Evidence map›Paper›PMID 42100976›Full record

ArticleJournal of biosciences2026

Computational insights into cancer stem cell dynamics and the urokinase plasminogen activation pathway.

Kumari Neelam Verma, Debabrata Dasgupta

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Article in Journal of biosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Kumari Neelam VermaDepartment of Mechanical Engineering, Indian Institute of Technology Delhi, Delhi 110016, India.
Debabrata DasguptaDepartment of Mechanical Engineering, Indian Institute of Technology Delhi, Delhi 110016, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces a novel computational model that integrates cancer stem cells (CSCs) and the plasminogen activation system, filling a crucial gap in cancer research. While theoretical models have separately explored CSCs and the plasminogen activation system, no prior computational framework has combined these elements. Our model focuses on the invasion dynamics of CSCs, emphasizing the critical interactions between urokinase plasminogen activator (uPA) and plasminogen activator inhibitor-1 (PAI-1). We employed reaction-diffusion equations and analyzed the determinant and eigenvalue spectra of the Jacobian matrix of the system to identify instability regions within tumors. The findings revealed that the production and binding of uPA and PAI-1 significantly enhance the invasiveness and motility of CSCs, resulting in more complex and aggressive tumor structures. Our study advances the theoretical understanding of cancer dynamics by integrating these two critical biological processes into a single computational framework. This work builds upon and extends previous models by offering a more comprehensive analysis of tumor growth, with significant implications for optimizing cancer treatment strategies. The insights of the model into the interplay between CSCs and the plasminogen activation system offer a valuable tool for both research and potential clinical applications, paving the way for more targeted and effective therapeutic approaches.

Indexed as

Models, BiologicalNeoplasmsNeoplastic Stem CellsPlasminogen Activator Inhibitor 1Urokinase-Type Plasminogen ActivatorCell MovementComputer SimulationHumansNeoplasm InvasivenessPlasminogenSignal TransductionPlasminogenPlasminogen Activator Inhibitor 1Urokinase-Type Plasminogen Activator

Identifiers

PMID42100976

What OpenQuestion holds

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Registered trials

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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.