Abstract
Abstract Objectives: Obesity is associated with higher immunotherapy efficacy, but body mass index is a convoluted marker of adipose and muscle tissue. We conducted a discovery scale study to assess the association of skeletal muscle and adipose tissue areas annotated on computed tomography (CT) scan images with selected tumor immunologic characteristics among patients with non-small-cell lung cancer (NSCLC). Methods: We analyzed publicly available data from 102 patients (mean age = 67.2, 47.1% female, and 70.6% stage I-II) who had diagnostic CT images in The Cancer Image Archive. All patients had the 12th thoracic vertebra (T12) image, and a subset (62 patients) had the 3rd lumber vertebra (L3) image. Paravertebral muscle areas on T12 and skeletal muscle and adipose tissue areas on L3 were annotated using Slice-O-Matic. RNA-seq data were provided by The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium; percentages of CD8, regulatory T cells, and activated NK cells were identified using the CIBERSORT. ESTIMATE algorithm was used to derive the stromal score and the immune score. Differences in the immune markers were examined using ANOVA adjusting for stage, histology, and study. Results and Conclusion: Patients with higher paravertebral muscle area (3rd tertile) had the lowest stromal scores, compared to the 2nd and 1st tertile (P<0.05). Patients in the 2nd tertile of paravertebral muscle areas had the highest immune score and CD274 (PD-L1) gene expression. Among the body composition types classified using L3 images, low muscle/high adiposity was associated with lower stromal scores, and low muscle was associated with lower immune scores, compared to high adiposity and high muscle/low adiposity types. Other immunological markers did not differ across the body composition types. Significance: These findings suggest associations between deconvoluted skeletal and adipose tissue components and tumor markers relevant to immune checkpoint inhibitor efficacies in NSCLC. Further validation using immune phenotyping in a large patient sample is warranted. Funding: The study is in part supported by NIH/NCI R37CA248371 and OSU Comprehensive Cancer Center - James. Citation Format: Ting-Yuan David Cheng, Cuthbert Mario Mahenge, Rand T. Akasheh, Ayse Selen Yilmaz, Ben Kinder, Xuan Nguyen, Maciej Pietrzak, Carolyn J. Presley, Peter G. Shields. CT-assessed body composition and tumor immunologic characteristics in patients with non-small-cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3405.
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