Therapeutic implications of cancer stem cells Cédric Blanpain, MD, PhD Laboratory of stem cells and cancer WELBIO, Université Libre de Bruxelles
Stem cell properties Differentiation Self-renewal
Tumor heterogeneity Inter-tumour heterogeneity Intra-tumour heterogeneity Dominance of clone 1 Dominance of clone 2 Mixed dominance Figure 4 Tumour heterogeneity in diagnostics. Similar to inter-tumour Marusyk A et al. Nat Rev Cancer 2012 heterogeneity, intra-tumour heterogeneity of cellular phenotypes that result from genetic and non-genetic influences can complicate definitive diagnostics and can
Stochastic cancer evolution versus cancer stem cells? Beck & Blanpain Nature Reviews Cancer 2013
Cancer stem cells Defining cancer stem cell by transplantation assays to and its limitation Studying cancer stem cells within their native environment and defining their clonal dynamic by lineage tracing experiments Uncovering the essential role and plasticity of cancer stem cell by lineage ablation
Assessing cancer stem cell potential by transplantation assays Nassar & Blanpain Annual Reviews of Pathology 2016
A cell initiating human acute myeloid leukaemia after transplantation into SCID mice Tsvee Lapidot, John E. Dick et al. Nature 367, 645-648 1994 Limiting dilution analysis showed that the frequency of these leukaemiainitiating cells in the peripheral blood of AML patients was one engraftment unit in 250,000 cells. We fractionated AML cells on the basis of cell-surfacemarker expression and found that the leukaemia-initiating cells that could engraft SCID mice to produce large numbers of colony-forming progenitors were CD34 + CD38 - ; however, the CD34 + CD38 + and CD34 - fractions contained no cells with these properties.
Do tumor heterogeneity in skin SCCs arise from the cancer cell of origin? Mathilde Latil, PhD Dany Nassar, PhD Tumor A = Tumor B?
The cellular origin of skin SCC controls EMT related tumour heterogeneity Latil et al. Cell Stem Cell 2017
IFE and hair follicle stem cells give rise to distinct tumor phenotypes upon KRasG12D/p53KO Epithelial features Mesenchymal features
Increased tumor propagation during EMT Latil et al. Cell Stem Cell 2017
Does EMT occur through distinct transitional states? Nieto et al. Cell 2016
expressed er of surface EpCAM EpCAM Identification of the tumor transition states occuring during EMT in vivo HF derived kin SCC model a Lgr5 Cre ER STOP p53 TOP e-cell YFP+ suspension TMCs FP+ ECs Fibroblasts b YFP+ TMCs Red blood cells HF derived skin SCC model KRas G12D YFP l suspension 30 roblasts 20 blood cells rs expressed Lgr5 Cre ER STOP p53 STOP 30 20 Eugenia Pastushenko, MD PhD 24 YFP+ skin SCC KRas G12D YFP c Screening 176 cell surface markers 11 Screening 176 cell surface markers 11 YFP+ skin SCC c FACS analysis Analysis