The hidden genomic landscape of acute myeloid leukemia: Subclonal structure revealed by undetected mutations

Margherita Bodini, Chiara Ronchini, Luciano Giacò, Anna Russo, Giorgio E M Melloni, Lucilla Luzi, Domenico Sardella, Sara Volorio, Syed K. Hasan, Tiziana Ottone, Serena Lavorgna, Francesco Lo-Coco, Anna Candoni, Renato Fanin, Eleonora Toffoletti, Ilaria Iacobucci, Giovanni Martinelli, Alessandro Cignetti, Corrado Tarella, Loris BernardPier Giuseppe Pelicci, Laura Riva

Research output: Contribution to journalArticlepeer-review


The analyses carried out using 2 different bioinformatics pipelines (SomaticSniper and MuTect) on the same set of genomic data from 133 acute myeloid leukemia (AML) patients, sequenced inside the Cancer Genome Atlas project, gave discrepant results. We subsequently tested these 2 variant-calling pipelines on 20 leukemia samples from our series (19 primary AMLs and 1 secondary AML). By validating many of the predicted somatic variants (variant allele frequencies ranging from 100% to 5%), we observed significantly different calling efficiencies. In particular, despite relatively high specificity, sensitivity was poor in both pipelines resulting in a high rate of false negatives. Our findings raise the possibility that landscapes of AML genomes might be more complex than previously reported and characterized by the presence of hundreds of genes mutated at low variant allele frequency, suggesting that the application of genome sequencing to the clinic requires a careful and critical evaluation. We think that improvements in technology and workflow standardization, through the generation of clear experimental andbioinformatics guidelines, are fundamental to translate the use of next-generation sequencing from research to the clinic and to transform genomic information into better diagnosis and outcomes for the patient.

Original languageEnglish
Pages (from-to)600-605
Number of pages6
Issue number4
Publication statusPublished - Jan 22 2015

ASJC Scopus subject areas

  • Hematology
  • Biochemistry
  • Cell Biology
  • Immunology


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