Ruhen Olivia, Qu Xinyu, Jamaluddin M Fairuz B, Salomon Carlos, Gandhi Aesha, Millward Michael, Nixon Brett, Dun Matthew D, Meehan Katie
Sarcoma Molecular Pathology Team, Institute of Cancer Research, Sutton SW7 3RP, UK.
Department of Otorhinolaryngology, Head and Neck Surgery, Chinese University of Hong Kong, Hong Kong.
Membranes (Basel). 2021 Nov 16;11(11):880. doi: 10.3390/membranes11110880.
Breast cancer is the leading cause of cancer death in women. The majority of these deaths are due to disease metastasis, in which cancer cells disseminate to multiple organs and disrupt vital physiological functions. It is widely accepted that breast cancer cells secrete extracellular vesicles (EVs), which contain dynamic molecular cargo that act as versatile mediators of intercellular communication. Therefore, Evs. secreted by breast cancer cells could be involved in the development of metastatic disease and resistance to treatment. Moreover, changes in EV cargo could reflect the effects of therapy on their parent tumor cells. The aim of this feasibility study was to quantitatively profile the proteomes of Evs. isolated from blood samples taken from treatment sensitive and resistant metastatic breast cancer patients to identify proteins associated with responses. Three serial blood samples were collected from three patients with metastatic breast cancer receiving systemic therapy including a responder, a non-responder, and a mixed-responder. Evs. were isolated from plasma using size exclusion chromatography and their protein cargo was prepared for tandem mass tag (TMT)-labelling and quantitative analyses using two-dimensional high-performance liquid chromatography followed by tandem mass spectrometry. After filtering, we quantitatively identified 286 proteins with high confidence using a q value of 0.05. Of these, 149 were classified as EV associated candidate proteins and 137 as classical, high abundant plasma proteins. After comparing EV protein abundance between the responder and non-responder, we identified 35 proteins with unique de-regulated abundance patterns that was conserved at multiple time points. We propose that this proof-of-concept approach can be used to identify proteins which have potential as predictors of metastatic breast cancer response to treatment.
乳腺癌是女性癌症死亡的主要原因。这些死亡中的大多数是由于疾病转移,即癌细胞扩散到多个器官并破坏重要的生理功能。人们普遍认为,乳腺癌细胞会分泌细胞外囊泡(EVs),其包含动态分子货物,作为细胞间通讯的多功能介质。因此,乳腺癌细胞分泌的EVs可能参与转移性疾病的发展和对治疗的抗性。此外,EV货物的变化可以反映治疗对其亲本肿瘤细胞的影响。这项可行性研究的目的是定量分析从治疗敏感和耐药的转移性乳腺癌患者采集的血液样本中分离出的EVs的蛋白质组,以鉴定与反应相关的蛋白质。从三名接受全身治疗的转移性乳腺癌患者(包括一名反应者、一名无反应者和一名混合反应者)采集了三份连续的血液样本。使用尺寸排阻色谱法从血浆中分离出EVs,并对其蛋白质货物进行串联质量标签(TMT)标记,并使用二维高效液相色谱法随后进行串联质谱分析进行定量分析。经过筛选,我们使用q值0.05定量鉴定了286种高可信度蛋白质。其中,149种被归类为与EV相关的候选蛋白质,137种为经典的、高丰度的血浆蛋白质。在比较反应者和无反应者之间的EV蛋白质丰度后,我们鉴定出35种具有独特的失调丰度模式的蛋白质,这些模式在多个时间点是保守的。我们认为,这种概念验证方法可用于鉴定具有作为转移性乳腺癌治疗反应预测指标潜力的蛋白质。