）。全组中位随诊时间为６０个月，ＥＧＦＲ阳性组术后总生存率明显低于阴性组（Ｐ＜０．００１）。在无腋淋巴结转移的病例中，ＥＧＦＲ阳性组和阴性组术后生存情况也有显著差异（Ｐ＜０．０１），提示ＥＧＦＲ表达与乳腺癌不良的预后有关。调整分析乳腺癌有关的预后因素，各组病例中均以ＥＧＦＲ表达阳性组的预后为差，说明ＥＧＦＲ对乳腺癌预后具有独立的作用，不受其他因素的影响。经Ｃｏｘ模型多因素分析显示，ＥＧＦＲ和腋淋巴结受累与否是对乳腺癌术后生存情况有显著性影响的两个因素。     

新疆地区1006例不同分子分型乳腺癌的临床病理特征及预后

目的 探讨新疆地区不同分子分型乳腺癌的临床病理特征和预后。方法 收集2008年1月至2010年12月新疆医科大学附属肿瘤医院行手术治疗的1006例女性乳腺癌患者的临床病历资料,根据雌激素受体（ER）、孕激素受体（PR）、人表皮生长因子受体-2（HER-2）和Ki-67的状态,将乳腺癌分为：Luminal A型、Luminal B型、HER-2过表达型及Basal like型,对比分析不同分子分型乳腺癌患者的临床病理特征、复发转移及预后情况。结果 Luminal A型551例（54.8％）,Luminal B型182例（18.1％）,HER-2过表达型77例（7.7％）,Basal-like型196例（19.4％）。不同分子分型乳腺癌在肿块大小、淋巴结转移数目、临床分期、组织学分级、民族及内分泌治疗的差异均具有统计学意义（P＜0.05）。获得随访的971例患者中,HER-2过表达型的局部复发率（12.3％）及远处转移率（27.4％）均高于其他分型（P＜0.05）。Luminal A型、Luminal B型、HER-2过表达型及Basal-like型6年无病生存率分别为86.8％、75.8％、58.9％、79.1％（P＜0.05）;6年生存率分别为92.1％、83.1％、67.1％、88.0％（P＜0.05）。Cox多因素回归分析显示,淋巴结转移数目、组织学分级、内分泌治疗及分子分型是影响新疆地区乳腺癌总生存时间（OS）和无病生存时间（DFS）的独立因素,民族亦是影响该地区乳腺癌患者DFS的独立因素。结论 新疆地区Luminal A型乳腺癌最常见,预后最好,HER-2过表达型比例最低,预后最差。乳腺癌预后与淋巴结转移数目、组织学分级、内分泌治疗及分子分型有关,民族是影响乳腺癌患者DFS的重要因素。     

Basal-like subtype of breast cancer: a review of its unique characteristics and their clinical significance

Subtyping of breast cancers by means of DNA microarray analyses has given rise to the new concept of the basal-like subtype; this subtype is in effect the equivalent of so-called “triple-negative” breast cancer. Basal-like breast cancer has aggressive characteristics, such as high histological grade, mutation of the TP53 gene, and negative hormone receptors. It tends to occur in relatively young women and is highly correlated with suppression of BRCA1 function. The EGFR gene is often overexpressed in this subtype. Here, research carried out in the last few years into the basal-like subtype of breast cancer will be reviewed.     

Mammography and ultrasound features of triple-negative breast cancer

Background   

Triple-negative breast cancer is characterized as a cancer with a high malignancy potential and a poor prognosis. Therefore, early detection of this subtype of breast cancer is vital. In this paper, we describe the mammography and ultrasound findings of triple-negative breast cancer in a large population and investigate the specific features of this subtype.     

Prognosis of metastatic breast cancer subtypes: the hormone receptor/HER2-positive subtype is associated with the most favorable outcome

Contrary to the situation in early breast cancer, little is known about the prognostic relevance of the hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) in metastatic breast cancer. The objectives of this study were to present survival estimates and to determine the prognostic impact of breast cancer subtypes based on HR and HER2 status in a recent cohort of metastatic breast cancer patients, which is representative of current clinical practice. Patients diagnosed with metastatic breast cancer between 2007 and 2009 were included. Information regarding patient and tumor characteristics and treatment was collected. Patients were categorized in four subtypes based on the HR and HER2 status of the primary tumor: HR positive (+)/HER2 negative (?), HR+/HER2+, HR?/HER2+ and triple negative (TN). Survival was estimated using the Kaplan–Meier method. Cox proportional hazards model was used to determine the prognostic impact of breast cancer subtype, adjusted for possible confounders. Median follow-up was 21.8 months for the 815 metastatic breast cancer patients included; 66 % of patients had the HR+/HER2? subtype, 8 % the HR?/HER2+ subtype, 15 % the TN subtype and 11 % the HR+/HER2+ subtype. The longest survival was observed for the HR+/HER2+ subtype (median 34.4 months), compared to 24.8 months for the HR+/HER2? subtype, 19.8 months for the HR?/HER2+ subtype and 8.8 months for the TN subtype (P < 0.0001). In the multivariate analysis, subtype was an independent prognostic factor, as were initial site of metastases and metastatic-free interval. The HR+/HER2+ subtype was associated with the longest survival after diagnosis of distant metastases.     

