Chromatographia DOI 10.1007/s10337-016-3046-8
ORIGINAL
Development and Validation of a Peptide Mapping Method for the Characterization of Adalimumab with QDa Detector Junjie Zhang1,2,3 · Ting Qin1,2,3 · Lu Xu1,2,3 · Boning Liu1,2,3 · Yantao Li2,3 · Huaizu Guo3,4 · Lankun Song6 · Qingcheng Guo2,3 · Jin Xu3,4 · Dapeng Zhang2,3 · Weizhu Qian3,4 · Jianxin Dai2,3 · Hao Wang2,3 · Sheng Hou2,3 · Yajun Guo1,3,5
Received: 22 November 2015 / Revised: 23 January 2016 / Accepted: 26 January 2016 © Springer-Verlag Berlin Heidelberg 2016
Abstract During antibody drug research and development, it is important to make sure the protein therapeutics are biosynthesized correctly, and peptide mapping works as a powerful analytical approach to confirm the identity of the monoclonal antibodies (mAbs). In this study, a novel quality control method combining tryptic peptide mapping with QDa detector for characterization of biotherapeutics was developed and validated. The peptides derived from complementarity determining regions (CDRs) of adalimumab were used as surrogates of adalimumab. Ten other antibody drugs were used to assess the method specificity. The results showed that this method has high specificity due to the high UV–MS selectivity; the limit of detection was 20 μg mL−1; carry-over J. Zhang, T. Qin and L. Xu have contributed equally to this work. Electronic supplementary material The online version of this article (doi:10.1007/s10337-016-3046-8) contains supplementary material, which is available to authorized users. * Sheng Hou
[email protected] * Yajun Guo
[email protected] 1
School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China
2
International Joint Cancer Institute, Second Military Medical University, Shanghai, China
3
State Key Laboratory of Antibody Medicine and Targeted Therapy, Shanghai Key Laboratory of Cell Engineering, Shanghai, China
4
Shanghai Zhangjiang Biotechnology Co., Shanghai, China
5
School of Pharmacy, Liaocheng University, Liaocheng, China
6
Waters Corporation, Shanghai, China
was about 1.69 %. Additionally, other validation parameters, like stability, were also evaluated. This novel LC–UV–QDa method may be a simple, cost-effective and robust peptidemapping method for other recombinant monoclonal antibodies during routine quality control analysis. Keywords LC–QDa · Adalimumab · CDR regions · Peptide mapping
Introduction Biotherapeutics developed rapidly in recent decades, especially monoclonal antibodies (mAbs) [1], from muromonab-CD3 [2], adalimumab [3] to trastuzumab [4], which have a great performance in cancer, transplant rejection, infection, cardiovascular and autoimmune diseases [1]. Tumor nectosis factor alpha (TNF-α) normally binds to TNF-α receptors, but the unregulated activities of TNF-α can lead to the development of inflammatory diseases [5, 6]. The mAbs drugs have been widely used for treatment TNF-α-related diseases for more than 10 years [7]. Adalimumab, by binding to TNF-α, was the first fully human mAb drug approved by the US Food and Drug Administration (FDA), now it is one of the most frequently administered TNF-α antagonists [1, 8]. By binding to TNF-α, adalimumab prevents TNF-α binding to its receptor and then reduces the inflammatory response of autoimmune diseases [9, 10]. Until now, adalimumab has been approved in the United States for several indications, including rheumatoid arthritis, psoriatic arthritis, ankylosing spondylitis, Crohn’s disease, ulcerative colitis, severe chronic plaque psoriasis and juvenile idiopathic arthritis [9–12]. The sales of adalimumab achieved $13 billion in 2014 and to be top 10 selling drug of 2014 [13].
