Authors
Pius Erheyovwe Bubu, Val Hyginus Udoka Eze, Kelechi John Ukagwu, Vidya Sankarapandian, Saidi Odoma, Awafung Emmanuel Adie, Nansamba Fridah Mirembe
Published in
Medicine. Volume 105. Issue 42. Pages e51105. Oct 16, 2026.
Abstract
Malignant brain tumors, including glioblastoma and medulloblastoma, remain highly treatment-resistant. Neural stem cells (NSCs) are being investigated as tumor-tropic therapeutic vectors, but the temporal interaction between tumor and NSC populations requires quantitative characterization before model-based treatment hypotheses can be interpreted reliably. This study aimed to develop and numerically evaluate a reproducible 2-population model of tumor-NSC dynamics and to quantify the influence of NSC persistence and NSC-mediated tumor killing on simulated tumor burden. A normalized system of 2 coupled nonlinear ordinary differential equations was used: dT/dt = rT(1 - T) - βTN and dN/dt = αN(1 - N) - γTN. The baseline simulation used r = 0.20000 day-1, α = 0.05000 day-1, β = 0.35000 day-1, γ = 0.30000 day-1, T0 = 0.50000, and N0 = 0.40000. Explicit Euler integration was performed with Δt = 0.01 day over 20 days. A descriptive nonlinear regression fit, Fourier spectral analysis, 1-parameter sensitivity analyses, and joint α-β sensitivity analysis were applied to the simulated trajectory. In the baseline simulation, tumor density decreased from 0.5000 to a minimum of 0.4772 at day 2.59 (4.57% below the initial value) and subsequently increased to T20 = 0.8273, while NSC density declined from 0.4000 to N20 = 0.0247. The descriptive regression reproduced the simulated tumor trajectory with R2 = 0.9973 and root mean square error = 0.00590. Increasing α from 0.05 to 0.10 day-1 reduced T20 by 12.6% relative to baseline, and increasing β from 0.35 to 0.50 day-1 reduced T20 by 19.9%. Jointly setting α = 0.10 and β = 0.50 day-1 yielded T20 = 0.4427, 46.5% below the baseline terminal tumor density. The Fourier spectrum was dominated by the zero and low-frequency components, with no distinct oscillatory peak over the 20-day window. The model indicates that NSC persistence and NSC-mediated tumor killing materially influence terminal tumor burden, but the baseline parameterization produces only transient early suppression followed by tumor regrowth as the NSC population declines. The results are population-level, model-based estimates rather than tumor-type-specific clinical efficacy measures. Tumour-specific calibration, spatial migration, immune interactions, and experimental validation are required before translational conclusions can be drawn.
PMID:
42888611
Bibliographic data and abstract were imported from PubMed on 17 Oct 2026.
Read full publication at:
Please sign in
to see all details.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 0
- Comments 0