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Benzoxazinoids in Prostate Cancer Patients after a Rye-Intensive Diet: Methods and Initial Results Stine Krogh Steffensen, Hans Albert Pedersen, Khem B. Adhikari, Bente Birgitte Laursen, Elena-Claudia Jensen, Søren Høyer, Michael Borre, Helene Holm Pedersen, Mette Borre, David Edwards, and Inge S. Fomsgaard J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b03765 • Publication Date (Web): 10 Oct 2016 Downloaded from http://pubs.acs.org on October 17, 2016

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Benzoxazinoids in Prostate Cancer Patients after a Rye-Intensive Diet: Methods and Initial Results Stine K. Steffensena*, Hans A. Pedersena, Khem B. Adhikaria, Bente B. Laursena, Claudia Jensena, Søren Høyerb, Michael Borrec, Helene H. Pedersenc, Mette Borred, David Edwardse, Inge S. Fomsgaarda. a

Department of Agroecology, Aarhus University, Forsøgsvej 1, DK-4200 Slagelse, Denmark.

b

Department of Pathology, Aarhus University Hospital, Nørrebrogade 44, DK-8000 Aarhus

C, Denmark c

Department of Urology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, DK-

8200 Aarhus N, Denmark d

Department of Medicine V (Hepatology and Gastroenterology), Aarhus University Hospital,

Nørrebrogade 44, DK-8000 Aarhus C, Denmark e

Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, DK-

8830 Tjele *Corresponding author: [email protected] Short title: Benzoxazinoids in Prostate Cancer Patients after a Rye-Intensive Diet

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Abstract

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Rye bread contains high amounts of benzoxazinoids and in vitro studies have shown

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suppressive effects of selected benzoxazinoids on prostate cancer cells. Thus research into

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benzoxazinoids as possible suppressors of prostate cancer is demanded. A pilot study was

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performed in which ten prostate cancer patients received a rye-enriched diet one week prior

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to prostatectomy. Plasma and urine samples were collected pre- and post-intervention. Ten

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prostate biopsies were obtained from each patient and histologically evaluated. The biopsies

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exhibited concentrations above the detection limit of seven benzoxazinoids ranging from 0.15

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to 10.59 ng/g tissue. An OPLS-DA analysis on histological and plasma concentrations of

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benzoxazinoids classified the subjects into two clusters. A tendency of higher benzoxazinoid

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concentrations towards the benign group encourages further investigations. Benzoxazinoids

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were quantified by an optimized LC-MS/MS method and matrix effects were evaluated. At

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low concentrations in biopsy and plasma matrices the matrix effect was concentration-

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dependent and non-linear. For the urine samples the general matrix effects were small but

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patient-dependent.

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Keywords:

Benzoxazinoid, Prostate cancer, Matrix effect, Tissue, LC-MS/MS

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17

 INTRODUCTION

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Globally, prostate cancer accounts for about 15% of all new cancers diagnosed among

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males.1 The age-standardized incidence of prostate cancer in Denmark is 138 per 100,000,

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which is comparable to other European Union countries and the USA (106 and 129 per

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100,000, respectively).2-4 However, as the elderly population increases, the prevalence of

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prostate cancer is expected to increase dramatically in the coming decades. The dominant

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type of prostate cancer is adenocarcinoma, an endocrine tumor. Despite treatment through

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androgen deprivation, most patients eventually experience disease progression within a

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median of 18-24 months.5

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Rye wholegrain and bran intake has shown beneficial effects on prostate cancer progression

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in animal models and humans, including lower tumor rates, smaller tumor volumes, and

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reduced prostate-specific antigen (PSA) concentrations.6-8 The relationship to the ingredients,

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however, was not investigated. The presence of benzoxazinoids, including the subgroups

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benzoxazolinones, lactams, and hydroxamic acids (see Figure 1) in rye grains and pretreated

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wheat and food products derived from these was reported recently.9-14 Benzoxazinoids have

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various potential pharmacological and health-protecting properties, which have been

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reviewed recently.15 The benzoxazinoid 2,4-dihydroxy-1,4-benzoxazin-3-one (DIBOA)

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inhibited the growth of the cancerous prostate cell line DU145.16, 17 Roberts et al.18 suggested

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that this effect was due to the ability of DIBOA to induce cell death. The reported

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suppressive effects of rye intake on prostate cancer, the newly discovered presence of

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benzoxazinoids in rye grains and the in vitro inhibition by DIBOA of prostate cancer cell

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growth, all provide compelling reasons for investigating the effect of a benzoxazinoid-

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containing rye-based diet on human prostate cancer.

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We have reported earlier that dietary benzoxazinoids are bioavailable in pigs, rats, and

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humans,12, 19, 20 but the extent to which benzoxazinoids are distributed to tissues in the human

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body has not yet been investigated.

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Analytical methods for the quantification of benzoxazinoids in plants and soil using LC-

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MS/MS have been presented in several studies.21-23 In 2012, we first analyzed the

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benzoxazinoid content of plasma and urine,12, 19 and several studies have since been

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published on benzoxazinoids and their derivatives in either plasma or urine.15, 20, 24-27 The aim

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of this initial study was to develop the analytical methodology for analysis of benzoxazinoids

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in minute amounts of tissue obtained from prostate biopsies, to elucidate the role that matrix

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effects play in the analysis of benzoxazinoids in biological samples, to present the first results

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ever on the occurrence of benzoxazinoids in prostate tissue in men after a week on a high-rye

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diet, and to examine the preliminary correlation between histological data and benzoxazinoid

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concentrations in plasma, urine, and tissue. Based on the results of this study, a full cross-

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over study will be planned.