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Antibodies and their derivatives are expensive medicines. As increasing healthcare costs is a burden in many countries, reducing the cost of medicines has become a greater economic and public health priority [14] and largescale production of mAbs is faced with a number of major problems. There is an increasing need for detailed product characterization and control of the manufacturing process [15, 16]. Additionally, the United States Pharmacopoeia (USP) has explicitly stipulated for submitting the relative retention times (RT) of complementarity determining region (CDR) peptides of mAbs for suitability requirements in evaluating system suitability [17]. The characterization of CDR peptides is necessary because they are characteristic markers in distinguishing different mAbs and should be identified. However, how to accurately indentify the peptides RT of CDR regions during routine quality control (QC) analysis is still a challenge. Literature survey reveals few routine analytical methods for the determination of CDR regions peptides, but there were some complicated methods to validate the peptides of CDR, such as LC–MS–Tof and LC–TQ methodology, which were used to study peptide mapping [18, 19]. However, these methods all have their own disadvantages during routine QC analysis such as operation-complicated, platform-expensive and high requirements of sample preparation. Here we developed and validated a novel peptide mapping method to confirm the relative RT of CDR peptides of adalimumab with LC–TUV–QDa. Due to low resolution and sensitivity of QDa, it is difficult to distinguish unmodified and deamidated peptides. However, according to requirement of the USP for submitting the relative RT of CDR peptides of mAbs in evaluating system suitability, LC–QDa coupled with TUV detector is a choice to confirm the relative RT of CDR peptides. Results demonstrate LC– QDa coupled with TUV provides a simple, cost-effective, and robust method for qualitative confirmation of CDR peptides. Total eight CDR specific peptides can be identified when the CDR regions of adalimumab were enzymatically digested. A wide molecular weight ranged from 630.3 to 3187.5 Da can be detected successfully.
Materials and Methods Chemicals and Materials Adalimumab (molecular weight ~150 kDa) and trypsin were manufactured by our laboratory. HPLC-grade acetonitrile (ACN, LC/MS grade) was purchased from Fisher Scientific (Waltham, MA, USA); sodium iodide (NaI, purity ≥ 99.5 %) and fibrinopeptide (GFP, HPLC grade, purity ≥ 99.5 %) were purchased from Sigma–Aldrich (St. Louis, MO, USA). Dithiothreitol (DTT), iodoacetamide (MIA), and formic acid
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(FA, purity ~98 %, MS grade) were obtained from Fluka (GER). Trifluoroacetic Acid (TFA, HPLC grade) was purchased from Tedia (Fairfield, OH, USA). High-purity nitrogen (purity > 99.9 %) was purchased from Shanghai YiZhi Cold Engineering System Co., LTD; ultra-pure water for the LC mobile phase was prepared in-house using a MilliQ system (Millipore, Billerica, MA, USA). Moreover, other representative mAbs, such as different subtypes (IgG1, IgG2, IgG4) and different species (Chimeric Antibody, Humanized Antibody, Fully Human Antibody), including alemtuzumab, evolocumab, golimumab, cetuximab, ipilimumab, pembrolizumab, nivolumab, ofatumumab, denosumab and trastuzumab, were also expressed by our laboratory. Equipments and Methods Preparation of Stock and Standard Solutions Prior to LC–QDa analysis, the adalimumab solution was prepared by dissolving in 50 mmol L−1 NH4HCO3 pH 8.0 to give a final concentration of 200 μg mL−1 and the solution, NH4HCO3, also be treated as blank at limit of detection (LOD) analysis. And different concentration levels of samples (100, 55, 50, 45, 40, 35, 20, 16, 12, 8, 4 μg mL−1) were prepared from the 200 μg mL−1 samples by serial dilutions with NH4HCO3 solution. 8 mol L−1 guanidine hydrochloride, 1 mol L−1 of DTT solution and 2.9 mol L−1 MIA solution were prepared in advance. Sample Preparation Adalimumab or other mAbs were added into mixed solution of 375 μL 8 mol L−1 guanidine hydrochloride and 7.2 μL 1.0 mol L−1 DTT and then incubated at 37 °C for 60 min. After cooling the samples at room temperature, 8.5 μL of 2.9 mol L−1 MIA was added to denatured sample, and the samples were incubated in the dark for 45 min at 30 °C. 17.8 μL of 1.0 mol L−1 DTT was added to samples to stop the alkylation. Finally, samples were desalted to 50 mmol L−1 NH4HCO3 pH 8.0 upon Sephadex G25 column. The sample digestion was initiated by adding 2.5 μL of 4 mg mL−1 trypsin (prepared in water) and incubated at 37 °C in a preheated dry bath for 3 h. The digestion reaction was then quenched by adding 5 μL FA solution. The final tryptic digest was centrifuged at 17,000g for 10 min, and the supernatant (~500 μL) was transferred to a clean EP tube for LC–QDa analysis. LC–QDa Setup for CDR Peptides Confirmation Procedure and Data Analysis Method An ACQUITY UPLC H-Class Bio System (Waters, Milford, MA) equipped with a reliance unit (conditioned
