Tumour Growth Mechanisms Determine Effectiveness of Adaptive Therapy in Glandular Tumours.

IF 3.9 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Interdisciplinary Sciences: Computational Life Sciences Pub Date : 2024-03-01 Epub Date: 2023-09-30 DOI:10.1007/s12539-023-00586-8
Rui Zhen Tan
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Abstract

In cancer treatment, adaptive therapy holds promise for delaying the onset of recurrence through regulating the competition between drug-sensitive and drug-resistant cells. Adaptive therapy has been studied in well-mixed models assuming free mixing of all cells and spatial models considering the interactions of single cells with their immediate adjacent cells. Both models do not reflect the spatial structure in glandular tumours where intra-gland cellular interaction is high, while inter-gland interaction is limited. Here, we use mathematical modelling to study the effects of adaptive therapy on glandular tumours that expand using either glandular fission or invasive growth. A two-dimensional, lattice-based model of sites containing sensitive and resistant cells within individual glands is developed to study the evolution of glandular tumour cells under continuous and adaptive therapies. We found that although both growth models benefit from adaptive therapy's ability to prevent recurrence, invasive growth benefits more from it than fission growth. This difference is due to the migration of daughter cells into neighboring glands that is absent in fission but present in invasive growth. The migration resulted in greater mixing of cells, enhancing competition induced by adaptive therapy. By varying the initial spatial spread and location of the resistant cells within the tumour, we found that modifying the conditions within the resistant cells containing glands affect both fission and invasive growth. However, modifying the conditions surrounding these glands affect invasive growth only. Our work reveals the interplay between growth mechanism and tumour topology in modulating the effectiveness of cancer therapy.

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肿瘤生长机制决定腺体肿瘤适应性治疗的有效性。
在癌症治疗中,适应性治疗有望通过调节药物敏感细胞和耐药细胞之间的竞争来延缓复发的发生。自适应治疗已经在假设所有细胞自由混合的良好混合模型和考虑单个细胞与其紧邻细胞相互作用的空间模型中进行了研究。这两个模型都没有反映腺肿瘤的空间结构,腺内细胞相互作用很高,而腺间相互作用有限。在这里,我们使用数学模型来研究适应性治疗对使用腺分裂或侵袭性生长扩张的腺肿瘤的影响。开发了一个二维的、基于晶格的模型,用于研究在连续和适应性治疗下腺肿瘤细胞的进化。我们发现,尽管这两种生长模型都受益于适应性治疗预防复发的能力,但侵入性生长比裂变生长受益更多。这种差异是由于子细胞迁移到相邻的腺体中,这些腺体在分裂中不存在,但在侵入性生长中存在。迁移导致细胞的更多混合,增强了适应性治疗诱导的竞争。通过改变耐药细胞在肿瘤内的初始空间分布和位置,我们发现改变含有腺体的耐药细胞内的条件会影响分裂和侵袭性生长。然而,改变这些腺体周围的条件只会影响侵袭性生长。我们的工作揭示了生长机制和肿瘤拓扑结构在调节癌症治疗效果方面的相互作用。
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来源期刊
Interdisciplinary Sciences: Computational Life Sciences
Interdisciplinary Sciences: Computational Life Sciences MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
8.60
自引率
4.20%
发文量
55
期刊介绍: Interdisciplinary Sciences--Computational Life Sciences aims to cover the most recent and outstanding developments in interdisciplinary areas of sciences, especially focusing on computational life sciences, an area that is enjoying rapid development at the forefront of scientific research and technology. The journal publishes original papers of significant general interest covering recent research and developments. Articles will be published rapidly by taking full advantage of internet technology for online submission and peer-reviewing of manuscripts, and then by publishing OnlineFirstTM through SpringerLink even before the issue is built or sent to the printer. The editorial board consists of many leading scientists with international reputation, among others, Luc Montagnier (UNESCO, France), Dennis Salahub (University of Calgary, Canada), Weitao Yang (Duke University, USA). Prof. Dongqing Wei at the Shanghai Jiatong University is appointed as the editor-in-chief; he made important contributions in bioinformatics and computational physics and is best known for his ground-breaking works on the theory of ferroelectric liquids. With the help from a team of associate editors and the editorial board, an international journal with sound reputation shall be created.
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