ReviewCancer research2011
Physical oncology: a bench-to-bedside quantitative and predictive approach.
Review in Cancer research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed, 46 citations in OpenAlex.
- Transport properties of pancreatic cancer describe gemcitabine delivery and response.The Journal of clinical investigation · 2014Trial
- Multicellular Ovarian Cancer Model for Evaluation of Nanovector Delivery in Ascites and Metastatic Environments.Pharmaceutics · 2021Article
- Modeling iontophoretic drug delivery in a microfluidic device.Lab on a chip · 2020Article
- Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.Frontiers in bioengineering and biotechnology · 2020Review
- Mathematical modeling of tumor-immune cell interactions.Journal of theoretical biology · 2019Review
- Predicting breast cancer response to neoadjuvant chemotherapy based on tumor vascular features in needle biopsies.JCI insight · 2019Article
- A Visually Apparent and Quantifiable CT Imaging Feature Identifies Biophysical Subtypes of Pancreatic Ductal Adenocarcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018Article
- Understanding the Connection between Nanoparticle Uptake and Cancer Treatment Efficacy using Mathematical Modeling.Scientific reports · 2018Article
- Simulation of Multispecies Desmoplastic Cancer Growth via a Fully Adaptive Non-linear Full Multigrid Algorithm.Frontiers in physiology · 2018Article
- The role of Allee effect in modelling post resection recurrence of glioblastoma.PLoS computational biology · 2017Article
- Model of vascular desmoplastic multispecies tumor growth.Journal of theoretical biology · 2017Article
- Multiscale biphasic modelling of peritumoural collagen microstructure: The effect of tumour growth on permeability and fluid flow.PloS one · 2017Article
- Multiscale modelling of solid tumour growth: the effect of collagen micromechanics.Biomechanics and modeling in mechanobiology · 2016Article
- Evaluation of uptake and distribution of gold nanoparticles in solid tumors.European physical journal plus · 2015Article
- Diagnostic assessment of osteosarcoma chemoresistance based on Virtual Clinical Trials.Medical hypotheses · 2015Article
- Simulation of the Protein-Shedding Kinetics of a Fully Vascularized Tumor.Cancer informatics · 2015Article
- Tumor growth in complex, evolving microenvironmental geometries: a diffuse domain approach.Journal of theoretical biology · 2014Article
- The effects of cell compressibility, motility and contact inhibition on the growth of tumor cell clusters using the Cellular Potts Model.Journal of theoretical biology · 2014Article
- Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.Frontiers in oncology · 2013Review
- The effect of interstitial pressure on tumor growth: coupling with the blood and lymphatic vascular systems.Journal of theoretical biology · 2013Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
Cancer models relating basic science to clinical care in oncology may fail to address the nuances of tumor behavior and therapy, as in the case, discussed herein, of the complex multiscale dynamics leading to the often-observed enhanced invasiveness, paradoxically induced by the very antiangiogenic therapy designed to destroy the tumor. Studies would benefit from approaches that quantitatively link the multiple physical and temporal scales from molecule to tissue in order to offer outcome predictions for individual patients. Physical oncology is an approach that applies fundamental principles from the physical and biological sciences to explain certain cancer behaviors as observable characteristics arising from the underlying physical and biochemical events. For example, the transport of oxygen molecules through tissue affects phenotypic characteristics such as cell proliferation, apoptosis, and adhesion, which in turn underlie the patient-scale tumor growth and invasiveness. Our review of physical oncology illustrates how tumor behavior and treatment response may be a quantifiable function of marginally stable molecular and/or cellular conditions modulated by inhomogeneity. By incorporating patient-specific genomic, proteomic, metabolomic, and cellular data into multiscale physical models, physical oncology could complement current clinical practice through enhanced understanding of cancer behavior, thus potentially improving patient survival.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.