C133 Snitkovsky fig1

Uncovering molecular biomarkers in gastric adenocarcinoma

Gastric adenocarcinoma is usually diagnosed at an advanced stage, which portends a poor prognosis. Molecular biomarkers are important tools to understand the underlying biology of its aggressive behaviour and to discover new targets for therapeutic agents. Microarray analyses and next generation sequencing are leading to a deeper understanding of tumour biology and the development of new biomarkers, offering hope for better treatment approaches in the future.

by Dr I. Snitcovsky, Dr F. Solange Pasini and Dr G. de Castro Jr

Background
Gastric cancer is the fourth most common cancer in the world and is especially prevalent in East Asia and South America [1]. Adenocarcinoma accounts for the great majority of these tumours, which are classified as intestinal or diffuse type. The pathogenesis is incompletely understood, but it is associated with Helicobacter pylori infection and dietary salt and nitrosamines, particularly in intestinal type tumours. In these cases, chronic inflammation is thought to lead to preneoplastic lesions that may progress to invasive cancer in a stepwise fashion. In a minority of cases, germline mutations of P53, CDH1 and mismatch repair genes are associated with familial cases. The most important prognostic factor is the tumour TNM stage, since the only curative approach is surgical resection, followed (or not) by adjuvant therapies. Thus, locally advanced and metastatic disease portends a poor prognosis, with a median survival of less than one year. Unfortunately, most patients in Western countries are diagnosed with advanced disease, and, in these cases, chemotherapy can palliate symptoms and prolong overall survival but it is not curative [2]. In patients with metastatic disease, the only biomarker routinely tested for in gastric adenocarcinoma is HER2 (human epidermal growth factor 2 receptor; by immunohistochemistry), which is associated with poor outcomes and is also predictive of the anti-tumour efficacy of the humanized anti-HER2 antibody, trastuzumab [3].

The development of innovative treatment approaches begins with the identification of molecular biomarkers relevant to tumour biology. The next step is clinical validation, usually by showing that the studied biomarker has a prognostic value. Finally, a targeted agent is developed and shown to prolong survival in phase III clinical trials. Genome-wide studies are revealing potential biomarkers for targeted therapies and immunotherapy. This review will focus on recently identified candidate biomarkers in gastric adenocarcinoma with potential clinical applications.

Biomarkers in the pre-genomic era
Cancer cells are characterized by self-sufficiency in growth signals, insensitivity to anti-growth signals, evasion of apoptosis, limitless reproductive potential, sustained angiogenesis and tissue invasion and metastasis [4]. Accordingly, in gastric adenocarcinoma, a great number of studies focused on the prognostic role of single molecules. They included, but were not restricted to, growth factors and their receptors [HER2, IGFR (insulin-like growth factor 1 receptor)], cell cycle regulators (p53), angiogenesis controllers [VEGF (vascular endothelial growth factor)] and matrix metalloproteinases, with so far no impact in patient management, with the exception of HER2.

The epidermal growth factor receptor (EGFR) family includes HER1 (EGFR), HER2 (ErbB2), HER3 (ErbB3) and HER4 (ErbB4). These molecules form dimers on the cell surface after ligand binding, which leads to intracellular signalling that modulates cell proliferation, metastasis and angiogenesis. HER2 has no known ligands, but forms heterodimers with other members of the HER family and potentiates signalling. In breast cancer, HER2 overexpression is related to poor prognosis and the humanized anti-HER2 monoclonal antibody trastuzumab prolongs survival in those patients with HER2 positive tumours [5]. In gastric adenocarcinoma, HER2 overexpression is detected in 9–35% of cases and implies a worse prognosis in some studies. A phase III trial that included patients with HER2-overexpressing gastric adenocarcinoma found that the addition of trastuzumab to chemotherapy resulted in an overall survival benefit of about two months, as compared to chemotherapy alone [3]. In contrast, phase III studies evaluating anti-angiogenic agents in unselected gastric adenocarcinoma patients presented conflicting results [6, 7].

Gene panels and next generation sequencing
Gastric adenocarcinoma is a heterogeneous disease, thus the simultaneous determination of several biomarkers may be more informative then single ones, nowadays possible by high-throughput technologies as microarray platforms and next generation sequencing. Chen et al. [8] proposed a prognostic three-gene model, derived from gene expression profiling in eighteen paired samples. Marchet et al. [9] proposed another three-gene model predictive of lymph node involvement in a cohort of 32 patients. Another prognostic four-gene signature was also described [10]. Little overlap was observed among these above-mentioned signatures, which is not informative in terms of advancing in the cancer biomarker development.

A study comparing 248 gastric adenocarcinoma tumour samples was able to classify tumours in three subtypes, based on gene expression patterns: proliferative, metabolic and mesenchymal. In addition, these subtypes were shown to have differences in molecular and genetic features, and response to therapy [11]. Next generation sequencing is providing a deeper level of understanding the tumour biology. Genetic alterations were observed in Wnt, Hedgehog, cell cycle, DNA damage and epithelial-to-mesenchymal-transition pathways by analysing the genome and the transcriptome in 50 adenocarcinoma samples. About 20% of these alterations could be considered as potential targets for drugs that are already available [12]. Novel fusion genes were identified, especially DUS4L-BCAP29, when transcriptome sequencing was performed in 12 gastric adenocarcinoma cell lines. Knockdown of this transcript inhibited cell proliferation, thus validating its functional role [13].

