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Infrastructure and strategies for precision medicine: leukemias, solid tumors and beyond
Olli Kallioniemi
Director of the Science for Life LaboratoryProfessor of Molecular Precision Medicine, Karolinska Institutet
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University of HelsinkiInstitute for Molecular
Medicine Finland, FIMMHelsinki, Finland
2008-
Karolinska InstitutetDept. of Oncology and Pathology
Molecular Precision MedicineStockholm, Sweden
2016-
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National center for molecular life sciences
i) Unique and enabling infrastructures for national life science research
ii) Collaborative researchamong scientists across universities
iii) Translation towards lasting societal benefits
40 national facilities1200 scientists700 publications3073 projects
Infra Research
Society
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Microfluidic processors forsingle-cell analysis
Hiseq-Xten /NovaSeq for next-gen DNA/RNA sequencing
Super-resolution Cryo-basedelectron microscopes
270 MSEK/y for national infrastructure170 MSEK/y for University research @ SciLifeLab1019 MSEK/y external grants to the community
National center for molecular life sciences
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SciLifeLab as a national infrastructureOne of the three main research infrastructures in Sweden, along with MAX-IV and ESS, the only one in Life Science
Max‐IV:next‐generation synchrotron (beamlines)
ESS: European Spallation Source (neutrons)
SciLifeLab: Life Sciences
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Motivation for a national SciLifeLab infrastructure
• Progress in (life) science is dependent on cutting‐edge, expensive infrastructure
• Healthcare and life science industry need access to scientific infrastructure and expertise
• Acquisition, professional operation, dynamic renewal of the infrastructure is a major challenge for individual universities
• Not all universities (in a small country) can have world‐class infrastructures in all fields of life science
=> Collaboration
=> Enabling systematic, comprehensive, holistic understanding of life
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Infrastructure organization with 41 facilities
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SciLifeLab Fellows’ program: recruitment of young scientists
8
Career program aiming at strengthening Swedish research in Molecular Biosciences. - International recruitment, attractive startup package
- Hosted initially (4+2 years) at SciLifeLab (proximity to research infrastructure)
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International recruitment of young talent to Sweden: Wallenberg Centers for MolecularMedicine
9
National Molecular Medicine Fellows Program
Collaborative network for recruited fellows at SciLifeLab and young group leaders of the four Wallenberg Centers for Molecular Medicine.
Regenerative Medicine
Regeneration,
Replacement
Repair
Metabolism
Neuroscience
Inflammation
Cancer
Degenerative diseases
Cancer Metabolism/DiabetesInfection biology Neuroscience
Medicine-technology interface
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Impact of SciLifeLab for diagnostics
Testbed for new technologies & technologytransitions in healthcare
SciLifeLabHealthcare
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GMS
GENOMIC MEDICINE SWEDEN
Richard Rosenquist BrandellKarolinska Institutet
Thoas FioretosLunds universitet
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Through national coodination and collaboration, enable that all health careregions could offer to their patients:
• The best diagnosis – e.g. with the help ofnext‐gen sequencing
• Precision medicin – right treatment to the right patient
Strengthen Swedish research, innovation and industrial collaboration in precision medicine
What is GMS aiming to achieve?
GMS
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Large national collaborative effort GMS
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Build on existing national resources:
• Science for Life Laboratory
• Biobank Sverige
• Regional cancer centers
• Center for rare diseases
• National quality registers
• Clinical study groups in Sweden
How do we create an internationally leading infrastructure? GMS
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Rare hereditary diseases
• Whole-genome sequencing
• >3 000 routine WGS for clinicalgenetics, molecular medicine, immunology
• >35% more diagnoses
Cancer:
• Solid tumors and leukemias:- Gene panels- (RNA-sequancing)- (WGS)
• >5 000 routine tests already at clinical genetics and pathology
GMS initial focus areas GMS
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• Reference/working groups:- 5 reference groups- 5 technical working groups- 5 working groups for ELSI, health economy, education, pharmacogenetics, innovation
• Ca 300 people participate in the workinggroups
• Pilot projects underway for hereditarydiseases, cancer and microbiology
• Regional genome medicine centers (GMCs) initiated
Status of GMS today GMS
National steering group
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Genomic Medicine Centers GMS
• Driven by university hospitals together withuniversities
• Representation from health care regions • Work towards national coordination• Competence from all parts of the chain e.g.
