CN102323351B - Bladder cancer patient urine specific metabolite spectrum, establishing method and application - Google Patents
Bladder cancer patient urine specific metabolite spectrum, establishing method and application Download PDFInfo
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Abstract
The invention provides a bladder cancer patient urine specific metabolite spectrum, an establishing method and an application, and especially provides a method for establishing a spectrum of specific metabolites in urine of bladder cancer patients, and a method for screening a related specific biomarker. Through metabonomics, especially metabonomics based on liquid chromatography-mass spectrometry combined technology, the invention establishes a bladder cancer patient urine specific metabolite spectrum. The invention provides a basis for early diagnosis of bladder cancer and bladder cancer diseases with different pathological stages, and also provides a spectrum of specific metabolites in urine of bladder cancer patients and a related specific biomarker. The method provided by the invention has the characteristics of noninvasiveness, convenience, and rapidness, can accurately reflect the difference of metabolite spectra of bladder cancer patients and normal people, and has high specificity.
Description
Technical field
The present invention relates to cancer, particularly carcinoma of urinary bladder.The invention still further relates to metabolism group, particularly the metabolism group based on liquid chromatography mass combination analysis technology.The present invention provides foundation for early diagnosis carcinoma of urinary bladder and different pathological carcinoma of urinary bladder disease by stages, and specific metabolic thing spectrum and relative specific biomarker in transitional cell bladder carcinoma are provided.And the present invention also provides the method that in transitional cell bladder carcinoma, specific metabolic thing is composed and screened relative specific biomarker of setting up.
Background technology
Carcinoma of urinary bladder is one of common clinically tumour, and in world wide, the carcinoma of urinary bladder incidence of disease occupies the 9th [1] of malignant tumour.Carcinoma of urinary bladder can betide any age, children even, but main age of onset is after the middle age, and its morbidity increases with advancing age.In China, the bladder carcinoma in males incidence of disease occupies the 8th of general tumour, and women comes after 12, and the incidence of disease is far below western countries.In recent years, the report of China's urban tumor incidence is shown as rising trend, 3～4 times [2] that carcinoma of urinary bladder male sex's incidence of disease is women.At present for the diagnosis of carcinoma of urinary bladder, lack more unified standard and existing diagnostic method and all there is certain defect as Symptom Observation (blood urine), ultrasonic examination, CT examination, cytolgical examination and cystoscope etc., for example, the observation of symptom subjectivity is too strong, ultrasonic examination, CT examination, cytolgical examination and cystoscope etc. are intrusive mood diagnosis, to patient, bring extra misery; The shortcomings such as markers in diagnosis single in the urine having now found that exists susceptibility and poor specificity, and false positive rate is higher, develop a kind of without wound, specificity, Diagnosis of Bladder method have great importance [3,4] accurately.
Metabolism group is the door system biology subject growing up after genomics and proteomics, postgraduate's object interior or external factor impact after its endogenous metabolism species, quantity and Changing Pattern.Metabolism group is analyzed organic whole metabolism spectrum, seeks the corresponding relation between metabolin and physiological and pathological variation, thereby provides foundation for medical diagnosis on disease.The employing gas chromatography combined with mass spectrometry such as Pasikanti have been analyzed the metabolite profile in urine, and the method for its metabolism group has 100% sensitivity, can be used for early diagnosis and the staging [5] of carcinoma of urinary bladder.Yet gas chromatography combined with mass spectrometry analysis only can be analyzed the metabolin that polarity is lower, and the method needs derivatization step, complex operation, and reappearance is poor, and cost is high.
Summary of the invention
For existing Diagnosis of Bladder method have shortcomings such as traumatic, invasive, problem to be solved by this invention is to provide a kind of metabonomic technology and provides foundation for carcinoma of urinary bladder early diagnosis, the method has highly sensitive, specificity is good, without advantages such as wounds.
The present invention adopts the analytical approach of liquid chromatography mass coupling, and urine is only needed to simple process, with low cost, is applicable to extensive examination, and has equally good specificity and sensitivity, has extraordinary application prospect.
The present invention provides foundation for early diagnosis carcinoma of urinary bladder and different pathological carcinoma of urinary bladder disease by stages.By finding specific metabolic thing spectrum and relative specific biomarker in transitional cell bladder carcinoma, set up the method that detects this biomarker.
