CN1707258A - Method for early detecting gastric cancer from blood serum - Google Patents
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Abstract
The early stage stomach cancer detecting method with serum is to utilize fingerprint comprising ten proteins of charge/mass ratio 4141 Da, 4474 Da, 3940 Da, 4633 Da, 4792 Da, 3957 Da, 4976 Da, 5348 Da, 4096 Da and 5915 Da separately in detection. The detecting method includes the following specific steps: preparing serum, collecting mass spectrum data, and biological informatics analysis of the collected data. The present invention provides new concept and method for the early stage diagnosis of stomach cancer and lays foundation of new tumor marker. The method of the present invention is reasonable and feasible, and has combined biological informatics method and analysis method with specificity and sensitivity over 84 % each and greatly raised stomach cancer detecting rate.
Description
Technical field
The present invention relates to malignant tumour early detection method, for a kind of detection method of new Noninvasive, cancer of the stomach is carried out early detection, early detection, its susceptibility and specificity all reach more than 84%.
Background technology
Cancer of the stomach is still the major reason of cancer mortality as the modal second largest malignant tumour in the whole world.The incidence of disease in China's cancer of the stomach is about 20,/10 ten thousand, and mortality ratio occupies the 2nd of cancer mortality in China, and belongs to middle and advanced stages among the prescription on individual diagnosis patient, poor prognosis more.According to statistics, radical surgery treatment 5 years survival rates early stage, advanced gastric carcinoma are respectively 90%, 40%, so have only early detection, early diagnosis that more patients with gastric cancer is benefited, but how asymptomatic early carcinoma of stomach is or nonspecific symptom arranged, at present China's early carcinoma of stomach discovery rate is about 10%, so have only the crowd to high risk factor is arranged to carry out the diagnostic level that extensive examination could improve early carcinoma of stomach.
Detecting cancer of the stomach the best way at present is fibergastroscopy, but because its invasive operation makes most of people be difficult to tolerate and can not be used for crowd's examination.The noninvasive method that detects cancer of the stomach mainly contains following several: 1. the present the most frequently used serum tumor marker of blood serum tumor markers mainly contains CEA, CA199, PG1/2, CA72-4 etc.,, between 16%-75%, be difficult to become desirable tumor marker and be used for clinical detection or examination in the The positive expression rate of cancer of the stomach serum; 2. the expression such as sudden change, oncogene such as c-met, c-erbB2 of some common tumor suppressor genes such as P53, APC etc. rising also can be used for detecting cancer of the stomach in the detection blood, but all there is the low contradiction of sensitivity and specificity, the effect that is used for serology detection cancer of the stomach is less, so seek all more satisfactory Noninvasive of sensitivity and specificity and be again high flux fast inspection method become present research focus, the emerging proteomic techniques and the development of method then provide technology platform for this reason.
The generation of cancer of the stomach, development be the process of experience gastritis companion mucous membrane atypical hyperplasia, early carcinoma of stomach, advanced gastric carcinoma and even transfer mostly, is the interactive result of the inside and outside cause of disease.Related to the change of polygenes and expressing protein product thereof, and protein is changed into the final form of changes of function, the protein performance analysis can reflect that more disease takes place and development.The main task of proteomics is that the body all protein is identified in identification, analyze its function and pattern thereof, reflect the hereditary capacity of malignant tumour cell interior in the disease development process and the influence of prevailing circumstances simultaneously, and direct expression analysis at protein level.The main relying on dielectrophoresis technology of proteomics research (Two Dimensional Electrophoresis in the past, 2DE), the protein number that detects lacks than total protein in the cell of estimating, and general 2DE can differentiate 1000～3000 protein spots, and low copy albumen, extreme acidity or basic protein in the pair cell, molecular weight is excessive or cross electrophoretic separation and the detection that small protein, indissoluble albumen (comprising memebrane protein) wait still faces very big difficulty.And the appearance of protein chip and analytical technology thereof has overcome the built in problem that 2DE exists, can be directly detection of biological mark--proteomic image in pretreatment sample or the micro-sample never, for quick, easy, easily row and high throughput analysis relatively provide possibility.
