Determination of Amino Acids in Human Pancreas Tissue Sections Using Liquid Chromatography Tandem Mass Spectrometry

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1 Original Paper Determination of Amino Acids in Human Pancreas Tissue Sections Using Liquid Chromatography Tandem Mass Spectrometry Chisato OKAMOTO 1, Hiroo YOSHIDA 1, Akira NAKAYAMA 1, Shinya KIKUCHI 1, Nobukazu ONO 1, Hiroshi MIYANO 1, Yoshinori INO 2, Nobuyoshi HIRAOKA 2,3, Toshimi MIZUKOSHI *1 1 Institute for Innovation, Ajinomoto Co., Inc., 1-1, Suzuki-cho, Kawasaki-ku, Kawasaki , Japan 2 Division of Molecular Pathology, National Cancer Center Research Institute, Tsukiji, Chuo-ku, Tokyo , Japan 3 Department of Pathology and Clinical Laboratories, National Cancer Center Hospital, Tsukiji, Chuo-ku, Tokyo , Japan Abstract A new analytical method was developed for the determination of 35 different amino acids in human pancreas tissue sections embedded in O.C.T. by liquid chromatography tandem mass spectrometry with precolumn derivatization. An AccQ-Tag was selected as a derivatization reagent because it could avoid the ion suppression caused by matrix compounds in the pancreas tissue. This new method uses two different internal standards during the pretreatment processes to achieve good accuracy and high sensitivity, as well as a multiple reaction monitoring time segment program during the acquisition process. This method was fully validated for 35 different amino acids and showed a good linearity of calibration curve (r 2 >0.993), with a lower limit of quantification in the range of µm. Furthermore, this method was applied to the analysis of 35 different amino acids in human pancreas tissue sections, and successfully allowed for the determination of 27 of these compounds. The accuracy of our newly developed method was estimated to be in the range of 87% 115% based on the results of a recovery test. This method therefore represents a powerful analytical platform for the analysis of human tissue sections and could be used to investigate the mechanism of pancreatic disease. Keywords: Amino acid; Pancreas; Tissue; LC-MS/MS 1. Introduction Pancreatic cancer is currently the seventh most common cause of cancer-related mortality worldwide, with an estimated 330,400 deaths from this disease in 2012 [1]. Surgical resection is the only curative option currently available to patients with pancreatic cancer, however approximately 70% of all cases are discovered during the advanced stages of the disease, making them inoperable with a 5-year survival rate of only 7% [2]. The poor prognosis of pancreatic cancer patients has been attributed to the symptomless nature of this disease, making it difficult to discover this disease during its early stages. The development of a highly sensitive screening test capable of the early detection of pancreatic cancer is therefore urgently required to improve detection and survival rates in patients suffering with this disease. Sensitive screening methods of this type could also be used to enhance our understanding of the mechanisms responsible for the progression of this disease. The emerging field of metabolomics research, which involves the quantitative determination of endogenous metabolites in biological samples, represents a promising approach for the diagnosis of various diseases. This technique can be used to study a wide range of endogenous metabolites, including organic acids, fatty acids, nucleic acids, and, peptides as diagnostic markers of specific * Corresponding author: Toshimi MIZUKOSHI Received: 21 June 2016 Tel: ; Fax: Accepted: 21 September toshimi_mizukoshi@ajinomoto.com J-STAGE Advance Published: 1 October 2016 DOI: /jpchrom

