CN106018640A - Method for rapid screening and identification of tumor biomarkers and application - Google Patents

Method for rapid screening and identification of tumor biomarkers and application Download PDF

Info

Publication number
CN106018640A
CN106018640A CN201610064097.1A CN201610064097A CN106018640A CN 106018640 A CN106018640 A CN 106018640A CN 201610064097 A CN201610064097 A CN 201610064097A CN 106018640 A CN106018640 A CN 106018640A
Authority
CN
China
Prior art keywords
hplc
tof
screening
tumor
msms
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201610064097.1A
Other languages
Chinese (zh)
Inventor
顾月清
张万存
吕丽伟
张奇
胡芳
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Pharmaceutical University
Original Assignee
China Pharmaceutical University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China Pharmaceutical University filed Critical China Pharmaceutical University
Priority to CN201610064097.1A priority Critical patent/CN106018640A/en
Publication of CN106018640A publication Critical patent/CN106018640A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/88Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02Column chromatography
    • G01N30/04Preparation or injection of sample to be analysed
    • G01N30/06Preparation

Landscapes

  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Other Investigation Or Analysis Of Materials By Electrical Means (AREA)

Abstract

The invention provides a HPLC-TOF-MSMS based metabolomic method for rapid screening and identification of tumor biomarkers and application. The specific steps include: collection and pretreatment of biological samples from tumor patients and normal people; acquisition of the biological samples' HPLC-TOF-MS and HPLC-TOF-MSMS data; HPLC-TOF-MS data processing, multivariate statistical analysis and differential metabolite screening; HPLC-TOF-MSMS data processing and differential metabolite identification; SPSS analysis for further confirmation of a group of differential compounds as tumor biomarkers; and quantitative analysis of the tumor biomarkers. The invention provides a method for rapid screening and identification of tumor biomarkers, the method has the advantages of short time and high accuracy, etc., is not only suitable for screening and identification of tumor patients' biomarkers, but is also suitable for screening and identification of the biomarkers of other metabolic diseases, like diabetes, uremia and depression, etc.

