bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown
Опубликована: Июль 4, 2024
Cells exhibit a wide array of morphological features, enabling computer vision methods to identify and track relevant parameters. Morphological analysis has long been implemented specific cell types responses. Here we asked whether features might also be used classify transcriptomic subpopulations within
Язык: Английский
Discover Oncology, Год журнала: 2024, Номер 15(1)
Опубликована: Авг. 11, 2024
Novel therapeutic agents in clinical trials offer a paradigm shift the approach to battling this prevalent and destructive disease, area of cancer therapy is on precipice trans formative revolution. Despite importance tried-and-true treatments like surgery, radiation, chemotherapy, disease continues evolve adapt, making new, more potent methods necessary. The field currently witnessing emergence wide range innovative approaches. Immunotherapy, including checkpoint inhibitors, CAR-T cell treatment, vaccines, utilizes host's immune system selectively target eradicate malignant cells while minimizing harm normal tissue. development targeted medicines kinase inhibitors monoclonal antibodies has allowed for less harmful approaches treating cancer. With help genomics molecular profiling, "precision medicine" customizes therapies each patient's unique genetic makeup maximize efficacy unwanted side effects. Epigenetic therapies, metabolic interventions, radio-pharmaceuticals, an increasing emphasis combination with synergistic effects further broaden landscape. Multiple-stage are essential determining safety these novel drugs, allowing patients gain access also furthering scientific understanding. future rife promise, as integration artificial intelligence big data potential revolutionize early detection prevention. Collaboration among researchers, healthcare providers, active involvement remain bedrock ongoing battle against In conclusion, dynamic evolving landscape provides hope improved treatment outcomes, emphasizing patient-centered, data-driven, ethically grounded we collectively strive towards cancer-free world.
Язык: Английский
Процитировано
29
Cancer Research, Год журнала: 2024, Номер 84(11), С. 1929 - 1941
Опубликована: Апрель 3, 2024
Standard-of-care treatment regimens have long been designed for maximal cell killing, yet these strategies often fail when applied to metastatic cancers due the emergence of drug resistance. Adaptive developed as an alternative approach, dynamically adjusting suppress growth treatment-resistant populations and thereby delay, or even prevent, tumor progression. Promising clinical results in prostate cancer indicate potential optimize adaptive protocols. Here, we deep reinforcement learning (DRL) guide scheduling demonstrated that schedules can outperform current protocols a mathematical model calibrated dynamics, more than doubling time The DRL were robust patient variability, including both dynamics monitoring schedules. framework could produce interpretable, based on single burden threshold, replicating informing optimal strategies. had no knowledge underlying model, demonstrating capability help develop novel complex settings. Finally, proposed five-step pathway, which combined mechanistic modeling with integrated conventional tools improve interpretability compared traditional "black-box" models, allow translation this approach clinic. Overall, generated personalized consistently outperformed standard-of-care
Язык: Английский
Процитировано
16
Cell Systems, Год журнала: 2024, Номер 15(6), С. 510 - 525.e6
Опубликована: Май 20, 2024
Язык: Английский
Процитировано
8
Frontiers in Physiology, Год журнала: 2024, Номер 15
Опубликована: Окт. 23, 2024
Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics sequencing technologies have paved way for unraveling this heterogeneity. Nevertheless, complexity data gathered from these methods cannot be fully interpreted through multimodal analysis alone. Mathematical modeling plays a crucial role delineating underlying mechanisms to explain sources heterogeneity using patient-specific data. Intra-tumoral diversity necessitates development precision oncology therapies utilizing multiphysics, multiscale mathematical models cancer. This review discusses recent advancements computational methodologies oncology, highlighting potential cancer digital twins enhance decision-making clinical settings. We efforts building patient-informed cellular tissue-level propose framework that utilizes agent-based an effective conduit integrate systems encode signaling at scale with twin predict response tumor microenvironment customized patient information. Furthermore, we discuss machine learning approaches surrogates complex models. These can potentially used conduct sensitivity analysis, verification, validation, uncertainty quantification, is especially important studies due their dynamic nature.
