• Whittaker, S. J.
• Ferreira, S.
• Calonje, E.
• Seed, Paul T.
• Fraser-Andrews, E. A.
• Mitchell, T.
• Russell-Jones, R.

Abstract

Background Histological evidence of lymph node involvement is associated with a poor prognosis in patients with cutaneous T-cell lymphoma (CTCL). Objectives To determine whether T-cell receptor (TCR) gene analysis is of prognostic relevance in CTCL. Methods TCR gene analysis was performed on lymph node specimens from 60 patients with mycosis fungoides (MF) and Sezary syndrome (SS) using a highly sensitive polymerase chain reaction (PCR)/single-strand conformational polymorphism analysis and results were correlated with skin, overall clinical and histological lymph node stages. Results The frequency with which a T-cell clone was detected in lymph node samples from patients with MF increased with skin stage, overall clinical stage and with the degree of histological involvement: six of 19 patients with uninvolved lymph nodes or limited histological involvement (LN0-2) and 13 of 14 patients with advanced histological involvement (LN3-4) had a detectable T-cell clone. In SS, 22 of 27 patients had a detectable lymph node T-cell clone. The clonal patients had a poorer prognosis than nonclonal patients (median survival from biopsy of > 72 months vs. 16 months for MF and 41.5 vs. 16.5 months for SS). Regression analysis confirmed that TCR gene analysis identifies a group of MF patients with a worse prognosis (P = 0.013). However, the molecular lymph node stage did not provide independent prognostic information in this cohort of patients in multivariate analysis. Conclusions Molecular staging in MF and SS using a PCR-based method for TCR gene analysis provides additional information to histological examination. Specifically, this study identified a group of MF patients with early lymph node involvement with a poorer prognosis. However, a larger prospective study of patients with MF and early histological lymph node involvement is required to confirm whether molecular staging of lymph nodes provides independent prognostic information in a multivariate model

Topics

• impedance spectroscopy