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Histology-directed matrix-assisted laser desorption/ionization analysis reveals tissue origin and p53 status of primary liver cancers

Authors
Jeon, Young EunLee, Seok CheolPaik, Seung SamLee, Kyeong GeunJin, So YoungKim, Hyo RimYoo, Chong WooPark, Hye MinHan, Sang YunChoi, Dong hoKim, Hark Kyun
Issue Date
Aug-2011
Publisher
WILEY-BLACKWELL
Keywords
cholangiocarcinoma; hepatocellular carcinoma; histology directed MALDI
Citation
PATHOLOGY INTERNATIONAL, v.61, no.8, pp.449 - 455
Indexed
SCIE
SCOPUS
Journal Title
PATHOLOGY INTERNATIONAL
Volume
61
Number
8
Start Page
449
End Page
455
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/167851
DOI
10.1111/j.1440-1827.2011.02686.x
ISSN
1320-5463
Abstract
To date, protein profiles for hepatocellular carcinomas and cholangiocarcinomas have not been systematically evaluated and compared with each other in an unbiased way. Thirty-six hepatocellular carcinomas and adjacent normal tissue samples were analyzed using histology-directed, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS). Four cholangiocarcinomas and adjacent normal tissue samples were also evaluated. Tissue samples were sectioned at 10 mm, with 1-3 sections thaw-mounted on a conductive indium tin oxide-coated glass slide. Sinapinic acid was manually deposited on areas of each tissue section enriched by epithelial cells, either tumor or normal, and mass spectra were acquired using a MALDI-time of flight instrument. According to class prediction analysis, average prediction accuracy in test sets (composed of 18 hepatocellular carcinoma-normal pairs) ranged from 93.0 to 95.8%. Cholangiocarcinomas and hepatocellular carcinomas had different protein profiles, as evidenced by average prediction accuracy of >95% in the test set for all classifiers. Permutation P-values for 0.632 + bootstrap cross validated misclassification rates (at feature selection P < 0.001) were less than 0.05 for predicting p53 immunostaining status. We conclude that MALDI MS profiles may be useful in assisting with the diagnosis and the differential diagnosis of primary liver cancers.
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