Scientific Reports · 2020 · 39 citations · 71 references
MedicineCell BiologyOncologyMolecular OncologyTranscriptomicsTumor MicroenvironmentCancer TranscriptomicsImmuno-oncology BiomarkersMelanocytic TumorsMolecular Tumor ProfilingTranscriptomic ProfilingTumor Immune MicroenvironmentConjunctival MelanocytesConjunctival Tumor PrognosisPrognostic BiomarkersPrognostic Expression SignaturesPrognostic Gene SignaturesRna SequencingRna Sequencing (Rna-seq)Tumor Microenvironment Biomarkers
This study characterizes the transcriptome and the cellular tumor microenvironment (TME) of conjunctival melanoma (CM) and identifies prognostically relevant biomarkers. 12 formalin-fixed and paraffin-embedded CM were analyzed by MACE RNA sequencing, including six cases each with good or poor clinical outcome, the latter being defined by local recurrence and/or systemic metastases. Eight healthy conjunctival specimens served as controls. The TME of CM, as determined by bioinformatic cell type enrichment analysis, was characterized by the enrichment of melanocytes, pericytes and especially various immune cell types, such as plasmacytoid dendritic cells, natural killer T cells, B cells and mast cells. Differentially expressed genes between CM and control were mainly involved in inhibition of apoptosis, proteolysis and response to growth factors. POU3F3, BIRC5 and 7 were among the top expressed genes associated with inhibition of apoptosis. 20 genes, among them CENPK, INHA, USP33, CASP3, SNORA73B, AAR2, SNRNP48 and GPN1, were identified as prognostically relevant factors reaching high classification accuracy (area under the curve: 1.0). The present study provides new insights into the TME and the transcriptional profile of CM and additionally identifies new prognostic biomarkers. These results add new diagnostic tools and may lead to new options of targeted therapy for CM.
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STAR: ultrafast universal RNA-seq aligner
Alexander Dobin, Carrie Davis, Felix Schlesinger et al. · Bioinformatics · 2012 · 56.2K citations · Full text
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
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