Evidence map›Paper›PMID 35132721›Full record

ArticleCell proliferation2022

A multiscale cell-based model of tumor growth for chemotherapy assessment and tumor-targeted therapy through a 3D computational approach.

Sahar Jafari Nivlouei, Madjid Soltani, Ebrahim Shirani, Mohammad Reza Salimpour, Rui Travasso, João Carvalho

Open access · goldAbstract read
In one paragraph

Article in Cell proliferation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 16 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Mathematical Modeling Support for Lung Cancer Therapy-A Short Review.International journal of molecular sciences · 2023
    Review
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 3 countries.

Sahar Jafari NivloueiDepartment of Mechanical Engineering, Isfahan University of Technology, Isafahan, Iran.
Madjid SoltaniDepartment of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.ORCID https://orcid.org/0000-0003-0878-6274
Ebrahim ShiraniDepartment of Mechanical Engineering, Isfahan University of Technology, Isafahan, Iran.
Mohammad Reza SalimpourDepartment of Mechanical Engineering, Isfahan University of Technology, Isafahan, Iran.
Rui TravassoDepartment of Physics, CFisUC, University of Coimbra, Coimbra, Portugal.
João CarvalhoDepartment of Physics, CFisUC, University of Coimbra, Coimbra, Portugal.
Isfahan University of Technology · IRUniversity of Coimbra · PTUniversity of Waterloo · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesComputational modeling of biological systems is a powerful tool to clarify diverse processes contributing to cancer. The aim is to clarify the complex biochemical and mechanical interactions between cells, the relevance of intracellular signaling pathways in tumor progression and related events to the cancer treatments, which are largely ignored in previous studies. MATERIALS AND

methodsA three-dimensional multiscale cell-based model is developed, covering multiple time and spatial scales, including intracellular, cellular, and extracellular processes. The model generates a realistic representation of the processes involved from an implementation of the signaling transduction network.

resultsConsidering a benign tumor development, results are in good agreement with the experimental ones, which identify three different phases in tumor growth. Simulating tumor vascular growth, results predict a highly vascularized tumor morphology in a lobulated form, a consequence of cells' motile behavior. A novel systematic study of chemotherapy intervention, in combination with targeted therapy, is presented to address the capability of the model to evaluate typical clinical protocols. The model also performs a dose comparison study in order to optimize treatment efficacy and surveys the effect of chemotherapy initiation delays and different regimens.

conclusionsResults not only provide detailed insights into tumor progression, but also support suggestions for clinical implementation. This is a major step toward the goal of predicting the effects of not only traditional chemotherapy but also tumor-targeted therapies.

Indexed as

Computer SimulationCell ProliferationHumansModels, BiologicalNeoplasmsNeovascularization, PathologicSignal Transductioncellular Potts modelchemotherapycomputational biologysignaling transductiontargeted therapytumor-induced angiogenesis

Identifiers

PMID35132721
PMCPMC8891571
OpenAlexW4210888315

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.