CN109725046A - It is a kind of based on modeling-predicting strategy target iipidomic method - Google Patents
It is a kind of based on modeling-predicting strategy target iipidomic method Download PDFInfo
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Abstract
The invention belongs to pharmaceutical technology fields, and in particular to a kind of target iipidomic method, tactful to lysophosphatidylcholine in blood plasma (LPC) progress efficient and sensible the qualitative and quantitative analysis of more precisely a kind of application " modeling-prediction ".The present invention is with carbon chain lengths (x1) and double bond number (x2) for independent variable, remove cluster voltage (DP), impact energy (CE), retention time (RT), response factor (RF) is that dependent variable establishes multiple linear regression model, it summarizes LPC (13:0), LPC (14:0), LPC (15:0), then the liquid chromatography mass spectrometric parameter regularity of LPC (17:0) LPC (18:1) LPC (19:0) LPC (20:0) reference substance can not obtain the relevant parameter of the LPC of reference substance with equation prediction.Quantitative analysis is carried out to the LPC in blood plasma using the liquid chromatography mass spectrometric parameter come is predicted, and screens the biomarker of various cancers by independent sample T inspection, PLS-DA, single factor test ROC curve, its diagnosis capability is evaluated by multifactor ROC curve.
Description
Technical field
The invention belongs to pharmaceutical technology fields, and in particular to a kind of target iipidomic method, it is more precisely a kind of
Using tactful to lysophosphatidylcholine in blood plasma (LPC) progress efficient and sensible the qualitative and quantitative analysis of " modeling-prediction ".
Background technique
Lipid is the framework ingredient of biomembrane, is to participate in biological vital movement, provide the important substance of energy for biology.
Iipidomic belongs to the important branch of metabolism group, is the analysis for carrying out system to the intracorporal lipid material of biology, studies its phase
Interaction and effect with other biological molecule, and then disclose and closed between the physiology of lipid-metabolism and organism, pathologic process
One new branch of science of system.
Due to the diversity of lipid backbone, group and carbochain, there is largely have different physicochemical properties and dynamic in vivo
The lipoid substance of range, a method are impossible all-sidedly and accurately all lipids of qualitative, quantitative.Therefore, we can root
Several subclasses are classified as according to the skeleton of lipid, are then gone more using the internal standard of optimization, pre-treating method and LC-MS/MS condition
Accurately quantitative one or several specific Lipid Subtypes, to provide more accurate biological explanation.
Due to rouge qualitative diversity and unstability, the reference substance of lipid is difficult to obtain, this makes the accurate quantitative analysis of lipid
As a great difficult problem.Therefore, need to propose a kind of strategy and method to solve this problem.
Summary of the invention
The first purpose of this invention is to overcome the deficiencies of existing technologies, and using the strategy of " modeling-prediction ", establishes blood plasma
The analysis method of middle lysophosphatidylcholine.
Second object of the present invention is that the concentration of lysophosphatidylcholine is measured by the analysis method of foundation.
Third object of the present invention is 60 measured in Healthy People and cancer patient's blood plasma by the analysis method of foundation
The concentration of kind lysophosphatidylcholine, and gone out by Independent samples t-test, PLS-DA, single factor test and multifactor ROC Analysis and Screening
The biomarkers of various cancers.
The present invention is implemented as follows:
(1) " modeling-prediction " strategy:
It is gone cluster voltage (DP), impact energy (CE), is retained for independent variable with carbon chain lengths (x1) and double bond number (x2) first
Time (RT), response factor (RF) are that dependent variable establishes multiple linear regression model, are summarized LPC (13:0), LPC (14:0),
LPC (15:0), the liquid chromatography mass spectrometric parameter regularity of LPC (17:0) LPC (18:1) LPC (19:0) LPC (20:0) reference substance, then
The relevant parameter of the LPC of reference substance can not be obtained with equation prediction.
(2) plasma sample pre-processes:
Plasma sample is taken, methanol, inner mark solution is added, is vortexed, ultrasound centrifugation takes supernatant to carry out LC-MS analysis.