Description

A kind of rapid screening, the method identifying tumor biomarker and application
Technical field
The present invention relates to life sciences and analytical chemistry field, be specifically related to a kind of based on HPLC-TOF-MS and HPLC- The metabolism group method of TOF-MSMS is for rapid screening, qualification tumor biomarker and application thereof.
Background technology
Tumor (Tumor), especially malignant tumor, have a strong impact on the health of the mankind and threatened the life of the mankind. Within 2014, tumor registration annual report shows, it is 22% that people suffers from the probability of malignant tumor in life.National malignant tumor sickness rate is 235.23/10 ten thousand (male 268.65/10 ten thousand, and women 200.21/10 ten thousand), Chinese population standardized rate (win bit rate) 184.58/10 Ten thousand.City acceptance of the bid sickness rate 187.53/10 ten thousand;Rural area acceptance of the bid sickness rate 181.10/10 ten thousand.National malignant tumor mortality rate It is 148.81/10 ten thousand (male 186.37/10 ten thousand, and women 109.42/10 ten thousand), win bit rate 113.92/10 ten thousand.City acceptance of the bid death Rate 109.21/10 ten thousand;Rural area acceptance of the bid mortality rate 119.00/10 ten thousand.Pulmonary carcinoma, women with breast cancer, gastric cancer, hepatocarcinoma, the esophageal carcinoma, knot are straight Intestinal cancer, cervical cancer are the malignant tumor that China is common, and worldwide, the M & M of malignant tumor goes out to present Cumulative year after year trend, and surmounted cardiovascular and cerebrovascular disease in 2010 and become the rank the first disease of position of whole world mortality rate and kill Hands.Speculate that the year two thousand twenty malignant tumor increases number of the infected newly and is up to about 16,000,000 according to World Health Organization (WHO), relative to The newly-increased number of the infected of 2000 10000000 will have the increase of more than 50%.Malignant tumor has become a global publilc health Problem, so the research carrying out malignant tumor is compeled at the tip of the brow.
The early diagnosis of tumor is one of effective way improving its Overall survival, so can use in the urgent need to novel strategy In the biomarker of screening early diagnosis of tumor and molecular diagnosis is converted to clinical practice from experimentation.But, pernicious Tumor is a kind of multifactor participation, causes the complex disease of body each systemic-function Balance disorders, in generation and the development of tumor During, each component of body can produce the disorder influencing each other, interacting in structure, function and form, the metabolism of body Product can occur corresponding dynamically change therewith.The generation of the tumour-specific metabolite cover all kinds biomolecule reported Thank, such as carbohydrate metabolism, lipid metabolism, amino acid metabolism, nucleotide metabolism etc..Research shows, relative to normal cell, tumor cell goes out Modern times thank to the change of spectrum, glucose absorption rate increases and strengthens with glycolysis, and synthetic DNA polymerase and rna polymerase activity are the most relatively Normal structure is high, and protein anabolism and catabolism all strengthen, and anabolism exceedes catabolism, even just can capture The often protein breakdown products of tissue, the protein that synthesis tumor itself needs, cause body to be in cachectic states.Tumor is thin Born of the same parents' not only metabolism is vigorous, and the generation of tumor and development also be unable to do without microenvironment about, and the surrounding that tumor growth is depended on for existence is micro- Environment is mainly some key metabolites, such as glucose, nutrient and the vegetative growth factor.Near tumor cells is acyclic acidic Border, the reason constituting this environment is that tumor cell carries out glycolysis under aerobic conditions, produces substantial amounts of lactic acid, meanwhile, tumor Cell peripheral environmental induction vascular endothelial cell growth factor (VEGF) great expression, the blood capillary formation that VEGF induction is new, for Tumor brings more nutrition, promotes that it grows.Visible, tumor occurs and the early stage of development changes closely related with metabolism network. Organism metabolism product is present in the body fluid such as tissue, blood, urine, saliva, carries out the metabolite composition of these biological specimens Detection and analysis, it may be appreciated that malignant tumor occurs and material adjoint in evolution changes and energy variation, and finds pernicious Tumor occurs and abnormal metabolism thing in evolution, and is applied to the early diagnosis of malignant tumor.
Existing early diagnosis of tumor associated biomarkers is mainly based on gene, protein matter.Genomics and Proteomics is respectively from gene and the mechanism of protein layer viewpoint tumor, and the most intracellular many activities are all sent out Raw in metabolism aspect.Along with group learns progressively going deep into of research, researcher is gradually recognized, the change of genome not necessarily can obtain To expressing, system is not produced impact.The concentration of some albumen can raise due to the change of external condition, but due to this egg Bai Keneng does not possess activity, thus system is not produced impact.The disappearance of certain gene or albumen can be by other genes or egg White existence and be compensated, the net result of final reaction is zero.The metabolite of little molecule is only this sequence of events Termination fruit, it can reflect the state of living things system more accurately.Globality that metabolism group is had, can be quantitative and can be pre- Survey Journal of Sex Research and demonstrate big advantage, from the dynamic metabolic pathway of body, occur to malignant tumor and each stage of development is equal There is an applications well prospect, especially contribute to the biomarker of early diagnosis of tumor and tumor pattern classification and pathology divides in screening Significant advantage is had in type.
