Cancer represents one of the diseases with the highest mortality rate worldwide. The burden of cancer continues to increase, not only affecting the health-related quality of life of patients but also causing an elevated global financial impact. The complexity and heterogeneity of cancer pose significant challenges in research and clinical practice, contributing to increase the failure rate of clinical trials for antitumoral drugs. This is partially due to the fact that preclinical models still present important limitations in faithfully recapitulating human tumors to serve as reliable indicators of drug effectiveness. Up to now, research and development strategies employ expensive animal models (including the so-called “humanized mice”) that not only raise ethical concerns, but also frequently fail to accurately predict responses to anticancer drugs because they do not faithfully replicate human physiology as well as the patient's tumor microenvironment. On the other side, traditional two-dimensional (2D) cell cultures fail to adequately reproduce the structural organization of tumor and the cellular heterogeneity found in vivo. The growing necessity to develop more accurate cancer models has increasingly emphasized the importance of three-dimensional (3D) in vitro cell cultures, such as cancer-derived spheroids and organoids, as promising alternatives to bridge the gap between 2D and animal models. In this review, we provide a brief overview focusing on 3D in vitro cell cultures as preclinical models capable of properly reproducing the tissue organization, biological composition, and complexity of in vivo tumors in a fine-tuned microenvironment. Despite their limitations, these models collectively enhance our understanding of the mechanisms underlying cancer and may offer the potential for a more reliable assessment of drug efficacy before clinical testing and, consequently, improve therapeutic outcomes for cancer patients.

Three-Dimensional In Vitro Cell Cultures as a Feasible and Promising Alternative to Two-Dimensional and Animal Models in Cancer Research

Andrea Esposito;Alessandra Ferraresi
;
Letizia Vallino;Beatrice Garavaglia;Ciro Isidoro
2024-01-01

Abstract

Cancer represents one of the diseases with the highest mortality rate worldwide. The burden of cancer continues to increase, not only affecting the health-related quality of life of patients but also causing an elevated global financial impact. The complexity and heterogeneity of cancer pose significant challenges in research and clinical practice, contributing to increase the failure rate of clinical trials for antitumoral drugs. This is partially due to the fact that preclinical models still present important limitations in faithfully recapitulating human tumors to serve as reliable indicators of drug effectiveness. Up to now, research and development strategies employ expensive animal models (including the so-called “humanized mice”) that not only raise ethical concerns, but also frequently fail to accurately predict responses to anticancer drugs because they do not faithfully replicate human physiology as well as the patient's tumor microenvironment. On the other side, traditional two-dimensional (2D) cell cultures fail to adequately reproduce the structural organization of tumor and the cellular heterogeneity found in vivo. The growing necessity to develop more accurate cancer models has increasingly emphasized the importance of three-dimensional (3D) in vitro cell cultures, such as cancer-derived spheroids and organoids, as promising alternatives to bridge the gap between 2D and animal models. In this review, we provide a brief overview focusing on 3D in vitro cell cultures as preclinical models capable of properly reproducing the tissue organization, biological composition, and complexity of in vivo tumors in a fine-tuned microenvironment. Despite their limitations, these models collectively enhance our understanding of the mechanisms underlying cancer and may offer the potential for a more reliable assessment of drug efficacy before clinical testing and, consequently, improve therapeutic outcomes for cancer patients.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11579/192202
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