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54

 MATERIALS AND METHODS

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Chemicals

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HPLC-grade acetonitrile and methanol (Rathburn, Walkerburn, Scotland), glacial acetic acid

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(Chromanorm, VWR, Fontenay-sous-Bois, France) and ultra-pure water (Milli-Q Advantage

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A10 with LC-pack, Merck Millipore, Darmstadt, Germany) were used for all sample

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preparations. LC-MS grade acetonitrile and Optima grade acetic acid (Fisher Scientific,

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Denmark) were used for analyses. The benzoxazinoid and phenoxazinone standards

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(systematic names and formulas in Figure 1) were obtained as described by Adhikari et al.20

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Inclusion Criterion and Recruitment

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Prostate cancer patients scheduled for radical prostatectomy were invited with a brief

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explanation from the project nurse to participate in this study, and in total, 10 patients were

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enrolled. The inclusion criterion was the presence of more than 10% cancerous tissue in at

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least one diagnostic needle biopsy of the enlarged prostate.

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Study Design and Sampling

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All 10 patients received a high-benzoxazinoid diet and subsequently had a consultation (Visit

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1) with the project dietician, who provided detailed information and instructions concerning

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the diet (see below) and how to keep a diet diary. At Visit 1, the patients were asked to

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provide blood and urine samples. Each patient would begin a high-benzoxazinoid diet one

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week prior to the scheduled prostatectomy. At Visit 2 (the day of the prostatectomy), the

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patient would bring a 24-hour urine sample and new blood samples (5 x 10 mL) would be

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obtained prior to the prostatectomy. The study was approved through the Danish Ethical

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Committee, Protocol no. 1-10-72-177-13.

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Diet

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The diet was designed to have a high content of benzoxazinoids based on the chemical

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analyses of bread and other cereal products presented in Steffensen et al. (in preparation)28 in

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the same manner used in our previous clinical study.29 Two types of rye bread were provided,

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as were rye flakes (“Rugflager”, Urtekram, Denmark) for the easy preparation of porridge.

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The first type of rye bread (“Multikerne rugbrød”, Schulstad, Denmark) was a loaf baked

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from rye kernels, whole-grain rye flour, sifted rye flour, barley malt, and wheat flour, and the

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second (“Rugfler”, Hatting, Denmark) was a bun baked from whole-grain rye flour with flax,

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sunflower, and pumpkin seeds. The patients were asked to consume a minimum amount of

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75-100 g of rye flakes, 3 slices of rye bread and 2 buns per day and to register their intake in

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a diet diary. Using a scoring system, the patients were offered the possibility of exchanging

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products without lowering the desired minimum intake of benzoxazinoids. The patients were

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allowed to consume any other food products according to their normal habits and tastes, with

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the exception of wheat and oats.

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Urine, Plasma and Tissue Samples

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The urine samples were obtained in beakers at Visit 1 and in 3-L containers for 24 hours prior

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to Visit 2. The samples were aliquoted and stored at -80°C until analysis. Furthermore, all

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urine samples were analyzed for creatinine at the Department of Clinical Biochemistry at

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Aarhus University Hospital in order to normalize the benzoxazinoid concentration across

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varying urine volumes.30 Blood was drawn in heparinized tubes, incubated for 30 min and

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subsequently centrifuged for 10 min at 2000 g (2.0 rcf) at room temperature to separate the

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plasma. The plasma samples were aliquoted and stored at -80°C until analysis. Using 18 G

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Bard Max-Core bioptomes, five random needle core biopsies were sampled from each lobe of

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the prostatectomies for histological and chemical analysis. Each biopsy was immediately

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placed in TissueTek (Sakura Finetek Europe B.V., Alphen aan den Rijn, The Netherlands) in 6 ACS Paragon Plus Environment

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a cryo vial, snap-frozen in liquid nitrogen and stored at -80˚C. An HE-stained 4-µm

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cryosection was cut from each core for histological assessment prior to the chemical analysis.

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The prostatectomies were processed for conventional histopathological analysis. An

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experienced pathologist microscopically assessed each core, and malignant infiltrations were

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assigned a Gleason score according to the ISUP 2005 guidelines.31

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Chemical Analysis of Metabolites in Urine, Plasma and Tissue Samples

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Preparation of plasma and urine samples:

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Plasma and urine samples were purified prior to benzoxazinoid analysis using our previously

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published methods.12 The SPE-cleaned urine and plasma extracts were diluted 1:3 with water

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and filtered using a KX syringe filter from Kinesis (PTFE, 13 mm, 0.22 µm, Mikrolab,

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Aarhus, Denmark) prior to injection into the LC-MS/MS.

