These included a heavily melanized uveal melanoma (UM) that had currently invaded the skull on the central nervous program, a nodular, apparently exclusively exophytically developing xanthoerythrophoroma (XE) and an extracutaneous melanoma (MM), that was a large aircraft dark tumor mass in the abdominal with massive invasion in to the body musculature and metastasis to inner organs including the spinal cord. within the genes. Low read counts are colored in green, high read counts are colored in red. 3a: Genes down-regulated in zebrafish, 3b: Genes up-regulated in zebrafish.(TIF) pone.0037880.s003.tif (1.1M) GUID:?22C56A34-C2DD-422C-8F41-63DE0275CBB3 Figure S4: Affected pathways based on genes commonly upregulated or downregulated more than 2-fold in human cutaneous primary melanoma compared to melanocytic skin nevi and fish tumors (XE, UM and MM) compared to fish nevi (HP). Red bars show the number of observed genes up-regulated or down-regulated in the dataset, blue bars show the statistically expected number of genes, given the result to be random.(PDF) pone.0037880.s004.pdf (5.7K) GUID:?0F9D1785-950B-491E-8C54-F03FCDAC7529 Figure S5: Gene Ontology analysis of functional gene groups commonly regulated in medaka tumors versus HP. The analysis was performed using the Gene Set Analysis Toolkit V2 (http://bioinfo.vanderbilt.edu/webgestalt/).(GIF) pone.0037880.s005.gif (83K) GUID:?C0B2CE1D-5343-49CA-A89A-84E87BFAE1D5 Table S1: Primers used for quantitative real-time PCR analysis. (DOC) pone.0037880.s006.doc (45K) GUID:?BDD6AE74-5B92-432B-8492-D32A834C5658 Table S2: List of genes with a more than 4-fold regulation in all tumors compared to the benign precursor lesion. (XLS) pone.0037880.s007.xls (657K) GUID:?60DF6FFF-0BFB-4780-BDCA-8488167AF87D Table S3: List of differentially spliced and differentially expressed genes. (XLS) NITD008 pone.0037880.s008.xls (170K) GUID:?A4C1AA02-2FD1-4F57-8664-AB2C61ED3CB4 Table S4: Number of genes with RPKM 2 showing an at least 2-fold up or down regulation in different tumor types compared to hyperpigmented skin. (DOC) pone.0037880.s009.doc (28K) GUID:?23EBA764-D823-4E67-BF8A-AB8642A9E6E8 Table S5: Genes common in medaka tumor transcriptomes and the Hoek human melanoma gene expression signature. Columns 5 to 8 indicate in which datasets a gene is commonly regulated (1) or not (0).(XLS) pone.0037880.s010.xls (45K) GUID:?52AE060C-589F-4917-A5F8-05F57ADA8E3D TRIB3 Abstract Aberrations in gene expression are a hallmark of cancer cells. Differential tumor-specific transcript levels of single genes or whole sets of genes may be critical for the neoplastic phenotype and important for therapeutic considerations or useful as biomarkers. As an approach to filter out such relevant expression differences from the plethora of changes noted in global expression profiling studies, we searched for changes of gene expression levels that are conserved. Transcriptomes from massive parallel sequencing of different types of melanoma from medaka were generated and compared to microarray datasets from zebrafish and human melanoma. This revealed molecular conservation at various levels between fish models and human tumors providing a useful strategy for identifying expression signatures strongly associated with disease phenotypes and uncovering new melanoma molecules. Introduction Melanoma is one of the most aggressive forms of cancer with still rapidly increasing incidence in the western world [1] (http://seer.cancer.gov/csr/1975_2008/browse_csr.php?section=16&page=sect_16_table.05.html). Treatment opportunities arise from a large portfolio of candidate drugs some of which have made it to clinical studies; however, with differing and often unpredictable outcomes. Thus the need for a better molecular understanding of melanomagenesis and preclinical studies in-vitro and in animal models is undisputed [2]. Melanoma is a paradigm for the complexity of cancer. Melanomas arise from pigment cells of the skin, from extracutaneous sites and from the uvea of the eye. A certain fraction of cutaneous melanomas form on the basis of nevi, which then represent a precursor lesion. Others are supposed to originate from single pigment cells of the skin. The clinical heterogeneity of the disease is astonishingly high, ranging from spontaneous total remission to extremely fast, fatal progression. Although gene expression signatures of melanomas have been reported [3], [4], [5], [6], [7], only few clues were obtained for molecular subtypes that could be of clinical relevance. Obvious differences were more correlated to anatomical sites, treatment history of patients, and progression stage. A further complication widely discussed to camouflage a clear diagnostic gene expression signature, are individual genetic differences and recurrent changes that reflect epiphenomena of the transformed phenotype and the pathological physiology of the melanoma cells. In general, and especially in the melanoma field, high throughput transcriptome studies have so far not revealed the expected consensus alterations that would help to ultimately understand melanoma biology and pathology (for