Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.
PLoS One. 2010 Jun 9;5(6):e11030. doi: 10.1371/journal.pone.0011030.
Mapping the expression changes during breast cancer development should facilitate basic and translational research that will eventually improve our understanding and clinical management of cancer. However, most studies in this area are challenged by genetic and environmental heterogeneities associated with cancer.
METHODOLOGY/PRINCIPAL FINDINGS: We conducted proteomics of the MCF10AT breast cancer model, which comprises of 4 isogenic xenograft-derived human cell lines that mimic different stages of breast cancer progression, using iTRAQ-based tandem mass spectrometry. Of more than 1200 proteins detected, 98 proteins representing at least 20 molecular function groups including kinases, proteases, adhesion, calcium binding and cytoskeletal proteins were found to display significant expression changes across the MCF10AT model. The number of proteins that showed different expression levels increased as disease progressed from AT1k pre-neoplastic cells to low grade CA1h cancer cells and high grade cancer cells. Bioinformatics revealed that MCF10AT model of breast cancer progression is associated with a major re-programming in metabolism, one of the first identified biochemical hallmarks of tumor cells (the "Warburg effect"). Aberrant expression of 3 novel breast cancer-associated proteins namely AK1, ATOX1 and HIST1H2BM were subsequently validated via immunoblotting of the MCF10AT model and immunohistochemistry of progressive clinical breast cancer lesions.
CONCLUSION/SIGNIFICANCE: The information generated by this study should serve as a useful reference for future basic and translational cancer research. Dysregulation of ATOX1, AK1 and HIST1HB2M could be detected as early as the pre-neoplastic stage. The findings have implications on early detection and stratification of patients for adjuvant therapy.
绘制乳腺癌发展过程中的表达变化图谱,将有助于基础和转化研究,最终改善我们对癌症的理解和临床管理。然而,该领域的大多数研究都受到与癌症相关的遗传和环境异质性的挑战。
方法/主要发现:我们使用 iTRAQ 串联质谱法对 MCF10AT 乳腺癌模型进行了蛋白质组学研究,该模型由 4 个同源异种移植衍生的人类细胞系组成,模拟了乳腺癌进展的不同阶段。在检测到的 1200 多种蛋白质中,有 98 种蛋白质代表了至少 20 个分子功能组,包括激酶、蛋白酶、黏附、钙结合和细胞骨架蛋白,这些蛋白质在 MCF10AT 模型中显示出显著的表达变化。随着疾病从 AT1k 前瘤细胞进展到低级别 CA1h 癌细胞和高级别癌细胞,表现出不同表达水平的蛋白质数量增加。生物信息学分析显示,MCF10AT 乳腺癌进展模型与代谢的重大重编程有关,这是肿瘤细胞的首批鉴定的生化特征之一(“沃伯格效应”)。随后,通过 MCF10AT 模型的免疫印迹和进行性临床乳腺癌病变的免疫组织化学,验证了 3 种新的乳腺癌相关蛋白 AK1、ATOX1 和 HIST1H2BM 的异常表达。
结论/意义:本研究提供的信息应作为未来基础和转化癌症研究的有用参考。在癌前阶段就可以检测到 ATOX1、AK1 和 HIST1HB2M 的失调。这些发现对早期检测和辅助治疗患者的分层具有重要意义。