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Transcriptional Landscape of B Cell Precursor Acute Lymphoblastic Leukemia Based on an International Study of 1,223 Cases

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Transcriptional Landscape of B Cell Precursor Acute Lymphoblastic Leukemia Based on an International Study of 1,223 Cases Transcriptional landscape of B cell precursor acute lymphoblastic leukemia based on an international study of 1,223 cases Jian-Feng Lia,1, Yu-Ting Daia,1, Henrik Lilljebjörnb,1, Shu-Hong Shenc, Bo-Wen Cuia, Ling Baia, Yuan-Fang Liua, Mao-Xiang Qiand, Yasuo Kubotae, Hitoshi Kiyoif, Itaru Matsumurag, Yasushi Miyazakih, Linda Olssonb, Ah Moy Tani, Hany Ariffinj, Jing Chenc, Junko Takitak, Takahiko Yasudal, Hiroyuki Manom, Bertil Johanssonb,n, Jun J. Yangd,o, Allen Eng-Juh Yeohp, Fumihiko Hayakawaq, Zhu Chena,r,s,2, Ching-Hon Puio,2, Thoas Fioretosb,n,2, Sai-Juan Chena,r,s,2, and Jin-Yan Huanga,s,2 aState 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; bDepartment of Laboratory Medicine, Division of Clinical Genetics, Lund University, 22184 Lund, Sweden; cKey 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; dDepartment of Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, TN 38105; eDepartment of Pediatrics, Graduate School of Medicine, The University of Tokyo, 1138654 Tokyo, Japan; fDepartment of Hematology and Oncology, Nagoya University Graduate School of Medicine, 4668550 Nagoya, Japan; gDivision of Hematology and Rheumatology, Kinki University Faculty of Medicine, 5778502 Osaka, Japan; hDepartment of Hematology, Atomic Bomb Disease Institute, Nagasaki University, 8528521 Nagasaki, Japan; iDepartment of Paediatrics, KK Women’s & Children’s Hospital, 229899 Singapore; jPaediatric Haematology-Oncology Unit, University of Malaya Medical Centre, 59100 Kuala Lumpur, Malaysia; kDepartment of Pediatrics, Graduate School of Medicine, Kyoto University, 6068501 Kyoto, Japan; lClinical Research Center, Nagoya Medical Center, National Hospital Organization, 4600001 Nagoya, Japan; mNational Cancer Center Research Institute, 1040045 Tokyo, Japan; nDepartment of Clinical Genetics, University and Regional Laboratories, Region Skåne, Lund 22185, Sweden; oDepartment of Oncology, St. Jude Children’s Research Hospital, Memphis, TN 38105; pCentre for Translational Research in Acute Leukaemia, Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, 119228 Singapore; qDepartment of Pathophysiological Laboratory Sciences, Nagoya University Graduate School of Medicine, 4618673 Nagoya, Japan; rKey Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China; and sPôle de Recherches Sino-Français en Science du Vivant et Génomique, Laboratory of Molecular Pathology, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China GENETICS Contributed by Zhu Chen, October 17, 2018 (sent for review August 29, 2018; reviewed by Christine J. Harrison and Patrick Tan) Most B cell precursor acute lymphoblastic leukemia (BCP ALL) can four decades, most of the recurring chromosomal abnormalities, be classified into known major genetic subtypes, while a sub- including aneuploidy, chromosomal rearrangements/gene fu- stantial proportion of BCP ALL remains poorly characterized in sions (e.g., ETV6–RUNX1, BCR–ABL1, and TCF3–PBX1), and relation to its underlying genomic abnormalities. We therefore rearrangements of KMT2A (previously MLL), were identified by initiated a large-scale international study to reanalyze and de- lineate the transcriptome landscape of 1,223 BCP ALL cases using RNA sequencing. Fourteen BCP ALL gene expression subgroups Significance (G1 to G14) were identified. Apart from extending eight previously described subgroups (G1 to G8 associated with MEF2D fusions, In BCP ALL, molecular classification is used for risk stratification TCF3–PBX1 fusions, ETV6–RUNX1–positive/ETV6–RUNX1–like, DUX4 and influences treatment strategies. We reanalyzed the tran- fusions, ZNF384 fusions, BCR–ABL1/Ph–like, high hyperdiploidy, and scriptomic landscape of 1,223 BCP ALLs and identified 14 sub- KMT2A fusions), we defined six additional gene expression sub- groups based on their transcriptional profiles. Eight of these groups: G9 was associated with both PAX5 and CRLF2 fusions; (G1 to G8) are previously well-known subgroups, harboring G10 and G11 with mutations in PAX5 (p.P80R) and IKZF1 (p.N159Y), specific genetic abnormalities. The sample size allowed the respectively; G12 with IGH–CEBPE fusion and mutations in ZEB2 identification of six previously undescribed subgroups, con- (p.H1038R); and G13 and G14 with TCF3/4–HLF and NUTM1 fu- sisting of cases harboring PAX5 or CRLF2 fusions (G9), PAX5 sions, respectively. In pediatric BCP ALL, subgroups G2 to G5 and (p.P80R) mutations (G10), IKZF1 (p.N159Y) mutations (G11), G7 (51 to 65/67 chromosomes) were associated with low-risk, G7 either ZEB2 (p.H1038R) mutations or IGH–CEBPE