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Preparation of the prostate biopsy samples:

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The tissue extraction method was developed using prostate tissue from mini-pigs (Ellegaard

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Göttingen Minipigs, Dalmose, Denmark) due to the limited supply of human tissue. Upon

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euthanasia the pig prostates were removed, bagged, frozen using dry ice and stored at -20°C

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until further use. The pig prostate biopsies were taken from the frozen tissue using a 1.0-mm-

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diameter biopsy punch with a plunger (Miltex GmbH, Reitheim-Weilheim, Germany). The

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biopsies were submerged in TissueTek and left at -80°C overnight to mimic the storage of

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human prostate tissue, thawed, transferred from the TissueTek to the extraction vials, and

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spiked with 5 µL of 200 ng/mL standard solution, weighing every step for control. After the

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solvent was evaporated, the samples were extracted. We tested several extraction methods

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such as shaking, sonication, and accelerated solvent extraction (ASE) in combination with a

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variety of extraction solvents containing either water, methanol, acetonitrile, or a mixture of

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these, acidified or neutral. The optimum results as a compromise between recovery and 7 ACS Paragon Plus Environment

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matrix effect were obtained by 30 min sonication in 20% acetonitrile and 0.5% acetic acid in

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water in a small glass vial using 500 µL for each biopsy. Prior to analysis, the extracts were

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filtered using a Kinesis KX syringe filter (PTFE, 4 mm, 0.22 µm). The human tissue samples,

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10 from each of 10 patients, having a mean weight of 5.6 mg, were extracted using this

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method. The recovery, limit of detection (LOD) and limit of quantification (LOQ) were

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determined in 6 replicate pig prostate samples following The International Council for

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Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH)

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harmonized tripartite guidelines for validation of analytical procedures.32 The determination

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of recovery in spiked pig prostate samples was performed for three different standard

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solutions containing standard compounds combined in groups that underwent no detectable

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interconversion. The groups are indicated in Figure 1.

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Instrumentation:

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The chemical analysis of the benzoxazinoids was performed using an Agilent (Glostrup,

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Denmark) 1260s HPLC system coupled to a Sciex (Copenhagen, Denmark) QTRAP 4500

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mass spectrometer equipped with electrospray ionization source. The compound dependent

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MS settings (declustering potential, collision energy, and collision cell exit potential) were

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optimized through direct infusion for maximum signal intensity in multiple reaction

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monitoring (MRM) mode. The resulting MRM transitions (Q1/Q3) and parameters are shown

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in Figure 1. The analytical method was divided into periods for optimized intensity (Figure

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1 and Table 1) and the general mass-spectrometric parameters (nebulizer gas, drying gas,

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curtain gas, temperature, and ion spray voltage) were optimized individually using flow

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injection analysis via the autosampler and HPLC flow. The analytes were separated using a

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Phenomenex (Allerød, Denmark) Synergi Polar RP-80A column (250 × 2 mm, 4 µm particle

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size), flow rate: 300 µL min-1; injection volume: 10 µL; column oven: 30.0°C; autosampler

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tray: 10°C. The wash vial contained a 1:1 acetonitrile/water solution. Analyst 1.6.2 software 8 ACS Paragon Plus Environment

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from Sciex (Copenhagen, Denmark) was used for instrument control, data acquisition, and

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subsequent quantifications. Data points of the standard curves were weighted according to x-

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1

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78% acetonitrile in water (v/v). Both solvents A and B contained 20 mM acetic acid. The

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optimized chromatographic method and instrument settings are listed in Table 1. The

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chromatographic method allowed sufficient separation of most of the compounds of interest

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in a single acquisition method (Figure 2).

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Investigation of the instrument detection limit:

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The instrument detection limit (IDL) was determined as a measure of the instrument

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performance of the analytical system33 at the concentration where peak height ≥ 2*S/N (S/N

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denotes the signal-to-noise ratio).32 The S/N ratio was calculated using the “Analyte signal to

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noise” feature in the Analyst software and dividing this value by 4 to cover 95% of the noise,

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assuming the noise is normally distributed. Low-concentration standard solutions of the

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different standard mixtures at different dilutions were injected six times in random order in

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order to measure the IDLs.

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Investigation of matrix effects:

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During optimization of the chromatographic method, the matrix effects of solvent and sample

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blanks were investigated through the infusion of a mixed standard solution (16.0 ng/mL, 7.0

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µL/min) into the HPLC stream to separate major matrix-effect contributors from target

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analytes chromatographically.34, 35

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The remaining matrix effect was individually determined for urine, plasma, and prostate

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tissue. For each sample type, six mixed standard curves were prepared in parallel, three

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curves in solvent and three curves in blank sample extracts of the same dilution as the

. The gradient was mixed from two eluent flasks: A, 7% acetonitrile in water (v/v), and B,

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corresponding sample matrices. Each of these standard curves had five dilution points,

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covering the range of sample concentrations for the given sample type. The three standard

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curves in sample extract were performed in blank samples from three different patients to

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evaluate the presence of matrix effect differences between different patients within the same

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matrix type (internal matrix effect) and the general matrix effect for each sample type

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according to Matuszewski et al.36 The matrix effects were investigated at concentration

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ranges from 100 to 0.391 ng/mL for urine and 1.60 to 0.00625 ng/mL for both prostate tissue

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and plasma extracts. The dilution series was prepared by adding 30 µL of a higher

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concentration to 90 µL of blank extract to form the next point in the series. Prior to analysis,

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the serial dilutions were filtered.

