Autoantibodies as potential biomarkers for breast cancer

Li Zhong¹^,2^,3 , Kun Ge¹ , Jin-chi Zu⁴ , Long-hua Zhao⁵ , Wei-ke Shen¹ , Jian-fei Wang¹ , Xiao-gang Zhang¹ , Xu Gao⁶ , Wanping Hu⁷ , Yun Yen² and Kemp H Kernstine³

¹Department of Molecular Biology, Hebei University College of Life Sciences, 180 Wusi Road, Baoding 071002, China

²Department of Clinical and Molecular Pharmacology, City of Hope and Beckman Research Institute, 1500 Duarte Road, Duarte, CA 91010, USA

³Thoracic Surgery & Lung Cancer Program, City of Hope and Beckman Research Institute, 1500 Duarte Road, Duarte, CA 91010, USA

⁴Department of Thoracic Surgery, Hebei University Affiliated Hospital, 320 Yuhua Road, Baoding 071000, China

⁵Teaching and Research Department, China University of Geosciences, Great Wall College, 1698 S. Second Circle Road, Baoding 071001, China

⁶Human Biology Program, Michigan State University College of Natural Science, 103 Natural Science Building, East Lansing, MI 48824, USA

⁷Hematology and Oncology, Kaiser Permanente Health Care, 2295 S. Vineyard, Ontario, CA 91761, USA

author email corresponding author email

Breast Cancer Research 2008, 10:R40doi:10.1186/bcr2091


Published:	7 May 2008

Abstract

Introduction

Only a limited number of tumor markers for breast cancer are currently available. Antibodies to tumor-associated proteins may expand the number of available tumor markers for breast cancer and may be used together in a serum profile to enhance sensitivity and specificity.

Methods

In the present study, we interrogated a breast cancer cDNA T7 phage library for tumor-associated proteins using biopan enrichment techniques with sera from normal individuals and from breast cancer patients. The enrichment of tumor-associated proteins after biopanning was tested using a plaque-lift assay and immunochemical detection. The putative tumor-associated phage clones were collected for PCR and sequencing analysis. Unique and open reading frame phage-expressed proteins were then used to develop phage protein ELISAs to measure corresponding autoantibodies using 87 breast cancer patients and 87 normal serum samples. A logistic regression model and leave-one-out validation were used to evaluate predictive accuracies with a single marker as well as with combined markers. Identities of those selected proteins were revealed through the sequence BLAST program.

Results

We harvested 100 putative tumor-associated phage clones after biopan enrichment. Sequencing analysis revealed that six phage proteins were inframe and unique. Antibodies to these six phage-expressed proteins were measured by ELISAs, and the results showed that three of the phage clones had statistical significance in discriminating patients from normal individuals. BLAST results of the three proteins showed great matches to ASB-9, SERAC1, and RELT. Measurements of the three predictive phage proteins were combined in a logistic regression model that achieved 80% sensitivity and 100% specificity in prediction of sample status, whereas leave-one-out validation achieved 77.0% sensitivity and 82.8% specificity among 87 patient samples and 87 control samples. Receiver operating characteristic curve analysis and the leave-one-out method both showed that combined measurements of the three antibodies were more predictive of disease than any of the single antibodies studied, underscoring the importance of identifying multiple potential markers.

Conclusion

Serum autoantibody profiling is a promising approach for early detection and diagnosis of breast cancer. Rather than one autoantibody, a panel of autoantibodies appears preferable to achieve superior accuracy. Further refinements will need to be made to further improve the accuracy. Once refined, the assay must be applied to a prospective patient population to demonstrate applicability.