technology, diagnostics, clinic• Built on advanced molecular diagnostics• Node for inclusion of clinical trials
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Genomic Medicine Sweden – Time table2017 2018 2019 2020 2021 2022 2023‐2029
AP1 Organisation
AP3 Diagnosrelaterade
plattformar
AP2 Informatik-plattform
AP5 Hälsoekonomi
& kliniska resultat
AP4 ELSI
Sällsynta diagnoser Hematologi
Solida tumörer
Mikro-biologi
BeslutsstödData-
processning
Data-delning Datalagring
Nationell funktion
Regionala GMCs
AP6 Utbildning &
kommunikation
Farmakogenomik
Komplexa sjukdomar
Innovation och företagssamverkan
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GMS
GENOMIC MEDICINE SWEDEN
Richard Rosenquist BrandellKarolinska Institutet
Thoas FioretosLunds universitet
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Real‐time precision systems oncology
Precision cancer medicine
Precision systems medicine in hematological cancers
Precision systems medicine POC in solid tumors
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University of HelsinkiInstitute for Molecular
Medicine Finland, FIMMHelsinki, Finland
2008-
Karolinska InstitutetDept. of Oncology and Pathology
Molecular Precision MedicineStockholm, Sweden
2016-
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No. of p
ublicationspe
r year
Precision / personalized cancer care
The grand challenges & opportunities in precision oncology:
Better patient treatment
More effective cancer therapy for society (payers)
Improved success of cancer drug development
Drug repositioning, Combinations, Sequences
Prevention, early diagnosis, follow‐up
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No. of p
ublicationspe
r year
Precision / personalized cancer care
Precision oncology does not change the fact that:
Cancer is heterogeneous
Advanced cancer is hard or impossible to cure
Drug resistance arises to single targeted treatments
We need more and better and cheaper cancer drugs, combinations, sequential tx
Prevention is the best way to deal with cancer
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Cell 148, February 3, 2012
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- Few patients eligible, few patients benefit outside of well-known drivers in specific cancers
- Small no. of available targeted drugs - Limits to the impact of single targeted drugs, given
cancer heterogeneity and redundancy of cell signaling - Toxicity of combinations- Lack of clinical evidence of benefits and increased
costs to health care
- Few patients eligible, few patients benefit outside of well-known drivers in specific cancers
- Small no. of available targeted drugs - Limits to the impact of single targeted drugs, given
cancer heterogeneity and redundancy of cell signaling - Toxicity of combinations- Lack of clinical evidence of benefits and increased
costs to health care
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What more can Systems Medicine do?
TCGA Weinstein et al., Nature Genetics 45, 1113–1120, 2013
Deep molecular profiling Deep functional profiling
Pemovska T et al., Cancer Disc 3:1416-1429, 2013Yadav B et al., Sci Rep 4:5193, 2014Pemovska T et al., Nature 7541:102-105, 2015Saeed K et al., Eur J Urol , May 5, 2017Ojamies P et al., Leukemia, 31 Oct 31, 2017Malani D et al., Leukemia, May 31, 2017
Ex vivo drug sensitivity as a proxyfor clinical efficacy of drugs
Deep functional profiling of PDCs
Clinical Precision Medicine
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Real‐time translation of systems biology/ systems medicine data
US National Academy of Sciences 2012
Can weprovidesystemsbiology
informationto the clinic
that mayhelp real-time withtreatmentdecisions?
Usuallytranslation of research to
the clinictakes a
decade or so
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Elements assembled to take precision systems medicine to the clinical setting
Genomics & othertechnologies
Individualized and improved cancer therapy
Ex‐vivo drug testing(clinical trial on a dish)Clinical
expertise& data
Clinicallaboratory
Biomedicalexpertise
Bioinformatics /decision support
CompaniesClinical trials
Patient
EthicalLegal
Regulatory
Team scienceReal‐time translation
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Drug sensitivity and resistance profiling (DSRT) Platform: High-throughput, nanoliter-scale drug testing of patient-derived cells (PDCs)
Viability / Toxicity by CellTiter-Glo / CellTox
Perc
ent i
nhib
ition
Drug concentration
Slope
Drug Sensitivity Score (DSS)
High throughput high-content image-based screens
100’s of PhenotypesOpera Phenix
Fresh material, expansion, single cell suspension
1-10000 nM dose response curves
525 oncology drugs149 approved drugs376 investigational drugs- conventional chemotherapeutics- hormone therapy drugs- kinase inhibitors- epigenetic/differentiating drugs- other targeted drugs- immunosuppressants
canc
erbe
nign
Leukemia sample
Solid tumors
Nanoliter acoustics
iQue HD 384 well FACS screens
Flow cytometry
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Detailed dose-response curves for all oncology drugs and many