2 disorders and diseases [3-6]. Among the numerous biomarkers reported to date, the free amino acids found in systemic circulation are considered to be potent indicators of disease because their profiles can be influenced by metabolic variations attributed to disease. For example, there have been several reports pertaining to the changes observed in the circulating free amino acids profiles of patients diagnosed with fatty liver disease [7], cardiovascular disease [8], Alzheimer s disease [9], and chronic kidney disease [10]. It was recently reported that multivariate analysis of fasting plasma free amino acid (PFAA) concentrations has great potential for improving the accuracy and sensitivity of cancer screening for colorectal, breast, lung, gastric, prostate and gynecological cancers [11,12]. The results of these multicenter clinical trials revealed that the PFAA levels varied significantly between cancer patients and healthy individuals, and that considerable variations were also observed in cancer patients at the early stages of the disease. In the case of pancreatic cancer, Fukutake et al. also reported significant variations in some PFAA concentrations, and they developed and validated a novel PFAA index to statistically discriminate pancreatic cancer patients from healthy individuals [13]. It is therefore envisaged that PFAA-based pancreatic cancer screening methods will improve the early discovery of cancer, although further work is required to enhance our understanding of the underlying mechanisms responsible for changes in the PFAAs. The PFAA-based pancreatic cancer detection study described above used a high-performance liquid chromatography -mass spectrometry (LC-MS) system equipped with a single-quadrupole analyzer to determine the different amino acids. Precolumn derivatization with 3- aminopyridyl-n-hydroxysuccinimidyl carbamate (APDS) was used in this case to improve the separation of the amino acids and enhance their ionization. This method was validated for 21 of the major PFAAs found in human plasma samples and used to other research [14,15]. However, further improvements in this methodology would be required to detect the subtle changes in PFAAs caused by pancreatic cancer from just a few milligrams of human pancreatic tissue sections containing a complex matrix of compounds. Liquid chromatography -tandem mass spectrometry (LC-MS/MS) is one possible solution for improving the selectivity and sensitivity of MS detection. Shimbo et al. reported the application of LC-MS/MS coupled with AccQ-Tag precolumn derivatization for the analysis of biofluid samples [16]. However, there have not been reports pertaining to the use of this methodology to study human pancreas tissue sections embedded in Tissue-Tek O.C.T. compound (Sakura Fineteck Japan Co., Ltd., Tokyo, Japan). The aim of this study was to develop a new method for the determination of 35 different amino acids in human pancreas tissue sections using LC-MS/MS coupled with an appropriate precolumn derivatization reagent. 2. Experimental 2.1. Ethics statement This study was conducted in accordance with the Declaration of Helsinki, and was approved by the National Cancer Center Institutional Review Board (NCC ) Chemicals An AccQ-Tag Ultra Derivatization Kit was obtained from Waters (Milford, MA, USA). Amino acid standard mixture solutions (type H and type B), L-glutamine, L-tryptophan, L- alanine, glycine, L- -aminoadipic acid, L-hydroxyproline and APDSTAG Wako Amino Acids Internal Standard Mixture Solution were acquired from Wako Pure Chemical Industries Ltd. (Osaka, Japan). L-Asparagine, L- -amino-nbutyric acid, DL- -aminoisobutyric acid, cystathionine, L- citrulline, taurine and L-phenyl-d 5 -alanine were obtained from Sigma-Aldrich Japan (Tokyo, Japan). Chloroform was purchased from Junsei Chemical Co., Ltd. (Tokyo, Japan). Acetic acid, acetonitrile and methanol were purchased as the LC/MS grade from Wako Pure Chemical Industries Ltd. Purified water was obtained from a Milli-Q gradient system (Merck Millipore, Billerica, MA, USA) Apparatus LC-MS/MS analysis was performed on a Shimadzu Nexera MP system consisting of a communications bus module, degasser, two binary pumps, an autosampler and a column oven. The system was also equipped with an LCMS- 8030PLUS mass spectrometer (Shimadzu, Kyoto, Japan). Data acquisition and processing