Cheng Jiongjia, Zhu Ting, Liu Shaoxian, Zhou Jiayu, Wang Xiaofeng, Liu Guangxiang
Key Laboratory of Advanced Functional Materials of Nanjing, School of Environmental Science, Nanjing Xiaozhuang University Nanjing 211171 China
RSC Med Chem. 2024 Sep 5;15(11):3853-61. doi: 10.1039/d4md00165f.
Gemcitabine remains a first-class chemotherapeutic drug for pancreatic cancer. However, due to the rapid development of gemcitabine resistance in pancreatic cancer, gemcitabine alone or in combination with other anti-cancer drugs only showed limited effect in the clinic. It is extremely challenging to effectively and efficiently determine the optimal drug regimens. Thus, identification of appropriate prediction biomarkers is critical for the rational design of gemcitabine-based therapeutic options. Herein, a pancreatic cancer stem cell (PCSC) model exhibiting chemoresistance to gemcitabine was used to test the activity of clinical cancer drugs in the presence or absence of gemcitabine. As determined by combinatorial treatment, several types of drugs resensitized gemcitabine-resistant PCSCs to gemcitabine, with sorafenib (EGFR inhibitor)/gemcitabine and sunitinib (TBK1 inhibitors)/gemcitabine drug combinations being the most preferred treatments for PCSCs. Following the validation of the PCSC model by an antibody array test of 15-gene expression of stemness biomarkers, NANOG showed markedly different expression in PCSCs compared to the parental cells. From comprehensive analysis of stem cell index combination index, a stemness-related correlation model was successfully constructed to demonstrate the correlation between NANOG expression and synergism. Cancer cell stemness was ascertained to be highly relevant to NANOG overexpression that can be abrogated by synergized gemcitabine-drug combinations. Therefore, NANOG works as a therapeutic biomarker for predicating efficient combinatorial treatment of gemcitabine in pancreatic cancer.
吉西他滨仍然是治疗胰腺癌的一流化疗药物。然而，由于胰腺癌中吉西他滨耐药性的迅速发展，单独使用吉西他滨或与其他抗癌药物联合使用在临床上仅显示出有限的效果。有效且高效地确定最佳药物方案极具挑战性。因此，识别合适的预测生物标志物对于基于吉西他滨的治疗方案的合理设计至关重要。在此，使用对吉西他滨具有化学抗性的胰腺癌干细胞（PCSC）模型来测试在有或没有吉西他滨存在的情况下临床癌症药物的活性。通过联合治疗确定，几种类型的药物使吉西他滨耐药的PCSC对吉西他滨重新敏感，索拉非尼（EGFR抑制剂）/吉西他滨和舒尼替尼（TBK1抑制剂）/吉西他滨药物组合是PCSC最优选的治疗方法。通过对干性生物标志物的15基因表达进行抗体阵列测试验证PCSC模型后，与亲本细胞相比，NANOG在PCSC中显示出明显不同的表达。通过对干细胞指数和联合指数的综合分析，成功构建了一个干性相关的关联模型，以证明NANOG表达与协同作用之间的相关性。确定癌细胞干性与NANOG过表达高度相关，而吉西他滨 - 药物联合使用可以消除这种过表达。因此，NANOG作为一种治疗生物标志物，可用于预测胰腺癌中吉西他滨的有效联合治疗。
