Zhao Ziying, Feng Xiaoqing, Wu Huijuan, Chen Shuisheng, Ma Changsong, Guan Ziyun, Lei Luwen, Tang Kejing, Chen Xiao, Dong Yong, Tang Yubo
Department of Pharmacy, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, China.
Transl Lung Cancer Res. 2024 Oct 31;13(10):2698-2712. doi: 10.21037/tlcr-24-490. Epub 2024 Oct 28.
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 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 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.
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.
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.
These findings suggest that the 3D hydrogel cell culture models more closely mimicked the 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.
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，但患者仍面临与耐药性和复发相关的挑战。目前评估抗癌药物活性的方法并不充分，因为它们依赖于二维（2D）细胞培养和动物模型。因此，开发一种能够预测个体对抗癌药物敏感性的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患者来源的肺癌细胞，并使用海藻酸钠（SA）和明胶构建三维（3D）培养模型。目的是研究3D培养模型中细胞的生物学特性，并基于海藻酸钠-明胶3D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。
使用条件重编程技术生成条件重编程的肺腺癌细胞（CRLCs）。制备海藻酸钠-明胶水凝胶微珠，以探索其在抗癌药物评估中的潜在用途。还使用MTS测定法检测细胞增殖。使用钙黄绿素乙酰氧基甲酯/碘化丙啶（钙黄绿素-AM/PI）双重染色进行活/死染色，以评估细胞分布和活力。通过蛋白质印迹法评估蛋白质表达。
在三维（3D）培养中生长的细胞处于持续增殖状态，并且存在明显的细胞团生长现象。药物敏感性测定结果表明，与在2D培养中生长的细胞相比，在海藻酸钠-明胶水凝胶微珠中生长的CRLCs对抗癌药物表现出更强的耐药性。结果还表明，与2D培养的细胞相比，3D培养的CRLCs显示出更高水平的干细胞标志物蛋白质表达，如纳米盒同源蛋白（NANOG）、SRY盒转录因子2（SOX-2）和醛脱氢酶1家族成员A1（ALDH1A1）。
这些发现表明，3D水凝胶细胞培养模型更紧密地模拟了细胞的生物学和临床行为，并且比2D细胞培养模型表现出更高的对抗癌药物的固有耐药性，因此可以作为诊断、药物筛选和个性化医学的有价值工具。