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Calculations and Statistics

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Matrix effect evaluation:

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The presence of an internal matrix effect within each matrix type was tested using Bartlett’s

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test for homogeneity of variance. The variance in triplicate standard dilutions in the matrix

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was tested against the triplicates in the solvent using a square-root transformation to

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normalize the variance across dilution points.

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The presence of a general matrix effect was investigated for each matrix type. The triplicate

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standard curves were prepared in both solvent and sample matrices. Two additive models

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were used to fit quadratic standard curves to the data points: The first model fitted one curve

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to all six replicates while the second model fitted two curves: one for the three replicates in

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solvent and one for the three replicates in sample matrix. The two models were compared

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using ANOVA to determine whether the second model was a significantly better fit than the

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first, thereby confirming the presence of a matrix effect. To determine a general numeric

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value for the matrix effect of each compound in each matrix, the standard curves in the

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matrix and in the solvent were integrated, and the matrix effect was calculated according to

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Equation 1 over the range of the standard dilution in question:

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    =

(1)

     

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− 1.

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Tests were performed using R version 3.2.1 statistical program.

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An attempt was made to correct the quantification data for matrix effects using the two

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triplicate sets of standard curves and Equation 2, where concquant is the quantified

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concentration; concactual is the actual concentration; a, b, and c are coefficients of the terms of

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the function in the absence of matrix; p, q, and r are correction factors to take into account the

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matrix effect; and m = 1 or 0 depending on the presence or absence of matrix.

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(2) 



= ( + # × %) ×   ' + (( + ) × %) ×   + ( +

 × %)

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The 95% confidence intervals were obtained for both curves within each model using the

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“predict” function of the stats package, and the root mean square prediction error (RMSPE)

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was obtained using the “cvTools” package to perform a six-fold validation, leaving out one of

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each of the six standard curve replicates (three with and three without matrix). For each

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model, RMSPE, standard curves, parameter values, and confidence intervals for both curves

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and parameters are given in Supporting Table 1.

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Multivariate data analysis:

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Histological scores of the human prostates were combined with the quantitative results of the

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targeted benzoxazinoid analysis of the biopsies, plasma, and urine samples of the human

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subjects, and then subjected to multivariate data analysis to differentiate the variables

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between the benign and malignant cell groups of the prostate biopsies. The variables were

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mean-centered and scaled to unit variance prior to analysis using SIMCA 14 software

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(Umetrics, Umeå, Sweden). Principal component analysis (PCA) was applied to evaluate the

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overall structure of the data without considering any group information. After observing the

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pattern of group differences between cell types in the PCA score plot, orthogonal partial least

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squares discriminant analysis (OPLS-DA) was performed on data to identify discriminant

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variables between the two cell groups. The quality of the models was evaluated through the

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R2Y(cum) and Q2(cum) parameters. The OPLS-DA model was validated through the analysis

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of the variance of cross-validated predictive residuals (CV-ANOVA), and the model was

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considered valid when the p-value was lower than 0.05.37 The loading-line plots, variable

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importance for projection (VIP), and S-plots generated from the model were used to visualize

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the relative importance of different variables.

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 RESULTS AND DISCUSSION

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Histology

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The results of the microscopic evaluation of the perioperative needle core biopsies and the

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prostatectomies are shown in Table 2. A total of 10 biopsies were available from each of the

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10 patients, with five biopsies being from each lobe. Acinar adenocarcima was observed in

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three patients. The number of malignant cores was one core in patient 1, five cores in patient

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9, and two cores in patient 10. The Gleason score in each core was 4+3=7, 3+5=8 and 3+4=7,

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respectively. The Gleason scores matched the global Gleason score of each prostatectomy.

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The estimated volume of carcinoma varied from 5% to 55% in the prostatectomies. The pT

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stage38 was pT2a in two prostatectomies indicating less than 50% carcinoma in one lobe and

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pT2c in eight prostatectomies indicating carcinoma in both prostate lobes.

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Diet Adherence

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Adherence was generally good for the short intervention period according to the dietary

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records provided by the patients; however, some individuals complained about the large

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quantities of rye consumed and the concomitant side effects, such as flatulence. These

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findings should be considered as possible constraints on full adherence in future, longer

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dietary interventions.

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Method Validation of the Chemical Analysis

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Instrument detection limit:

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The instrument detection limit (IDL) is given as the mean concentrations, and S/N is

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measured for each analyte at the dilution level, where all signals had S/N ≥ 2 (Table 3). Thus

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the instrument was sensitive enough to measure picogram levels of compounds in 1 mL of

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solvent.