Development and Validation of a Peptide Mapping Method for the Characterization of…
stacker, auto-sampler and TUV detector) was used to couple QDa detector. The column in application was ACQUITY UPLC BEH 130 Å C18 1.7 μm 2.1 × 100 mm (Waters, Milford, MA). To study the effect of the eluent composition on the charge envelope, the following mobile phases were evaluated: (a) 0.1 % FA in water and 0.1 % FA in ACN; (b) 0.08 % FA + 0.02 % TFA in water and 0.08 % FA + 0.02 % TFA in ACN; (c) 0.02 % FA + 0.08 % TFA in water and 0.02 % FA + 0.08 % TFA in ACN; (d) 0.1 % TFA in water and 0.1 % TFA in ACN; (e) 0.12 % TFA in water and 0.12 % TFA in ACN. The LC gradient program was 1–37 % B for 80 min, and total run time was 100 min. The flow rate was 0.2 mL min−1, and the column temperature was 45 °C; the auto-sampler temperature was set at 12 °C. QDa parameters were as follows: capillary voltage, 0.8 kV; cone voltage, 20 V; source temperature, 600 °C; desolvation gas flow, 800 L h−1. SIR mode was selected to acquire data. Empower 3 (Waters, Milford, MA) was used to control LC-QDa system and analyze data obtained. LC–MS Setup for CDR Peptides Identification Procedure and Data Analysis Method To select target peptides from adalimumab to monitor CDR region, the LC–MS/MS system consisted of a UPLC coupled to a XEVO G2-S QTof (Waters, Milford, MA) was employed. In the UPLC system (H-class BIO, Waters, Milford, MA), mobile phases were as follows: A1 (99.9 % H2O + 0.1 % FA), B1 (99.9 % ACN + 0.1 % FA). An ACQUITY UPLC BEH 130Å C18 1.7 μm 2.1 × 100 mm column (Waters, Milford, MA) was used, and the linear gradient was 1–37 % B in 80, 100 min in total. The flow rate was 0.2 mL min−1, and the injection volume was 5 μL. Data were obtained with positive ionization (electrospray ionization, ESI), and the acquisition range was 150– 2000 Da. The ion source setup was presented as follows: capillary voltage, 3.0 kV; the desolvation temperature, 450 °C; the source temperature, 120 °C; and the desolvation gas flow, 800 L h−1. The instrument was calibrated over the mass-to-charge ratio (m/z) range 50–2000 using NaI in 50 % aqueous isopropanol. The system was controlled by MassLynx 4.1 (Waters, Milford, MA), and the data analysis was performed with BiopharmaLynx 1.3.3 used MSE mode to obtain target peptides data of biotherapeutics. Optimization of Enzyme Digestion Conditions To optimize enzyme digestion conditions, protein to trypsin ratio and digestion time were investigated carefully at 37 °C. In the protein to trypsin ratio experiment, the amount of trypsin was varied at intervals with a constant
substrate. As to the effect of incubation time on digestion efficiency, samples were digested for different time at optimized protein to trypsin ratio and 37 °C.
Method Validation The validation studies are conducted to demonstrate that the obtained data are steady and reliable and this analytical method is applicable for the routine QC analysis. The specificity of LC–QDa method was validated according to the current regulatory guidelines of the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use -Q2 (ICH-Q2) and Guidance of Good Manufacturing Practices for Drug (CFDA) [20, 21]. Additionally, other validation parameters including stability, LOD, and carry-over were also evaluated. Validation runs were conducted on three consecutive days, each of which was consisted of three lots of QC sample [22]. Specificity To ensure the absence of potential interferences in the mass spectra peak region where the peptides were expected to detect, mass spectra of 10 other mAbs available were compared with adalimumab samples. Mixed sample and crosscontamination were also conducted to demonstrate the specificity of the method. Stability To ensure that this method is suitable to routine QC analysis and stable at the situation of parameter fluctuation, stability was assessed by altering composition of mobile phase, column temperature, and pH value of mobile phase. So, the detection stability of samples at different conditions (mobile phase with different proportion of TFA with 0.02, 0.08 or 0.1 %; different acidy of mobile phase with 0.08 or 0.12 % FA; different column temperature, 40 or 50 °C) were tested respectively by 6 replicates at the sample concentration of 200 μg mL−1. In addition, the stability of digested peptides in NH4HCO3 solution was determined at three batches of QC sample after storage under different conditions designed to mimic possible conditions during actual analysis. The freeze–thaw stability was evaluated over three freeze–thaw cycles. Stability was also assessed by placing samples (200 μg mL−1) at room temperature (25 °C) and 4 °C or sit in the auto-sampler at 25 °C for 24 h before injection.
