A high percentage of BRAFV600E alleles in papillary thyroid carcinoma predicts a poorer outcome.J Clin Endocrinol Metab. 2012 Jul; 97(7):2333-40.JC
BRAF(V600E) is considered a negative prognostic marker in papillary thyroid carcinoma (PTC), but unexplained conflicting results are present in the literature. In light of the new finding that most PTC consist of a mixture of tumor cells with wild-type and mutant BRAF, we examined the associations between the percentage of BRAF(V600E) alleles and both the clinicopathological parameters at time of diagnosis and the disease outcome in a large series of PTCs.
Tumors from 168 patients with PTC were genotyped for BRAF(V600E) using BigDye Terminator sequencing and pyrosequencing, and the clinical parameters were analyzed. The associations between clinicopathological characteristics, including disease recurrence at follow-up (median 5.1 yr) and the percentage of mutant BRAF alleles were assessed.
The observed prevalence of BRAF(V600E) was higher when using pyrosequencing then when using BigDye Terminator sequencing (53.6 vs. 36.9%). In the PTC positive for BRAF(V600E), the percentage of mutant alleles ranged from 5.1 to 44.7% of the total BRAF alleles, with a median of 20.6%. The presence or the percentage of BRAF(V600E) alleles did not correlate significantly with sex, multicentricity, lymph node metastasis, or tumor stage. The percentage of BRAF(V600E) alleles directly correlated with age at diagnosis and tumor volume (R(2) = 0.223, P = 0.039, and R(2) = 0.166, P < 0.001, respectively). The percentage of BRAF(V600E) alleles (P = 0.014), tumor volume (P = 0.012), and lymph node metastasis (P = 0.008) predicted the disease outcome. The odds ratio of recurrence for PTC with BRAF(V600E) alleles of 30% or greater, compared with that for PTC with BRAF(V600E) alleles of less than 30%, was 5.31 (P = 0.002).
A high percentage of BRAF(V600E) alleles defines a PTC molecular subtype and predicts a poorer disease outcome. The analysis of BRAF mutations by pyrosequencing is useful to refine the risk stratification of patients with PTC.