were performed using the LCMS solutions software (version 5.60 SP1). The amino acid mixtures were separated using an L-column ODS ( mm i.d., particle size 3 µm, Chemicals Evaluation and Research Institute, Tokyo, Japan) as an analytical column with an Inertsil ODS-3 ( mm i.d., particle size 3 µm, GL Sciences, Tokyo, Japan) as a guard column Analytical conditions The samples were eluted with a mobile phase consisting of 0.2% aqueous acetic acid (A) and water/acetonitrile/acetic acid solution (40:60:0.2, v/v/v) (B). The gradient program was as follows: min (isocratic 2% B), min (linear from 2% to 25% B), min (isocratic 25% B), min (linear from 25% to 40% B), min (from 40% to 80% B), (isocratic 80% B), (from 80% to 2% B) and min (isocratic 2% B). The flow rate and column temperature were set at 0.25 ml/min and 40 C, respectively. The temperature of the autosampler was set at 4 C throughout the analysis. The

3 sample volume for injection into the LC-MS/MS system was set at 3 µl. A triple quadrupole mass spectrometer with an electrospray interface was operated at unit mass resolution in the positive ionization mode with multiple reaction monitoring (MRM). Nitrogen was used as the nebulizing and dying gases with flow rates of 3 and 20 L/min, respectively. The desolvation line and heat block temperatures were set at 250 and 500 C, respectively. The MS conditions used for the different amino acids are summarized in Table 1. The pause and dwell times were set to 1.0 and 10.0 msec, respectively Method for calculating the corrected amino acid concentration using the internal standard The amino acid concentration was calculated using two different types of internal standard. Internal standard 1 (80% aqueous methanol solution containing 6 µm phenyl-d 5 - alanine) was used to correct the recovery rate for the deproteination, delipidation and concentration processes, whereas internal standard 2, which was the ten-fold diluted APDSTAG Wako Amino Acids Internal Standard Mixture Solution, was used for internal standard ratio quantitation to correct for derivatization efficiency and matrix effects during the analysis as follows. Fig. 1. Flow chart for the preparation of the tissue sections of human pancreas. The details of the internal standards are listed below. Internal standard 1: phenyl-d5-alanine; Internal standard 2: APDSTAG Wako Amino Acids Internal Standard Mixture Solution was diluted ten-fold with purified water Preparation of the amino acid standard solutions All of the calibration ranges for the amino acids are listed in Table 2. An amino acids standard solution was prepared by the subsequent dilution of the stock solutions. Stock solutions of L-glutamine, L-asparagine and L-tryptophan were freshly prepared prior to being used because of their poor stability Preparation of tissue sections of human pancreas Fresh samples of healthy pancreas tissue were obtained from a surgical specimen and frozen in Tissue-Tek O.C.T. compound using a mixture of dry ice and acetone. These samples were subsequently stored at 80 C before being analyzed. The frozen blocks of pancreas tissue (approximately 1.0 cm 3 in size) were sliced into 12 serial sections of 6 µm in thickness using a cryostat (CM1510, Leica Biosystems, Nussloch, Germany) at 20 C. Image data for the first and twelfth sections mounted on the slide glasses were captured using a scanner (NanoZoomer Digital Pathology system, Hamamatsu Photonics, Hamamatsu, Japan), and the average areas of the tissue sections were measured using the Image-J software (National Institutes of Health). The weights of the remaining 10 sections were calculated by taking the product of the average area and thickness of each sample with a specific gravity of 1.0. All 10 sections (i.e., the second to the 11th) were stored in 1 ml of internal standard 1 and stored at 80 C in a freezer before being homogenized. The frozen pancreas tissue sections were homogenized using a Multi-bead shocker (Yasui Kikai Corporation, Osaka, Japan) at 1,700 rpm for 10 