恶性肿瘤干性及其量化分析方法的研究进展  

The Research Progress of Malignant Tumor Stemness and Its Quantitative Methods

作　　者：孙学梦 刘芳远 苏丽娅[1,2] SUN Xuemeng;LIU Fangyuan;SU Liya(Research Center for Clinical Medicine,the Affiliated Hospital of Inner Mongolia Medical University,Hohhot 010050,China;Inner Mongolia Key Laboratory of Medical Cell Biology,Hohhot 010050,China;Surgery Lab,the Affiliated Hospital of Inner Mongolia Medical University,Hohhot 010050,China)

机构地区：[1]内蒙古医科大学临床医学研究中心,呼和浩特010050 [2]内蒙古医科大学,呼和浩特010050 [3]内蒙古医科大学附属医院外科实验室,呼和浩特010050

出　　处：《中国细胞生物学学报》2023年第3期443-451,共9页Chinese Journal of Cell Biology

基　　金：国家自然科学基金(批准号:81860541);内蒙古自治区高等学校科学研究项目(批准号:NJZY22674);内蒙古医科大学致远人才计划(批准号:ZY0120025);内蒙古医科大学青年创新基金(批准号:YKD2020QNCX028)资助的课题。

摘　　要：一直以来,肿瘤干细胞一直是恶性肿瘤研究领域的重要研究靶点之一,其干性特征影响了癌症的发生、治疗抵抗和复发。传统的肿瘤干性机制研究需要实验流式技术对肿瘤干细胞进行分选和提取。二代测序技术在肿瘤研究领域的普及产生了大量的肿瘤组织测序数据并提供了丰富的恶性肿瘤遗传和分子图谱。随着计算方法的不断革新,研究人员基于分子特征或机器学习原理,通过改良算法和组合策略对恶性肿瘤组织中的干性水平进行评估,并使用干性指数对其描述和定义。对干性的量化计算,可以为恶性肿瘤中干性调控机制提供帮助,基于干性指数等指标进行建模预测,能够指导临床对癌症患者的治疗和预后进行评估。Cancer stem cells are believed to play an important role in the progression,treatment resistance and recurrence of tumors,which make it attractive in the field of malignancy.Next-generation sequencing generated large scale of sequencing data and provided abundant genetic and molecular atlas of malignancy instead of traditional sorting and extracting methods based on flow cytometry.With the innovation of computational methods,researchers utilized stemness score to describe and define stemness by improved algorithms and combinatorial strategies by molecular features or machine learning.The quantitative calculation of stemness has guiding significance for the research on regulated mechanism of stemness in malignant tumor,and modeling and forecasting by stemness score provide guidance to the treatment and prognosis of cancer patients.

关 键 词：肿瘤干细胞 干性指数 测序 算法 预后 

分 类 号：R730.2[医药卫生—肿瘤]