Evidence map›Paper›PMID 36221111›Full record

ArticleJournal of experimental & clinical cancer research : CR2022

The world's first digital cell twin in cancer electrophysiology: a digital revolution in cancer research?

Christian Baumgartner

Open access · goldAbstract readEditorial
In one paragraph

Article in Journal of experimental & clinical cancer research : CR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

12 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Cancer: A bioelectric disease?Clinical and translational medicine · 2026
    Review
  3. Review
  4. Article
  5. Article
  6. Computational modeling and simulation in oncology.Clinical and translational medicine · 2025
    Article
  7. Review
  8. Review
  9. G protein-coupled receptor digital twins for precision and personalized medicine.Computational and structural biotechnology journal · 2025
    Review
  10. Article
  11. Article
  12. 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

1 author at 1 institution in 1 country.

Christian BaumgartnerInstitute of Health Care Engineering With European Testing Center of Medical Devices, Computational Cancer Electrophysiology Lab, Graz University of Technology, 8010, Graz, Austria. christian.baumgartner@tugraz.at.ORCID http://orcid.org/0000-0002-3763-5195
Graz University of Technology · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe introduction of functional in-silico models, in addition to in-vivo tumor models, opens up new and unlimited possibilities in cancer research and drug development. The world's first digital twin of the A549 cell's electrophysiology in the human lung adenocarcinoma, unveiled in 2021, enables the investigation and evaluation of new research hypotheses about modulating the function of ion channels in the cell membrane, which are important for better understanding cancer development and progression, as well as for developing new drugs and predicting treatments. MAIN BODY: The developed A549 in-silico model allows virtual simulations of the cell's rhythmic oscillation of the membrane potential, which can trigger the transition between cell cycle phases. It is able to predict the promotion or interruption of cell cycle progression provoked by targeted activation and inactivation of ion channels, resulting in abnormal hyper- or depolarization of the membrane potential, a potential key signal for the known cancer hallmarks. For example, model simulations of blockade of transient receptor potential cation channels (TRPC6), which are highly expressed during S-G2/M transition, result in a strong hyperpolarization of the cell's membrane potential that can suppress or bypass the depolarization required for the S-G2/M transition, allowing for possible cell cycle arrest and inhibition of mitosis. All simulated research hypotheses could be verified by experimental studies. SHORT

conclusionFunctional, non-phenomenological digital twins, ranging from single cells to cell-cell interactions to 3D tissue models, open new avenues for modern cancer research through "dry lab" approaches that optimally complement established in-vivo and in-vitro methods.

Indexed as

Adenocarcinoma of LungLung NeoplasmsCell DivisionElectrophysiologyHumansTRPC6 Cation ChannelTRPC6 Cation ChannelA549 cellsCancer electrophysiologyDigital cancer cell twinsHuman lung adenocarcinomaIn-silico models

Identifiers

PMID36221111
PMCPMC9552501
OpenAlexW4304187571

What OpenQuestion holds

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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.