Clinical impact of small TP53 mutated subclones in chronic lymphocytic leukemia

作者: Davide Rossi , Hossein Khiabanian , Valeria Spina , Carmela Ciardullo , Alessio Bruscaggin

DOI: 10.1182/BLOOD-2013-11-539726

关键词: LeukemiaChronic lymphocytic leukemiaPopulationCancer researchSanger sequencingAllele frequencySurvival analysisDrug resistanceMutationBiologyGenetics

摘要: TP53 mutations are strong predictors of poor survival and refractoriness in chronic lymphocytic leukemia (CLL) have direct implications for disease management. Clinical information on is limited to lesions represented >20% leukemic cells. Here, we tested the clinical impact prediction chemorefractoriness very small mutated subclones. The gene underwent ultra-deep-next generation sequencing (NGS) 309 newly diagnosed CLL. A robust bioinformatic algorithm was established highly sensitive detection few cells (down 3 out ∼1000 wild-type cells). Minor subclones were validated by independent approaches. Ultra-deep-NGS identified 28/309 (9%) untreated CLL that, due their low abundance (median allele frequency: 2.1%), missed Sanger sequencing. Patients harboring showed same phenotype (hazard ratio = 2.01; P .0250) as those patients carrying clonal lesions. By longitudinal analysis, before treatment became predominant population at time relapse anticipated development chemorefractoriness. This study provides a proof-of-principle that minor detected diagnosis an important driver subsequent course.

参考文章(44)
David R. Cox, Regression Models and Life-Tables Springer Series in Statistics. ,vol. 34, pp. 527- 541 ,(1992) , 10.1007/978-1-4612-4380-9_37
A. Ciampi, J.F. Lawless, S.M. McKinney, K. Singhal, Regression and recursive partition strategies in the analysis of medical survival data Journal of Clinical Epidemiology. ,vol. 41, pp. 737- 748 ,(1988) , 10.1016/0895-4356(88)90160-6
DAVID SCHOENFELD, Partial residuals for the proportional hazards regression model Biometrika. ,vol. 69, pp. 239- 241 ,(1982) , 10.1093/BIOMET/69.1.239
E. L. Kaplan, Paul Meier, Nonparametric Estimation from Incomplete Observations Springer Series in Statistics. ,vol. 53, pp. 319- 337 ,(1992) , 10.1007/978-1-4612-4380-9_25
T Zenz, S Häbe, T Denzel, D Winkler, H Döhner, S Stilgenbauer, How little is too much? p53 inactivation: from laboratory cutoff to biological basis of chemotherapy resistance. Leukemia. ,vol. 22, pp. 2257- 2258 ,(2008) , 10.1038/LEU.2008.114
S Pospisilova, , D Gonzalez, J Malcikova, M Trbusek, D Rossi, A P Kater, F Cymbalista, B Eichhorst, M Hallek, H Döhner, P Hillmen, M van Oers, J Gribben, P Ghia, E Montserrat, S Stilgenbauer, T Zenz, ERIC recommendations on TP53 mutation analysis in chronic lymphocytic leukemia. Leukemia. ,vol. 26, pp. 1458- 1461 ,(2012) , 10.1038/LEU.2012.25
Audrey Petitjean, Ewy Mathe, Shunsuke Kato, Chikashi Ishioka, Sean V. Tavtigian, Pierre Hainaut, Magali Olivier, Impact of mutant p53 functional properties on TP53 mutation patterns and tumor phenotype: lessons from recent developments in the IARC TP53 database. Human Mutation. ,vol. 28, pp. 622- 629 ,(2007) , 10.1002/HUMU.20495
J. C. Van Houwelingen, S. Le Cessie, Predictive value of statistical models Statistics in Medicine. ,vol. 9, pp. 1303- 1325 ,(1990) , 10.1002/SIM.4780091109
Shunsuke Kato, Shuang-Yin Han, Wen Liu, Kazunori Otsuka, Hiroyuki Shibata, Ryunosuke Kanamaru, Chikashi Ishioka, None, Understanding the function–structure and function–mutation relationships of p53 tumor suppressor protein by high-resolution missense mutation analysis Proceedings of the National Academy of Sciences of the United States of America. ,vol. 100, pp. 8424- 8429 ,(2003) , 10.1073/PNAS.1431692100
Simona Soverini, Caterina De Benedittis, K. Machova Polakova, Adela Brouckova, David Horner, Michele Iacono, Fausto Castagnetti, Gabriele Gugliotta, Francesca Palandri, Cristina Papayannidis, Ilaria Iacobucci, Claudia Venturi, Maria Teresa Bochicchio, Hana Klamova, Federica Cattina, Domenico Russo, Paola Bresciani, Gianni Binotto, Barbara Giannini, Alexander Kohlmann, Torsten Haferlach, Andreas Roller, Gianantonio Rosti, Michele Cavo, Michele Baccarani, Giovanni Martinelli, Unraveling the complexity of tyrosine kinase inhibitor–resistant populations by ultra-deep sequencing of the BCR-ABL kinase domain Blood. ,vol. 122, pp. 1634- 1648 ,(2013) , 10.1182/BLOOD-2013-03-487728