| Name | IQCH antisense RNA 1 |
| Summary |
{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n Although none of the provided abstracts specifically mention IQCH‐AS1, the collective insights from these studies underscore key roles for long non‐coding RNAs (lncRNAs) in disease development and prognosis. For example, one study demonstrating an individualized approach to differential lncRNA expression in lung adenocarcinoma showed that disruptions in the normal ordering of lncRNA expression can be harnessed to build prognostic signatures that reliably stratify patients (see."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": " In another investigation focused on severe burn injuries, lncRNAs were integrated into miRNA–mRNA regulatory networks, suggesting that such molecules can modulate critical cellular pathways including ribosome biogenesis and MAPK signaling."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "2"}]}, {"type": "t", "text": " Similarly, a study in multiple myeloma identified a lincRNA signature that independently predicted progression-free and overall survival, further highlighting the potential clinical impact of deregulated lncRNA expression."}, {"type": "fg", "children": [{"type": "fg_f", "ref": "3"}]}, {"type": "t", "text": "\n "}]}, {"type": "t", "text": "\n "}, {"type": "p", "children": [{"type": "t", "text": "\n By extrapolating from these findings, IQCH‐AS1—a long non‐coding RNA—could be hypothesized to exert similar functional influences. It may participate in the deregulation of gene expression networks in disease contexts, potentially affecting cell proliferation, stress response, or other pathways involved in oncogenesis or tissue repair. However, targeted investigations are required to clarify its precise molecular mechanisms and its impact on disease initiation and progression.\n "}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Fuduan Peng, Ruiping Wang, Yuanyuan Zhang, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Differential expression analysis at the individual level reveals a lncRNA prognostic signature for lung adenocarcinoma."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Mol Cancer (2017)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/s12943-017-0666-z"}], "href": "https://doi.org/10.1186/s12943-017-0666-z"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "28587642"}], "href": "https://pubmed.ncbi.nlm.nih.gov/28587642"}]}, {"type": "r", "ref": 2, "children": [{"type": "t", "text": "Gongjie Tang, Tao Zhang, Xinbo Wang, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Sub-pathway analysis for severe burns injury patients: Identification of potential key lncRNAs by analyzing lncRNA-mRNA profile."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Exp Ther Med (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.3892/etm.2018.6089"}], "href": "https://doi.org/10.3892/etm.2018.6089"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "29805546"}], "href": "https://pubmed.ncbi.nlm.nih.gov/29805546"}]}, {"type": "r", "ref": 3, "children": [{"type": "t", "text": "Mehmet Kemal Samur, Stephane Minvielle, Annamaria Gulla, et al. "}, {"type": "b", "children": [{"type": "t", "text": "Long intergenic non-coding RNAs have an independent impact on survival in multiple myeloma."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Leukemia (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1038/s41375-018-0116-y"}], "href": "https://doi.org/10.1038/s41375-018-0116-y"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "29749396"}], "href": "https://pubmed.ncbi.nlm.nih.gov/29749396"}]}]}]}
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| NCBI Gene ID | 100506686 |
| 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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IQCH-AS1 has 827 functional associations with biological entities spanning 5 categories (organism, disease, phenotype or trait, chemical, cell line, cell type or tissue, gene, protein or microRNA) extracted from 14 datasets.
Click the + buttons to view associations for IQCH-AS1 from the datasets below.
If available, associations are ranked by standardized value
| Dataset | Summary | |
|---|---|---|
| Allen Brain Atlas Developing Human Brain Tissue Gene Expression Profiles by RNA-seq | tissue samples with high or low expression of IQCH-AS1 gene relative to other tissue samples from the Allen Brain Atlas Developing Human Brain Tissue Gene Expression Profiles by RNA-seq dataset. | |
| CCLE Cell Line Gene CNV Profiles | cell lines with high or low copy number of IQCH-AS1 gene relative to other cell lines from the CCLE Cell Line Gene CNV Profiles dataset. | |
| COSMIC Cell Line Gene CNV Profiles | cell lines with high or low copy number of IQCH-AS1 gene relative to other cell lines from the COSMIC Cell Line Gene CNV Profiles dataset. | |
| GEO Signatures of Differentially Expressed Genes for Diseases | disease perturbations changing expression of IQCH-AS1 gene from the GEO Signatures of Differentially Expressed Genes for Diseases dataset. | |
| GEO Signatures of Differentially Expressed Genes for Gene Perturbations | gene perturbations changing expression of IQCH-AS1 gene from the GEO Signatures of Differentially Expressed Genes for Gene Perturbations dataset. | |
| GEO Signatures of Differentially Expressed Genes for Small Molecules | small molecule perturbations changing expression of IQCH-AS1 gene from the GEO Signatures of Differentially Expressed Genes for Small Molecules dataset. | |
| GEO Signatures of Differentially Expressed Genes for Transcription Factor Perturbations | transcription factor perturbations changing expression of IQCH-AS1 gene from the GEO Signatures of Differentially Expressed Genes for Transcription Factor Perturbations dataset. | |
| GEO Signatures of Differentially Expressed Genes for Viral Infections | virus perturbations changing expression of IQCH-AS1 gene from the GEO Signatures of Differentially Expressed Genes for Viral Infections dataset. | |
| GTEx Tissue Gene Expression Profiles | tissues with high or low expression of IQCH-AS1 gene relative to other tissues from the GTEx Tissue Gene Expression Profiles dataset. | |
| GTEx Tissue Sample Gene Expression Profiles | tissue samples with high or low expression of IQCH-AS1 gene relative to other tissue samples from the GTEx Tissue Sample Gene Expression Profiles dataset. | |
| GTEx Tissue-Specific Aging Signatures | tissue samples with high or low expression of IQCH-AS1 gene relative to other tissue samples from the GTEx Tissue-Specific Aging Signatures dataset. | |
| Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles | cell lines with high or low copy number of IQCH-AS1 gene relative to other cell lines from the Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles dataset. | |
| Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene Expression Profiles | cell lines with high or low expression of IQCH-AS1 gene relative to other cell lines from the Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene Expression Profiles dataset. | |
| MotifMap Predicted Transcription Factor Targets | transcription factors regulating expression of IQCH-AS1 gene predicted using known transcription factor binding site motifs from the MotifMap Predicted Transcription Factor Targets dataset. | |