Evidence map›Paper›PMID 30836073›Full record

ReviewJournal of theoretical biology2019

Mathematical modeling of tumor-immune cell interactions.

Grace E Mahlbacher, Kara C Reihmer, Hermann B Frieboes

Abstract readReview
In one paragraph

Review in Journal of theoretical biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
–field-weighted citation impact
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

58 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. [A coupled diffusion-based model of interaction between tumor metastasis and myeloid-derived suppressive cells].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2025
    Article
  8. Gaming the cancer-immunity cycle by synchronizing the dose schedules.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Oscillations in a tumor-immune system interaction model with immune response delay.Mathematical medicine and biology : a journal of the IMA · 2025
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Review
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

3 authors.

Grace E MahlbacherDepartment of Bioengineering, University of Louisville, KY, USA.
Kara C ReihmerDepartment of Bioengineering, University of Louisville, KY, USA.
Hermann B FrieboesDepartment of Bioengineering, University of Louisville, KY, USA; James Graham Brown Cancer Center, University of Louisville, KY, USA; Department of Pharmacology & Toxicology, University of Louisville, KY, USA. Electronic address: hbfrie01@louisville.edu.

Funding

Integrated framework to predict chemotherapy response post lung tumor resectionR15CA203605 · NCI · UNIVERSITY OF LOUISVILLE · PI FRIEBOES, HERMANN · 2016 to 2016
$462k
NCI NIH HHS R15 CA203605
6 · The paper itself

Abstract

The anti-tumor activity of the immune system is increasingly recognized as critical for the mounting of a prolonged and effective response to cancer growth and invasion, and for preventing recurrence following resection or treatment. As the knowledge of tumor-immune cell interactions has advanced, experimental investigation has been complemented by mathematical modeling with the goal to quantify and predict these interactions. This succinct review offers an overview of recent tumor-immune continuum modeling approaches, highlighting spatial models. The focus is on work published in the past decade, incorporating one or more immune cell types and evaluating immune cell effects on tumor progression. Due to their relevance to cancer, the following immune cells and their combinations are described: macrophages, Cytotoxic T Lymphocytes, Natural Killer cells, dendritic cells, T regulatory cells, and CD4+ T helper cells. Although important insight has been gained from a mathematical modeling perspective, the development of models incorporating patient-specific data remains an important goal yet to be realized for potential clinical benefit.

Indexed as

Cell CommunicationModels, BiologicalAnimalsHumansLymphocytesNeoplasmsCancerCancer immunologyCancer immunotherapyComputational simulationImmune systemMathematical modelingOnco-immunotherapyTumor growth

Identifiers

PMID30836073
PMCPMC6579737

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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.