emerging cancer compoundsfor individual patient cell samples
02/10/2018
Pharmacopeia-wide drug sensitivity and resistance testing with dose-response curves for each drug
319
149
Investigational Clinical drugs
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Pharmacopeia-wide drug sensitivity and resistance testing (DSRT) of patients’ cancer cells: data analysis
Drug testing of patients’ cells ex vivo
Comparative efficacydata for 540 drugs
Comparing the same drug across different patients
Cross- comparingdrugs andpatients
Comparing different drugs in one patient
Identification of responsebiomarkers
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Big data management, integration and rapid interpretation needed to give real-time feedback to the clinic
Drug sensitivity testing Exome sequencing
Gene expression Phosphoproteomics Fusion genes
Integration, Interpretation Feedback to clinic
(4 days to 2 weeks)n=1
Integration, Interpretation Feedback to clinic
(4 days to 2 weeks)n=1
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2071 800
997
393_
339
3_1
1064
1145
_111
45_6 313
1534
1067
1993 693
801
252_
313
4620
9511
45_3 542
250
1054
1280
600_
322
00 718
2080 410
1867
1690
4701
001
784_
265
178
4_1
600_
114
9711
3225
2_5
252_
256
0_1
155
252_
160
0_2
560_
914
08_1
1278
05
1015202530
DSS
Axitinib
AML patient samples
T315I mutated patient samplesPh+ patient samples
Healthy control samples
KinaseAxitinibKd (nM)
ABL1 36ABL1(T315I) 1.5ABL1(H396P) 20ABL1(M351T) 36ABL1(E255K) 63ABL1(Y253F) 230ABL1(F317I) 800
VEGFR2 5.9
1. Drug efficacy in a subgroup ex‐vivo:‐ T315I gate‐keeper mutation in BCR‐ABL‐ Resistance to ABL inhibitors
2. Molecularmechanisms
3. Clinical proof of concept
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Individualized Systems Medicine study of 164 consecutive AML samples
Biology of AML
Re-positioningcancer drugs
New drug effectsand biomarkers
Therapy insight
(Acute Myeloid Leukemia)
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some conclusions in AML
so far...
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VenetoclaxOmipalisibNavitoclaxAZD8055
DexamethasonePF-04691502
AZD2014BIIB021
OmacetaxineZSTK474
RalimetinibMocetinostat
PictilisibINK128
DoramapimodSNS-032
TeniposideMethylprednisolone
LuminespibEntinostat
CamptotechinTretinoin
PomalidomideDeferoxamine aq
TrametinibMK1775
BosutinibCrenolanib
AT 101SelumetinibDanusertib
Chloroquine aqDocetaxel
MidostaurinC646
DasatinibNintedanibPaclitaxel
StatticPF477736
-15-10 -5 0 5 10 15 20 25 30 35
CTG_sDSS
Subgroup responding to glucocorticoids
Clinical Proof of concept:
Opportunities to reposition existing cancer drugsIn biomarker-defined subgroups
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AML therapies in patients often eliminate cancer subclones, but new clones emerge and cause resistance and relapse
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706: PHF6 A>G variant at relapse after filtering
Freq: 0.5%Variant coverage: 67/12468 reads
Variantposition
0
300
600
900
1200
1 11 21 31 41 51 61 71 81 91 101
111
121
131
141
151
161
171
181
191
201
211
221
231
241
251
261
271
G
A
C
T
0
20
40
60
80
100
1 11 21 31 41 51 61 71 81 91 101
111
121
131
141
151
161
171
181
191
201
211
221
231
241
251
261
271
Abs
olut
e re
ad c
ount
16 relapse-associated mutations identified before treatment (at frequencies of 0,54-2%) that were not detected by exome sequencing
Drug-resistance arises from pre-existing rare cell variants
45
30
0
31
42
0,8 0
10
20
30
40
50
60
70
706_Diagnosis_2011 706_Relapse_2013
PHF6
TET2_2
TET2_1, DNMT3A,
INPPA4, DLEC1
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What next?
Refinement and consistency of the functional assays and cell models
Clinical trials based on systems medicine (and ex-vivo drug sensitivity / trial on a dish) in a pan-Nordic / pan-EU / global setting
Precision systems medicine POCs in solid tumors (ovarian cancer)
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42
Astrid Murumägi, Ralf Butzov et al.,
Progenitor cells isolated from ovarian cancer ascites for functional drug testing
Excellent representation of genomics between conditionally reprogrammed cells ex vivo and patient’s primary tumor
02/10/2018
Both Primary tumor sample from 2012 (FFPE) and conditionally reprogrammed cells carry KRAS (G12V) hotspot mutation and TP53 (S215N) mutation
Precision Systems Cancer Medicine: Ovarian cancer
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Senior scientists: Päivi Östling, Vilja Pietiäinen, Teijo Pellinen, Astrid Murumägi, Brinton Seashore-Ludlow
Collaborators & PIs @ FIMM:- Kimmo Porkka- Satu Mustjoki- Caroline Heckman- Krister Wennerberg- Tero Aittokallio- Jing Tang- FIMM TC Platforms
Collaborators / SciLifeLab/KI:- Sören Lehman- Janne Lehtiö- Thomas Helleday- Yudi Pawitan- SciLifeLab platforms
AML 2.0 data team:Disha MalaniAshwini KumarBhagwan Yadav
Acknowledgements
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Thank You for Your Attention!Thank You for Your Attention!