ArticleOncogene2018
RNA-seq analysis identifies different transcriptomic types and developmental trajectories of primary melanomas.
Article in Oncogene, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.
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Who cites it
67 citing papers in PubMed, 115 citations in OpenAlex.
- Transcriptomic profiling identifies immunotherapy-responsive phenotypes in microsatellite-stable metastatic colorectal cancer.Oncogene · 2026Article
- A Targetable Developmental Program Coregulates Angiogenesis and Immune Evasion in Melanoma.Cancer discovery · 2026Article
- Context-dependent phosphorylation of CSDE1 drives interactions with ribosomes.RNA (New York, N.Y.) · 2025Article
- Towards a transcriptomic biomarker for the classification of melanocytic neoplasms.PLoS genetics · 2025Article
- Uncovering Novel lncRNAs Linked to Melanoma Growth and Migration with CRISPR Inhibition Screening.Cancer research communications · 2025Article
- Crosstalk in Skin: Loss of Desmoglein 1 in Keratinocytes Inhibits BRAFThe Journal of investigative dermatology · 2025Article
- Spatial determinants of tumor cell dedifferentiation and plasticity in primary cutaneous melanoma.bioRxiv : the preprint server for biology · 2025Article
- No Evidence for Distinct Transcriptomic Subgroups of Devil Facial Tumor Disease (DFTD).Evolutionary applications · 2025Article
- Exploiting Paradoxical Activation of Oncogenic MAPK Signaling by Targeting Mitochondria to SensitizeInternational journal of molecular sciences · 2025Article
- PPIXpress and PPICompare webservers infer condition-specific and differential PPI networks.Bioinformatics advances · 2025Article
- Application of transcriptomics techniques in skin cancer.Frontiers in oncology · 2025Review
- Identification of biomarkers and target drugs for melanoma: a topological and deep learning approach.Frontiers in genetics · 2025Article
- A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections.Current issues in molecular biology · 2024Article
- Heterogeneity and molecular landscape of melanoma: implications for targeted therapy.Molecular biomedicine · 2024Review
- NRN1 interacts with Notch to increase oncogenic STAT3 signaling in melanoma.Cell communication and signaling : CCS · 2024Article
- Thiol starvation triggers melanoma state switching in an ATF4 and NRF2-dependent manner.Redox biology · 2024Article
- Unsupervised analysis of whole transcriptome data from human pluripotent stem cells cardiac differentiation.Scientific reports · 2024Article
- PTEN Lipid Phosphatase Activity Suppresses Melanoma Formation by Opposing an AKT/mTOR/FRA1 Signaling Axis.Cancer research · 2024Article
- Uncovering potential diagnostic and pathophysiological roles of α-synuclein and DJ-1 in melanoma.Cancer medicine · 2024Article
- Functional analysis of recurrent CDC20 promoter variants in human melanoma.Communications biology · 2023Article
7 more citing papers are in PubMed but not listed here.
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Authors and funding
24 authors at 11 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 harbor signatures of BRAF/MEK inhibitor resistance and M2 melanomas harbor signatures of anti-PD-1 antibody treatment resistance. Pseudotime dynamics of nevus and melanoma samples are suggestive for 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.
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