Immune biomarkers
Cancer, including gastric adenocarcinoma, is viewed as a tissue disease. This implies that the microenvironment plays a key role in tumour biology [4]. Thus, immune cell infiltrate has been shown to be of prognostic value in gastric adenocarcinoma. As depicted in Figure 1, tumour-associated macrophages present two different polarizations: classical (M1) characterized by immunostimulation activity and tumour suppression; and alternative (M2) characterized by tumour promotion and immune suppression. A higher ratio of M1/M2 macrophages was associated with a favourable prognosis [14]. The underlying mechanism is complex, but may involve growth factor modulation [15]. We conducted a gene expression study, including a total of 51 freshly frozen tumour samples from patients with gastric adenocarcinoma treated with surgery. An immune-related gene trio (OLR1, CXCL11 and ADAMDEC1) was identified as an independent biomarker of prognosis. We proposed that immune dampening in the tumour microenvironment was present in patients with poor prognosis. Three main observations supported our hypothesis. First, the expression levels of genes belonging to the functional group of immune/inflammatory response were markedly reduced as a whole. Second, a network analysis suggested an unwired inflammatory response, and third, a decreased expression of type-1 helper lymphocyte (Th1) and other immune activating genes was found [16]. The biomarkers we identified may be good candidates for selecting patients for immunomodulation therapies, including immune checkpoint inhibitors [17].

Conclusions and perspectives
Gastric adenocarcinoma needs better treatment approaches. New technologies are offering the necessary tools to identify molecular biomarkers, leading to a deeper understanding of tumour biology and the development of innovative treatment strategies, and we are entering an era of cautious optimism. Considering the tumour heterogeneity and the limited survival gains with targeted agents in solid tumours, it is possible that patient selection by immune biomarkers and the use of immune checkpoint inhibitors are promising alternatives. The impressive response rates and overall survival benefits observed in patients with squamous cell lung cancer and melanoma, two notoriously chemoresistant tumours, when treated with anti-PD1 or anti-PD1L are good examples [18].

References
1. Ferlay J, et al. GLOBOCAN 2012 v1.0, Cancer Incidence and Mortality Worldwide: IARC CancerBase No. 11; 2013. (http://globocan.iarc.fr)
2. Waddell T, et al. Gastric cancer: ESMO-ESSO-ESTRO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2013;24(Suppl 6):57.
3. Bang YJ, et al. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer. Lancet 2010;376: 687.
4. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011;144:646.
5. Figueroa-Magalhães MC, et al. Treatment of HER2- positive breast cancer. Breast 2013;doi:10.1016/j.breast.2013.11.011.
6. Ohtsu A, et al. Bevacizumab in combination with chemotherapy as first-line therapy in advanced gastric cancer: a randomized, double-blind, placebo-controlled phase III study. J Clin Oncol. 2011;29:3968.
7. Fuchs CS, et al. Ramucirumab monotherapy for previously treated advanced gastric or gastro-oesophageal junction adenocarcinoma (REGARD): an international, randomised, multicentre, placebo-controlled, phase 3 trial. Lancet 2014;383:31.
8. Chen CN, et al. Gene expression profile predicts patient survival of gastric cancer after surgical resection. J Clin Oncol. 2005;23:7286.
9. Marchet A, et al. Gene expression profile of primary gastric cancer: towards the prediction of lymph node status. Ann Surg Oncol. 2007;14:1058.
10. Xu ZY, et al. Gene expression profile towards the prediction of patient survival of gastric cancer. Biomed Pharmacother. 2010;64:133.
11. Lei Z, et al.
Identification of molecular subtypes of gastric cancer with different responses to PI3-kinase inhibitors and 5-fluorouracil. Gastroenterology 2013; 145:554.
12. Holbrook JD, et al. Deep sequencing of gastric carcinoma reveals somatic mutations relevant to personalized medicine. J Transl Med. 2011;9:119.
13. Kim HP, et al. Novel fusion transcripts in human gastric cancer revealed by transcriptome analysis. Oncogene 2013;doi:10.1038/onc.2013.490.
14. Pantano F, et al. The role of macrophages polarization in predicting prognosis of radically resected gastric cancer patients. J Cell Mol Med. 2013;17:1415.
15. Cardoso AP, et al. Macrophages stimulate gastric and colorectal cancer invasion through EGFR Y(1086), c-Src, Erk1/2 and Akt phosphorylation and smallGTPase activity. Oncogene 2013;doi:10.1038/onc.2013.154.
16. Pasini FS, et al. A gene expression profile related to immune dampening in the tumor microenvironment is associated with poor prognosis in gastric adenocarcinoma. J Gastroenterol. 2013;doi:10.1007/s00535-013-0904-0.
17. Eggermont AM, et al. Immunotherapy and the concept of a clinical cure. Eur J Cancer 2013;49: 2965.
18. Brahmer JR, et al. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N Engl J Med. 2012;366:2455.
 
