Affiliations 

  • 1 State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 200025 Shanghai, China
  • 2 Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, 22184 Lund, Sweden
  • 3 Key Laboratory of Pediatric Hematology and Oncology, Ministry of Health, Department of Hematology and Oncology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, 200127 Shanghai, China
  • 4 Department of Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN 38105
  • 5 Department of Pediatrics, Graduate School of Medicine, The University of Tokyo, 1138654 Tokyo, Japan
  • 6 Department of Hematology and Oncology, Nagoya University Graduate School of Medicine, 4668550 Nagoya, Japan
  • 7 Division of Hematology and Rheumatology, Kinki University Faculty of Medicine, 5778502 Osaka, Japan
  • 8 Department of Hematology, Atomic Bomb Disease Institute, Nagasaki University, 8528521 Nagasaki, Japan
  • 9 Department of Paediatrics, KK Women's & Children's Hospital, 229899 Singapore
  • 10 Paediatric Haematology-Oncology Unit, University of Malaya Medical Centre, 59100 Kuala Lumpur, Malaysia
  • 11 Department of Pediatrics, Graduate School of Medicine, Kyoto University, 6068501 Kyoto, Japan
  • 12 Clinical Research Center, Nagoya Medical Center, National Hospital Organization, 4600001 Nagoya, Japan
  • 13 National Cancer Center Research Institute, 1040045 Tokyo, Japan
  • 14 Centre for Translational Research in Acute Leukaemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore
  • 15 Department of Pathophysiological Laboratory Sciences, Nagoya University Graduate School of Medicine, 4618673 Nagoya, Japan
  • 16 State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 200025 Shanghai, China; zchen@stn.sh.cn ching-hon.pui@stjude.org thoas.fioretos@med.lu.se sjchen@stn.sh.cn jinyan@shsmu.edu.cn
  • 17 Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN 38105; zchen@stn.sh.cn ching-hon.pui@stjude.org thoas.fioretos@med.lu.se sjchen@stn.sh.cn jinyan@shsmu.edu.cn
  • 18 Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, 22184 Lund, Sweden; zchen@stn.sh.cn ching-hon.pui@stjude.org thoas.fioretos@med.lu.se sjchen@stn.sh.cn jinyan@shsmu.edu.cn
Proc Natl Acad Sci U S A, 2018 12 11;115(50):E11711-E11720.
PMID: 30487223 DOI: 10.1073/pnas.1814397115

Abstract

Most B cell precursor acute lymphoblastic leukemia (BCP ALL) can be classified into known major genetic subtypes, while a substantial proportion of BCP ALL remains poorly characterized in relation to its underlying genomic abnormalities. We therefore initiated a large-scale international study to reanalyze and delineate the transcriptome landscape of 1,223 BCP ALL cases using RNA sequencing. Fourteen BCP ALL gene expression subgroups (G1 to G14) were identified. Apart from extending eight previously described subgroups (G1 to G8 associated with MEF2D fusions, TCF3-PBX1 fusions, ETV6-RUNX1-positive/ETV6-RUNX1-like, DUX4 fusions, ZNF384 fusions, BCR-ABL1/Ph-like, high hyperdiploidy, and KMT2A fusions), we defined six additional gene expression subgroups: G9 was associated with both PAX5 and CRLF2 fusions; G10 and G11 with mutations in PAX5 (p.P80R) and IKZF1 (p.N159Y), respectively; G12 with IGH-CEBPE fusion and mutations in ZEB2 (p.H1038R); and G13 and G14 with TCF3/4-HLF and NUTM1 fusions, respectively. In pediatric BCP ALL, subgroups G2 to G5 and G7 (51 to 65/67 chromosomes) were associated with low-risk, G7 (with ≤50 chromosomes) and G9 were intermediate-risk, whereas G1, G6, and G8 were defined as high-risk subgroups. In adult BCP ALL, G1, G2, G6, and G8 were associated with high risk, while G4, G5, and G7 had relatively favorable outcomes. This large-scale transcriptome sequence analysis of BCP ALL revealed distinct molecular subgroups that reflect discrete pathways of BCP ALL, informing disease classification and prognostic stratification. The combined results strongly advocate that RNA sequencing be introduced into the clinical diagnostic workup of BCP ALL.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.