High-throughput mass spectrometry and bioinformatics analysis of breast cancer proteomic data

The project contains raw and result files from a comparative proteomic analysis of malignant [primary breast tumor (PT) and axillary metastatic lymph nodes (LN)] and non-tumor [contralateral (NCT) and adjacent breast (ANT)] tissues of patients diagnosed with invasive ductal carcinoma. A label-free mass spectrometry was conducted using nano-liquid chromatography coupled to electrospray ionization–mass spectrometry (LC-ESI-MS/MS) followed by functional annotation to reveal differentially expressed proteins and their predicted impacts on pathways and cellular functions in breast cancer. A total of 462 proteins was observed as differentially expressed (DEPs) among the groups of samples analyzed. Ingenuity Pathway Analysis software version 2.3 (QIAGEN Inc.) was employed to identify the most relevant signaling and metabolic pathways, diseases, biological functions and interaction networks affected by the deregulated proteins. Upstream regulator and biomarker analyses were also performed by IPA’s tools. Altogether, our findings revealed differential proteomic profiles that affected the associated and interconnected cancer signaling processes.

本数据集包含针对确诊浸润性导管癌患者的恶性与非肿瘤乳腺组织的比较蛋白质组学分析原始数据及结果文件，其中恶性组织涵盖原发性乳腺肿瘤（primary breast tumor, PT）与腋窝转移性淋巴结（axillary metastatic lymph nodes, LN），非肿瘤组织则包括对侧乳腺组织（contralateral breast tissue, NCT）与癌旁乳腺组织（adjacent breast tissue, ANT）。本研究采用纳升液相色谱耦联电喷雾电离串联质谱（nano-liquid chromatography coupled to electrospray ionization–mass spectrometry, LC-ESI-MS/MS）开展无标记质谱（label-free mass spectrometry）分析，并通过功能注释流程，明确乳腺癌中差异表达蛋白（differentially expressed proteins, DEPs）及其对通路与细胞功能的预测调控效应。本研究共在分析的样本组中鉴定出462种差异表达蛋白（DEPs）；采用QIAGEN公司发布的2.3版Ingenuity Pathway Analysis（IPA）软件，识别受失调蛋白影响的核心信号通路、代谢通路、疾病类型、生物学功能及相互作用网络，同时借助IPA工具完成上游调控因子与生物标志物分析。综上，本研究结果揭示了可影响相关且相互关联的癌症信号通路过程的差异蛋白质组学特征。