The present invention uses the metabolite profile of analyzing in batch normal population and bladder cancer patients group's urine specimen based on liquid chromatography mass combination analysis technology, and analyze the relatively metabolite profile of normal population and bladder cancer patients group with pattern-recognition, determine specificity liquid chromatography mass data, qualitative or quantitative test bladder cancer patients obtains specific metabolic thing spectrum data, for follow-up theoretical research and clinical diagnosis provide foundation.
The invention provides the application of a kind of metabonomic technology in carcinoma of urinary bladder disease, the steps include:
(1) collection of sample and processing: the urine specimen of collecting clinical patient or animal pattern; Sample carries out liquid-liquid extraction through organic solvent, and organic solvent includes but not limited to ethyl acetate, chloroform, ether, normal butyl alcohol, sherwood oil, methylene chloride, acetonitrile etc.; Or through albumen precipitation, albumen precipitation method comprises and adds organic solvent (for example methyl alcohol, ethanol, acetone, acetonitrile, isopropyl alcohol), all kinds of acid-alkali salt precipitation, thermal precipitation, filtration/ultrafiltration, Solid-Phase Extraction, and the independent or comprehensive mode of method such as centrifugal is processed; Sample is dried or is not dried the various organic solvents of recycling (isopropyl alcohol, chloroform etc., are preferably methyl alcohol, acetonitrile for methyl alcohol for example, acetonitrile) or water (separately or combination, not saliferous or saliferous) and dissolves; Sample does not carry out derivatization or utilizes reagent (for example trimethyl silane, ethyl chloroformate, the silica-based trifluoroacetamide of N-methyl trimethoxy base etc.) to carry out derivatization treatment.
(2) (HPLC-MS) measured in liquid chromatography mass analysis: adopt and obtain the metabolite profile in urine based on liquid chromatography and mass spectrographic method, metabolite profile is through processing data such as obtaining the peak height at each peak or peak area and mass number and retention time.
(3) metabolite profile in pattern recognition analysis urine: above-mentioned data acquisition multivariate data statistical software, can be R, MATLAB, SPSS, SIMCA-P etc., select principal component analysis (PCA) (PCA), partial least square method (PLS), partial least square method discriminatory analysis (PLS-DA), quadrature partial least square method (OPLS), quadrature partial least square method discriminatory analysis (OPLS-DA), the methods such as cluster analysis are set up mathematical model, the metabolite profile producing in step (2) is analyzed, the difference that compares normal person and bladder cancer patients metabolite profile, thereby determine specific metabolic thing spectrum.
(4) biomarker: found that biomarker in one group of urine provides foundation for the diagnosis of carcinoma of urinary bladder disease or for carcinoma of urinary bladder early diagnosis.
The little molecule of body endogenous is the basis of vital movement, the state of disease and the variation of body function will inevitably cause the variation of metabolism in vivo of the little molecule of endogenous, research shows, there is obvious difference in normal person and carcinoma of urinary bladder patient's metabolism spectrum, and the spectrum of the metabolism in different pathological phase bladder cancer patients exists obvious difference equally, and metabonomic technology contributes to the diagnosis of the diseases such as carcinoma of urinary bladder.
1. the metabolite profile in detection urine and relevant biomarker, compare with commonly using at present the invasive methods such as cystoscopy, cytolgical examination, has without wound, conveniently feature.
2. accurately reflection bladder cancer patients and normal person's metabolism spectral difference is different, and specificity is high.
Do not wish to be bound by any theory restrictions, inventor points out that these biomarkers are the endogenous compound that are present in human body.By method of the present invention, the metabolite profile of experimenter's urine is analyzed, the quality numerical value in metabolite profile is indicated the existence of corresponding biomarker and the correspondence position in metabolite profile.Meanwhile, the described biomarker of bladder cancer patients shows certain content range value in its metabolite profile.
Embodiment
Below in conjunction with embodiment, embodiment of the present invention are described in detail, but it will be understood to those of skill in the art that the following example is only for the present invention is described, and should not be considered as limiting scope of the present invention.
One aspect of the present invention provides a kind of method of the experimenter's of foundation urine metabolite spectrum, comprises the following steps:
(1) collection of sample and processing: collect experimenter's urine specimen, the large molecule such as treated removal protein;
(2) liquid chromatography mass analysis is measured: adopt and obtain the metabolite profile in urine based on liquid chromatography and mass spectrographic method, and metabolism spectrum is analyzed.
