LC–MS/MS determination of D-mannose in human serum as a potential cancer biomarker

Abstract

Several metabolites in human serum have been identified as potential cancer biomarkers for early detection. This study focuses on the LC–MS/MS method development and validation of D-mannose in human serum. Surrogate blank serum, coupled with stable isotope D-mannose-¹³C₆, as internal standard, was used for generating standard curves ranging from 1 to 50 μg/mL. Separation was achieved by an Agilent 1200 series HPLC equipped with a SUPELCOGELTM Pb, 6% Crosslinked column with HPLC water as a mobile phase at flow rate of 0.5 mL/min at 80 °C. Mass detection was performed under negative ionization electrospray. Inter- and intra-day accuracy and precision were <2%. The extraction recovery and matrix effect were 104.1%–105.5% and 97.0%–100.0%, respectively. This method was successfully applied for the quantification of D-mannose in the serum samples of 320 esophageal cancer patients and 323 healthy volunteers. We report a simple, specific and reproducible LC–MS/MS method for the quantification of D-mannose in human serum as a potential cancer biomarker.

1. Introduction

The burden of cancer on public health is significantly high, with more than 14 million new cases worldwide, and 8.2 million deaths in 2012 [1]. The rise of more rapid, specific, and sensitive methods for earlier detection of cancer will result in more efficient management. Development and utilization of early detection methods such as biomarkers will improve the clinical outcome of this disease. There is an urgent need for standardized, noninvasive, objective, and accurate markers that are sensitive and specific for risk stratification.

Metabolites are low molecular weight compounds that can be used as biomarkers for numerous diseases. Profiling of the metabolic changes caused by cancer has become important for cancer screening, intervention and early detection. Metabolic approaches that use liquid chromatography (LC)–mass spectrometry (MS) are very powerful to identify and quantify metabolites from various sample matrices. Therefore, it is essential to develop simple, accurate methods of detection and separation of metabolic biomarkers that have been linked with certain types of cancer.

Esophageal cancer (EC) is one of the most common cancers in the world with roughly 455,000 new cases and 400,200 deaths in 2012 [2]. The most common subtypes of EC are esophageal adenocarcinoma (EAC) and squamous cell carcinoma (ESCC). With increased prevalence of obesity and gastroesophageal reflux disease (GERD, a risk factor for EAC), EAC is the highest growing cancer in the United States. To improve the survival rate, there is a growing need to identify and validate non-invasive and objective methods such as biological markers that are sensitive enough for early diagnosis of EC and for monitoring tumor progression.

Serum autoantibodies, antigens and proteins from EC patients have been utilized as biomarkers for EC. For example, Brockmann and colleagues discovered that CYFRA21-1 serum levels correlated with EC tumor burden [3]. Scarpa et al. discovered that preoperative CEA and CA19.19 levels could be used as biomarkers of occult advanced EAC [4]. Gion et al. found that serum levels of CEA and TPA correlated with the extent of ESCC [5]. In addition, Dong et al. found a higher positive detection rate of ESCC when using CDC25B-Abs versus CEA, SCC-Ag, and CYFRA211 serum markers [6]. However, these methods lack in sensitivity for EAC or are specific for ESCC only. Moreover, the studies by Gion et al. and Dong et al. were conducted to identify biomarkers for EC prognosis, while we aim to identify a serum marker for early detection of EC. With a dismal 5-year survival rate of 15%, early detection is crucial. Kilic et al. examined serum autoantibodies and proteins for early detection of EAC and found that anti-NY-ESO-1 and Fas ligand were able to detect EAC from GERD [7]. Yet, this study is limited by the low sample number and aimed to identify rather than validate specific markers for EAC.

It has been long known that certain tumors have high rates of glycolysis. Mannose has recently been correlated with cancer metabolism. D-mannose was shown to be higher in the serum concentrations of metastatic breast cancer patients versus early stage breast cancer patients [8]. We previously reported the correlation of D-mannose as a candidate biomarker for esophageal adenocarcinoma (EAC) [9,10]. The utilization of mannose as a biomarker for early detection of esophageal cancer may improve the clinical outcome of this disease.

