蛋白质组学在乳腺癌研究中应用的现状与展望

蛋白质组学是研究细胞内所有蛋白质及其动态变化规律的科学，随着人类基因组计划的完成，蛋白质组成为研究的热点。2-维凝胶电泳技术（2DE）、质谱的应用，以及生物信息学的引入，蛋白质组学的研究获得了飞速发展；新的蛋白质组学技术如激光捕获显微切割（LCM），串联质谱、二维液相分离-质谱鉴定等加速了乳腺癌研究的进展。鉴定出与乳腺癌癌变相关的蛋白质以及病情发展过程中蛋白质的变化对揭示乳腺癌变机制及早期诊断非常重要。通过综述文献，介绍蛋白质组学在乳腺癌肿瘤标志物的筛选与鉴定、肿瘤生物学行为判断与治疗中研究的进展。     

蛋白质组学在乳腺癌研究中的应用

蛋白质组学在肿瘤研究中的应用是近几年的研究热点,许多新方法也不断应用于蛋白质组学的研究中,包括组织芯片、蛋白质芯片、差异显示双相凝胶电泳以及最新的表面增强激光解析电离飞行时间质谱(SELDI-TOF-MS)蛋白质芯片技术,这些新方法在乳腺癌的早期诊断、预后评价以及信号转导等方面都取得一定进展。     

蛋白质组学在乳腺癌研究中的应用

蛋白质组学在肿瘤研究中的应用是近几年的研究热点,许多新方法也不断应用于蛋白质组学的研究中,包括组织芯片、蛋白质芯片、差异显示双相凝胶电泳以及最新的表面增强激光解析电离飞行时间质谱（SELDI-TOF-MS）蛋白质芯片技术,这些新方法在乳腺癌的早期诊断、预后评价以及信号转导等方面都取得一定进展。     

肿瘤蛋白质组学:过去、现在和将来

将蛋白质组学的技术方法应用到肿瘤生物学的研究中,产生了-门新学科--肿瘤蛋白质组学.它以寻找肿瘤标志物为目的,以蛋白质组学方法为手段,结合肿瘤分子机制的基础研究与肿瘤检测、诊断等临床研究.最终产出能应用于临床的肿瘤检测和治疗的蛋白质靶标.肿瘤蛋白质组学经历了表达谱、修饰谱到活性谱的进化过程,在不同的层面上揭示肿瘤可能的致病机制.本文概述了近年来在常见的恶性肿瘤中进行的肿瘤蛋白质组研究,应用各种蛋白质组技术方法,如二维凝胶电泳(two-dimensional gel eleetrophresis,2DE)、细胞培养稳定同位素标记技术(stable isotope labeling by amino acid in cell culture,SILAC)、基质辅助激光解析(matrix assisted laser desorption/ionization,MALDI)质谱等,找到了大量的蛋白质标志物.将来的挑战在于如何从理论上应用候选标志物解析肿瘤的分子机制,以及从实践上鉴定能真正应用于临床的标志物.     

蛋白质组技术在大肠癌生物标志物筛选中的应用

蛋白质组学是研究蛋白质的组成和动态变化的一门新兴学科,蛋白质组技术主要包括双向凝胶电泳(2-DE)、质谱(MS)、蛋白质芯片及蛋白质信息技术和数据库.目前,蛋白质组技术已成为研究肿瘤发生发展机制及寻找肿瘤标志物的重要工具.现就蛋白质组技术在分离、鉴定大肠癌生物标志物的应用进展作一介绍.     

基于质谱的高通量蛋白质组学技术探索肿瘤蛋白标志物的研究进展

蛋白质组学研究虽已开展20余年，早期研究基于Western blot技术，后来采用质谱技术鉴定蛋白质。但最初质谱技术的测序深度和鉴定蛋白质数量有限，使蛋白质组学研究遇到瓶颈。近年来，随着质谱技术的飞速发展，实现了高通量的蛋白质组学鉴定，从此蛋白质组学研究进入新时代。目前，高通量蛋白质组学技术在肿瘤领域的应用主要包括揭示肿瘤发生发展机制、寻找特异性生物标志物、阐明耐药性产生机制和发现新治疗靶点等。肿瘤的早期发现和诊断有助于及时地进行医疗干预，从而大幅提高患者的生存率及生存质量。国内外研究已发现了很多候选肿瘤生物标志物，但仅极少数应用于临床。因此，仅针对探索肿瘤特异性生物标志物，本文选取并分析高通量蛋白质组学技术应用较为广泛深入、且发病率/死亡率较高的肺癌、乳腺癌、结直肠癌和肝癌4种肿瘤类型。在不同肿瘤类型中筛选发表期刊影响因子较高、经扩大样本量验证或功能验证、证据较强的研究。介绍基于质谱的高通量蛋白质组学技术和常用标本类型，重点综述在上述4种高发癌症中，基于该技术发现的可能用于早期诊断、预测预后、靶向治疗的蛋白质标志物，旨在为实现肿瘤精准诊疗提供新的理论依据。      