Summary of the invention
Goal of the invention
It is an object of the invention to set up a kind of metabolism group method based on HPLC-TOF-MSMS for knubble biological mark Remember the screening of thing, identify and apply, have an advantage in that by the biological specimen of high-volume tumour patient and normal person is carried out HPLC-TOF-MS and HPLC-TOF-MSMS analyzes, in conjunction with multivariate statistical analysis for the screening of tumor biomarker and mirror Fixed.
Technical scheme
For achieving the above object, the technical solution used in the present invention is as follows.
1, the biological specimen of the tumour patient and normal person that carry out metabonomic analysis in advance is grouped.To the sample often organized This carries out merging in equal-volume pipettes (or etc. quality weigh) and organizes respectively, and the most often group sample at least takes plural single Biological specimen merges, and is often organized the merging sample of sample, and merging sample equal-volume (quality) of each group is mixed, To quality control sample.And according to analysis purpose, each sample and merging sample are carried out metabolite extraction (as tissue samples uses Chloroform/methanol/aqueous systems or methanol/water system are extracted;Plasma/serum sample takes methanol or acetonitrile system precipitation egg In vain;Saliva, urine are directly centrifuged) obtain being available for the sample of HPLC-TOF-MS and HPLC-TOF-MSMS analysis sample introduction.Utilize The biological specimen of tumour patient and normal person is acquired by HPLC-TOF-MS, for multivariate statistical analysis.
2, utilize HPLC-TOF-MSMS that the biological specimen of tumour patient and normal person is acquired, for screening Difference metabolite is identified.The standard substance bought are carried out HPLC-TOF-MS and HPLC-TOF-MSMS to analyze for right simultaneously Difference metabolite carries out qualitative and quantitative analysis.
3, the initial data gathering HPLC-TOF-MS utilizes MassHun ter Quantitative Analysis to enter The automatic blob detection of row and chromatographic deconvolution, derive the CSV. file arranged with relative molecular mass, retention time and peak height three, according to Packed compressed for be uploaded to after ZIP. file metabolism group online treatment software MetaboAnalyst 3.0 (http: // Www.metaboanalyst.ca/MetaboAnalyst/) carry out peak alignment, filter is made an uproar and standardization.
4, the file after MetaboAnalyst 3.0 standardization utilizes SIMCA-P software to carry out principal component analysis (principal component analysis, PCA) and orthogonal partial least squares discriminant analysis (orthogonal Projection on latent structures discriminant analysi s, OPLS-DA).Utilize in PLS-DA VIP value size screening difference metabolite.
5, the authentication method of difference metabolite is: (1) utilizes HPLC-TOF-MSMS second order ms fragment to combine Human Metabolome Database (http://www.hmdb.ca/) and METLIN (https: //metlin.scripps.edu/ Index.php) the second order ms fragment ion in is compared.(2) the one-level fragment of combined standard product, secondary ion fragment and Retention time carries out qualitative analysis to difference metabolite.
6, SPSS is utilized to analyze the difference metabolite identified, further screening tumor biomarker and ROC (receiver operating characteri st ic curve is called for short ROC curve) is analyzed.
7, the quantitative analysis of tumor biomarker.
Beneficial effect
The method by carrying out first mass spectrometric and second mass analysis combines existing online, off-line and divides to large number of biological specimen Analysis software also combines existing network data base, screens and identify difference metabolite, utilizes the SPSS software difference to screening simultaneously Metabolite is analyzed to identify tumor biomarker further, and the data cycle is short, detection range width, method favorable reproducibility to have process Etc. advantage, it is suitable for tumor or the screening of other metabolism class disease biomarker and qualification.
Accompanying drawing explanation
Fig. 1 metabolism group based on HPLC-TOF-MSMS methods analyst flow chart;
The BPC figure of the HPLC-TOF-MS of Fig. 2 tumour patient and normal person;
Fig. 3 tumour patient and the 3D-PCA of normal person;
Fig. 4 tumour patient and the 3D-PLS-DA of normal person;
The VIP figure of the PLS-DA of Fig. 5 tumour patient and normal person;
The BPC figure of Fig. 6 uracil and two kinds of standard of physical product of pseudouracil;
Isomers in differentiation compound is identified (as a example by uracil and pseudouracil by Fig. 7 based on standard substance; Upper figure is first mass spectrometric, and figure below is second order ms);
Differentiation compound is identified and (with glycine betaine is by Fig. 8 second order ms based on HPLC-TOF-MSMS fragment ion Example, upper figure is first mass spectrometric, and figure below is second order ms);
Fig. 9 SPSS analysis process;
Figure 10 ROC curve.
Detailed description of the invention
A kind of metabolism group method based on HPLC-TOF-MSMS for tumour patient urine biology marker screening, Identify and application comprises the following steps.
1, the collection of sample
Collect tumour patient and normal person stage casing urina sanguinis 10mL, 1O centrifuge tube of subpackage, each centrifuge tube 1mL ,-80 DEG C of guarantors Deposit.
2, the pretreatment of sample
Taking-80 DEG C of urine sample 1mL thaw at RT preserved, 10000-15000r/min is centrifuged 1O-20min, takes supernatant 0.6mL, controlling Fmoc-glycine concentration in urine is 1 μm ol/L, is HPLC-TOF-MS and HPLC-TOF-MSMS sample. Quality control samples is prepared according to the control method of above-mentioned Quality control samples.Tumour patient and normal person biological specimen 50- 60% is used for setting up multivariate statistical analysis model, screening differentiation compound and biomarker as training set, and 20-25% makees For checking collection for that optimize multivariate statistical analysis model and biomarker, the sample of 20-25% as test set to swollen The susceptiveness of tumor biomarker, specificity detect.
