Rapid identification of BCR/ABL1-like acute lymphoblastic leukaemia patients using a predictive statistical model based on quantitative real time-polymerase chain reaction: clinical, prognostic and therapeutic implications

Sabina Chiaretti*, Monica Messina, Sara Grammatico, Alfonso Piciocchi, Anna L. Fedullo, Filomena Di Giacomo, Nadia Peragine, Valentina Gianfelici, Alessia Lauretti, Rohan Bareja, Maria P. Martelli, Marco Vignetti, Valerio Apicella, Antonella Vitale, Loretta S. Li, Cyril Salek, Olivier Elemento, Giorgio Inghirami, David M. Weinstock, Anna GuariniRobin Foà

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

BCR/ABL1-like acute lymphoblastic leukaemia (ALL) is a subgroup of B-lineage acute lymphoblastic leukaemia that occurs within cases without recurrent molecular rearrangements. Gene expression profiling (GEP) can identify these cases but it is expensive and not widely available. Using GEP, we identified 10 genes specifically overexpressed by BCR/ABL1-like ALL cases and used their expression values – assessed by quantitative real time-polymerase chain reaction (Q-RT-PCR) in 26 BCR/ABL1-like and 26 non-BCR/ABL1-like cases to build a statistical “BCR/ABL1-like predictor”, for the identification of BCR/ABL1-like cases. By screening 142 B-lineage ALL patients with the “BCR/ABL1-like predictor”, we identified 28/142 BCR/ABL1-like patients (19·7%). Overall, BCR/ABL1-like cases were enriched in JAK/STAT mutations (P < 0·001), IKZF1 deletions (P < 0·001) and rearrangements involving cytokine receptors and tyrosine kinases (P = 0·001), thus corroborating the validity of the prediction. Clinically, the BCR/ABL1-like cases identified by the BCR/ABL1-like predictor achieved a lower rate of complete remission (P = 0·014) and a worse event-free survival (P = 0·0009) compared to non-BCR/ABL1-like ALL. Consistently, primary cells from BCR/ABL1-like cases responded in vitro to ponatinib. We propose a simple tool based on Q-RT-PCR and a statistical model that is capable of easily, quickly and reliably identifying BCR/ABL1-like ALL cases at diagnosis.

Original languageEnglish (US)
Pages (from-to)642-652
Number of pages11
JournalBritish Journal of Haematology
Volume181
Issue number5
DOIs
StatePublished - Jun 2018

Funding

The authors wish to thank Associazione Italiana per la Ricerca sul Cancro (AIRC), Special Program Molecular Clinical Oncology-Extension program, 5 9 1000 (10007), Milan (Italy) to RF; Finanziamento per l’avvio alla ricerca 2015 (Sapienza University of Rome) to MM; Finanziamento Medi Progetti Universitari 2015 to SC (Sapienza University of Rome); Fondazione Le Molinette Onlus, Turin (Italy); MM was partly supported by Associazione Cristina Bassi Onlus (Genova). DMW is supported by NCI 5R01CA151898 and 5R01CA17238. SC designed research, analysed data and wrote the manuscript; MM performed experiments, analysed data and wrote the manuscript; SG performed experiments and analysed data; AP designed the BCR/ABL1-like predictor model and performed statistical analyses; ALF, VG, AL, NP performed experiments; FDG performed RNA sequencing experiments; MV performed statistical analyses; MPM, VA, AV and CS provided samples and clinico-biological data; OE and RB analysed RNA-sequencing data; LSL and DW provided clinical samples; GI analysed data and critically revised the manuscript; AG and RF designed the study, analysed data and critically revised the manuscript.

Keywords

  • Acute lymphoblastic leukaemia
  • BCR/ABL1-like
  • adults
  • prognosis
  • tyrosine kinase inhibitors

ASJC Scopus subject areas

  • Hematology

Fingerprint

Dive into the research topics of 'Rapid identification of BCR/ABL1-like acute lymphoblastic leukaemia patients using a predictive statistical model based on quantitative real time-polymerase chain reaction: clinical, prognostic and therapeutic implications'. Together they form a unique fingerprint.

Cite this