Research Papers:

Quantitative screening of serum protein biomarkers by reverse phase protein arrays

Zhizhou Kuang, Ruochun Huang, Zhimin Yang, Zhiqiang Lv, Xinyan Chen, Fuping Xu, Yu-Hua Yi, Jian Wu and Ruo-Pan Huang _

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Oncotarget. 2018; 9:32624-32641. https://doi.org/10.18632/oncotarget.25976

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Zhizhou Kuang1,2, Ruochun Huang1,2, Zhimin Yang3,4, Zhiqiang Lv1, Xinyan Chen3,4, Fuping Xu3,4, Yu-Hua Yi1,6, Jian Wu5 and Ruo-Pan Huang1,2,6

1RayBiotech Inc, Guangzhou, China

2RayBiotech Inc, Parkway Lane, Norcross, GA, USA

3Guangdong Provincial Academy of Chinese Medical Sciences, Guangzhou, China

4Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China

5The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

6South China Biochip Research Center, Guangzhou, China

Correspondence to:

Ruo-Pan Huang, email: [email protected]

Keywords: reverse phase protein array; biomarker screening; serum protein; hepatocellular carcinoma

Received: January 24, 2018     Accepted: May 19, 2018     Published: August 24, 2018


Screening biomarkers in serum samples for different diseases has always been of great interest because it presents an early, reliable, and, most importantly, noninvasive means of diagnosis and prognosis. Reverse phase protein arrays (RPPAs) are a high-throughput platform that can measure single or limited sets of proteins from thousands of patients' samples in parallel. They have been widely used for detection of signaling molecules involved in diseases, especially cancers, and related regulation pathways in cell lysates. However, this approach has been difficult to adapt to serum samples. Previously, we developed a sensitive method called the enhanced protein array to quantitatively measure serum protein levels from large numbers of patient samples. Here, we further refine the technology on several fronts: 1. simplifying the experimental procedure; 2. optimizing multiple parameters to make the assay more robust, including the support matrix, signal reporting method, background control, and antibody validation; and 3. establishing a method for more accurate quantification. Using this technology, we quantitatively measured the expression levels of 10 proteins: alpha-fetoprotein (AFP), beta 2 microglobulin (B2M), Carcinoma Antigen 15-3(CA15-3), Carcinoembryonic antigen (CEA), golgi protein 73 (GP73), Growth differentiation factor 15 (GDF15), Human Epididymis Protein 4 (HE4), Insulin Like Growth Factor Binding Protein 2 (IGFBP2), osteopontin (OPN) and Beta-type platelet-derived growth factor receptor (PDGFRB) from serum samples of 132 hepatocellular carcinoma (HCC) patients and 78 healthy volunteers. We found that 6 protein expression levels are significantly increased in HCC patients. Statistical and bioinformatical analysis has revealed decent accuracy rates of individual proteins, ranging from 0.617 (B2M) to 0.908 (AFP) as diagnostic biomarkers to distinguish HCC from healthy controls. The combination of these 6 proteins as a specific HCC signature yielded a higher accuracy of 0.923 using linear discriminant analysis (LDA), logistic regression (LR), random forest (RF) and support vector machine (SVM) predictive model analyses. Our work reveals promise for using reverse phase protein arrays for biomarker discovery and validation in serum samples.

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