Spatially variant immune infiltration scoring in human cancer tissues

• Type of Material: Article
• Authors: Mayar Allam, Georgia Institute of Technology; Thomas Hu, Georgia Institute of Technology; Jeongjin Lee, Georgia Institute of Technology; Jefferey Aldrich, Emory University; Sunil Badve, Emory University; Yesim Gökmen-Polar, Emory University; Manali Bhave, Emory University; Suresh Ramalingam, Emory University; Frank Schneider, Emory University; Ahmet F Coskun, Georgia Institute of Technology
• Language: English
• Date: 2022-09-01
• Publisher: NATURE PORTFOLIO
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2022
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1038/s41698-022-00305-4
• Title of Journal or Parent Work: NPJ PRECISION ONCOLOGY
• Volume: 6
• Issue: 1
• Start Page: 60
• End Page: 60
• Keywords: CELLS; PROGRESSION; Science & Technology; TUMOR; Oncology; Life Sciences & Biomedicine
• Research Categories: Health Sciences, Oncology; Engineering, Biomedical

Abstract

The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues.