High diagnostic value of miRNAs for NSCLC: quantitative analysis for both single and combined miRNAs in lung cancer

Minhan Yi; Zexi Liao; Langmei Deng; Li Xu; Yun Tan; Kun Liu; Ziliang Chen; Yuan Zhang

doi:10.1080/07853890.2021.2000634

High diagnostic value of miRNAs for NSCLC: quantitative analysis for both single and combined miRNAs in lung cancer

Ann Med. 2021 Dec;53(1):2178-2193. doi: 10.1080/07853890.2021.2000634.

Authors

Minhan Yi^{1

2

3}, Zexi Liao^{1

4}, Langmei Deng^{1

5}, Li Xu^{1

2}, Yun Tan², Kun Liu², Ziliang Chen⁶, Yuan Zhang^{1

3}

Affiliations

¹ Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China.
² School of Life Sciences, Central South University, Changsha, Hunan, China.
³ National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
⁴ Xiangya Medical School, Central South University, Changsha, Hunan, China.
⁵ Department of Emergency, The Third Xiangya Hospital, Central South University, Changsha, Hunan, China.
⁶ School of Computer Science and Engineering, Central South University, Changsha, Hunan, China.

Abstract

Background: MicroRNAs (miRNAs) are good candidates as biomarkers for Lung cancer (LC). The aim of this article is to figure out the diagnostic value of both single and combined miRNAs in LC.

Methods: Normative meta-analysis was conducted based on PRISMA. We assessed the diagnostic value by calculating the combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) and the area under the curve (AUC) of single and combined miRNAs for LC and specific subgroups.

Results: A total of 80 qualified studies with a total of 8971 patients and 10758 controls were included. In non-small cell lung carcinoma (NSCLC), we involved 20 single-miRNAs and found their Sen, Spe and AUC ranged from 0.52-0.81, 0.66-0.88, and 0.68-0.90, respectively, specially, miR-19 with the maximum Sen, miR-20 and miR-10 with the highest Spe as well as miR-17 with the maximum AUC. Additionally, we detected miR-21 with the maximum Sen of 0.74 [95%CI: 0.62-0.83], miR-146 with the maximum Spe and AUC of 0.93 [95%CI: 0.79-0.98] and 0.89 [95%CI: 0.86-0.92] for early-stage NSCLC. We also identified the diagnostic power of available panel (miR-210, miR-31 and miR-21) for NSCLC with satisfying Sen, Spe and AUC of 0.82 [95%CI: 0.78-0.84], 0.87 [95%CI: 0.84-0.89] and 0.91 [95%CI: 0.88-0.93], and furtherly constructed 2 models for better diagnosis.

Conclusions: We identified several single miRNAs and combined groups with high diagnostic power for NSCLC through pooled quantitative analysis, which shows that specific miRNAs are good biomarker candidates for NSCLC and further researches needed.

Keywords: Lung cancer; NSCLC; diagnostic biomarker; early diagnosis; microRNA.

Publication types

Meta-Analysis
Research Support, Non-U.S. Gov't

MeSH terms

Area Under Curve
Biomarkers, Tumor / genetics
Carcinoma, Non-Small-Cell Lung* / diagnosis
Carcinoma, Non-Small-Cell Lung* / genetics
Humans
Lung Neoplasms* / diagnosis
Lung Neoplasms* / genetics
MicroRNAs* / metabolism

Substances

Biomarkers, Tumor
MicroRNAs

Grants and funding

This research was supported by the National Natural Science Foundation of China [No. 82001357, No. 31500999], the Hunan Provincial Natural Science Foundation of China [No. 2020JJ5951, No. 2021JJ80079], the Changsha Municipal Natural Science Foundation [No. kq2014123], the Scientific Research Project of Hunan Provincial Health Commission [No. 202103021406], the Youth Science Foundation of Xiangya Hospital [No. 2019Q17], the Degree & Postgraduate Education Reform Project of Central South University [No. 2020JGB125, No. 2021YJSKSA10] and the Undergraduate Education Reform Project of Central South University [No. 2020jy146, No.2020kcsz032].