ReviewFrontiers in oncology2021
Multiplexed Immunohistochemistry and Digital Pathology as the Foundation for Next-Generation Pathology in Melanoma: Methodological Comparison and Future Clinical Applications.
Review in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Research progress and perspectives on the application of tyramide signal amplification-based multiplex immunohistochemistry/immunofluorescence: a bibliometrics analysis.Frontiers in oncology · 2024Pooled it
- Label-Efficient Deep Color Deconvolution of Brightfield Multiplex IHC Images.IEEE transactions on medical imaging · 2026Article
- From Slide to Insight: The Emerging Alliance of Digital Pathology and AI in Melanoma Diagnostics.Cancers · 2025Review
- Enhanced patient selection with quantitative continuous scoring of PD-L1 expression for IO treatment in metastatic NSCLC.NPJ precision oncology · 2025Article
- Spatial Transcriptomics in Inflammatory Skin Diseases Using GeoMx Digital Spatial Profiling: A Practical Guide for Applications in Dermatology.JID innovations : skin science from molecules to population health · 2025Article
- Immunogenomic characteristics and prognostic implications of terminally exhausted CD8Frontiers in immunology · 2025Article
- Scoping Review: Methods and Applications of Spatial Transcriptomics in Tumor Research.Cancers · 2024Article
- The Role of Artificial Intelligence in Early Diagnosis and Molecular Classification of Head and Neck Skin Cancers: A Multidisciplinary Approach.Diagnostics (Basel, Switzerland) · 2024Review
- Revolutionizing Pathology with Artificial Intelligence: Innovations in Immunohistochemistry.Journal of personalized medicine · 2024Review
- Advancing Precision Medicine: Algebraic Topology and Differential Geometry in Radiology and Computational Pathology.Laboratory investigation; a journal of technical methods and pathology · 2024Review
- Integrating Spatial and Morphological Characteristics into Melanoma Prognosis: A Computational Approach.Cancers · 2024Article
- Redefining clinical practice through spatial profiling: a revolution in tissue analysis.Annals of the Royal College of Surgeons of England · 2024Article
- Machine-learning-based image analysis algorithms improve interpathologist concordance when scoring PD-L1 expression in non-small-cell lung cancer.Journal of clinical pathology · 2024Article
- Heterogeneity of the tumor immune microenvironment and clinical interventions.Frontiers of medicine · 2023Review
- Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images.Proceedings of machine learning research · 2023Article
- Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.NPJ precision oncology · 2023Article
- Generating immunogenomic data-guided virtual patients using a QSP model to predict response of advanced NSCLC to PD-L1 inhibition.bioRxiv : the preprint server for biology · 2023Article
- High-Plex Spatial Profiling of RNA and Protein Using Digital Spatial Profiler.Methods in molecular biology (Clifton, N.J.) · 2023Article
- The promise and challenge of spatial omics in dissecting tumour microenvironment and the role of AI.Frontiers in oncology · 2023Review
- Bright-Field Multiplex Immunohistochemistry Assay for Tumor Microenvironment Evaluation in Melanoma Tissues.Cancers · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.