The authors
Igor Snitcovsky1,2 MD, PhD; Fátima Solange Pasini1,2 PhD; and Gilberto de Castro Jr*1,3 MD, PhD
1 Departamento de Radiologia e Oncologia, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
2 Centro de Investigação Translacional em Oncologia, Instituto de Câncer do Estado de São Paulo (ICESP), São Paulo, Brazil
3 Oncologia Clínica, Instituto do Câncer do Estado de São Paulo (ICESP), São Paulo, Brazil

*Corresponding author
E-mail: gilberto.castro@usp.br

p16 04

Serum B-cell maturation antigen: a novel marker for multiple myeloma

B-cell maturation antigen (BCMA) was originally identified as a cell surface receptor expressed on late-stage B cells, plasma cells, and B-cell malignancies including multiple myeloma (MM). We recently discovered that BCMA is shed into the blood of MM patients, and, therefore, serum BCMA may serve as a new prognostic marker to track disease status and response to treatment.

by Eric Sanchez, Suzie Vardanyan, Mingjie Li, Cathy Wang, Dr Haiming Chen, and Dr James R. Berenson

Background
B-cell maturation protein (BCMA, also referred to as TNFRSF17 or CD269) is a receptor shown to be expressed in B lymphocytes and at increasing levels as these cells mature [1]. BCMA binds the ligands BAFF (B-cell activating factor) and APRIL (a proliferation inducing ligand) [2, 3]. Membrane-bound expression of BCMA has been demonstrated in human CD138-expressing cells from multiple myeloma (MM) bone marrow (BM) and MM cell lines [4]. It has also been shown to be expressed on malignant cells from Hodgkin’s lymphoma and Waldenstrom’s macroglobulinemia (WM) patients [5, 6]. Although the response to treatment of MM patients is traditionally followed with measurement of their monoclonal immunoglobulin (Ig) levels, some patients do not produce this marker; and, moreover, in others, it is lost during the course of their disease.

Serum BCMA levels are elevated in MM patients
We measured serum BCMA by ELISA from patients with newly diagnosed MM, monoclonal gammopathy of undetermined significance (MGUS) and healthy control subjects. Using the International Staging System, 30, 12 and 7 patients with stages 1, 2 and 3, respectively, and one with unknown staging were analysed. We found that the serum levels of BCMA in MM patients (13.87 ng/ml) were elevated when compared to healthy controls (2.57 ng/ml; P <0.0001) and MGUS individuals (5.30 ng/ml; P = 0.0157; Fig.1A). We then determined that serum BCMA levels correlated with the MM patient’s response to therapy. Patients responding to their treatment regime had lower serum BCMA levels than patients with progressive disease (P = 0.0038; Fig. 1B). To confirm that the BCMA found in the blood of MM patients came from cells within the BM, BM aspirates were obtained from MM patients and BM mononuclear cells (MCs) were isolated and cultured for 48 hours. MM patients showed high levels of BCMA in culture medium whereas healthy subjects lacked significant amounts of BCMA.  Moreover, serum and supernatant BCMA levels from MM patients were compared and showed a strong correlation (r = 0.82) between the levels in the serum and supernatants from cultured MM BMMCs (Fig. 2). To exclude the possibility that the BCMA detected in MM patient serum and from cultured MM BMMCs may have been derived from non-malignant cells, we evaluated human BCMA levels in our human MM xenografts growing in severe combined immunodeficient (SCID) mice.  Animals were implanted with the human MM tumour LAGκ-2 and analysed for human serum BCMA levels. SCID mice dosed with bortezomib (0.5 mg/kg, twice weekly) had a reduction in tumour volume compared to untreated mice (P = 0.0067; Fig. 3A), and human serum BCMA levels from these bortezomib-treated animals were also markedly lower compared to untreated mice (P = 0.0006; Fig. 3B). Similar results were obtained when using our other MM xenograft models (LAGλ-1, LAGκ-1A). Human BCMA was not detected in the serum of non-tumour-bearing mice (data not shown). A rise in serum BCMA levels from the possible release of membrane-bound protein from dead MM cells was not observed in mice following drug treatment. Thus, it can be concluded that the serum levels of BCMA in the mice are derived from live MM cells. Soluble BCMA has been shown to inhibit normal B-cell development through interference with the binding of its ligands (BAFF and/or APRIL) to membrane-bound BCMA on normal B cells. One group demonstrated that administration of BCMA–Ig fusion protein to normal mice, which inhibits the binding of BAFF to B cells, resulted in a dramatic reduction in B-cell numbers in the blood and peripheral lymphoid organs [2]. Splenic B-cell reductions were shown to occur in an in vitro mouse splenocyte proliferation assay following in vivo administration of BCMA–Fc fusion protein to normal mice [7]. Other investigators have shown that injecting soluble BCMA–Fc fusion protein, which binds BAFF and APRIL both as free and membrane-bound ligands, into nude mice bearing human colon or lung carcinoma cell lines resulted in inhibition of tumour growth [3]. The authors suggested that BCMA bound its ligand APRIL, and prevented the known stimulatory effect of APRIL on these cell lines. Additionally, investigators have shown in vitro the existence of BCMA–BAFF complexes [3, 7, 8]. In the context of cancer growth, one group demonstrated that BCMA injected into mice reduced the growth of tumour cells from human colon or lung carcinoma cell lines in vivo by binding its ligand APRIL [3]. Thus, we are currently conducting studies to determine if such complexes exist in vivo and may block the immune function of myeloma patients.