Wherein, the inner mark solution is LPC (13:0)；
The volume ratio of the blood plasma and methanol are as follows: 1:3-1:5.
(3) liquid phase separation:
Chromatographic column: Kinetex XB-C18 (4.6 × 100mm, 2.6 μm)；
Mobile phase: A phase: 0.1-0.3% formic acid water, B phase: 0.1-0.3% formic acid methanol；
Flow velocity: 0.4mlmin-1；
Sample volume: 2 μ l；
Column temperature: 25 DEG C；
Gradient elution program is shown in Table 1.
1 gradient elution program of table
(4) MS is measured:
Electric spray ion source, cation scanning, other parameters and determinand ion channel are shown in Table 2.
2 LPC mass spectrometry parameters of table
* qualitative ion
(5) various cancers data processing: are screened by independent sample T inspection, PLS-DA, single factor test ROC curve first
Biomarker, and its diagnosis capability is evaluated by multifactor ROC curve.
Detailed description of the invention
Fig. 1 is the specific flow chart of " modeling-prediction " strategy.
Fig. 2A is the diagnosis capability ROC curve figure of the LPC class biomarker of lung cancer.
Fig. 2 B is the diagnosis capability ROC curve figure of the LPC class biomarker of breast cancer.
Fig. 2 C is the diagnosis capability ROC curve figure of the LPC class biomarker of colorectal cancer.
Fig. 2 D is the diagnosis capability ROC curve figure of the LPC class biomarker of gastric cancer.
Specific embodiment
Embodiment 1
(1) it first with carbon chain lengths (x1) and double bond number (x2) for independent variable, goes cluster voltage (DP), impact energy (CE),
Retention time (RT), response factor (RF) are that dependent variable is established multiple linear regression model (table 3), are summarized LPC (13:0), LPC
(14:0), LPC (15:0), the liquid chromatography mass spectrometric parameter rule of LPC (17:0) LPC (18:1) LPC (19:0) LPC (20:0) reference substance
Rule, then can not obtain the relevant parameter of the LPC of reference substance with equation prediction, and detailed process is shown in Fig. 1.
More reproducibility regression equations of 3 liquid chromatography mass spectrometric parameter of table
(2) plasma sample pre-processes: it takes 100 μ l of plasma sample in EP pipe, 10 μ l of methanol, 50 μ l of inner mark solution is added,
Acetonitrile 400 μ l, vortex mixed 3min, ice-bath ultrasonic 10min is added, in 4 DEG C of centrifugations (12000r/min) in vortex mixed 30s
5min takes supernatant to carry out LC-MS analysis.
(3) liquid phase separation: chromatographic column: Kinetex XB-C18 (4.6 × 100mm, 2.6 μm)；Mobile phase: A phase: 0.1%
Formic acid water B phase: 0.1% formic acid methanol；Flow velocity: 0.4mlmin-1；Sample volume: 2 μ l；Column temperature: 25 DEG C；Gradient elution program is shown in
Table 1.
(4) MS is measured: electric spray ion source, and cation scanning, other parameters and determinand ion channel are shown in Table 2.
(5) biology of lung cancer data processing: is screened by independent sample T inspection, PLS-DA, single factor test ROC curve first
Marker, and its diagnosis capability is evaluated by multifactor ROC curve, the final biomarker for determining lung cancer is LPC18:1
(sn-1), LPC18:2 (sn-1), LPC18:2 (sn-2), LPC19:2 (sn-2), associated prediction ability are shown in Fig. 2A.
Embodiment 2
(1) it first with carbon chain lengths (x1) and double bond number (x2) for independent variable, goes cluster voltage (DP), impact energy (CE),
Retention time (RT), response factor (RF) are that dependent variable is established multiple linear regression model (table 3), are summarized LPC (13:0), LPC
(14:0), LPC (15:0), the liquid chromatography mass spectrometric parameter rule of LPC (17:0) LPC (18:1) LPC (19:0) LPC (20:0) reference substance
Rule, then can not obtain the relevant parameter of the LPC of reference substance with equation prediction, and detailed process is shown in Fig. 1.
