Eight-gene ENE-related RNA signature stratifies metastasis risk and immune features in nasopharyngeal carcinoma

An RNA sequencing study of 159 patients with nasopharyngeal carcinoma developed an eight-gene, ENE-related machine-learning signature to predict distant metastasis risk. The model achieved a concordance index of 0.819 and an area under the receiver operating characteristic curve of 0.813 in the in-house cohort, while an external validation cohort produced an AUC of 0.762. The findings indicate predictive performance, but the abstract does not establish that use of the signature improves clinical decisions or patient outcomes.

The researchers stratified patients by extracapsular nodal extension, or ENE, and identified differentially expressed genes associated with that status. Risk groups defined by the resulting signature had distinct inferred immune microenvironment characteristics. Low-risk tumors had higher overall immune scores, greater inferred infiltration by CD8-positive T cells and B cells, and elevated expression of immune checkpoint genes such as CTLA4 and PDCD1. These measurements suggested a more immune-active phenotype in low-risk tumors, although the reported immune-cell values were inferred rather than directly measured in the analyzed patients.

An exploratory analysis of the IMvigor210 cohort found associations between the signature and immune checkpoint blockade response. The abstract did not provide the size, cancer composition or response findings from that analysis, and its relevance to nasopharyngeal carcinoma remains uncertain because the investigators stated that validation in nasopharyngeal carcinoma immunotherapy cohorts is still required. The study therefore links a metastasis-risk model with immune features and exploratory immunotherapy-response associations, rather than demonstrating that the signature can select effective treatment.

C19orf18 emerged as a candidate among the eight signature genes. Cell-based functional assays found that knocking down C19orf18 reduced the migratory and invasive capacities of nasopharyngeal carcinoma cells, while immunohistochemistry showed higher expression in tumor and metastatic tissues than in comparator tissue. These laboratory findings support further investigation of C19orf18 as a metastasis-associated biomarker, but they do not demonstrate a clinical benefit in patients. The available evidence is summarized here from the study abstract, which did not describe cohort characteristics beyond the 159 in-house patients, external validation details, uncertainty estimates or performance across additional validation cohorts.

Subject of Research: Transcriptomic prediction of distant metastasis risk and immune microenvironment features in nasopharyngeal carcinoma

Article Title: An ENE-related transcriptomic signature predicts distant metastasis risk and immune microenvironment features in nasopharyngeal carcinoma

Article References: Pan, J., Li, Y., Xu, S., Xu, W., Lin, C., Liu, W., Warsi, M. A., Chen, X., Chen, X., & Qiu, S. (2026). An ENE-related transcriptomic signature predicts distant metastasis risk and immune microenvironment features in nasopharyngeal carcinoma. BMC Cancer. https://doi.org/10.1186/s12885-026-16929-9

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16929-9

Keywords: nasopharyngeal carcinoma, extracapsular nodal extension, distant metastasis, RNA sequencing, gene signature, immune microenvironment, machine learning, C19orf18, tumor infiltration, immunotherapy response, ENE-related, transcriptomic