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Identification of 2R-ohnologue gene families displaying the same mutation-load skew in multiple cancers.

Tinti M, Dissanayake K, Synowsky S, Albergante L, MacKintosh C - Open Biol (2014)

Bottom Line: The complexity of signalling pathways was boosted at the origin of the vertebrates, when two rounds of whole genome duplication (2R-WGD) occurred.The non-mutated 2R-ohnologues are therefore potential therapeutic targets.These include proteins linked to growth factor signalling, neurotransmission and ion channels.

View Article: PubMed Central - PubMed

Affiliation: Division of Cell and Developmental Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK.

ABSTRACT
The complexity of signalling pathways was boosted at the origin of the vertebrates, when two rounds of whole genome duplication (2R-WGD) occurred. Those genes and proteins that have survived from the 2R-WGD-termed 2R-ohnologues-belong to families of two to four members, and are enriched in signalling components relevant to cancer. Here, we find that while only approximately 30% of human transcript-coding genes are 2R-ohnologues, they carry 42-60% of the gene mutations in 30 different cancer types. Across a subset of cancer datasets, including melanoma, breast, lung adenocarcinoma, liver and medulloblastoma, we identified 673 2R-ohnologue families in which one gene carries mutations at multiple positions, while sister genes in the same family are relatively mutation free. Strikingly, in 315 of the 322 2R-ohnologue families displaying such a skew in multiple cancers, the same gene carries the heaviest mutation load in each cancer, and usually the second-ranked gene is also the same in each cancer. Our findings inspire the hypothesis that in certain cancers, heterogeneous combinations of genetic changes impair parts of the 2R-WGD signalling networks and force information flow through a limited set of oncogenic pathways in which specific non-mutated 2R-ohnologues serve as effectors. The non-mutated 2R-ohnologues are therefore potential therapeutic targets. These include proteins linked to growth factor signalling, neurotransmission and ion channels.

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Relationships among ML of 2R-ohnologues in melanoma, cancer/control mRNA expression in melanoma and proteins identified in 14-3-3-affinity capture experiments using melanoma cell lysates. Each cross represents a gene in the E-GEOD-3189 transcription profiling dataset [34]. The log2 ratio of mRNA expression in malignant melanoma versus benign melanocytic lesions in the E-GEOD-3189 dataset is plotted on the y-axis against the ML score of the gene calculated from the Alexandrov et al. [15] data on the x-axis. The genes whose mRNA levels are most strongly up- or downregulated in melanoma are in red and blue, respectively. Also plotted (circles) are the proteins that were isolated by 14-3-3-affinity capture of cell lysates from both SKMEL13 and SBCL2 melanoma cells, and identified by mass spectrometric analyses. The data used for this figure are in the electronic supplementary material, table S6.
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RSOB140029F5: Relationships among ML of 2R-ohnologues in melanoma, cancer/control mRNA expression in melanoma and proteins identified in 14-3-3-affinity capture experiments using melanoma cell lysates. Each cross represents a gene in the E-GEOD-3189 transcription profiling dataset [34]. The log2 ratio of mRNA expression in malignant melanoma versus benign melanocytic lesions in the E-GEOD-3189 dataset is plotted on the y-axis against the ML score of the gene calculated from the Alexandrov et al. [15] data on the x-axis. The genes whose mRNA levels are most strongly up- or downregulated in melanoma are in red and blue, respectively. Also plotted (circles) are the proteins that were isolated by 14-3-3-affinity capture of cell lysates from both SKMEL13 and SBCL2 melanoma cells, and identified by mass spectrometric analyses. The data used for this figure are in the electronic supplementary material, table S6.

Mentions: An important question is whether the 2R-ohnologues that are relatively free of mutations are expressed in the cancers. While we cannot answer this question for the Alexandrov et al. [15] dataset, other available data record differences in mRNA levels between samples of malignant cancers compared with benign or normal controls. We found a moderate, but statistically significant tendency for 2R-ohnologues with low ML scores (mutation-free relative to sister 2R-ohnologues) to have their mRNA levels strongly upregulated in melanoma in the E-GEOD-3189 dataset [34] (figure 5; electronic supplementary material, figure S4 and table S6). A similar trend was observed in the E-GEOD-32867 dataset, which reports gene expression levels in lung adenocarcinoma relative to adjacent non-tumour tissue (electronic supplementary material, figure S5 and table S7). These results indicate the existence of selection pressures that affect the expression levels of certain 2R-ohnologues in cancer cells. The 2R-ohnologues whose expression is altered in the cancer have a greater tendency to be maintained with a low ML.FigureĀ 5.


Identification of 2R-ohnologue gene families displaying the same mutation-load skew in multiple cancers.

