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Schmid JA, Festl Y, Severin Y, Bacher U, Kronig MN, Snijder B, Pabst T. Efficacy and feasibility of pharmacoscopy-guided treatment for acute myeloid leukemia patients who have exhausted all registered therapeutic options. Haematologica 2024; 109:617-621. [PMID: 37439341 PMCID: PMC10828754 DOI: 10.3324/haematol.2023.283224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 07/06/2023] [Indexed: 07/14/2023] Open
Affiliation(s)
| | - Yasmin Festl
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich
| | - Yannik Severin
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich
| | - Ulrike Bacher
- Department of Hematology; Inselspital, University Hospital Bern, University of Bern, Bern
| | - Marie-Noëlle Kronig
- Department of Medical Oncology; Inselspital, University Hospital Bern, University of Bern, Bern
| | - Berend Snijder
- Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, Zürich.
| | - Thomas Pabst
- Department of Medical Oncology; Inselspital, University Hospital Bern, University of Bern, Bern
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2
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Chen Y, He L, Ianevski A, Ayuda-Durán P, Potdar S, Saarela J, Miettinen JJ, Kytölä S, Miettinen S, Manninen M, Heckman CA, Enserink JM, Wennerberg K, Aittokallio T. Robust scoring of selective drug responses for patient-tailored therapy selection. Nat Protoc 2024; 19:60-82. [PMID: 37996540 DOI: 10.1038/s41596-023-00903-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 08/10/2023] [Indexed: 11/25/2023]
Abstract
Most patients with advanced malignancies are treated with severely toxic, first-line chemotherapies. Personalized treatment strategies have led to improved patient outcomes and could replace one-size-fits-all therapies, yet they need to be tailored by testing of a range of targeted drugs in primary patient cells. Most functional precision medicine studies use simple drug-response metrics, which cannot quantify the selective effects of drugs (i.e., the differential responses of cancer cells and normal cells). We developed a computational method for selective drug-sensitivity scoring (DSS), which enables normalization of the individual patient's responses against normal cell responses. The selective response scoring uses the inhibition of noncancerous cells as a proxy for potential drug toxicity, which can in turn be used to identify effective and safer treatment options. Here, we explain how to apply the selective DSS calculation for guiding precision medicine in patients with leukemia treated across three cancer centers in Europe and the USA; the generic methods are also widely applicable to other malignancies that are amenable to drug testing. The open-source and extendable R-codes provide a robust means to tailor personalized treatment strategies on the basis of increasingly available ex vivo drug-testing data from patients in real-world and clinical trial settings. We also make available drug-response profiles to 527 anticancer compounds tested in 10 healthy bone marrow samples as reference data for selective scoring and de-prioritization of drugs that show broadly toxic effects. The procedure takes <60 min and requires basic skills in R.
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Affiliation(s)
- Yingjia Chen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Liye He
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Aleksandr Ianevski
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Pilar Ayuda-Durán
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Swapnil Potdar
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Jani Saarela
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Juho J Miettinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sari Kytölä
- Department of Hematology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland
| | - Susanna Miettinen
- Adult Stem Cell Group, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Research, Development and Innovation Centre, Tampere University Hospital, Tampere, Finland
| | | | - Caroline A Heckman
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jorrit M Enserink
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Section for Biochemistry and Molecular Biology, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Krister Wennerberg
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Tero Aittokallio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
- iCAN Digital Precision Cancer Medicine Flagship, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
- Centre for Biostatistics and Epidemiology (OCBE), Faculty of Medicine, University of Oslo, Oslo, Norway.
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3
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Ayuda-Durán P, Hermansen JU, Giliberto M, Yin Y, Hanes R, Gordon S, Kuusanmäki H, Brodersen AM, Andersen AN, Taskén K, Wennerberg K, Enserink JM, Skånland SS. Standardized assays to monitor drug sensitivity in hematologic cancers. Cell Death Discov 2023; 9:435. [PMID: 38040674 PMCID: PMC10692209 DOI: 10.1038/s41420-023-01722-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 10/21/2023] [Accepted: 11/13/2023] [Indexed: 12/03/2023] Open
Abstract
The principle of drug sensitivity testing is to expose cancer cells to a library of different drugs and measure its effects on cell viability. Recent technological advances, continuous approval of targeted therapies, and improved cell culture protocols have enhanced the precision and clinical relevance of such screens. Indeed, drug sensitivity testing has proven diagnostically valuable for patients with advanced hematologic cancers. However, different cell types behave differently in culture and therefore require optimized drug screening protocols to ensure that their ex vivo drug sensitivity accurately reflects in vivo drug responses. For example, primary chronic lymphocytic leukemia (CLL) and multiple myeloma (MM) cells require unique microenvironmental stimuli to survive in culture, while this is less the case for acute myeloid leukemia (AML) cells. Here, we present our optimized and validated protocols for culturing and drug screening of primary cells from AML, CLL, and MM patients, and a generic protocol for cell line models. We also discuss drug library designs, reproducibility, and quality controls. We envision that these protocols may serve as community guidelines for the use and interpretation of assays to monitor drug sensitivity in hematologic cancers and thus contribute to standardization. The read-outs may provide insight into tumor biology, identify or confirm treatment resistance and sensitivity in real time, and ultimately guide clinical decision-making.
