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Transcriptome profiling identifies HMGA2 as a novel gene in melanoma progression

ABSTRACT: The identification of novel tumor-specific markers may improve understanding of melanoma progression and prognostic accuracy. Whole genome expression profiling of 46 primary melanomas, 12 metastases, and 16 normal skin samples using Affymetrix U133 PLUS 2.0 array generated gene lists including both known and new melanoma genes. The molecular genetic alterations contributing to the pathogenesis of melanoma are incompletely defined and few independent prognostic features have been identified beyond the pathologic characteristics of the primary tumor. Early stage melanoma is frequently curable, in contrast to the inferior prognosis of melanomas with regional lymph nodes involvement and the incurability of distant metastatic disease. The identification of novel tumor-specific markers may improve our understanding of melanoma progression and prognostic accuracy. To find differentially expressed genes that can distinguish melanoma from normal tissue, we performed a whole genome expression profiling of 46 primary melanoma samples, 12 regional or distant metastases, and 16 normal skin samples using Affymetrix U133 2.0 Plus array. Our study generated lists of differentially expressed genes in melanoma and identified novel prognostic marker HMGA2. It is a novel, highly overexpressed melanoma gene associated with poor prognosis. The overexpression of HMGA2 is strongly associated with regional and distant metastases and serves as an independent predictor of disease-free survival and overall survival in melanoma. Melanoma samples were obtained through an IRB-approved protocol using informed consent at the University of Michigan Multidisciplinary Melanoma Clinic. A portion of pigmented lesions clinically suspicious for melanoma and known melanoma were sampled by punch biopsy at the time of excision. The punch biopsy was bisected; half was sent to for clinical diagnosis and the other half along with adjacent normal skin when available immediately snap-frozen in liquid nitrogen. Snap-frozen tissue was embedded in OCT (TissueTek) followed by frozen sectioning and H&E slide preparation. The slides were evaluated by dermatopathologist who identified areas with greater than 70% tumor cellularity, which were sampled for RNA extraction. Primary melanomas and melanoma metastases were derived from different patients. Metastatic samples included lymph nodes (n=8), subcutaneous soft tissue (n=2), spleen (n=1), and small intestine (n=1).

ORGANISM(S): Homo sapiens

SUBMITTER: Raskin Leon

PROVIDER: S-ECPF-GEOD-15605 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:The identification of novel tumor-specific markers may improve understanding of melanoma progression and prognostic accuracy. Whole genome expression profiling of 46 primary melanomas, 12 metastases, and 16 normal skin samples using Affymetrix U133 PLUS 2.0 array generated gene lists including both known and new melanoma genes. The molecular genetic alterations contributing to the pathogenesis of melanoma are incompletely defined and few independent prognostic features have been identified beyond the pathologic characteristics of the primary tumor. Early stage melanoma is frequently curable, in contrast to the inferior prognosis of melanomas with regional lymph nodes involvement and the incurability of distant metastatic disease. The identification of novel tumor-specific markers may improve our understanding of melanoma progression and prognostic accuracy. To find differentially expressed genes that can distinguish melanoma from normal tissue, we performed a whole genome expression profiling of 46 primary melanoma samples, 12 regional or distant metastases, and 16 normal skin samples using Affymetrix U133 2.0 Plus array. Our study generated lists of differentially expressed genes in melanoma and identified novel prognostic marker HMGA2. It is a novel, highly overexpressed melanoma gene associated with poor prognosis. The overexpression of HMGA2 is strongly associated with regional and distant metastases and serves as an independent predictor of disease-free survival and overall survival in melanoma. Melanoma samples were obtained through an IRB-approved protocol using informed consent at the University of Michigan Multidisciplinary Melanoma Clinic. A portion of pigmented lesions clinically suspicious for melanoma and known melanoma were sampled by punch biopsy at the time of excision. The punch biopsy was bisected; half was sent to for clinical diagnosis and the other half along with adjacent normal skin when available immediately snap-frozen in liquid nitrogen. Snap-frozen tissue was embedded in OCT (TissueTek) followed by frozen sectioning and H&E slide preparation. The slides were evaluated by dermatopathologist who identified areas with greater than 70% tumor cellularity, which were sampled for RNA extraction. Primary melanomas and melanoma metastases were derived from different patients. Metastatic samples included lymph nodes (n=8), subcutaneous soft tissue (n=2), spleen (n=1), and small intestine (n=1).

