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Currently prostate-specific antigen is used for prostate cancer (PCa) screening, however it lacks the necessary specificity for differentiating PCa from other diseases of the prostate such as benign prostatic hyperplasia (BPH), presenting a clinical need to distinguish these cases at the molecular level. Protein glycosylation plays an important role in a number of cellular processes involved in neoplastic progression and is aberrant in PCa. In this study, we systematically interrogate the alterations in the circulating levels of hundreds of serum proteins and their glycoforms in PCa and BPH samples using multi-lectin affinity chromatography and quantitative mass spectrometry-based proteomics. Specific lectins (AAL, PHA-L and PHA-E) were used to target and chromatographically separate core-fucosylated and highly-branched protein glycoforms for analysis, as differential expression of these glycan types have been previously associated with PCa. Global levels of CD5L, CFP, C8A, BST1, and C7 were significantly increased in the PCa samples. Notable glycoform-specific alterations between BPH and PCa were identified among proteins CD163, C4A, and ATRN in the PHA-L/E fraction and among C4BPB and AZGP1 glycoforms in the AAL fraction. Despite these modest differences, substantial similarities in glycoproteomic profiles were observed between PCa and BPH sera.

Background Quantitative proteomics allows for the discovery and functional investigation of blood-based pre-diagnostic biomarkers for early cancer detection. However, a major limitation of proteomic investigations in biomarker studies remains the biological and technical variability in the analysis of complex clinical samples. Moreover, unlike ‘omics analogues such as genomics and transcriptomics, proteomics has yet to achieve reproducibility and long-term stability on a unified technological platform. Few studies have thoroughly investigated protein variability in pre-diagnostic samples of cancer patients across multiple platforms. Methods We obtained ten blood plasma “case” samples collected up to 2 years prior to breast cancer diagnosis. Each case sample was paired with a matched control plasma from a full biological sister without breast cancer. We measured protein levels using both mass-spectrometry and antibody-based technologies to: (1) assess the technical considerations in different protein assays when analyzing limited clinical samples, and (2) evaluate the statistical power of potential diagnostic analytes. Results Although we found inherent technical variation in the three assays used, we detected protein dependent biological signal from the limited samples. The three assay types yielded 32 proteins with statistically significantly (p

Ongoing cancer genome characterization studies continue to elucidate the spectrum of genomic abnormalities that drive many cancers, and in the clinical arena assessment of the driver genetic alterations in patients is playing an increasingly important diagnostic and/or prognostic role for many cancer types. However, the landscape of genomic abnormalities is still unknown for less common cancers, and the influence of specific genotypes on clinical behavior is often still unclear. To address some of these deficiencies, we developed Profile, a prospective cohort study to obtain genomic information on all patients at a large tertiary care medical center for cancer-related care. We enrolled patients with any cancer diagnosis, and, for each patient (unselected for cancer site or type) we applied mass spectrometric genotyping (OncoMap) of 471 common recurrent mutations in 41 cancer-related genes. We report the results of the first 5000 patients, of which 26% exhibited potentially actionable somatic mutations. These observations indicate the utility of genotyping in advancing the field of precision oncology.

The ability to harness the power of next generation sequencing for characterizing the cancer genome would be extremely valuable to the cancer research community and ultimately improve diagnosis and individualized therapy. We present a targeted approach using massively parallel sequencing to simultaneously detect mutations, translocations and copy-number variations in archived clinical tumor specimen. Targeted sequencing was achieved by designing RNA baits to capture the exons of 504 genes with relevance to cancer. The bait set was augmented with specific intronic sequences to detect translocations often involved in cancer. The overall performance of the hybrid capture was improved by optimizing the tiling strategy of the baits. These improvements significantly shifted fragments with low or no-coverage closer to the overall mean, resulting in a more uniform coverage distribution. To validate the targeted gene panel we sequenced tumor samples harboring mutations, translocations and copy-number alterations that were previously identified by clinically approved assays. All the known alterations were confirmed with additional potentially actionable mutations. The ultimate goal of the targeted panel is to screen cancer patients quickly and economically allowing simultaneous detection of all common genomic alterations in the cancer genome. Citation Format: Paul Van Hummelen, Matthew Ducar, Robert T. Jones, Alina Raza, Ashwini Sunkavalli, Megan Hanna, Adri Mills, Ravali Adusumilli, Prateek Kumar, Laura Schubert, Marc Breneiser, Anna C. Cooley, Elizabeth Garcia, Lynette M. Scholl, Neal I. Lindeman, Nikhil Wagle, Levi Garraway, Kristian Cibulskis, Scott L. Carter, Michael Lawrence, Gad Getz, Matthew L. Meyerson, William C. Hahn, Laura E. MacConaill. Targeted sequencing to detect somatic mutations, translocations and copy-number variation in human tumors simultaneously. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 819. doi:10.1158/1538-7445.AM2013-819