Evaluation of TP53 mutations with the AmpliChip p53 research test in chronic lymphocytic leukemia: correlation with clinical outcome and gene expression profiling.

Abstract

Given that TP53 alterations predict prognosis and response to therapy in chronic lymphocytic leukemia (CLL), screening for TP53 mutations has an increasing role in patient management. TP53 direct sequencing is a time-consuming method, while the AmpliChip p53 Research Test is a novel non time-consuming microarray-based resequencing assay and queries Exons 2-11. We evaluated the impact of TP53 mutations on clinical outcome by analyzing 98 untreated CLL using the AmpliChip p53 Research Test and direct sequencing and performed microarrays analysis on TP53 mutated and/or deleted cases. The AmpliChip p53 Research Test detected 17 mutations in 14 patients (17.3%); a significant association between TP53 mutations and del(17p) was recorded. From a clinical standpoint, a higher percentage of mutation was found in CLL with unfavorable outcome (17.2% vs. 7.1% in progressive vs. stable cases). Detection of TP53 mutations by the AmpliChip p53 Research Test was associated with a significantly worse survival (P = 0.0002). Comparison of the array and direct sequencing tests showed that the p53 Research Test detected more mutations, although it failed to identify two microdeletions. Finally, microarrays analysis showed a more distinctive signature associated with del(17p) than with TP53 mutations, likely due to a concomitant gene dosage effect. The AmpliChip p53 Research Test is a straightforward method that bears prognostic value. This study confirms a high percentage of TP53 mutations in CLL with unfavorable outcome and a significant association between TP53 aberrations and del(17p). Finally, specific gene expression profiles are recognized for TP53 alterations.

DOI: 10.1002/gcc.20852

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@article{Chiaretti2011EvaluationOT, title={Evaluation of TP53 mutations with the AmpliChip p53 research test in chronic lymphocytic leukemia: correlation with clinical outcome and gene expression profiling.}, author={Sabina Chiaretti and Simona Tavolaro and Marilisa Marinelli and Monica Messina and Ilaria del Giudice and Francesca Romana Mauro and Simona Santangelo and Alfonso Piciocchi and Nadia Peragine and Sim Truong and Nancy Patten and Emanuela M. Ghia and Isabella Torrente and Maria Stefania de Propris and Mauro Nanni and Jeff Lawrence and Anna R Guarini and Robin Fo{\'a}}, journal={Genes, chromosomes & cancer}, year={2011}, volume={50 4}, pages={263-74} }