Dataset Information

Molecular profiling reveals low- and high-grade forms of primary melanoma.

ABSTRACT: For primary melanomas, tumor thickness, mitotic rate, and ulceration are well-laid cornerstones of prognostication. However, a molecular exposition of melanoma aggressiveness is critically missing. We recently uncovered a four-class structure in metastatic melanoma, which predicts outcome and informs biology. This raises the possibility that a molecular structure exists even in the early stages of melanoma and that molecular determinants could underlie histophenotype and eventual patient outcome.We subjected 223 archival primary melanomas to a horizontally integrated analysis of RNA expression, oncogenic mutations at 238 lesions, histomorphometry, and survival data.Our previously described four-class structure that was elucidated in metastatic lesions was evident within the expression space of primary melanomas. Because these subclasses converged into two larger prognostic and phenotypic groups, we used the metastatic lesions to develop a binary subtype-based signature capable of distinguishing between "high" and "low" grade forms of the disease. The two-grade signature was subsequently applied to the primary melanomas. Compared with low-grade tumors, high-grade primary melanomas were significantly associated with increased tumor thickness, mitotic rate, ulceration (all P < 0.01), and poorer relapse-free (HR = 4.94; 95% CI, 2.84-8.59), and overall (HR = 3.66; 95% CI, 2.40-5.58) survival. High-grade melanomas exhibited elevated levels of proliferation and BRCA1/DNA damage signaling genes, whereas low-grade lesions harbored higher expression of immune genes. Importantly, the molecular-grade signature was validated in two external gene expression data sets.We provide evidence for a molecular organization within melanomas, which is preserved across all stages of disease.

SUBMITTER: Harbst K

PROVIDER: S-EPMC3467105 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular profiling reveals low- and high-grade forms of primary melanoma.

Harbst Katja K Staaf Johan J Lauss Martin M Karlsson Anna A Måsbäck Anna A Johansson Iva I Bendahl Pär-Ola PO Vallon-Christersson Johan J Törngren Therese T Ekedahl Henrik H Geisler Jürgen J Höglund Mattias M Ringnér Markus M Lundgren Lotta L Jirström Karin K Olsson Håkan H Ingvar Christian C Borg Åke Å Tsao Hensin H Jönsson Göran G

Clinical cancer research : an official journal of the American Association for Cancer Research 20120606 15

<h4>Purpose</h4>For primary melanomas, tumor thickness, mitotic rate, and ulceration are well-laid cornerstones of prognostication. However, a molecular exposition of melanoma aggressiveness is critically missing. We recently uncovered a four-class structure in metastatic melanoma, which predicts outcome and informs biology. This raises the possibility that a molecular structure exists even in the early stages of melanoma and that molecular determinants could underlie histophenotype and eventual ...[more]

PMID: 22675174

Similar Datasets

Project description:Purpose: To define copy number alterations and gene expression signatures underlying pediatric high-grade glioma (HGG). Patients and Methods: We conducted a high-resolution analysis of genomic imbalances in 78 de novo pediatric HGG, including 7 diffuse intrinsic pontine gliomas, and 10 HGG cases arising in children who received cranial irradiation for a previous cancer, using Affymetrix 500K GeneChips. Gene expression signatures for 53 tumors were analyzed with Affymetrix U133v2 arrays. Results were compared with publicly available data from adult tumors. Results: Pediatric and adult glioblastoma were clearly distinguished by frequent gain of chromosome 1q (30% vs 9%) and lower frequency of chromosome 7 gain (13% vs 74%), respectively. The most common focal amplifications also differed, with PDGFRA and EGFR predominant in childhood and adult populations respectively. These common alterations in pediatric HGG were detected at higher frequency in irradiation-induced tumors, suggesting that these are initiating events in childhood gliomagenesis. CDKN2A was the most common tumor suppressor gene targeted by homozygous deletion in pediatric HGG. No IDH1 hotspot mutations were found in pediatric tumors, highlighting molecular differences in pathogenesis between childhood HGG and adult secondary glioblastoma. Integrated copy number and gene expression data indicated that deregulated PDGFRA signaling plays a major role in pediatric HGG. Conclusions: Integrated molecular profiling showed substantial differences in the molecular features underlying pediatric and adult HGG, indicating that findings in adult tumors cannot be simply extrapolated to younger patients. PDGFRA may be a useful target for pediatric HGG including diffuse pontine gliomas. Keywords: disease state analysis 78 samples for SNP analysis, including 10 samples arising in children who received cranial irradiation for a previous cancer and 7 diffuse pontine gliomas; 53 of them with gene expression analysis; 2 tumor grades To have access to SNP CEL files, please contact Dr. Suzanne Baker (suzzane.baker@stjude.org).