The present invention provides a kind of method of setting up bladder cancer patient urine specific metabolite spectrum on the other hand, comprises the following steps:
(1) collection of sample and processing: collect clinical patient and normal person's urine specimen, the large molecule such as treated removal protein;
(2) liquid chromatography mass analysis is measured: adopt and obtain the metabolite profile in urine based on liquid chromatography and mass spectrographic method, and metabolism spectrum is analyzed;
(3) metabolite profile in pattern recognition analysis urine: above-mentioned data acquisition is set up mathematical model with multivariate data statistical software, the metabolite profile producing in step (2) is analyzed, the difference that compares normal person and bladder cancer patients metabolite profile, thus determine specific metabolic thing spectrum.
In the method for a kind of experimenter's of foundation urine metabolite spectrum of the present invention or a kind of method of setting up bladder cancer patient urine specific metabolite spectrum, the processing in step (1) comprises that sample carries out liquid-liquid extraction through organic solvent; Or through albumen precipitation; Sample is dried or is not dried, and recycling organic solvent or water independent or combination dissolve, and described water does not conform to salt or saliferous, and salt comprises sodium chloride, phosphate, carbonate etc.; Sample does not carry out derivatization or utilizes reagent to carry out derivatization treatment.
In a specific embodiment of the present invention, step (1) organic solvent carries out in liquid-liquid extraction, and described organic solvent includes but not limited to ethyl acetate, chloroform, ether, normal butyl alcohol, sherwood oil, methylene chloride, acetonitrile.
In a specific embodiment of the present invention, in step (1) albumen precipitation, include but not limited to add organic solvent, all kinds of acid-alkali salt precipitation, thermal precipitation, filtration/ultrafiltration, Solid-Phase Extraction, centrifugal method separately or the mode of combination process, wherein said organic solvent comprises methyl alcohol, ethanol, acetone, acetonitrile, isopropyl alcohol.
In a specific embodiment of the present invention, in step (1), preferably include and use albumen precipitation method to process, preferably use ethanol to carry out albumen precipitation.
In a specific embodiment of the present invention, step (1) sample is dried or is not dried, and in recycling organic solvent or water-soluble solution, described organic solvent comprises methyl alcohol, acetonitrile, isopropyl alcohol, chloroform, is preferably methyl alcohol, acetonitrile.
In a specific embodiment of the present invention, step (1) sample utilizes reagent to carry out in derivatization treatment, and described reagent comprises trimethyl silane, ethyl chloroformate, the silica-based trifluoroacetamide of N-methyl trimethoxy base.
In a specific embodiment of the present invention, metabolite profile obtains raw data through processing in step (2), and described raw data is the data such as the peak height at each peak or peak area and mass number and retention time preferably.
In a specific embodiment of the present invention, in step (2), raw data is carried out to peak detection and peak match, preferably adopt XCMS software to carry out the detection of described peak and peak match.
In a specific embodiment of the present invention, multivariate data statistical software in step (3) comprises R, MATLAB, SPSS, SIMCA-P, select principal component analysis (PCA) (PCA), partial least square method (PLS), partial least square method discriminatory analysis (PLS-DA), quadrature partial least square method (OPLS), quadrature partial least square method discriminatory analysis (OPLS-DA), one or more of clustering method or these methods are set up mathematical model, preferably use the capable peak of XCMS software to detect and peak match, adopt R software to adopt O-PLS-DA to carry out otherness variable to normal group metabolite profile and carcinoma of urinary bladder group metabolite profile and carry out pattern recognition analysis, set up O-PLS-DA mathematical model,
The present invention comprises the bladder cancer patient urine specific metabolite spectrum of the method foundation of using kind provided by the present invention to set up bladder cancer patient urine specific metabolite spectrum on the other hand.
The present invention further provides the purposes of described metabolite profile, it is for judging whether described experimenter suffers from carcinoma of urinary bladder, comprising following steps: experimenter's sample evidence method of the present invention is analyzed, and result and bladder cancer patient urine specific metabolite spectrum of the present invention are compared, preferably utilize multivariate statistical model to sort out and compare, thereby judge whether described experimenter suffers from carcinoma of urinary bladder.
The present invention also comprises the method for the biomarker in screening urine, except above-mentioned steps (1)-(3), it is further comprising the steps for screening the biomarker of transitional cell bladder carcinoma, and described biomarker provides foundation for the diagnosis of carcinoma of urinary bladder disease or for carcinoma of urinary bladder early diagnosis:
Adopt principal component analytical method and OPLS-DA to carry out otherness variable to normal group metabolite profile and carcinoma of urinary bladder group metabolite profile and carry out pattern recognition analysis, preferably adopt SIMCA-P+12.0.1 software, further by VIP value and S-plot, screen potential biomarker.
