The British journal of dermatology · 2006
Molecular staging of lymph nodes from 60 patients with mycosis fungoides and Sézary syndrome: correlation with histopathology and outcome suggests prognostic relevance in mycosis fungoides.
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Fraser-Andrews E A, Mitchell T, Ferreira S, Seed P T, Russell-Jones R, Calonje E, Whittaker S J
Аннотация
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 Sézary 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.
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 Sézary 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.