Project description:BackgroundPediatric brain tumors are the leading cause of death for children with cancer in the U.S. Incorporating next-generation sequencing data for both pediatric low-grade (pLGGs) and high-grade gliomas (pHGGs) can inform diagnostic, prognostic, and therapeutic decision-making.Materials and methodsWe performed comprehensive genomic profiling on 282 pediatric gliomas (157 pHGGs, 125 pLGGs), sequencing 315 cancer-related genes and calculating the tumor mutational burden (TMB; mutations per megabase [Mb]).ResultsIn pLGGs, we detected genomic alterations (GA) in 95.2% (119/125) of tumors. BRAF was most frequently altered (48%; 60/125), and FGFR1 missense (17.6%; 22/125), NF1 loss of function (8.8%; 11/125), and TP53 (5.6%; 7/125) mutations were also detected. Rearrangements were identified in 35% of pLGGs, including KIAA1549-BRAF, QKI-RAF1, FGFR3-TACC3, CEP85L-ROS1, and GOPC-ROS1 fusions. Among pHGGs, GA were identified in 96.8% (152/157). The genes most frequently mutated were TP53 (49%; 77/157), H3F3A (37.6%; 59/157), ATRX (24.2%; 38/157), NF1 (22.2%; 35/157), and PDGFRA (21.7%; 34/157). Interestingly, most H3F3A mutations (81.4%; 35/43) were the variant K28M. Midline tumor analysis revealed H3F3A mutations (40%; 40/100) consisted solely of the K28M variant. Pediatric high-grade gliomas harbored oncogenic EML4-ALK, DGKB-ETV1, ATG7-RAF1, and EWSR1-PATZ1 fusions. Six percent (9/157) of pHGGs were hypermutated (TMB >20 mutations per Mb; range 43-581 mutations per Mb), harboring mutations deleterious for DNA repair in MSH6, MSH2, MLH1, PMS2, POLE, and POLD1 genes (78% of cases).ConclusionComprehensive genomic profiling of pediatric gliomas provides objective data that promote diagnostic accuracy and enhance clinical decision-making. Additionally, TMB could be a biomarker to identify pediatric glioblastoma (GBM) patients who may benefit from immunotherapy.Implications for practiceBy providing objective data to support diagnostic, prognostic, and therapeutic decision-making, comprehensive genomic profiling is necessary for advancing care for pediatric neuro-oncology patients. This article presents the largest cohort of pediatric low- and high-grade gliomas profiled by next-generation sequencing. Reportable alterations were detected in 95% of patients, including diagnostically relevant lesions as well as novel oncogenic fusions and mutations. Additionally, tumor mutational burden (TMB) is reported, which identifies a subpopulation of hypermutated glioblastomas that harbor deleterious mutations in DNA repair genes. This provides support for TMB as a potential biomarker to identify patients who may preferentially benefit from immune checkpoint inhibitors.

Dataset Information

Molecular profiling reveals low- and high-grade forms of primary melanoma.

Publications

Molecular profiling reveals low- and high-grade forms of primary melanoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets