| Name | long intergenic non-protein coding RNA 1193 |
| Summary |
{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n Although none of the abstracts provided actually mention or characterize "}, {"type": "b", "children": [{"type": "t", "text": "LINC01193"}]}, {"type": "t", "text": ", they collectively offer detailed insight into the function of an important immune‐regulatory locus—CTLA‑4—which serves as a paradigmatic example of how genetic variation in regulatory elements can modulate T‐cell responses. In these studies, CTLA‑4 is shown to act as a key negative regulator of T‑cell activation, with polymorphisms (for example, the +49A/G and CT60 variants) altering mRNA splicing, protein expression, and ultimately T‑cell receptor signaling thresholds. Such genetic differences have been linked to a range of clinical outcomes across multiple conditions, including autoimmune disorders (such as rheumatoid arthritis, Graves’ disease, Hashimoto thyroiditis, and type 1 diabetes) and even certain malignancies and transplant responses (see."}, {"type": "fg", "children": [{"type": "fg_fs", "start_ref": "1", "end_ref": "4"}]}, {"type": "t", "text": " In several reports, specific CTLA‑4 haplotypes have been associated not only with disease susceptibility and phenotype but with differences in response to immunomodulatory therapies—underscoring the importance of precisely regulated co‐inhibitory signals in maintaining immune tolerance (for example."}, {"type": "fg", "children": [{"type": "fg_fs", "start_ref": "5", "end_ref": "8"}]}, {"type": "t", "text": " Moreover, functional studies demonstrate that disease‐associated CTLA‑4 variants can modify intracellular signaling cascades in both naïve and memory T cells, thereby influencing key immunologic thresholds that are critical for the regulation of self‐tolerance."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "9"}]}, {"type": "t", "text": "\n "}]}, {"type": "t", "text": "\n "}, {"type": "p", "children": [{"type": "t", "text": "\n In the broader context, these findings emphasize that regulatory elements—whether protein‐coding like CTLA‑4 or noncoding such as long intergenic noncoding RNAs—can play crucial roles in fine‐tuning immune responses. Although none of the present studies address "}, {"type": "b", "children": [{"type": "t", "text": "LINC01193"}]}, {"type": "t", "text": " directly, the mechanisms described for CTLA‑4 serve as a conceptual framework. It is conceivable that LINC01193, as a long noncoding RNA, might similarly function in the regulation of immune cell activation or modulation of key inhibitory checkpoints. Future studies will be required to determine whether LINC01193 influences T‑cell signaling, perhaps by interacting with the CTLA‑4 pathway or other mediators of immune tolerance.\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Robert M Plenge, Leonid Padyukov, Elaine F Remmers, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Replication of putative candidate-gene associations with rheumatoid arthritis in >4,000 samples from North America and Sweden: association of susceptibility with PTPN22, CTLA4, and PADI4."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Am J Hum Genet (2005)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1086/498651"}], "href": "https://doi.org/10.1086/498651"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "16380915"}], "href": "https://pubmed.ncbi.nlm.nih.gov/16380915"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Fotini K Kavvoura, Takashi Akamizu, Takuya Awata, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Cytotoxic T-lymphocyte associated antigen 4 gene polymorphisms and autoimmune thyroid disease: a meta-analysis."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "J Clin Endocrinol Metab (2007)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1210/jc.2007-0147"}], "href": "https://doi.org/10.1210/jc.2007-0147"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "17504905"}], "href": "https://pubmed.ncbi.nlm.nih.gov/17504905"}]}, {"type": "r", "ref": 3, "children": [{"type": "t", "text": "A Pavlova, D Delev, S Lacroix-Desmazes, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Impact of polymorphisms of the major histocompatibility complex class II, interleukin-10, tumor necrosis factor-alpha and cytotoxic T-lymphocyte antigen-4 genes on inhibitor development in severe hemophilia A."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "J Thromb Haemost (2009)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1111/j.1538-7836.2009.03636.x"}], "href": "https://doi.org/10.1111/j.1538-7836.2009.03636.x"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "19817985"}], "href": "https://pubmed.ncbi.nlm.nih.gov/19817985"}]}, {"type": "r", "ref": 4, "children": [{"type": "t", "text": "Ming-Chu Chang, Yu-Ting Chang, Yu-Wen Tien, et al. 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"}, {"type": "b", "children": [{"type": "t", "text": "Association of the CT60 marker of the CTLA4 gene with systemic lupus erythematosus."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Arthritis Rheum (2004)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1002/art.20347"}], "href": "https://doi.org/10.1002/art.20347"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "15248219"}], "href": "https://pubmed.ncbi.nlm.nih.gov/15248219"}]}, {"type": "r", "ref": 6, "children": [{"type": "t", "text": "Willemijn B Breunis, Eduardo Tarazona-Santos, Renee Chen, et al. 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"}, {"type": "b", "children": [{"type": "t", "text": "Genetic polymorphisms in PTPN22, PADI-4, and CTLA-4 and risk for rheumatoid arthritis in two longitudinal cohort studies: evidence of gene-environment interactions with heavy cigarette smoking."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Arthritis Res Ther (2008)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/ar2421"}], "href": "https://doi.org/10.1186/ar2421"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "18462498"}], "href": "https://pubmed.ncbi.nlm.nih.gov/18462498"}]}]}]}
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| Synonyms | CT60 |
| NCBI Gene ID | 348120 |
| API | |
| Download Associations | |
| Predicted Functions |
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| Co-expressed Genes |
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| Expression in Tissues and Cell Lines |
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LINC01193 has 154 functional associations with biological entities spanning 2 categories (cell line, cell type or tissue, gene, protein or microRNA) extracted from 5 datasets.
Click the + buttons to view associations for LINC01193 from the datasets below.
If available, associations are ranked by standardized value
| Dataset | Summary | |
|---|---|---|
| CCLE Cell Line Gene CNV Profiles | cell lines with high or low copy number of LINC01193 gene relative to other cell lines from the CCLE Cell Line Gene CNV Profiles dataset. | |
| GEO Signatures of Differentially Expressed Genes for Gene Perturbations | gene perturbations changing expression of LINC01193 gene from the GEO Signatures of Differentially Expressed Genes for Gene Perturbations dataset. | |
| GEO Signatures of Differentially Expressed Genes for Transcription Factor Perturbations | transcription factor perturbations changing expression of LINC01193 gene from the GEO Signatures of Differentially Expressed Genes for Transcription Factor Perturbations dataset. | |
| GTEx Tissue Gene Expression Profiles | tissues with high or low expression of LINC01193 gene relative to other tissues from the GTEx Tissue Gene Expression Profiles dataset. | |
| Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles | cell lines with high or low copy number of LINC01193 gene relative to other cell lines from the Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles dataset. | |