Dataset Information

Learning from Embryogenesis-A Comparative Expression Analysis in Melanoblast Differentiation and Tumorigenesis Reveals miRNAs Driving Melanoma Development.

ABSTRACT: Malignant melanoma is one of the most dangerous tumor types due to its high metastasis rates and a steadily increasing incidence. During tumorigenesis, the molecular processes of embryonic development, exemplified by epithelial-mesenchymal transition (EMT), are often reactivated. For melanoma development, the exact molecular differences between melanoblasts, melanocytes, and melanoma cells are not completely understood. In this study, we aimed to identify microRNAs (miRNAs) that promote melanoma tumorigenesis and progression, based on an in vitro model of normal human epidermal melanocyte (NHEM) de-differentiation into melanoblast-like cells (MBrCs). Using miRNA-sequencing and differential expression analysis, we demonstrated in this study that a majority of miRNAs have an almost equal expression level in NHEMs and MBrCs but are significantly differentially regulated in primary tumor- and metastasis-derived melanoma cell lines. Further, a target gene analysis of strongly regulated but functionally unknown miRNAs yielded the implication of those miRNAs in many important cellular pathways driving malignancy. We hypothesize that many of the miRNAs discovered in our study are key drivers of melanoma development as they account for the tumorigenic potential that differentiates melanoma cells from proliferating or migrating embryonic cells.

SUBMITTER: Linck-Paulus L

PROVIDER: S-EPMC8197100 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Learning from Embryogenesis-A Comparative Expression Analysis in Melanoblast Differentiation and Tumorigenesis Reveals miRNAs Driving Melanoma Development.

Linck-Paulus Lisa L Lämmerhirt Lisa L Völler Daniel D Meyer Katharina K Engelmann Julia C JC Spang Rainer R Eichner Norbert N Meister Gunter G Kuphal Silke S Bosserhoff Anja Katrin AK

Journal of clinical medicine 20210524 11

Malignant melanoma is one of the most dangerous tumor types due to its high metastasis rates and a steadily increasing incidence. During tumorigenesis, the molecular processes of embryonic development, exemplified by epithelial-mesenchymal transition (EMT), are often reactivated. For melanoma development, the exact molecular differences between melanoblasts, melanocytes, and melanoma cells are not completely understood. In this study, we aimed to identify microRNAs (miRNAs) that promote melanoma ...[more]