fusions (G12), (with ≤50 chromosomes) and G9 were intermediate-risk, whereas HLF rearrangements (G13), or NUTM rearrangements (G14). In G1, G6, and G8 were defined as high-risk subgroups. In adult BCP addition, this study allowed us to determine the prognostic ALL, G1, G2, G6, and G8 were associated with high risk, while G4, impact of several recently defined subgroups. This study G5, and G7 had relatively favorable outcomes. This large-scale suggests that RNA sequencing should be a valuable tool in the transcriptome sequence analysis of BCP ALL revealed distinct mo- routine diagnostic workup for ALL. lecular subgroups that reflect discrete pathways of BCP ALL, informing disease classification and prognostic stratification. The Author contributions: Z.C., C.-H.P., T.F., S.-J.C., and J.-Y.H. designed research; J.-F.L., combined results strongly advocate that RNA sequencing be in- Y.-T.D., H.L., S.-H.S., B.-W.C., L.B., Y.-F.L., M.-X.Q., Y.K., H.K., I.M., Y.M., L.O., A.M.T., H.A., J.C., J.T., T.Y., H.M., B.J., J.J.Y., A.E.-J.Y., F.H., Z.C., C.-H.P., T.F., S.-J.C., and J.-Y.H. troduced into the clinical diagnostic workup of BCP ALL. performed research; S.-H.S., Y.-F.L., J.C., J.J.Y., and F.H. collected the samples and clinical data; J.-F.L., Y.-T.D., H.L., B.-W.C., L.B., Z.C., C.-H.P., T.F., S.-J.C., and J.-Y.H. analyzed data; BCP ALL | RNA-seq | subtypes | gene fusion | gene mutation Z.C., C.-H.P., T.F., S.-J.C., and J.-Y.H. wrote the paper; and J.-F.L., Z.C., C.-H.P., T.F., S.-J.C., and J.-Y.H. critically revised the manuscript. Reviewers: C.J.H., Newcastle University; and P.T., Duke–NUS Medical School. cell precursor acute lymphoblastic leukemia (BCP ALL), the Bmost common childhood cancer, is a highly heterogeneous The authors declare no conflict of interest. malignant hematological disorder (1). Previous genome- and/or Published under the PNAS license. 1 transcriptome-wide analyses of BCP ALLs have greatly im- J.-F.L., Y.-T.D., and H.L. contributed equally to this work. 2To whom correspondence may be addressed. Email: [email protected], ching-hon.pui@ proved our understanding of the pathogenesis and prognostic stjude.org, [email protected], [email protected], or [email protected]. impact of many molecular abnormalities in BCP ALL (2, 3). This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. Structural chromosomal alterations as well as sequence muta- 1073/pnas.1814397115/-/DCSupplemental. tions are common in childhood and adult BCP ALL. In the last www.pnas.org/cgi/doi/10.1073/pnas.1814397115 PNAS Latest Articles | 1of10 Downloaded by guest on September 24, 2021 cytogenetics and fluorescence in situ hybridization. Subsequently, those involving ZNF384, MEF2D,andDUX4 rearrangements (6– gene expression profiling revealed that these cytogenetic sub- 11), among those cases with no defining chromosomal abnor- groups displayed specific gene expression patterns (3–5). With the malities, termed “B-other-ALL.” advent of genome sequencing technology, several groups discov- However, it remained unknown whether additional novel BCP ered a large number of novel gene mutations and fusions, such as ALL subtypes could be detected by integrated analysis of pooled Age Gender MEF2D fusions TCF3-PBX1 ETV6-RUNX1 ETV6-RUNX1-like DUX4 fusions ZNF384/ZNF362 fusions BCR-ABL1 Ph-like CRLF2 fusions Hyperdiploidy KMT2A fusions PAX5 fusions TCF3/4-HLF NUTM1 fusions IGH-CEBPE PAX5 (p.P80R) ZEB2 (p.H1038R) IKZF1 (p.N159Y) G1 G2 G3 G4 G5 G6 G7 G8 G9 G10-14 Subgroup Color Key Low High Age Adult Paediatric Gender Male Female Subgroup G1 (MEF2D fusions) G2 (TCF3-PBX1) G3 (ETV6-RUNX1/-like) G4 (DUX4 fusions) G5 (ZNF384 fusions) G6 (BCR-ABL1/Ph-like) G7 (Hyperdiploidy) G8 (KMT2A fusions) G9 (PAX5 and CRLF2 fusions) PAX5 G10 G11 G12 G13 G14 G10 [ (p.P80R) mutation] Subgroup(G10-G14) G11 [IKZF1 (p.N159Y) mutation] Age Gender G12 [ZEB2 (p.H1038R)/IGH-CEBPE] PAX5 (p.P80R) TCF3/4-HLF IKZF1 (p.N159Y) G13 ( ) IGH-CEBPE G14 (NUTM1 fusions) ZEB2 (p.H1038R) TCF3/4-HLF NUTM1 fusions Fig. 1. Two-step unsupervised hierarchical clustering of the global gene expression profile from 1,223 BCP ALL patients. In the gene expression subgroups of G1 to G7 (Left) and G8 to G14 (Right), columns indicate 1,223 BCP ALL patients and rows represent gene expression levels or genetic features for each patient. Genes showing over- and underexpression in the heatmap are shown in red and blue, respectively. The first box above the heatmap indicates genotypes and fusion genes, followed by a box including three clusters of hotspot sequence mutations defined in this analysis. The first row below the heatmap specifies the 14 BCP ALL subgroups identified on the basis of gene expression profiles. In the unsupervised hierarchical clustering heatmap of G10 to G14 (Lower Right), columns represent patients and rows are top variance genes in G10 to G14.
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