Instituto Keizo Asami, Universidade Federal de Pernambuco, Recife 50740-600, Pernambuco, Brazil.
Programa de Pós-Graduação em Biologia Aplicada à Saúde, Centro de Biociências, Universidade Federal de Pernambuco, Recife 50740-600, Pernambuco, Brazil.
Int J Mol Sci. 2023 Nov 20;24(22):16516. doi: 10.3390/ijms242216516.
This systematic review aims to evaluate the influence of environmental enrichment (EE) on oncological factors in experimental studies involving various types of cancer models. A comprehensive search was conducted in three databases: PubMed (161 articles), Embase (335 articles), and Scopus (274 articles). Eligibility criteria were applied based on the PICOS strategy to minimize bias. Two independent researchers performed the searches, with a third participant resolving any discrepancies. The selected articles were analyzed, and data regarding sample characteristics and EE protocols were extracted. The outcomes focused solely on cancer and tumor-related parameters, including cancer type, description of the cancer model, angiogenesis, tumor occurrence, volume, weight, mice with tumors, and tumor inhibition rate. A total of 770 articles were identified across the three databases, with 12 studies meeting the inclusion criteria for this systematic review. The findings demonstrated that different EE protocols were effective in significantly reducing various aspects of tumor growth and development, such as angiogenesis, volume, weight, and the number of mice with tumors. Furthermore, EE enhanced the rate of tumor inhibition in mouse cancer models. This systematic review qualitatively demonstrates the impacts of EE protocols on multiple parameters associated with tumor growth and development, including angiogenesis, occurrence, volume, weight, and tumor incidence. Moreover, EE demonstrated the potential to increase the rate of tumor inhibition. These findings underscore the importance of EE as a valuable tool in the management of cancer.
本系统评价旨在评估环境富集(EE)对涉及各种癌症模型的实验研究中肿瘤学因素的影响。在三个数据库中进行了全面检索:PubMed(161 篇文章)、Embase(335 篇文章)和 Scopus(274 篇文章)。基于 PICOS 策略应用入选标准,以最大程度地减少偏倚。两名独立研究人员进行了搜索,第三名参与者解决了任何差异。对选定的文章进行了分析,并提取了有关样本特征和 EE 方案的数据。研究结果仅关注癌症和肿瘤相关参数,包括癌症类型、癌症模型描述、血管生成、肿瘤发生、体积、重量、患有肿瘤的小鼠和肿瘤抑制率。在三个数据库中总共确定了 770 篇文章,其中有 12 项研究符合本系统评价的入选标准。研究结果表明,不同的 EE 方案在显著减少肿瘤生长和发展的各个方面是有效的,如血管生成、体积、重量和患有肿瘤的小鼠数量。此外,EE 提高了小鼠癌症模型中肿瘤抑制率。本系统评价定性地展示了 EE 方案对与肿瘤生长和发展相关的多个参数的影响,包括血管生成、发生、体积、重量和肿瘤发生率。此外,EE 显示出增加肿瘤抑制率的潜力。这些发现强调了 EE 作为癌症管理中一种有价值工具的重要性。