sec, followed by a period at 2,000 rpm for 10 sec, during which time the sample tube was cooled with liquid nitrogen. The resulting homogenate was centrifuged at 21,630 g for 5 min at 4 C (5417R, Eppendorf, Tokyo, Japan), and the supernatant was stored at 80 C before being used in the sample preparation step. A blank solution containing no tissue section was also prepared according to the procedure described above. This solution was used to evaluate the extraction efficiency by monitoring phenyl-d 5 -alanine as an indicator. The stored supernatants were thawed out and pooled prior to the delipidation process. Four hundred microliters of the pooled supernatant was added to 400 µl of purified water, followed by 400 µl of chloroform, and the resulting biphasic solution was centrifuged at 21,630 g for 5 min at 4 C. Six hundred microliters of the upper layer was transferred to a 1.5 ml polypropylene micro test tube and cooled to 80 C in a freezer or with liquid nitrogen. The sample was then concentrated (Speed Vac system AES2010, Thermo- Savant) for about 5 h at room temperature to give a residue, which was dissolved in 60 µl of purified water Derivatization of the amino acid standards, as well as the blank and pancreatic tissue samples Ten microliter samples of the amino acid standard, blank, or human pancreas tissue extracts were treated with 10 µl of internal standard solution 2, 60 µl of AccQ Fluor borate

4 buffer and 20 µl of the AccQ Fluor reagent solution, and the resulting mixture was heated at 55 C for 10 min. The mixture was then cooled to room temperature and treated with 400 µl of 0.2% aqueous acetic acid solution before being placed in an autosampler for quantitative amino acid analysis Validation of our newly developed method using human pancreas tissue Our newly developed method was validated in terms of the linearity of its calibration curve, lower limit of quantification (LLOQ), carryover, precision and accuracy. The linearity of this method was evaluated using a standard solution over 4 different days. Each calibration range was determined against the blank calibration values, and all of the points were found to be within 100% ± 15% of the theoretical values. The square correlation coefficient (r 2 ) of each amino acid was estimated. The LLOQ values were evaluated using a signal to noise ratio (S/N) of 10 for the lowest measurable concentration of each amino acid standard solution. The precision was evaluated using an intermediate concentration standard solution, and human pancreas tissue spiked with amino acids at concentrations equivalent to their endogenous concentrations and pool of healthy human pancreas tissue. The intra-day precision of the standard solution was evaluated five times, whereas the inter-day precision was evaluated five times on 3 different days. The intra-day precision of human pancreas tissue spiked with amino acid standards was evaluated six times. The intra-day precision of pool of healthy human pancreas tissue was evaluated five times, whereas the inter-day precision was evaluated three times on 1 day and five times on 2 different days. The intraday samples listed in Table 3 were individually pretreated with homogenate from the pancreatic tissue. The intra- and inter-day precision listed in Table 4 were estimated using the same pretreated samples. The accuracy was evaluated by measuring the responses of human pancreas tissue extracts spiked with amino acid standard solutions. Each extract was evaluated six times on 1 day. The concentrations of the spiked amino acids were adjusted to equal those of the human pancreas tissue extract. The following formula was used to calculate the accuracy: (Concentration of amino acids in human pancreas tissue spiked with standard solution - Concentrations of amino acids in human pancreas tissue spiked with normal saline solution) / Theoretical spiked concentration. Carryover was evaluated by measuring the chromatogram of one blank water sample immediately after the analysis of the highest concentration