Affiliations: Dept. of Pathology, Radboud University Nijmegen Medical Centre, The Netherlands | Dept. of Hematology, Radboud University Nijmegen Medical Centre, The Netherlands
Note: [] Corresponding author: Corine Jansen, 824 Dept. of Pathology, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands. Tel.: +31 24 361 89 45; Fax: + 31 24 366 8750; E-mail: c.jansen@pathol.umcn.nl.
Abstract: Non-Hodgkin's lymphoma comprises many related but distinct diseases and diagnosis and classification is complex. Protein profiling of lymphoma biopsies may be of potential value for use in this lymphoma classification and the discovery of novel markers. In this study, we have optimized a method for SELDI-TOF MS based protein profiling of frozen tissue sections, without dissection of tumour cells. First we have compared chip surfaces and lysis buffers. Also, we have determined the minimal input using laser dissection microscopy. Subsequently, we have analyzed and compared protein profiles of diffuse large B-cell lymphoma (n=8), follicular lymphoma (n=8) and mantle cell lymphoma (n=8). Benign, reactive lymph nodes (n=14) were used as a reference group. CM10 chip surface in combination with urea lysis buffer and an input of approximately 50,000 lymphocytes allowed the detection of many differential peaks. Identification of the diffuse large B-cell lymphoma cases was reliably made in the supervised classification. Unsupervised clustering showed segregation into a benign/indolent cluster predominantly formed by benign, reactive lymph nodes and follicular lymphoma cases and into a more aggressive cluster formed by diffuse large B-cell lymphoma and mantle cell lymphoma cases. In conclusion, our protocol enables protein profiling of protein lysates derived from small histological samples and the subsequent detection of many differentially expressed proteins, without the need of tumour cell dissection. These results support further evaluation of protein profiling of small lymphoma biopsies as an additional tool in pathology.
Keywords: Classification, non-Hodgkin's lymphoma, protein profiling, proteomics, SELDI-TOF MS
