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乳腺癌是女性常见癌症，死亡率很高。它是一种异质性疾病，在组织病理学上多样性程度很高，根据属性可以划分为luminal A、luminal B、HER2/Neu富集阳性、基底样（BBC）和正常乳腺样乳腺癌。在临床上根据ER、PR、和HER2的表达分为三阴型和非三阴型乳腺癌。不同的亚型具有不同的基因表达谱、以及不同治疗和预后。
Breast cancer is a frequently diagnosed carcinoma and is the leading cause of cancer death among females world- wide. Breast cancer is a heterogeneous disease with a high degree of diversity in histopathology, and can be classified into five major intrinsic subtypes: luminal A, luminal B, HER2/Neu-enriched, basal-like, and normal-like breast cancer. In clinic, breast cancer is also defined as triple-negative and non triple-negative breast cancer according to ER,PR,and HER2 expression. Different subtypes have different gene expression profiling, therapeutic scheme and prognosis.
三阴型乳腺癌(TNBC)是一种极为凶猛的乳腺癌亚型，很大一部分都属于基底样乳腺癌。一些基于GE的研究已经发现一些基因是治疗TNBC的潜在的药物靶点。比如通过kinome-wide检测，多个GE数据集的整合分析和体内体外实验证实MELK是一种导致基底样乳腺癌的致癌性激酶；通过多个微阵列数据集和相关实验也证实BCL11A是一种新的TNBC致癌基因。
Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer and the vast majority is basal-like phenotype. Several studies based on GE have identified several critical genes that may be potential druggable targets for the treatment of TNBC. MELK has been characterized as an oncogenic kinase essential for basal-like breast cancer (BBC) via a kinome-wide screening, integrative analysis with multiple GE datasets, and further in vitro and in vivo experiments. BCL11A has also been reported to be a novel TNBC oncogene by in silico analysis of several microarray datasets and subsequent experimental validations.
但是，目前已经开发的一些帮助研究人员利用乳腺癌基因表达谱的数据集和相关的工具都比较分散和独立，缺少一种能够结合多组学数据和常规分析工具的乳腺癌的整合平台。BCIP就是一个以基因为中心的整合多组学数据和分析工具的乳腺癌的数据分析和可视化平台。提供对被查询基因的差异表达分析、拷贝数变异分析、生存分析、共表达分析、miRNA调控分析和通路分析的可视化分析结果展示。（网址为http://omics.bmi.ac.cn/bcancer/ )
In order to help researchers use gene expression profiles, some databases and tools have been developed. However, integrative platforms combined with multi-omics data and customized analysis tools for breast cancer are still lacking. BCIP: a gene-centered platform for identifying potential regulatory genes in breast cancer, which provides differential expression analysis, copy number variation analysis, survival analysis, co-expression analysis, microRNA (miRNA) regulation analysis, and pathway analysis for query genes. (BCIP, http://omics.bmi.ac.cn/bcancer/).
BCIP在构建过程中，从GEO、EBI和TCGA的29个数据集选出了经过严格质控和标准化处理9,381个样本，同时也整合了3,035个样本的拷贝数变异信息、324,219 miRNA靶相互作用信息、286 KEGG通路信息、和乳腺/乳腺上皮细胞的组织特异性的基因功能网络的数据信息。BCIP一个最显著的特点是它提供给科研用户一个灵活方便的交互模式，就是用户可以通过选择一个或多个临床特征来实现对其所关心的乳腺癌亚型的分析。
We collected and obtained GE profile data on 9,381 samples from 29 datasets with strict quality control and uniform processing. We also incorporated CNV information on 3,035 samples, 324,219 miRNA-target interactions, 286 KEGG pathways, and data from tissue-specific gene functional networks of mammary gland and mammary epithelium.
The prominent characteristic of BCIP is that users can perform analysis by customizing subgroups with single or combined clinical features.
BCIP的使用：BCIP 门户网站包括四个模块：分析类型模块、样本亚型分析模块、数据集模块和结果展示模块。用户在使用的时候，首先在查询框输入基因名称，为了方便用户，支持基因的模糊查询。随后用户须从分析面板中提供的包括转录组分析、拷贝数变异分析、miRNA靶相互作用分析、通路分析和基因功能网络5大分析类别选择。接着用户可以在样品亚型面板中选择一个或多个临床数据来实现个性化亚型的定制。BCIP总共提供了15个临床特征，包括三阴/非三阴型、PAM50型、组织学分级、病理分期、转移状态、淋巴结转移、ER＋／－、PR＋／－、Her2+／－、TP53突变、是否绝绝经、年龄、肿瘤大小、疗效和预后。点击搜索后，在数据集面板中BCIP提供了所选的分析类型和相对应的样品亚型的所有可获得的数据集。选择相应数据集，在结果分析面板中提供相应的分析选项和样品亚型的图表的可视化展示。
BCIP provides a user- friendly interface consisting of four panels: Analysis Type, Sample Subgrouping, Dataset, and Result. A gene symbol can be input in the text field where we provide a fuzzy matching function. Users can then select any of 5 analytical categories in the Analysis Type panel, including Transcriptome Analysis, Copy Number Variation Analysis, MicroRNA-target Interaction Analysis, Pathway Analysis, and Gene Functional Network Analysis. After selecting analytical category, users can customize subgroups with single or combined clinical features of interest in the Sample Subgrouping panel. BCIP provides a total of 15 clinical features, including TNBC and non- TNBC subtypes, PAM50 subtypes, histological grades, pathologic stages, metastasis status, lymph node status, ER/PR/HER2 status, TP53 mutation status, menopause status, age, tumor size, therapy responses, and prognosis. The Dataset panel provides all of the available datasets for the selected options in the Analysis Type and Sample Subgrouping. Finally, the Result panel returns corresponding graphical and tabular presentation and analysis results after choosing from the above options.
