A1 Refereed original research article in a scientific journal
Applying Single-Cell Technology in Uveal Melanomas: Current Trends and Perspectives for Improving Uveal Melanoma Metastasis Surveillance and Tumor Profiling
Authors: Wang Mona Meng, Chen Chuanfei F, Lynn Myoe Naing, Figueiredo Carlos Rogerio, Tan Wei Jian, Lim Tong Seng, Coupland Sarah E, Chan Anita Sook Yee
Publisher: FRONTIERS MEDIA SA
Publication year: 2021
Journal: Frontiers in Molecular Biosciences
Journal name in source: FRONTIERS IN MOLECULAR BIOSCIENCES
Journal acronym: FRONT MOL BIOSCI
Article number: ARTN 611584
Volume: 7
Number of pages: 10
DOI: https://doi.org/10.3389/fmolb.2020.611584(external)
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/53390986(external)
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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