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A Subset of Nuclear Receptors are Uniquely Expressed in Uveal Melanoma Cells.

Huffman KE, Carstens R, Martinez ED - Front Endocrinol (Lausanne) (2015)

Bottom Line: First, in agreement with our past studies identifying RXRg as a CM-specific marker, we found that UM cells also exhibit high levels of RXRg expression, making it a universal biomarker for melanoma tumors.Third, we found that RARg, PPARd, EAR2, RXRa, and TRa expressions could subdivide UM from CM.We found unique NR expression profiles associated with each of these UM mutations.

View Article: PubMed Central - PubMed

Affiliation: Hamon Center for Therapeutic Oncology Research , Dallas, TX , USA.

ABSTRACT
Uveal melanoma (UM) is recognized as the most common intraocular malignancy and the second most common form of melanoma. Nearly 50% of UM patients develop untreatable and fatal metastases. The 48-member nuclear receptor (NR) superfamily represents a therapeutically targetable group of transcription factors known for their regulation of key cancer pathways in numerous tumor types. Here, we profiled the expression of the 48 human NRs by qRT-PCR across a melanoma cell line panel including 5 UM lines, 9 cutaneous melanoma (CM) lines, and normal primary melanocytes. NR expression patterns identified a few key features. First, in agreement with our past studies identifying RXRg as a CM-specific marker, we found that UM cells also exhibit high levels of RXRg expression, making it a universal biomarker for melanoma tumors. Second, we found that LXRb is highly expressed in both UM and CM lines, suggesting that it may be a therapeutic target in a UM metastatic setting as it has been in CM models. Third, we found that RARg, PPARd, EAR2, RXRa, and TRa expressions could subdivide UM from CM. Previous studies of UM cancers identified key mutations in three genes: GNAQ, GNA11, and BRAF. We found unique NR expression profiles associated with each of these UM mutations. We then performed NR-to-NR and NR-to-genome expression correlation analyses to find potential NR-driven transcriptional programs activated in UM and CM. Specifically, RXRg controlled gene networks were identified that may drive melanoma-specific signaling and metabolism. ERRa was identified as a UM-defining NR and genes correlated with its expression confirm the role of ERRa in metabolic control. Given the plethora of available NR agonists, antagonists, and selective receptor modulators, pharmacologic manipulation of these NRs and their transcriptional outputs may lead to a more comprehensive understanding of key UM pathways and how we can leverage them for better therapeutic alternatives.

No MeSH data available.


Related in: MedlinePlus

NR-to-NR pairwise correlation comparisons. Pairwise Pearson correlation coefficient (PCC) analysis of the nuclear receptors. Hierarchical clustering analysis was performed as in Figure 1. Positive correlations are depicted in orange with the strongest intensities corresponding to higher correlations (0.95 was the highest pairwise correlation). Similarly, negative correlations are depicted in blue tending toward white as they become less intense. The range of positive correlations (0–0.95) was greater than the range of negative correlations (0 to −0.64).
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Figure 3: NR-to-NR pairwise correlation comparisons. Pairwise Pearson correlation coefficient (PCC) analysis of the nuclear receptors. Hierarchical clustering analysis was performed as in Figure 1. Positive correlations are depicted in orange with the strongest intensities corresponding to higher correlations (0.95 was the highest pairwise correlation). Similarly, negative correlations are depicted in blue tending toward white as they become less intense. The range of positive correlations (0–0.95) was greater than the range of negative correlations (0 to −0.64).

Mentions: To better understand the relationships between the NRs themselves within the melanoma panel, we calculated correlation coefficients (performed as before) for all possible pairwise combinations of the 48 NRs. The results of this unsupervised clustering analysis are shown as a heat map in Figure 3. Several clusters of strongly positive correlations could be seen, including a cluster containing receptors identified as differentially regulated between CM and UM. The CM-specific cluster included EAR2, REV-ERb, RARg, NOR1, and GCNF while the UM-specific cluster contained LXRb, ERRb, TR2, and ERRa. These pockets of strong correlation suggest transcriptional and/or functional interconnections within these receptor subgroups and within specific melanoma subtypes.


