A multiplex immunoassay of serum biomarkers for the detection of uveal melanoma

用于检测葡萄膜黑色素瘤的血清生物标志物的多重免疫测定

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作者:Jin Song, Shannath L Merbs, Lori J Sokoll, Daniel W Chan, Zhen Zhang

Background

Approximately 50% of uveal melanoma (UM) patients develop metastases preferentially in the liver leading to death within 15 months. Currently, there is no effective treatment for metastatic UM, in part because the tumor burden is typically high when liver metastases are detected through abnormal liver function tests (LFTs) or imaging studies. The use of LFTs

Conclusions

The multiplex immunoassay provides sufficient analytical performance to evaluate serum biomarkers that complement each other in detection of UM, and warrants further validation with a larger number of patient samples.

Methods

Magnetic bead-based multiplex immunoassays were developed for the selected serum biomarkers using a Bio-Plex 200 system. The dynamic ranges, lower limits of detection and quantification, cross-reactivity, and intra- and inter-assay precision were assessed. All proteins were analyzed in sera of 48 patients diagnosed with UM (14 metastatic, 9 disease-free (DF) ≥ 5 years, 25 unknown) and 36 healthy controls. The performance of the biomarkers was evaluated individually and in combination for their ability to detect UM.

Results

A 7-plex immunoassay of OPN, MIA, CEACAM-1, MIC-1, SPON1, POSTN and HSP27 was developed with negligible cross-reactivity, recovery of 84-105%, and intra-assay and inter-assay precision of 2.3-7.5% or 2.8-20.8%, respectively. Logistic regression identified a two-marker panel of HSP27 and OPN that significantly improved the individual biomarker performance in discriminating UM from healthy controls. The improved discrimination of a two-marker panel of MIA and MIC-1 was also observed between metastatic UM and DF, however not statistically significant due to the small sample size. Conclusions: The multiplex immunoassay provides sufficient analytical performance to evaluate serum biomarkers that complement each other in detection of UM, and warrants further validation with a larger number of patient samples.

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