PMID: 34073664

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Project description:Purpose: We hypothesized that embryonic melanocytic pathways would be reinitiated in melanoma metatastasis. To identify nove melanoblast signaling pathways with which to explore our hypothesis we used the inducible Dct-GFP mouse model, in which GFP is expressed in both immature melanoblasts and mature melanocytes. Mouse melanoblasts/melanoytes were extracted using Fluorescence Activated Cell Sorting and transcriptomes were analyzed using RNA-sequencing. Abstract: Cutaneous malignant melanoma is an aggressive cancer of melanocytes with a strong propensity to metastasize. We posit that melanoma cells acquire metastatic capability by adopting an embryonic-like phenotype, and that a lineage approach would uncover novel metastatic melanoma biology. Using a genetically engineered mouse model to generate a rich melanoblast transcriptome dataset, we identify melanoblast-specific genes whose expression contribute to metastatic competence and derive a 43-gene signature that predicts patient survival. We identify a melanoblast gene, KDELR3, whose loss impairs experimental metastasis. In contrast, KDELR1 deficiency enhances metastasis, providing the first example of different disease etiologies within the KDELR-family of retrograde transporters. We show that KDELR3 regulates the metastasis suppressor, KAI1, and report an interaction with the E3 ubiquitin-protein ligase gp78, a regulator of KAI1 degradation. Our work demonstrates that the melanoblast transcriptome can be mined to uncover targetable pathways for melanoma therapy. Method: FVB/N iDct-GFP mice were used and doxycycline was administered to activate GFP expression. Multiple litters were used for each developmental stage, and embryos/pups from each stage were pooled to ensure adequate numbers of GFP+ cells. At E17.5, P1 and P7 stages, most melanocytes have reached the dermis, thus only the skin was collected from these developmental stages. Back skin was immersed in a shallow layer of 1X PBS and subcutaneous fat was scraped off until skin appeared translucent. E15.5 was the youngest age assessed due to the necessity to capture sufficient cells for RNA-sequencing. Embryos of the same developmental age that were heterozygous for the TRE-H2B-GFP gene but lacked the Dct-rtTA gene were used as negative controls. Cell doublets were excluded from the analysis. Cells were sorted based on GFP expression and SSC-A. Based on these reference sorts, gates were set so that background cells represented less than 10% of sorted cells. Cells were lysed in 10-fold TRIzol reagent (w/v), phases were separated by addition of 0.2X volume of chloroform, the aqueous phase was combined with an equal volume of 70% ethanol and applied to a RNeasy Micro column (Qiagen) and processed as per the manufacturer’s instructions. Paired-end sequencing libraries were prepared using 1 μg of purified RNA following the mRNA-Seq Sample Prep Kit according to the manufacturer’s instructions (Illumina). RNA-Seq libraries were sequenced on two lanes each of an Illumina GAIIx Genome Analyser to a minimum depth of 49 million reads. Sequence reads were aligned to the mm9 genome using the TopHat software (https://ccb.jhu.edu/software/tophat/index.shtml). Quantified Fragments Per Kilobase of transcript per Million mapped reads (FPKM) values were generated using the Cufflinks software (http://cole-trapnell-lab.github.io/cufflinks/). The UCSC KnownGenes gene models were used for guided alignment and quantification. Results: DESeq2 analysis identified melanoblast-specific gene expression, which was shown by further analyses using patient data and wet lab techniques to likewise be upregulated in metastatic melanoma and facilitate metastasis.

Project description:Somatic embryogenesis (SE), which resembles zygotic embryogenesis, is an essential component of the process of plant cell differentiation and embryo development. Although microRNAs (miRNAs) are important regulators of many plant develop- mental processes, their roles in SE have not been thoroughly investigated. In this study, we used deep-sequencing, computational, and qPCR methods to identify, profile, and describe conserved and novel miRNAs involved in longan (Dimocarpus longan) SE. A total of 643 conserved and 29 novel miRNAs (including star strands) from more than 169 miRNA families were identified in longan embryogenic tissue using Solexa sequencing. By combining computational and degradome sequencing approaches, we were able to predict 2063 targets of 272 miRNAs and verify 862 targets of 181 miRNAs. Target annotation revealed that the putative targets were involved in a broad variety of biological processes, including plant metabolism, signal transduction, and stimulus response. Analysis of stage- and tissue-specific expressions of 20 conserved and 4 novel miRNAs indicated their possible roles in longan SE. These miRNAs were dlo-miR156 family members and dlo-miR166c* associated with early embryonic culture developmental stages; dlo-miR26, dlo-miR160a, and families dlo-miR159, dlo-miR390, and dlo-miR398b related to heart-shaped and torpedo- shaped embryo formation; dlo-miR4a, dlo-miR24, dlo-miR167a, dlo-miR168a*, dlo-miR397a, dlo-miR398b.1, dlo-miR398b.2, dlo-miR808 and dlo-miR5077 involved in cotyledonary embryonic development; and dlo-miR17 and dlo-miR2089*-1 that have regulatory roles during longan SE. In addition, dlo-miR167a, dlo-miR808, and dlo-miR5077 may be required for mature embryo formation. This study is the first reported investigation of longan SE involving large-scale cloning, characterization, and expression profiling of miRNAs and their targets. The reported results contribute to our knowledge of somatic embryo miRNAs and provide insights into miRNA biogenesis and expression in plant somatic embryo development.

Dataset Information

Learning from Embryogenesis-A Comparative Expression Analysis in Melanoblast Differentiation and Tumorigenesis Reveals miRNAs Driving Melanoma Development.

Publications

Learning from Embryogenesis-A Comparative Expression Analysis in Melanoblast Differentiation and Tumorigenesis Reveals miRNAs Driving Melanoma Development.

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