构建基于藻酸盐/明胶微珠的肺癌三维培养模型,用于药物评估。

IF 4 2区 医学 Q2 ONCOLOGY
Translational lung cancer research Pub Date : 2024-10-31 Epub Date: 2024-10-28 DOI:10.21037/tlcr-24-490
Ziying Zhao, Xiaoqing Feng, Huijuan Wu, Shuisheng Chen, Changsong Ma, Ziyun Guan, Luwen Lei, Kejing Tang, Xiao Chen, Yong Dong, Yubo Tang
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引用次数: 0

摘要

背景:肺癌是全球最常见的恶性肿瘤之一:肺癌是全球最常见的恶性肿瘤之一。尽管肺癌治疗取得了进展,但患者仍面临耐药性和复发的挑战。目前评估抗癌药物活性的方法依赖于二维(2D)细胞培养和动物模型,因此存在不足。因此,开发一种能够预测个体对抗癌药物敏感性的体外药物评估模型,将大大提高肺癌患者药物治疗的成功率。本研究的目的是利用条件重编程技术培养源自患者的肺癌细胞,并使用海藻酸钠(SA)和明胶构建体外三维培养模型。目的是研究三维培养模型中细胞的生物学特性,并基于海藻酸钠-明胶三维培养模型进一步研究抗癌药物的敏感性。这种方法为个性化精准抗癌治疗和新型抗癌药物的开发提供了新的手段和见解:方法:利用条件重编程技术生成条件重编程肺腺癌细胞(CRLCs)。方法:利用条件重编程技术生成了条件重编程肺腺癌细胞(CRLCs),并制作了海藻酸明胶水凝胶微珠,以探索其在抗癌药物评估中的潜在用途。此外,还使用 MTS 检测法对细胞增殖进行了检测。使用钙黄绿素乙酰氧甲基酯/碘化丙啶(钙黄绿素-AM/PI)双重染色法进行活/死染色,以评估细胞分布和存活率。蛋白表达通过 Western 印迹进行评估:三维(3D)培养的细胞处于持续增殖状态,并有明显的细胞增殖现象。药敏试验结果表明,与二维培养的细胞相比,生长在海藻酸明胶水凝胶微珠中的 CRLC 对抗癌药物的耐药性更强。结果还显示,与二维生长细胞相比,三维培养的CRLC显示出更高的干细胞标志蛋白表达水平,如Nanog同源染色体(NANOG)、SRY-Box转录因子2(SOX-2)和醛脱氢酶1家族成员A1(ALDH1A1):这些研究结果表明,三维水凝胶细胞培养模型比二维细胞培养模型更接近细胞在体内的生物学和临床表现,对抗癌药物的先天耐受性更高,因此可作为诊断、药物筛选和个性化医疗的重要工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Construction of a lung cancer 3D culture model based on alginate/gelatin micro-beads for drug evaluation.

Background: Lung cancer is one of the most common malignant tumors worldwide. Despite advances in lung cancer treatment, patients still face challenges related to drug resistance and recurrence. Current methods for evaluating anti-cancer drug activity are insufficient, as they rely on two-dimensional (2D) cell culture and animal models. Therefore, the development of an in vitro drug evaluation model capable of predicting individual sensitivity to anti-cancer drugs would greatly enhance the success rate of drug treatments for lung cancer patients. The purpose of this research is to utilise conditional reprogramming technology to cultivate patient-derived lung cancer cells and to construct an in vitro 3D culture model using sodium alginate (SA) and gelatin. The aim is to study the biological characteristics of cells in the 3D culture model and to further investigate the sensitivity of anti-cancer drugs based on the alginate-gelatin 3D culture model. This approach provides new means and insights for personalized precision anti-cancer therapy and the development of new anti-cancer drugs.

Methods: Conditional reprogramming technology was used to generate conditionally reprogrammed lung adenocarcinoma cells (CRLCs). Alginate-gelatin hydrogel micro-beads were created to explore their potential use in the assessment of anti-cancer drugs. Cell proliferation was also examined using the MTS assay method. Live/dead staining was performed to estimate cell distribution and viability using calcein acetoxymethyl ester/propidium iodide (calcein-AM/PI) double staining. Protein expression was assessed by Western blot.

Results: The cells grown in the three-dimensional (3D) culture were in a state of continuous proliferation, and there was an obvious phenomenon of cell mass growth. The drug sensitivity assay results demonstrated that compared with the 2D-grown cells, the CRLCs grown in the alginate-gelatin hydrogel micro-beads exhibited more resistance to anti-cancer drugs. The results also showed that the 3D-cultured CRLCs showed greater protein expression levels of stem cell hallmarks, such as Nanog Homeobox (NANOG), SRY-Box Transcription Factor 2 (SOX-2), and aldehyde dehydrogenase 1 family member A1 (ALDH1A1), than the 2D-grown cells.

Conclusions: These findings suggest that the 3D hydrogel cell culture models more closely mimicked the in vivo biological and clinical behavior of cells, and demonstrated higher innate resistance to anti-cancer drugs than the 2D cell culture models, and thus could serve as valuable tools for diagnosis, drug screening, and personalized medicine.

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来源期刊
CiteScore
7.20
自引率
2.50%
发文量
137
期刊介绍: Translational Lung Cancer Research(TLCR, Transl Lung Cancer Res, Print ISSN 2218-6751; Online ISSN 2226-4477) is an international, peer-reviewed, open-access journal, which was founded in March 2012. TLCR is indexed by PubMed/PubMed Central and the Chemical Abstracts Service (CAS) Databases. It is published quarterly the first year, and published bimonthly since February 2013. It provides practical up-to-date information on prevention, early detection, diagnosis, and treatment of lung cancer. Specific areas of its interest include, but not limited to, multimodality therapy, markers, imaging, tumor biology, pathology, chemoprevention, and technical advances related to lung cancer.
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