| Literature DB >> 20631065 |
Jing Sun1, Michael D Masterman-Smith, Nicholas A Graham, Jing Jiao, Jack Mottahedeh, Dan R Laks, Minori Ohashi, Jason DeJesus, Ken-ichiro Kamei, Ki-Bum Lee, Hao Wang, Zeta T F Yu, Yi-Tsung Lu, Shuang Hou, Keyu Li, Max Liu, Nangang Zhang, Shutao Wang, Brigitte Angenieux, Eduard Panosyan, Eric R Samuels, Jun Park, Dirk Williams, Vera Konkankit, David Nathanson, R Michael van Dam, Michael E Phelps, Hong Wu, Linda M Liau, Paul S Mischel, Jorge A Lazareff, Harley I Kornblum, William H Yong, Thomas G Graeber, Hsian-Rong Tseng.
Abstract
The clinical practice of oncology is being transformed by molecular diagnostics that will enable predictive and personalized medicine. Current technologies for quantitation of the cancer proteome are either qualitative (e.g., immunohistochemistry) or require large sample sizes (e.g., flow cytometry). Here, we report a microfluidic platform-microfluidic image cytometry (MIC)-capable of quantitative, single-cell proteomic analysis of multiple signaling molecules using only 1,000 to 2,800 cells. Using cultured cell lines, we show simultaneous measurement of four critical signaling proteins (EGFR, PTEN, phospho-Akt, and phospho-S6) within the oncogenic phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) signaling pathway. To show the clinical application of the MIC platform to solid tumors, we analyzed a panel of 19 human brain tumor biopsies, including glioblastomas. Our MIC measurements were validated by clinical immunohistochemistry and confirmed the striking intertumoral and intratumoral heterogeneity characteristic of glioblastoma. To interpret the multiparameter, single-cell MIC measurements, we adapted bioinformatic methods including self-organizing maps that stratify patients into clusters that predict tumor progression and patient survival. Together with bioinformatic analysis, the MIC platform represents a robust, enabling in vitro molecular diagnostic technology for systems pathology analysis and personalized medicine.Entities:
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Year: 2010 PMID: 20631065 PMCID: PMC3163840 DOI: 10.1158/0008-5472.CAN-10-0076
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 12.701