3, the HPLC-TOF-MS of sample gathers
Flowing phase: A=O.1% formic acid water, B=O.1% formic acid acetonitrile, elution requirement: 0-6min, 5-10%B;6- 11min, 10-20%B;11-12min, 20%-100%B;12-18min, 100%B.Chromatographic column is Inertsil ODS-3C18 Post, its a size of 250mm × 4.6mm, i.d.5 μm, sampling volume 10 μ L, column temperature 25 DEG C, flow velocity 1mL/min.Mass spectrum yin, yang from Subpattern condition: nitrogen is used as to be dried gas, nitrogen temperature 325 DEG C, flow velocity 12L/min, atomization air pressure 35psi;Capillary voltage: Cation 4000V, anion 3500V;Fragmentation voltage: 100V;Separator voltage 60V;Quality acquisition range: zwitterion pattern It is 0.05-1KDa.
4, the HPLC-TOF-MSMS of sample gathers
The same HPLC-TOF-MS of HPLC and MS condition.MSMS applied voltage is 20V.
5, the process of HPLC-TOF-MS data
Original HPLC-TOF-MS data separate MassHunter Quan ti tative Analysis carries out the inspection of automatic peak Survey and chromatographic deconvolution, extract absolute peak tall and big in 10000, derive and arrange with relative molecular mass, retention time, peak height three CSV. file, tumour patient and normal person are respectively put into two files, both of these documents are clamped and are condensed to ZIP. files passe Carrying out peak alignment to online MetahoAnalyst 3.0, filter and make an uproar and standardization, wherein mass deviation 0.01Da, during reservation Between deviation 0.5min, data filtering mode be Interquantile range (IQR), Data scaling mode be Pareto Scaling, obtains the standardized data of HPLC-TOF-MS.
6, HPLC-TOF-MS data metabonomic analysis and the screening of difference metabolite
The standardized data of HPLC-TOF-MS is uploaded to SIMCA-P12.0 and carries out PCA and PLS-DA analysis, PCA and PSL- DA all uses first three main constituent to be analyzed.The result of PCA and PLS-DA such as accompanying drawing.The size of the VIP value of PLS-DA is used for Evaluate the size of metabolite difference, it is considered that the compound of VIP >=2 is taken as difference metabolite.
7, difference metabolite is identified by second order ms fragment based on HPLC-TOF-MSMS and retention time.Citing As follows
1. the qualification of isomerss based on standard substance, as a example by uracil and pseudouracil, pseudouracil go out peak Time is 3.7min, and the appearance time of uracil is 5.3min, although the mass spectrographic fragment ion of its one-level is the same, but its two grades Mass spectrographic fragment ion is different.
2. identify based on HPLC-MSMS second order ms fragment ion, as a example by valine and glycine betaine, valine and The relative molecular mass of glycine betaine is 117.079, and under cation mode, its one-level mass ions fragment is 118.0863, but It is to be by the second order ms fragment ion of inquiry Human Metabo lome Database and METLIN discovery valine 55.0547,57.0576,59.0503 and 72.0581 (second order ms voltage 20V), and the second order ms fragment ion of glycine betaine It is 58.0660 and 59.0703 (second order ms voltage 20V), finds to go out peak at 2.87min by comparison second order ms fragment ion First mass spectrometric fragment ion be the compound of 118.0863 be glycine betaine rather than valine.
8, the SPSS of difference metabolite analyzes and is used for confirming that tumor biomarker and ROC analyze.Comprise the steps:
1. two independent sample T inspection: the difference metabolite identified above is carried out the most respectively T inspection, judges each one by one Material between two groups of biological specimens average whether there were significant differences;
2. binomial logistic regression analysis: the above average difference metabolite that there were significant differences is carried out binomial in the lump Logistic regression analysis, by introduce forward method, backward scalping method or backward step by step filter method carry out independent variable screening, it is thus achieved that One group of tumor biomarker, obtains the recurrence side of disease pathogenetic logistic prediction optimal models according to regression coefficient (B) Journey;
3. Receiver operating curve (ROC) analyzes.Logistic (P) value obtained with above-mentioned regression equation is drawn and is subject to Examination person's performance curve, the transverse and longitudinal coordinate of ROC curve represents specificity and sensitivity, the effective ROC of this inspection respectively Its area under curve of curve (area under curve, be called for short AUC) should between 0.5-1.0, this inspection of the biggest explanation of AUC Diagnostic is the biggest.Optimal marginal value is the most permanent by means of " outstanding mounting index ", i.e. sensitivity+specificity-1, and this index takes Point corresponding during big value is exactly best cut point, utilize the coordinate figure of above-mentioned ROC curve can try to achieve the sensitivity of each coordinate points+ Specificity-1, the point that its maximum is corresponding is exactly optimal marginal value point.The biomarker of confirmation is bent to utilize above method to draw Under line, area is more than 90%, and the diagnostic of the biomarker illustrating to utilize above method to be screened is higher.
9, the quantitative analysis of biomarker.Specifically comprise the following steps that
1. the preparation of variable concentrations biomarker solution;
2. HPLC-TOF-MS and HPLC-TOF-MSMS of variable concentrations standard substance gathers;
3. the standard curve of biomarker is set up according to the mass spectrographic peak height of HPLC-TOF-MS, simultaneously to its stability, essence Density, average recovery, detection line, quantitative limit are analyzed.As we detect the standard curve of a kind of biomarker For y=4634.5x, (with a height of vertical coordinate of mass spectra peak, with the concentration of every kind of nucleosides material as abscissa, correlation coefficient is 0.9902), detection be limited to 0.114692929 μM, be quantitatively limited to 0.382309763 μM, precision O.58%, stability 6.23%, average recovery is 95.0%.

