Abstract 1106: RNA-based risk model for nasopharyngeal carcinoma distant metastasis
Authors: Zhaozheng Hou, Ping Feng, Kazi Anisha Islam, Songran Liu, Ying Wang, Yingpei Zhang, Michael King-yung Chung, Ngar-Woon Kam, Zi-Lu Huang, Victor Ho-Fun Lee, Anne WM Lee, Dora LW Kwong, Wai-Tong Ng, Yun-Fei Xia, Wei Dai
Journal: Cancer Research (2025)

Abstract Background: With advancements in the treatment of nasopharyngeal carcinoma (NPC), the five-year relative survival rate for patients has the potential to reach upwards of 90%. However, patients who develop distant metastases after receiving primary treatment suffer from a significantly reduced survival rate. Method: We analyzed bulk-RNA sequencing of primary NPC biopsies and clinical characteristics from 177 patients across multiple centers. We established a prediction model for distant metastasis and patient stratification in NPC. Patients diagnosed with NPC at four Hong Kong hospitals (Queen Mary, Queen Elizabeth, Princess Margaret, and Pamela Youde Nethersole Eastern Hospitals) and at Sun Yat-sen University Cancer Center in Guangzhou were selected. Metastatic NPC (MET-NPC) patients were defined as those who developed distant metastasis within three years after standard treatment, while other patients were grouped into non-metastatic NPC (nonMET-NPC). We evaluated the prediction accuracy using the area under the curve (AUC) index with two-way cross-cohort validation and applied Pareto optimization to select the final models. Histological analysis was applied to evaluate the number of Tertiary Lymphoid Structures (TLS) formation in NPC clinical tissues. Results: Our RNA-based risk score for NPC distant metastasis prediction significantly improved the AUC to 90.4% when combined with a model based on known and identified prognostic clinical parameters including TNM stage, body-mass-index, and plasma EBV DNA level. Pathway-level analysis indicated that the benefit of the proposed risk score might derive from its correlation with the development and activities of B cells and T helper 17 (Th17) cells in the tumor microenvironment, which are highly linked to TLS formation. Multiplex IHC staining further confirmed that the number of TLS was highly correlated with the RNA-based risk score and this number was significantly reduced in MET-NPC. Conclusions: This study effectively improves the accuracy of NPC metastasis prediction and introduces a new perspective for understanding and forecasting metastasis. We highlighted the potential association of immunosuppression characterized by dysregulated B cell and Th17 function, along with reduced TLS formation, with metastasis. This encourages future studies on understanding how NPC interacts with its tumor immune microenvironment to contribute to metastasis. Acknowledgements: This work was supported by General Research Fund (17102619) and Theme-based Research Scheme (T12-703/22-R; T123-70323-N) from Research Grant Council, and Health and Medical Research Grant from Health Bureau (08192296) from Hong Kong (SAR), P. R. China, Science and Technology Program of Guangdong Province in China (2021A0505110010). Citation Format: Zhaozheng Hou, Ping Feng, Kazi Anisha Islam, Songran Liu, Ying Wang, Yingpei Zhang, Michael King-yung Chung, Ngar-Woon Kam, Zi-Lu Huang, Victor Ho-Fun Lee, Anne WM Lee, Dora LW Kwong, Wai-Tong Ng, Yun-Fei Xia, Wei Dai. RNA-based risk model for nasopharyngeal carcinoma distant metastasis [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 1106.