Automated subcellular localization and quantification of protein expression in tissue microarrays.
The recent development of tissue microarrays-composed of hundreds of tissue sections from different tumors arrayed on a single glass slide-facilitates rapid evaluation of large-scale outcome studies. Realization of this potential depends on the ability to rapidly and precisely quantify the protein expression within each tissue spot. We have developed a set of algorithms that allow the rapid, automated, continuous and quantitative analysis of tissue microarrays, including the separation of tumor from stromal elements and the sub-cellular localization of signals. Validation studies using estrogen receptor in breast carcinoma show that automated analysis matches or exceeds the results of conventional pathologist-based scoring. Automated analysis and sub-cellular localization of beta-catenin in colon cancer identifies two novel, prognostically significant tumor subsets, not detected by traditional pathologist-based scoring. Development of automated analysis technology empowers tissue microarrays for use in discovery-type experiments (more typical of cDNA microarrays), with the added advantage of inclusion of long-term demographic and patient outcome information.
Camp
Robert L
RL
Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA.
Chung
Gina G
GG
Rimm
David L
DL
D000465:Algorithms; D002451:Cell Compartmentation; D003598:Cytoskeletal Proteins / Q000378:metabolism; D009369:Neoplasms / Q000145:classification / Q000473:pathology; D011506:Proteins / Q000378:metabolism*; D013347:Subcellular Fractions / Q000378:metabolism*; D015534:Trans-Activators / Q000378:metabolism; D051176:beta Catenin
D003598:Cytoskeletal Proteins; D011506:Proteins; D015534:Trans-Activators; D051176:beta Catenin