Conclusions and future directions
Measurement of MM tumour mass is indirect, given the location of this BM based malignancy. Thus, assessment of tumour burden in response to therapy is difficult but essential to effectively monitor patients with MM. Traditionally, changes in Ig levels have been used to follow disease progression and response to treatment. In fact, for three decades Ig was a prognostic factor used in the Durie-Salmon staging system [9], which, until recently, was the most widely used staging system [10].  However, assessment of this protein does not always accurately reflect changes in MM tumour burden [11–13]. Additionally, small subsets of MM patients do not produce this marker. Thus, additional markers are needed to assess response to therapy in these non-secretory patients and in MM patients as a whole.

We have now shown that BCMA is present in the serum of MM patients; and, moreover, its levels correlate with the patient’s response to therapy [14]. We have also previously shown that supernatant from cultured BMMCs from MM patients with active disease contain much higher levels of this protein in their culture medium than in healthy subjects and those with MGUS or indolent MM [14]. SCID mice bearing human MM xenografts also showed high levels of BCMA in their sera, and these levels decreased in response to anti-MM therapy. We believe that that serum BCMA will eventually be used in the clinic as a diagnostic and prognostic marker for MM patients.

References
1. Laabi Y, Gras MP, Brouet JC, et al. The BCMA gene, preferentially expressed during lymphoid maturation, is bidirectionally transcribed. Nucleic Acids Res. 1994; 22(7): 1147–1154.
2. Thompson JS, Schneider P, Kalled SL, et al. BAFF binds to the tumor necrosis factor receptor-like molecule B cell maturation antigen and is important for maintaining the peripheral B cell population. J Exp Med. 2000; 192(1): 129–135.
3. Rennert P, Schneider P, Cachero TG, et al. A soluble form of B cell maturation antigen, a receptor for the tumor necrosis family member APRIL, inhibits tumor cell growth. J Exp Med. 2000; 192(11): 1677–1684.
4. Novak AJ, Darce JR, Arendt BK, et al. Expression of BCMA, TACI, and BAFF-R in multiple myeloma: a mechanism for growth and survival. Blood 2004; 103(2): 689–694.
5. Chiu A, Xu W, He B, et al. Hodgkin lymphoma cells express TACI and BCMA receptors and generate survival and proliferation signals in response to BAFF and APRIL. Blood 2007; 109(2): 729–739.
6. Elsawa SF, Novak AJ, Grote DM, et al. B-lymphocyte stimulator (BLyS) stimulates immunoglobulin production and malignant B-cell growth in Waldenstrom macroglobulinemia. Blood 2006; 107(7): 2882–2888.
7. Pelletier M, Thompson JS, Qian F, et al. Comparisons of soluble decoy IgG fusion proteins of BAFF-R and BCMA as Antagonist for BAFF. J Biol Chem. 2003; 278(35): 33127–33133.
8. Shu HB, Johnson H. B cell maturation protein is a receptor for the tumor necrosis factor family member TALL-1. Proc Natl Acad Sci U S A 2000; 97(16): 9156–9161.
9. Durie BG, Salmon SE. A clinical staging system for multiple myeloma: correlation of measured myeloma cell mass with presenting clinical features, response to treatment and survival. Cancer 1975; 36(3): 842–854.
10. Larson RS, Sukpanichnant S, Greer JP, et al. The spectrum of multiple myeloma: diagnostic and biological implications. Hum Pathol. 1997; 28(12): 1336–1347.
11. Sullivan PW, Salmon SE. Kinetics of tumor growth and regression in IgG multiple myeloma. J Clin Invest. 1972; 51(7): 1697–1708.
12. Kawano M, Huang N, Harada H, et al. Identification of immature and mature cells in the bone marrow of human myelomas. Blood 1993; 82(2): 564–570.
13. Zaanen HCT, Lokhorst HM, Aarden LA, et al. Chimaeric anti-interleukin 6 monoclonal antibodies in the treatment of advanced multiple myeloma: a phase I dose-escalating study. Br J Haematol. 1998; 102(3): 783–790.
14. Sanchez E, Li M, Kitto A, et al. Serum B-cell maturation is elevated in multiple myeloma and correlates with disease status and survival. Br J Haematol. 2012; 158(6): 727–738.

The authors
Eric Sanchez BA; Suzie Vardanyan BS; Mingjie Li BS; Cathy Wang BS; Haiming Chen MD, PhD; and James R. Berenson* MD
Institute for Myeloma & Bone Cancer Research, West Hollywood, CA, USA


*Corresponding author
E-mail: Jberenson@imbcr.org

 

C131 Gul M Mustafa figure1

Quantitative proteomics: closing the gap between biomarker discovery and validation – the rate-limiting step

Many potential cancer biomarkers have been identified, however, the transfer of these biomarkers from discovery to clinical practice is still a process filled with pitfalls and limitations. To prove clinical utility and performance, these candidate biomarkers need to be reproducible, specific, sensitive, and validated using large sample cohorts, all of which require development of robust and highly sensitive multiplex protein assays.

by Dr G. M. Mustafa, Prof. J. R. Petersen, Prof. L. Denner Prof. F. A. Hussain and Prof. C. Elferink

Background
Although remarkable scientific and technological advances in medicine have been achieved, cancer incidences are still increasing worldwide with the ratio of deaths to new cancer cases remaining relatively unchanged at 49% [1]. The ability of physicians to effectively treat and cure cancer is directly dependent on their ability to detect cancer at an early stage. When cancer develops in an area of the body, such as an organ, as long as it hasn’t spread (metastasized), it may respond well to treatment and in some cases a cure may be possible.  Many disease states, especially various types of cancer, can be better diagnosed by the aid of biomarkers, a key element of modern diagnostics and the value of which continuing to increase in modern medicine. As indicators of biological status, biomarkers, whether detected in blood, urine, or tissue, can be useful for the clinical management of various diseases. The changes in biomarker concentration have the potential to guide therapy in disease progression, prognosis and potentially be used to identify the stage of the cancer.  Overall, protein biomarkers are needed to help our understanding of cancer biology and to improve our ability to diagnose, monitor and treat cancers.

