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      HCP5 is a SMAD3-responsive long non-coding RNA that promotes lung adenocarcinoma metastasis via miR-203/SNAI axis

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          Abstract

          Introduction: Transforming growth factor-beta (TGFβ) signaling plays a vital role in lung adenocarcinoma (LUAD) progression. However, the involvement of TGFβ-regulated long non-coding RNAs (lncRNAs) in metastasis of LUAD remains poorly understood.

          Methods: We performed bioinformatic analyses to identify putative lncRNAs regulated by TGF-β/SMAD3 and validated the results by quantitative PCR in LUAD cells. We performed luciferase reporter and chromatin immunoprecipitation assays to demonstrate the transcriptional regulation of the lncRNA histocompatibility leukocyte antigen complex P5 (HCP5) we decided to focus on. Stable HCP5 knockdown and HCP5-overexpressing A549 cell variants were generated respectively, to study HCP5 function and understand its mechanism of action. We also confirmed our findings in mouse xenografts and metastasis models. We analyzed the correlation between the level of lncRNA expression with EGFR, KRAS mutations, smoke state and prognostic of LUAD patients.

          Results: We found that the lncRNA HCP5 is induced by TGFβ and transcriptionally regulated by SMAD3 , which promotes LUAD tumor growth and metastasis. Moreover, HCP5 is overexpressed in tumor tissues of patients with LUAD, specifically in patients with EGFR and KRAS mutations and current smoker. HCP5 high expression level is positively correlated with poor prognosis of patients with LUAD. Finally, we demonstrated that upregulation of HCP5 increases the expression of Snail and Slug by sponging the microRNA-203 ( miR-203) and promoting epithelial-mesenchymal transition (EMT) in LUAD cells.

          Conclusions: Our work demonstrates that the lncRNA HCP5 is transcriptionally regulated by SMAD3 and acts as a new regulator in the TGFβ/SMAD signaling pathway. Therefore, HCP5 can serve as a potential therapeutic target in LUAD.

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          Most cited references34

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          Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

          Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .
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            JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update

            JASPAR is a popular open-access database for matrix models describing DNA-binding preferences for transcription factors and other DNA patterns. With its third major release, JASPAR has been expanded and equipped with additional functions aimed at both casual and power users. The heart of the JASPAR database—the JASPAR CORE sub-database—has increased by 12% in size, and three new specialized sub-databases have been added. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval. JASPAR is available at http://jaspar.genereg.net.
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              Clinical development of galunisertib (LY2157299 monohydrate), a small molecule inhibitor of transforming growth factor-beta signaling pathway

              Transforming growth factor-beta (TGF-β) signaling regulates a wide range of biological processes. TGF-β plays an important role in tumorigenesis and contributes to the hallmarks of cancer, including tumor proliferation, invasion and metastasis, inflammation, angiogenesis, and escape of immune surveillance. There are several pharmacological approaches to block TGF-β signaling, such as monoclonal antibodies, vaccines, antisense oligonucleotides, and small molecule inhibitors. Galunisertib (LY2157299 monohydrate) is an oral small molecule inhibitor of the TGF-β receptor I kinase that specifically downregulates the phosphorylation of SMAD2, abrogating activation of the canonical pathway. Furthermore, galunisertib has antitumor activity in tumor-bearing animal models such as breast, colon, lung cancers, and hepatocellular carcinoma. Continuous long-term exposure to galunisertib caused cardiac toxicities in animals requiring adoption of a pharmacokinetic/pharmacodynamic-based dosing strategy to allow further development. The use of such a pharmacokinetic/pharmacodynamic model defined a therapeutic window with an appropriate safety profile that enabled the clinical investigation of galunisertib. These efforts resulted in an intermittent dosing regimen (14 days on/14 days off, on a 28-day cycle) of galunisertib for all ongoing trials. Galunisertib is being investigated either as monotherapy or in combination with standard antitumor regimens (including nivolumab) in patients with cancer with high unmet medical needs such as glioblastoma, pancreatic cancer, and hepatocellular carcinoma. The present review summarizes the past and current experiences with different pharmacological treatments that enabled galunisertib to be investigated in patients.
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                Author and article information

                Journal
                Theranostics
                Theranostics
                thno
                Theranostics
                Ivyspring International Publisher (Sydney )
                1838-7640
                2019
                13 April 2019
                : 9
                : 9
                : 2460-2474
                Affiliations
                [1 ]The Key Laboratory of Carcinogenesis of the Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, Hunan, China
                [2 ]The Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute and School of Basic Medical Sciences, Central South University, Changsha, Hunan, China
                [3 ]Department of Thoracic and Cardiovascular Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
                [4 ]Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China
                [5 ]High Resolution Mass Spectrometry Laboratory of Advanced Research Center, Central South University, Changsha, Hunan, China
                Author notes
                ✉ Corresponding author: Zheng Li, Cancer Research Institute, Central South University, 110 Xiangya Road, 410078, Changsha, China. E-mail: lizheng@ 123456csu.edu.cn .

                Competing Interests: The authors have declared that no competing interest exists.

                Article
                thnov09p2460
                10.7150/thno.31097
                6525996
                31131047
                c240284a-a862-48e9-8780-9b800d6f55c0
                © Ivyspring International Publisher

                This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license ( https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions.

                History
                : 30 October 2018
                : 23 March 2019
                Categories
                Research Paper

                Molecular medicine
                smad3,long non-coding rna,hcp5,lung adenocarcinoma,metastasis.
                Molecular medicine
                smad3, long non-coding rna, hcp5, lung adenocarcinoma, metastasis.

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