of each amino acid standard solution on 3 different days. 3. Results and discussion 3.1. Preparation of tissue sections of human pancreas Tissue sections embedded in Tissue-Tek O.C.T. compound typically contain many more fatty components, such as polyvinyl alcohol and polyethylene glycol, than do fasting plasma samples. Given that phospholipids have been reported to cause unwanted matrix effects during analysis, we added a delipidation process to our new method using chloroform to avoid this issue. Furthermore, pancreatic tissue samples typically contain numerous proteases such as trypsin and chymotrypsin, which can lead to changes in the concentrations of specific amino acids by the digestion of proteins. With this in mind, the tissue samples used in the current study were frozen upon collection at 80 C in a cooled sample tube (liquid nitrogen). During the extraction process, we used an 80% aqueous methanol solution to inactivate the proteases, under the assumption that the addition of this solvent would lead to the precipitation of the extracted proteins from tissue [17]. Furthermore, the samples were pretreated on ice prior to being analyzed by LC-MS/MS Selection of derivatization reagent and internal standards Given that the human pancreas tissue sections used in this study were very small in size (around 6 mg) and contained numerous contaminants, it would be necessary to develop a highly sensitive and selective analytical method to allow for the detection of the amino acids. To improve the sensitivity, we examined a variety of different mobile phases and derivatizing reagents for the amino groups of the amino acids. We initially adopted an acidic solvent to increase the sensitivity according to the reasoning provided in the Section 3.3. We subsequently evaluated several derivatization reagents. We previously reported that attaching a ureide moiety to the amino group of amino acid yielded a distinct fragment during MS/MS analysis, which enabled us to conduct simultaneous amino acid analysis using a sensitive and selective MRM mode. AccQ-tag derivatized amino acids provided the best results for the separation of the 35 derivatized amino acids using the acidic elution conditions mentioned above with very few matrix effects from the tissue samples. We also evaluated stable isotope labeled internal standards for the quantitative determination of the amino acids in the human pancreas tissue samples. Twenty-five stable amino acid isotopes were used as internal standards (Internal standard 2) before the derivatization process, and demonstrated the good quantitative performance of this method by reducing matrix effects and correcting the derivatization efficiency. Finally, we investigated stable isotopically-labeled Internal standard 1 to calculate the recovery rates during the homogenization, deproteination, delipidation, concentration and dissolution processes. This internal standard was selected based on the following considerations. First, the

5 Table 1. Mass Spectrometry conditions for each analyte Analyte Q1 (m/z) Q3 (m/z ) Q1 Prebias (V)Q3 Prebias (V) CE (V) Monitoring time (min) Internal standard Q1 (m/z) Q3 (m/z )Q1 Prebias (V)Q3 Prebias (V) CE (V) Monitoring time (min) ethanolamine ethanolamine (1,1,2,2-d4) ~6.5 glycine glycine ( 13 C2, 15 N) ~6.5 alanine alanine ( 13 C3) aminobutyric acid alanine ( 13 C3) aminoisobutyric acid alanine ( 13 C3) amino-n-butyric acid ornitine ( 13 C5) serine serine ( 13 C3, 15 N) proline proline ( 13 C5, 15 N) valine valine ( 13 C5, 15 N) threonine threonine ( 13 C4) ~7.5 taurine taurine ( 13 C2) ~6.5 hydroxyproline histidine ( 13 C6, 15 N3) ~5.0 isoleucine isoleucine ( 13 C6, 15 N) ~11.5 leucine leucine (5,5,5-d3) asparagine asparagine ( 13 C4, 15 N2) ~5.5 ornithine ornitine ( 13 C5) aspartic acid aspartic acid (2,3,3-d3) glutamine glutamine ( 13 C5, 15 N2) lysine lysine 2HCl ( 13 C6, 15 N2) glutamic acid glutamic acid ( 13 C5, 15 N) methionine methionine ( 13 C5, 15 N) histidine histidine ( 13 C6, 15 N3) aminoadipic acid alanine ( 13 C3) hydroxylysine alanine ( 13 C3) phenylalanine phenylalanine ( 13 C9, 15 N) methylhistidine methylhistidine (methyl-d3) methylhistidine methylhistidine (methyl-d3) arginine arginine ( 15 N4) citrulline citrulline (4,4,5,5-d4) tyrosine tyrosine (ring- 13 C6) tryptophan ornitine ( 13 C5) cystathionine cystine (3,3,3',3'-d4) carnosine glutamine ( 13 C5, 15 N2) anserine arginine ( 15 N4) cystine cystine (3,3,3',3'-d4) phenyl-d 5-alanine phenylalanine ( 13 C9, 15 N)

