The Urinary Proteome Differs with the Presence and Type of Breast Cancer

Despite advancements in screening and treatment, the
incidence
of breast cancer (BC) and associated mortality are projected to increase.
Therefore, developing a companion diagnostic for BC remains important.
Herein, we explore the urinary proteome for biomarkers of BC: 130
urine samples from (1) newly diagnosed breast cancer (BC), n = 46, (2) benign breast disease (BBD), n = 36, (3) symptom control (SC), n = 30, and (4)
healthy control (HC), n = 18. The BC class included
preinvasive: ductal carcinoma in situ (DCIS) (n =
3), invasive ductal carcinoma (IDC) (n = 23), and
IDC accompanied by DCIS (n = 8) classes. Protein
profiling was performed using ThermoScientific ProteomeDiscoverer
and analyzed using MetaboAnalyst v6.0, DAVID, and STRING v12.0. Analyses
identified 346 significantly (p < 0.05) differentially
expressed proteins (DEP) across BC, BBD, SC, and HC. Multivariate
Receiver Operating Characteristic curves (five proteins) suggested
Area Under the Curve values of 0.985, 0.989, and 0.999 distinguishing
BC from BBD, SC, and HC, respectively. DEP elevated in BC included
beta-glucuronidase isoform 1, fibrinogen gamma chain, alpha-actinin-1,
peptidase inhibitor 16, cysteine-rich C-terminal protein 1 isoform
X1, guanine nucleotide-binding protein G(I)/G(S)/G(T) subunit beta-1,
vascular cell adhesion protein 1, ATP-dependent translocase ABCB1,
and tumor protein p63-regulated gene 1 isoform X1. BC types were differentiated
based on calpain-2 and cystatin-C expression (p <
0.05). Thus, BC has distinct urinary–protein profiles based
on clinical diagnosis, which could be used in real-time noninvasive
BC monitoring.

尽管在乳腺癌（breast cancer, BC）的筛查与治疗领域已取得诸多进展，但其发病率及相关死亡率仍预计将呈上升趋势。因此，开发乳腺癌配套诊断手段仍具有重要意义。本研究探索尿液蛋白质组以筛选乳腺癌生物标志物，共纳入130份尿液样本，分为四组：(1) 新确诊乳腺癌组（BC，n=46）、(2) 乳腺良性疾病（benign breast disease, BBD）组（n=36）、(3) 症状对照（symptom control, SC）组（n=30）以及(4) 健康对照（healthy control, HC）组（n=18）。乳腺癌组进一步细分为三类：导管原位癌（ductal carcinoma in situ, DCIS，n=3）、浸润性导管癌（invasive ductal carcinoma, IDC，n=23）以及伴导管原位癌的浸润性导管癌（n=8）。采用赛默飞世尔（ThermoScientific）ProteomeDiscoverer平台完成蛋白质谱分析，并通过MetaboAnalyst v6.0、DAVID及STRING v12.0工具进行数据分析。数据分析共筛选得到346个在四组样本中显著差异表达的蛋白质（differentially expressed proteins, DEP，p < 0.05）。基于5种差异蛋白构建的多变量受试者工作特征曲线（Receiver Operating Characteristic Curve, ROC）分析显示，其区分乳腺癌与BBD、SC、HC的曲线下面积（Area Under the Curve, AUC）分别为0.985、0.989及0.999。在乳腺癌中高表达的差异蛋白包括：β-葡萄糖醛酸苷酶亚型1、纤维蛋白原γ链、α-辅肌动蛋白1、肽酶抑制剂16、富含半胱氨酸C端蛋白1亚型X1、鸟苷酸结合蛋白G(I)/G(S)/G(T)亚基β-1、血管细胞黏附蛋白1、ATP依赖性转运蛋白ABCB1以及肿瘤蛋白p63调控基因1亚型X1。基于钙蛋白酶-2与胱抑素C的表达水平（p < 0.05），可实现不同乳腺癌亚型的区分。综上，乳腺癌患者存在特征性的尿液蛋白质组表达谱，该谱可用于实时、无创的乳腺癌监测。