Purpose: Integration of evolutionary dynamics into systemic therapy for metastatic cancers can prolong tumor control compared with standard maximum tolerated dose (MTD) strategies. Prior investigations have focused on monotherapy, but many clinical cancer treatments combine two or more drugs. Optimizing the evolutionary dynamics in multidrug therapy is challenging because of the complex cellular interactions and the large parameter space of potential variations in drugs, doses, and treatment schedules. However, multidrug therapy also represents an opportunity to further improve outcomes using evolution-based strategies.
Experimental Design: We examine evolution-based strategies for two-drug therapy and identify an approach that divides the treatment drugs into primary and secondary roles. The primary drug has the greatest efficacy and/or lowest toxicity. The secondary drug is applied solely to reduce the resistant population to the primary drug.
Results: Simulations from the mathematical model demonstrate that the primary-secondary approach increases time to progression (TTP) compared with conventional strategies in which drugs are administered without regard to evolutionary dynamics. We apply our model to an ongoing adaptive therapy clinical trial of evolution-based administration of abiraterone to treat metastatic castrate-resistant prostate cancer. Model simulations, parameterized with data from individual patients who progressed, demonstrate that strategic application of docetaxel during abiraterone therapy would have significantly increased their TTP.
Conclusions: Mathematical models can integrate evolutionary dynamics into multidrug cancer clinical trials. This has the potential to improve outcomes and to develop clinical trials in which these mathematical models are also used to estimate the mechanism(s) of treatment failure and explore alternative strategies to improve outcomes in future trials.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6665681 | PMC |
| http://dx.doi.org/10.1158/1078-0432.CCR-19-0006 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Exploration of the genetic landscape of bacterial dsDNA viruses reveals an ANI gap amid extensive mosaicism.
mSystems
January 2025
Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.
Average nucleotide identity (ANI) is a widely used metric to estimate genetic relatedness, especially in microbial species delineation. While ANI calculation has been well optimized for bacteria and closely related viral genomes, accurate estimation of ANI below 80%, particularly in large reference data sets, has been challenging due to a lack of accurate and scalable methods. To bridge this gap, we introduce MANIAC, an efficient computational pipeline optimized for estimating ANI and alignment fraction (AF) in viral genomes with divergence around ANI of 70%.
View Article and Find Full Text PDFCan spatial self-organization inhibit evolutionary adaptation?
J R Soc Interface
January 2025
The Swiss Institute for Dryland Environmental and Energy Research, BIDR, Ben-Gurion University of the Negev, Midreshet Ben-Gurion 8499000, Israel.
Plants often respond to drier climates by slow evolutionary adaptations from fast-growing to stress-tolerant species. These evolutionary adaptations increase the plants' resilience to droughts but involve productivity losses that bear on agriculture and food security. Plants also respond by spatial self-organization, through fast vegetation patterning involving differential plant mortality and increased water availability to the surviving plants.
View Article and Find Full Text PDFA network-enabled pipeline for gene discovery and validation in non-model plant species.
Cell Rep Methods
January 2025
MSU-DOE Plant Research Lab, Michigan State University, East Lansing, MI 48824, USA; Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA; Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI 48824, USA. Electronic address:
Identifying key regulators of important genes in non-model crop species is challenging due to limited multi-omics resources. To address this, we introduce the network-enabled gene discovery pipeline NEEDLE, a user-friendly tool that systematically generates coexpression gene network modules, measures gene connectivity, and establishes network hierarchy to pinpoint key transcriptional regulators from dynamic transcriptome datasets. After validating its accuracy with two independent datasets, we applied NEEDLE to identify transcription factors (TFs) regulating the expression of cellulose synthase-like F6 (CSLF6), a crucial cell wall biosynthetic gene, in Brachypodium and sorghum.
View Article and Find Full Text PDFWeb Visualization for Spatiotemporal Genomic Epidemiology, Annotation, and Mutation Dynamics of Orthohantavirus hantanense Using Nextstrain.
Am J Trop Med Hyg
January 2025
Department of Microbiology, Korea University College of Medicine, Seoul, Republic of Korea.
The phylogeographic inference approach aims to connect genomic data with epidemiology to understand the spread and evolution of pathogens using visualization of spatiotemporal reconstructions. Orthohantavirus hantanense (HTNV), the causative agent of hemorrhagic fever with renal syndrome (HFRS), represents a significant global public health concern. Here, we introduce a localized Nextstrain platform for HTNV, offering a comprehensive resource for facilitating spatiotemporal genomic surveillance and the study of evolutionary dynamics of viral genomes.
View Article and Find Full Text PDFEnzymes in a human cytoplasm model organize into submetabolon complexes.
Proc Natl Acad Sci U S A
February 2025
Department of Chemistry, University of Illinois Urbana-Champaign, Urbana, IL 61801.
Enzyme-enzyme interactions are fundamental to the function of cells. Their atomistic mechanisms remain elusive mainly due to limitations of in-cell measurements. We address this challenge by atomistically modeling, for a total of ≈80 μs, a slice of the human cell cytoplasm that includes three successive enzymes along the glycolytic pathway: glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), and phosphoglycerate mutase (PGM).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!