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      Applying Single-Cell Technology in Uveal Melanomas: Current Trends and Perspectives for Improving Uveal Melanoma Metastasis Surveillance and Tumor Profiling

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          Abstract

          Uveal melanoma (UM) is the most common primary adult intraocular malignancy. This rare but devastating cancer causes vision loss and confers a poor survival rate due to distant metastases. Identifying clinical and molecular features that portend a metastatic risk is an important part of UM workup and prognostication. Current UM prognostication tools are based on determining the tumor size, gene expression profile, and chromosomal rearrangements. Although we can predict the risk of metastasis fairly accurately, we cannot obtain preclinical evidence of metastasis or identify biomarkers that might form the basis of targeted therapy. These gaps in UM research might be addressed by single-cell research. Indeed, single-cell technologies are being increasingly used to identify circulating tumor cells and profile transcriptomic signatures in single, drug-resistant tumor cells. Such advances have led to the identification of suitable biomarkers for targeted treatment. Here, we review the approaches used in cutaneous melanomas and other cancers to isolate single cells and profile them at the transcriptomic and/or genomic level. We discuss how these approaches might enhance our current approach to UM management and review the emerging data from single-cell analyses in UM.

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          Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq.

          To explore the distinct genotypic and phenotypic states of melanoma tumors, we applied single-cell RNA sequencing (RNA-seq) to 4645 single cells isolated from 19 patients, profiling malignant, immune, stromal, and endothelial cells. Malignant cells within the same tumor displayed transcriptional heterogeneity associated with the cell cycle, spatial context, and a drug-resistance program. In particular, all tumors harbored malignant cells from two distinct transcriptional cell states, such that tumors characterized by high levels of the MITF transcription factor also contained cells with low MITF and elevated levels of the AXL kinase. Single-cell analyses suggested distinct tumor microenvironmental patterns, including cell-to-cell interactions. Analysis of tumor-infiltrating T cells revealed exhaustion programs, their connection to T cell activation and clonal expansion, and their variability across patients. Overall, we begin to unravel the cellular ecosystem of tumors and how single-cell genomics offers insights with implications for both targeted and immune therapies.
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            The distribution of secondary growths in cancer of the breast. 1889.

            S. PAGET (1989)
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              Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer

              Single-cell transcriptome profiling of tumour tissue isolates allows the characterization of heterogeneous tumour cells along with neighbouring stromal and immune cells. Here we adopt this powerful approach to breast cancer and analyse 515 cells from 11 patients. Inferred copy number variations from the single-cell RNA-seq data separate carcinoma cells from non-cancer cells. At a single-cell resolution, carcinoma cells display common signatures within the tumour as well as intratumoral heterogeneity regarding breast cancer subtype and crucial cancer-related pathways. Most of the non-cancer cells are immune cells, with three distinct clusters of T lymphocytes, B lymphocytes and macrophages. T lymphocytes and macrophages both display immunosuppressive characteristics: T cells with a regulatory or an exhausted phenotype and macrophages with an M2 phenotype. These results illustrate that the breast cancer transcriptome has a wide range of intratumoral heterogeneity, which is shaped by the tumour cells and immune cells in the surrounding microenvironment.
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                Author and article information

                Contributors
                Journal
                Front Mol Biosci
                Front Mol Biosci
                Front. Mol. Biosci.
                Frontiers in Molecular Biosciences
                Frontiers Media S.A.
                2296-889X
                06 January 2021
                2020
                : 7
                : 611584
                Affiliations
                [1] 1Singapore National Eye Centre and Singapore Eye Research Institute , Singapore, Singapore
                [2] 2Cytogenetics Laboratory, Department of Molecular Pathology, Singapore General Hospital , Singapore, Singapore
                [3] 3MediCity Research Laboratory and Institute of Biomedicine, University of Turku , Turku, Finland
                [4] 4A. Menarini Biomarkers Singapore Pte Ltd , Singapore, Singapore
                [5] 5Department of Molecular and Clinical Cancer Medicine, ITM, University of Liverpool , Liverpool, United Kingdom
                [6] 6Liverpool Clinical Laboratories, Royal Liverpool University Hospital , Liverpool, United Kingdom
                [7] 7Duke-Nus Medical School , Singapore, Singapore
                Author notes

                Edited by: Abhijit De, Tata Memorial Hospital, India

                Reviewed by: Mizue Terai, Thomas Jefferson University, United States; Amit Kumar Pandey, Amity University Gurgaon, India

                *Correspondence: Anita Sook Yee Chan anita.chan.s.y@ 123456singhealth.com.sg

                This article was submitted to Molecular Diagnostics and Therapeutics, a section of the journal Frontiers in Molecular Biosciences

                Article
                10.3389/fmolb.2020.611584
                7874218
                33585560
                a80afe25-d095-4f67-bfcc-c2b2536e4e6e
                Copyright © 2021 Wang, Chen, Lynn, Figueiredo, Tan, Lim, Coupland and Chan.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 September 2020
                : 25 November 2020
                Page count
                Figures: 1, Tables: 1, Equations: 0, References: 97, Pages: 10, Words: 8768
                Categories
                Molecular Biosciences
                Perspective

                uveal melanoma,single-cell analysis,deparray nxt technology,cellsearch,circulating tumor cells,ffpe,melanoma prognostication,melanoma surveillance

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