3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      SLC7A1 Overexpression Is Involved in Energy Metabolism Reprogramming to Induce Tumor Progression in Epithelial Ovarian Cancer and Is Associated with Immune-Infiltrating Cells

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Cationic amino acid transporters (SLC7A1/CAT1) are highly expressed in human ovarian cancer (OC) tissues. However, the specific biological functions and mechanisms involved remain unclear. We used bioinformatics analysis to explore SLC7A1 expression level, prognostic value, and tumor mutation burden (TMB) in ovarian cancer (OC) tissues. We performed in vitro experiments to identify the expression and biological function of SLC7A1 in epithelial ovarian cancer (EOC) tissues and cells. An amino acid autoanalyzer was used to detect the effect of SLC7A1 on amino acid metabolism in EOC cells. Finally, SLC7A1 in OC was evaluated for cell-to-cell signalling and immune infiltration using online databases. We found that increased SLC7A1 expression in EOC cells and tissues was associated with poorer survival outcomes ( P < 0.05) but not with tumor stage or grade of OC ( P > 0.05). SLC7A1 is involved in the transport of phenylalanine and arginine in EOC cells, and its knockdown reduced the proliferation and migration of EOC cells and the resistance of cells to cisplatin. Furthermore, the TIMER database indicated that SLC7A1 overexpression was significantly positively correlated with levels of CD4 + memory resting cells, CD8 + effector memory cells, M0 macrophages, and cancer-associated fibroblasts (CAFs) in OC ( P < 0.05) and significantly negatively correlated with CD4 + memory-activated cells ( P < 0.05). Cell immunofluorescence indicated that SLC7A1 overexpression may affect the distribution of immune-infiltrating lymphocytes in tumors by inhibiting the expression of CCL4. Therefore, we concluded that SLC7A1 is involved in the metabolic remodelling of amino acids in EOC to promote tumor development and cisplatin resistance and is related to the tumor-infiltrating immune microenvironment of OC. SLC7A1 is a biomarker for predicting EOC progression and cisplatin resistance and represents a promising target for EOC treatment.

          Related collections

          Most cited references47

          • Record: found
          • Abstract: found
          • Article: not found

          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

            DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Proteomics. Tissue-based map of the human proteome.

              Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body. Copyright © 2015, American Association for the Advancement of Science.
                Bookmark

                Author and article information

                Contributors
                Journal
                J Oncol
                J Oncol
                jo
                Journal of Oncology
                Hindawi
                1687-8450
                1687-8469
                2022
                12 September 2022
                : 2022
                : 5864826
                Affiliations
                1Department of Obstetrics and Gynaecology, The Affiliated Hospital of Qingdao University, Qingdao, 266003 Shandong, China
                2Department of Gynecology, Qingdao Municipal Hospital, Qingdao, 266011 Shandong, China
                3Medical Research Center, The Affiliated Hospital of Qingdao University, Qingdao, 266000 Shandong, China
                Author notes

                Academic Editor: Magesh Muthu

                Author information
                https://orcid.org/0000-0002-3044-1494
                https://orcid.org/0000-0002-2740-8060
                https://orcid.org/0000-0002-4633-8328
                https://orcid.org/0000-0002-9521-521X
                https://orcid.org/0000-0003-1546-1048
                Article
                10.1155/2022/5864826
                9484923
                36131790
                d922f31d-631d-48f0-9125-fe118539ec77
                Copyright © 2022 Shijing You et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 3 June 2022
                : 8 August 2022
                : 24 August 2022
                Funding
                Funded by: Science and Technology Bureau of Qingdao West Coast New Area
                Award ID: 2019-55
                Funded by: Natural Science Foundation of Shandong Province, China
                Award ID: ZR2021QH207
                Funded by: 2020 Annual Science and Technology Project of Qingdao West Coast New Area
                Award ID: 2020-53
                Funded by: Natural Science Foundation of Shandong Province
                Funded by: Qingdao West Coast New Area
                Categories
                Research Article

                Oncology & Radiotherapy
                Oncology & Radiotherapy

                Comments

                Comment on this article