دورية أكاديمية
Using birth-death processes to infer tumor subpopulation structure from live-cell imaging drug screening data.
| العنوان: | Using birth-death processes to infer tumor subpopulation structure from live-cell imaging drug screening data. |
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| المؤلفون: | Wu C; Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America., Gunnarsson EB; School of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America.; Applied Mathematics Division, Science Institute, University of Iceland, Reykjavík, Iceland., Myklebust EM; Oslo Centre for Biostatistics and Epidemiology, Faculty of Medicine, University of Oslo, Oslo, Norway., Köhn-Luque A; Oslo Centre for Biostatistics and Epidemiology, Faculty of Medicine, University of Oslo, Oslo, Norway.; Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway., Tadele DS; 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.; Department of Medical Genetics, Oslo University Hospital, Oslo, Norway., Enserink JM; 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., Frigessi A; Oslo Centre for Biostatistics and Epidemiology, Faculty of Medicine, University of Oslo, Oslo, Norway., Foo J; School of Mathematics, University of Minnesota, Minneapolis, Minnesota, United States of America., Leder K; Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America. |
| المصدر: | PLoS computational biology [PLoS Comput Biol] 2024 Mar 06; Vol. 20 (3), pp. e1011888. Date of Electronic Publication: 2024 Mar 06 (Print Publication: 2024). |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: San Francisco, CA : Public Library of Science, [2005]- |
| مواضيع طبية MeSH: | Neoplasms*/drug therapy , Neoplasms*/pathology , Genetic Phenomena*, Humans ; Drug Evaluation, Preclinical |
| مستخلص: | Tumor heterogeneity is a complex and widely recognized trait that poses significant challenges in developing effective cancer therapies. In particular, many tumors harbor a variety of subpopulations with distinct therapeutic response characteristics. Characterizing this heterogeneity by determining the subpopulation structure within a tumor enables more precise and successful treatment strategies. In our prior work, we developed PhenoPop, a computational framework for unravelling the drug-response subpopulation structure within a tumor from bulk high-throughput drug screening data. However, the deterministic nature of the underlying models driving PhenoPop restricts the model fit and the information it can extract from the data. As an advancement, we propose a stochastic model based on the linear birth-death process to address this limitation. Our model can formulate a dynamic variance along the horizon of the experiment so that the model uses more information from the data to provide a more robust estimation. In addition, the newly proposed model can be readily adapted to situations where the experimental data exhibits a positive time correlation. We test our model on simulated data (in silico) and experimental data (in vitro), which supports our argument about its advantages. Competing Interests: The authors have declared that no competing interests exist. (Copyright: © 2024 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.) |
| التعليقات: | Update of: ArXiv. 2023 Jun 13;:. (PMID: 37396610) |
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| معلومات مُعتمدة: | R01 CA241137 United States CA NCI NIH HHS |
| تواريخ الأحداث: | Date Created: 20240306 Date Completed: 20240320 Latest Revision: 20240320 |
| رمز التحديث: | 20240320 |
| مُعرف محوري في PubMed: | PMC10947663 |
| DOI: | 10.1371/journal.pcbi.1011888 |
| PMID: | 38446830 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1011888 |