of marker YFP+Ep+ and YFP+Ep- tumor cells expression tumor Heterogeneously cells expressed markers CD24 CD106 Single-cell suspension CD24 CD106 FSC YFP+ Single-cell YFP+ suspension TECs TMCs YFP+ TECs Fibroblasts Fibroblasts Red blood cells Red blood cells CD51 CD51 YFP+ TMCs FACS analysis YFP+Ep+ and YFP+Ep- Heterogeneously expressed markers CD61 Not CD61 expressed Heterogeneously expressed CD140a CD147 Homogeneously CD140a CD147 expressed Marker FSC Homogeneously expressed markers Scree surf Scree surf Analys ex
markers expressed STOP YFP Identification of cell surface markers heterogenously expressed during EMT in vivo b 30 c Number of surface 20 10 0 24 2 Ep+ 11 17 Ep- Homogeneous Heterogeneous e EpCAM- cells f
g EpCAM CD61 CD61 CD106 CD61 CD61 Heterogeneously Identification of the tumor transition states expressed occuring during EMT in vivo rkers 61 147 d CD106+ CD51- CD61- FSC Gated on YFP+ EpCAM- TMCs Marker expressed Homogeneously expressed (TP) CD106+ CD51+ CD61+ CD106+ CD51+ CD61- rkers 47 98 (TN) CD106- CD51- CD61- CD51 CD106- CD51+ CD61+ CD106- CD51+ CD61-
% of total YFP+ cells Vim K14 K14 Vim CD61 CD61 0 2 Ep+ Ep- CD51 CD49a CD61- CD106- CD51+ CD73 CD98 Heterogeneous CD51+ CD61- (TN) CD106- Uncovering the order of CD61+ Homogeneous transition during EMT CD106- CD51- g EpCAM- cells from mixed SCC EpCAM- Vim+ cells from Vim+K14 mesenchymal K14+ SCC K14-Vim- f Ep+ CD106 TP g 100 80 60 40 20 0 Ep+ TN CD106 CD51 CD106/ CD51/ TP TN CD106 CD51 CD106/ 51 CD51 /61 61TP
% in total YFP+ EpCAM- cells % in total YFP+ EpCAM- tumor cells % in total YFP+ EpCAM- cells YFP YF bb EMT transition YFP+/Ep-/CD106 states present similar TPC Histological Number of grafted cells 1000 7/9 (n=3) 10/12 (n=3) 9/12 (n=2) 15/17 (n=2) 12/15 (n=3) 6/6 (n=2) 14/18 (n=3) 10/12 (n=2) Number of of Ep+ Ep+ Ep- Ep- TN TN CD106 CD106 CD51 CD106/51 CD51/61 TP TP 100 grafted cells cells 1/9 (n=3) 15/18 (n=4) 23/24 (n=4) 17/24 (n=4) 3/3 (n=3) 13/18 (n=3) 19/24 (n=3) 13/17 (n=4) 1000 7/9 (n=3) 10/12 (n=3) 12/15 (n=3) 10 1000 1/9 7/9 (n=3) (n=3) 18/24 10/12 (n=3) 7/30 9/12 (n=4) (n=2) 100 1/9 (n=3) 15/18 (n=4) 23/24 (n=4) TPC 100 1/614 1/9 (n=3) 15/18 1/93(n=4) 23/24 1/146 (n=4) frequency10 (1/1266-1/297) 1/9 (n=3)(1/159-1/54) 18/24 (n=3)(1/246-1/86) 7/30 (n=4) 10 1/9 (n=3) 18/24 (n=3) 7/30 (n=4) TPC TPC p= 0.004-3.35e-08 1/614 1/93 1/146 frequency (1/1266-1/297) 1/614 (1/159-1/54) 1/93 (1/245-1/86) 1/146 frequency (1/1266-1/297) (1/159-1/54) (1/246-1/86) p= 0.004-3.35e-08 p= 0.004-3.35e-08 c c 50 40 90 50 35 42 40 SSC-A subopulations YFP+/Ep-/TN YFP+/Ep-/CD106 NOD/SCID/IL2 mice FACS secondary tumors tumor cell YFP+/Ep-/TP grafting into FACS analysis (c) subopulations YFP+/Ep-/CD51 NOD/SCID/IL2 mice NOD/SCID/IL2Rgnull analysis subpopulations (c) YFP+/Ep-/CD51 YFP+/Ep-/CD106/51 secondary tumors YFP+/Ep-/CD106/51 YFP+/Ep-/CD51/61 Histological analysis (d,e) analysis YFP+/Ep-/CD51/61 YFP+/Ep-/TP subpopulations (d) secondary tumors YFP+/Ep-/TP NOD/SCID/IL2Rgnull Ep+ TN CD106 CD106/51 CD51/61 TP 17/20 (n=3) 15/18 (n=3) 8/9 (n=3) 14/18 (n=3) 13/15 (n=3) 15/17 21/46 (n=2) (n=4) 12/15 14/19 (n=3) (n=3) 6/66/18 (n=2)(n=3) 14/1814/30 (n=3) (n=3) 10/1212/21 (n=2) (n=3) 17/24 (n=4) 3/3 (n=3) 13/18 (n=3) 19/24 (n=3) 13/17 (n=4) 17/241/99 (n=4) 3/31/130 (n=3) 13/18 (n=3) 1/59 19/24 (n=3) 1/16813/17 (n=4) 1/124 21/46 (1/156-1/63) (n=4) 14/19 (1/246-1/68) (n=3) 6/18 (1/99-1/35) (n=3) 14/30 (1/285-1/99) (n=3) 12/21 (n=3) (1/226-1/69) 21/46 (n=4) 14/19 (n=3) 6/18 (n=3) 14/30 (n=3) 12/21 (n=3) 1/126 1/130 1/116 p=0.001 1/168 1/124 (1/204-1/77) 1/99p=0.0049 (1/246-1/68) 1/130 (1/208-1/65) 1/59 (1/285-1/99) 1/168 (1/226-1/68) 1/124 (1/156-1/63) (1/246-1/68) (1/99-1/35) (1/285-1/99) (1/226-1/69) p=0.0049 TN CD106 CD51 CD106/51 CD51/61 TP Ep+ TN CD106 CD51 CD106/51 CD51/61 TP TN CD106 CD51 CD106/51 CD51/61 TP YFP Vim YFP K14 YFP Vim YFP K14 d YFP Vim YFP K14 d d p=0.001 Grafted TN Grafted TN Grafted TN e e e Grafted TP Grafted TP Grafted TP capacity SSC-A but exhibit different NOD/SCID/IL2Rgnull Ep- CD51 plasticity SSC-A 3835 30 30 30 25 20 20 1025 10 20 0 0 10 Ep+ Ep- 0 Ep- TN CD106 CD51 CD106/51 CD51/61 TP TN CD106 Grafted CD51 cells CD106/51 CD51/61 TP TN CD106 CD51 CD106/51 CD51/61 TP Grafted cells
Number of metastasis per lungs Number of metastasis per lungs % of total metastasis % of total metastasis % of total metastasis %YFP+ CTCs % of total metastasis Number of metastasis p % of total metas % of total metast 60 Different EMT transition states present different 40 metastatic potential 0 Ep+ TN CD106 CD51 CD106 CD51 a. YFP+/Ep+ /51 /61 15 10 5 YFP 0 5 UPDATED DATA 40 SSC-A PREVIOUS DATA 20 10 0 FACS isolation tumor cell Ep+ TN CD106 CD51 CD106 /51 Ep+ TN CD106 CD51 CD106 /51 CD51 /61 YFP+/Ep- YFP+/Ep-/TN YFP+/Ep-/CD106 YFP+/Ep-/CD51 YFP+/Ep-/CD106/51 YFP+/Ep-/CD51/61 YFP+/Ep-/TP TP CD51 /61 100 80 60 40 20TP 0 TP Intravenous injections (tail vein) Ep+ Big 20 100 80 0 NOD/SCID/IL2Rgnull Medium Ep+ TN CD106 CD51CD106 /51 TN CD106 CD51CD106 /51 Small TP Analysis number and type of metastasis n=3 n=20 n=28 n=4 n=2 n=6 n=3 n=20 n=28 n=4 n=2 n=6 60 100 60 40 20 0 Big Medium 80 60 40 Ep+ TN 106 51 20106 /51 K14-Vim- * 60 ** ** ***** K14+Vim- 0 TP n=5 n=57 n=111 n=14 n=11 n=11 n=19 50 40 30 20 10 0 Ep+ TN K14+Vim+ 51 /61 Small CD106 CD51 TP CD106/51 CD51/61 60 40 20 100 TP 0 K14-Vim+ 80 40 20 0 Ep+ TN CD106 CD51CD106 /51 n=5 TP Ep Ep+
Transition through the different EMT states CD106 CD106/51 TN EMT Celià-Terrassa and Kang Genes and Dev 2016 TP Pastushenko Nature 2018 in press
Defining the mode of tumor growth by clonal analysis