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In general, the Analytical Methods Committee33 has recommended the investigation of the

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limit of detection (LOD) in a blank sample; however, the complexity of the sample matrices

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in this study and the possibility of internal matrix effects (see below) would provide an LOD

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containing variation from the instrument performance, the matrix effects, and the sample

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preparation procedures. This complexity would not contribute to the clarity of the overall

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results, as the cause of systematic and random errors would remain unclear; hence, in this

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case, IDL was preferred to classic LOD. Notably, the IDL is a measure used to describe the

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performance of the analytical instrument: It is the lowest concentration at which an observed

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peak can be taken as a true peak, rather than noise, with 95% certainty. It is not, however, the

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concentration at which a true peak is first observed. Compounds can be detected at

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concentrations well below the IDL, although the certainty of these measurements is lower

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than that of the measurements above the IDL. The standard curves for quantifying the plasma

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and biopsy extracts descend to concentrations around or below the IDL values reported in

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Table 3. This finding is in accordance with the recommendations of the Analytical Methods

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Committee,33 which state that measures lower than the detection limit should not be omitted

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when performing multivariate statistical analysis of a dataset, as the low-concentration

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samples might contain important information and omitting them might introduce bias. The

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aim of our upcoming crossover study is to compare high and low concentrations to

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investigate correlations between the benzoxazinoid content and prostate cancer scores for the

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patients. Therefore, concentrations are measured as low as possible by visual inspection. To

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minimize the uncertainty of these low-concentration measurements, standard curves are used

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that approach the visual limit of detection. The random errors in these measurements are not a

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problem, as the statistical models focus on systematic and not random variations.

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Matrix effects:

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The matrix effects were treated in a two-step procedure, as suggested by Van Eeckhaut et

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al.39 Firstly, during method development, matrix effects were detected by infusing an analyte

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solution into a blank sample stream, resulting in negative peaks when a critical matrix effect

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was present. Subsequently, the chromatographic method was adjusted to minimize co-elution

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of analytes and matrix components. This was done for all three sample matrix types.

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Secondly, after method development, the residual matrix effect was determined by

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comparison of triplicate standard curves in solvent to triplicate standard curves in biopsy

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extracts, plasma extracts, and urine extracts. Different patient sample lots were used for each

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replicate to investigate both general as well as internal matrix effects.

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Despite measures to reduce matrix effects during method development and sample

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pretreatment, matrix effects were observed to some extent for most analytes in all three

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matrices. The size and shape of the curves, however, differed between analytes, matrix types,

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and concentration ranges. Figure 3 shows an example of a standard curve in solvent and in

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matrix for a) biopsy extracts, b) plasma extracts, and c) urine extracts. The matrix effect was

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dependent on concentration and was positive at low concentrations for most analytes but

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gradually decreased and became negative at higher concentrations. The non-linear change in

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the matrix effect indicated that the electrospray ionization depended on more than one

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mechanism, with one mechanism being more important at low analyte concentrations, while

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another mechanism was more important at high concentrations. To our knowledge this

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concentration dependence has not previously been demonstrated. A detailed list of dilution

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points for matrix and solvent curves and variations can be found in Supporting Table 2. A

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summary of the matrix effects can be found in Table 3. The general matrix effects indicated

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were calculated using Equation 1 and hence, do not reflect the concentration-dependent

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variations. The presence of a general matrix effect was tested by ANOVA, and the level of

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significance is marked by an asterisk (*) in the table. The ANOVA tests showed significant 15 ACS Paragon Plus Environment

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matrix effects for most analytes in the three matrices. Most matrix effects for the urine

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extracts were negative; but, the values for most analytes were numerically small, indicating

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that the matrix effect in these cases introduced only a minor inaccuracy to the result. The

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matrix effects were generally positive for both biopsy and plasma extracts, although plasma

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in particular exhibited a shift from a positive to a negative matrix effect with increasing

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concentration, explaining why the mean-like values of the general matrix effect, shown in

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Table 3, were low for plasma, while the ANOVA showed a significant matrix effect. These

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results clearly demonstrate that elucidating matrix effects only through infusion of standard

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compounds into a blank sample stream, or only determining the matrix effects at one

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concentration is not sufficient to describe the accuracy of an analytical system in term of the

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matrix effects.

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The internal matrix effect was investigated by testing whether the variance of the dilution

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points of the standard curve was larger in the matrix than in the solvent and the results are

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listed in Table 3. For the urine extract, almost all analytes exhibited an internal matrix effect

316

in the examined concentration range, decreasing the overall precision of the quantification in

317

urine. The biopsy and plasma extracts exhibited few significant signs of internal matrix

318

effects, but at these low concentrations the normal variation of the method might disguise an

319

internal matrix effect when present.

320

As shown above, it is recommendable whenever possible to use matrix-matched standard

321

curves in the analysis of complex samples. However due to insufficient matrix material and

322

the presence of internal matrix effects, analytes like the benzoxazinoids examined in this

323

study had to be quantified against standard curves prepared only in solvent. We investigated

324

whether the triplicate standard curves in solvent and matrix could be used for correcting data

325

for matrix effect. For each of the combinations of 16 compounds × 3 matrices, a model giving

326

two quadratic curves was created to describe the quantified concentration (concquant) as a 16 ACS Paragon Plus Environment

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327

function of the actual concentration (concactual) in the solvent and in the matrix according to

328

Equation 2 (see Supporting Table 1). Estimated concentrations and their 95% confidence

329

intervals were found by solving the equations. The confidence intervals, however, were only

330

acceptable for some compounds and the approach was therefore abandoned.

