Global proteome survey

The human proteome is highly complex. Despite recent advancement in mass spectrometry (MS) technologies, extensive sample fractionation is typically required to fully characterize the complex proteome derived from clinical samples such as tissue. To meet required sensitivity, dynamic range, resolution, and reproducibility, the group of Carl Borrebaeck developed a conceptually novel method, denoted global proteome survey (GPS) and apply this for biomarker discovery (1).

GPS applies especially for purpose recombinant single-chain variable antibody fragments (scFv) termed Context Independent Motif Specific (CIMS) antibodies that are designed to recognize short peptide motifs shared by many proteins. These are used for specific enrichment of a subset of peptides which are analyzed through mass spectrometry (MS) to generate a high-quality protein signature for molecular profiling.

Next generation GPS platform

We are now developing the next generation GPS platform to allow state-of-the-art sensitivity and specificity for multi-biomarker discovery through applying a wider range of CIMS antibodies and improved antibody immobilization strategies for more efficient peptide captures. This will be applied to demonstrate and validate the next generation GPS platform as a tool to identify treatment-response biomarker signatures in oncology patients, starting in breast cancer.

Breast cancer

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among women. Histological grading, one of the most commonly used prognostic factors, is a combined score based on the morphological and cytological features of tumor cells and reflects the aggressiveness of a tumor. This combined score is then used to stratify breast cancer tumors into grade 1, slow growing and well differentiated; grade 2, moderately differentiated; and grade 3, highly proliferative and poorly differentiated. The many (30% to 60%) tumors classified as histological grade 2 belongs to a heterogeneous patient cohort.  

Clinical data

The clinical value of histological grades for these patients has proven to be less informative for clinical decision making and many patients are overtreated or treated with a therapy that does not offer any benefits. We have in a previous study applied GPS analysis to breast cancer tumor analysis and defined a molecular signature for molecular grading (2).

We have recently improved the GPS technology and are now in the process to further advance the initial molecular signature to acquire a deeper molecular understanding of breast cancer biology and tumor progression, and contribute to individualize prognosis and treatment decisions using an objective, high-performing classifier.

References

1. Proteomic analysis and discovery using affinity proteomics and mass spectrometry. Olsson N, Wingren C, Mattsson M, James P, O'Connell D, Nilsson F, Cahill DJ, Borrebaeck CA. Mol Cell Proteomics. 2011 Oct;10(10)
2. Grading breast cancer tissues using molecular portraits. Olsson N, Carlsson P, James P, Hansson K, Waldemarson S, Malmström P, Fernö M, Ryden L, Wingren C, Borrebaeck CA. Mol Cell Proteomics. 2013 Dec;12(12)