6 molecular weight of the Internal standard 1 should differ from those of the labeled stable isotopes in Internal standard 2 by more than 3 mass units, so that they can be distinguished by MS. Second, the standard should be commercial available and inexpensive. For these reasons, we selected phenyl-d 5 - alanine (MW=170) as Internal standard 1, while UCNphenylalanine (MW=175) was used in Internal standard Separation of 35 different amino acids Figure 2 shows a mass chromatogram for the standard solution of 35 different amino acids. The separation conditions were examined in detail, resulting in a satisfactory method for the separation of the 35 amino acids over a 12 min run time using aqueous acetic acid solution as the mobile phase. separated more than 1 min away from the peak belonging to hydroxyproline, which was the first amino acid peak eluted from the column (Fig 2). This separation therefore minimized the matrix effect resulting from the degradation of the AccQ Fluor reagent. Furthermore, this method allowed for the separation of amino acids with the same molecular weight (e.g., 1-methylhistidine and 3-methylhistidine; - aminobutyric acid, -aminoisobutyric acid and -amino-nbutyric acid; isoleucine and leucine) using a combination of isocratic and linear gradient programs (Fig 3). Fig. 3. Mass chromatograms of amino acids evaluated in this study that gave the same mass by LC-MS/MS. (a) 1- Methylhistidine (1MeHis) and 3-methylhistidine (3MeHis), (b) - aminobutyric acid (GABA), -aminoisobutyric acid ( -AiBA) and -amino-n-butyric acid ( -ABA), and (c) isoleucine and leucine. Fig. 2. Typical mass chromatograms of the target peaks and their concentrations (µm): hydroxyproline (HyPro):12.5, histidine (His):25.0, 1-methylhistidine (1MeHis):12.5, 3-methylhistidine (3MeHis):12.5, asparagine (Asn):12.5, arginine (Arg):25.0, carnosine (Car):12.5, anserine (Ans):12.5, serine (Ser):12.5, glutamine (Gln):25.0, taurine (Tau):12.5, glycine (Gly):25.0, ethanolamine (EtOHNH2):12.5, aspartic acid (Asp):12.5, citrulline (Cit):12.5, glutamic acid (Glu):12.5, threonine (Thr):12.5, alanine (Ala):25.0, -aminobutyric acid (GABA):12.5, -aminoadipic acid ( -AAA):12.5, proline (Pro):12.5, hydroxylysine (HyLys):12.5, - aminoisobutyric acid ( -AiBA):12.5, -amino-n-butyric acid ( - ABA):12.5, ornithine (Orn):12.5, cystathionine (Cysthi):12.5, cystine (Cys2):12.5, lysine (Lys):25.0, tyrosine (Tyr):12.5, methionine (Met):12.5, Valine (Val):12.5, isoleucine (Ile):12.5, leucine (Leu):12.5, phenylalanine (Phe):12.5, and tryptophan (Trp):12.5. An acidic mobile phase was used in the current study because acidic mobile phases have been reported to afford higher sensitivity for the detection of the amino acid derivatives by MS compared with neutral or basic mobile phase. Furthermore, the use of an acidic mobile phase was better suited for the trace analysis of the amino acids typically found in a human pancreas tissue. The aqueous acetic acid solution used in this study was also suitable for the separation of the degradation product resulting from the removal of the AccQ Fluor reagent (Retention time 1.92 min, transition m/z 145.1) from the amino acid derivatives. The degradation product was poorly retained by the column, and 3.4. Mass spectroscopic detection The mass chromatograms were acquired based on 56 different transitions, which were monitored in the MRM mode (Table 1). Data acquisition was conducted over a specific time period for each amino acid to avoid shortages in the acquisition time and the number chromatographic