The double-edged sword role of fibroblasts in the interaction with cancer cells; an agent-based modeling approach

Heidary, Zarifeh; Ghaisari, Jafar; Moein, Shiva; Javanmard, Shaghayegh Haghjooy

doi:10.1371/journal.pone.0232965

Cited by 19 publications

(17 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our simulations demonstrated that fibroblasts can cause a faster failure of adaptive therapy. In tumors, fibroblasts influence the growth of the tumor cells in a spectrum of ways [48][49][50][51]. For example, in breast cancer, fibroblasts increase the growth by secreting epidermal growth factor (EGF); furthermore, the transforming growth factor-β (TGF-β) produced by the tumor cells converts fibroblasts into myofibriblasts, which increase the secretion of EGF and thus cause even more rapid tumor progression [52].…”

Section: Discussionmentioning

confidence: 99%

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

Chi

Kim

2021

Preprint

View full text Add to dashboard Cite

A long-standing practice in the treatment of cancer is that of hitting hard with the maximum tolerated dose to eradicate tumors. This continuous therapy, however, selects for resistant cells, leading to the failure of the treatment. A different type of treatment strategy, adaptive therapy, has recently been shown to have a degree of success in both preclinical xenograft experiments and clinical trials. Adaptive therapy is used to maintain a tumor's volume by exploiting the competition between drug-sensitive and drug-resistant cells with minimum effective drug doses or timed drug holidays. To further understand the role of competition in the outcomes of adaptive therapy, we developed a 2D on-lattice agent-based model. Our simulations show that the superiority of the adaptive strategy over continuous therapy depends on the local competition shaped by the spatial distribution of resistant cells. Cancer cell migration and increased carrying capacity accelerate the progression of the tumor under both types of treatments by reducing the spatial competition. Intratumor competition can also be affected by fibroblasts, which produce microenvironmental factors that promote cancer cell growth. Our simulations show that the spatial architecture of fibroblasts modulates the benefits of adaptive therapy. Finally, as a proof of concept, we simulated the outcomes of adaptive therapy in multiple metastatic sites composed of different spatial distributions of fibroblasts and drug-resistant cell populations.

show abstract

Section: Discussionmentioning

confidence: 99%

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

Chi

Kim

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Our simulations demonstrated that fibroblasts can cause a faster failure of adaptive therapy. In tumors, fibroblasts influence the growth of the tumor cells in a spectrum of ways [58][59][60][61]. For example, in breast cancer, fibroblasts increase the growth by secreting epidermal growth factor (EGF); furthermore, the transforming growth factor-β (TGF-β) produced by the tumor cells converts fibroblasts into myofibroblasts, which increase the secretion of EGF and thus cause even more rapid tumor progression [62].…”

Section: Plos Computational Biologymentioning

confidence: 99%

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

et al. 2022

View full text Add to dashboard Cite

A long-standing practice in the treatment of cancer is that of hitting hard with the maximum tolerated dose to eradicate tumors. This continuous therapy, however, selects for resistant cells, leading to the failure of the treatment. A different type of treatment strategy, adaptive therapy, has recently been shown to have a degree of success in both preclinical xenograft experiments and clinical trials. Adaptive therapy is used to maintain a tumor’s volume by exploiting the competition between drug-sensitive and drug-resistant cells with minimum effective drug doses or timed drug holidays. To further understand the role of competition in the outcomes of adaptive therapy, we developed a 2D on-lattice agent-based model. Our simulations show that the superiority of the adaptive strategy over continuous therapy depends on the local competition shaped by the spatial distribution of resistant cells. Intratumor competition can also be affected by fibroblasts, which produce microenvironmental factors that promote cancer cell growth. To this end, we simulated the impact of different fibroblast distributions on treatment outcomes. As a proof of principle, we focused on five types of distribution of fibroblasts characterized by different locations, shapes, and orientations of the fibroblast region with respect to the resistant cells. Our simulation shows that the spatial architecture of fibroblasts modulates tumor progression in both continuous and adaptive therapy. Finally, as a proof of concept, we simulated the outcomes of adaptive therapy of a virtual patient with four metastatic sites composed of different spatial distributions of fibroblasts and drug-resistant cell populations. Our simulation highlights the importance of undetected metastatic lesions on adaptive therapy outcomes.

show abstract

“…Interactions mediating metabolic changes and phenotypic adaptations [ 207 ], evolution of several metabolites and their inhibition [ 208 ], tumor specific alterations [ 209 ], and models of the Warburg effect such as genome-scale computational study of metabolic targets inhibiting cancer migration [ 210 ] or models behind the glycolytic switch [ 211 ]. A very recent study [ 212 ] proposes an agent-based dynamic model to investigate the role of CAFs further; however, it focuses almost exclusively on their crosstalk with cancer cells and does not consider metabolic reprogramming.…”

Section: Computational Systems Biology Approachesmentioning

confidence: 99%

Metabolic Reprogramming of Fibroblasts as Therapeutic Target in Rheumatoid Arthritis and Cancer: Deciphering Key Mechanisms Using Computational Systems Biology Approaches

Aghakhani

Zerrouk

Niarakis

2020

Cancers

View full text Add to dashboard Cite

Fibroblasts, the most abundant cells in the connective tissue, are key modulators of the extracellular matrix (ECM) composition. These spindle-shaped cells are capable of synthesizing various extracellular matrix proteins and collagen. They also provide the structural framework (stroma) for tissues and play a pivotal role in the wound healing process. While they are maintainers of the ECM turnover and regulate several physiological processes, they can also undergo transformations responding to certain stimuli and display aggressive phenotypes that contribute to disease pathophysiology. In this review, we focus on the metabolic pathways of glucose and highlight metabolic reprogramming as a critical event that contributes to the transition of fibroblasts from quiescent to activated and aggressive cells. We also cover the emerging evidence that allows us to draw parallels between fibroblasts in autoimmune disorders and more specifically in rheumatoid arthritis and cancer. We link the metabolic changes of fibroblasts to the toxic environment created by the disease condition and discuss how targeting of metabolic reprogramming could be employed in the treatment of such diseases. Lastly, we discuss Systems Biology approaches, and more specifically, computational modeling, as a means to elucidate pathogenetic mechanisms and accelerate the identification of novel therapeutic targets.

show abstract

The double-edged sword role of fibroblasts in the interaction with cancer cells; an agent-based modeling approach

Cited by 19 publications

References 64 publications

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

The impact of the spatial heterogeneity of resistant cells and fibroblasts on treatment response

Metabolic Reprogramming of Fibroblasts as Therapeutic Target in Rheumatoid Arthritis and Cancer: Deciphering Key Mechanisms Using Computational Systems Biology Approaches

Contact Info

Product

Resources

About