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Monitoring the progression of metastatic breast cancer on nanoporous silica chips

机译:在纳米多孔二氧化硅芯片上监测转移性乳腺癌的进展

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摘要

Breast cancer accounted for 15 per cent of total cancer deaths in female patients in 2010. Although significant progress has been made in treating early-stage breast cancer patients, there is still no effective therapy targeting late-stage metastatic breast cancers except for the conventional chemotherapy interventions. Until effective therapy for later-stage cancers emerges, the identification of biomarkers for the early detection of tumour metastasis continues to hold the key to successful management of breast cancer therapy. Our study concentrated on the low molecular weight (LMW) region of the serum protein and the information it contains for identifying biomarkers that could reflect the ongoing physiological state of all tissues. Owing to technical difficulties in harvesting LMW species, studying these proteins/peptides has been challenging until now. In our study, we have recently developed nanoporous chip-based technologies to separate small proteins/peptides from the large proteins in serum. We used nanoporous silica chips, with a highly periodic nanostructure and uniform pore size distribution, to isolate LMW proteins and peptides from the serum of nude mice with MDA-MB-231 human breast cancer lung metastasis. By matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and biostatistical analysis, we were able to identify protein signatures unique to different stages of cancer development. The approach and results reported in this study possess a significant potential for the discovery of proteomic biomarkers that may significantly enhance personalized medicine targeted at metastatic breast cancer.
机译:乳腺癌占2010年女性患者癌症总死亡人数的15%。尽管在治疗早期乳腺癌患者方面取得了重大进展,但除常规化疗外,仍没有针对晚期转移性乳腺癌的有效疗法干预。在出现针对晚期癌症的有效疗法之前,用于早期发现肿瘤转移的生物标记物的识别仍然是成功实施乳腺癌治疗的关键。我们的研究集中于血清蛋白的低分子量(LMW)区域及其包含的信息,这些信息可用于识别可反映所有组织正在进行的生理状态的生物标志物。由于收获LMW物种的技术困难,到目前为止,研究这些蛋白质/肽一直是一项挑战。在我们的研究中,我们最近开发了基于纳米孔芯片的技术,可以从血清中的大蛋白中分离出小蛋白/肽。我们使用具有高度周期性的纳米结构和均一的孔径分布的纳米多孔二氧化硅芯片,从MDA-MB-231人乳腺癌肺转移的裸鼠血清中分离LMW蛋白和多肽。通过基质辅助激光解吸/电离飞行时间质谱和生物统计学分析,我们能够鉴定出癌症发展不同阶段所特有的蛋白质特征。这项研究中报道的方法和结果具有发现蛋白质组生物标志物的巨大潜力,可以显着增强针对转移性乳腺癌的个性化药物。

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