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Spatially variant immune infiltration scoring in human cancer tissues.
Allam, Mayar; Hu, Thomas; Lee, Jeongjin; Aldrich, Jeffrey; Badve, Sunil S; Gökmen-Polar, Yesim; Bhave, Manali; Ramalingam, Suresh S; Schneider, Frank; Coskun, Ahmet F.
Afiliación
  • Allam M; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
  • Hu T; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
  • Lee J; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
  • Aldrich J; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
  • Badve SS; Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, GA, USA.
  • Gökmen-Polar Y; Winship Cancer Institute, Emory University, Atlanta, GA, USA.
  • Bhave M; Winship Cancer Institute, Emory University, Atlanta, GA, USA.
  • Ramalingam SS; Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
  • Schneider F; Winship Cancer Institute, Emory University, Atlanta, GA, USA.
  • Coskun AF; Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
NPJ Precis Oncol ; 6(1): 60, 2022 Sep 01.
Article en En | MEDLINE | ID: mdl-36050391
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: NPJ Precis Oncol Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: NPJ Precis Oncol Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido