Clinical Drug Resistance Linked to Inter
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Clinical Drug Resistance Linked to Inter-convertible Phenotypic and Functional States of TumourPropagating cells in Multiple Myeloma Dr Aristeidis Chaidos MD PhD Centre for Haematology, Imperial College London Hammersmith Hospital, Imperial Healthcare NHS Trust Pathogenesis of multiple myeloma Molecular Heterogeneity Primary Genetic Events The Bone Marrow Microenviroment translocations involving the IgH locus (14q32) (40%) Hyperdiploid Myeloma (60%) Anderson & Carrasco, Annu Rev Path 2011 Secondary Genetic Events Palumbo & Anderson, NEJM 2011 TP53, c-Myc, Ras, RB ? Myeloma (“stem”) propagating cell Controversies on the identity and function of myeloma-propagating cells: a hierarchical model? B cell or PC? CD138- or CD138+ ? B cell or PC? CD138- or CD138+ ? Modified from JE Dick, Nat Biotechnology 2009 Myeloma clonotypic B cells exist Chen & Epstein, Blood 1996 Rasmussen et al Leuk Lymphoma 2004 CD38hiCD45- PC engraft huSCID mice Yaccoby & Epstein, Blood 1999 CD34+CD45lowCD19- engraft NOD/SCID mice Pilarski et al, Clinical cancer Res 2002 Only CD138- engraft NOD/SCID mice Matsui et al, Blood 2004 CD138- PC are CD20+, CD27+ and more drug resistant in vitro than CD138+ PC Matsui et al, Cancer Res 2008 Myeloma-propagating cell is a post CSR cell Class Switch Recombination JH6 5’ Cμ Sμ Sγ3 Cδ 3’ Cγ3 VHDJH Cγ1 LT PCR amplicon 5’ Fw CDR3 primer JH6 VHDJH Rv γ primer Sγ3 Sμ 3’ Cγ3 breakpoint LT PCR in gDNA from purified primary CD138+ plasma cells 1 2 3 4 5 6 7 8 9 10 NTC 11Kb 6Kb 5Kb Chaidos et al, Blood 2013 Dissecting the myeloma phenotypic diversity multi-parameter flow cytometry (12c) analysis and cell sorting (10c) of BM and PBMC samples in 30 myeloma patients & patient specific IgH CDR3 Taqman qPCR in flow-sorted cells to quantify clonotypic cells within the sorted cells IGH@ BM PC CD138+ selection gDNA/cDNA PCR for IgH CDR3 amplification and sequencing 5’ VHL VH VH qPCR product ~ 100 bp DH Fw: IgH CDR3 JH 3’ probe Rv: JH4 VH1 VH2 VH3 VH4 VH5 VH6 NTC 5’ 600bp 3’ germline JH4 primer 1 2 3 4 5 6 7 8 9 10 Chaidos et al, Blood 2013 Two types of CD19+ clonotypic cells: resting memory B cells & plasmablasts BM CD19+ cells 7.3% 86.5% CD10 CD19+IgD-CD10+ Immature B cells qPCR: undetected CD19+IgD+ Naive B cells qPCR: undetected 6.2% IgD 10.9% 85% CD20 HLA-DR CD138 surface IgG CD38 CD38 CD38 Plasmablasts (PBL) CD19+CD38++CD319+ qPCR: 70% (35.2-89%) CD319 qPCR: 0.95% (0.07-7.4%) CD19+IgD-CD10- CD27 Resting Memory B cells CD19+CD38CD27+/-sIg+/- Chaidos et al, Blood 2013 The CD19- myeloma cell hierarchy CD138- PrePC CD138low PC CD138+ PC CD19- BM cells DAPI- BM cells CD138 CD45 CD319 1.9% PrePC CD38 CD56 CD319 CD200 98.4% CD138low CD138 CD2 CD3 CD14 CD16 GPA PC qPCR 100% CD45 17.7% 95.2% 79.3% CD200 CD19 12.6% CD56 CD38 BM cells gated on DAPI- singlets BM cells CD19-CD319+CD200+CD45-/lowCD56+ Chaidos et al, Blood 2013 Distinct morphology of PrePC PrePC PrePC PC BM cells gated on CD19-CD319+CD45-CD38++ 80.6% 9.7% 9.1% PC 71% CD138 PC PrePC are more quiescent 89.6% 4.1% 4.2% FSC-A 3.9% MGG x1000 PrePC DAPI DAPI PrePC can differentiate to PC PrePC share oncogenic events with PC post-sorting Day 5 Day 0 IL-6 + IL-10 + IGF-1 PC 100% 99.9% IGH/CCND1 normal PrePC PC CD138 0.1% 98.7% Pre-PC 100% CD38 14 11 2R2G 1R1G1F 1R1G1F 2R2G 1R1G 1R1G 1.3% 13 Chaidos et al, Blood 2013 Normal counterpart of PrePC in peripheral blood N=15 Chaidos et al, Blood 2013 Normal counterpart of PrePC in bone marrow N=5 Chaidos et al, Blood 2013 Frequency of myeloma clonotypic cells Bone marrow Peripheral Blood N=30 105 12,565 104 434 103 1,640 102 2.23 101 1 undetected Preferential presence of PrePC/CD138low Cells per 105 PBMC Cells per 105 BM MNC Incremental frequency in BM 104 103 102 101 1 undetected B cells PrePC CD138low PC 72.7 3.31 101 1 undetected B cells PrePC CD138low PC Cells per 105 PBMC Cells per 105 BM MNC 104 60.4 102 B cells PrePC CD138low PC 105 1,105 103 104 103 102 101 1 undetected B cells PrePC CD138low PC Chaidos et al, Blood 2013 Biological insights from mathematical probabilistic modeling PCPrePC transition is predicted Chaidos et al, Blood 2013 Myeloma-propagating activity of CD138+ PC in NOD/SCID/IL-2R-/- (NSG) mouse xenografts tail vein injection 200cGy follow-up 24-32 wks post-sorting CD138+ BM cells murine spleen 7.8% 7.2% murine liver 275x103 cells mCD45.1 CD138 100% murine BM qPCR 100% CD38 2.5% hCD59 human BM CD138 94.5% 5.5% CD38 92.3% 7.7% 47.9% 52.1% 67.5% 32.5% Myeloma-propagating activity of CD138+ PC in NOD/SCID/IL-2R-/- (NSG) mouse xenografts preferential presence of PrePC in spleen and liver murine BM gated on mCD45.1-hCD59+CD138- p=0.028 p=0.04 p=0.04 97.8% 0.5% % of total clonotypic cells p=0.028 engrafted PC & PrePC retain the features of the original cells in human BM murine BM gated on mCD45.1-hCD59+CD138+ 83.6% 4.7% 0.9% S S G2 Pre-PC G0/G1 DAPI PrePC bone marrow Pre-PC spleen liver CD138low PC 11.4% G2 PC G0/G1 DAPI PC Chaidos et al, submitted Myeloma-propagating activity of CD138- PrePC in NOD/SCID/IL-2R-/- (NSG) mouse xenografts human BM gated on CD2-CD3-CD14-CD16CD34-CD138- murine BM gated on mCD45.1-CD59+ 94% qPCR 13.4% 67.5% CD138 CD319 50x103 PrePC CD19 6% CD38 Engrafted PC and PrePC regenerate the CD19- hierarchy of the original human BM suggesting a PrePCPC bi-directional transition Preferential presence of CD138low cells and PrePC in spleen/liver suggests the existence of an extramedullary niche for these phenotypes Chaidos et al, Blood 2013 Global RNA gene expression: PC vs PrePC 1000 more differentially expressed genes (Log10FC) Affymetrix Human Gene ST1.0 Arrays N=9 N=7 Chaidos et al, Blood 2013 Global RNA gene expression: PC vs PrePC 1509 differentially expressed genes (p<0.05) PCA p=4x10-6 1059 genes Functional Annotation Clustering (DAVID) Top Annotation Cluster Enrichment Score: 12.8 p SP_PIR_KEYWORDS chromatin regulator 3.27x10-15 GOTERM_BP_FAT chromatin modification 1.69x10-13 GOTERM_BP_FAT chromatin organization 2.99x10-13 GOTERM_BP_FAT chromosome organization 1.97x10-12 Chaidos et al, Blood 2013 Epigenetic basis of phenotypic transition PrePC are enriched in epigenetic regulators Chromatin remodeling Several member of the SWI/SNF chromatin remodelers Polycomb Repressive Complex 2 Polycomb repressive complex Histone methylation Histone acetylation MLL complex KDMs demethylases No change of PrePC frequency in response to treatment despite clinical remission: in vivo drug resistance? p=0.08 p=0.1 3.18 0.75 0.35 BM PrePC % of total BM MNC % of BM CD19+ cells BM Clonotypic B cells p=0.27 0.43 N=30 p=0.76 0.75 0.26 undetected Diagnosis Remission Relapse Diagnosis Remission Relapse p=0.09 BM PC p=0.01 p=0.013 p=0.11 3.06 1.68 0.8 Diagnosis Remission Relapse % of total BM MNC % of total BM MNC BM CD138low 13.9 11.5 3.01 Diagnosis Remission Relapse Chaidos et al, Blood 2013 Clonotypic cells per 105 BM MNC PrePC and clinical drug resistance patient 2 D Rem B cells patient 4 D PPC Rem patient 12 patient 18 Rel Rem D CD138low Rem patient 19 Rel Rem patient 26 D Rem patient 27 D Rem patient 30 D Rem PC PrePC are 10-fold less responsive to treatment than PC in vivo Fold decrease p=0.008 PC/PrePC ratio of fold decrease 220 30 PrePC 10.3 PC Chaidos et al, Blood 2013 Conclusions Myeloma clonal organisation -resembles normal late B cell development non-genetic clonal diversification Memory B cell CD19+ CD38CD27+/- PBL PrePC CD19+ CD38++ CD319+ CD19-CD138- PC CD138low PC CD19-CD138low CD19-CD138+ ? ? Epigenetic Plasticity myeloma-propagating myeloma-propagating drug resistant more quiescent extramedullary localisation PrePC and PC represent two dynamic and inter-convertible states of the same population with myeloma propagating activity Clinical importance of PrePC: MRD, therapeutic targeting Acknowledgements Tassos Karadimitris Amin Rahemtulla Irene Roberts Mauritius Kleijnen Jane Apperley Saad Abdalla Helen Yarranton Evangelos Terpos Athens, Greece Maria Papaioannou Thessaloniki, Greece Evdoxia Hatjiharissi Thessaloniki, Greece Members of Prof Karadimitris & Prof Roberts group Department of Cell and Developmental Biology, University College London Helen Doolittle Gillian Cowan Georg Bohn Valentina Caputo Suhail Chaudry David O’Connor Deena Iskander Katerina Goudevenou Kalliopi Makarona Joana Simoes-Costa Andi Roy Chris Barnes Centre for Bioinformatics and Institute of Mathematical Sciences Heather Harrington Michael Stumpf Imperial Molecular Pathology Laboratory Letizia Foroni Gareth Gerrard Cytogenetics Alistair Reid Valeria Melo Philippa May Histopathology Kikkeri Naresh Weatheral Institute of Molecular Medicine, Oxford Paresh Vyas