In this study, we report an LC–MS/MS method that was developed and validated for application to our clinical study, which involved the analysis of D-mannose in the human serum of EAC patients and healthy volunteers [9]. Several methods of analysis have been used for measuring the levels of D-mannose in biological fluids. These methods include enzymatic [11,12], HPLC [13,14], gas-liquid chromatography [15] and capillary electrophoretic [16] techniques. However, these methods are time consuming and are not ideal for routine analysis due to the difficulty in removing interference of the 100 fold excess D-glucose, a C2 epimer of D-mannose. Miwa and Taguchi recently reported an HPLC method for analysis of D-mannose in plasma but this study requires derivatization of sugars before analysis [14]. The LC–MS/MS assay described in this report was previously presented as a poster at the 2016 AAPS Annual Meeting [10] and was used to support our metabolomics study, which was conducted to identify novel serum biomarkers for EAC [9].

2. Materials and methods

2.1. Chemicals and reagents

D-(+)-mannose (≥99.5% pure), D-mannose-¹³C₆ (98 atom% ¹³C, 99% pure, internal standard, IS), bovine serum albumin (BSA), phosphate buffered saline (PBS), formic acid, and HPLC grade acetonitrile and water were purchased from Sigma-Aldrich (St. Louis, MO).

2.2. Standards and quality controls

Stock solutions of D-mannose (10 mg/mL) and IS (4 mg/mL) were prepared individually by dissolving each substance in water, and stored at 4°C until used. Fresh standards were prepared on a monthly basis. A series of standard samples of D-mannose were prepared by diluting the stock solution with water and then spiking in surrogate blank serum (4% BSA in PBS) to obtain the following concentrations: 1, 2, 5, 20, and 50 μg/mL. The low, medium and high concentration levels of quality control (QC) samples were prepared by the same method as the standards at 2.5, 10 and 40 μg/mL, respectively. IS working solution was prepared by diluting the stock solution with water to obtain 400 μg/mL. Stability QC standards were prepared in pooled human serum.

2.3. Sample preparation

An aliquot (50 μL) of standard, QC, or human serum sample was first mixed with 5 μL of IS working solution. The mixture was then extracted and deproteinized by adding 100 μL of acetonitrile and vortex mixed for 30 s. The mixture was centrifuged for 10 min at 20,800 × g at room temperature. An aliquot (100 μL) of the supernatant was taken into a glass of culture tube and dried by nitrogen gas for 40 min in 40°C water bath. The residue was reconstituted by adding 100 μL 0.1% formic acid in water and vortex mixed for 30 s. After centrifugation an aliquot of the supernatant was taken for LC–MS/MS analysis.

2.4. Chromatographic conditions

The chromatographic separation was achieved by an Agilent 1200 series HPLC equipped with a SUPELCOGEL™ Pb, 6% Crosslinked HPLC column (300 × 7.8 mm, 9 μm, Supelco) at 80°C with a flow rate of 0.5 mL/min. The mobile phase was 100% HPLC water and each sample injection volume was 5 μL. The MS analysis was performed by an API 3200 QTRAP triple quadrupole mass spectrometer with a Turbo Ion Spray ion source (Applied Biosystem/MDS SCIEX). The quantification was performed by selected reaction monitoring (SRM) at negative mode to detect the specific precursor to product ion transitions m/z 179 → 59 for D-mannose, and m/z 185 → 92 for IS (IS fragmentation pattern is shown in Supplementary material Fig. S1). The compound dependent parameters for D-mannose and IS are listed in Table 1. The source parameters were set as follows: ionspray voltage, −4500 V; ion source temperature, 500°C; nebulizer gas, 65 psi; heater gas, 30 psi; curtain gas, 20 psi; and the collision gas, medium. The LC–MS/MS system was controlled and data was acquired by Analyst software version 1.5. Fig. 1 shows an overlaid D-mannose and Glucose spectrum along with a representative chromatogram of human serum sample spiked with IS.

Table 1.

Compound dependent parameters for D-mannose and IS in SRM mode for LC–MS/MS analysis.

Compound	[M-H]−	SRM transition	Dwell time (ms)	DPa (V)	EPb (V)	CEPc (v)	CEd (V)	CXPe (V)
D-mannose	178.8	58.6	300	−30	−3.5	−16	−22	−6
D-mannose-13C6	185	92.2	300	−25	− 3	−10	− 12	−2

^aDP, declustering potential.

^bEP, entrance potential.

^cCEP, collision cell entrance potential.

^dCE, collision cell.

^eCXP, collision cell exit potential.

Fig. 1.

