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      Lysophosphatidic acid receptor 6 regulated by miR-27a-3p attenuates tumor proliferation in breast cancer

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          Abstract

          Purpose

          Lysophosphatidic acid (LPA) is a bioactive molecule which participates in many physical and pathological processes. Although LPA receptor 6 (LPAR6), the last identified LPA receptor, has been reported to have diverse effects in multiple cancers, including breast cancer, its effects and functioning mechanisms are not fully known.

          Methods

          Multiple public databases were used to investigate the mRNA expression of LPAR6, its prognostic value, and potential mechanisms in breast cancer. Western blotting was performed to validate the differential expression of LPAR6 in breast cancer tissues and their adjacent tissues. Furthermore, in vitro experiments were used to explore the effects of LPAR6 on breast cancer. Additionally, TargetScan and miRWalk were used to identify potential upstream regulating miRNAs and validated the relationship between miR-27a-3p and LPAR6 via real-time polymerase chain reaction and an in vitro rescue assay.

          Results

          LPAR6 was significantly downregulated in breast cancer at transcriptional and translational levels. Decreased LPAR6 expression in breast cancer is significantly correlated with poor overall survival, disease-free survival, and distal metastasis-free survival, particularly for hormone receptor-positive patients, regardless of lymph node metastatic status. In vitro gain and loss-of-function assays indicated that LPAR6 attenuated breast cancer cell proliferation. The analyses of TCGA and METABRIC datasets revealed that LPAR6 may regulate the cell cycle signal pathway. Furthermore, the expression of LPAR6 could be positively regulated by miR-27a-3p. The knockdown of miR-27a-3p increased cell proliferation, and ectopic expression of LPAR6 could partly rescue this phenotype.

          Conclusion

          LPAR6 acts as a tumor suppressor in breast cancer and is positively regulated by miR-27a-3p.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s12094-021-02704-8.

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          clusterProfiler: an R package for comparing biological themes among gene clusters.

          Guangchuang Yu, Li-Gen Wang, Yanyan Han … (2012)
          Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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            Cancer Statistics, 2021

            Rebecca Siegel, Kimberly D Miller, Hannah Fuchs … (2021)
            Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2017) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2018) were collected by the National Center for Health Statistics. In 2021, 1,898,160 new cancer cases and 608,570 cancer deaths are projected to occur in the United States. After increasing for most of the 20th century, the cancer death rate has fallen continuously from its peak in 1991 through 2018, for a total decline of 31%, because of reductions in smoking and improvements in early detection and treatment. This translates to 3.2 million fewer cancer deaths than would have occurred if peak rates had persisted. Long-term declines in mortality for the 4 leading cancers have halted for prostate cancer and slowed for breast and colorectal cancers, but accelerated for lung cancer, which accounted for almost one-half of the total mortality decline from 2014 to 2018. The pace of the annual decline in lung cancer mortality doubled from 3.1% during 2009 through 2013 to 5.5% during 2014 through 2018 in men, from 1.8% to 4.4% in women, and from 2.4% to 5% overall. This trend coincides with steady declines in incidence (2.2%-2.3%) but rapid gains in survival specifically for nonsmall cell lung cancer (NSCLC). For example, NSCLC 2-year relative survival increased from 34% for persons diagnosed during 2009 through 2010 to 42% during 2015 through 2016, including absolute increases of 5% to 6% for every stage of diagnosis; survival for small cell lung cancer remained at 14% to 15%. Improved treatment accelerated progress against lung cancer and drove a record drop in overall cancer mortality, despite slowing momentum for other common cancers.
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              Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

              J. Gao, B. A. Aksoy, U Dogrusoz … (2015)
              The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
              Article 0 comments Cited 6243 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                S. Liu:
                ORCID: http://orcid.org/0000-0002-9933-3643
                liushengchun1968@163.com
                Journal
                Journal ID (nlm-ta): Clin Transl Oncol
                Journal ID (iso-abbrev): Clin Transl Oncol
                Title: Clinical & Translational Oncology
                Publisher: Springer International Publishing (Cham )
                ISSN (Print): 1699-048X
                ISSN (Electronic): 1699-3055
                Publication date (Electronic): 12 September 2021
                Publication date PMC-release: 12 September 2021
                Publication date (Print): 2022
                Volume: 24
                Issue: 3
                Pages: 503-516
                Affiliations
                [1 ]GRID grid.452206.7, ISNI 0000 0004 1758 417X, Endocrine Breast Surgery, , The First Affiliated Hospital of Chongqing Medical University, ; No.1 Youyi Road, Yuzhong District, Chongqing, 400016 China
                [2 ]Department of Cardiology, Chongqing Kanghua Zhonglian Cardiovascular Hospital, Jiangbei District, No. 168 Haier Rd, Chongqing, 400016 China
                Author information
                http://orcid.org/0000-0002-9933-3643
                Article
                Publisher ID: 2704
                DOI: 10.1007/s12094-021-02704-8
                PMC ID: 8885522
                PubMed ID: 34510318
                SO-VID: fe3c1332-a162-4164-bf92-c0f3d020445f
                Copyright © © The Author(s) 2021
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 16 June 2021
                Date accepted : 31 August 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, national natural science foundation of china;
                Award ID: 81772979
                Award Recipient :
                Categories
                Subject: Research Article
                Custom metadata
                issue-copyright-statement © The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO) 2022

                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: lysophosphatidic acid receptor 6,mir-27a-3p,breast cancer,cell proliferation
                Data availability:
                ScienceOpen disciplines: Oncology & Radiotherapy
                Keywords: lysophosphatidic acid receptor 6, mir-27a-3p, breast cancer, cell proliferation

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