Presentation Category
Other
Introduction/Context/Diagnosis
Oral squamous cell carcinoma (OSCC) is an aggressive cancer with a high mortality rate. Prognostic biomarkers from the tumor immune microenviroment (TIME) are needed to determine treatment plans. We hypothesized that imaging mass cytometry (IMC) would reveal distinct TIME characteristics associated with histopathological grades. A 40-plex IMC, covering markers for tumor structure, multiple immune cells, and their signaling activity, was used to investigate the TIMEs of formalin-fixed, paraffin-embedded (FFPE) incisional oral tongue biopsies. These biopsies were sourced from 24 OSCC patients at the University of the Pacific, Arthur A. Dugoni School of Dentistry, and contained 13 well-differentiated, 10 moderately differentiated, and one poorly differentiated histological graded samples. Spatial characteristics of the tumor core, front, and stroma were identified by spatial subsetting. A multivariable predictive model with 909 IMC features accurately classified tumor histological grades (AUC: 0.88). Spatial subsetting improved intrapatient and interpatient feature reproducibility. The top predictive immune features of higher histological grade were the smaller abundance and size of stromal CD4+ memory T cells and tumor-core CD8+ memory T cells, as well as decreased interactions between regulatory CD4+ T cells and non-poliferating tumor cells at the tumor front. This study establishes a robust modeling framework for distilling complex imaging data, classifying histological grades, and uncovering sentinel characteristics of the OSCC TIME to facilitate prognostic biomarker discovery.
Location
Arthur A Dugoni School of Dentistry, 155 5th St, San Francisco, CA 94103, USA
Format
Presentation
Classification of Immune Landscapes in Oral Squamous Cell Carcinoma
Arthur A Dugoni School of Dentistry, 155 5th St, San Francisco, CA 94103, USA
Oral squamous cell carcinoma (OSCC) is an aggressive cancer with a high mortality rate. Prognostic biomarkers from the tumor immune microenviroment (TIME) are needed to determine treatment plans. We hypothesized that imaging mass cytometry (IMC) would reveal distinct TIME characteristics associated with histopathological grades. A 40-plex IMC, covering markers for tumor structure, multiple immune cells, and their signaling activity, was used to investigate the TIMEs of formalin-fixed, paraffin-embedded (FFPE) incisional oral tongue biopsies. These biopsies were sourced from 24 OSCC patients at the University of the Pacific, Arthur A. Dugoni School of Dentistry, and contained 13 well-differentiated, 10 moderately differentiated, and one poorly differentiated histological graded samples. Spatial characteristics of the tumor core, front, and stroma were identified by spatial subsetting. A multivariable predictive model with 909 IMC features accurately classified tumor histological grades (AUC: 0.88). Spatial subsetting improved intrapatient and interpatient feature reproducibility. The top predictive immune features of higher histological grade were the smaller abundance and size of stromal CD4+ memory T cells and tumor-core CD8+ memory T cells, as well as decreased interactions between regulatory CD4+ T cells and non-poliferating tumor cells at the tumor front. This study establishes a robust modeling framework for distilling complex imaging data, classifying histological grades, and uncovering sentinel characteristics of the OSCC TIME to facilitate prognostic biomarker discovery.
Comments/Acknowledgements
Presentation Category: PIP: Bench or Clinical Research