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A microfluidic platform for systems pathology: multiparameter single-cell signaling measurements of clinical brain tumor specimens

Authors :
Paul S. Mischel
Yi-Tsung Lu
Ken-ichiro Kamei
Jing Jiao
Zeta Tak For Yu
Vera Konkankit
Hao Wang
Keyu Li
Eduard H. Panosyan
Linda M. Liau
Max Liu
Minori Ohashi
Shutao Wang
Thomas G. Graeber
Michael E. Phelps
William H. Yong
Dan R. Laks
Dirk Williams
Nangang Zhang
Jorge A. Lazareff
Ki-Bum Lee
Michael Masterman-Smith
R. Michael van Dam
Harley I. Kornblum
Nicholas A. Graham
Hsian-Rong Tseng
Jason DeJesus
Eric R. Samuels
Hong Wu
Shuang Hou
Jing Sun
Jack Mottahedeh
Brigitte Angenieux
Jun Park
David Nathanson
Publication Year :
2010

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. Cancer Res; 70(15); 6128–38. ©2010 AACR.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....d01e1fdfa1b395225927d880f58369ec