discussion see [8]. To pinpoint relevant expression patterns common to all tumor subtypes important information can be obtained from a cross-species comparative approach with melanoma animal models. Changes in gene expression that are conserved over large evolutionary distances have a high probability of reflecting common molecular mechanisms critical for the development of the same disease in different organisms [9], [10],.In general, and especially in the melanoma field, high throughput transcriptome studies have so far not revealed the expected consensus alterations that would help to ultimately understand melanoma biology and pathology (for discussion see [8]. based on genes commonly upregulated or downregulated more than 2-fold in human cutaneous primary melanoma compared to melanocytic skin nevi and fish tumors (XE, UM and MM) compared to fish nevi (HP). Red bars show the number of observed genes up-regulated or down-regulated in the dataset, blue bars show the statistically expected number of genes, given the result to be random.(PDF) pone.0037880.s004.pdf (5.7K) GUID:?0F9D1785-950B-491E-8C54-F03FCDAC7529 Figure S5: Gene Ontology analysis of functional gene groups commonly regulated in medaka tumors versus HP. The analysis was performed using the Gene Set Analysis Toolkit V2 (http://bioinfo.vanderbilt.edu/webgestalt/).(GIF) pone.0037880.s005.gif (83K) GUID:?C0B2CE1D-5343-49CA-A89A-84E87BFAE1D5 Table S1: Primers used for quantitative real-time NITD008 PCR analysis. (DOC) pone.0037880.s006.doc (45K) GUID:?BDD6AE74-5B92-432B-8492-D32A834C5658 Table S2: List of genes with a more than 4-fold regulation in all tumors compared to the benign precursor lesion. (XLS) pone.0037880.s007.xls (657K) GUID:?60DF6FFF-0BFB-4780-BDCA-8488167AF87D Table S3: List of differentially spliced and differentially expressed genes. NITD008 (XLS) pone.0037880.s008.xls (170K) GUID:?A4C1AA02-2FD1-4F57-8664-AB2C61ED3CB4 Table S4: Number of genes with RPKM 2 showing an at least 2-fold up or down regulation in different tumor types compared to hyperpigmented skin. (DOC) pone.0037880.s009.doc (28K) GUID:?23EBA764-D823-4E67-BF8A-AB8642A9E6E8 Table S5: Genes common in medaka tumor transcriptomes and the Hoek human melanoma gene expression signature. Columns 5 to 8 indicate in which datasets a gene is commonly regulated (1) or not (0).(XLS) pone.0037880.s010.xls (45K) GUID:?52AE060C-589F-4917-A5F8-05F57ADA8E3D Abstract Aberrations in gene expression are a hallmark of cancer cells. Differential tumor-specific transcript levels of single genes or whole sets of genes may be critical for the neoplastic phenotype NITD008 and important NITD008 for therapeutic considerations or useful as biomarkers. As an approach to filter out such relevant expression differences from the plethora of changes noted in global expression profiling studies, we searched for changes of gene expression levels that are conserved. Transcriptomes from massive parallel sequencing of different types of melanoma from medaka were generated and compared to microarray datasets from zebrafish and human melanoma. This revealed molecular conservation at various levels between fish models and human tumors providing a useful strategy for identifying expression signatures strongly associated with disease phenotypes and uncovering new melanoma molecules. Introduction Melanoma is one of the most aggressive forms of cancer with still rapidly increasing incidence in the western world [1] (http://seer.cancer.gov/csr/1975_2008/browse_csr.php?section=16&page=sect_16_table.05.html). Treatment opportunities arise from a large portfolio of candidate drugs some of which have made it to clinical studies; however, with differing and often unpredictable outcomes. Thus the need for a better molecular understanding of melanomagenesis and preclinical studies in-vitro and in animal models is undisputed [2]. Melanoma is a paradigm for the complexity of cancer. Melanomas arise from pigment cells of the skin, from extracutaneous sites and from the uvea of the eye. A certain fraction of cutaneous melanomas form on the basis of nevi, which then represent a precursor lesion. Others are supposed to originate from single pigment cells of the skin. The clinical heterogeneity of the disease is astonishingly high, ranging from spontaneous total remission to extremely fast, fatal progression. Although gene expression signatures of melanomas have been reported [3], [4], [5], [6], [7], only few clues were obtained for molecular subtypes that could be of clinical relevance. Obvious differences were more correlated to anatomical sites, treatment history of patients, and progression stage. A further complication widely discussed to camouflage a clear diagnostic gene expression signature, are individual genetic differences and recurrent changes that reflect epiphenomena of the transformed phenotype and the pathological physiology of the melanoma cells. In general, and especially in the melanoma field, high throughput transcriptome studies have so far not revealed the expected consensus alterations that would help to ultimately understand melanoma biology and pathology.