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LOD
Results and Conclusion
LC-QDa assay is a novel QC method for CDR validation. Here, we have assessed the detective capacity of QDa for CDR peptides. LOD, defined as the lowest concentration on the detective range, had to fulfill the requirement that the signal-to-noise ratio was at least 3:1 [22]. Here LOD value was obtained by analyzing 3 blank NH4HCO3 solution and analyte in series concentrations.
Target Peptides Identification of Adalimumab
Carry‑over According to relevant laws and regulations, carry-over should be addressed and minimized during method development. Carry-Over of peptides may be affected by properties of amino acid residues. And this was evaluated [23]. The carry-over was assessed by injecting blank sample dierectly after a high concentration (0.2 mg mL−1) sample. Three separate batches of six replicates were tested. Calculations To eliminate the influence of the weight of large area peaks, to make the results more comparable, we used a calculation to normalize the peak area [24, 25]. Each CDR peptide peak area of samples was normalized by dividing the mean peak area of all the peptides from different samples. For each sample, the division was calculated by summing up the eight normalized values of CDR peptides. Formula (1):
Fi =
Optimization of Enzyme Digestion Conditions
Ai AVE(Ai + Bi + · · · + Xi )
Then Sx =
Fi
(1)
i = CDR peptides number, (1, 2, 3,…,8), X = Number of samples involved, (A, B, C, …, N); Terms for the equations presented above are as follows. Fi represents the normalized peptide peak area of analyte Xi. SX is the sum of the normalized peak area for a sample. In addition, during method validation, some parameters, such as stability, can be carried out to ensure that every step taken in experiment do not affect the normalized peak area significantly. Here, during assessment, peak area ratio of later to former were used to evaluate influence of conditions in this method. Formula (2):
Ri =
Pa Pb
(2)
where i presents i th peptide, Ri is the peak area ratio, and Pb and Pa are the peak area of the i th peptide before and after being changed conditions, respectively.
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The qualitative analysis was performed with QDa detector operating in positive-ion mode. However, QDa is a single quadrupole controlled by Empower 3 which could not process deconvolution directly to confirm the RT and massto-charge ratio (m/z) of target peptides, and its acquisition detection range theoretically is from 50 to 1250. Here, we adopted XEVO G2-S QTof to validate target peptides, and operating parameters were listed as above. To obtain steady and effective monitoring result, we firstly selected the high respond m/z in QTof for each peptide because QDa detector is also ionized by ESI. However, comparing to QTof system, higher m/z (>800) peptides have lower response in QDa system. The peptide responses in different charge state were shown in Fig. S1 (Electronic Supplementary Material) and higher response data were collected. Some CDR peptides were too short to achieve the high specificity, which should be eliminated. Theoretically, the heavy chain and light chain CDRs of adalimumab contained 3 and 6 peptides, respectively. However, the length of L:T8 peptide located in the light chain CDR is too short to achieve the high specificity, so it was not taken into account (Table S2, Electronic Supplementary Material). The m/z and RT derived from QTof were listed (Adalimumab, Table 1; Trastuzumab and Cetuximab, Table S1, Electronic Supplementary Material).
