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Toward predicting metastatic progression of melanoma based on gene expression data.

ABSTRACT: Primary and metastatic melanoma tumors share the same cell origin, making it challenging to identify genomic biomarkers that can differentiate them. Primary tumors themselves can be heterogeneous, reflecting ongoing genomic changes as they progress toward metastasizing. We developed a computational method to explore this heterogeneity and to predict metastatic progression of the primary tumors. We applied our method separately to gene expression and to microRNA (miRNA) expression data from ~450 primary and metastatic skin cutaneous melanoma (SKCM) samples from the Cancer Genome Atlas (TCGA). Metastatic progression scores from RNA-seq data were significantly associated with clinical staging of patients' lymph nodes, whereas scores from miRNA-seq data were significantly associated with Clark's level. The loss of expression of many characteristic epithelial lineage genes in primary SKCM tumor samples was highly correlated with predicted progression scores. We suggest that those genes/miRNAs might serve as putative biomarkers for SKCM metastatic progression.

SUBMITTER: Li Y

PROVIDER: S-EPMC4469521 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Toward predicting metastatic progression of melanoma based on gene expression data.

Li Yuanyuan Y Krahn Juno M JM Flake Gordon P GP Umbach David M DM Li Leping L

Pigment cell & melanoma research 20150424 4

Primary and metastatic melanoma tumors share the same cell origin, making it challenging to identify genomic biomarkers that can differentiate them. Primary tumors themselves can be heterogeneous, reflecting ongoing genomic changes as they progress toward metastasizing. We developed a computational method to explore this heterogeneity and to predict metastatic progression of the primary tumors. We applied our method separately to gene expression and to microRNA (miRNA) expression data from ~450 ...[more]

PMID: 25847062

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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:BackgroundThe process of malignant transformation, progression and metastasis of melanoma is poorly understood. Gene expression profiling of human cancer has allowed for a unique insight into the genes that are involved in these processes. Thus, we have attempted to utilize this approach through the analysis of a series of primary, non-metastatic cutaneous tumors and metastatic melanoma samples.MethodsWe have utilized gene microarray analysis and a variety of molecular techniques to compare 40 metastatic melanoma (MM) samples, composed of 22 bulky, macroscopic (replaced) lymph node metastases, 16 subcutaneous and 2 distant metastases (adrenal and brain), to 42 primary cutaneous cancers, comprised of 16 melanoma, 11 squamous cell, 15 basal cell skin cancers. A Human Genome U133 Plus 2.0 array from Affymetrix, Inc. was utilized for each sample. A variety of statistical software, including the Affymetrix MAS 5.0 analysis software, was utilized to compare primary cancers to metastatic melanomas. Separate analyses were performed to directly compare only primary melanoma to metastatic melanoma samples. The expression levels of putative oncogenes and tumor suppressor genes were analyzed by semi- and real-time quantitative RT-PCR (qPCR) and Western blot analysis was performed on select genes.ResultsWe find that primary basal cell carcinomas, squamous cell carcinomas and thin melanomas express dramatically higher levels of many genes, including SPRR1A/B, KRT16/17, CD24, LOR, GATA3, MUC15, and TMPRSS4, than metastatic melanoma. In contrast, the metastatic melanomas express higher levels of genes such as MAGE, GPR19, BCL2A1, MMP14, SOX5, BUB1, RGS20, and more. The transition from non-metastatic expression levels to metastatic expression levels occurs as melanoma tumors thicken. We further evaluated primary melanomas of varying Breslow's tumor thickness to determine that the transition in expression occurs at different thicknesses for different genes suggesting that the "transition zone" represents a critical time for the emergence of the metastatic phenotype. Several putative tumor oncogenes (SPP-1, MITF, CITED-1, GDF-15, c-Met, HOX loci) and suppressor genes (PITX-1, CST-6, PDGFRL, DSC-3, POU2F3, CLCA2, ST7L), were identified and validated by quantitative PCR as changing expression during this transition period. These are strong candidates for genes involved in the progression or suppression of the metastatic phenotype.ConclusionThe gene expression profiling of primary, non-metastatic cutaneous tumors and metastatic melanoma has resulted in the identification of several genes that may be centrally involved in the progression and metastatic potential of melanoma. This has very important implications as we continue to develop an improved understanding of the metastatic process, allowing us to identify specific genes for prognostic markers and possibly for targeted therapeutic approaches.

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Toward predicting metastatic progression of melanoma based on gene expression data.

Publications

Toward predicting metastatic progression of melanoma based on gene expression data.

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