Abstract. Breast cancer is one of the most common types of invasive cancer in females worldwide. Despite major advances in early cancer detection and emerging therapeutic strategies, further improvement has to be achieved for precise diagnosis to reduce the chance of metastasis and relapses. Recent proteomic technologies have offered a promising opportunity for the identification of new breast cancer biomarkers. Matrix-assisted laser desorption/ionization, time-of-flight mass spectrometry (MALDI-TOF MS) and the derived surface-enhanced laser desorption/ionization mass spectrometry (SELDI-TOF MS) enable the development of high-throughput proteome analysis based on comprehensive reliable biomarkers. In this review, we examined proteomic technologies and their applications, and provided focus on the proteomics-based profiling analyses of tumor tissues/cells in order to identify and confirm novel biomarkers of breast cancer.

Ovarian cancer is the leading cause of gynecologic cancer death and the fifth leading cause of cancer death in North American women, primarily due to lack of early symptoms or effective screening. Early detection of ovarian cancer increases the 5-year survival rate from less than 30% to 70% - 90%, but less than 20% of cases are diagnosed early. Several early detection markers have been proposed, but to date all have failed validation. In order to discover novel serum markers, we performed a meta-analysis of 7 microarray data sets in the NCBI Gene Expression Omnibus (GEO), consisting of 396 samples. We identified 160 genes consistently overexpressed in ovarian cancer in these studies. We validated our results in an independent, high-quality cohort of 591 pre-treatment ovarian cancer patients and 8 controls available from The Cancer Genome Atlas (TCGA). In this cohort, our top 5 genes clearly separated cancer cases from controls (AUC = 0.954), better than the 5 genes encoding the proteins in the OVA1 panel approved for monitoring patients with a pelvic mass (AUC = 0.874). Including the top 13 genes identified by our analysis achieved an AUC of 0.985. We then used TCGA clinical and genomic data to prioritize our candidates. 80 of the 160 genes identified via meta-analysis were significantly overexpressed in the 46 stage I/II cases. Many of these genes were correlated with survival and a subset of cases had mutations in these genes. Of note, many genes with a role in ovarian cancer or recently proposed as potential biomarkers (including CA125, B7H4, KLK6, EPCAM, and MMP7) are detected by our meta-analysis but are not overexpressed in early stages. In a second independent cohort (GSE4122) consisting of 32 cases and 32 normal or benign controls, our top 3 early stage genes separated the cases and controls (AUC 0.92) better than the OVA1 genes (AUC = 0.76). We hypothesized that the mRNA changes identified via meta-analysis could point to their coded proteins as potential serum diagnostics. Proteins for 19 of the 80 early stage genes were identified in previous international serum/plasma proteome projects. We selected two of these, the kinase PRKDC and the DNA damage repair protein RAD54L, for pilot ELISA tests in the serum of 12 treatment-naïve ovarian cancer patients and 12 normal controls. Serum levels of PRKDC distinguished cancer from normal (p = .0055) at a magnitude and significance similar to proteins in the OVA1 panel. Serum levels of RAD54L identified 2 distinct subgroups of ovarian cancers, which may be useful for predicting response to chemotherapy or disease aggressiveness. In summary, using publicly available gene expression data, we have identified PRKDC as a novel serum protein biomarker for ovarian cancer that performs as well as current biomarkers. We are continuing to prioritize the remaining candidate genes for validation in order to create a biomarker panel that will enable more accurate early detection of the disease and thereby improve survival. Citation Format: Linda A. Szabo, Purvesh Khatri, Xiaodan Liu, Zhongkai Hu, Bruce Ling, Atul J. Butte. Identification of novel biomarkers for early detection of ovarian cancer. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr B20.