Biomarker research
One of the goals of biomarker research is to discover and validate markers that can be used in clinical research applications such as patient stratification, diagnosis and therapeutic monitoring, or in pharmaceutical development to fully characterize the behaviour and efficacy of candidate drugs. The identification of prognostic, predictive or pharmacodynamic biomarkers can be carried out using genomic or proteomic technologies. Proteomic profiling of body fluids, such as serum, has potential as a sensitive diagnostic tool for early cancer detection. Serum provides a rich sample for diagnostic analyses because the expression and release of proteins (potential biomarkers) into the bloodstream occurs in response to specific physiological states. As human plasma has a 1010 dynamic range of proteins [2] with 22 proteins being responsible for 99% of the proteins identified, one of the challenges working with such a complex biological fluid is the difficulty in identifying medium and low abundance proteins. Thus, sample enrichment is a very important step in the discovery phase.

Biomarker validation – the rate-limiting step

Discovery platforms typically result in an extensive hit-list of candidate biomarkers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Over the last several years, many proteins have been proposed as potential biomarkers for various cancers without further evaluation of their clinical utility.  The lack of follow-up is due, to a large extent, to the lack of an efficient technology for reproducible and accurate verification of these proteins as biomarkers in a specific disease state.  Without proper validation, the identification of biomarkers is of minimal utility. To show clinical utility, biomarkers must be validated using a reliable assay with an independent cohort in a prospective or longitudinal study. A search of the scientific literature clearly indicates that most published biomarkers are inadequate for replacing an existing clinical test or that they are only useful for detecting disease in an advanced stage, where treatment success and/or survival rates are low. Traditionally, validation has been performed with immunoassays which require antibodies that are often unavailable or of poor quality. In addition the immunoassays may not adequately identify or differentiate between post-translational modifications. The process of generating antibodies is also time consuming and costly and is therefore not a practical solution for screening the hit-list of proteins derived from discovery.

Targeted mass spectrometry for multiplexed protein quantitation
A targeted mass-spectrometry-based antibody-free platform for multiplexed protein quantitation fills the well-recognized gap between early biomarker discovery and final clinical assay. Stable-isotope-dilution multiple-reaction-monitoring mass spectrometry (SID-MRM-MS) is a novel technique whereby the quantification of a protein can be calculated from isotopically labelled peptide standards of known concentrations that correspond to the protein of interest [3]. With two to five unique peptides per protein, the concentration of the protein of interest can be accurately determined.  Further, the technique can be multiplexed to allow for the simultaneous measurement of many proteins. We have validated this approach using serum samples to identify biomarkers in hepatocellular carcinoma and are confident that it also has the potential for biomarker discovery in other cancers [4].  This powerful workflow opens up new possibilities for biomarker research that may lead to faster, more robust, and improved clinical assays. Targeted proteomics workflows based on SRM and MRM on triple quadruple mass spectrometry platforms show the potential for rapid verification of biomarker candidates in plasma by using heavy isotope-labeled internal standards. This approach has the selectivity, reproducibility, and sensitivity for a range of multiplexed protein assays and has the potential for quantifying protein isoforms in addition to posttranslational modifications for which good quality antibodies often do not exist.  The ability to rapidly quantify proteins in a highly multiplexed manner using MRM with internal standard peptides closes the gap between discovery and validation in the biomarker pipeline, which is the rate-limiting step in the biomarker world. Using a triple quadruple mass spectrometer, the first mass analyser (Q1) is set to only transmit the parent weight of a peptide from the target protein, the collision energy is then optimized to produce a diagnostic charged fragment of a peptide fragment in the second mass analyser (Q2), and the third mass analyser (Q3) is set to only transmit and identify this diagnostic peptide fragment (Fig. 1). The key strength of this work flow is that the protein assay development for hundreds of proteins can occur on the order of a month. Once identified, it just takes months to validate the low to sub-ng/ml concentration of candidate biomarkers in hundreds of blood samples. No target-specific reagents, such as antibodies, are needed and only a very small amount of sample (<500ng) is required for quantitation. In addition all potential biomarkers can be quantified in a single assay that is more accurate, rapid, and cost-effective. The capacity of SRM for multiplexed, high-throughput analysis, together with its sensitivity and quantitation, positions SRM as a promising application in medical screening [5, 6]. Summary
The type of clinical proteomics described here has important direct ‘bedside’ applications. We can foresee a future in which the physician will use these proteomic analyses at many points in the management of disease and drug discovery.

