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The stable traits of melanoma genetics: an alternate approach to target discovery.

Spivey TL, De Giorgi V, Zhao Y, Bedognetti D, Pos Z, Liu Q, Tomei S, Ascierto ML, Uccellini L, Reinboth J, Chouchane L, Stroncek DF, Wang E, Marincola FM - BMC Genomics (2012)

Bottom Line: This phenotype expressed, therefore, transcripts previously associated to more aggressive cancer.The second class (B) prevalently expressed genes associated with melanoma signaling including MITF, melanoma differentiation antigens, and displayed a Th1 immune phenotype associated with better prognosis and likelihood to respond to immunotherapy.The three phenotypes were confirmed by unsupervised principal component analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Infectious Disease and Immunogenetics Section (IDIS), Department of Transfusion Medicine, Clinical Center and trans-NIH Center for Human Immunology (CHI), National Institutes of Health, Bethesda, MD 20892, USA.

ABSTRACT

Background: The weight that gene copy number plays in transcription remains controversial; although in specific cases gene expression correlates with copy number, the relationship cannot be inferred at the global level. We hypothesized that genes steadily expressed by 15 melanoma cell lines (CMs) and their parental tissues (TMs) should be critical for oncogenesis and their expression most frequently influenced by their respective copy number.

Results: Functional interpretation of 3,030 transcripts concordantly expressed (Pearson's correlation coefficient p-value < 0.05) by CMs and TMs confirmed an enrichment of functions crucial to oncogenesis. Among them, 968 were expressed according to the transcriptional efficiency predicted by copy number analysis (Pearson's correlation coefficient p-value < 0.05). We named these genes, "genomic delegates" as they represent at the transcriptional level the genetic footprint of individual cancers. We then tested whether the genes could categorize 112 melanoma metastases. Two divergent phenotypes were observed: one with prevalent expression of cancer testis antigens, enhanced cyclin activity, WNT signaling, and a Th17 immune phenotype (Class A). This phenotype expressed, therefore, transcripts previously associated to more aggressive cancer. The second class (B) prevalently expressed genes associated with melanoma signaling including MITF, melanoma differentiation antigens, and displayed a Th1 immune phenotype associated with better prognosis and likelihood to respond to immunotherapy. An intermediate third class (C) was further identified. The three phenotypes were confirmed by unsupervised principal component analysis.

Conclusions: This study suggests that clinically relevant phenotypes of melanoma can be retraced to stable oncogenic properties of cancer cells linked to their genetic back bone, and offers a roadmap for uncovering novel targets for tailored anti-cancer therapy.

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PCA analysis based on the complete transciptional data set visualizing the tridimentsional distribution of cell lines (CM, pink) compared to pair melanoma tumors (TM, yellow) (A) of the distribution of the samples according to the patient identity from which either TMs or CMs were derived (B). (C) Venn diagram displaying the results of a Pearson's correlation analysis of gene expression between TMs and CMs (p-value cutoff < 0.05). (D) Self-organizing hierarchical tree based on the top 1,006 genes whose expression was most significantly (p-value < 0.01) correlated between TMs light green) and CMs (light pink); sample ID refers to the patients from which either a TM or CM was derived. Brackets underline autologous TM/CM pairs demonstrating a comparable expression pattern. (E) Top functional network generated by Ingenuity Pathway Analysis (IPA) www.ingenuity.com based on the 3,030 target genes. (F) Bar graph demonstrating the top biological functions of the 3,030 target genes according to IPA.
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Figure 2: PCA analysis based on the complete transciptional data set visualizing the tridimentsional distribution of cell lines (CM, pink) compared to pair melanoma tumors (TM, yellow) (A) of the distribution of the samples according to the patient identity from which either TMs or CMs were derived (B). (C) Venn diagram displaying the results of a Pearson's correlation analysis of gene expression between TMs and CMs (p-value cutoff < 0.05). (D) Self-organizing hierarchical tree based on the top 1,006 genes whose expression was most significantly (p-value < 0.01) correlated between TMs light green) and CMs (light pink); sample ID refers to the patients from which either a TM or CM was derived. Brackets underline autologous TM/CM pairs demonstrating a comparable expression pattern. (E) Top functional network generated by Ingenuity Pathway Analysis (IPA) www.ingenuity.com based on the 3,030 target genes. (F) Bar graph demonstrating the top biological functions of the 3,030 target genes according to IPA.