蛋白质组技术在大肠癌生物标志物筛选中的应用

蛋白质组学是研究蛋白质的组成和动态变化的一门新兴学科，蛋白质组技术主要包括双向凝胶电泳(2-DE)、质谱(MS)、蛋白质芯片及蛋白质信息技术和数据库。目前，蛋白质组技术已成为研究肿瘤发生发展机制及寻找肿瘤标志物的重要工具。现就蛋白质组技术在分离、鉴定大肠癌生物标志物的应用进展作一介绍。     

蛋白质组学及其在肿瘤研究中的应用

蛋白质组学技术如样品制备、双向电泳(2-DE)、凝胶染色、质谱分析、生物信息学、差异凝胶电泳(DIGE)、同位素亲和标签(ICAT)、蛋白质芯片等的研究取得较大进展,蛋白质组学在探讨肿瘤发病机制及诊断等方面得到广泛应用.现就蛋白质组学相关技术研究进展及其在肿瘤研究中的应用作一综述.     

蛋白质组学及其在肿瘤研究中的应用

蛋白质组学技术如样品制备、双向电泳(2-DE)、凝胶染色、质谱分析、生物信息学、差异凝胶电泳(DIGE)、同位素亲和标签(ICAT)、蛋白质芯片等的研究取得较大进展，蛋白质组学在探讨肿瘤发病机制及诊断等方面得到广泛应用。现就蛋白质组学相关技术研究进展及其在肿瘤研究中的应用作一综述。     

表面增强激光解吸附-离子化飞行时间-质谱与乳腺癌临床研究

乳腺癌是危害女性健康的主要肿瘤,目前还没有特定的方法及生物标记物能够在早期发现及诊断。蛋白质组学通过对蛋白质动态的分析可以在疾病早期发现最微小的指标和征兆,从而发现各种疾病的特殊标志分子。表面增强激光解吸附-离子化飞行时间-质谱(SELDI-TOF-MS) 技术具有所需检测样品少、快速、敏感和准确的特点,显示了在基础研究及临床检验方面的优势。现综述其在乳腺癌临床研究及肿瘤标记物发现中的应用进展。     

Breast cancer classification by proteomic technologies: Current state of knowledge

Breast cancer is traditionally considered as a heterogeneous disease. Molecular profiling of breast cancer by gene expression studies has provided us an important tool to discriminate a number of subtypes. These breast cancer subtypes have been shown to be associated with clinical outcome and treatment response. In order to elucidate the functional consequences of altered gene expressions related to each breast cancer subtype, proteomic technologies can provide further insight by identifying quantitative differences at the protein level. In recent years, proteomic technologies have matured to an extent that they can provide proteome-wide expressions in different clinical materials. This technology can be applied for the identification of proteins or protein profiles to further refine breast cancer subtypes or for discovery of novel protein biomarkers pointing towards metastatic potential or therapy resistance in a specific subtype. In this review, we summarize the current state of knowledge of proteomic research on molecular breast cancer classification and discuss important aspects of the potential usefulness of proteomics for discovery of breast cancer-associated protein biomarkers in the clinic.     

Implications of Functional Proteomics in Breast Cancer

Breast cancer is one of the major public health problems of the Western world. Recent advances in genomics and gene expression‐profiling approaches have enriched our understanding of this heterogeneous disease. However, progress in functional proteomics in breast cancer research has been relatively slow. Allied with genomics, the functional proteomics approach will be important in improving diagnosis through better classification of breast cancer and in predicting prognosis and response to different therapies, including chemotherapy, hormonal therapy, and targeted therapy. In this review, we will present functional proteomic approaches with a focus on the recent clinical implications of utilizing the reverse‐phase protein array platform in breast cancer research.     

