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Transcriptional characterization of conjunctival melanoma identifies the cellular tumor microenvironment and prognostic gene signatures.

ABSTRACT: 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.

SUBMITTER: Wolf J

PROVIDER: S-EPMC7550331 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Transcriptional characterization of conjunctival melanoma identifies the cellular tumor microenvironment and prognostic gene signatures.

Wolf Julian J Auw-Haedrich Claudia C Schlecht Anja A Boneva Stefaniya S Mittelviefhaus Hans H Lapp Thabo T Agostini Hansjürgen H Reinhard Thomas T Schlunck Günther G Lange Clemens A K CAK

Scientific reports 20201012 1

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 en ...[more]

PMID: 33046735

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Project description:Purpose: To characterize the transcriptome and cellular the tumor microenvi-ronment of conjunctival melanoma (CM) compared to healthy conjunctiva and to analyze the transcriptional differences between CM with good and poor clinical outcome. Methods: Twelve formalin-fixed and paraffin-embedded (FFPE) CM of twelve patients were analyzed by Massive Analysis of cDNA Ends (MACE) RNA se-quencing. Six samples each with good and poor clinical outcome were exam-ined, the latter being defined by local recurrence or systemic metastases with a follow-up of at least 24 months. Eight age-matched healthy FFPE conjunctival specimens from eight patients who underwent retinal detachment surgery served as controls. Bioinformatic cell type enrichment analysis with xCell was used to characterize the tumor microenvironment (TME). Differentially expressed genes (DEG) and the associated biological processes were analyzed between CM and control conjunctiva. Additionally, a prognostic transcription profile was identified by comparing melanoma of good and poor clinical outcome. Results: The TME of conjunctival melanoma was characterized by the enrich-ment of melanocytes, pericytes and especially several immune cell types. Among them, plasmacytoid dendritic cells (pDC), natural killer T cells (NKT), B cells and mast cells were most significantly increased in CM compared to healthy conjunc-tiva. DEG between CM and control were mainly involved in biological processes such as inhibition of apoptosis, proteolysis and response to growth factors. POU3F3, BIRC5 and 7 were among the top expressed genes associated with inhibition of apoptosis. Twenty genes, among them CENPK, INHA, USP33 and CASP3, were identified as prognostically relevant factors reaching high classifi-cation accuracy (AUC: 1.0). Conclusions: The present study provides new insights into the TME and the transcriptional profile of CM and additionally identifies new prognostic bi-omarkers. These results might lead to new diagnostic and therapeutic options for CM.

Project description:Breast cancer is one of the most common female malignancies worldwide. Due to its early metastases formation and a high degree of malignancy, the 10 year-survival rate of metastatic breast cancer does not exceed 30%. Thus, more precise biomarkers are urgently needed. In our study, we first estimated the tumor microenvironment (TME) infiltration using the xCell algorithm. Based on TME infiltration, the three main TME clusters were identified using consensus clustering. Our results showed that the three main TME clusters cause significant differences in survival rates and TME infiltration patterns (log-rank test, p = 0.006). Then, multiple machine learning algorithms were used to develop a nine-pathway-based TME-related risk model to predict the prognosis of breast cancer (BRCA) patients (the immune-related pathway-based risk score, defined as IPRS). Based on the IPRS, BRCA patients were divided into two subgroups, and patients in the IPRS-low group presented significantly better overall survival (OS) rates than the IPRS-high group (log-rank test, p < 0.0001). Correlation analysis revealed that the IPRS-low group was characterized by increases in immune-related scores (cytolytic activity (CYT), major histocompatibility complex (MHC), T cell-inflamed immune gene expression profile (GEP), ESTIMATE, immune, and stromal scores) while exhibiting decreases in tumor purity, suggesting IPRS-low patients may have a strong immune response. Additionally, the gene-set enrichment analysis (GSEA) result confirmed that the IPRS-low patients were significantly enriched in several immune-associated signaling pathways. Furthermore, multivariate Cox analysis revealed that the IPRS was an independent prognostic biomarker after adjustment by clinicopathologic characteristics. The prognostic value of the IPRS model was further validated in three external validation cohorts. Altogether, our findings demonstrated that the IPRS was a powerful predictor to screen out certain populations with better prognosis in breast cancer and may serve as a potential biomarker guiding clinical treatment decisions.

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Transcriptional characterization of conjunctival melanoma identifies the cellular tumor microenvironment and prognostic gene signatures.

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Transcriptional characterization of conjunctival melanoma identifies the cellular tumor microenvironment and prognostic gene signatures.

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