Using protein microarray as a diagnostic assay for non-small cell lung cancer

Abstract

Rationale: Phenotypic and genotypic heterogeneity of lung cancer likely precludes the identification of a single predictive marker and suggests the importance of identifying and measuring multiple markers.

Objectives: We describe the use of a fluorescent protein microarray to identify and measure multiple non-small cell lung cancer-associated antibodies and show how simultaneous measurements can be combined into a single diagnostic assay.

Methods: T7 phage cDNA libraries of non-small cell lung cancer were first biopanned with plasma samples from normal subjects and patients with non-small cell lung cancer to enrich the component of tumor-associated proteins, and then applied to microarray slides. Two hundred twelve immunogenic phage-expressed proteins were identified from roughly 4,000 clones, using high-throughput screening with patient plasmas and assayed with 40 cancer and 41 normal plasma samples. Twenty patient and 21 normal plasma samples were randomly chosen and used for statistical determination of the predictive value of each putative marker. Statistical analysis identified antibody reactivity to seven unique phage-expressed proteins that were significantly different (p < 0.01) between patient and normal groups. The remaining 20 patient and 20 normal plasma samples were used as an independent test of the predictive ability of the selected markers.

Main results: Measurements of the 5 most predictive phage proteins were combined in a logistic regression model that achieved 90% sensitivity and 95% specificity in prediction of patient samples, whereas leave-one-out statistical analysis achieved 88.9% diagnostic accuracy among all 81 samples.

Conclusion: Our data indicate that antibody profiling is a promising approach that could achieve high diagnostic accuracy for non-small cell lung cancer.

Figure 1.

High-throughput screening of marker candidate phages. Biopanned phage clones were spotted on microarray slides and tested with NSCLC plasma samples. The partial array images show reactivity patterns for (A) normal and (B) patient samples, and the corresponding scatter plots show different distributions of reactive phage clones. The computer-generated regression line and standard deviation lines on the scatter plots assist in identifying candidate marker phages.

Figure 2.

Normalization of array data among chips. “Empty” T7 phage proteins were spotted as a standard control on the diagnostic chips. Open circles on the scatter plots in (A) show the T7 phages on two different chips. (B) Patterns of Cy5:Cy3 signal ratio distribution before normalization; (C) distribution after normalization to T7 proteins. (B and C) Triangles, normal subjects; circles, patients.