Claims (8)

1. tumour patient and normal person's biological sample difference screening compound, qualification comprise the steps:
A () tumour patient and the collection of normal person's biological specimen, pretreatment obtain HPLC-TOF-MS and HPLC-TOF-MSMS sample Product;
HIPLC-TOF-MS collection, multivariate statistical analysis and the differentiation compound of (b) tumour patient and normal person's biological specimen Screening;
C the HPLC-TOF-MSMS of () tumour patient and normal person's biological specimen gathers, analyzes and the qualification of differentiation compound;
The step that 2.SPSS screens tumor biomarker further is as follows:
A the T inspection of () tumour patient and normal person's biological specimen differentiation compound two independent sample, for screening at two groups of samples Between distribution of mean value there is the differentiation compound of significant difference;
B the average difference metabolite that there were significant differences between above group is carried out binomial logistic regression analysis by () in the lump, pass through Introduce forward method, backward scalping method or backward step by step filter method carry out independent variable screening, it is thus achieved that one group of tumor biomarker, To regression coefficient (B), and thus obtain the regression equation of disease pathogenetic logistic prediction optimal models;
C () draws the ROC curve of one group of tumor biomarker according to logistic (P) value, calculate AUC and according to " especially stepping on Index " determine optimal marginal value.
3. utilize standard substance, by Criterion curve, tumor biomarker carried out quantitative analysis, determine tumour patient and The absolute content of this material in normal person's biological specimen.
4. the 50-60% of tumour patient and normal person's biological specimen as training set be used for setting up multivariate statistical analysis model, Screening differentiation compound and biomarker, 20-25% as checking collection for that optimize multivariate statistical analysis model and raw Substance markers thing, susceptiveness, the specificity of tumor biomarker are detected by the sample of 20-25% as test set.
5. the biological specimen in claim 1 can be tissue, blood, urine or saliva, with Fmoc-glycine as internal standard, is inside marked on Final concentration in sample controls in 1-10 μm ol/L.
6. the HPLC-TOF-MS data in claim 1 combine Metaboanalyst and SIMCA-P carry out peak alignment, filter make an uproar, Utilizing the VIP of PLS-DA to screen difference metabolite after standardization, its HPLC-TOF-MS condition is as follows:
(a) HPLC condition: flowing phase: A=0.1% formic acid water, B=0.1% formic acid acetonitrile, elution requirement: 0-6min, 5-10% B;6-11min, 10-20%B;11-12min, 20%-100%B;12-18min, 100%B;
(b) Mass Spectrometry Conditions: nitrogen is used as to be dried gas, nitrogen temperature 325 DEG C, flow velocity 12L/min, atomization air pressure 35psi;Capillary tube Voltage: cation 4000V, anion 3500V;Fragmentation voltage: 100V;Separator voltage 65V;Quality acquisition range: negative and positive from Subpattern is 0.05-1KDa.
7. the HPLC-TOF-MSMS data in claim 1 are for the qualification of difference metabolite, and HPLC-TOF-MSMS condition is such as Under: second order ms applied voltage is 10V, 20V or 30V;It is 0.03-1KDa that second order ms gathers fragment ion.
8. this method is not only suitable for the screening of tumor biomarker, qualification, is also suitable for other metabolism class disease simultaneously The screening of biomarker, qualification, such as diabetes, uremia, depression etc..
CN201610064097.1A 2016-01-27 2016-01-27 Method for rapid screening and identification of tumor biomarkers and application Pending CN106018640A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610064097.1A CN106018640A (en) 2016-01-27 2016-01-27 Method for rapid screening and identification of tumor biomarkers and application

