Poster #39 - Sameen S. Hossain

Characterizing Cellular Heterogeneity and Spatial Organization in Lung Adenocarcinoma with Visium HD

Sameen S. Hossain, School of Life Sciences and Sustainability, CHS, VCU; The Honors College, VCU Katarzyna M. Tyc, PhD, Department of Biostatistics, SOPH, VCU; Massey BISR

Spatial transcriptomics is an emerging technology that enables the profiling of gene expression while preserving the spatial context of cells within intact tissue sections. This approach offers unprecedented insights into tissue architecture and cellular neighborhoods, critical for understanding disease mechanisms and identifying clinically relevant biomarkers. Visium HD, a high-resolution spatial transcriptomics platform developed by 10x Genomics, allows for detailed transcriptome mapping across diverse tissue types. In this study, we use the R package Seurat and establish a streamlined, best-practice workflow for analyzing high-resolution Visium HD data using the Seurat framework. We apply this pipeline to a human lung adenocarcinoma dataset, the most prevalent form of non-small cell lung cancer in the United States. We map tumor and immune cell populations within the microenvironment and highlight the utility of spatial methods for cancer research and precision medicine. Briefly, we identify thirteen distinct clusters representing tumor cells, immune infiltrates, and stromal components. Malignant clusters showed retention of alveolar type 2 (AT2)-like features, marked by NAPSA and CEACAM5 expression, while tumor-associated macrophages (TAMs) and tumor-infiltrating plasma cells (TIPCs) were spatially localized within separate areas of the tumor microenvironment. Endothelial cells exhibiting vascular activation were also identified, suggesting ongoing angiogenic and inflammatory processes. Our integration of spatial gene expression with cell-type annotation reveals complex tissue organization and reveals molecular markers defining functionally relevant subpopulations. Further analysis of cell-cell communication will enhance understanding of tumor-immune crosstalk and therapeutic targets. We plan to apply single-cell segmentation to achieve more precise biomarker mapping and to delineate the spatial organization of immune populations in relation to CNA-defined tumor subclones. By focusing on topography of TAMs and TIPCs, we aim to uncover how their spatial interactions drive lung adenocarcinoma progression. Ultimately, such efforts will guide the rational design of spatially informed, targeted therapeutic strategies.