5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Molecular characteristics and therapeutic implications of Toll-like receptor signaling pathway in melanoma

      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

          Melanoma is a malignant tumor of melanocytes and is often considered immunogenic cancer. Toll-like receptor-related genes are expressed differently in most types of cancer, depending on the immune microenvironment inside cancer, and the key function of Toll-like receptors (TLRs) for melanoma has not been fully elucidated. Based on multi-omics data from TCGA and GEO databases, we first performed pan-cancer analysis on TLR, including CNV, SNV, and mRNA changes in TLR-related genes in multiple human cancers, as well as patient prognosis characterization. Then, we divided melanoma patients into three subgroups (clusters 1, 2, and 3) according to the expression of the TLR pathway, and explored the correlation between TLR pathway and melanoma prognosis, immune infiltration, metabolic reprogramming, and oncogene expression characteristics. Finally, through univariate Cox regression analysis and LASSO algorithm, we selected six TLR-related genes to construct a survival prognostic model, divided melanoma patients into the training set, internal validation set 1, internal validation set 2, and external validation set for multiple validations, and discussed the correlation between model genes and clinical features of melanoma patients. In conclusion, we constructed a prognostic survival model based on TLR-related genes that precisely and independently demonstrated the potential to assess the prognosis and immune traits of melanoma patients, which is critical for patients’ survival.

          Related collections

          Most cited references49

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

          Toward understanding the origin and evolution of cellular organisms

          In this era of high‐throughput biology, bioinformatics has become a major discipline for making sense out of large‐scale datasets. Bioinformatics is usually considered as a practical field developing databases and software tools for supporting other fields, rather than a fundamental scientific discipline for uncovering principles of biology. The KEGG resource that we have been developing is a reference knowledge base for biological interpretation of genome sequences and other high‐throughput data. It is now one of the most utilized biological databases because of its practical values. For me personally, KEGG is a step toward understanding the origin and evolution of cellular organisms.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            KEGG for taxonomy-based analysis of pathways and genomes

            KEGG ( https://www.kegg.jp ) is a manually curated database resource integrating various biological objects categorized into systems, genomic, chemical and health information. Each object (database entry) is identified by the KEGG identifier (kid), which generally takes the form of a prefix followed by a five-digit number, and can be retrieved by appending /entry/kid in the URL. The KEGG pathway map viewer, the Brite hierarchy viewer and the newly released KEGG genome browser can be launched by appending /pathway/kid, /brite/kid and /genome/kid, respectively, in the URL. Together with an improved annotation procedure for KO (KEGG Orthology) assignment, an increasing number of eukaryotic genomes have been included in KEGG for better representation of organisms in the taxonomic tree. Multiple taxonomy files are generated for classification of KEGG organisms and viruses, and the Brite hierarchy viewer is used for taxonomy mapping, a variant of Brite mapping in the new KEGG Mapper suite. The taxonomy mapping enables analysis of, for example, how functional links of genes in the pathway and physical links of genes on the chromosome are conserved among organism groups.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors.

              The discovery of Toll-like receptors (TLRs) as components that recognize conserved structures in pathogens has greatly advanced understanding of how the body senses pathogen invasion, triggers innate immune responses and primes antigen-specific adaptive immunity. Although TLRs are critical for host defense, it has become apparent that loss of negative regulation of TLR signaling, as well as recognition of self molecules by TLRs, are strongly associated with the pathogenesis of inflammatory and autoimmune diseases. Furthermore, it is now clear that the interaction between TLRs and recently identified cytosolic innate immune sensors is crucial for mounting effective immune responses. Here we describe the recent advances that have been made by research into the role of TLR biology in host defense and disease.
                Bookmark

                Author and article information

                Contributors
                afn199505@163.com
                amy4963@163.com
                qihangdy@163.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                4 September 2023
                4 September 2023
                2023
                : 13
                : 13788
                Affiliations
                [1 ]GRID grid.452435.1, ISNI 0000 0004 1798 9070, Department of Dermatology, , First Affiliated Hospital of Dalian Medical University, ; Dalian, Liaoning China
                [2 ]GRID grid.452435.1, ISNI 0000 0004 1798 9070, Department of General Surgery, , First Affiliated Hospital of Dalian Medical University, ; Dalian, Liaoning China
                [3 ]GRID grid.452435.1, ISNI 0000 0004 1798 9070, Department of Urology, , First Affiliated Hospital of Dalian Medical University, ; Dalian, Liaoning China
                [4 ]GRID grid.452435.1, ISNI 0000 0004 1798 9070, Department of Oncology, , First Affiliated Hospital of Dalian Medical University, ; Dalian, China
                Article
                38850
                10.1038/s41598-023-38850-y
                10477197
                37666853
                4aeac3a6-d588-4dec-8bb8-a01a32ed3367
                © Springer Nature Limited 2023

                Open Access This 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
                : 20 May 2023
                : 16 July 2023
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2023

                Uncategorized
                computational biology and bioinformatics,oncology,pathogenesis
                Uncategorized
                computational biology and bioinformatics, oncology, pathogenesis

                Comments

                Comment on this article