Top pane, overlaid D-mannose (blue line) and glucose spectrum (red line); bottom pane, representative chromatogram of human serum (blue line) sample spiked with internal standard (D-mannose-¹³C₆, red line), with calculated D-mannose concentration of 12.98 μg/mL. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

2.5. Equivalency between surrogate and real human serum

To test the equivalency between surrogate matrix and real human serum, a set of three QC samples at high concentration level were prepared in human serum. The equivalency was calculated according to Eq. (1):

$$\%\text{Equivalency}=\frac{\mathrm{Re}{\text{sponse}}_{\text{serumspike}}-\mathrm{Re}{\text{sponse}}_{\text{serum}}}{\mathrm{Re}{\text{sponse}}_{\text{surrogatespike}}}\times 100\%$$ (1)

where Response_serumspike is the peak area count for D-mannose spiked at high QC sample concentration level in human serum, Response_serum is the peak area count for D-mannose in “blank” human serum, and Response_{surrogatespike} is the peak area count for D-mannose spiked at high QC sample concentration level in surrogate serum.

2.6. Method validation

The LC–MS/MS assay described herein was validated according to Center for Drug Evaluation and Research (CDER) “Guidance for Industry: Bioanalytical Method Validation” [17].

2.6.1. Linearity and sensitivity

Calibration curves (Supplementary material Fig. S2) in surrogate serum were created by plotting the peak area ratio of D-mannose and IS against the known concentrations of the D-mannose. The least-squares linear regression method with 1/x² weighting was applied to generate the slope, intercept, and correlation coefficient of each linear regression equation. Since D-mannose is an endogenous compound, both the LLOQ and ULOQ were determined based on the level of D-mannose found in normal human serum. The LLOQ is defined as the lowest measurable concentration in the standard curve with acceptable accuracy and precision. The highest calibration standard (ULOQ) is defined as the maximum analyte concentration that can be quantified with acceptable precision and accuracy.

2.6.2. Recovery and matrix effect

To examine the extraction recovery and matrix effect, the QC samples at three concentration levels were evaluated. The extraction recovery and matrix effect were calculated according to Eqs. (2) and (3), respectfully.

$$\%\mathrm{Re}\mathrm{cov}\text{ery}=\frac{\mathrm{Re}{\text{sponse}}_{\text{pre-extractionspike}}}{\mathrm{Re}{\text{sponse}}_{\text{pre-extractionspike}}}\times 100\%$$ (2)

$$\%\text{Matrix}\text{factor}=\left(\frac{\mathrm{Re}{\text{sponse}}_{\text{post-extractionspike}}}{\mathrm{Re}{\text{sponse}}_{\text{matrix-freespike}}}\right)\times 100\%$$ (3)

Where Response_{pre-extractionspike} is the mean peak area count for D-mannose samples that have undergone the extraction process. Response_{post-extractionspike} is the mean peak area count for D-mannose spiked into extracted matrix after the extraction procedure. Response_{matrix-freespike} is the mean peak area count for the same concentration of D-mannose in water. Experiments were conducted in triplicate.

2.6.3. Accuracy and precision

The intra- or inter-day accuracy and precision of the LC–MS/MS method were evaluated by analyzing the QC samples via calibration curves created on the same day or three different days. Experiments were conducted in sextuplicate.

2.6.4. Stability

All stability studies were conducted with pooled human serum at low, medium and high QC levels using three replicates at each concentration level. All samples were compared with freshly prepared samples at the same concentrations. Short-term (bench-top) stability samples were freshly prepared and left on the bench-top at room temperature for 24 h. Freeze-thaw (FT) stability samples were exposed to three cycles of freeze (−80°C) and thaw (RT, room temperature). The stability of processed sample was determined by the comparison of freshly obtained serum extracts to serum extracts that remained in the auto-sampler for 24 h at 15°C. Long-term storage stability samples were freshly prepared and stored at −80°C for 14 days.

2.7. Assay application in quantification of clinical human serum samples

This validated LC–MS/MS method was successfully applied to a clinical study involving quantification of D-mannose in human serum in a set of 643 serum samples which included earlystage EAC patients (N = 145), late-stage EAC patients (N = 175),and healthy controls (N = 323) matched by age and gender. These clinical samples were received from MD Anderson Cancer Center. All cases were newly diagnosed, histologically confirmed patients with esophageal adenocarcinoma who had not received chemotherapy or radiotherapy before participation. Healthy volunteers for the control group had no prior history of cancer were identified from Kelsey-Seybold Clinic. The protocol was approved by the institutional review board (IRB) at Texas Southern University. Differences in the host characteristics between cases and controls were evaluated by Pearson χ² test. After quantification and quality control analyses, Wilcoxon rank-sum test was used to compare the D-mannose concentration levels between the EAC cases and healthy controls. All analyses were done using STATA (StataCorp LP, College Station, TX) and P values less than 0.05 considered as statistically significant.