The surface laser enhanced is resolved ionization-time of flight mass spectrometry (Surface-Enhanced LaserDesorption/Inionation-Time Of Flight-Mass Spectra, SELDI-TOF-MS) a kind of new protein science research method for growing up in recent years, design chips be can be protein-bonded solid point surface, be coated with stain hydrophobicity carbohydrates (Hydrophobic Surface at solid surface, H4), water-wetted surface (Normal Phase, NP), specificity mating surface (Preactivated Surface, PS), reinforcing yin essence ion-exchange surface (Strong Anion Exchange, SAX), weak cation exchange surface (WeakCation Exchange, WCX), the affine surface of fixing metal (Immobilized Metal AffinityCapture, IMAC) etc., can be non-special or specificity in conjunction with the protein in the sample, in conjunction with energy absorption molecule (Energy absorb matrix, EAM) after, in vacuum tube by laser bombardment, protein breaks away from chip surface, owing to wherein be added with a positive charge, in electric field, fly to negative electrode, the flight time that molecular weight is big is long, the flight time that molecular weight is little is short, and according to the quality and the charge ratio (M/Z) of protein, the peak value of each protein obviously separates and forms the collection of illustrative plates or the peak value of protein (being retained in the protein on the chip).The advantage of SELDI protein biochip technology is: 1. can analyze the protein that 2DE can't analyze, comprise hydrophobic protein, the protein that isoelectric point (pI) value is too high or too low, and low-molecular-weight (＜25kD) protein; 2. can analyze many concealed low concentration protein in the undressed sample, increase the chance of finding disease marker; 3. sample need not to use liquid chromatography or gas chromatography purifying in advance, so be applicable to the biological sample of analyzing the component complexity; 4. required sample size is few, detects weak point consuming time, and experimental repeatability is good.These advantages make the SELDI protein biochip technology be particularly suitable for screening tumor markers.
Summary of the invention
An object of the present invention is to provide a kind of from serum early stage Noninvasive detect the method for cancer of the stomach, this method provides new approach for early detecting gastric cancer, and for finding that further new tumor marker provides the foundation.Specifically realize by following steps:
1, serum sample is prepared:
(1) take out reinforcing yin essence ion-exchange surface (SAX) the chip biochip processor of packing into, every hole adds SAX binding buffer liquid preprocessed chip;
(2) blood serum sample thaws in ice bath, gets fully mixing of serum and sex change damping fluid U9 (9M Urea, 2%CHARPS, 50mM Tris-HCl PH9), gets wherein sample and the quick mixing of SAX binding buffer liquid again, and the blood serum sample of handling well is added on the chip;
(3) get rid of that every hole adds SAX binding buffer liquid behind the serum deprivation sample, the concussion back adds the washed with de-ionized water chip;
(4) take out chip, treat that every hole, little dried back adds 0.5ul energy absorption matrix SPA, treat upward machine testing of little dried back, collect mass signal with Ciphergen ProteinChip Software 3.2 softwares.
2, the collection of mass spectrometric data:
(1) setting laser intensity is 170, and sensitivity is 6, and the scope of collecting data is 1000～200000Da molecular weight protein matter, and assembling position is collected 20 times for average every from 20～80, and it is 140 times that collection is always counted;
(2) collect the preceding standard protein chip calibration molecule amount of using of experimental data, make repeatability with quality controlled serum and detect;
(3) all raw data are made the homogenization of total ionic strength adjustment buffer degree and molecular weight earlier of Ciphergen ProteinChip Software 3.2;
(4) mass-to-charge ratio is positioned at the peak value of 2000～20000Da, does noise filtering with software Biomarker Wizard, it is 5 that initial noise filtering value is set, and secondary noise filtering value is 2, is that minimum threshold carries out cluster with 10%;
(5) obtain results of preliminary screening, the burst data average that cancer of the stomach group and non-cancer of the stomach control group are done in the mass-to-charge ratio peak that preliminary screening is come out is u-test relatively.