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610064097.1A CN106018640A (en) 2016-01-27 2016-01-27 Method for rapid screening and identification of tumor biomarkers and application

Publications (1)

Publication Number Publication Date
CN106018640A true CN106018640A (en) 2016-10-12

Family

ID=57082738

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610064097.1A Pending CN106018640A (en) 2016-01-27 2016-01-27 Method for rapid screening and identification of tumor biomarkers and application

Country Status (1)

Country Link
CN (1) CN106018640A (en)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106680400A (en) * 2017-01-25 2017-05-17 青岛市食品药品检验研究院 Headspace gas chromatography-mass spectrometry linked method for qualitatively and quantitatively determining vegetable oil adulteration
CN107894507A (en) * 2017-11-22 2018-04-10 南宁科城汇信息科技有限公司 One kind is found and identification liver cancer serum differentially expressed protein and proof mark thing protein process
CN107917980A (en) * 2017-11-14 2018-04-17 河南科技大学 Identify biomarker, acquisition methods and its application of the elm age of tree
CN109033747A (en) * 2018-07-20 2018-12-18 福建师范大学福清分校 It is a kind of to disturb integrator gene selection and the recognition methods of tomour specific gene subset based on PLS more
CN110243921A (en) * 2019-06-28 2019-09-17 浙江大学 A kind of Rapid tumor organization discrimination method based on tissue surface lipid fingerprint chromatogram
CN110850072A (en) * 2019-11-08 2020-02-28 郑州大学第一附属医院 Screening method and application of liver cancer anion marker
CN111257436A (en) * 2018-11-30 2020-06-09 中国科学院大连化学物理研究所 Method for identifying specific markers and differential markers of genuine medicinal materials and judging genuine medicinal materials by using mass spectrometry technology
CN115985497A (en) * 2022-12-16 2023-04-18 首都医科大学附属北京地坛医院 System for predicting prognosis of non-operation treatment primary liver cancer patient mainly based on platelet/spleen major-diameter ratio

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008145384A1 (en) * 2007-05-31 2008-12-04 Biocrates Life Sciences Ag Inflammation and oxidative stress level assay
CN101832977A (en) * 2009-03-09 2010-09-15 复旦大学附属妇产科医院 Ovarian tumor serum marker
CN102445512A (en) * 2010-10-09 2012-05-09 中国人民解放军第二军医大学 Small molecule metabolite map for identifying liver cancer, hepatitis or liver cirrhosis and manufacturing method thereof

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2008145384A1 (en) * 2007-05-31 2008-12-04 Biocrates Life Sciences Ag Inflammation and oxidative stress level assay
CN101832977A (en) * 2009-03-09 2010-09-15 复旦大学附属妇产科医院 Ovarian tumor serum marker
CN102445512A (en) * 2010-10-09 2012-05-09 中国人民解放军第二军医大学 Small molecule metabolite map for identifying liver cancer, hepatitis or liver cirrhosis and manufacturing method thereof

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
YANJIE LI 等: "Serum metabolic profiling study of lung cancer using ultra high performance liquid chromatography/quadrupole time-of-flight mass spectrometry", 《JOURNAL OF CHROMATOGRAPHY B》 *
YU CHENG 等: "Distinct Urinary Metabolic Profile of Human Colorectal Cancer", 《JOURNAL OF PROTEOME RESEARCH》 *
王鑫 等: "肝细胞癌患者血清中生物标记物研究", 《中国当代医药》 *
第10期: "癌症患者尿液的代谢组学研究", 《中国优秀硕士学位论文全文数据库 医药卫生科技辑》 *

