Syövät pirstaloituvat: haaste hoidon kehitykselle Kimmo Porkka Professor, head of division hematology Helsinki University Central Hospital Helsinki, Finland
Syövän heterogeenisyys: esimerkkinä akuutti myelooinen leukemia (AML) Harvinainen sairaus; 50 potilasta/vuosi 10-70% paranee intensiivisellä solunsalpaajahoidolla ja allogeenisella kantasolujensiirrolla Ei täsmähoitoja (poikkeus APL) Molekylaarinen patogeneesi tunnettu genomitasolla (2013-2014)
AML classification in 2010 (European Leukemianet, CN) Blood 2010, Vol. 115, No. 3, pp. 453-474.
Koko genomin/eksomin/transkriptomin sekvensointi
AML:n genomiikka 2013 T. Ley ASH2012
Added complexity: within-patient, time- and therapy-dependent clonal heterogeneity Ding et al. Nature 2012
AML challenge for conventional drug studies 100 newly diagnosed AML patients AML genotype 3 AML genotype 7 AML genotype 1 AML genotype 5 AML genotype 2 AML genotype 6 AML genotype 100 AML genotype 98 AML genotype 99 New drug 1: Phase I-II (n=10-40) Response rate 2/100= 2% Study fail End development
Goal 201x AML diagnosis Personalized therapy machine Patient-specific drug list AML in remission
Finnish Hematology Registry and Biobank (FHRB) Registry FHRB = + Biobank hematology.fi/fhrb
Patient consent Sample, data collection Hospitals FHRB 30 ml blood, 30 ml bone marrow, skin biopsy (opt.) at diagnosis, remission (opt.), relapses all university and central hospitals (n=21) Sample processing Finnish Red Cross Blood Service (centralized) Biobanking FIMM FAH Clinical registry Experiments, discovery Research groups Clinical applications Diagnostics Imaging Targeted therapies
FHRB: Samples biobanked/patient Ca. 50 Hematology sample Research Unit Helsinki tubes/patient/sampling: all stored in LN 2
FHRB: biobanking timeline Started in Helsinki Dec 5, 2012; currently all newly-diagnosed and relapse patients sampled (acute leukemias, MDS, myeloma, MPN, CLL, CML) All university hospitals (Helsinki, Turku, Tampere, Oulu, Kuopio) collecting samples, All other hospitals treating hematological patients by the end of 2014 Part of clinical care of the patients (453 /sample) 1000-1500 patients/year (50-75.000 samples/year)
Goal 201x AML diagnosis Personalized therapy machine Patient-specific drug list AML in remission
Reversing molecular drug discovery Genome/transcriptome-driven Molecular profiling of leukemic cells Disease-associated genomic variants - Rarely directly clinically actionable Molecularly targeted therapies - 3-10+ years Drug-response phenotype-driven Drug response profiling of leukemic cells Disease-associated drug responses Molecularly dissection of drug response Molecularly targeted therapies - Often directly clinically actionable - Unbiased - Drug repurposing - 1-5+ years
Individualized systems medicine platform/helsinki Sampling Methods Results Outcome Drug sensitivity and resistance testing (DSRT) - 664 anti-cancer agents and targeted inhibitors Resistant drugs Effective drugs Individualized drug combinations Diagnosis Relapse 1 Relapse 2 Molecular profiling - Genome - Transcriptome - Signalome Patient specific treatment recommendations Database and treatment decision system Understanding drug resistance Clonal evolution, mutations, signaling Implementation and translation +
Leukemia sample work flow FIMM Hematology Clinic FIMM DSRT 4 days Proteomics 2 days 1 h 1 day FHRB NGS 3-4 weeks Sample collection Bone marrow aspirate Peripheral blood Skin biopsy Biobanking Sample processing Mononuclear cell separation Protein lysates DNA extraction RNA extraction Sample analysis Drug screening Phospho-protein analysis Whole genome/exome sequencing RNA sequencing
DSRT reporting as waterfall plots Resistant drugs Effective drugs
Patient example FHRB.600: - primary chemorefractory AML (failure to 3 induction regimens) DSRT AND MOLECULAR PROFILING RESULTS
FHRB.600: DSRT and treatment response In vivo Dasatinib Sunitinib Diarrhea perineal infection RNAseq: NUP98-NSD1 fusion Temsirolimus
At relapse, a total loss of drug sensitivity ex vivo (and in vivo) After DSRT-targeted therapy Before DSRT-targeted therapy
Yhteenveto Syövän patogeneesi on hyvin heterogeeninen => jako yhä pienempiin alaluokkiin => konventionaalinen lääketutkimus (Faasi I-III) vaikeaa/mahdotonta Lähivuosina monen syövän geneettinen tausta kartoitetaan; funktionaaliseen ymmärtämiseen ja rationaaliseen lääkekehitykseen kuitenkin pidempi matka Yksilöllistetty tutkimus ja hoito on kehityksen avain biopankit keskeinen työkalu Lääketeollisuudelta vaaditaan uutta ajattelutapaa ja innovaatioita lääkekehityksen nopeuttamiseksi
Kiitokset: FHRB Hallitus Vesa Lindström Maija Itälä-Remes Sari Tiitinen Elina Honkavaara Henna Jalovaara Outi Huoponen Eeva Mainio Kari Aranko Kimmo Pitkänen Janna Saarela Caroline Heckman Tiina Vesterinen Kyösti Sutinen Olli Kallioniemi Anssi Nykänen http://www.hematology.fi/fhrb
Kiitokset: AML personalized medicine FIMM Pesonalized Cancer Medicine Caroline Heckman Jonathan Knowles Samuli Eldfors Riikka Karjalainen Jarno Kivioja Ashwini Kumar Heikki Kuusanmäki Muntasir Mamun Majumder Alun Parsons Cancer Systems Medicine Olli Kallioniemi Henrik Edgren Disha Malani John Patrick Mpindi Astrid Murumägi Päivi Östling Chemical Biology Krister Wennerberg Evgeny Kulesskiy Tea Pemovska Laura Turunen Anna Lehto Computational Systems Biology Tero Aittokallio Petteri Hintsanen Agnieszka Szwajda Bhagwan Yadav Technology Center Janna Saarela Pekka Ellonen Maija Lepistö Sonja Lagström Sari Hannula Pirkko Mattila Aino Palva HUCH/HruH Kimmo Porkka Mika Kontro Satu Mustjoki Erkki Elonen Hanna Koskela Mette Ilander Emma Anderson Paavo Pietarinen Jaakko Vartia Tuija Lundán 28 28