3. Results and discussion

3.1. Chromatography

D-mannose is notoriously difficult to accurately quantify due to its coelution or closely eluting peaks with other endogenous epimers of D-mannose such as D-glucose, D-fructose and, D-galactose. After various trials utilizing various HPLC configurations, we found that the Supelcogel Pb + 2 provided optimal resolution between the sugars. The Supelcogel column is a Pb + 2 ion exchange resin column. Separation of this column is by size exclusion and ligand-exchange nodes. Since D-mannose has the same molecular weight as D-glucose, D-galactose and D-fructose, this column will separate the epimers by ligand-exchenge. This phenomenon is possibly due to the location and availability of the hydroxyl groups of the sugars to the bound lead cations of the column.

One limitation to our study is the lengthy run-time. Although a long run-time is not ideal for routine use, this time is necessary due to the similarity in the compounds we are separating. The total run-time for each chromatographic analysis was 25 min. The retention time was 15.76 min for D-glucose, 18.95 min for D-galactose, 20.38 min for both D-mannose and IS, and 21.50 min for D-fructose. This method provided clear separation of the mono-sugars and therefore, D-glucose, D-galactose, and D-fructose do not co-elute with D-mannose. A stable isotope of D-mannose was selected as the IS, which is the best choice for a LC–MS/MS analysis because it can effectively compensate for variability such as in ionization efficiency, stability, and extraction recovery. Fig. 1 shows typical chromatogram representatives from: (top pane) blank surrogate serum spiked with the IS only and (bottom pane) human serum sample spiked with IS. The utility of this assay was confirmed by applying the method to a clinical study. The data showed that this simple method successfully separated D-mannose from glucose with no interferential peaks.

3.2. Equivalency between surrogate and real human serum

The equivalency (mean ± SD) at the high QC level determined according to Eq. (1) was 92.43 ± 0.30% with an RSD of 0.33%. This result proved that surrogate serum was equivalent to real human serum in this LC–MS/MS analysis of D-mannose.

3.3. Method validation

3.3.1. Linearity and sensitivity

The linearity of the calibration curves was established over the concentration range of 1–50 μg/mL with correlation coefficient values greater than 0.999. The values (mean ± SD; n = 9) of the slope and intercept were 0.0333 ± 0.0033 and −0.0031 ± 0.0029 respectively. Since D-mannose is endogenous compound, and the concentration of D-mannose in normal human serum was reported to be 3.6–7.2 μg/mL [11–14], the LLOQ selected in this work was 1 μg/mL, which is more than 3 times lower than the normal level. The ULOQ of the calibration curves selected was 50 μg/mL, which is more than 5 times greater than the normal level.

3.3.2. Recovery and matrix effect

The extraction recovery and matrix effect are represented as mean ± standard deviation (SD) along with relative standard deviation (RSD) in Table 2. The mean extraction recovery for D-mannose was 104.13, 105.53, and 104.84, for the low, medium, and high QC concentrations, respectively. Matrix effect was measured to determine a potential increase or decrease in ionization efficiency caused by co-eluting matrix components. The matrix factor was 100.04%, 96.85%, and 97.03%, for the low, medium and high QC concentrations, respectively. No significant matrix effect was considered if RSD was within ±15%. The RSD of matrix factors was less than 4%, suggesting no significant matrix effect. This data shows that the simple sample preparation method yielded very high and stable extraction recovery. Also, the sample preparation method plus the use of SUPELCOGEL™ Pb, 6% crosslinked HPLC Column resulted in no measurable matrix effect.

Table 2.

Extraction recovery and matrix effect (mean ± SD and RSD) of D-mannose from human serum.

Analyte	Concentration μg/mL	Extraction Recovery		Matrix effect
		Mean ± SD (%)	RSD (%)	Mean ± SD (%	RSD (%)
D-mannose	2.5	104.13 ± 3.10	2.98	102.90 ± 4.04	3.92
	10	105.53 ± 3.22	3.05	99.16 ± 3.27	3.30
	40	104.84 ± 3.91	3.73	98.28 ± 1.80	1.80

3.3.3. Accuracy and precision

The intra- and inter-day accuracy (present as relative error) and precision (present as relative standard deviation) of the assay were within the 15% acceptance range (results are summarized in Table 3). This data indicates that the developed LC–MS/MS method is accurate and precise for the analysis of D-mannose in human serum samples at a concentration of 1–50 μg/mL.

