LINC00606 Gene

Name long intergenic non-protein coding RNA 606
Summary
{"type": "root", "children": [{"type": "p", "children": [{"type": "t", "text": "\n In a study focused on the prognostic potential of long noncoding RNAs (LncRNAs) and pseudogenes in renal cell carcinoma (RCC) (1), several LncRNAs—such as LINC00520, PIK3CD‐AS1, LINC01559, CEACAM22P, MSL3P1, and TREML3P—were identified as promising non‐invasive serum biomarkers and were correlated with tumor stage, metastasis, overall survival, and recurrence. Notably, this study did not report on or characterize the function of LINC00606 in RCC. Therefore, within the context of this work, no direct evidence was provided regarding the role or activity of LINC00606, highlighting a gap that could be addressed by future research."}]}, {"type": "t", "text": "\n "}, {"type": "p", "children": [{"type": "fg", "children": [{"type": "fg_f", "ref": "1"}]}, {"type": "t", "text": ""}]}, {"type": "rg", "children": [{"type": "r", "ref": 1, "children": [{"type": "t", "text": "Binghai Chen, Chengyue Wang, Jin Zhang, et al. "}, {"type": "b", "children": [{"type": "t", "text": "New insights into long noncoding RNAs and pseudogenes in prognosis of renal cell carcinoma."}]}, {"type": "t", "text": " "}, {"type": "i", "children": [{"type": "t", "text": "Cancer Cell Int (2018)"}]}, {"type": "t", "text": " DOI: "}, {"type": "a", "children": [{"type": "t", "text": "10.1186/s12935-018-0652-6"}], "href": "https://doi.org/10.1186/s12935-018-0652-6"}, {"type": "t", "text": " PMID: "}, {"type": "a", "children": [{"type": "t", "text": "30337839"}], "href": "https://pubmed.ncbi.nlm.nih.gov/30337839"}]}]}]}
NCBI Gene ID 285370
API
Download Associations
Predicted Functions View LINC00606's ARCHS4 Predicted Functions.
Co-expressed Genes View LINC00606's ARCHS4 Predicted Functions.
Expression in Tissues and Cell Lines View LINC00606's ARCHS4 Predicted Functions.

Functional Associations

LINC00606 has 162 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 9 datasets.

Click the + buttons to view associations for LINC00606 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 LINC00606 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 LINC00606 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 LINC00606 gene from the GEO Signatures of Differentially Expressed Genes for Diseases dataset.
GEO Signatures of Differentially Expressed Genes for Kinase Perturbations kinase perturbations changing expression of LINC00606 gene from the GEO Signatures of Differentially Expressed Genes for Kinase Perturbations dataset.
GEO Signatures of Differentially Expressed Genes for Small Molecules small molecule perturbations changing expression of LINC00606 gene from the GEO Signatures of Differentially Expressed Genes for Small Molecules dataset.
GEO Signatures of Differentially Expressed Genes for Viral Infections virus perturbations changing expression of LINC00606 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 LINC00606 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 LINC00606 gene relative to other cell lines from the Klijn et al., Nat. Biotechnol., 2015 Cell Line Gene CNV Profiles dataset.
MotifMap Predicted Transcription Factor Targets transcription factors regulating expression of LINC00606 gene predicted using known transcription factor binding site motifs from the MotifMap Predicted Transcription Factor Targets dataset.