References
1. Yeom YI, Kim SY, Lee HG, et al. Cancer biomarkers in ’omics age. Biochip Journal 2008; 2(3): 160–174.
2. Anderson L.  Candidate-based proteomics in the search for biomarkers of cardiovascular disease. J Physiol. 2005; 15: 23–60.
3. Lange V, Picotti P, Domon B, Aebersold R. Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol. 2008; 4: 222.
4. Mustafa MG, Petersen JR, Ju H, Cicalese L, et al. Biomarker discovery for early detection of hepatocellular carcinoma in hepatitis C-infected patients. Mol Cell Proteomics 2013; 12(12): 3640–3652
5. Keshishian H, Addona TA, Burgess M, et al. Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution. Mol Cell Proteomics (2007); 6(12): 2212–2229
6. Zhao Y, Jia W, Sun W, et al. Combination of improved 18O incorporation and multiple reaction monitoring: a universal strategy for absolute quantitative verification of serum candidate biomarkers of liver cancer. J Proteome Res. (2010); 9(6): 3319–3327

The authors

Gul M. Mustafa*1 PhD, John R. Petersen2 PhD, Larry Denner3 PhD, Feroze A. Hussain4 MD, and Cornelis Elferink1 PhD
1 Department of Pharmacology, University of Texas Medical Branch, Galveston, Texas, USA
2 Victory Lakes Clinical Laboratory, Department of Pathology, University of Texas Medical Branch, Galveston, Texas, USA
3 Department of Internal Medicine, University of Texas Medical Branch, Galveston, Texas, USA
4 Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Texas Medical Branch, Galveston, Texas, USA

*Corresponding author
E-mail: gmmustaf@utmb.edu

p23

The role of expressed prostatic secretion biomarkers in prostate cancer screening/surveillance

Expressed prostatic secretion (EPS) is obtained after prostatic message by milking the urethra and collecting fluid directly from the urethral meatus. Clinicians have previously used this biospecimen primarily for the diagnosis of urinary infections. More recently it has been recognized as a rich source of biomarkers of prostate malignancy. Many of those biomarkers are accessible only in EPS, where it has shown a unique potential in both prostate cancer screening and active surveillance programmes.

by Dr J. Linehan, Dr J. Yamzon, Prof. T. Wilson and Prof. S. Smith

Current risk assessment tools
An estimated 238,590 new cases of prostate cancer will be diagnosed in the United States during 2013. A substantial proportion of these patients are considered ‘low-risk’ for progression and may be best served with conservative management. Yet many will undergo definitive treatment by means of radiotherapy or radical prostatectomy, both of which have risks of life-altering side effects. This huge – and ultimately unsustainable – pattern of over-treatment has incited a shift in practice patterns toward initial conservative management known as Active Surveillance (AS), the premise of which is to minimize unnecessary treatment by performing close monitoring. Should there be signs of tumour progression upon recurring reassessment, then treatment can be offered with curative intent. Currently, our ability to discern one’s risk for harbouring an indolent form of prostate cancer utilizes clinical parameters that lack predictive ability. Serum PSA level, clinical stage determined on digital rectal examination (DRE), and tumour grade determined upon biopsy, known as the Gleason Score (GS), are currently used to stratify the risk of tumour progression, although with only limited accuracy. This is evidenced by studies of men eligible for AS who are found to have more advanced disease upon treatment with radical prostatectomy [1] despite meeting AS criteria using the standard criteria. Tools based on the biology of prostate cancer offer a potential platform for improved risk stratification, and hence allow more appropriate levels of intervention.

Invasive and non-invasive testing
Current efforts in biomarker discovery and validation stand to complement the existing tools that gauge eligibility for AS. Several tools, such as Oncotype DX-Prostate® (Genomic Health) and Prolaris® (Myriad Genetics), are commercially available and generate risk scores for harbouring more advanced disease. These rely on extraction of RNA from tumour tissue, most commonly taken from the biopsy specimen that may not contain the sufficient amounts of cancer tissue needed to perform these proprietary tests. AS protocols require periodic repeat biopsies of the tumour, which may have potential complications of bleeding, infection, and pain. Thus, a less invasive method of assessment is ideal. Tools reliant on serum and urine specimens are attractive in that they are more readily obtained. Serum tests, such as free-to-total PSA ratios, the 4K Score (OPKO Health), and the Prostate Health Index (Beckman-Coulter), show promise in refining prostate cancer diagnosis, but these rely on proteins shed from the tumour into circulation. Urine based tests like PCA3 (Gen-Probe) or DNA based tests like ConfirmMDx (MDxHealth) rely on proteins shed into the urine after prostate massage, or DNA extracted from biopsy specimens. These latter tests are utilized in the clinical scenario where prostate cancer remains undiagnosed despite high suspicion by standard parameters.

The biological function of the prostate gland is the production of seminal fluid critical to reproduction. It contains DNA, RNA, proteins and metabolites that have the potential to serve as biomarkers useful in prostate cancer diagnosis and risk assessment. Its contents can be retrieved by two non-invasive methods. The first, variously called a post-DRE urine or post-massage urine, is obtained as a urine sample collected immediately after an attentive DRE. The second, termed prostatic fluid or expressed prostatic secretion (EPS) is obtained after prostatic massage by milking the urethra and collecting fluid directly from the urethral meatus. Neither specimen requires invasive techniques and both contain significant numbers of prostate cancer cells and prostate cancer biomarkers [2–5]. Each has advantages and disadvantages. Post-DRE urine is relatively straightforward to collect; however, the urine volume, and cell lysis that occurs in urine, can significantly dilute the informative cellular material and hinder the recovery of the informative components of the fluid. EPS specimens require more effort to collect but are undiluted and do not promote cell lysis or block activity measurements. Most clinicians would prefer to collect post-DRE urine samples, but the extra effort required to collect EPS could be justified because a number of useful biomarkers cannot be assessed in post-DRE urine. Patient acceptance of both biopsy and EPS collection are improved dramatically by the administration of valium prior to biopsy. Moreover, EPS collection prior to biopsy can be performed in a single clinical visit.