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Affiliation(s)
- Pilar Ayuda-Durán
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Johanne U Hermansen
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Mariaserena Giliberto
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Yanping Yin
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Haematology, Oslo University Hospital, Oslo, Norway
| | - Robert Hanes
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Section for Biochemistry and Molecular Biology, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Sandra Gordon
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Heikki Kuusanmäki
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Andrea M Brodersen
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Section for Biochemistry and Molecular Biology, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Aram N Andersen
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Section for Biochemistry and Molecular Biology, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Kjetil Taskén
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- K. G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Krister Wennerberg
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
| | - Jorrit M Enserink
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
- Section for Biochemistry and Molecular Biology, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - Sigrid S Skånland
- Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
- K. G. Jebsen Centre for B Cell Malignancies, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
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4
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Kropivsek K, Kachel P, Goetze S, Wegmann R, Festl Y, Severin Y, Hale BD, Mena J, van Drogen A, Dietliker N, Tchinda J, Wollscheid B, Manz MG, Snijder B. Ex vivo drug response heterogeneity reveals personalized therapeutic strategies for patients with multiple myeloma. NATURE CANCER 2023; 4:734-753. [PMID: 37081258 DOI: 10.1038/s43018-023-00544-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 03/17/2023] [Indexed: 04/22/2023]
Abstract
Multiple myeloma (MM) is a plasma cell malignancy defined by complex genetics and extensive patient heterogeneity. Despite a growing arsenal of approved therapies, MM remains incurable and in need of guidelines to identify effective personalized treatments. Here, we survey the ex vivo drug and immunotherapy sensitivities across 101 bone marrow samples from 70 patients with MM using multiplexed immunofluorescence, automated microscopy and deep-learning-based single-cell phenotyping. Combined with sample-matched genetics, proteotyping and cytokine profiling, we map the molecular regulatory network of drug sensitivity, implicating the DNA repair pathway and EYA3 expression in proteasome inhibitor sensitivity and major histocompatibility complex class II expression in the response to elotuzumab. Globally, ex vivo drug sensitivity associated with bone marrow microenvironmental signatures reflecting treatment stage, clonality and inflammation. Furthermore, ex vivo drug sensitivity significantly stratified clinical treatment responses, including to immunotherapy. Taken together, our study provides molecular and actionable insights into diverse treatment strategies for patients with MM.
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Affiliation(s)
- Klara Kropivsek
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Paul Kachel
- Department of Medical Oncology and Hematology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Sandra Goetze
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Swiss Multi-Omics Center, PHRT-CPAC, ETH Zurich, Zurich, Switzerland
| | - Rebekka Wegmann
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Yasmin Festl
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Yannik Severin
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Benjamin D Hale
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Julien Mena
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Audrey van Drogen
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Swiss Multi-Omics Center, PHRT-CPAC, ETH Zurich, Zurich, Switzerland
| | - Nadja Dietliker
- Department of Medical Oncology and Hematology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Joëlle Tchinda
- Pediatric Oncology, Children's Research Centre, University Children's Hospital Zurich, Zurich, Switzerland
| | - Bernd Wollscheid
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute of Translational Medicine, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Swiss Multi-Omics Center, PHRT-CPAC, ETH Zurich, Zurich, Switzerland
| | - Markus G Manz
- Department of Medical Oncology and Hematology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
- Comprehensive Cancer Center Zurich (CCCZ), Zurich, Switzerland
| | - Berend Snijder
- Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, Zurich, Switzerland.
- Swiss Institute of Bioinformatics, Lausanne, Switzerland.
- Comprehensive Cancer Center Zurich (CCCZ), Zurich, Switzerland.
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5
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Duran-Frigola M, Cigler M, Winter GE. Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence. J Am Chem Soc 2023; 145:2711-2732. [PMID: 36706315 PMCID: PMC9912273 DOI: 10.1021/jacs.2c11098] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) promises to overcome some of these limitations. In brief, TPD is dependent on small molecules that induce the proximity between a protein of interest (POI) and an E3 ubiquitin ligase, causing ubiquitination and degradation of the POI. In this perspective, we want to reflect on current challenges in the field, and discuss how advances in multiomics profiling, artificial intelligence, and machine learning (AI/ML) will be vital in overcoming them. The presented roadmap is discussed in the context of small-molecule degraders but is equally applicable for other emerging proximity-inducing modalities.
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Affiliation(s)
- Miquel Duran-Frigola
- CeMM
Research Center for Molecular Medicine of the Austrian Academy of
Sciences, 1090 Vienna, Austria,Ersilia
Open Source Initiative, 28 Belgrave Road, CB1 3DE, Cambridge, United Kingdom,
| | - Marko Cigler
- CeMM
Research Center for Molecular Medicine of the Austrian Academy of
Sciences, 1090 Vienna, Austria
| | - Georg E. Winter
- CeMM
Research Center for Molecular Medicine of the Austrian Academy of
Sciences, 1090 Vienna, Austria,
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