Protein profiling in pathology: analysis and evaluation of 239 frozen tissue biopsies for diagnosis of B-cell lymphomas.
OBJECTIVE
We determined the potential value of protein profiling of tissue samples by assessing how precise this approach enables discrimination of B-cell lymphoma from reactive lymph nodes, and how well the profiles can be used for lymphoma classification.


METHODS
Protein lysates from lymph nodes (n=239) from patients with the diagnosis of reactive hyperplasia (n=44), follicular lymphoma (n=63), diffuse large B-cell lymphoma (n=43), mantle cell lymphoma (n=47), and chronic lymphocytic leukemia/small lymphocytic B-cell lymphoma (n=42) were analysed by SELDI-TOF MS. Data analysis was performed by (i) classification and regression tree-based analysis and (ii) binary and polytomous logistic regression analysis.


RESULTS
After internal validation by the leave-one-out principle, both the classification and regression tree and logistic regression classification correctly identified the majority of the malignant (87 and 96%, respectively) and benign cases (73 and 75%, respectively). Classification was less successful since approximately one-third of the cases of each group were misclassified according to the histological classification. However, an additional mantle cell lymphoma case that was misclassified as chronic lymphocytic leukemia/small lymphocytic B-cell lymphoma initially was identified based on the protein profile.


CONCLUSIONS
SELDI-TOF MS protein profiling allows for reliable identification of the majority of malignant lymphoma cases; however, further validation and testing robustness in a diagnostic setting is needed.
Department of Pathology, Radboud University Nijmegen Medical Centre, The Netherlands.
Corine
C
Jansen
Ton
T
Feuth
John M M
JM
Raemaekers
Jos
J
Rijntjes
Jos W
JW
Meijer
Pieter J
PJ
Westenend
Joop
J
van Baarlen
Johan H J M
JH
van Krieken
Konnie M
KM
Hebeda
Patricia J T A
PJ
Groenen
D006801:Humans; D006965:Hyperplasia / Q000175:diagnosis; D015451:Leukemia, Lymphocytic, Chronic, B-Cell / Q000175:diagnosis; D016015:Logistic Models; D008198:Lymph Nodes / Q000737:chemistry* / Q000473:pathology; D016393:Lymphoma, B-Cell / Q000175:diagnosis* / Q000473:pathology; D008224:Lymphoma, Follicular / Q000175:diagnosis; D016403:Lymphoma, Large B-Cell, Diffuse / Q000175:diagnosis; D020522:Lymphoma, Mantle-Cell / Q000175:diagnosis; D009363:Neoplasm Proteins / Q000032:analysis*; D040081:Protein Array Analysis; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
D009363:Neoplasm Proteins