How else can we approach prostate cancer biomarker discovery

The need continues for new prostate cancer (PCa) biomarkers for use in early detection, recurrence and metastatic disease diagnostics, therapeutic monitoring, and prediction of treatment benefit. As the urology, radiology and oncology disciplines continue to evaluate how to minimize the overdiagnosis and overtreatment associated with current prostate specific antigen (PSA) serum tests [1], there has been significant emphasis placed on multiparametric magnetic resonance imaging (mpMRI) based detection of clinically significant PCa. It is used for multiple indications including stratification of patients into low, intermediate, and high risk groups that guide treatment regimens from active surveillance to radical prostatectomy. Although an important step forward, inherent limitations with the use of MR in the detection of clinically significant cancer are still present and contribute to both false positives and false negatives [2]. Therefore optimizing tissue biomarker discovery that can be used as “ground truth” for further optimization of clinical imaging protocols represents a significant unmet need in the field. As a potential alternative, genomic-based liquid biopsy targets of cell free DNA (cfDNA) and circulating tumor cells (CTC) have emerged [3]. A recent consensus report of clinical experts in circulating prostate cancer biomarkers highlights these needs, especially in regards to developing biomarkers for treatment decisions, efficacy and metastasis [4]. These opinions were all based on developing genomic-based cfDNA and CTC assays. Genomics-based classification and risk stratification have made great strides, but many limitations still exist due to the continued interpretation of complex genomic data, its relation to impact on clinical outcomes, and not every mutation may be clinically actionable. Therefore, employing complementary research strategies to better clarify the functional readout of the cancer genome, i.e, how pathways downstream of genome regulation enhance tumorigenesis, may lead to new approaches for diagnosis and treatment for advanced PCa, as well as new biomarker targets. One well-known functional readout of the cancer genome is metabolism. Carbohydrate, or sugar, metabolism, specifically glucose, has been documented as a hallmark of tumorigenesis that enhances cell energetics (e.g. ATP synthesis) and biosynthetic processes (e.g. nucleotide and amino acid synthesis) [5]. This provides the basis of fluorodeoxyglucose positron emission tomographic (FDG-PET) imaging where tumor FDG uptake inversely correlates with survival in numerous cancers, including prostate cancer [6]. However, carbohydrates also can be incorporated into multiple types of complex carbohydrate structures that comprise the cell surface glycocalyx. These glycans are represented by N-linked and O-linked glycoproteins, glycosphingolipids, and glycosaminoglycans attached to proteoglycans and can interact with multiple extracellular matrix (ECM) proteins in the stroma, many of which are also glycosylated, as well various cell types including the immune system [7]. The role of the stroma in promoting and supporting cancer progression is a major area of cancer research, including PCa. Malignant transformation of the ECM disrupts the homeostatic tissue microenvironment, altering tissue processes of adhesion, cell death, migration, and proliferation to promote tumor growth [8]. Overall, targeting carbohydrate utilization as a functional end-product of metabolism, combined with targeted analysis of ECM constituents, could lead to novel diagnostic and therapeutic biomarkers of PCa across the clinical spectrum of the disease. Herein, we propose a strategy for PCa biomarker discovery in tissues, that spatially registers tissue glycosylation and protein expression of tumor, ECM, and immune components by merging matrix assisted laser desorption ionization (MALDI) imaging mass spectrometry and clinical prostate multiparametric magnetic resonance imaging (mpMRI). Specifically, MRI scans that are performed prior to prostatectomy are used to generate histologic 3D printed molds that are used to section the prostate in the same orientation as the MRI scan [9]. This allows for the coregistration of MRI imaging biomarkers and histology. Once the tumor tissue is sectioned by the pathologist using these molds, it is formalin fixed and paraffin embedded. Molecular MALDI imaging mass spectrometry of glycans and ECM proteins from the same patient tissues are then performed on unstained slides that directly correspond to the clinical imaging slices (see Figure 1). Open in a separate window Figure 1. An integrated three dimensional multimodality work flow to evaluate new glycomic and extracellular matrix biomarker candidates for prostate cancer. A. Representative pre-prostatectomy MRI images for T2W (T2 Weighted Image) and DWI (Diffusion-weighted image). B. A representative 3D-mold from mpMRI used for preparing prostatectomy tissue co-registered with mpMRI coordinates. C. Gross pathology and standard H&E stained tissue section, with two representative MALDI-IMS images of tumor and stroma localized N-glycans and collagenase derived ECM peptides in the same tissue slice.