Mentions: With the assumption that genes stably expressed by cell lines and parental tissues might be most relevant to the survival and growth of cancer cells, we applied whole genome gene expression profiling to the 15 pairs of melanoma tumors (TMs) and cell lines (CMs). PCA analysis comparing TMs to CMs demonstrated that the cell lines grown in identical culture conditions clustered homogeneously compared to the parental tumors (Figure 2A). Moreover, there was little concordance in the transcriptional patterns of autologous CMs and TMs (Figure 2B). This could be expected as the transcriptional profile of TMs included transcripts expressed by infiltrating normal cells and variations in gene expression in cancer cells reacting to micro-environmental stimuli absent in culture. To test whether the expression of genes related to melanoma biology could match TM with the respective CM, we sorted cancer testis antigens [24], melanoma differentiation antigens [25,26], melanoma-restricted genes [26] and cancer specific biomarkers expressed by cancerous tissues in vivo but not normal tissues [27] from the complete data set. This exercise demonstrated that the expression of cancer-restricted genes was consistent between 10 of 15 TM/CM pairs (Additional file 1: Figure S1). This observation encouraged further identification of transcripts stably expressed by CMs and TMs. Applying Pearson's correlation we compared the expression of individual genes between TMs and CMs. At a cutoff p-value < 0.05 or < 0.01, we identified 3,030 or 1,006 genes respectively (Figure 2C, gene list provided in Additional file 2: Table S1). Hierarchical clustering based on the 1,006 gene set demonstrated transcriptional proximity in 12 of 15 pairs (Figure 2D); moreover, duplicate cell lines derived from the same lesions clustered together (thicker gray and dark green brackets, Figure 2D). IPA suggested that the top self-organizing network related to the 3,030 gene set was centered on genetic disorders, metabolic disease and cancer. The hubs of the network were VEGF, CDKN2A and PTEN (Figure 2E). Top biological functions included genetic disorders and cancer (p < 0.009, p < 0.01 respectively, (Figure 2F). Similarly, top molecular and cellular function pathways included cell cycle, gene expression, cell death, cellular growth and proliferation and cellular assembly and organization (p < 0.01 for all pathways). These results confirmed that genes concordantly expressed by CMs and TMs are primarily related to the oncogenesis. To evaluate whether this strategy would also enrich for housekeeping genes, we identified putative endogenous reference genes according to two previous studies [28,29] and compared the ratio of their presence in the whole data set compared to the ratio of those included among the 3,030 (Additional file 3: Table S2). Of 408 putative housekeeping genes according to one reference [29] (1.4% of the complete array data set), only a 56 were included in the 3,000 genes (1.9%) and 19 in the 1,000 more stringent data set (1.9%). Thus only a modest enrichment in housekeeping genes was observed. Of 48 genes suggested by the other reference [28] (0.2% of the complete data set, only 8 and 2 were included in the 3,000 and 1,000 gene data sets (0.3 and 0.2% respectively). Thus, it is unlikely that the genes identified as stably expressed by cancer cells in this analysis represent a significant proportion of housekeeping genes.


The stable traits of melanoma genetics: an alternate approach to target discovery.

Spivey TL, De Giorgi V, Zhao Y, Bedognetti D, Pos Z, Liu Q, Tomei S, Ascierto ML, Uccellini L, Reinboth J, Chouchane L, Stroncek DF, Wang E, Marincola FM - BMC Genomics (2012)

PCA analysis based on the complete transciptional data set visualizing the tridimentsional distribution of cell lines (CM, pink) compared to pair melanoma tumors (TM, yellow) (A) of the distribution of the samples according to the patient identity from which either TMs or CMs were derived (B). (C) Venn diagram displaying the results of a Pearson's correlation analysis of gene expression between TMs and CMs (p-value cutoff < 0.05). (D) Self-organizing hierarchical tree based on the top 1,006 genes whose expression was most significantly (p-value < 0.01) correlated between TMs light green) and CMs (light pink); sample ID refers to the patients from which either a TM or CM was derived. Brackets underline autologous TM/CM pairs demonstrating a comparable expression pattern. (E) Top functional network generated by Ingenuity Pathway Analysis (IPA) www.ingenuity.com based on the 3,030 target genes. (F) Bar graph demonstrating the top biological functions of the 3,030 target genes according to IPA.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3362771&req=5

