TP53 mutation analysis in chronic lymphocytic leukemia: comparison of different detection methods

Autor: Alexandra Oltová, Sim Truong, Jana Kotašková, Jana Šmardová, Jiri Mayer, Boris Tichy, Jitka Malčíková, Šárka Pospíšilová, Nancy Patten, Šárka Pavlová, Karla Plevová, Eva Divíšková, Nikola Tom, Michael Doubek, Martin Trbušek, Yvona Brychtová, Barbara Kantorová
Rok vydání: 2014
Předmět:
Zdroj: Tumor Biology
ISSN: 1423-0380
Popis: TP53 gene defects represent a strong adverse prognostic factor for patient survival and treatment resistance in chronic lymphocytic leukemia (CLL). Although various methods for TP53 mutation analysis have been reported, none of them allow the identification of all occurring sequence variants, and the most suitable methodology is still being discussed. The aim of this study was to determine the limitations of commonly used methods for TP53 mutation examination in CLL and propose an optimal approach for their detection. We examined 182 CLL patients enriched for high-risk cases using denaturing high-performance liquid chromatography (DHPLC), functional analysis of separated alleles in yeast (FASAY), and the AmpliChip p53 Research Test in parallel. The presence of T53 gene mutations was also evaluated using ultra-deep next generation sequencing (NGS) in 69 patients. In total, 79 TP53 mutations in 57 (31 %) patients were found; among them, missense substitutions predominated (68 % of detected mutations). Comparing the efficacy of the methods used, DHPLC and FASAY both combined with direct Sanger sequencing achieved the best results, identifying 95 % and 93 % of TP53-mutated patients. Nevertheless, we showed that in CLL patients carrying low-proportion TP53 mutation, the more sensitive approach, e.g., ultra-deep NGS, might be more appropriate. TP53 gene analysis using DHPLC or FASAY is a suitable approach for mutation detection. Ultra-deep NGS has the potential to overcome shortcomings of methods currently used, allows the detection of minor proportion mutations, and represents thus a promising methodology for near future.
Databáze: OpenAIRE