Gene Summary

Gene:RXRG; retinoid X receptor, gamma
Aliases: RXRC, NR2B3
Summary:This gene encodes a member of the retinoid X receptor (RXR) family of nuclear receptors which are involved in mediating the antiproliferative effects of retinoic acid (RA). This receptor forms dimers with the retinoic acid, thyroid hormone, and vitamin D receptors, increasing both DNA binding and transcriptional function on their respective response elements. This gene is expressed at significantly lower levels in non-small cell lung cancer cells. Alternatively spliced transcript variants have been described. [provided by RefSeq, Jun 2010]
Databases:OMIM, VEGA, HGNC, Ensembl, GeneCard, Gene
Protein:retinoic acid receptor RXR-gamma
Source:NCBIAccessed: 06 August, 2015


What does this gene/protein do?
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Pathways:What pathways are this gene/protein implicaed in?
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Cancer Overview

Research Indicators

Publications Per Year (1990-2015)
Graph generated 06 August 2015 using data from PubMed using criteria.

Literature Analysis

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Tag cloud generated 06 August, 2015 using data from PubMed, MeSH and CancerIndex

Specific Cancers (4)

Data table showing topics related to specific cancers and associated disorders. Scope includes mutations and abnormal protein expression.

Note: list is not exhaustive. Number of papers are based on searches of PubMed (click on topic title for arbitrary criteria used).

Latest Publications: RXRG (cancer-related)

Lee SM, Lee JY, Choi JE, et al.
Epigenetic inactivation of retinoid X receptor genes in non-small cell lung cancer and the relationship with clinicopathologic features.
Cancer Genet Cytogenet. 2010; 197(1):39-45 [PubMed] Related Publications
Retinoid X receptors (RXRs) are nuclear receptors for retinoids that play a critical role in the regulation of growth and differentiation in normal and tumor cells. Deregulation of RXR expression has been reported in non-small cell lung cancer (NSCLC); however, the mechanism underlying the impaired expression of RXRs in lung cancer is not known. Aberrant methylation of promoter CpG islands is known to be a major mechanism for inactivation of tumor suppressor genes. We investigated the methylation status of the RXR genes in 139 surgically resected NSCLCs and correlated the results with the clinicopathologic characteristics of the patients. Methylation in the tumors was detected in all three genes: RXRA, 5.7%; RXRB, 4.3%; RXRG, 23.7%. Reverse transcriptase-polymerase chain reaction analysis showed that RXRG methylation correlates with mRNA expression. Methylation of the RXRG gene was not significantly associated with the prognosis of patients. When the patients were categorized by smoking status, however, the effect of RXRG methylation on prognosis was significantly different between never- and ever-smokers (P=0.003, test for homogeneity). Specifically, RXRG methylation was associated with a significantly worse survival in never-smokers; a trend to better survival outcome was observed for ever-smokers, although not statistically significant. This finding suggests that methylation-associated downregulation of the RXRG gene may play a differential role in the carcinogenesis of NSCLCs according to smoking status, but further studies are needed to confirm this.

Jarzab B, Wiench M, Fujarewicz K, et al.
Gene expression profile of papillary thyroid cancer: sources of variability and diagnostic implications.
Cancer Res. 2005; 65(4):1587-97 [PubMed] Related Publications
The study looked for an optimal set of genes differentiating between papillary thyroid cancer (PTC) and normal thyroid tissue and assessed the sources of variability in gene expression profiles. The analysis was done by oligonucleotide microarrays (GeneChip HG-U133A) in 50 tissue samples taken intraoperatively from 33 patients (23 PTC patients and 10 patients with other thyroid disease). In the initial group of 16 PTC and 16 normal samples, we assessed the sources of variability in the gene expression profile by singular value decomposition which specified three major patterns of variability. The first and the most distinct mode grouped transcripts differentiating between tumor and normal tissues. Two consecutive modes contained a large proportion of immunity-related genes. To generate a multigene classifier for tumor-normal difference, we used support vector machines-based technique (recursive feature replacement). It included the following 19 genes: DPP4, GJB3, ST14, SERPINA1, LRP4, MET, EVA1, SPUVE, LGALS3, HBB, MKRN2, MRC2, IGSF1, KIAA0830, RXRG, P4HA2, CDH3, IL13RA1, and MTMR4, and correctly discriminated 17 of 18 additional PTC/normal thyroid samples and all 16 samples published in a previous microarray study. Selected novel genes (LRP4, EVA1, TMPRSS4, QPCT, and SLC34A2) were confirmed by Q-PCR. Our results prove that the gene expression signal of PTC is easily detectable even when cancer cells do not prevail over tumor stroma. We indicate and separate the confounding variability related to the immune response. Finally, we propose a potent molecular classifier able to discriminate between PTC and nonmalignant thyroid in more than 90% of investigated samples.

