期刊
FRONTIERS IN ONCOLOGY
卷 11, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2021.636681
关键词
melanoma; multiplex; single cell; digital pathology; spatial proteomics
类别
资金
- Leuven Kankerinstituut (LKI)
- Opening The Future (OTF) foundation
- Kom op tegen kanker (KOTK) foundation
In recent years, there has been a significant revolution in the field of melanoma treatment, transitioning from traditional chemotherapy to personalized molecular and immunological therapies, necessitating a deep understanding of the immune microenvironment and cellular composition for improving treatment efficacy. The introduction of single-cell profiling methods offers the potential to study the specific cellular structures and interactions within tumor tissues.
The state-of-the-art for melanoma treatment has recently witnessed an enormous revolution, evolving from a chemotherapeutic, one-drug-for-all approach, to a tailored molecular- and immunological-based approach with the potential to make personalized therapy a reality. Nevertheless, methods still have to improve a lot before these can reliably characterize all the tumoral features that make each patient unique. While the clinical introduction of next-generation sequencing has made it possible to match mutational profiles to specific targeted therapies, improving response rates to immunotherapy will similarly require a deep understanding of the immune microenvironment and the specific contribution of each component in a patient-specific way. Recent advancements in artificial intelligence and single-cell profiling of resected tumor samples are paving the way for this challenging task. In this review, we provide an overview of the state-of-the-art in artificial intelligence and multiplexed immunohistochemistry in pathology, and how these bear the potential to improve diagnostics and therapy matching in melanoma. A major asset of in-situ single-cell profiling methods is that these preserve the spatial distribution of the cells in the tissue, allowing researchers to not only determine the cellular composition of the tumoral microenvironment, but also study tissue sociology, making inferences about specific cell-cell interactions and visualizing distinctive cellular architectures - all features that have an impact on anti-tumoral response rates. Despite the many advantages, the introduction of these approaches requires the digitization of tissue slides and the development of standardized analysis pipelines which pose substantial challenges that need to be addressed before these can enter clinical routine.
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