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Updated: Jul 30, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer
Edwin Roger Parra1, Jiexin Zhang2, Mei Jiang3
1Departments of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. erparra@mdanderson.org.
Abstract:
Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns-an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions.
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