A Subset of Nuclear Receptors are Uniquely Expressed in Uveal Melanoma Cells.

Huffman KE, Carstens R, Martinez ED - Front Endocrinol (Lausanne) (2015)

NR-to-NR pairwise correlation comparisons. Pairwise Pearson correlation coefficient (PCC) analysis of the nuclear receptors. Hierarchical clustering analysis was performed as in Figure 1. Positive correlations are depicted in orange with the strongest intensities corresponding to higher correlations (0.95 was the highest pairwise correlation). Similarly, negative correlations are depicted in blue tending toward white as they become less intense. The range of positive correlations (0–0.95) was greater than the range of negative correlations (0 to −0.64).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493406&req=5

Figure 3: NR-to-NR pairwise correlation comparisons. Pairwise Pearson correlation coefficient (PCC) analysis of the nuclear receptors. Hierarchical clustering analysis was performed as in Figure 1. Positive correlations are depicted in orange with the strongest intensities corresponding to higher correlations (0.95 was the highest pairwise correlation). Similarly, negative correlations are depicted in blue tending toward white as they become less intense. The range of positive correlations (0–0.95) was greater than the range of negative correlations (0 to −0.64).
Mentions: To better understand the relationships between the NRs themselves within the melanoma panel, we calculated correlation coefficients (performed as before) for all possible pairwise combinations of the 48 NRs. The results of this unsupervised clustering analysis are shown as a heat map in Figure 3. Several clusters of strongly positive correlations could be seen, including a cluster containing receptors identified as differentially regulated between CM and UM. The CM-specific cluster included EAR2, REV-ERb, RARg, NOR1, and GCNF while the UM-specific cluster contained LXRb, ERRb, TR2, and ERRa. These pockets of strong correlation suggest transcriptional and/or functional interconnections within these receptor subgroups and within specific melanoma subtypes.

Bottom Line: First, in agreement with our past studies identifying RXRg as a CM-specific marker, we found that UM cells also exhibit high levels of RXRg expression, making it a universal biomarker for melanoma tumors.Third, we found that RARg, PPARd, EAR2, RXRa, and TRa expressions could subdivide UM from CM.We found unique NR expression profiles associated with each of these UM mutations.

View Article: PubMed Central - PubMed

Affiliation: Hamon Center for Therapeutic Oncology Research , Dallas, TX , USA.

ABSTRACT
Uveal melanoma (UM) is recognized as the most common intraocular malignancy and the second most common form of melanoma. Nearly 50% of UM patients develop untreatable and fatal metastases. The 48-member nuclear receptor (NR) superfamily represents a therapeutically targetable group of transcription factors known for their regulation of key cancer pathways in numerous tumor types. Here, we profiled the expression of the 48 human NRs by qRT-PCR across a melanoma cell line panel including 5 UM lines, 9 cutaneous melanoma (CM) lines, and normal primary melanocytes. NR expression patterns identified a few key features. First, in agreement with our past studies identifying RXRg as a CM-specific marker, we found that UM cells also exhibit high levels of RXRg expression, making it a universal biomarker for melanoma tumors. Second, we found that LXRb is highly expressed in both UM and CM lines, suggesting that it may be a therapeutic target in a UM metastatic setting as it has been in CM models. Third, we found that RARg, PPARd, EAR2, RXRa, and TRa expressions could subdivide UM from CM. Previous studies of UM cancers identified key mutations in three genes: GNAQ, GNA11, and BRAF. We found unique NR expression profiles associated with each of these UM mutations. We then performed NR-to-NR and NR-to-genome expression correlation analyses to find potential NR-driven transcriptional programs activated in UM and CM. Specifically, RXRg controlled gene networks were identified that may drive melanoma-specific signaling and metabolism. ERRa was identified as a UM-defining NR and genes correlated with its expression confirm the role of ERRa in metabolic control. Given the plethora of available NR agonists, antagonists, and selective receptor modulators, pharmacologic manipulation of these NRs and their transcriptional outputs may lead to a more comprehensive understanding of key UM pathways and how we can leverage them for better therapeutic alternatives.

No MeSH data available.


Related in: MedlinePlus