Tinti M, Dissanayake K, Synowsky S, Albergante L, MacKintosh C - Open Biol (2014)

Relationships among ML of 2R-ohnologues in melanoma, cancer/control mRNA expression in melanoma and proteins identified in 14-3-3-affinity capture experiments using melanoma cell lysates. Each cross represents a gene in the E-GEOD-3189 transcription profiling dataset [34]. The log2 ratio of mRNA expression in malignant melanoma versus benign melanocytic lesions in the E-GEOD-3189 dataset is plotted on the y-axis against the ML score of the gene calculated from the Alexandrov et al. [15] data on the x-axis. The genes whose mRNA levels are most strongly up- or downregulated in melanoma are in red and blue, respectively. Also plotted (circles) are the proteins that were isolated by 14-3-3-affinity capture of cell lysates from both SKMEL13 and SBCL2 melanoma cells, and identified by mass spectrometric analyses. The data used for this figure are in the electronic supplementary material, table S6.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4042849&req=5

RSOB140029F5: Relationships among ML of 2R-ohnologues in melanoma, cancer/control mRNA expression in melanoma and proteins identified in 14-3-3-affinity capture experiments using melanoma cell lysates. Each cross represents a gene in the E-GEOD-3189 transcription profiling dataset [34]. The log2 ratio of mRNA expression in malignant melanoma versus benign melanocytic lesions in the E-GEOD-3189 dataset is plotted on the y-axis against the ML score of the gene calculated from the Alexandrov et al. [15] data on the x-axis. The genes whose mRNA levels are most strongly up- or downregulated in melanoma are in red and blue, respectively. Also plotted (circles) are the proteins that were isolated by 14-3-3-affinity capture of cell lysates from both SKMEL13 and SBCL2 melanoma cells, and identified by mass spectrometric analyses. The data used for this figure are in the electronic supplementary material, table S6.
Mentions: An important question is whether the 2R-ohnologues that are relatively free of mutations are expressed in the cancers. While we cannot answer this question for the Alexandrov et al. [15] dataset, other available data record differences in mRNA levels between samples of malignant cancers compared with benign or normal controls. We found a moderate, but statistically significant tendency for 2R-ohnologues with low ML scores (mutation-free relative to sister 2R-ohnologues) to have their mRNA levels strongly upregulated in melanoma in the E-GEOD-3189 dataset [34] (figure 5; electronic supplementary material, figure S4 and table S6). A similar trend was observed in the E-GEOD-32867 dataset, which reports gene expression levels in lung adenocarcinoma relative to adjacent non-tumour tissue (electronic supplementary material, figure S5 and table S7). These results indicate the existence of selection pressures that affect the expression levels of certain 2R-ohnologues in cancer cells. The 2R-ohnologues whose expression is altered in the cancer have a greater tendency to be maintained with a low ML.FigureĀ 5.

Bottom Line: The complexity of signalling pathways was boosted at the origin of the vertebrates, when two rounds of whole genome duplication (2R-WGD) occurred.The non-mutated 2R-ohnologues are therefore potential therapeutic targets.These include proteins linked to growth factor signalling, neurotransmission and ion channels.

View Article: PubMed Central - PubMed

Affiliation: Division of Cell and Developmental Biology, College of Life Sciences, University of Dundee, Dundee DD1 5EH, UK.

ABSTRACT
The complexity of signalling pathways was boosted at the origin of the vertebrates, when two rounds of whole genome duplication (2R-WGD) occurred. Those genes and proteins that have survived from the 2R-WGD-termed 2R-ohnologues-belong to families of two to four members, and are enriched in signalling components relevant to cancer. Here, we find that while only approximately 30% of human transcript-coding genes are 2R-ohnologues, they carry 42-60% of the gene mutations in 30 different cancer types. Across a subset of cancer datasets, including melanoma, breast, lung adenocarcinoma, liver and medulloblastoma, we identified 673 2R-ohnologue families in which one gene carries mutations at multiple positions, while sister genes in the same family are relatively mutation free. Strikingly, in 315 of the 322 2R-ohnologue families displaying such a skew in multiple cancers, the same gene carries the heaviest mutation load in each cancer, and usually the second-ranked gene is also the same in each cancer. Our findings inspire the hypothesis that in certain cancers, heterogeneous combinations of genetic changes impair parts of the 2R-WGD signalling networks and force information flow through a limited set of oncogenic pathways in which specific non-mutated 2R-ohnologues serve as effectors. The non-mutated 2R-ohnologues are therefore potential therapeutic targets. These include proteins linked to growth factor signalling, neurotransmission and ion channels.

Show MeSH
Related in: MedlinePlus