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Review: Challenges of In Vitro CAF Modelling in Liver Cancers.

ABSTRACT: Primary and secondary liver cancer are the third cause of death in the world, and as the incidence is increasing, liver cancer represents a global health burden. Current treatment strategies are insufficient to permanently cure patients from this devastating disease, and therefore other approaches are under investigation. The importance of cancer-associated fibroblasts (CAFs) in the tumour microenvironment is evident, and many pre-clinical studies have shown increased tumour aggressiveness in the presence of CAFs. However, it remains unclear how hepatic stellate cells are triggered by the tumour to become CAFs and how the recently described CAF subtypes originate and orchestrate pro-tumoural effects. Specialized in vitro systems will be needed to address these questions. In this review, we present the currently used in vitro models to study CAFs in primary and secondary liver cancer and highlight the trend from using oversimplified 2D culture systems to more complex 3D models. Relatively few studies report on the impact of cancer (sub)types on CAFs and the tumour microenvironment, and most studies investigated the impact of secreted factors due to the nature of the models.

SUBMITTER: Herrero A

PROVIDER: S-EPMC8656609 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Review: Challenges of In Vitro CAF Modelling in Liver Cancers.

Herrero Alba A Knetemann Elisabeth E Mannaerts Inge I

Cancers 20211124 23

Primary and secondary liver cancer are the third cause of death in the world, and as the incidence is increasing, liver cancer represents a global health burden. Current treatment strategies are insufficient to permanently cure patients from this devastating disease, and therefore other approaches are under investigation. The importance of cancer-associated fibroblasts (CAFs) in the tumour microenvironment is evident, and many pre-clinical studies have shown increased tumour aggressiveness in th ...[more]

PMID: 34885024

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Project description:BackgroundMalaria is one of the most devastating tropical diseases, resulting in loss of lives each year, especially in children under the age of 5 years. Malaria burden, related deaths and stall in the progress against malaria transmission is evident, particularly in countries that have moderate or high malaria transmission. Hence, mitigating malaria spread requires information on the distribution of vectors and the drivers of insecticide resistance (IR). However, owing to the impracticality in establishing the critical need for real-world information at every location, modelling provides an informed best guess for such information. Therefore, this review examines the various methodologies used to model spatial, temporal and spatio-temporal patterns of IR within populations of malaria vectors, incorporating pest-biology parameters, adopted ecological principles, and the associated modelling challenges.MethodsThe review focused on the period ending March 2023 without imposing restrictions on the initial year of publication, and included articles sourced from PubMed, Web of Science, and Scopus. It was also limited to publications that deal with modelling of IR distribution across spatial and temporal dimensions and excluded articles solely focusing on insecticide susceptibility tests or articles not published in English. After rigorous selection, 33 articles met the review's elibility criteria and were subjected to full-text screening.ResultsResults show the popularity of Bayesian geostatistical approaches, and logistic and static models, with limited adoption of dynamic modelling approaches for spatial and temporal IR modelling. Furthermore, our review identifies the availability of surveillance data and scarcity of comprehensive information on the potential drivers of IR as major impediments to developing holistic models of IR evolution.ConclusionsThe review notes that incorporating pest-biology parameters, and ecological principles into IR models, in tandem with fundamental ecological concepts, potentially offers crucial insights into the evolution of IR. The results extend our knowledge of IR models that provide potentially accurate results, which can be translated into policy recommendations to combat the challenge of IR in malaria control.

Project description:The management of advanced or recurrent endometrial cancers presents a challenge due to the development of resistance to treatments. The knowledge regarding the role of the tumor microenvironment (TME) in determining the disease's progression and treatment outcome has evolved in recent years. As a TME component, cancer-associated fibroblasts (CAFs) are essential in developing drug-induced resistance in various solid tumors, including endometrial cancers. Hence, an unmet need exists to test the role of endometrial CAF in overcoming the roadblock of resistance in endometrial cancers. We present a novel tumor-TME two-cell ex vivo model to test CAF's role in resisting the anti-tumor drug, paclitaxel. Endometrial CAFs, both NCAFs (tumor-adjacent normal-tissue-derived CAFs) and TCAFs (tumor-tissue-derived CAFs) were validated by their expression markers. Both TCAFs and NCAFs expressed positive markers of CAF, including SMA, FAP, and S100A4, in varying degrees depending on the patients, while they consistently lacked the negative marker of CAF, EpCAM, as tested via flow cytometry and ICC. CAFs expressed TE-7 and immune marker, PD-L1, via ICC. CAFs better resisted the growth inhibitory effect of paclitaxel on endometrial tumor cells in 2D and 3D formats compared to the resistance of the tumoricidal effect of paclitaxel in the absence of CAFs. TCAF resisted the growth inhibitory effect of paclitaxel on endometrial AN3CA and RL-95-2 cells in an HyCC 3D format. Since NCAF similarly resisted the growth inhibitor action of paclitaxel, we tested NCAF and TCAF from the same patient to demonstrate the protective action of NCAF and TCAF in resisting the tumoricidal effect of paclitaxel in AN3CA in both 2D and 3D matrigel formats. Using this hybrid co-culture CAF and tumor cells, we established a patient-specific, laboratory-friendly, cost-effective, and time-sensitive model system to test drug resistance. The model will help test the role of CAFs in developing drug resistance and contribute to understanding tumor cell-CAF dialogue in gynecological cancers and beyond.

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Review: Challenges of In Vitro CAF Modelling in Liver Cancers.

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Review: Challenges of In Vitro CAF Modelling in Liver Cancers.

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