To optimize the digestion conditions, protein-to-trypsin ratio and digestion time were investigated. In one experiment, the amount of trypsin was varied at intervals with constant substrate. Four digestion ratios (5:1, 10:1, 20:1, 50:1) were investigated (Fig. 1a). Digestion efficiency was evaluated from the normalized average peak area ratios obtained from the target peptides mass spectra. Calculation formula was listed as above (Formula 1). As the data shown in Fig. 1a, the protein-to-trypsin ratio 5:1, 10:1 and 20:1 have a higher digest efficiency. And the trypsin efficiency is significantly decreased at ratio above 20. Although there is no significant difference between the protein-to-trypsin ratio 10:1 and 20:1, the ratio 20:1 is adjacent to the edge of the safety zone. Therefore, the protein-to-trypsin ratio 10:1 was chosen as the best enzyme digestion ratio. In addition, the digestion time was also evaluated. With the constant protein-to-trypsin ratio (10:1) and digestion temperature (37 °C), the digestion time varied. Aliquots were taken at certain digestion times (0.5, 0.75, 1, 2, 3, 4 h). It showed that the digestion efficiency in 1 h was significantly lower than that in 2 h. By increasing reaction time
Development and Validation of a Peptide Mapping Method for the Characterization of… Table 1 Validating the m/z and RT of peptides involved in the CDR regions of adalimumab with XEVO G2-S QTof system Light chain
Heavy chain
CDR1
CDR2
L:T3
L:T4
L:T6
35.3
46.24
CDR3 L:T7
L:T8
L:T9
CDR1
CDR2
CDR3
H:T3
H:T5
H:T10
57.7
57.65
RT (min)
6.79
58.94
2.3
24.67
56.28
Observed m/z
316.176 [2+] 499.256 [3+] 559.310 [3+]
798.094 [4+]
452.227 [1+]
535.267 [2+]
745.654 [3+] 888.084 [3+] 936.798 [3+]
Theoretical m/z
316.179 [2+] 499.261 [3+] 559.313 [3+]
797.863 [4+]
452.218 [1+]
535.266 [2+]
745.655 [3+] 888.089 [3+] 936.797 [3+]
Fig. 1 Optimization of enzymeprotein ratio and enzyme digestion time. a Protein-totrypsin ratio optimization. Four digestion ratios (5:1, 10:1, 20:1, 50:1) were investigated for samples digested for 3 h with trypsin at 37 °C. b Effect of incubation time on digestion efficiency. Samples were digested for 0.5, 0.75, 1, 2, 3, 4, and 5 h with trypsin at 37 °C
from 2 to 5 h, the efficiency was not significantly changed. To ensure the adalimumab being digested completely, we should better choose the digestion time of 3 h at 37 °C (Fig. 1b). Eventually, the enzymatic reaction was completed in 3 h by high protein-to-trypsin ratio (10:1, w/w) and mild temperature (37 °C).
Method Validation Specificity According to ICH-Q2, an investigation of specificity should be conducted during the validation of identification tests. To ensure that this analytical method can differentiate the adalimumab from other mAbs, we used the same methodology and parameters setting of adalimumab and adopted other 10 listed antibody drugs to evaluate this method specificity, including alemtuzumab, evolocumab, golimumab, cetuximab, ipilimumab, pembrolizumab, nivolumab, ofatumumab, denosumab and trastuzumab. As shown in Fig. 2, eight CDR peptides can be identified in adalimumab (anti TNF-alpha antibody) (8 CDR peptides were also confirmed using high-resolution QTof), but the eight significant peptides could not be detected in the 10 representative mAbs simultaneously (including a anti TNF-alpha antibody golimumab). There were only one or two relatively high
response target peptides similar to adalimumab in the 10 mAbs. For example, there was a high response peak similar to L:T9 (535.2668) at 26.2 min in Denosumab. However, these responses could not match the signature peptides for either wrong RT or incorrect the peak number (Fig. 2a). Other samples have not any significant response compared to the eight peptides of adalimumab (Fig. 2b). Conclusively, all the above demonstrated that the eight peptides were specific for adalimumab in this method. To ensure that this analytical method can accurately differentiate and identify the adalimumab in the presence of other components, we spiked trastuzumab and cetuximab into adalimumab and the final concentration ratio was isometric. From Fig. 2c, the eight specific peaks were detected, which indicated that discrimination of adalimumab was unaffected by the presence of trastuzumab and cetuximab. Additionally, we have simultaneously monitored the CDR peptides of adalimumab, trastuzumab and cetuximab. It also demonstrated high specificity to trastuzumab and cetuximab which meant that this method can be used to identificate cross-contamination from other mAbs produced in one site (Fig. 2d). Stability Evaluation of stability should be carried out to ensure that every step taken during sample preparation and sample
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J. Zhang et al. Fig. 2 Method specificity analysis. a Represents there are one or two ▸ relatively high response peptides in other mAbs responding to target peptides of adalimumab, but its retension time is deflected; b shows other mAbs do not appear any significant response with the methodology and parameter setting of adalimumab; c shows that validation of adalimumab is not affected by trantuzumab and cetuximab; d this system can be used as a potential cross-contamination monitor method
