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Abstract
Abstract Natural killer (NK) cell-based immunotherapy has demonstrated promising anti-tumor efficacy and safety in multiple early clinical trials against hematological and solid tumors. However, intrinsic NK resistance in tumors has resulted in a variable response to adoptively transferred NK cells. To enhance the treatment efficacy, a personalized approach must be adopted. Current methods for screening NK cell sensitive tumors using transcriptomic or proteomic techniques can be costly and often biased by the limited markers detected. Studies showed that cancer cells undergoing the process of epithelial mesenchymal transition (EMT) increase their vulnerability to NK mediated cytotoxicity. We hypothesize that by utilizing image-based analysis to quantify EM morphology change we can correlate EMT morphology with NK cell sensitivity. To analyze EM morphology, we trained a machine learning model based on cell morphological features using the A549 cell line treated with transforming growth factor-β (TGF- β), which depicts various cell morphology across the EMT spectrum. We optimized an organelle specific and live cell compatible staining panel that targets the nucleus, nucleic acid, cell membrane, and F-actin, which does not rely on antigen presentation. The images were processed via a Cell Painting cell segmentation and feature extraction pipeline. In parallel, we conducted a NK cell cytotoxicity assay on cells undergoing the same treatments and confirmed the EMT status via transcriptomic analysis. Our machine learning model successfully identified the EM status of A549 cells treated with TGF- β for different durations (0, 24, 48, and 72 hours) by assigning each cancer cell a quantitative EM score (zero be most epithelial and one be most mesenchymal). We identified a correlative trend between higher EM scores and increased NK cell sensitivity. The same trend was observed when we evaluated the workflow on various non-small lung cancer (NSCLC) cell lines, including two in-house patient derived CTC cell lines. In conclusion, we have established a quantitative measurement for EM status in NSCLC cancer cell lines and observed a correlation between EM score and NK cell sensitivity. We will extend this work by transferring our EM score model to process clinic patient tumor samples, paving the way for developing a rapid screening method for personalized NK cell therapy. Citation Format: Yin Zou, Harrison Ball, Yuru Chen, Nithya Ramnath, Venkateshwar Keshamouni, Sunitha Nagrath. Correlation between natural killer cell sensitivity and epithelial mesenchymal transition morphology: A cell morphology based screening for NK cell susceptible tumor cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3688.
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