Feature extraction via composite scoring and voting in breast cancer

Identification and characterization of tumor subtypes using gene expression profiles of triple negative breast cancer patients. Microarray data of four breast cancer studies were pooled and evaluated. Molecular subtype classification was performed using random forest and a novel algorithm for feature extraction via composite scoring and voting. Biological and clinical properties were evaluated via GSEA, functional annotation clustering and clinical endpoint analysis. The subtype signatures are highly predictive for distant metastasis free survival of tamoxifen-treated patients. Consensus clustering and the novel algorithm proposed three triple negative subtypes. One subtype shows low E2F4 gene expression and is predictive for survival of ER negative breast cancer patients. The other two subtypes share commonalities with luminal B tumors. Classification of breast cancer expression profiles may reveal novel tumor subtypes, possessing clinical impact. Furthermore, subtype characterizing gene signatures might hold potential for novel strategies in cancer therapy.     

可手术的不同分子亚型乳腺癌的临床特征和生存分析

目的 分析Luminal A型、Luminal B型、人表皮生长因子受体2(HER-2)型和Basal-like型4种乳腺癌亚型的临床特征和生存状况,探讨乳腺癌个体化综合治疗的理论基础.方法 回顾性分析经手术治疗、资料完整、免疫组化方法能明确判定受体状况的乳腺癌患者408例,比较各型乳腺癌的临床特征、复发转移及生存情况.结果 Luminal A型248例,占60.8%;Luminal B型32例,占7.8%;HER-2型51例,占12.5%;Basal-like型77例,占18.9%.HER-2型乳腺癌≤45岁者明显少于其他亚型,Basal-like型乳腺痛发生腋窝淋巴结转移者的比例低于其他亚型,Luminal B型晚期病例多于其他亚型,而HER-2型早期病例多于其他亚型.获得随访的243例患者中,复发或转移58例,死亡51例.Luminal A型的复发转移率明显低于Luminal B型和Basal-like型(均P<0.05).Luminal A型、Luminal B型、HER-2型和Basal-like型的5年生存率分别为89.83%、86.15%、86.70%和79.85%,Luminal A型高于Basal-like型(P=0.008).Luminal A型、Luminal B型、HER-2型和Basal-like型的5年无病生存率分别为83.52%、68.88%、75.83%和71.66%,Luminal A型高于Luminal B型和Basal-like型(P=0.0481和P=0.0306).结论 中国人各亚型乳腺癌的构成比与欧美国家接近,Luminal A型是最常见的乳腺癌亚型,预后较好,Basal-like型和Luminal B型所占比例较小,但预后较差.     

云南省乳腺癌分子分型与临床病理特点分析

目的：了解云南省乳腺癌患者的分子分型与临床病理特点.方法：收集2012年1月-2012年12月云南省肿瘤医院乳腺病科所收治的经根治性手术后病理确诊为原发性乳腺癌的初诊患者587例,统计分析分子分型与患者年龄、民族、病理类型、病灶大小、淋巴结分期、病理分期、p53等的相关性.结果：不同民族、病灶大小、淋巴结分期、p53表达与分子分型之间差异无统计学意义.不同年龄段与分子分型之间差异有统计学意义,P=0.033.不同病理类型与分子分型之间差异有统计学意义,P=0.022.不同病理分期与分子分型之间差异有统计学意义,P=0.004.结论：云南省乳腺癌不同年龄段、不同病理分期的分子分型存在差异.     

Constitutive activation of nuclear factor-κB is preferentially involved in the proliferation of basal-like subtype breast cancer cell lines

Constitutive nuclear factor (NF)-κB activation is thought to be involved in survival, invasion, and metastasis in various types of cancers. However, neither the subtypes of breast cancer cells with constitutive NF-κB activation nor the molecular mechanisms leading to its constitutive activation have been clearly defined. Here, we quantitatively analyzed basal NF-κB activity in 35 human breast cancer cell lines and found that most of the cell lines with high constitutive NF-κB activation were categorized in the estrogen receptor negative, progesterone receptor negative, ERBB2 negative basal-like subtype, which is the most malignant form of breast cancer. Inhibition of constitutive NF-κB activation by expression of IκBα super-repressor reduced proliferation of the basal-like subtype cell lines. Expression levels of mRNA encoding NF-κB-inducing kinase (NIK) were elevated in several breast cancer cell lines, and RNA interference-mediated knockdown of NIK reduced NF-κB activation in a subset of the basal-like subtype cell lines with upregulated NIK expression. Taken together, these results suggest that constitutive NF-κB activation, partially dependent on NIK, is preferentially involved in proliferation of basal-like subtype breast cancer cells and may be a useful therapeutic target for this subtype of cancer. ( Cancer Sci 2009; 100: 1668–1674)     

MicroRNA expression profiling of male breast cancer

Introduction

Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation.

Methods

We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies.

Results

We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient.

Conclusions

Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.     

An integration of complementary strategies for gene-expression analysis to reveal novel therapeutic opportunities for breast cancer

Introduction

Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation.

Methods

We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies.

Results

We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient.

Conclusions

Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.