A Microfluidic Platform for Systems Pathology: Multiparameter Single-Cell Signaling Measurements of Clinical Brain Tumor Specimens

作者：Sun Jing; Masterman Smith Michael D; Graham Nicholas A; Jiao Jing; Mottahedeh Jack; Laks Dan R; Ohashi Minori; DeJesus Jason; Kamei Ken ichiro; Lee Ki Bum; Wang Hao; Yu Zeta T F; Lu Yi Tsung; Hou Shuang; Li Keyu; Liu Max; Zhang Nangang; Wang Shutao; Angenieux Brigitte; Panosyan Eduard; Samuels Eric R; Park Jun; Williams Dirk; Konkankit Vera; Nathanson David; van Dam R Michael; Phelps Michael E; Wu Hong; Liau Linda M; Mischel Paul S; Lazareff Jorge A

来源：Cancer Research, 2010, 70(15): 6128-6138.

DOI：10.1158/0008-5472.CAN-10-0076

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. Cancer Res; 70(15); 6128-38.

• 出版日期2010-8-1