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106680400A (en) * 2017-01-25 2017-05-17 青岛市食品药品检验研究院 Headspace gas chromatography-mass spectrometry linked method for qualitatively and quantitatively determining vegetable oil adulteration
CN106680400B (en) * 2017-01-25 2019-08-06 青岛市食品药品检验研究院 Static headspace-GC-MS is combined the adulterated method of qualitative, quantitative measurement vegetable oil
CN107917980A (en) * 2017-11-14 2018-04-17 河南科技大学 Identify biomarker, acquisition methods and its application of the elm age of tree
CN107894507A (en) * 2017-11-22 2018-04-10 南宁科城汇信息科技有限公司 One kind is found and identification liver cancer serum differentially expressed protein and proof mark thing protein process
CN109033747A (en) * 2018-07-20 2018-12-18 福建师范大学福清分校 It is a kind of to disturb integrator gene selection and the recognition methods of tomour specific gene subset based on PLS more
CN109033747B (en) * 2018-07-20 2022-03-22 福建师范大学福清分校 PLS multi-disturbance integrated gene selection-based tumor specific gene identification method
CN111257436A (en) * 2018-11-30 2020-06-09 中国科学院大连化学物理研究所 Method for identifying specific markers and differential markers of genuine medicinal materials and judging genuine medicinal materials by using mass spectrometry technology
CN110243921A (en) * 2019-06-28 2019-09-17 浙江大学 A kind of Rapid tumor organization discrimination method based on tissue surface lipid fingerprint chromatogram
CN110850072A (en) * 2019-11-08 2020-02-28 郑州大学第一附属医院 Screening method and application of liver cancer anion marker
CN115985497A (en) * 2022-12-16 2023-04-18 首都医科大学附属北京地坛医院 System for predicting prognosis of non-operation treatment primary liver cancer patient mainly based on platelet/spleen major-diameter ratio
CN115985497B (en) * 2022-12-16 2023-08-08 首都医科大学附属北京地坛医院 System for predicting prognosis of patient with non-operative treatment primary liver cancer based on platelet/spleen aspect ratio value

Similar Documents

Publication Publication Date Title
CN106018640A (en) Method for rapid screening and identification of tumor biomarkers and application
CN109884302B (en) Lung cancer early diagnosis marker based on metabonomics and artificial intelligence technology and application thereof
CN110057955B (en) Method for screening specific serum marker of hepatitis B
CN102323246B (en) One group for detecting the characteristic protein of pulmonary carcinoma
CN111289736A (en) Slow obstructive pulmonary early diagnosis marker based on metabonomics and application thereof
CN109725072A (en) A kind of targeting qualitative, quantitative metabonomic analysis methods of the screening biomarker for cancer based on LC-MS/MS technology
CN101611313A (en) Mass spectrometry biomarker assay
CN111562338B (en) Application of transparent renal cell carcinoma metabolic marker in renal cell carcinoma early screening and diagnosis product
CN101769910A (en) Method for screening malignant ovarian tumor markers from blood serum metabolic profiling
CN101832977A (en) Ovarian tumor serum marker
US20130023056A1 (en) Early detection of recurrent breast cancer using metabolite profiling
US20120142542A1 (en) Metabolite Biomarkers for the Detection of Esophageal Cancer Using NMR
CN103776891A (en) Method for detecting differentially-expressed protein
CN110057954B (en) Application of plasma metabolism marker in diagnosis or monitoring of HBV
CN105759065A (en) Use of blood metabolism marker and depression detecting kit
CN101424661B (en) Serodiagnosis model establishing method for active tuberculosis disease
CN112151121A (en) Diagnostic marker, kit and screening method for esophageal cancer diagnosis and construction method of esophageal cancer diagnosis model
CN106370753A (en) Identification and analysis method for coronary heart disease urine metabolic markers
CN109946411B (en) Biomarker for diagnosis of ossification of yellow ligament of thoracic vertebra and screening method thereof
CN106018572A (en) HPLC-TOF-MS/MS method for simultaneous determination of 10 nucleosides and application
CN110568196B (en) Metabolic marker related to low-grade glioma in urine and application thereof
CN101169417A (en) Reagent kit and method for judging normal person and liver cancer using magnetic bead supported matrix
CN109946467B (en) Biomarker for ossification diagnosis of thoracic vertebra ligamentum flavum
CN103694342B (en) Detect the polypeptide marker of people's aging
CN102324001A (en) Method for predicting gastric cancer on the basis of high performance liquid chromatography/mass spectrometry (HPLC/MS) metabonomics data analysis

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20161012