癌症研究
干细胞
循环肿瘤细胞
仿形(计算机编程)
肿瘤细胞
化学
计算生物学
生物
细胞生物学
遗传学
癌症
计算机科学
转移
操作系统
作者
Chia‐Lin Chen,Juan Carlos Hernandez,Dinesh Babu Uthaya Kumar,Tatsuya Machida,Stanley M. Tahara,Anthony B. El-Khoueiry,Meng Li,Vasu Punj,Suresh Kumar Swaminathan,Ameya R. Kirtane,Yibu Chen,Jayanth Panyam,Keigo Machida
出处
期刊:Advanced Science
[Wiley]
日期:2023-03-22
卷期号:10 (14): e2206812-e2206812
被引量:10
标识
DOI:10.1002/advs.202206812
摘要
Abstract A critical barrier to effective cancer therapy is the improvement of drug selectivity, toxicity, and reduced recurrence of tumors expanded from tumor‐initiating stem‐like cells (TICs). The aim is to identify circulating tumor cell (CTC)‐biomarkers and to identify an effective combination of TIC‐specific, repurposed federal drug administration (FDA)‐approved drugs. Three different types of high‐throughput screens targeting the TIC population are employed: these include a CD133 (+) cell viability screen, a NANOG expression screen, and a drug combination screen. When combined in a refined secondary screening approach that targets Nanog expression with the same FDA‐approved drug library, histone deacetylase (HDAC) inhibitor(s) combined with all‐trans retinoic acid (ATRA) demonstrate the highest efficacy for inhibition of TIC growth in vitro and in vivo. Addition of immune checkpoint inhibitor further decreases recurrence and extends PDX mouse survival. RNA‐seq analysis of TICs reveals that combined drug treatment reduces many Toll‐like receptors (TLR) and stemness genes through repression of the lncRNA MIR22HG . This downregulation induces PTEN and TET2, leading to loss of the self‐renewal property of TICs. Thus, CTC biomarker analysis would predict the prognosis and therapy response to this drug combination. In general, biomarker‐guided stratification of HCC patients and TIC‐targeted therapy should eradicate TICs to extend HCC patient survival.
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