ArticleJournal of the Royal Society, Interface2017
Cell dynamics in tumour environment after treatments.
Article in Journal of the Royal Society, Interface, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 12 citations in OpenAlex.
- Patient-Specific Mathematical Model of the Clear Cell Renal Cell Carcinoma Microenvironment.Journal of personalized medicine · 2022Article
- A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice.Journal of personalized medicine · 2022Article
- Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model.PLoS computational biology · 2022Article
- A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration.Journal of personalized medicine · 2021Article
- Investigating Optimal Chemotherapy Options for Osteosarcoma Patients through a Mathematical Model.Cells · 2021Article
- Article
- Data-Driven Mathematical Model of Osteosarcoma.Cancers · 2021Article
- Data Driven Mathematical Model of Colon Cancer Progression.Journal of clinical medicine · 2020Article
- The role of backward cell migration in two-hit mutants' production in the stem cell niche.PloS one · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most cancer treatments cause necrotic cell deaths in the tumour microenvironment. Necrotic cells send signals to immune cells to start the wound healing process in the tissue. Therefore, we assume after stopping treatments there is a wound that needs to be healed. We develop a simple computational model to investigate cell dynamics during the wound healing process after treatments. The model predicts that the involvement of high-fitness cancer cells in the wound healing leads to fast relapse, and cancer cells outside of the wound can cause a slow recurrence of the tumour. Therefore, the absence of relapse after treatments may imply a slow-developing tumour that might not reach an observable size in the patients' lifetime. Additionally, the model indicates that the location of remaining cancer cells after treatments is an important factor in the recurrence time. The fastest recurrence happens when high-fitness cancer cells remain inside of the wound. However, the longest time to recurrence corresponds to cancer cells located outside of the wound. Note that this model is the first attempt to study cell dynamics in the wound healing process after cancer treatments, and it has some limitations that might influence the results. Experiments are needed to validate the results.
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.