Validation of an Epstein-Barr virus antibody risk stratification signature for nasopharyngeal carcinoma by use of multiplex serology - Simon, Julia; Liu, Zhiwei; Brenner, Nicole; Yu, Kelly J.; Hsu, Wan-Lun; Wang, Cheng-Ping; Chien, Yin-Chu; Coghill, Anna E.; Chen, Chien-Jen; Butt, Julia; Proietti, Carla; Doolan, Denise L.; et al. (Journal of clinical microbiology, 2020)
Serological testing for nasopharyngeal carcinoma (NPC) has recently been reinvigorated by the implementation of novel Epstein-Barr virus (EBV)-specific IgA and IgG antibodies from a proteome array. Although proteome arrays are well suited for comprehensive antigen selection, they are not applicable for large-scale studies. We adapted a 13-marker EBV antigen signature for NPC risk identified by proteome arrays to multiplex serology to establish an assay for large-scale studies. Taiwanese NPC cases (n = 175) and matched controls (n = 175) were used for assay validation. Spearman’s correlation was calculated, and the diagnostic value of all multiplex markers was assessed independently using the area under the receiver operating characteristic curve (AUC). Two refined signatures were identified using stepwise logistic regression and internally validated with 10-fold cross validation. Array and multiplex serology showed strong correlation for each individual EBV marker, as well as for a 13-marker combined model on continuous data. Two refined signatures with either four (LF2 and BGLF2 IgG, LF2 and BMRF1 IgA) or two (LF2 and BGLF2 IgG) antibodies on dichotomous data were identified as the most parsimonious set of serological markers able to distinguish NPC cases from controls with AUCs of 0.992 (95% confidence interval [CI], 0.983 to 1.000) and 0.984 (95% CI, 0.971 to 0.997), respectively. Neither differed significantly from the 13-marker model (AUC, 0.992; 95% CI, 0.982 to 1.000). All models were internally validated. Multiplex serology successfully validated the original EBV proteome microarray data. Two refined signatures of four and two antibodies were capable of detecting NPC with 99.2% and 98.4% accuracy.
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