Dataset Information

Expression profiles of p53/p73, NME and GLI families in metastatic melanoma tissue and cell lines.

ABSTRACT: Unlike other tumours, TP53 is rarely mutated in melanoma; however, it fails to function as a tumour suppressor. We assume that its functions might be altered through interactions with several families of proteins, including p53/p73, NME and GLI. To elucidate the potential interplay among these families we analysed the expression profiles of aforementioned genes and proteins in a panel of melanoma cell lines, metastatic melanoma specimens and healthy corresponding tissue. Using qPCR a higher level of NME1 gene expression and lower levels of ?40p53?, ?Np73, GLI1, GLI2 and PTCH1 were observed in tumour samples compared to healthy tissue. Protein expression of ?133p53?, ?160p53? and ?Np73? isoforms, NME1 and NME2, and N'?GLI1, GLI1FL, GLI2?N isoforms was elevated in tumour tissue, whereas ?Np73? was downregulated. The results in melanoma cell lines, in general, support these findings. In addition, we correlated expression profiles with clinical features and outcome. Higher ?133p53? and p53? mRNA and both GLI1 mRNA and GLI3R protein expression had a negative impact on the overall survival. Shorter overall survival was also connected with lower p53? and NME1 gene expression levels. In conclusion, all examined genes may have implications in melanoma development and functional inactivity of TP53.

SUBMITTER: Ozretic P

PROVIDER: S-EPMC6713730 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Expression profiles of p53/p73, NME and GLI families in metastatic melanoma tissue and cell lines.

Ozretić Petar P Hanžić Nikolina N Proust Bastien B Sabol Maja M Trnski Diana D Radić Martina M Musani Vesna V Ciribilli Yari Y Milas Ivan I Puljiz Zvonimir Z Bosnar Maja Herak MH Levanat Sonja S Slade Neda N

Scientific reports 20190828 1

Unlike other tumours, TP53 is rarely mutated in melanoma; however, it fails to function as a tumour suppressor. We assume that its functions might be altered through interactions with several families of proteins, including p53/p73, NME and GLI. To elucidate the potential interplay among these families we analysed the expression profiles of aforementioned genes and proteins in a panel of melanoma cell lines, metastatic melanoma specimens and healthy corresponding tissue. Using qPCR a higher leve ...[more]

PMID: 31462745

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Project description:Melanoma can progress rapidly from a slow-growing surgically curable lesion to aggressive metastatic disease, with high mortality and poor response to current therapies. The mechanisms underlying melanoma progression and resistance to therapeutic agents are not well understood. There are few treatment options for melanoma once it has metastasized, and new biomarkers that aid diagnosis, predict clinical outcome, and suggest new therapies are required. This aim of this study was to invesigate the molecular basis of melanoma biology and heterogeneity by defining genomic characteristics that correlated with tumour phenotype in a novel panel of 25 cell lines derived largely from New Zealand patients with metastatic melanoma. The goals of this study were to (i) stratify melanoma cell lines by using global gene expression profiling ; (ii) correlate gene expression profiles with invasive potential; and (iii) identify new prognostic markers and therapeutic targets that might aid clinical cancer diagnosis and management. Two-colour spotted oligonucleotide microarrays were used to measure global gene expression in metastatic melanoma cell lines against a common universal reference. Biological replication was achieved by performing replicate arrays on a subset of randomly selected cell lines, in which the replicate total RNA samples were isolated from different vials of cells at different passage numbers, grown by different researchers, and often in different laboratories. Further, NZM01 and NZM02 were derived from different tumours from the same patient at different surgeries, and NZM07.2 and 07.4 were derived from the NZM07 cell line. The array hybridisations were peformed in three batches. Technical replication was achieved by using intra- and inter-batch replicates with different RNA samples from 6/25 of the cell lines: NZM04, 2 x batch 1, 1 x batch 2; NZM22, 2 x batch 1; NZM40, 1 x batch 1, 1 x batch 2; NZM06, 1 x batch 1, 1 x batch 3; NZM09, 1 x batch 1, 1 x batch 2; NZM15, 1 x batch 2, 1 x batch 3.

Project description:BACKGROUND:Heritable factors are evidently involved in prostate cancer (PrCa) carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making treatment decisions to distinguish aggressive cases from indolent disease, for which heritable factors could be a useful tool. The genetic makeup of PrCa has only recently begun to be unravelled through large-scale genome-wide association studies (GWAS). The thus far identified Single Nucleotide Polymorphisms (SNPs) explain, however, only a fraction of familial clustering. Moreover, the known risk SNPs are not associated with the clinical outcome of the disease, such as aggressive or metastasised disease, and therefore cannot be used to predict the prognosis. Annotating the SNPs with deep clinical data together with miRNA expression profiles can improve the understanding of the underlying mechanisms of different phenotypes of prostate cancer. RESULTS:In this study microRNA (miRNA) profiles were studied as potential biomarkers to predict the disease outcome. The study subjects were from Finnish high risk prostate cancer families. To identify potential biomarkers we combined a novel non-parametrical test with an importance measure provided from a Random Forest classifier. This combination delivered a set of nine miRNAs that was able to separate cases from controls. The detected miRNA expression profiles could predict the development of the disease years before the actual PrCa diagnosis or detect the existence of other cancers in the studied individuals. Furthermore, using an expression Quantitative Trait Loci (eQTL) analysis, regulatory SNPs for miRNA miR-483-3p that were also directly associated with PrCa were found. CONCLUSION:Based on our findings, we suggest that blood-based miRNA expression profiling can be used in the diagnosis and maybe even prognosis of the disease. In the future, miRNA profiling could possibly be used in targeted screening, together with Prostate Specific Antigene (PSA) testing, to identify men with an elevated PrCa risk.

Dataset Information

Expression profiles of p53/p73, NME and GLI families in metastatic melanoma tissue and cell lines.

Publications

Expression profiles of p53/p73, NME and GLI families in metastatic melanoma tissue and cell lines.

Similar Datasets

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