analysis as well as the storage conditions used do not affect the analytes. TFA is an important ion pairing agent in liquid chromatography for organic compounds, particularly peptides and small proteins [26]. However, in LC–MS detector system, it decrease the sensitivity through suppression of analytes ionization in ESI source. By altering eluent compositions to test if the TFA could satisfy this method, the peak areas eluted from solvent, water and ACN containing 0.02 % TFA + 0.08 % FA, 0.08 % TFA + 0.02 % FA, 0.1 % TFA or 0.12 % TFA, were evaluated (Fig. S2, Electronic Supplementary Material). It showed that compared with 0.1 % FA, peak area only occupied 1.77 and 7.03 % for 0.1 % TFA and 0.02 % TFA, respectively. With the increase of TFA concentration, ionization could be suppressed obviously (Fig. S2, Electronic Supplementary Material). Additionally, according to laws and regulations, acidity fluctuations and column temperature were evaluated. Depending on formula (2), by comparing peak area of 0.08 % FA and 0.12 % FA with 0.1 % FA, it showed that solvent acidity affected both RT and peptides response. 0.12 % FA caused a delay in RT about 0.14 min averagely compared with 0.1 % FA, while peptide were eluted 0.34 min earlier in 0.08 % FA. In terms of identifying peptides of CDR (Fig. 3a), it showed that fluctuation of acidity has no significant influence on the QC results. Similarly, variation of column temperature also impact on RT and elution efficiency (Fig. 3b). Comparing with 45 °C, L:T7 and H:T3 were eluted ineffectively at 50 and 40 °C, respectively (Fig. 3b), while other peptides were not affected; this maybe the result of sensitivity characteristic of peptides to temperature. Leaving out antibody storage and sample preparation conditions, here, we focused on the stability of processed samples. The stability of unique peptides in several situations including at room temperature (25 °C) and 4 °C for 24 h, in the auto-sampler at 25 °C for 24 h and three freeze–thaw cycles from −20 °C to room temperature were evaluated respectively. The results showed that a total of eight significant peptides were detected at different conditions, which meant that this qualitative method is robust. Moreover, the stability of peptide in various conditions was demonstrated by comparing the stored peptide peak area
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Development and Validation of a Peptide Mapping Method for the Characterization of… Fig. 3 Impact assessments of fluctuation of acidity a and column temperature b to peptides elution
Fig. 4 The stability assessment of analytes in different conditions, a 4 °C for 24 h; b room temperature (25 °C) 24 h; c sitting in the auto-sampler at 25 °C for 24 h; d three freeze– thaw cycles were tested. The results show that this method was sufficiently robust for routine QC analysis
with initial peptide peak area, using formula (2). Figure 4 presents that this method gave stable results under all storage conditions tested, suggesting that our LC-QDa method is sufficiently robust for routine QC analysis. Therefore, gathering all the results under different conditions, it suggested that there was not significant influence regarding to the fluctuation of sample analysis and processed sample storage.
adalimumab was diluted gradually (200, 100, 55, 50, 45, 40, 35, 20, 16, 12, 8, 4 μg mL−1) and detected by LC-QDa system coupled with TUV detector. The signal-to-noise ratio for the limit of determination (LOD) should be above 3:1 [22]. Finally, 20 μg mL−1 was validated as LOD and it was low enough for QC analysis during routine test.
LOD
FDA has pointed out that carryover should be assessed and monitored during analysis. If carryover occurs, it should be mitigated or reduced [22]. To assess the impact of carryover on the results, in our study, carry-over was assessed by injecting blank sample, NH4CO3, directly after a routine sample (Con. = 0.2 mg mL−1). Six replicates were tested. Carry-over was calculated by dividing the peak area of
To obtain basic data for routine testing, the limitation of detection (LOD) for eight peptides from adalimumab CDR regions was evaluated. L:T7 was adopted as the representative peptide, because its spectra response was minimal among the eight peptides. After digested by trypsin,
Carry‑over
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J. Zhang et al. (14DZ2272300), Shanghai Key technologies R&D Program of Biological medicine (15431906100) and Shanghai Excellent technical leader (13XD1424000). Compliance with ethical standards Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
References
Fig. 5 Analysis of carry-over for each peptide
peptide in routine sample by that of blank sample. In this study, the total carry-over of eight peptides is 1.69 % and the carry-over was