Both EPS and post-DRE urine specimens have proven successful in prostate cancer detection using gene expression biomarkers, where PCA3 and TMPRSS2:ERG fusions have proven effective. Here, sufficient quantities of RNA are present in either specimen, permitting roughly equivalent improvements in performance in the prediction of biopsy outcome (Table 1). The moderate improvement in test performance seen in EPS compared to post-DRE urine appears to be attributable to the need for normalization to PSA messenger RNA measured in the same specimen [6]. This requirement is unique to post-DRE urine as a specimen since urine volume collection is not constant, making it necessary to gauge the informative RNA signals against a fixed RNA signal. The choice of PSA messenger RNA in this application tends to suppress the informative signals since more of it is released into the urine from regions of prostate cancer where the basement membrane is compromised. Moreover it is not possible to measure the volume of the prostatic fluid after it is diluted by the variable urine catch.

DNA methylation is much more difficult to quantify, since DNA is present in much lower concentration in cells, and the required chemical treatments of the isolated DNA results in a severe reduction of the DNA available for quantitative PCR amplification. It has only been reported to be effective in the prediction of biopsy outcome in EPS [4], where the combination of hypermethylation at RARß, RASSF1 and GSTP1performed as well as PCA3 as a single marker.

The field defect and prostate function
Prostate functionality becomes an important diagnostic tool when one considers the extensive field defect that characterizes the disease [8]. Field defects are best defined as functional aberrations that extend beyond the morphologically recognizable tumour in otherwise histologically normal tissue. The concept dates to the early 1950s and has been shown to involve altered DNA methylation patterns extending several millimeters from the prostate tumour. In prostate tumorigenesis it has recently been documented that extensive chromosome rearrangements occur in single steps involving chromothripsis and chromoplexy [9, 10]. In this view the field defect represents clonal progeny of an earlier stage in tumour evolution from which additional chromothripsis and chromoplexy events generate the malignancy. Since most reports of hypermethyled loci fall at or extremely near fragile sites [11], DNA methylation alterations may be linked to chromoplexy and chromothripsis, making it possible to detect cancer by looking for early alterations DNA methylation patterning. Mitochondrial DNA aberrations also appear to track prostate tumour evolution and the field defect includes mitochondrial DNA deletions [12].

Each of these findings suggests that capacity of the prostate gland to produce functional prostatic fluid will be regionally compromised. Genome wide aberrations in DNA methylation coupled with the aberrant expression of transcription factors, such as ERG, could indicate wholesale aberrations in gene expression, while the mitochondrial deletions may underlie alterations in the unique metabolic pathways present in the normal gland. The field defect around larger or more highly evolved tumours could in fact affect the entire gland and can be expected to significantly alter not only the nature but also the amount of prostatic fluid that the gland can produce.

Anecdotally, surgeons collecting EPS by the non-invasive procedure prior to prostatectomy or by squeezing the excised gland just after prostatectomy note that a prostate with a larger tumour burden yields less fluid than a gland bearing small tumour foci, suggesting that the measured volume of the recoverable fluid should be an effective biomarker for prostate cancer. This was demonstrated in recent studies with patients who are eligible for active surveillance by various criteria but were treated with robot assisted radical prostatectomy instead.

For these studies, we used a biomarker set that measures the secretion capacity of the prostate gland. This set includes recovered EPS volume in microlitres and total recovered RNA in nanograms. It is measured along with pre-operative serum PSA value as baseline in multivariate logistic regression analysis (Fig. 1).

Future directions
Given the utility of EPS biomarkers in predicting the presence of occult extracapsular extension in an AS cohort, we believe that the advantages of EPS in assessing the functionality of the gland make it uniquely suited for initial risk stratification in determining eligibility for AS and also in monitoring the disease during surveillance. One of the most perplexing issues in this area is detecting misclassification. In preliminary work in this area (Wittig et al. in prepartion) we noted that more than 40% of patients initially scored as GS 6 in an NCCN cohort can be occult GS 7 comprising largely GS 3+4 patterns with relatively fewer pattern 4+3 GS 7s. Although GS 7 patients are referred for definitive treatment this data suggests that many have not progressed during AS. None of the available biomarkers that we have tested in EPS thus far (TMPRSS2:ERG, PCA3, Secretion Capacity, TXNRD1 or PSA-mRNA) reliably detect this relatively subtle change in the GS. Misclassification recognized at repeat biopsy is generally accepted as an error of initial biopsy undersampling. One can question the clinical significance of such a subtle nuance and its affect on the grander outcomes of disease metastasis and prostate cancer death. Biopsy misclassification is yet another example of the under-performance of standard parameters (like the GS) and the need for biomarker based determinations of disease aggressiveness.

