Yuma Sakamoto
   Department   Kawasaki Medical School  Kawasaki Medical School, Department of Immunology and Molecular Genetics,
   Position   Instructor
Article types 原著
Language English
Peer review Peer reviewed
Title Improved clonality detection in B-cell lymphoma using a semi-nested modification of the BIOMED-2 PCR assay for IGH rearrangement: A paraffin-embedded tissue study.
Journal Formal name:Pathology international
Abbreviation:Pathol Int
ISSN code:14401827/13205463
Domestic / ForeginForegin
Volume, Issue, Page 67(9),pp.453-460
Author and coauthor Yuma Sakamoto, Ayako Masaki, Satsuki Aoyama, Shusen Han, Kosuke Saida, Kana Fujii, Hisashi Takino, Takayuki Murase, Shinsuke Iida, Hiroshi Inagaki
Publication date 2017/09
Summary The BIOMED-2 PCR protocol for targeting the IGH gene is widely employed for detecting clonality in B-cell malignancies. Unfortunately, the detection of clonality with this method is not very sensitive when paraffin sections are used as a DNA source. To increase the sensitivity, we devised a semi-nested modification of a JH consensus primer. The clonality detection rates of three assays were compared: the standard BIOMED-2, BIOMED-2 assay followed by BIOMED-2 re-amplification, and BIOMED-2 assay followed by semi-nested BIOMED-2. We tested more than 100 cases using paraffin-embedded tissues of various B-cell lymphomas, and found that the clonality detection rates with the above three assays were 63.9%, 79.6%, and 88.0%, respectively. While BIOMED-2 re-amplification was significantly more sensitive than the standard BIOMED-2, the semi-nested BIOMED-2 was significantly more sensitive than both the standard BIOMED-2 and BIOMED-2 re-amplification. An increase in sensitivity was observed in all lymphoma subtypes examined. In conclusion, tumor clonality may be detected in nearly 90% of B-cell lymphoma cases with semi-nested BIOMED-2. This ancillary assay may be useful when the standard BIOMED-2 fails to detect clonality in histopathologically suspected B-cell lymphomas.
DOI 10.1111/pin.12566
PMID 28868745