Literature DB >> 33253979

miRNAs in lung cancer. A systematic review identifies predictive and prognostic miRNA candidates for precision medicine in lung cancer.

Shen Zhong1, Heiko Golpon2, Patrick Zardo3, Jürgen Borlak4.   

Abstract

Lung cancer (LC) is the leading cause of cancer-related death worldwide and miRNAs play a key role in LC development. To better diagnose LC and to predict drug treatment responses we evaluated 228 articles encompassing 16,697 patients and 12,582 healthy controls. Based on the criteria of ≥3 independent studies and a sensitivity and specificity of >0.8 we found blood-borne miR-20a, miR-10b, miR-150, and miR-223 to be excellent diagnostic biomarkers for non-small cell LC whereas miR-205 is specific for squamous cell carcinoma. The systematic review also revealed 38 commonly regulated miRNAs in tumor tissue and the circulation, thus enabling the prediction of histological subtypes of LC. Moreover, theranostic biomarker candidates with proven responsiveness to checkpoint inhibitor treatments were identified, notably miR-34a, miR-93, miR-106b, miR-181a, miR-193a-3p, and miR-375. Conversely, miR-103a-3p, miR-152, miR-152-3p, miR-15b, miR-16, miR-194, miR-34b, and miR-506 influence programmed cell death-ligand 1 and programmed cell death-1 receptor expression, therefore providing a rationale for the development of molecularly targeted therapies. Furthermore, miR-21, miR-25, miR-27b, miR-19b, miR-125b, miR-146a, and miR-210 predicted response to platinum-based treatments. We also highlight controversial reports on specific miRNAs. In conclusion, we report diagnostic miRNA biomarkers for in-depth clinical evaluation. Furthermore, in an effort to avoid unnecessary toxicity we propose predictive biomarkers. The biomarker candidates support personalized treatment decisions of LC patients and await their confirmation in randomized clinical trials.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  AD = adenocarcinoma; AUC-ROC curve = area under the receiver operating characteristics curve; BSC = best supportive care; CEA = carcinoembryonic antigen; CYFRA21-1 = cytokeratin 19 fragment 21-1; ICIs = immune checkpoint inhibitors; LCC = large cell carcinoma; LC = lung cancer; LDCT = low-dose CT; NSCLC = non–small cell lung cancer; PBMC = peripheral blood mononuclear cell; PD-1 = programmed cell death-1; PD-L1 = programmed cell death-ligand 1; PET = positron emission tomography; PNs = pulmonary nodules; SCC = squamous cell carcinoma antigen; SCLC = small cell lung cancer; SQ = squamous cell carcinoma; TMB = tumor mutation burden; ddPCR = droplet digital PCR

Year:  2020        PMID: 33253979     DOI: 10.1016/j.trsl.2020.11.012

Source DB:  PubMed          Journal:  Transl Res        ISSN: 1878-1810            Impact factor:   7.012


  26 in total

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Authors:  Zhikun Shi; Xu Zhou; Meijing Bao; Rongxia Jia; Yuqing Chu; Yang Lin
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2.  Cellular and Molecular Profiling of Tumor Microenvironment and Early-Stage Lung Cancer.

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Review 4.  Insights Into Platelet-Derived MicroRNAs in Cardiovascular and Oncologic Diseases: Potential Predictor and Therapeutic Target.

Authors:  Qianru Leng; Jie Ding; Meiyan Dai; Lei Liu; Qing Fang; Dao Wen Wang; Lujin Wu; Yan Wang
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Authors:  Yuka Muramatsu-Maekawa; Kyojiro Kawakami; Yasunori Fujita; Manabu Takai; Daiki Kato; Keita Nakane; Taku Kato; Tomohiro Tsuchiya; Takuya Koie; Yuri Miura; Masafumi Ito; Kosuke Mizutani
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Review 7.  Next-Generation Sequencing with Liquid Biopsies from Treatment-Naïve Non-Small Cell Lung Carcinoma Patients.

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Journal:  Ann Med       Date:  2021-12       Impact factor: 4.709

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Authors:  Ke Wan; Ziwei Tu; Zhentian Liu; Yun Cai; Yinglan Chen; Chunhua Ling
Journal:  Exp Ther Med       Date:  2021-06-07       Impact factor: 2.447

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