BCIP的功能：BCIP可以辅助研究人员识别被查询的基因是否是潜在的乳腺癌的调控和驱动基因或生物标志物。
For a query gene, BCIP helps to demonstrate its potential as a biomarker or regulatory gene in breast cancer.
MELK目前被许多研究报道为具有基底样乳腺癌的治疗靶点的前景，我们就以MELK为例，看看BCIP都能做些什么。
Take MELK, a promising therapeutic target of BBC reported recently, as an example to demonstrate the utility and advantage of BCIP.
差异表达分析表明在所包含的数据集中，肿瘤组织相比于周围正常组织，MELK的表达量要高出许多；PAM50型乳腺癌中的基底样乳腺癌，MELK的表达量最高。
Differential expression analysis shows that MELK has a much higher expression level in tumors than adjacent normal tissues across all of the available datasets and has the highest expression level in basal-like subtype among PAM50 subtypes across all of the datasets.
亚型被个性化选择为肿瘤分级后，我们发现，MELK的表达量高低与肿瘤的组织学分级呈显著性正相关。
When subgroups are customized with tumor grades, we found that higher MELK expression level was significantly associated with higher histological grades among all of the datasets.
生存分析显示MELK的过量表达与较差预后相关。这些数据都表明MELK与BBC相关。
Survival analysis shows that overexpression of MELK is strongly correlated with poor prognosis. These in silico results indicate that MELK might play roles in BBC.
共表达基因分析可以进一步的分析MELK影响基底样乳腺癌的机理。在基底样乳腺癌的METABRIC数据集中，MELK与包括CDCA5,TPX2和CEP55在内的78个基因共表达。一些研究已经阐述了TPX2和CEP55是参与乳腺癌转移、侵袭、增殖和扩散的关键分子。CDCA5也被报道在肺癌中起关键作用，并可作为口腔鳞细胞癌的治疗靶点。这些结果都可以作为挖掘MELK在乳腺癌中的潜在功能和机制的有用线索。
To provide clues of the possible molecular mechanism of MELK in BBC, we further analyzed the co-expression genes and regulatory miRNAs of MELK. In basal-like subtype of the METABRIC dataset, MELK was significantly co-expressed with 78 genes with PCC > 0.6, including CDCA5, TPX2, and CEP55. Several studies have demonstrated that TPX2 and CEP55 are critical molecules for breast cancer migration, invasion, cell proliferation, and metastasis. CDCA5 has been reported to play a crucial role in human lung carcinogenesis and has the potential of being a therapeutic target for oral squamous cell carcinoma. These results may be valuable clues for the investigation of potential function and molecular mechanism of MELK in breast cancer.
miRNA靶相互作用分析发现hsa-miR-193b-3p and hsa-miR-372-5p与miRNA靶相互作用有关。有研究证实miR-193b抑制细胞增殖并且调控黑色素瘤细胞周期D1蛋白；miR-372 在抑制许多种类型的肿瘤增殖、侵袭和转移。这些结果都可以作为预测在乳腺癌中MELK可能是被miR-193b-3p 和 miR-372-5p 调控的依据。
Additionally, we found miRNAs targeting MELK, including hsa-miR-193b-3p and hsa-miR-372-5p. Previous studies have shown that miR-193b represses cell proliferation and regulates cyclin D1 in melanoma, and miR-372 suppresses tumor proliferation, invasion, and migration in various tumor types. This result indicates that MELK might be regulated by miR-193b-3p and miR-372-5p in breast cancer.
总之，作为一个方便高效的平台，BCIP可以辅助识别乳腺癌潜在生物标志物和相应基因的潜在功能和机制，并为广大研究人员提供后续实验和医学分析的依据。目前BCIP可以通过http://omics.bmi.ac.cn/bcancer/ 免费访问。
BCIP serves as a convenient and efficient platform to identify biomarkers, characterize potential functions and mechanisms of genes in breast cancer. Researchers can find clues for subsequent experiments and clinical analysis.
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