Integrated mutational and cytogenetic analysis identifies new prognostic subgroups in chronic lymphocytic leukemia

Davide Rossi, Silvia Rasi, Valeria Spina, Alessio Bruscaggin, Sara Monti, Carmela Ciardullo, Clara Deambrogi, Hossein Khiabanian, Roberto Serra, Francesco Bertoni, Francesco Forconi, Luca Laurenti, Roberto Marasca, Michele Dal-Bo, Francesca Maria Rossi, Pietro Bulian, Josep Nomdedeu, Giovanni Del Poeta, Valter Gattei, Laura PasqualucciRaul Rabadan, Robin Foà, Riccardo Dalla-Favera, Gianluca Gaidano

Research output: Contribution to journalArticlepeer-review

352 Scopus citations

Abstract

The identification of new genetic lesions in chronic lymphocytic leukemia (CLL) prompts a comprehensive and dynamic prognostic algorithm including gene mutations and chromosomal abnormalities and their changes during clonal evolution. By integrating mutational and cytogenetic analysis in 1274 CLL samples and using both a training-validation and a time-dependent design, 4 CLL subgroups were hierarchically classified: (1) high-risk, harboring TP53 and/or BIRC3 abnormalities (10-year survival: 29%); (2) intermediate-risk, harboring NOTCH1 and/or SF3B1 mutations and/or del11q22-q23 (10-year survival: 37%); (3) low-risk, harboring +12 or a normal genetics (10-year survival: 57%); and (4) very low-risk, harboring del13q14 only, whose 10-year survival (69.3%) did not significantly differ from a matched general population. This integrated mutational and cytogenetic model independently predicted survival, improved CLL prognostication accuracy compared with FISH karyotype (P <.0001), and was externally validated in an independent CLL cohort. Clonal evolution from lower to higher risk implicated the emergence of NOTCH1, SF3B1, and BIRC3 abnormalities in addition to TP53 and 11q22-q23 lesions. By taking into account clonal evolution through time-dependent analysis, the genetic model maintained its prognostic relevance at any time from diagnosis. These findings may have relevant implications for the design of clinical trials aimed at assessing the use of mutational profiling to inform therapeutic decisions.

Original languageEnglish (US)
Pages (from-to)1403-1412
Number of pages10
JournalBlood
Volume121
Issue number8
DOIs
StatePublished - Feb 21 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Immunology
  • Hematology
  • Cell Biology

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