Contribution of oncoproteomics to cancer biomarker discovery

Oncoproteomics is the study of proteins and their interactions in a cancer cell by proteomic technologies. Proteomic research first came to the fore with the introduction of two-dimensional gel electrophoresis. At the turn of the century, proteomics has been increasingly applied to cancer research with the wide-spread introduction of mass spectrometry and proteinchip. There is an intense interest in applying proteomics to foster an improved understanding of cancer pathogenesis, develop new tumor biomarkers for diagnosis, and early detection using proteomic portrait of samples. Oncoproteomics has the potential to revolutionize clinical practice, including cancer diagnosis and screening based on proteomic platforms as a complement to histopathology, individualized selection of therapeutic combinations that target the entire cancer-specific protein network, real-time assessment of therapeutic efficacy and toxicity, and rational modulation of therapy based on changes in the cancer protein network associated with prognosis and drug resistance. Besides, oncoproteomics is also applied to the discovery of new therapeutic targets and to the study of drug effects. In pace with the successful completion of the Human Genome Project, the wave of proteomics has raised the curtain on the postgenome era. The study of oncoproteomics provides mankind with a better understanding of neoplasia. In this article, the discovery of cancer biomarkers in recent years is reviewed. The challenges ahead and perspectives of oncoproteomics for biomarkers development are also addressed. With a wealth of information that can be applied to a broad spectrum of biomarker research projects, this review serves as a reference for biomarker researchers, scientists working in proteomics and bioinformatics, oncologists, pharmaceutical scientists, biochemists, biologists, and chemists.     

Proteomic analysis of human breast cancer tissue with laser-capture microdissection and reverse-phase protein microarrays

Despite recent advances in breast cancer therapy, women with similar types of breast cancers may respond very differently to standard treatments. The emerging field of clinical proteomics has the potential to revolutionize breast cancer therapy. The ultimate goal of clinical proteomics is to characterize information flow through protein cascades for individual patients. After the protein networks have been elucidated, drug therapies may be specially designed for each patient. The following review describes the proteomic technologies of laser-capture microdissection (LCM) and reverse-phase protein arrays (RPPAs). These technologies allow scientists to analyze relative abundances of key cellular signaling proteins from pure cell populations. Cell survival and apoptotic protein pathways are currently being monitored with LCM and RPPAs at the National Institutes of Health, in phase II clinical trials of metastatic breast and ovarian cancers. Ultimately, proteomics will become an integral component of tracking and managing individualized breast cancer therapy.     

Proteomic portrait of human breast cancer progression identifies novel prognostic markers

Breast cancer is the second leading cause of cancer death for women in the United States. Of the different subtypes, estrogen receptor-negative (ER(-)) tumors, which are ErbB2+ or triple-negative, carry a relatively poor prognosis. In this study, we used system-wide analysis of breast cancer proteomes to identify proteins that are associated with the progression of ER(-) tumors. Our two-step approach included an initial deep analysis of cultured cells that were obtained from tumors of defined breast cancer stages, followed by a validation set using human breast tumors. Using high-resolution mass spectrometry and quantification by Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC), we identified 8,750 proteins and quantified 7,800 of them. A stage-specific signature was extracted and validated by mass spectrometry and immunohistochemistry on tissue microarrays. Overall, the proteomics signature reflected both a global loss of tissue architecture and a number of metabolic changes in the transformed cells. Proteomic analysis also identified high levels of IDH2 and CRABP2 and low levels of SEC14L2 to be prognostic markers for overall breast cancer survival. Together, our findings suggest that global proteomic analysis provides information about the protein changes specific to ER(-) breast tumor progression as well as important prognostic information.     