Figure 2: PCA analysis based on the complete transciptional data set visualizing the tridimentsional distribution of cell lines (CM, pink) compared to pair melanoma tumors (TM, yellow) (A) of the distribution of the samples according to the patient identity from which either TMs or CMs were derived (B). (C) Venn diagram displaying the results of a Pearson's correlation analysis of gene expression between TMs and CMs (p-value cutoff < 0.05). (D) Self-organizing hierarchical tree based on the top 1,006 genes whose expression was most significantly (p-value < 0.01) correlated between TMs light green) and CMs (light pink); sample ID refers to the patients from which either a TM or CM was derived. Brackets underline autologous TM/CM pairs demonstrating a comparable expression pattern. (E) Top functional network generated by Ingenuity Pathway Analysis (IPA) www.ingenuity.com based on the 3,030 target genes. (F) Bar graph demonstrating the top biological functions of the 3,030 target genes according to IPA.
Mentions: With the assumption that genes stably expressed by cell lines and parental tissues might be most relevant to the survival and growth of cancer cells, we applied whole genome gene expression profiling to the 15 pairs of melanoma tumors (TMs) and cell lines (CMs). PCA analysis comparing TMs to CMs demonstrated that the cell lines grown in identical culture conditions clustered homogeneously compared to the parental tumors (Figure 2A). Moreover, there was little concordance in the transcriptional patterns of autologous CMs and TMs (Figure 2B). This could be expected as the transcriptional profile of TMs included transcripts expressed by infiltrating normal cells and variations in gene expression in cancer cells reacting to micro-environmental stimuli absent in culture. To test whether the expression of genes related to melanoma biology could match TM with the respective CM, we sorted cancer testis antigens [24], melanoma differentiation antigens [25,26], melanoma-restricted genes [26] and cancer specific biomarkers expressed by cancerous tissues in vivo but not normal tissues [27] from the complete data set. This exercise demonstrated that the expression of cancer-restricted genes was consistent between 10 of 15 TM/CM pairs (Additional file 1: Figure S1). This observation encouraged further identification of transcripts stably expressed by CMs and TMs. Applying Pearson's correlation we compared the expression of individual genes between TMs and CMs. At a cutoff p-value < 0.05 or < 0.01, we identified 3,030 or 1,006 genes respectively (Figure 2C, gene list provided in Additional file 2: Table S1). Hierarchical clustering based on the 1,006 gene set demonstrated transcriptional proximity in 12 of 15 pairs (Figure 2D); moreover, duplicate cell lines derived from the same lesions clustered together (thicker gray and dark green brackets, Figure 2D). IPA suggested that the top self-organizing network related to the 3,030 gene set was centered on genetic disorders, metabolic disease and cancer. The hubs of the network were VEGF, CDKN2A and PTEN (Figure 2E). Top biological functions included genetic disorders and cancer (p < 0.009, p < 0.01 respectively, (Figure 2F). Similarly, top molecular and cellular function pathways included cell cycle, gene expression, cell death, cellular growth and proliferation and cellular assembly and organization (p < 0.01 for all pathways). These results confirmed that genes concordantly expressed by CMs and TMs are primarily related to the oncogenesis. To evaluate whether this strategy would also enrich for housekeeping genes, we identified putative endogenous reference genes according to two previous studies [28,29] and compared the ratio of their presence in the whole data set compared to the ratio of those included among the 3,030 (Additional file 3: Table S2). Of 408 putative housekeeping genes according to one reference [29] (1.4% of the complete array data set), only a 56 were included in the 3,000 genes (1.9%) and 19 in the 1,000 more stringent data set (1.9%). Thus only a modest enrichment in housekeeping genes was observed. Of 48 genes suggested by the other reference [28] (0.2% of the complete data set, only 8 and 2 were included in the 3,000 and 1,000 gene data sets (0.3 and 0.2% respectively). Thus, it is unlikely that the genes identified as stably expressed by cancer cells in this analysis represent a significant proportion of housekeeping genes.

Bottom Line: This phenotype expressed, therefore, transcripts previously associated to more aggressive cancer.The second class (B) prevalently expressed genes associated with melanoma signaling including MITF, melanoma differentiation antigens, and displayed a Th1 immune phenotype associated with better prognosis and likelihood to respond to immunotherapy.The three phenotypes were confirmed by unsupervised principal component analysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Infectious Disease and Immunogenetics Section (IDIS), Department of Transfusion Medicine, Clinical Center and trans-NIH Center for Human Immunology (CHI), National Institutes of Health, Bethesda, MD 20892, USA.

ABSTRACT

Background: The weight that gene copy number plays in transcription remains controversial; although in specific cases gene expression correlates with copy number, the relationship cannot be inferred at the global level. We hypothesized that genes steadily expressed by 15 melanoma cell lines (CMs) and their parental tissues (TMs) should be critical for oncogenesis and their expression most frequently influenced by their respective copy number.

Results: Functional interpretation of 3,030 transcripts concordantly expressed (Pearson's correlation coefficient p-value < 0.05) by CMs and TMs confirmed an enrichment of functions crucial to oncogenesis. Among them, 968 were expressed according to the transcriptional efficiency predicted by copy number analysis (Pearson's correlation coefficient p-value < 0.05). We named these genes, "genomic delegates" as they represent at the transcriptional level the genetic footprint of individual cancers. We then tested whether the genes could categorize 112 melanoma metastases. Two divergent phenotypes were observed: one with prevalent expression of cancer testis antigens, enhanced cyclin activity, WNT signaling, and a Th17 immune phenotype (Class A). This phenotype expressed, therefore, transcripts previously associated to more aggressive cancer. The second class (B) prevalently expressed genes associated with melanoma signaling including MITF, melanoma differentiation antigens, and displayed a Th1 immune phenotype associated with better prognosis and likelihood to respond to immunotherapy. An intermediate third class (C) was further identified. The three phenotypes were confirmed by unsupervised principal component analysis.

Conclusions: This study suggests that clinically relevant phenotypes of melanoma can be retraced to stable oncogenic properties of cancer cells linked to their genetic back bone, and offers a roadmap for uncovering novel targets for tailored anti-cancer therapy.

Show MeSH
Related in: MedlinePlus