In the method for the biomarker in screening urine of the present invention, according to the potential mark of VIP value screening of pattern recognition model OPLS-DA, in OPLS-DA model, extract the variable that VIP value is greater than 3, and further further select to have the variable of relatively large deviation and correlativity according to load diagram and S-plot figure, and the variable that is less than 0.05 in conjunction with P value.
The present invention also comprises according to the method for the biomarker in above-mentioned screening urine, the biomarker of the carcinoma of urinary bladder obtaining, described biomarker is in OPLS-DA model, to extract the variable that VIP value is greater than 3, and in load diagram and S-plot figure, there is the variable of relatively large deviation and correlativity and the variable that is less than 0.05 in conjunction with P value.
Biomarker of the present invention preferably includes one or more in 21 kinds of biomarkers shown in table 1, preferably at least comprises the CHO in table 1
8n, and comprise at least a kind in table 1,2 kinds, 3 kinds, 4 kinds, 5 kinds, 6 kinds, 7 kinds, 8 kinds, 9 kinds, 10 kinds, 15 kinds, or 21 kinds.
The present invention also relates to use biomarker of the present invention on the other hand for the purposes of diagnosing bladder cancer, the method that wherein experimenter's urine is set up experimenter's urine metabolite spectrum through kind of the present invention is analyzed, and determines biomarker of the present invention according to gained experimenter urine metabolite spectrum.
The present invention further comprises the purposes of described biomarker in the kit for the preparation of diagnosing bladder cancer.
Embodiment
Embodiment 1
1.1 sample collections: collect volunteer's urina sanguinis, be placed in immediately-80 ℃ of low temperature refrigerators and store.Normal group is collected 34 parts of urine specimens altogether, and carcinoma of urinary bladder group is collected 48 parts of urine specimens altogether.
The processing of 1.2 samples: freezing sample is placed under room temperature and thaws, gets urine specimen 500 μ L as in 2.0mL centrifuge tube, adds methyl alcohol 500 μ L dilutions, and the centrifugal 5min of 10000rpm is standby.
1.3 liquid chromatography mass combination analysis
Instrument and equipment
HPLC-MS-LTQ?Orbitrap?Discovery(Thermo，Germany)
Chromatographic condition
Chromatographic column: C18 post (150mm * 2.1mm, 5 μ m); Mobile phase A: 0.1% aqueous formic acid, Mobile phase B: 0.1% formic acid acetonitrile solution; Gradient elution program: 0～3min, 5%B, 3～36min, 5%～80%B, 36～40min, 80%～100%B, 40～45min, 100%B, 45～50min, 100%～5%B, 50～60min, 5%B; Flow velocity: 0.2mL/min; Sampling volume 20 μ L.
Mass spectrum condition
ESI ion gun, positive ion mode image data, quality of scanning m/z 50～1000.Source parameters ESI: sheath gas is 10, auxiliary gas is 5, capillary temperature is 350 ℃, taper hole voltage 4.5KV.
1.4 data processing
Adopt XCMS software (for example deriving from http://metlin.scripps.edu/xcms/) to carry out peak detection and peak match to raw data, (Fig. 1 a) carries out otherness variable and carries out pattern recognition analysis, sets up O-PLS-DA mathematical model to normal group metabolite profile (Fig. 1 b) and carcinoma of urinary bladder group metabolite profile to adopt R software to adopt O-PLS-DA (Orthogonalprojections to latent structures discriminant analysis).
1.5 compare and definite characteristic metabolite profile
By comparing the urine metabolite spectrogram of normal group and carcinoma of urinary bladder group, set up transitional cell bladder carcinoma metabolite profile (Fig. 1), and by K-O-PLS-DA model, unknown sample is predicted, contribute to the diagnosis of carcinoma of urinary bladder disease.Preliminary Results, normal and carcinoma of urinary bladder group can be distinguished preferably in tp direction; By choosing 80% normal group and carcinoma of urinary bladder group metabolite profile data acquisition, use K-O-PLS-DA modeling as training set (PZC-train and PGC-train), this model can 100% the grouping (PZC-test and PGC-test) of Accurate Prediction 20% residue test sample book, there is higher accuracy and specificity, there is the good prospect that is developed as diagnostic method, thereby provide according to (Fig. 2) for the diagnosis of carcinoma of urinary bladder disease.