data points. This MRM methodology provided reliable and reproducible peak shapes Validation of our newly developed method using human pancreas tissue Standard solutions were used to determine the linearity, LLOQ, precision and carryover properties of the method. Table 2 shows the linearity, LLOQ, precision of the calibration curves obtained using our newly developed method. The concentrations of the calibration standards for all of the amino acids evaluated in the current study were within 15% of the nominal concentration with r 2 values greater than All of the calibration curves showed good linearity with LLOQ values in the range of µm, except for citrulline. The LLOQ of citrulline was high because of the higher noise level associated with this material. These results therefore showed that our newly develop method could be used to achieve high enough sensitivity to allow for the detection of trace amounts of amino acids in human pancreas tissues. Notably, the LLOQ of our newly developed method was improved more than 100- fold for the best amino acid result compared with exiting analytical methods for the detection of amino acids [14]. Furthermore, this method gave intra-day precision values in the range of

7 1.1% 9.3% and inter-day precision values in the range of 1.9% 10.9% for all of the detected amino acids. 1- Methylhistidine and 3-methylhistidine gave precision values of more than 15% because of the lack of sensitivity. These data therefore highlight the utility of our newly developed method for the analysis of human pancreas tissue. The carryover peaks detected for all 35 of the amino acids evaluated in this study gave S/N ratios of less than 3 for the aqueous samples. Table 2. Concentration range, linearity LLOQ and precision values of the 35 standard different amino acids evaluated in this study, as well as those of phenyl-d5-alanine. Amino acid Concentration range [ M] Linearity [r 2 ] LLOQ [ M] (S/N 10) Precision [%] Intra-day Inter-day ethanolamine glycine alanine aminobutyric acid aminoisobutyric acid amino-n-butyric acid serine proline valine threonine taurine hydroxyproline isoleucine leucine asparagine ornithine aspartic acid glutamine lysine glutamic acid methionine histidine aminoadipic acid hydroxylysine phenylalanine methylhistidine methylhistidine arginine citrulline tyrosine tryptophan cystathionine carnosine anserine cystine phenyl-d 5-alanine Table 3 and 4 shows the concentration of amino acids in tissue sample, and accuracy, intra-day precision and interday precision obtained using our newly developed method. The accuracy values for the 27 different amino acids detected in the human pancreas tissue homogenate were in the range of 87% 115 %. It is noteworthy that this result satisfies the bioanalytical method validation guidelines [18]. This method gave intra-day precision values in the range of 1.8% 10.9% (Table 3) and 1.2% 7.9% and inter-day precision values in the range of 1.6% 16.5% (Table 4) in all of the detected amino acids. This method can therefore be considered suitable for measuring the amino acids found in Table 3. Accuracy and precision values of the 27 amino acids and phenyl-d5-alanine detected in the human pancreas tissue sample. Amino acid Concentrarion [ M] Intra-day Accuracy [%] Tissue Spiked standard Precision [%] ethanolamine glycine alanine aminobutyric acid amino-n-butyric acid serine proline valine threonine taurine hydroxyproline isoleucine leucine asparagine ornithine aspartic acid glutamine lysine glutamic acid methionine histidine aminoadipic acid phenylalanine arginine tyrosine tryptophan phenyl-d 5-alanine Table 4. Intra- and Inter-day precision values for the 27 amino acids and phenyl-d5-alanine detected in the human pancreas tissue sample. Amino acid Precision [%] Intra-day Inter-day ethanolamine glycine alanine aminobutyric acid amino-n-butyric acid serine proline valine threonine taurine hydroxyproline isoleucine leucine asparagine ornithine aspartic acid glutamine lysine glutamic acid methionine histidine aminoadipic acid phenylalanine arginine tyrosine tryptophan phenyl-d 5-alanine