Hansel DE, Rahman A, House M, et al.
Met proto-oncogene and insulin-like growth factor binding protein 3 overexpression correlates with metastatic ability in well-differentiated pancreatic endocrine neoplasms.
Clin Cancer Res. 2004; 10(18 Pt 1):6152-8 [PubMed] Related Publications
Pancreatic endocrine neoplasms are neoplastic proliferations of islet cells or islet cell precursors and are capable of secreting a variety of synthetic products, including insulin, glucagon, gastrin, and vasoactive intestinal peptide. The biological behavior of pancreatic endocrine neoplasms is often unpredictable, and there are few reliable histopathologic criteria reliably correlating with metastatic ability. We have used the Affymetrix U133 GeneChip set (HG_U133 A and B; Affymetrix; Santa Clara, CA) representing approximately 33,000 characterized transcripts to examine global gene expression profiles from well-differentiated nonmetastatic (n=5) and metastatic (n=7) pancreatic endocrine neoplasms to determine molecular markers that predict disease progression. Microarray hybridization data were normalized using the GeneLogic GeneExpress Software System to identify differentially up- and down-regulated genes in metastatic versus nonmetastatic pancreatic endocrine neoplasms. Using a 3-fold change in gene expression as a threshold, we have identified 65 overexpressed and 57 underexpressed genes in metastatic pancreatic endocrine neoplasms as compared with nonmetastatic pancreatic endocrine neoplasms. Several classes of genes, including growth factors and growth factor-related molecules (IGFBP1, IGFBP3, and MET), developmental factors (TBX3 and MEIS2), cytoskeletal factors (beta 1 tubulin and ACTN2), cholesterol homeostasis mediators (LRP5, SLC27A2, and RXRG), intracellular signaling pathway mediators (DYRK1A, PKIB, and AK2), methyltransferases (MGMT and GAMT), and DNA repair and regulatory molecules (CHEK1 and ZNF198), were identified as differentially over- or underexpressed via this method. Immunohistochemical validation of microarray data were performed for two overexpressed genes, namely, the met proto-oncogene (MET) and insulin-like growth factor binding protein 3 (IGFBP3) with tissue microarrays of nonmetastatic (n=24) and metastatic (n=15) pancreatic endocrine neoplasms. Increased expression of IGFBP3 was confirmed in metastatic versus nonmetastatic pancreatic endocrine neoplasms (12 of 15, 80% versus 10 of 24, 42%), as well as in lymph node (6 of 7, 86%) and liver (9 of 9, 100%) metastases. Similarly, overexpression of MET was confirmed in metastatic versus nonmetastatic pancreatic endocrine neoplasms (5 of 15, 33% versus 4 of 24, 17%), as well as in lymph node metastases (4 of 7, 57%) and liver metastases (5 of 9, 56%). The majority of genes that demonstrated altered expression has not been previously identified as differentially expressed in metastatic pancreatic endocrine neoplasm lesions and may therefore represent newly identified molecules in the progression of these lesions.

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Cite this page: Cotterill SJ. RXRG, Cancer Genetics Web: http://www.cancer-genetics.org/RXRG.htm Accessed:

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This page in Cancer Genetics Web by Simon Cotterill is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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