331

Recovery of benzoxazinoids spiked to prostate tissue:

332

The recovery experiments were performed in pig prostate tissue as sufficient human prostate

333

tissue was unavailable. Biopsies were obtained from the pig tissue to mimic human samples,

334

then spiked and subsequently extracted as described above. Due to the small sample sizes,

335

extra efforts were undertaken to reduce variations due to lab procedures. Therefore, the

336

biopsies, spiking solutions, and the extraction solvent were weighed to correct for variations

337

in the pipetting procedure. The results of the recovery experiment are shown in Supporting

338

Table 3 both before and after correction for variance in the pipetting procedure. These results

339

showed that in most cases, as the recovery percentage increases, the variation decreases when

340

the weight of the pipetted solutions is accounted for. Pipetting thus introduces both

341

systematic and random errors to the analysis results. The accuracy expressed as recovery

342

percentage for most of the compounds was within or close to the range of 80-120% set by the

343

ICH harmonized tripartite guideline for analytical procedures validation.32 The precision of

344

this analytical method as measured by the coefficient of variation (CV) was in the range of 4-

345

13% (Supporting Table 3) demonstrating the high precision of the method.

346

To determine whether the recovery was dependent on the mass of the individual biopsies,

347

these data (not shown) were plotted against each other; however, no significant correlation

348

was observed.

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349

Benzoxazinoid Content of Prostate Tissue

350

The quantification data for the prostate tissue biopsies from the patients after one week on an

351

intensive rye diet is shown in Figure 4a. The prostate tissue of patients 6 and 8 had

352

significantly higher benzoxazinoid content (>2.6 ng/g tissue) than that of the other patients

353

(2. In urine, several methoxylated benzoxazinoids

422

were observed at low concentrations, indicating that these compounds were both absorbed

423

and excreted, although they were not detected in plasma and prostate tissue samples. Small 20 ACS Paragon Plus Environment

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424

amounts of the phenoxazinones 2-aminophenoxazin-3-one (APO) and 2-

425

acetylaminophenoxazin-3-one (AAPO), which are degradation products of benzoxazinoids,42

426

were primarily detected in the urine samples from post-intervention samples. It was not

427

possible, however, to establish whether these transformation products were formed in the

428

body or after delivery of the urine sample. APO forms from 2-aminophenol, a hydrolysis

429

product of BOA or HBOA, and this reaction spontaneously occurs in the presence of oxygen

430

and is catalyzed by microbial enzymes.42 The transformation of APO into AAPO is unlikely

431

to occur spontaneously in urine and is therefore an indicator of biological transformation.

432

This reaction could, however, reflect microorganisms deposited in the urine sample during

433

the 24-h sampling period in the patient’s home.

434

OPLS-DA analysis resulted in a 1+1 OPLS model with R2Y(cum) and Q2(cum) values of

435

0.71 and 0.27, respectively, illustrating the poor predictivity of the model (Figure 8a), which

436

was not unexpected in this short pilot study. This may have been due to the short intervention

437

period and few patients in the malignant cell group. Thus, despite the poor predictivity of the

438

discriminant analysis of the variables between the two cell types in this pilot study, a longer

439

intervention study with more patients could be relevant. The observations spread over the

440

vertical direction and separated along the orthogonal component t0 [1] showed variation

441

before and after the intervention. Histological data were the most discriminant variables

442

contributing to the differentiation of the malignant carcinoma group from the benign cell

443

group (Figure 8b). As in plasma, most benzoxazinoids were correlated with the benign cell

444

group. The negative correlation of benzoxazinoids and histological data suggested that

445

benzoxazinoids might play a role in carcinoma progression, thereby requiring a longer-

446

duration intervention study.

447

The inhibiting effect of consumption of wholegrain rye on prostate cancer is of great potential

448

in public health management. However, causality must first be established, in order to take 21 ACS Paragon Plus Environment

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Journal of Agricultural and Food Chemistry

449

full advantage of the potential of rye-based food products. Rye phytochemicals are likely

450

candidates, and the benzoxazinoids must be considered prime suspects, as they have

451

previously shown anti-prostate cancer activity in in vitro experiments. We have established a

452

comprehensive methodology for testing this hypothesis by analyzing the benzoxazinoids in

453

prostate biopsies in addition to urine and plasma samples. The benzoxazinoids were

454

detectable in urine and plasma as a picture of the dynamic metabolic processes in the body.

455

Most interestingly, the benzoxazinoids, which were also detectable in prostate tissue after

456

prostate cancer patients had spent just one week on a rye-enriched diet, could cause a direct

457

effect on the prostate tissue following long-term dietary exposure. Our preliminary statistical

458

results indicated an inverse correlation between the concentrations of benzoxazinoids and

459

histological data of malignant tissue in the prostatectomies, but more research is still needed

460

to confirm these indications. Causality testing requires robust analytical methods. Elaborate

461

matrix effect studies is a way to test both accuracy and precision of such analytical methods.

462

Furthermore, the elucidation of inter-patient matrix effects may also reveal a source of

463

causalities indicated by statistics and should always be considered before final conclusions

464

are made. We show that matrix effects exhibit complicated patterns and that simplistic matrix

465

effect testing will not give a good indication of the true influence of the sample matrix.

466

 ASSOCIATED CONTENT

467

Supporting Information

468

Detailed list of dilution points for matrix and solvent standard curves and variations

469

(Supplementary Table 1), model parameters of matrix effect analysis (Supplementary Table

470

2), and recovery analysis (Supplementary Table 3) (PDF).