8 pancreas tissue samples. The recovery of this method was determined to be 80% for phenyl-d 5 -alanine following its addition to the human pancreas tissue homogenate. While it is impossible to prevent small losses from aqueous solutions following their concentration, these losses can be accurately measured and correcting for using an internal standard. These findings therefore confirmed that our newly developed method is suitable for the determination of 27 different amino acids detected in human pancreas tissue samples. 4. Conclusion We have developed a new analytical method for the determination of 27 different amino acids detected in human pancreas tissue sections by LC-MS/MS using precolumn derivatization. This newly developed method represents a reliable platform for the analysis of human pancreas tissue samples. Our previous efforts in this area required the development of separate methods for the analysis of the amino acids and tissue diagnosis. It is envisaged that this newly developed method will be applied to the analysis of frozen tissue samples embedded in O.C.T., including tissues from a wide range of organs. This method also represents a reliable tool for understanding the mechanisms involved in the progression of human disease by allowing for the accurate determination of amino acids associated with different diseases. References [1] Torre, A. L.; Bray, F.; Siegel, L. R.; Ferlay, J.; Lortet- Tieulent, J.; Jemal, A. CA Cancer J Clin. 2015, 65, [2] Greene, L. F.; Page, L. D.; Fleming, D. I.; Fritz, G. A.; Balch, M. C.; Haller, G. D.; Morrow, M. AJCC Cancer Staging Manual 6th ed. New York: Springer-Verlag [3] Kałuzna-Czapli nska, J.; Zurawicz, E.; Struck, W.; Markuszewski, M. J. Chromatogr. B 2014, 966, [4] Wang, C. D.; Sun, H. C.; Liu, Y. L.; Sun, H. X.; Jin, W. X.; Song, L. W.; Liu, Q. X.; Wan, L. X. Neurobiol. Aging 2012, 33, [5] Rabinowits, G.; Gerçel-Taylor, C.; Day, M. J.; Taylor, D. D.; Kloecker, H. G. Clin. Lung Cancer 2009, 10, [6] Neuhaus, J.; Schiffer, E.; Wilcke, P.; Bauer, W. H.; Leung, H.; Siwy, J.; Ulrici, W.; Paasch, U.; Horn, C. L.; Stolzenburg, U. J. PLoS One 2013, 8, e [7] Kalhan, S.; Guo, L.; Edmison, J.; Dasarathy, S.; McCullough, A.; Hanson, R.; Milburn, M. Metabolism 2011, 60, [8] Kume, S.; Araki, S.; Ono, N.; Shinhara, A.; Muramatsu, T.; Araki, H.; Isshiki, K.; Nakamura, K.; Miyano, H.; Koya, D.; Haneda, M.; Ugi, S.; Kawai, H.; Kashiwagi, A.; Uzu, T.; Maegawa, H. PLoS One 2014, 9, e [9] Gueli, C. M.; Taibi, G. Neurol. Sci. 2013, 34, [10] Suliman, E.M.; Stenvinkel, P.; Qureshi, A.R.; Bárány, P.; Heimbürger, O.; Anderstam, B.; Alvestrand, A.; Lindholm, B. Am. J. Kidney Dis. 2004, 44, [11] Miyagi, Y.; Higashiyama, M.; Gochi, A.; Akaike, M.; Ishikawa, T.; Miura, T.; Saruki, N.; Bando, E.; Kimura, H.; Imamura, F.; Moriyama, M.; Ikeda, I.; Chiba, A.; Oshita, F.; Imaizumi, A.; Yamamoto, H.; Miyano, H.; Horimoto, K.; Tochikubo, O.; Mitsushima, T.; Yamakado, M.; Okamoto, N. PLoS One 2011, 6, e [12] Ihata, Y.; Miyagi, E.; Numazaki, R.; Muramatsu, T.; Imaizumi, A.; Yamamoto, H.; Yamakado, M.; Okamoto, N.; Hirahara, F. Int. J. Clin. Oncol. 2014, 19, [13] Fukutake, N.; Ueno M.; Hiraoka, N.; Shimada, K.; Shiraishi, K.; Saruki, N.; Ito, T.; Yamakado, M.; Ono, N.; Imaizumi, A.; Kikuchi, S.; Yamamoto, H.; Katayama, K. PLoS One 2015, 10, e [14] Yoshida, H.; Kondo, K.; Yamamoto, H.; Kageyama, N.; Ozawa, S.; Shimbo, K.; Muramatsu, T.; Imaizumi, A.; Mizukoshi, T.; Masuda, J.; Nakayama, D.; Hayakawa, Y.; Watanabe, K.; Mukaibatake, K.; Miyano, H. J. Chromatogr. B 2015, 998, [15] Nakamura, H.; Kageyama, N.; Yoshida, H.; Mori, M.; Mizukoshi, T.; Miyano, H. Chromatography 2016, 37, [16] Nakatsukasa, M.; Sotozono, C.; Shimbo, K.; Ono, N.; Miyano, H.; Okano, A.; Hamuro, J.; Kinoshita, S. Am. J. Ophthalmol. 2011, 151, [17] Blanchard, J. J. Chromatogr. 1981, 226, [18] Committee for Medicinal Products for Human Use, European Medicines Agency, Guideline on bioanalytical method validation