Several new biomarkers are evaluable exclusively in EPS. One example is PSA activity. PSA is a proteolytic enzyme that cannot be assayed in urine specimens, although the assay may function in urine sediment. It is active in EPS and has been shown to be inversely proportional to tumour aggressiveness [13] . Another biomarker with potential in EPS is citrate, which has been shown to be an indicator of prostate cancer in seminal fluid. This marker [14] reflects the overall health of the gland, since the unique metabolism of the normal prostate is designed to secrete citrate into the prostatic fluid. A third biomarker approachable only in EPS is zinc [15]. This ion is taken up preferentially in normal prostate where it blocks the degradation of citrate by inhibiting aconitase in the citric acid cycle thus contributing to the normal function of the gland in citrate secretion.
In summary, the suboptimal performance of the current clinicopatholigic parameters utilized in prostate cancer diagnosis and risk stratification drive the need for additional tools. Biomarkers examined in EPS offer the additional dimension of prostate-function assessment through a non-invasive platform that has great potential to improve prostate cancer diagnosis, risk stratification, and AS.

Abbreviations
AS, active surveillance
AUC, area under curve
DRE, digital rectal examination
EPS, expressed prostatic secretion
GS, Gleason Score
PSA, prostate-specific antigen
ROC, receiver operating characteristic

References
1. Conti SL, Dall’era M, Fradet V, Cowan JE, Simko J, Carroll PR. Pathological outcomes of candidates for active surveillance of prostate cancer. J Urol. 2009; 181: 1628–1633 (Discussion pp. 1624–1633).
2. Groskopf J, Aubin SM, Deras IL, Blase A, Bodrug S, Clark C. APTIMA PCA3 molecular urine test: development of a method to aid in the diagnosis of prostate cancer. Clin Chem. 2006; 52: 1089–1095.
3. Crocitto LE, Korns D, Kretzner L, Shevchuk T, Blair SL, Wilson TG, Ramin, SA, Kawachi MH, Smith SS. Prostate cancer molecular markers GSTP1 and hTERT in expressed prostatic secretions as predictors of biopsy results. Urology 2004; 64: 821–825.
4. Clark JP, Munson KW, Gu JW, Lamparska-Kupsik K, Chan KG, Yoshida JS, Kawachi MH, Crocitto LE, Wilson TG, et al. Performance of a single assay for both type III and type VI TMPRSS2:ERG fusions in non-invasive prediction of prostate biopsy outcome. Clin Chem. 2008; 54: 2007–2017.
5. Laxman B, Tomlins SA, Mehra R, Morris DS, Wang L, Helgeson BE, Shah RB, Rubin MA, Wei JT, Chinnaiyan AM. Noninvasive detection of TMPRSS2:ERG fusion transcripts in the urine of men with prostate cancer. Neoplasia 2006; 8: 885–888.
6. Whelan C, Crocitto L, Kawachi M, Chan K, Smith D, Wilson T, Smith S. The influence of PSA-RNA yield on the analysis of expressed prostatic secretions (EPS) for prostate cancer diagnosis. Can J Urol. 2013; 20: 6597–6602.
7. Tomlins SA, Aubin SM, Siddiqui J, Lonigro RJ, Sefton-Miller L, Miick S, Williamsen S, Hodge P, Meinke J, et al. Urine TMPRSS2:ERG fusion transcript stratifies prostate cancer risk in men with elevated serum PSA. Sci Transl Med. 2011; 3: 94ra72.
8. Mehrotra J, Varde S, Wang H, Chiu H, Vargo J, Gray K, Nagle RB, Neri JR, Mazumder A. Quantitative, spatial resolution of the epigenetic field effect in prostate cancer. Prostate 2008; 68: 152–160.
9. Crasta K, Ganem NJ, Dagher R, Lantermann AB, Ivanova EV, Pan Y, Nezi L, Protopopov A, Chowdhury D, Pellman D. DNA breaks and chromosome pulverization from errors in mitosis. Nature 2012; 482: 53–58.
10. Baca SC, Prandi D, Lawrence MS, Mosquera JM, Romanel A, Drier Y, Park K, Kitabayashi N, MacDonald TY, et al. Punctuated evolution of prostate cancer genomes. Cell 2013; 153: 666–677.
11. Smith SS. Maintaining the unmethylated state. Clin Epigenetics 2013; 5: 17.
12. Maki J, Robinson K, Reguly B, Alexander J, Wittock R, Aguirre A, Diamandis EP, Escott N, Skehan A, et al. Mitochondrial genome deletion aids in the identification of false- and true-negative prostate needle core biopsy specimens. Am J Clin Pathol. 2008; 129: 57–66.
13. Ahrens MJ, Bertin PA, Vonesh EF, Meade TJ, Catalona WJ, Georganopoulou D. PSA enzymatic activity: A new biomarker for assessing prostate cancer aggressiveness. Prostate 2013; 73: 1731–1737.
14. Kline EE, Treat EG, Averna TA, Davis MS, Smith AY, Sillerud LO. Citrate concentrations in human seminal fluid and expressed prostatic fluid determined via 1H nuclear magnetic resonance spectroscopy outperform prostate specific antigen in prostate cancer detection. J Urol. 2006; 176: 2274–2279.
15. Zaichick V, Sviridova TV, Zaichick SV. Zinc in the human prostate gland: normal, hyperplastic and cancerous. Int Urol Nephrol. 1997; 29: 565–574.

The authors
Jennifer Linehan MD, Jonathan Yamzon MD, Timothy Wilson MD, and Steven Smith* PhD
NanoLab, Division of Urology, City of Hope, Duarte, California, USA

*Corresponding author
E-mail: ssmith@coh.org

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