Table 3.

Intra- and inter-day accuracy and precision of D-mannose LC–MS/MS analysis [9].

Concentration (μg/mL)	Intra-day (n = 6)		Inter-day (n = 6)
	Accuracy (REa, %)	Precision (RSDb, %)	Accuracy (RE, %)	Precision (RSD, %)
2.5	1.88	1.84	1.41	1.04
10	0.68	0.94	1.10	1.36
40	1.19	0.74	1.02	1.67

^aRE, relative error.

^bCV, coefficient of variation.

3.3.4. Stability

Stability studies were conducted to evaluate the stability of D-mannose under expected sample handling and storage conditions. The results of the stability study are expressed in Table 4 as the mean remaining percentages of nominal concentration (n = 3; mean ± SD). The stability of the low, medium and high QC samples at room temperature for 24 h, after three freeze-thaw cycles, at 15°C in the auto-sampler for 24 h, and at −80°C for 14 days is summarized in Table 4. The mean percentages remaining were all within 6% of nominal concentration and the RSDs were less than 15%. This data indicates that D-mannose in human serum is stable after at least 24 h at room temperature on the bench-top, after three freeze-thaw cycles, after 24 h in the auto-sampler at 15 °C, and after at least 14 days at −80°C.

Table 4.

Stability of D-mannose in human serum expressed as percent of nominal concentration (n = 3; mean ± SD).

Mean ± SD (%)
Nominal concentration (μg/mL)	Short-term (24 h)	Auto-sampler at 15°C (24 h)	3 Cycles of Freeze thaw	Long term −80 °C (14 days)
2.5	95.44 ± 8.36	100.74 ± 3.69	100.54 ± 14.58	95.24 ± 11.68
10	99.06 ± 2.25	99.85 ± 4.62	106.76 ± 3.77	102.47 ± 4.00
40	99.61 ± 0.31	98.08 ± 2.00	99.47 ± 1.96	100.76 ± 3.65

4. Assay application in quantification of clinical human serum samples

In this study, we analyzed the serum D-mannose metabolite levels from 320 EAC patients and 323 healthy controls matched by age and gender using the developed LC–MS/MS method. Mannose data were pooled for comparison and analyzed by Wilcoxon rank-sum test. As previously reported by Sanchez-Espiridion et al., the statistical analyses in Table 5 show significantly higher levels of serum D-mannose in the early-stage EAC patients as compared to the healthy volunteers (8.97 μg/mL versus 6.28 μg/mL, P < 0.001)[9].

Table 5.

Levels of mannose in controls, early-stage and late-stage EAC cases [9].

	Control Meana (SD) (N = 323)	Cases Meana (SD)		P valueb
		Early-stage (N = 145)	Late-stage (N = 175)	(Early vs Controls)	(Late vs Controls)
D-Mannose	6.28 (3.61)	8.97 (3.36)	10.61 (4.79)	<0.001	<0.001

^aAbsolute mean values in μg/ml.

^bWilcoxon-rank sum test.

5. Conclusion

We have developed and validated a simple, specific, and reproducible LC–MS/MS method for the quantification of D-mannose in human serum that is suitable for clinical sample analysis. The utility of this assay was confirmed by applying the method to a clinical study [9]. This method demonstrated good linearity over the concentration range of 1–50 μg/mL. The sample handling and storage conditions of the method had no impact on the stability of D-mannose. The intra- and inter-day accuracy and precision of the calibration curves and QC samples complied with FDA acceptance criteria for bioanalytical method validation. To our knowledge, this is the first specific individual LC–MS/MS method developed and applied for quantification of D-mannose concentration levels in clinical human serum samples. More importantly, this assay presents a new approach to the analysis of monosugars by using LC–MS/MS with a stable isotope as internal standard and standard samples in blank surrogate serum. We have performed a serum metabolic analysis to determine if there is a correlation between serum levels of D-mannose and EAC. This study provides preliminary evidence that EAC patients have significantly higher D-mannose levels as compared to the healthy controls [9]. Though requiring further validation, the results suggest that D-mannose levels may prove to be a useful biomarker for the screening and diagnosis of this disease.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jpba.2016.12.017.