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Blood, 1 May 2007, Vol. 109, No. 9, pp. 3922-3928.
Prepublished online as a Blood First Edition Paper on January 30, 2007January 25, 2007; DOI 10.1182/blood-2006-09-046391.
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Submitted September 18, 2006
Accepted December 22, 2006
Clinical quantitation of diagnostic and predictive gene expression levels in follicular and diffuse large B-cell lymphoma by RT-PCR gene expression profiling
Ebrahim Sakhina, Caroline Glennie, Judith A Hoyland, Lia P Menasce, Gerard Brady, Crispin Miller, John A Radford, and Richard J Byers*
Division of Regenerative Medicine, School of Medicine, Faculty of Medical & Human Sciences, University of Manchester, Manchester, United Kingdom
Dept of Histopathology, Christie Hospital NHS Trust, Manchester, United Kingdom
Epistem Ltd, Incubator Building, Manchester, United Kingdom
Paterson Institute for Cancer Research, Manchester, United Kingdom
Cancer Research UK Dept of Medical Oncology, University of Manchester & Christie Hospital NHS Trust, Manchester, United Kingdom
* Corresponding author; email: r.byers{at}manchester.ac.uk.
Recent microarray gene expression profiling studies have identified gene signatures predictive of outcome, so-called "Indicator" genes, for diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). However, measurement of these genes in routine practice remains difficult. We applied real-time PCR, to polyA cDNAs prepared from 106 archived human frozen lymph nodes (63 of FL, 25 of DLBCL, 10 reactive lymph nodes and 4 cases with paired samples of FL (4) and subsequent DLBCL (4)). Reverse transcription and polyA RT-PCR was performed and resultant cDNA probed by real-time PCR for 36 candidate Indicator genes, selected from microarray studies. Nine genes showed statistically significant different expression between FL and DLBCL, including Cyclin B, COL3A1, NPM3, H731, PKC.B1, OVGL, ZFPC150, HLA-DQ-a, and XPB. Of these, Cyclin B, NPM3, and COL3A1 were higher in DLBCL. Six genes showed statistically significant higher expression in the neoplastic nodes compared to reactive nodes, namely PKCB-1, BCL-6, EAR2, ZFX, Cyclin B, YY.1. High levels of YY.1 were associated with a shorter survival interval in both FL and DLBCL. The method is simple, sensitive and robust, facilitating routine use and may be used as a platform for clinical measurement of prognostic gene signatures.
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