Whole-exome sequencing association study reveals genetic effects on tumor microenvironment components in nasopharyngeal carcinoma
Yanni Zeng, … , Yi-Xin Zeng, Jin-Xin Bei
Yanni Zeng, … , Yi-Xin Zeng, Jin-Xin Bei
Published January 2, 2025
Citation Information: J Clin Invest. 2025;135(1):e182768. https://doi.org/10.1172/JCI182768.
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Research Article Genetics Oncology

Whole-exome sequencing association study reveals genetic effects on tumor microenvironment components in nasopharyngeal carcinoma

Abstract

Nasopharyngeal carcinoma (NPC) presents a substantial clinical challenge due to the limited understanding of its genetic underpinnings. Here we conduct the largest scale whole-exome sequencing association study of NPC to date, encompassing 6,969 NPC cases and 7,100 controls. We unveil 3 germline genetic variants linked to NPC susceptibility: a common rs2276868 in RPL14, a rare rs5361 in SELE, and a common rs1050462 in HLA-B. We also underscore the critical impact of rare genetic variants on NPC heritability and introduce a refined composite polygenic risk score (rcPRS), which outperforms existing models in predicting NPC risk. Importantly, we reveal that the polygenic risk for NPC is mediated by EBV infection status. Utilizing a comprehensive multiomics approach that integrates both bulk-transcriptomic (n = 356) and single-cell RNA sequencing (n = 56) data with experimental validations, we demonstrate that the RPL14 variant modulates the EBV life cycle and NPC pathogenesis. Furthermore, our data indicate that the SELE variant contributes to modifying endothelial cell function, thereby facilitating NPC progression. Collectively, our study provides crucial insights into the intricate genetic architecture of NPC, spotlighting the vital interplay between genetic variations and tumor microenvironment components, including EBV and endothelial cells, in predisposing to NPC. This study opens new avenues for advancements in personalized risk assessments, early diagnosis, and targeted therapies for NPC.

Authors

Yanni Zeng, Chun-Ling Luo, Guo-Wang Lin, Fugui Li, Xiaomeng Bai, Josephine Mun-Yee Ko, Lei Xiong, Yang Liu, Shuai He, Jia-Xin Jiang, Wen-Xin Yan, Enya Hui Wen Ong, Zheng Li, Ya-Qing Zhou, Yun-He Zhou, An-Yi Xu, Shu-Qiang Liu, Yun-Miao Guo, Jie-Rong Chen, Xi-Xi Cheng, Yu-Lu Cao, Xia Yu, Biaohua Wu, Pan-Pan Wei, Zhao-Hui Ruan, Qiu-Yan Chen, Lin-Quan Tang, James D. McKay, Wei-Hua Jia, Hai-Qiang Mai, Soon Thye Lim, Jian-Jun Liu, Dong-Xin Lin, Chiea Chuen Khor, Melvin Lee Kiang Chua, Mingfang Ji, Maria Li Lung, Yi-Xin Zeng, Jin-Xin Bei

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Figure 7

Tumor-suppressive function of RPL14 in NPC.

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Tumor-suppressive function of RPL14 in NPC. (A) Western blot analysis sh...
(A) Western blot analysis showing RPL14 protein levels in NPC cells infected with RPL14 overexpressing lentivirus. Actin serves as the loading control. (B) Cell growth curves of the cells described in A. (C) Colony formation assay for the cells described in A. Corresponding statistical analysis is shown below. (D) Transwell migration assay evaluating the migration ability of the cells described in A. Scale bar: 50 μm. The statistical analysis is presented on the right. (E–H) Tumor growth evaluation in a nude mouse model with subcutaneous injection of CNE2-EBV cells described in A. Tumor volumes were measured every 3 days. Visual presentation of tumor after sacrifice (F) and weight (G) were presented. IF detection of Ki-67 expression (H) in the tumors described in F, and the corresponding statistical analysis is shown on the right. Scale bar: 50 μm. (I) Transcriptomic analysis showcasing mRNA levels of RPL14 in NPC (n = 87) versus control samples (n = 10). (J) Kaplan-Meier survival curve and Cox’s regression analyses linking RPL14 expression to overall survival (OS) of NPC patients in the Chen et al. cohort (n = 150). RPL14 expression levels were adjusted using EPCAM expression to account for the epithelial cell proportion in tumor tissue and subsequently scaled to a mean of 0 and a variance of 1. P(Cox) and HR(Cox) represent the P value and hazard ratio for the effect of RPL14 expression on OS in the Cox-regression model, adjusting age and sex. 95%CI: 95% confidence interval. P(log-rank): P value from the log-rank test comparing 2 groups with high (red) versus low (blue) RPL14 expression, determined by the median in the Kaplan-Meier analysis. Statistical method for between-group comparisons: t test. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.