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471

 AUTHOR INFORMATION

472

Corresponding Author

473

Email: [email protected]. Phone: (45) 87158178. Fax: (45) 87156082

474

Funding

475

This study was conducted as part of the project “Whole grain rye as a functional food for

476

suppression of prostate cancer - elucidating the role of benzoxazinoids and other bioactive

477

constituents” (RyeproC) and generously funded through the grant 0602-02416B from the

478

Danish Council for Independent Research, Technology and Production (FTP).

479

Notes

480

Inge S. Fomsgaard is listed as co-inventor on the patent application, PA 84245 "Use of

481

benzoxazinoids-containing cereal grain products for health-improving purposes". The

482

remaining authors have no conflicts of interest.

483

The authors declare no competing financial interest.

484

 ACKNOWLEDGMENTS

485

The authors would like to thank Ellegaard Göttingen Minipigs A/S (Dalmose, Denmark) for

486

supplying pig tissue for method development, CytoTrack ApS (Lyngby, Denmark) for

487

running the circulating tumor cell screenings, and Lantmännen (Stockholm, Sweden) for

488

supplying bread for the diets.

489

 ABBREVIATIONS USED

490

AAPO, 2-acetylaminophenoxazin-3-one; APO, 2-aminophenoxazin-3-one; BOA,

491

benzoxazolin-2-one; DIBOA, 2,4-dihydroxy-1,4-benzoxazin-3-one; DIBOA-glc, 2-β-D-

492

glucopyronosyloxy-4-hydroxy-1,4-benzoxazin-3-one; DIMBOA-glc, 2-β-D-

493

glucopyranosyloxy-4-hydroxy-7-methoxy-1,4-benzoxazin-3-one; HBOA, 2-hydroxy-1,423 ACS Paragon Plus Environment

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Journal of Agricultural and Food Chemistry

494

benzoxazin-3-one; HBOA-glc, 2-β-D-glucopyronosyloxy -1,4-benzoxazin-3-one; HMBOA,

495

2-hydroxy-7-methoxy-1,4-benzoxazin-3- one; HMBOA-glc, 2-β-D-glucopyranosyloxy-7-

496

methoxy-1,4-benzoxazin-3-one; CV-ANOVA, analysis of variance of cross-validated

497

predictive residuals; IDL, instrument detection limit; MRM, multiple reaction monitoring;

498

OPLS-DA, orthogonal partial least squares discriminant analysis; PCA, principal component

499

analysis; RMSPE, root mean square prediction error.

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500

References

501

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502

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631

Figure caption

632

Figure 1

633

The benzoxazinoids and phenoxazinones. Compound abbreviations, structural information, chemical

634

names, mass spectrometric parameters, and analytical groups. Q1/Q3: Mother/daughter ion mass

635

transition; DP: Declustering potential; CE: Collision energy; CXP: Collision cell exit potential.

636

Figure 2

637

MRM chromatograms of benzoxazinoid and phenoxazinone standards at a concentration of 50 ng/mL.

638

The MBOA peak is cut off due to scaling up or low-intensity peaks such as DIBOA. Retention times

639

are given in parentheses. Signal intensity is given in counts per second (cps).

640

Figure 3

641

Standard curves in matrix versus standard curves in solvent for DIBOA-glc in the three different

642

sample matrices. This example is representative of the general tendencies for all analytes in the three

643

matrices. Solid line and black points: standard curve in matrix. Dashed line and white points: standard

644

curve in solvent.

645

Figure 4

646

Benzoxazinoid content of prostate tissue. a) Mean content of each benzoxazinoid in prostate tissue

647

from each patient. Data from peaks where S/N > 2 or where compounds were present in only one

648

biopsy were excluded. b) Relative contributions of individual biopsies to the total benzoxazinoid

649

content for each patient. Ten biopsies were taken from each patient. Asterisks indicate biopsies

650

containing malignant tissue.

651

Figure 5

652

Pre- and post-intervention content of benzoxazinoids and phenoxazinones in plasma.

653

Figure 6

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Journal of Agricultural and Food Chemistry

654

Tentative correlations between plasma benzoxazinoids and histological data for prostate cancer

655

patients. a) OPLS-DA score plot for plasma samples showing a benign (green circle) and malignant

656

(blue circle) group. Statistical parameters for the 1+2 OPLS-DA model were R2X = 0.78, R2Y = 0.83,

657

Q2 = 0.65, p[CV-ANOVA] = 0.01 b) OPLS-DA loading plot for plasma samples.

658

Figure 7

659

Pre- and post-intervention content of benzoxazinoids and phenoxazinones in urine. The 24h post-

660

intervention urine sample for patient 4 was not collected, and is therefore absent.

661

Figure 8

662

Tentative correlations between urine benzoxazinoids and histological data for prostate cancer patients.

663

a) OPLS-DA score plot for urine samples showing separation of a benign (green circle) and malignant

664

(blue circle) group. Statistical parameters for the 1+1 OPLS-DA model were R2X = 0.53, R2Y = 0.71,

665

Q2 = 0.27, p[CV-ANOVA] = 0.31 b) OPLS-DA loading plot for urine.