Project description:BackgroundDeveloping analytical methodologies to identify biomarkers in easily accessible body fluids is highly valuable for the early diagnosis and management of cancer patients. Peripheral whole blood is a "nucleic acid-rich" and "inflammatory cell-rich" information reservoir and represents systemic processes altered by the presence of cancer cells.Methodology/principal findingsWe conducted transcriptome profiling of whole blood cells from melanoma patients. To overcome challenges associated with blood-based transcriptome analysis, we used a PAXgene™ tube and NuGEN Ovation™ globin reduction system. The combined use of these systems in microarray resulted in the identification of 78 unique genes differentially expressed in the blood of melanoma patients. Of these, 68 genes were further analyzed by quantitative reverse transcriptase PCR using blood samples from 45 newly diagnosed melanoma patients (stage I to IV) and 50 healthy control individuals. Thirty-nine genes were verified to be differentially expressed in blood samples from melanoma patients. A stepwise logit analysis selected eighteen 2-gene signatures that distinguish melanoma from healthy controls. Of these, a 2-gene signature consisting of PLEK2 and C1QB led to the best result that correctly classified 93.3% melanoma patients and 90% healthy controls. Both genes were upregulated in blood samples of melanoma patients from all stages. Further analysis using blood fractionation showed that CD45(-) and CD45(+) populations were responsible for the altered expression levels of PLEK2 and C1QB, respectively.Conclusions/significanceThe current study provides the first analysis of whole blood-based transcriptome biomarkers for malignant melanoma. The expression of PLEK2, the strongest gene to classify melanoma patients, in CD45(-) subsets illustrates the importance of analyzing whole blood cells for biomarker studies. The study suggests that transcriptome profiling of blood cells could be used for both early detection of melanoma and monitoring of patients for residual disease.

Project description:BackgroundGene expression profiling has revolutionized our ability to molecularly classify primary human tumors and significantly enhanced the development of novel tumor markers and therapies; however, progress in the diagnosis and treatment of melanoma over the past 3 decades has been limited, and there is currently no approved therapy that significantly extends lifespan in patients with advanced disease. Profiling studies of melanoma to date have been inconsistent due to the heterogeneous nature of this malignancy and the limited availability of informative tissue specimens from early stages of disease.Methodology/principle findingsIn order to gain an improved understanding of the molecular basis of melanoma progression, we have compared gene expression profiles from a series of melanoma cell lines representing discrete stages of malignant progression that recapitulate critical characteristics of the primary lesions from which they were derived. Here we describe the unsupervised hierarchical clustering of profiling data from melanoma cell lines and melanocytes. This clustering identifies two distinctive molecular subclasses of melanoma segregating aggressive metastatic tumor cell lines from less-aggressive primary tumor cell lines. Further analysis of expression signatures associated with melanoma progression using functional annotations categorized these transcripts into three classes of genes: 1) Upregulation of activators of cell cycle progression, DNA replication and repair (CDCA2, NCAPH, NCAPG, NCAPG2, PBK, NUSAP1, BIRC5, ESCO2, HELLS, MELK, GINS1, GINS4, RAD54L, TYMS, and DHFR), 2) Loss of genes associated with cellular adhesion and melanocyte differentiation (CDH3, CDH1, c-KIT, PAX3, CITED1/MSG-1, TYR, MELANA, MC1R, and OCA2), 3) Upregulation of genes associated with resistance to apoptosis (BIRC5/survivin). While these broad classes of transcripts have previously been implicated in the progression of melanoma and other malignancies, the specific genes identified within each class of transcripts are novel. In addition, the transcription factor NF-KB was specifically identified as being a potential "master regulator" of melanoma invasion since NF-KB binding sites were identified as consistent consensus sequences within promoters of progression-associated genes.Conclusions/significanceWe conclude that tumor cell lines are a valuable resource for the early identification of gene signatures associated with malignant progression in tumors with significant heterogeneity like melanoma. We further conclude that the development of novel data reduction algorithms for analysis of microarray studies is critical to allow for optimized mining of important, clinically-relevant datasets. It is expected that subsequent validation studies in primary human tissues using such an approach will lead to more rapid translation of such studies to the identification of novel tumor biomarkers and therapeutic targets.

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Transcriptome profiling identifies HMGA2 as a novel gene in melanoma progression

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