Rapid protein display profiling of cancer progression directly from human tissue using a protein biochip
✍ Scribed by Cloud P. Paweletz; John W. Gillespie; David K. Ornstein; Nicole L. Simone; Monica R. Brown; Kristina A. Cole; Quan-Hong Wang; Jing Huang; Nan Hu; Tai-Tung Yip; William E. Rich; Elise C. Kohn; W. Marston Linehan; Thomas Weber; Phil Taylor; Mike R. Emmert-Buck; Lance A. Liotta; Emanuel F. Petricoin III
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 283 KB
- Volume
- 49
- Category
- Article
- ISSN
- 0272-4391
No coin nor oath required. For personal study only.
✦ Synopsis
The complicated, changing pattern of protein expression should contain important information about the pathologic process taking place in the cells of actual tissue. Utilization of this information for the selection of druggable targets could be possible if a means existed to rapidly analyze and display changes in protein expression in defined microscopic cellular subpopulations. As a demonstration of feasibility, we show the generation of sensitive, rapid, and reproducible molecular weight protein profiles of patient-matched normal, premalignant, malignant, and metastatic microdissected cell populations from stained human esophageal, prostate, breast, ovary, colon, and hepatic tissue sections through the application of an affinity-based biochip. Reproducible, discriminatory protein biomarker profiles can be obtained from as few as 25 cells in less than 5 min from dissection to the generation of the protein fingerprint. Furthermore, these protein pattern profiles reveal reproducible changes in expression as cells undergo malignant transformation, and are discriminatory for different tumor types. Consistent protein changes were identified in the microdissected cells from patient-matched tumor and normal epithelium from eight out of eight different malignant esophageal tissue sets and three out of three malignant prostate tissue sets. A means to rapidly generate a display of expressed proteins from microscopic cellular populations sampled from tissue could be an important enabling technology for pharmacoproteomics, molecular pathology, drug intervention strategies, therapeutic assessment of drug entities, disease diagnosis, toxicity, and gene therapy monitoring.