32 ACS Paragon Plus Environment

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Tables Table 1. Time table for the chromatographic and instrument settings for the LC-MSMS method. Time (min) Eluent B (%) LC stream Acquisition period (min) Ionization mode Curtain gas (psi) Ion spray voltage (V) Entrance potential (V) Temperature (°C) Drying gas (psi) Nebulizer gas (psi)

0 0

1 8

2

3 4 5 10 to waste 0.0-8.4

6

7

8

9

10

11

8.4-11.3

12

13 14 70 90 to MS 11.3-15.0

negative 20 -4500 -2 550 85

450 50

15

16 90

17 0

18

19

20

21

22

23 0

to waste 15.0-23.0 positive 40 4500 5 500 60

90

33

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Table 2. Histological data of the prostate tissues of the patients involved in the study Needle core biopsies a

Prostatectomy Histological Data

Biopsy No. 1 2 3 4 5 6 7 8 9 10 % Carcinoma Gleason score pT

a

Patient 1

BM B B B B B B B B

30

4+3

pT2c

Patient 2

BB B B BBB BB B

5

3+4

pT2a

Patient 3

BB B B BBB BB B

30

3+4

pT2c

Patient 4

BB B B BBB BB B

15

4+3

pT2c

Patient 6

BB B B BBB BB B

25

4+3

pT2c

Patient 7

BB B B BBB BB B

15

3+3

pT2c

Patient 8

BB B B BBB BB B

20

4+3

pT2c

Patient 9

B B M B MBMMBM

30

3+5

pT2c

Patient 10 B B B M B B M B B B

55

3+4

pT2c

Patient 11 B B B B B B B B B B

5

3+3

pT2a

B denotes benign prostate cell type, M denotes malignant prostate cell type

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Table 3: Instrument detection limit and matrix effect. Biopsy and plasma matrices were investigated at analyte concentrations of 1.60, 0.400, 0.100, 0.0250, and 0.00625 ng/mL, and urine at 100, 25.0, 6.25, 1.56, and 0.391 ng/mL.

Compound

Solvent

Biopsy

Plasma

Urine

IDLa mean concentration

General

Internal

General

Internal

General

Internal

(ng/mL), [mean S/N]

matrix

matrix

matrix

matrix

matrix

matrix

effect b

effect c

effect

effect c

effect

effect c

HBOA

0.00171 [2.7]

0.08**

0.05***

-0.15***

#

BOA

0.00654 [3.1]

-0.23***

0.03***

-0.25***

###

MBOA

0.00128 [2.4]

-0.39***

-0.02***

-0.18***

#

HMBOA

0.000960 [2.5]

0.02

0.03***

-0.24***

###

DIBOA

0.326 [5.6]

0.16*d

-0.08*** d

-0.10**

DIMBOA

0.311 [2.4]

0.09 d

-0.17*** d

-0.23***

###

HBOA-glc

0.00571 [3.0]

0.19***

0.08***

-0.08**

##

HBOA-glc-hex

0.0117 [2.5]

0.22***

0.12***

-0.04*

##

HMBOA-glc

0.00324 [2.5]

0.22***

0.08***

-0.12***

###

DIBOA-glc

0.00645 [2.9]

0.20***

0.07***

-0.09***

#

DIMBOA-glc

0.0219 [2.9]

0.20***

-0.00***

-0.08*

#

DIBOA-glc-

0.00237 [2.7]

0.26***

0.05***

-0.03*

#

APO

0.00292 [2.7]

0.64***

0.38***

0.00

AMPO

0.00225 [2.2]

0.88***

0.78***

0.02*

AAPO

0.000699 [2.3]

0.28***

0.14**

-0.03

AAMPO

0.000713 [2.6]

0.15*

0.06***

-0.03*

##

#

hex

a

##

IDL = Instrument detection limit. The concentration measured for six injections of a low-concentration

standard solution where all injections had a signal-to-noise ratio (S/N) >2. b

The general matrix effect was calculated as the integrated matrix standard curve divided by the integrated

solvent standard curve minus 1. This value, however, does not reflect intersecting standard curves (Figure 3). Asterisks indicate statistically significant differences between standard curves in matrix and solvent with pvalues denotaed as follows: p < 0.001: ***, 0.001 < p < 0.01: **, 0.01 < p < 0.05: *. c

The presence of an internal matrix effect was confirmed when Bartlett’s test showed that the variance of the

dilution points of the matrix standard curve was significantly greater than that of the solvent standard curve.

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Journal of Agricultural and Food Chemistry

Hashtags indicate statistical significance, with p-values denoted as follows: p < 0.001: ###, 0.001 < p < 0.01: ##, 0.01 < p < 0.05: #. d

Reduced sample set reflecting a higher detection limit.

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Figures Figure 1

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Journal of Agricultural and Food Chemistry

Figure 2 3E+06

HBOA-Glc-Hex (7.49) MBOA (13.83)

DIMBOA-Glc (10.24)

DIBOA-Glc-Hex (7.53)

AAPO (17.51)

3E+06 AAMPO (17.86)

Intensity, cps

DIBOA-Glc (8.81)

HBOA (10.67)

2E+06 HMBOA-Glc (10.09)

2E+06

APO (16.45)

HMBOA (11.79)

HBOA-Glc (8.72)

1E+06

AMPO (16.92) BOA (13.00)

DIBOA (10.58)

5E+05 0E+00 6

8

10

12

14

16

18

20

Time, min

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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