Hua Peng1, Jia Wang1, Jia Li2, Mei Zhao1, Sheng-Kai Huang1, Yu-Yu Gu1, Yan Li1, Xiao-Jie Sun3, Lin Yang4, Qing Luo5, Chang-Zhi Huang6. 1. Department of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, China. 2. Clinical Laboratory Department, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 3. Department of Biochemistry, Qiqihar Medical University, China. Electronic address: 389581415@qq.com. 4. Department of Pathology, Cancer Hospital, Chinese Academy of Medical Sciences, 17 Panjiayuan Nanli, Chaoyang District, Beijing, China. Electronic address: yanlin@cicams.ac.cn. 5. Molecular Oncology Laboratory, Cancer Hospital, Affiliated Hospital of Zunyi Medical College, Zunyi, China. Electronic address: luoqing730@126.com. 6. Department of Etiology and Carcinogenesis, State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing, China. Electronic address: huangpumc@163.com.
Abstract
AIMS: Early non-small cell lung cancer (NSCLC) diagnosis is generally poor due to the lack of convenient and noninvasive tools. MicroRNAs (miRNAs) and the long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) are non-coding RNAs, that have attracted increased attention for their use as NSCLC tumor diagnostic markers. MAIN METHODS: We constructed a serum miRNA and MALAT1 non-coding RNA panel and tested its diagnostic performance as an NSCLC biomarker. We tested the expression of 11 candidate miRNAs and MALAT1 in a training set (36 NSCLCs vs. 36 controls) by quantitative reverse transcription polymerase chain reactions. The serum non-coding RNA panel's diagnostic efficiency was tested and validated in a second validation sample set (120 NSCLCs and 71 controls) by receiver operating characteristic (ROC) curve analyses. KEY FINDINGS: In the training set, the expression of the four non-coding RNAs (miR-1254, miR-485-5p, miR-574-5p, and MALAT1) was obviously different between the NSCLC patients and healthy controls. Risk score analysis revealed that the four non-coding RNA panel can distinguish NSCLC patient samples from controls. The ROC curve results revealed areas under the curves (AUCs) of 0.861 (95% confidence interval (CI) 0.771-0.952) and 0.844 (95% CI0.778-0.910) for the training set and validation set, respectively. SIGNIFICANCE: The four non-coding RNA risk scores were also associated with NSCLC progression, and its diagnostic efficiency was relatively high for stages I/II/III. In conclusion, these data indicate that the four non-coding RNA panel can serve as a convenient tool for early NSCLC diagnosis.
AIMS: Early non-small cell lung cancer (NSCLC) diagnosis is generally poor due to the lack of convenient and noninvasive tools. MicroRNAs (miRNAs) and the long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) are non-coding RNAs, that have attracted increased attention for their use as NSCLC tumor diagnostic markers. MAIN METHODS: We constructed a serum miRNA and MALAT1 non-coding RNA panel and tested its diagnostic performance as an NSCLC biomarker. We tested the expression of 11 candidate miRNAs and MALAT1 in a training set (36 NSCLCs vs. 36 controls) by quantitative reverse transcription polymerase chain reactions. The serum non-coding RNA panel's diagnostic efficiency was tested and validated in a second validation sample set (120 NSCLCs and 71 controls) by receiver operating characteristic (ROC) curve analyses. KEY FINDINGS: In the training set, the expression of the four non-coding RNAs (miR-1254, miR-485-5p, miR-574-5p, and MALAT1) was obviously different between the NSCLCpatients and healthy controls. Risk score analysis revealed that the four non-coding RNA panel can distinguish NSCLCpatient samples from controls. The ROC curve results revealed areas under the curves (AUCs) of 0.861 (95% confidence interval (CI) 0.771-0.952) and 0.844 (95% CI0.778-0.910) for the training set and validation set, respectively. SIGNIFICANCE: The four non-coding RNA risk scores were also associated with NSCLC progression, and its diagnostic efficiency was relatively high for stages I/II/III. In conclusion, these data indicate that the four non-coding RNA panel can serve as a convenient tool for early NSCLC diagnosis.
Authors: Lisha Ying; Lingbin Du; Ruiyang Zou; Lei Shi; Nan Zhang; Jiaoyue Jin; Chenyang Xu; Fanrong Zhang; Chen Zhu; Junzhou Wu; Kaiyan Chen; Minran Huang; Yingxue Wu; Yimin Zhang; Weihui Zheng; Xiaodan Pan; Baofu Chen; Aifen Lin; John Kit Chung Tam; Rob Martinus van Dam; David Tien Min Lai; Kee Seng Chia; Lihan Zhou; Heng-Phon Too; Herbert Yu; Weimin Mao; Dan Su Journal: Proc Natl Acad Sci U S A Date: 2020-09-17 Impact factor: 11.205