上皮细胞黏附分子表达与乳腺癌淋巴结转移的相关性

目的 探讨上皮细胞黏附分子(Ep-CAM)在乳腺癌中的表达及意义.方法 收集经病理学确诊的乳腺癌新鲜组织标本23例及配对的淋巴结转移灶.应用同位素标记的相对和绝对定量(iTRAQ)蛋白质组学技术筛选及鉴定乳腺癌原发灶和淋巴结转移灶的差异表达蛋白,在4例新鲜乳腺癌原发灶组织和配对淋巴结转移灶中进行Western blotting检测Ep-CAM的表达.采用免疫组织化学法检测252例乳腺病变标本中Ep-CAM的表达.结果 定量蛋白质组学检测结果显示乳腺癌原发灶和淋巴结转移灶存在差异表达蛋白,其中Ep-CAM在转移灶的表达高于原发灶,Western blotting显示Ep-CAM在转移灶的表达(1.46±0.22)高于原发灶(1.16±0.09),变化趋势与蛋白质组学结果一致.免疫组织化学检测结果显示,Ep-CAM在淋巴结转移灶中的阳性表达率(93.16％,109/117)显著高于无淋巴结转移的乳腺癌原发灶(72.73％,64/88),差异有统计学意义(x2=15.921,P=0.000);有淋巴结转移的乳腺癌原发灶Ep-CAM阳性表达率为72.65％(85/117),较配对淋巴结转移灶阳性表达率低,差异有统计学意义(P=0.001).结论 Ep-CAM在乳腺癌原发灶和淋巴结转移灶呈差异表达,该蛋白可能与乳腺癌淋巴结转移有关.     

转录组学与蛋白组学在三阴性乳腺癌中的预后研究进展

三阴性乳腺癌（triple-negative breast cancer,TNBC）系雌激素受体（ER）、孕激素受体（PR）、人表皮生长因子受体-2（HER-2）表达缺乏的一种异质性肿瘤,常表现出侵袭性强、易复发转移等特点。与其他亚型相比,TNBC因缺乏治疗靶点,除化疗外对内分泌治疗及靶向治疗均不敏感。因此,明确TNBC的预后特点及有效的治疗靶点有助于尽早实行个体化治疗。近年来各种研究技术的快速发展使研究者利用"组学"技术整合"大数据"与生物系统,以期解决上述难题。本文就转录组学与蛋白组学在TNBC中的预后研究进展进行综述。      

Breast carcinomas fulfill the Warburg hypothesis and provide metabolic markers of cancer prognosis

The aim of this study was to investigate selected proteomic markers of the metabolic phenotype of breast carcinomas as prognostic markers of cancer progression. For this purpose, a series of 101 breast carcinomas and 13 uninvolved breast samples were examined for quantitative differences in protein expression of mitochondrial and glycolytic markers. The beta-subunit of the mitochondrial H(+)-ATP synthase (beta-F1-ATPase) and heat shock protein 60 (Hsp60), and the glycolytic glyceraldehyde-3-phosphate dehydrogenase, pyruvate kinase and lactate dehydrogenase were identified by immunological techniques. Correlations of the expression level of the protein markers and of the ratios derived from them were established with the clinicopathological information of the tumors and the follow-up data of the patients. The metabolic proteome of breast cancer specimens revealed a pronounced shift towards an enhanced glycolytic phenotype concurrent with a profound alteration on the mitochondrial beta-F1-ATPase/Hsp60 ratio when compared with normal samples. Discriminant analysis using markers of the metabolic signature as predictor variables revealed a classification sensitivity of approximately 97%. Kaplan-Meier survival analysis showed that several of the proteomic variables significantly correlated with overall and disease-free survival of the patients. The expression level of beta-F1-ATPase per se allowed the identification of a subgroup of breast cancer patients with significantly worse prognosis. Multivariate Cox regression analysis indicated that tumor expression of beta-F1-ATPase is a significant marker independent from clinical variables to assess the prognosis of the patients. We conclude that the alteration of the mitochondrial and glycolytic proteomes is a hallmark feature of breast cancer further providing relevant markers to aid in the prognosis of breast cancer patients.     

Proteomics of breast cancer: outcomes and prospects

Breast cancer is a major public health problem. The identification of new markers to differentiate neoplastic from the normal cells, more thorough understanding of different stages of the pathology, as well as the definition of new therapeutic targets, are all of critical importance. With the completion of human genome sequencing and the introduction of mass spectrometry, combined with protein identification via advanced bioinformatics, proteomics has emerged as a valuable tool for the discovery of new molecular markers. New methods in functional proteomics have also been developed to study the intracellular signaling pathways that underline the development of breast cancer. As illustrated with the examples of fibroblast growth factor-2 and H19, an oncogenic, noncoding mRNA, proteomics have become a powerful approach for deciphering the complex signaling circuitry involved in tumor growth. Breast cancer proteomics have already identified proteins of potential clinical interest (such as the molecular chaperone 14-3-3 sigma) and technological innovations in large scale/high throughput analysis are now ushering in new prospects.