(2) plasma sample pre-processes: it takes 100 μ l of plasma sample in EP pipe, 10 μ l of methanol, 50 μ l of inner mark solution is added,
Acetonitrile 400 μ l, vortex mixed 3min, ice-bath ultrasonic 10min is added, in 4 DEG C of centrifugations (12000r/min) in vortex mixed 30s
5min takes supernatant to carry out LC-MS analysis.
(3) liquid phase separation: chromatographic column: Kinetex XB-C18 (4.6 × 100mm, 2.6 μm)；Mobile phase: A phase: 0.1%
Formic acid water B phase: 0.1% formic acid methanol；Flow velocity: 0.4mlmin-1；Sample volume: 2 μ l；Column temperature: 25 DEG C；Gradient elution program is shown in
Table 1.
(4) MS is measured: electric spray ion source, and cation scanning, other parameters and determinand ion channel are shown in Table 2.
(5) life of breast cancer data processing: is screened by independent sample T inspection, PLS-DA, single factor test ROC curve first
Object marker, and its diagnosis capability is evaluated by multifactor ROC curve, the final biomarker for determining breast cancer is LPC
18:2 (sn-1), LPC 18:2 (sn-2), LPC 22:4 (sn-1), associated prediction ability are shown in Fig. 2 B.
Embodiment 3
(1) it first with carbon chain lengths (x1) and double bond number (x2) for independent variable, goes cluster voltage (DP), impact energy (CE),
Retention time (RT), response factor (RF) are that dependent variable is established multiple linear regression model (table 3), are summarized LPC (13:0), LPC
(14:0), LPC (15:0), the liquid chromatography mass spectrometric parameter rule of LPC (17:0) LPC (18:1) LPC (19:0) LPC (20:0) reference substance
Rule, then can not obtain the relevant parameter of the LPC of reference substance with equation prediction, and detailed process is shown in Fig. 1.
(2) plasma sample pre-processes: it takes 100 μ l of plasma sample in EP pipe, 10 μ l of methanol, 50 μ l of inner mark solution is added,
Acetonitrile 400 μ l, vortex mixed 3min, ice-bath ultrasonic 10min is added, in 4 DEG C of centrifugations (12000r/min) in vortex mixed 30s
5min takes supernatant to carry out LC-MS analysis.
(3) liquid phase separation: chromatographic column: Kinetex XB-C18 (4.6 × 100mm, 2.6 μm)；Mobile phase: A phase: 0.1%
Formic acid water B phase: 0.1% formic acid methanol；Flow velocity: 0.4mlmin-1；Sample volume: 2 μ l；Column temperature: 25 DEG C；Gradient elution program is shown in
Table 1.
(4) MS is measured: electric spray ion source, and cation scanning, other parameters and determinand ion channel are shown in Table 2.
(5) colorectal cancer data processing: is screened by independent sample T inspection, PLS-DA, single factor test ROC curve first
Biomarker, and its diagnosis capability is evaluated by multifactor ROC curve, the final biomarker for determining colorectal cancer is
LPC 17:0 (sn-1), LPC 19:0 (sn-2), LPC 19:1 (sn-2), LPC 19:2 (sn-2), associated prediction ability are shown in figure
2C。
Embodiment 4
(1) it first with carbon chain lengths (x1) and double bond number (x2) for independent variable, goes cluster voltage (DP), impact energy (CE),
Retention time (RT), response factor (RF) are that dependent variable is established multiple linear regression model (table 3), are summarized LPC (13:0), LPC
(14:0), LPC (15:0), the liquid chromatography mass spectrometric parameter rule of LPC (17:0) LPC (18:1) LPC (19:0) LPC (20:0) reference substance
Rule, then can not obtain the relevant parameter of the LPC of reference substance with equation prediction, and detailed process is shown in Fig. 1.
(2) plasma sample pre-processes: it takes 100 μ l of plasma sample in EP pipe, 10 μ l of methanol, 50 μ l of inner mark solution is added,
Acetonitrile 400 μ l, vortex mixed 3min, ice-bath ultrasonic 10min is added, in 4 DEG C of centrifugations (12000r/min) in vortex mixed 30s
5min takes supernatant to carry out LC-MS analysis.