Язык: Английский
Процитировано
7
Clinical Oncology, Год журнала: 2025, Номер 41, С. 103793 - 103793
Опубликована: Фев. 25, 2025
Язык: Английский
Процитировано
1
Computers & Industrial Engineering, Год журнала: 2024, Номер 191, С. 110078 - 110078
Опубликована: Март 24, 2024
Cancer is a leading cause of death and cost burden on healthcare systems worldwide. The mainstay treatment chemotherapy which most often administered empirically. Optimizing the frequency drug administration would benefit patients by avoiding overtreatment reducing costs. In this work, optimization regimens using mathematical programming techniques demonstrated developing simple model for fictitious drug. question to be answered solution how should so that tumor size does not exceed predefined reaches minimum value. proposed computer-implemented well-established system, thus keeping effort obtaining results low. An example used demonstrate superiority approach over approach.
Язык: Английский
Процитировано
6
Deleted Journal, Год журнала: 2024, Номер 1(1)
Опубликована: Авг. 1, 2024
Abstract Antifragility characterizes the benefit of a dynamical system derived from variability in environmental perturbations. carries precise definition that quantifies system’s output response to input variability. Systems may respond poorly perturbations (fragile) or (antifragile). In this manuscript, we review range applications antifragility theory technical systems (e.g., traffic control, robotics) and natural cancer therapy, antibiotics). While there is broad overlap methods used quantify apply across disciplines, need for precisely defining scales at which operates. Thus, provide brief general introduction properties applied relevant literature both systems’ antifragility. We frame within three common systems: intrinsic (input–output nonlinearity), inherited (extrinsic signals), induced (feedback control), with associated counterparts biological ecological (homogeneous systems), evolutionary (heterogeneous interventional (control). use noun designing exhibit antifragile behavior guide reader along spectrum fragility–adaptiveness–resilience–robustness–antifragility, principles behind it, its practical implications.
Язык: Английский
Процитировано
4
Cancer Control, Год журнала: 2024, Номер 31
Опубликована: Янв. 1, 2024
Cancer treatment optimizations select the most optimum combinations of drugs, sequencing schedules, and appropriate doses that would limit toxicity yield an improved patient quality life. However, these often lack adequate consideration cancer's near-infinite potential for evolutionary adaptation to therapeutic interventions. Adapting cancer therapy based on monitored tumor burden clonal composition is intuitively sound approach as inherently complex adaptive system. The be driven by clinical outcome setpoints embodying aims thwart resistance maintain a long-term management disease or even cure. given nonlinear, stochastic dynamics response interventions, strategies may at least need one-step-ahead prediction their control over growth dynamics. article explores feasibility state feedback assuming cell fitness underlying source phenotypic plasticity pathway entropy biomarker trajectory. exploration undertaken using deterministic models
Язык: Английский
Процитировано
3
PLoS Computational Biology, Год журнала: 2025, Номер 21(2), С. e1012815 - e1012815
Опубликована: Фев. 14, 2025
Biological and dynamic mechanisms by which Drug-tolerant persister (DTP) cells contribute to the development of acquired drug resistance have not been fully elucidated. Here, integrating multidimensional data from drug-treated PC9 cells, we developed a novel multiscale mathematical model an evolutionary perspective that encompasses epigenetic cellular population dynamics. By coupling stochastic simulation with quantitative analysis, identified instability as most prominent kinetic feature related emergence DTP cell subpopulations effectiveness intermittent treatment. Moreover, revealed optimal schedule for treatment, including area therapeutic time holidays. leveraging single-cell RNA-seq characterizing tolerance lung cancer, validated predictions made our further previously unrecognized biological features such autophagy migration, well new biomarker genes tolerance. Our work only provides paradigm integration models newly emerging genomics but also improves understanding crucial roles offers guidance developing treatment strategies against in cancer.
Язык: Английский
Процитировано
0
bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown
Опубликована: Фев. 17, 2025
SUMMARY Adaptive therapy (AT) improves cancer treatment by controlling the competition between sensitive and resistant cells via holidays. This study highlights critical role of treatment-pausing thresholds in AT for tumors composed drug-sensitive cells. Using a Lotka-Volterra model, research compares with maximum tolerated dose intermittent therapy, showing that AT’s success largely depends on threshold at which is paused resumed, as well Three scenarios comparison others are identified: uniform-decline, conditionalimprove, uniform-improve, illustrating optimizing crucial effectiveness. Tumor composition, including initial tumor burden proportion cells, influences outcomes. Adjusting values enables to suppress subclones, preserving ultimately improving progression-free survival. These findings underscore importance personalized strategies management enhancing long-term therapeutic
Язык: Английский
Процитировано
0