Dataset Information

MicroRNA in Lung Cancer Metastasis.

ABSTRACT: Tumor metastasis is a hallmark of cancer, with distant metastasis frequently developing in lung cancer, even at initial diagnosis, resulting in poor prognosis and high mortality. However, available biomarkers cannot reliably predict cancer spreading sites. The metastatic cascade involves highly complicated processes including invasion, migration, angiogenesis, and epithelial-to-mesenchymal transition that are tightly controlled by various genetic expression modalities along with interaction between cancer cells and the extracellular matrix. In particular, microRNAs (miRNAs), a group of small non-coding RNAs, can influence the transcriptional and post-transcriptional processes, with dysregulation of miRNA expression contributing to the regulation of cancer metastasis. Nevertheless, although miRNA-targeted therapy is widely studied in vitro and in vivo, this strategy currently affords limited feasibility and a few miRNA-targeted therapies for lung cancer have entered into clinical trials to date. Advances in understanding the molecular mechanism of metastasis will thus provide additional potential targets for lung cancer treatment. This review discusses the current research related to the role of miRNAs in lung cancer invasion and metastasis, with a particular focus on the different metastatic lesions and potential miRNA-targeted treatments for lung cancer with the expectation that further exploration of miRNA-targeted therapy may establish a new spectrum of lung cancer treatments.

SUBMITTER: Wu SG

PROVIDER: S-EPMC6406837 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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MicroRNA in Lung Cancer Metastasis.

Wu Shang-Gin SG Chang Tzu-Hua TH Liu Yi-Nan YN Shih Jin-Yuan JY

Cancers 20190223 2

Tumor metastasis is a hallmark of cancer, with distant metastasis frequently developing in lung cancer, even at initial diagnosis, resulting in poor prognosis and high mortality. However, available biomarkers cannot reliably predict cancer spreading sites. The metastatic cascade involves highly complicated processes including invasion, migration, angiogenesis, and epithelial-to-mesenchymal transition that are tightly controlled by various genetic expression modalities along with interaction betw ...[more]

PMID: 30813457

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Project description:The lung is one of the most common sites of distant metastasis in breast cancer (BC). Identifying ideal biomarkers to construct a more accurate prediction model than conventional clinical parameters is crucial. MicroRNAs (miRNAs) data and clinicopathological data were acquired from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. miR-663, miR-210, miR-17, miR-301a, miR-135b, miR-451, miR-30a, and miR-199a-5p were screened to be highly relevant to lung metastasis (LM) of BC patients. The miRNA-based risk score was developed based on the logistic coefficient of the individual miRNA. Univariate and multivariate logistic regression selected tumor node metastasis (TNM) stage, age at diagnosis, and miRNA-risk score as independent predictive parameters, which were used to construct a nomogram. The Cancer Genome Atlas (TCGA) database was used to validate the signature and nomogram. The predictive performance of the nomogram was compared to that of the TNM stage. The area under the receiver operating characteristics curve (AUC) of the nomogram was higher than that of the TNM stage in all three cohorts (training cohort: 0.774 vs. 0.727; internal validation cohort: 0.763 vs. 0.583; external validation cohort: 0.925 vs. 0.840). The calibration plot of the nomogram showed good agreement between predicted and observed outcomes. The net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision-curve analysis (DCA) of the nomogram showed that its performances were better than that of the TNM classification system. Functional enrichment analyses suggested several terms with a specific focus on LM. Subgroup analysis showed that miR-30a, miR-135b, and miR-17 have unique roles in lung metastasis of BC. Pan-cancer analysis indicated the significant importance of eight predictive miRNAs in lung metastasis. This study is the first to establish and validate a comprehensive lung metastasis predictive nomogram based on the METABRIC and TCGA databases, which provides a reliable assessment tool for clinicians and aids in appropriate treatment selection.

Dataset Information

MicroRNA in Lung Cancer Metastasis.

Publications

MicroRNA in Lung Cancer Metastasis.

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