生物谷报道：来自台湾大学医学院临床实验科学，医学生物技术系，NTU基因组医学中心（NTU Center for Genomic Medicine，生物谷注），中央研究院（Academia Sinica），台中荣民总医院（Taichung Veterans General Hospital），加州大学洛杉矶分校的研究人员利用现代生物技术手段，发现了5个能预测肺癌存活及复发的miRNA信号，对于癌症的预测与治疗提供了新的资料。这一研究成果公布在Cell子刊Cancer Cell杂志上。
领导这一研究的是台湾大学医学院的杨泮池教授，其早年毕业于台湾大学，获得了硕士及博士学位，现任台湾大学医学院基因组医学中心执行秘书，芯片核心实验室（Microarray Core Facility，生物谷注）项目主任等。
在最新的一份报告中指出（美国癌症协会），2007年全球的新增癌症病例将超过1200万，并且有760万人死于癌症，即每天有2万人死于癌症。在发展中国家，男性最常诊断出的癌症类型分别为肺癌、胃癌和肝癌；女性最常诊断出的前三位癌症分别为乳腺癌、宫颈癌和胃癌。作为癌症死亡率已占癌症死亡率之首的一种常见的肺部恶性肿瘤，肺癌在国内的发病率和病死率均迅速上升。
肺癌共有四种不同类型的肺癌：小细胞肺癌、非小细胞肺癌，后者包括鳞癌、腺癌和支气管肺泡癌，其中非小细胞肺癌（Non-Small Cell Lung Cancer，NSCLC，生物谷注）占肺癌的85％以上，而非小细胞肺癌中85％以上又都属中晚期肺癌而失去根治性手术治疗的机会，因此这部分肺癌研究尤其吸引研究人员。
在这篇文章中，研究人员对患有NSCLC的病患进行了检测，分析miRNA表达是否能预测NSCLC的临床效果，利用实时RT-PCR手段，研究人员获得了112个病患的miRNA表达数据。通过Cox模型（Cox regression）和风险评分（risk-score，生物谷注）分析，研究人员发现了5个预测NSCLC治疗效果的miRNA信号。带有这些miRNA信号的高风险基数的病人相对于风险基数低的病人，治疗效果较差。因此研究人员认为这些miRNA信号是NSCLC病患癌症复发和存活的独立预测因子。
微小RNA (microRNA，简称miRNA)是生物体内源长度约为20－23个核苷酸的非编码小RNA，通过与靶mRNA的互补配对而在转录后水平上对基因的表达进行负调控，导致mRNA的降解或翻译抑制。到目前为止，已报道有几千种miRNA存在于动物、植物、真菌等多细胞真核生物中，进化上高度保守。
许多研究证明，miRNA可以用以标记癌症，比如今年三月，俄亥俄州立大学的Stefano Volinia等人通过分析来自肺部、胸部、胃部、前列腺、结肠和胰腺等处的癌细胞样品540份，发现了由过量表达的大部分miRNAs组成的实体癌症miRNA信号，在这些miRNA中包括miR-17-5p、miR-20a、miR-21、miR-92、miR-106a和miR-155。而对于编码蛋白的肿瘤抑制子（protein-coding tumor suppressors）和致癌基因，这些miRNAs差异表达作用的靶目标会大量富集，其中得到证实的是肿瘤抑制子RB1（Retinoblastoma 1）和TGFBR2 (transforming growth factor, beta receptor II)。这说明miRNAs在实体肿瘤的癌症发病机理中发挥着重要的作用。
生物谷推荐英文原文：
Copyright © 2008 Cell Press. All rights reserved.
Cancer Cell, Vol 13, 48-57, 08 January 2008
MicroRNA Signature Predicts Survival and Relapse in Lung Cancer
Sung-Liang Yu,1,2,3 Hsuan-Yu Chen,2,6,7 Gee-Chen Chang,9,11 Chih-Yi Chen,10,12 Huei-Wen Chen,13 Sher Singh,14 Chiou-Ling Cheng,2 Chong-Jen Yu,4 Yung-Chie Lee,5 Han-Shiang Chen,15,16 Te-Jen Su,2,11 Ching-Cheng Chiang,2 Han-Ni Li,2 Qi-Sheng Hong,2 Hsin-Yuan Su,2 Chun-Chieh Chen,2 Wan-Jiun Chen,13 Chun-Chi Liu,11 Wing-Kai Chan,3 Wei J. Chen,2,6 Ker-Chau Li,7,17,18 Jeremy J.W. Chen,2,11,18 and Pan-Chyr Yang2,4,8,18,
1 Department of Clinical Laboratory Sciences and Medical Biotechnology, National Taiwan University College of Medicine, Taipei, Taiwan 100, Republic of China
2 NTU Center for Genomic Medicine, National Taiwan University College of Medicine, Taipei, Taiwan 100, Republic of China
3 Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan 100, Republic of China
4 Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan 100, Republic of China
5 Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan 100, Republic of China
6 Graduate Institute of Epidemiology, National Taiwan University, Taipei, Taiwan 100, Republic of China
7 Institute of Statistical Science, Academia Sinica, Taipei, Taiwan 115, Republic of China
8 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan 115, Republic of China
9 Division of Chest Medicine, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan 407, Republic of China
10 Division of Thoracic Surgery, Department of Surgery, Taichung Veterans General Hospital, Taichung, Taiwan 407, Republic of China
11 Institutes of Biomedical Sciences and Molecular Biology, National Chung Hsing University, Taichung, Taiwan 402, Republic of China
12 Division of Thoracic Surgery, Department of Surgery, School of Medicine, China Medical University Hospital, Taichung, Taiwan 404, Republic of China
13 Institute of Pharmacology, College of Medicine, National Yang-Ming University, Taipei, Taiwan 112, Republic of China
14 Department of Life Science, National Taiwan Normal University, Taipei, Taiwan 116, Republic of China
15 Department of Colon & Rectal Surgery, Hualien Tzu Chi Medical Center, Hualien, Taiwan 970, Republic of China
16 Department of Surgery, Hualien Tzu Chi Medical Center, Hualien, Taiwan 970, Republic of China
17 Department of Statistics, University of California, Los Angeles, Los Angeles, California, CA 90095, USA
Corresponding author
Pan-Chyr Yang
pcyang@ntu.edu.tw
Summary
We investigated whether microRNA expression profiles can predict clinical outcome of NSCLC patients. Using real-time RT-PCR, we obtained microRNA expressions in 112 NSCLC patients, which were divided into the training and testing sets. Using Cox regression and risk-score analysis, we identified a five-microRNA signature for the prediction of treatment outcome of NSCLC in the training set. This microRNA signature was validated by the testing set and an independent cohort. Patients with high-risk scores in their microRNA signatures had poor overall and disease-free survivals compared to the low-risk-score patients. This microRNA signature is an independent predictor of the cancer relapse and survival of NSCLC patients.
