Ontology highlight
ABSTRACT:
PROVIDER: PRJNA717153 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14068164_1.fastq.gz | Fastqsanger.gz | |||
| SRR14068164_2.fastq.gz | Fastqsanger.gz | |||
| SRR14068165_1.fastq.gz | Fastqsanger.gz | |||
| SRR14068165_2.fastq.gz | Fastqsanger.gz | |||
| SRR14068166_1.fastq.gz | Fastqsanger.gz |
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Project description:Recent studies revealed trajectories of mutational events in early melanomagenesis, but the accompanying changes in gene expression are far less understood. Therefore, we performed a comprehensive RNA-Seq analysis of laser-microdissected melanocytic nevi (n=23) and primary melanoma samples (n=57) and characterized the molecular mechanisms of early melanoma development. Using self-organizing maps, unsupervised clustering and analysis of pseudotime (PT) dynamics to identify evolutionary trajectories, we describe here two transcriptomic types of melanocytic nevi (N1 and N2) and primary melanomas (M1 and M2). N1/M1 lesions are characterized by pigmentation-type and MITF gene signatures, and a high prevalence of NRAS mutations in M1 melanomas. N2/M2 lesions are characterized by inflammatory-type and AXL gene signatures with an equal distribution of wild type and mutated BRAF and low prevalence of NRAS mutations in M2 melanomas. Interestingly, N1 nevi and M1 melanomas and N2 nevi and M2 melanomas, respectively, cluster together, but there is no clustering in a stage-dependent manner. Transcriptional signatures of M1 melanomas harbour signatures of BRAF/MEK inhibitor resistance and M2 melanomas harbour signatures of anti-PD-1 antibody treatment resistance. Transcriptomic signatures suggest that the epigenetic regulators SMARCA2 and SMARCA4 are differentially involved in the epigenetic programming of the two melanoma types. Pseudotime dynamics of nevus and melanoma samples reflect a switch-like immune-escape mechanism in melanoma development with downregulation of immune genes paralleled by an increasing expression of a cell cycle signature in late-stage melanomas. Taken together, the transcriptome analysis identifies gene signatures and mechanisms underlying development of melanoma in early and late stages with relevance for diagnostics and therapy.
2018-07-19 | GSE112509 | GEO
Project description:To gain insights into the genetic profile of every stage of the melanoma progression pathway, and to determine to what extent these profiles are similar or distinct, we performed whole-genome expression profiling of tissue specimens representing normal skin, benign and atypical nevi, and early and advanced-stage melanomas. The results of this study provide first-time evidence that significant molecular changes occur distinctly at the border of/transition from melanoma in situ to primary melanoma, and that genes involved in mitotic cell cycle regulation and cell proliferation constitute the two leading categories of genes associated with these changes. Keywords: Stage comparative analysis
2006-04-01 | GSE4587 | GEO
Project description:To gain insights into the genetic profile of every stage of the melanoma progression pathway, and to determine to what extent these profiles are similar or distinct, we performed whole-genome expression profiling of tissue specimens representing normal skin, benign and atypical nevi, and early and advanced-stage melanomas. The results of this study provide first-time evidence that significant molecular changes occur distinctly at the border of/transition from melanoma in situ to primary melanoma, and that genes involved in mitotic cell cycle regulation and cell proliferation constitute the two leading categories of genes associated with these changes.
2007-12-14 | E-GEOD-4587 | biostudies-arrayexpress
Project description:BACKGROUND: Because of the distinct clinical presentation of early and advanced stage ovarian cancer, we aim to clarify whether these disease entities are solely separated by time of diagnosis or whether they arise from distinct molecular events. METHODS: Sixteen early and sixteen advanced stage ovarian carcinomas, matched for histological subtype and differentiation grade, were included. Genomic aberrations were compared for each early and advanced stage ovarian cancer by array comparative genomic hybridization. To study how the aberrations correlate to the clinical characteristics of the tumors we clustered tumors based on the genomic aberrations. RESULTS: The genomic aberration patterns in advanced stage cancer equalled those in early stage, but were more frequent in advanced stage (p = 0.012). Unsupervised clustering based on genomic aberrations yielded two clusters that significantly discriminated early from advanced stage (p = 0.001), and that did differ significantly in survival (p = 0.002). These clusters however did give a more accurate prognosis than histological subtype or differentiation grade. CONCLUSION: This study indicates that advanced stage ovarian cancer either progresses from early stage or from a common precursor lesion but that they do not arise from distinct carcinogenic molecular events. Furthermore, we show that array comparative genomic hybridization has the potential to identify clinically distinct patients.
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Project description:Here we analyze key epigenetic marks from medaka (O. latipes) during the vertebrate phylotypic period (stage 24).
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Project description:BACKGROUND: Because of the distinct clinical presentation of early and advanced stage ovarian cancer, we aim to clarify whether these disease entities are solely separated by time of diagnosis or whether they arise from distinct molecular events. METHODS: Sixteen early and sixteen advanced stage ovarian carcinomas, matched for histological subtype and differentiation grade, were included. Genomic aberrations were compared for each early and advanced stage ovarian cancer by array comparative genomic hybridization. To study how the aberrations correlate to the clinical characteristics of the tumors we clustered tumors based on the genomic aberrations. RESULTS: The genomic aberration patterns in advanced stage cancer equalled those in early stage, but were more frequent in advanced stage (p?=?0.012). Unsupervised clustering based on genomic aberrations yielded two clusters that significantly discriminated early from advanced stage (p?=?0.001), and that did differ significantly in survival (p?=?0.002). These clusters however did give a more accurate prognosis than histological subtype or differentiation grade. CONCLUSION: This study indicates that advanced stage ovarian cancer either progresses from early stage or from a common precursor lesion but that they do not arise from distinct carcinogenic molecular events. Furthermore, we show that array comparative genomic hybridization has the potential to identify clinically distinct patients. Sixteen early and sixteen advanced stage ovarian carcinomas
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Project description:We have improved the DamID method to make it applicable for vertebrate life specimens. We use iDamID-seq to profile the binding profile of the transcription factor Rx2 in medaka embryos at stage 22 of development. We compare two replicates of the fusion Dam-Rx2 against two replicates of the fusion Dam-GFP as control. Medaka embryos at 1-cell stage were injected with mRNA transcribed in vitro from one of the two Dam fusions. The embryos were allowed to grow in normal conditions up to stage 22. The genomic DNA was isolated and treated to extract only the DpnI fragments that had adenine methylation. These fragments were subjected to deep sequencing.
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Project description:An epigenetic gene signature underlies phenotype switching in early stage melanomas.
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