Case study on implementation 2
2.1 sample collections: collect volunteer's urina sanguinis, be placed in immediately-80 ℃ of low temperature refrigerators and store.Normal group is collected 34 parts of urine specimens altogether, and carcinoma of urinary bladder group is collected 48 parts of urine specimens altogether.
The processing of 2.2 samples: freezing sample is placed under room temperature and thaws, gets urine specimen 500 μ L as in 2.0mL centrifuge tube, adds methyl alcohol 500 μ L dilutions, and the centrifugal 5min of 10000rpm is standby.
2.3 liquid chromatography mass combination analysis
Instrument and equipment
HPLC-MS-LTQ?Orbitrap?Discovery(Thermo，Germany)
Chromatographic condition
Chromatographic column: C18 post (150mm * 2.1mm, 5 μ m); Mobile phase A: 0.1% aqueous formic acid, Mobile phase B: 0.1% formic acid acetonitrile solution; Gradient elution program: 0～3min, 5%B, 3～36min, 5%～80%B, 36～40min, 80%～100%B, 40～45min, 100%B, 45～50min, 100%～5%B, 50～60min, 5%B; Flow velocity: 0.2mL/min; Sampling volume 20 μ L.
Mass spectrum condition
ESI ion gun, positive ion mode image data, quality of scanning m/z 50～1000.Source parameters ESI: sheath gas is 10, auxiliary gas is 5, capillary temperature is 350 ℃, taper hole voltage 4.5KV.
2.4 data processing
Adopt XCMS software to the raw data pre-treatment of be correlated with, obtain two-dimensional matrix data, T-test adds up the significant difference at metabolin peak; Adopt SIMCA-P+12.0.1 software to adopt principal component analytical method (PCA) and OPLS-DA (Orthogonal partial least squaresproject to latent structures-discriminant analysis) to carry out otherness variable to normal group metabolite profile (Fig. 1 b) and carcinoma of urinary bladder group metabolite profile and carry out pattern recognition analysis, in conjunction with VIP and S-plot figure, filter out potential biomarker.
2.5 metabolism analysis of spectrums and potential biomarker
2.5.1 principal component analysis (PCA) (PCA)
PCA is a kind of without teacher's supervised recognition method, can in hyperspace, describe intuitively the difference between sample.As can be seen from Figure 2, in pca model, two groups are substantially separated in first principal component direction, show that the urine metabolism spectrum of normal group and carcinoma of urinary bladder group exists significantly difference.Carcinoma of urinary bladder group sample distribution, at the two ends of normal group, shows that carcinoma of urinary bladder group sample self exists obvious difference, sees Fig. 3,4.
2.5.2 quadrature partial least square method discriminatory analysis (OPLS-DA)
Adopt OPLS-DA method to distinguish normal group and carcinoma of urinary bladder group, further by VIP value and S-plot, screen potential mark.As can be seen from Figure 4, normal group and carcinoma of urinary bladder group are at t[1] significantly distinguished in direction.As shown in Figure 5, in S-plot figure, each point represents a variable, and S-plot figure shows the correlativity of variable and model.Variable with frame triangular marker is the variable that VIP is greater than 3, and they have larger deviation and have good correlativity with model, see Fig. 5,6.
2.5.3 potential source biomolecule label
According to the potential mark of VIP value screening of pattern recognition model OPLS-DA, in OPLS-DA model, extract the variable that VIP value is greater than 3, and further according to load diagram and S-plot figure, further select to have the variable of relatively large deviation and correlativity, and the variable that is less than 0.05 in conjunction with P value, obtain altogether 21 potential biomarkers, as shown in table 1.
The biomarker that table 1 is potential
List of references:
1.Parkin?MD，Bray?F，Ferlay?J，et?al.Global?Cancer?Statistics，2002.A?Cancer?Journal?for?Clinicians，2005，55，74-108
2. Xu Gui is blue, gives million people, Duan Jijun, etc. year Incidence analysis of nineteen ninety-five-1997, Wuhan City. Chinese tumour, 2002,11,455-456
3.Schroeder?GL，Lorenzo?Gomez?MF，Hautmann?SH，et?al.Aside?by?side?comparison?of?cytology?and?biomarkers?for?bladdercancer?detection.The?Journal?of?Urology，2004，172，1123-1126
4.Glas?AS，Roos?D，Deutekom?M，Zwinderman?AH，Bossuyt?PM，Kurth?KH.Tumor?markers?in?the?diagnosis?of?primary?bladdercancer.a?systematic?review.The?Journal?of?Urology，2003，169，1975-1982
5.Kishore?Kumar?Pasikanti，Kesavan?Esuvaranathan，Paul?C.Ho，et?al.Noninvasive?urinary?metabonomic?diagnosis?of?humanbladder?cancer.Journal?of?Proteome?Research，2010，9，2988-2995
Accompanying drawing explanation
Fig. 1. bladder cancer patients group (a) and normal person's group (b) mass spectrum total ion current figure.
Fig. 2 .K-O-PLS-DA model.PZC-train is normal group training set, PZC-test normal group forecast set; PGC-train is carcinoma of urinary bladder group training set, PGC-test carcinoma of urinary bladder group forecast set.
Fig. 3. principal component analysis (PCA) shot chart.Rhombus represents normal group, and square represents carcinoma of urinary bladder group.
Fig. 4. principal component analysis (PCA) load diagram.With frame triangle, represent the variable that VIP value is greater than 3.
Fig. 5 .OPLS-DA shot chart.Rhombus represents normal group, and square represents carcinoma of urinary bladder group.
Fig. 6 .S-plot figure.With frame triangle, represent the variable that VIP value is greater than 3.
Claims (2)
1. the composition for carcinoma of urinary bladder medical diagnosis on disease that comprises following biomarker, described biomarker at least comprises the biomarker that in table 1, quality is 154.9685, and comprises at least a kind in table 1,2 kinds, 3 kinds, 4 kinds, 5 kinds, 6 kinds, 7 kinds, 8 kinds, 9 kinds, 10 kinds, 15 kinds, or 21 kinds:
Table 1
2. the purposes of biomarker in the kit for the preparation of diagnosing bladder cancer, described biomarker at least comprises the biomarker that in the table 1 shown in claim 1, quality is 154.9685, and comprises at least a kind in table 1,2 kinds, 3 kinds, 4 kinds, 5 kinds, 6 kinds, 7 kinds, 8 kinds, 9 kinds, 10 kinds, 15 kinds, or 21 kinds.
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| KR102150837B1 (en) * | 2019-02-22 | 2020-09-03 | 고려대학교 산학협력단 | Metabolome sample preparation methods for metabolite profiling of human urine samples |
| WO2020215219A1 (en) * | 2019-04-23 | 2020-10-29 | 中国医学科学院北京协和医院 | Machine learning-based autism spectrum disorder diagnosis method and device using metabolite as marker |
| CN110794054A (en) * | 2019-11-01 | 2020-02-14 | 中国医学科学院基础医学研究所 | Metabolic marker of medulloblastoma in urine and application thereof |
| CN111208229B (en) * | 2020-01-17 | 2021-02-26 | 华中农业大学 | Screening method of serum metabolic marker for low bone density joint diagnosis of laying hens and application of serum metabolic marker |
| CN112834644A (en) * | 2020-12-31 | 2021-05-25 | 郑州大学第一附属医院 | Bladder cancer related combined marker and detection kit |
-
2011
- 2011-08-12 CN CN201110230207.4A patent/CN102323351B/en active Active
Non-Patent Citations (3)
| Title |
|---|
| Detection of Bladder Cancer in Human Urine by Metabolomic Profiling Using High Performance Liquid Chromatography/Mass Spectrometry;Haleem J. Issaq等;《The journal of urology》;20080630;第179卷(第6期);摘要、正文第2423页第2栏样品制备和分析，数据解读和分析部分至第2425页讨论部分,第2426页第1栏第1段 * |
| Haleem J. Issaq等.Detection of Bladder Cancer in Human Urine by Metabolomic Profiling Using High Performance Liquid Chromatography/Mass Spectrometry.《The journal of urology》.2008,第179卷(第6期),摘要、正文第2423页第2栏样品制备和分析，数据解读和分析部分至第2425页讨论部分,第2426页第1栏第1段. * |
| 陈静等.一种基于液相色谱-质谱技术进行血清代谢组学研究的方法：从代谢指纹到潜在标志物.《中国科学B辑：化学》.2009,第39卷(第10期),摘要、正文第1269页第2.4节,第1272页第(4)段. * |
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