TA SC Lineage tracing SC and their progeny ROSA 26 Lineage specific promoter Lox CRE ER Lox YFP TAM A B C D Differentiated cells Tracing SC ROSA 26 Lox YFP Tracing progenitors A B C D A B C D
Clonal tracing to define the mode of tumor growth Equipotency Cancer stem cell Cancer stem cell with neutral cell competition Blanpain & Simons Nat Rev Mol Cel Biol 2013
Most tumor clones disappear over time together with the emergence of dominant clones Gregory Driessens, PhD Driessens et al. Nature 2012
Changes in the proliferation dynamics during skin tumor progression Homeostasis Papilloma Squamous cell carcinoma Mascré et al. Nature 2012 Driessens et al. Nature 2012
Cancer stem cells: implications for therapy Reya et al. Nature 2001
Unraveling the role of cancer stem cell by lineage ablation experiments Nassar & Blanpain Annual Reviews of Pathology 2016
Sox2-GFP expressing cells are greatly enriched in tumor propagating cells in skin cancers Soufiane Boumhadi Primitive SCC
Lineage ablation of Sox2 expressing cells leads to tumor regression Boumhadi, et al. Nature 2014
LGR5 + marks CSCs in human CRCs LGR5-CreER/Rainbow Organoids RFP: Tracing reporter Xeno Tam Tracing reporter analysis 3 10 Days post-tamoxifen Shimokawa Nature 2017
Synergy between LGR5 + CSC Targeting and conventional chemotherapy Shimokawa Nature 2017
Tumor volume (mm 3 ) Tumor volume (mm 3 ) LGR5+ cells depletion decreases tumor growth Graft DT ON (50μg/kg) DT OFF Tumor 0 20 days s.c Organoids (Lgr5 DTR ) allograft Host (Lgr5 WT ) 1200 1000 800 AKVPL Saline DT 1500 1000 AKVPSL Saline DT +DT Tumor response 600 400 200 DT ON DT OFF 0 10 20 30 40 Time (days) 500 DT ON DT OFF 0 0 10 20 30 Time (days) F. de Sousa e Melo et al. Nature 2017
DT RFP cells (out of 100K live) Saline Lgr5+ cells are critical for metastasis formation Graft DT ON (50μg/kg) Tumor 2wpi 5wpi Liver Analysis BLI FACS Histology 5wpi 3000 P < 0.0001 2000 1000 0 saline DT Saline DT H&E F. de Sousa e Melo et al. Nature 2017
BCC current treatments 1) Physical removal of the BCC ( surgical excision, Mohs micrographic sugery or cryosurgery) BCC is the most common diagnosed human cancer 2)Topical medications -Imiquimod -5 -Fluorouracil ( chemotherapy) 3)Oral medication ( HH inhibitors) -Vismodegib Metastatic or -Sonidegib locally advanced BCC
Resistance to vismodegib therapy in patients Sekulic A, et al., NEJM, 2012 Sekulic A, et al., BMC Cancer, 2017
Development of tumor resistant lesions during vismodegib treatment in the Ptch1KO model
K14-CreER/ SmoM2 K14-CreER/Ptch1 fl/fl Vismodegib-resistant tumor cells are slow-cycling
Wnt signaling pathway remains active in vismodegib-resistant lesions Mouse models BCC patients
Synergy between Wnt and Smo inhibition
Overcoming the resistance to HH inhibitor in BCC Sanchez-Danes et al. in revision 2018