(3) liquid phase separation: chromatographic column: Kinetex XB-C18 (4.6 × 100mm, 2.6 μm)；Mobile phase: A phase: 0.1%
Formic acid water B phase: 0.1% formic acid methanol；Flow velocity: 0.4mlmin-1；Sample volume: 2 μ l；Column temperature: 25 DEG C；Gradient elution program is shown in
Table 1.
(4) MS is measured: electric spray ion source, and cation scanning, other parameters and determinand ion channel are shown in Table 2.
(5) biology of gastric cancer data processing: is screened by independent sample T inspection, PLS-DA, single factor test ROC curve first
Marker, and its diagnosis capability is evaluated by multifactor ROC curve, the final biomarker for determining gastric cancer is LPC 18:0
(sn-1), LPC 19:0 (sn-2), LPC 20:0 (sn-1), LPC 20:0 (sn-2), associated prediction ability are shown in Fig. 2 D.
Claims (10)
1. the target iipidomic method that one kind is based on " modeling-prediction " strategy, which comprises the steps of:
(1) " modeling-prediction " strategy:
It is gone cluster voltage (DP), impact energy (CE), retention time with carbon chain lengths (x1) and double bond number (x2) for independent variable first
(RT), response factor (RF) is that dependent variable establishes multiple linear regression model, is summarized LPC (13:0), LPC (14:0), LPC (15:
0), the liquid chromatography mass spectrometric parameter regularity of LPC (17:0) LPC (18:1) LPC (19:0) LPC (20:0) reference substance, then uses the equation
Prediction can not obtain the relevant parameter of the LPC of reference substance；
(2) plasma sample pre-processes；
(3) liquid phase separation；
(4) MS is measured；
(5) different carcinoma data processing: is screened by independent sample T inspection, PLS-DA, single factor test and multifactor ROC curve first
The biomarker of disease.
2. the method as described in claim 1, which is characterized in that
Plasma sample is taken in step (2), methanol, inner mark solution is added, is vortexed, and ultrasound centrifugation takes supernatant to carry out LC-MS points
Analysis；Wherein, the inner mark solution is LPC (13:0), the volume ratio of the blood plasma and methanol are as follows: 1:3-1:5.
3. the method as described in claim 1, which is characterized in that
The condition of liquid phase separation is in step (3):
Chromatographic column: Kinetex XB-C18 (4.6 × 100mm, 2.6 μm)；
Mobile phase: A phase: 0.1-0.3% formic acid water, B phase: 0.1-0.3% formic acid methanol；
Flow velocity: 0.4mlmin-1；
Sample volume: 2 μ l；
Column temperature: 25 DEG C；
Gradient elution program is shown in Table 1.
1 gradient elution program of table
4. the method as described in claim 1, which is characterized in that the cancer is lung cancer, breast cancer, colorectal cancer or gastric cancer.
5. method as claimed in claim 4, which is characterized in that the biomarker of lung cancer be LPC18:1 (sn-1), LPC18:
2 (sn-1), LPC18:2 (sn-2), LPC19:2 (sn-2).
6. method as claimed in claim 4, which is characterized in that the biomarker of breast cancer is LPC 18:2 (sn-1),
LPC18:2 (sn-2), LPC 22:4 (sn-1).
7. method as claimed in claim 4, which is characterized in that the biomarker of colorectal cancer is LPC 17:0 (sn-1),
LPC 19:0 (sn-2), LPC 19:1 (sn-2), LPC 19:2 (sn-2).
8. method as claimed in claim 4, which is characterized in that the biomarker of gastric cancer is LPC 18:0 (sn-1), LPC
19:0 (sn-2), LPC 20:0 (sn-1), LPC 20:0 (sn-2).
9. application of the method described in claim 1 in the concentration of measurement lysophosphatidylcholine.
10. application of the method described in claim 1 in screening cancer biomarkers object.
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