Robust scoring of selective drug responses for patient-tailored therapy selection
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Nature Protocols |
| Vol/bind | 19 |
| Sider (fra-til) | 60-82 |
| ISSN | 1754-2189 |
| DOI | |
| Status | Udgivet - 2024 |
Bibliografisk note
Funding Information:
We are most grateful to the patients and their families for participating in the studies. The authors thank K. Porkka (Helsinki University Hospital, Finland), O. Kallioniemi (Science for Life Laboratory, Sweden) and J. Tyner (Oregon Health & Science University, USA) for making the AML drug testing data openly available. We thank V. Davidsson (University of Helsinki, Finland) for testing the R-codes and procedures; M. Zucknick (University of Oslo, Norway) for discussions about statistical aspects of drug-sensitivity scoring; and S. Skånland (Oslo University Hospital) for discussions about patient drug testing. We thank R. Hanes for bioinformatics assistance and QC analysis, and A. Andersen and A. Brodersen for theoretical input. CSC (IT Center for Science, Finland) is thanked for the computational resources, and the FIMM High-Throughput Biology unit and the NCMM Chemical Biology Platform are thanked for the drug screening. Y.C. received a personal grant from CSC (China) and EDUFI (Finland). L.H. received funding from the Nordic EMBL Partnership Hub for Molecular Medicine (NordForsk grant #96782) and the Cancer Foundation Finland (travel grant). S.M. received funding from the Academy of Finland (grants 336666, 326588, 312413 and 353177) and the Competitive State Research Financing of the Expert Responsibility area of Tampere University Hospital. C.A.H. received funding from the Academy of Finland (grants 1320185 and 334781), the Cancer Foundation Finland and the Sigrid Jusélius Foundation. J.M.E. received funding from the Norwegian Health Authority South-East (HSØ grants 2017064, 2018012 and 2019096), the Norwegian Cancer Society (grants 182524 and 208012) and the Research Council of Norway through its Centers of Excellence funding scheme (grant 262652) and through research grants 261936, 294916 and 314811, and from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 847912 (RESCUER). T.A. received funding from the European Union’s Horizon Europe Research & Innovation programme (REMEDi4ALL project, grant agreement no. 101057442), the European Union’s Horizon 2020 Research and Innovation Programme (ERA PerMed JAKSTAT-TARGET and CLL-CLUE projects), the Academy of Finland (grants 310507, 313267, 326238, 340141, 344698 and 345803), the Norwegian Health Authority South-East (grant 2020026), the Cancer Society of Finland, the Norwegian Cancer Society and the Sigrid Jusélius Foundation. For S.P. and J.S., the FIMM-HTB unit is supported by the University of Helsinki, HiLIFE and the Biocenter Finland.
Funding Information:
S.M. receives research funding from Oncopeptides for work unrelated to the present study. C.A.H. receives research funding from Kronos Bio, Novartis, Oncopeptides, WNTResearch and Zentalis Pharmaceuticals for work unrelated to the present study and honoraria from Amgen. T.A. receives research funding from the European Union’s Horizon Europe Research & Innovation programme under grant agreement no. 101057442. The views and opinions expressed in this document are those of the authors only. They do not necessarily reflect those of the European Union who cannot be held responsible for the information it contains. All the other authors declare no competing interests.
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© 2023, Springer Nature Limited.
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