Spatial Transcriptomic Profiling of Cutaneous Melanoma Progression
Xue, Gloria, Indiana University School of Medicine; Krish Jayarapu, Johns Hopkins University; Hongming Zhou, Department of Dermatology, Indiana University School of Medicine; Xiaoling Xuei, Departments of Medical and Molecular Genetics, Center for Medical Genomics, Indiana University School of Medicine; Hongyu Gao, Departments of Medical and Molecular Genetics, Center for Medical Genomics, Indiana University School of Medicine; Yunglong Liu, Departments of Medical and Molecular Genetics, Center for Medical Genomics, Biostatistics, BioHealth Informatics, Indiana University School of Medicine; Simon Warren, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine; Ahmed Alomari, Department of Pathology and Laboratory Medicine, Indiana University School of Medicine; Matthew J. Turner, Departments of Dermatology, Microbiology and Immunology, Indiana University School of Medicine, Richard L. Roudebush VA Medical Center
Background/Significance/Rationale: In 2022, an estimated 99,780 new melanomas will be diagnosed in the United States. As incidence rates continue to rise, identification of biomarkers for disease progression is urgently needed to prevent overdiagnosis and provide therapeutic targets. The purpose of this project was to determine if spatial transcriptomics can be used to identify transcript changes during melanoma progression.
Methods: For this study and after specimen quality control (via DV200 values), four archival formalin fixed paraffin embedded (FFPE) human melanoma specimens were processed using the Visium Spatial Gene Expression platform. In Loupe Browser v6.0.0. (10x Genomics Inc.), K-means clustering was used as an unbiased approach in addition to manual selection of areas of melanoma adjacent to and distant from (i.e. nonadjacent) the epidermis to determine regions of interest for identification of differentially expressed genes (DEGs).
Results/Findings: Expression of PAEP was significantly increased in a micrometastasis (~7.2 fold; Log2 scale) versus the primary melanoma in one specimen. Other DEGs also distinguished the micrometastasis (SLC16A3, CCND1, SCML4, and CSAG3) from this primary melanoma (S100A14, TRIM29, PTPRZ1, and BCAN). In the other specimens, a similar pattern of differential gene expression was seen between areas of melanoma adjacent to and nonadjacent to the epidermis. In addition, K-means clustering identified a region of differential gene expression suggestive of an inflammatory cell infiltrate next to the PAEP-enriched micrometastasis.
Conclusions/Discussion: This study demonstrates the feasibility of using spatial transcriptomics to investigate transcriptional changes during melanoma progression. Increased PAEP transcripts and the immunosuppressive functions of PAEP suggest PAEP may be an important mediator of melanoma progression. The current study suggests increased PAEP transcript levels are associated with inflammatory cell infiltrates.
Translational/Human Health Impact: Understanding mechanistic links between increased PAEP and inflammation during melanoma progression could provide prognostic and therapeutic insights and thus, improved care for melanoma patients.