3, adopt bioinformatics to analyze to the mass spectrometric data that obtains:
(1) use minimum preceding 10 peaks of u-test p value as candidate markers, these 10 marks have 574 kinds of combinations, 574 SVM models that assessment is set up with these 574 kinds combinations;
(2) adopt the leaving-one method crosscheck, take out a sample at every turn, set up the SVM diagnostic model with remaining sample as training set, use the SVM model that obtains to test a sample of taking-up, all sample standard deviations will be tested, and the accuracy rate of model is assessed by test result;
(3) select the highest combination of youden index (youden index=susceptibility+specificity-1) of test, as the final mark of setting up model.
(4) serum protein fingerprint of being set up (comprises phosphorylation by the protein that seven mass-to-charge ratioes (M/Z) are positioned at 4141Da, 4474Da, 3940Da, 4633Da, 4792Da, 3957Da, 4976Da, 5348Da, 4096Da and 5915Da; methylate, before the acetyl group modification or modify the back) form.
Description of drawings
Fig. 1 is 7 the mass spectral protein peak mass-to-charge ratio of constitutive protein distribution plans;
Fig. 2 is the mass spectrogram (left side) and the corresponding simulation electrophoretogram (right side) of 7 mass-to-charge ratioes (M/Z) serum proteins of being positioned at 3940Da (A), 3957Da (A), 4096Da (A), 4633Da (B), 4792Da (B), 4976Da (C) and 5348Da (C).(1,2,3 is patients with gastric cancer; 4,5,6 is healthy people);
Fig. 3 is ROC area under a curve result (A) and total ROC area under curve (B) at 7 M/Z peaks.
Embodiment
The present invention will be described further in conjunction with specific embodiments, and these examples only are used for illustration purpose, and are not used in the restriction scope of the invention.
Embodiment one:
1, serum sample is prepared:
(1) after all blood serum samples thawed in ice bath 30-60 minute centrifugal 5 minutes, get fully mixing of 10ul serum and 20ul sex change damping fluid U9 (9M Urea, 2%CHARPS, 50mM Tris-HCl PH9), vibration is 30 minutes in ice bath;
(2) carefully take out the SAX chip and carry out mark, the biochip processor of packing into, every hole adds 2 preprocessed chips of 200ulSAX binding buffer liquid concussion;
(3) get wherein in the 10ul sample and 110ul SAX binding buffer liquid (50mM Tris-HCl pH9) solution mixing fast, avoid bubble to produce, every hole adds the blood serum sample 100ul that handles well, 4 ℃ of concussions 60 minutes;
(4) every hole adds 200ul SAX binding buffer liquid behind the blood serum sample, and concussion is 2 times under the room temperature, adds 200ul washed with de-ionized water chip again 2 times;
(5) take out chip, treat that every hole, little dried back adds 0.5ul SPA, treats little dried back repetition 1 time;
(6) last 5 machine testings are collected mass signal with Ciphergen ProteinChip Software 3.2 (U.S. Ciphergen) software.
2, the collection of mass spectrometric data:
(1) laser intensity of setting SELDI-TOF-MS is 170, and sensitivity is 6, and the scope of collecting data is 1000～200000Da molecular weight protein matter, and assembling position is collected 20 times for average every from 20～80, and it is 140 times that collection is always counted;
(2) before collecting each experimental data, use all in one standard protein chips (U.S. Ciphergen) calibration molecule amount, make repeatability with quality controlled serum and detect;
(3) all raw data are made the homogenization of total ionic strength adjustment buffer degree and molecular weight earlier of Proteinchip Software 3.2;
(4) mass-to-charge ratio is positioned at the peak value of 2000～20000Da, does noise filtering with software Biomarker Wizard, it is 5 that initial noise filtering value is set, and secondary noise filtering value is 2, is that minimum threshold carries out cluster with 10%;
(5) obtain results of preliminary screening, the burst data average that cancer of the stomach group and non-cancer of the stomach control group are done in the mass-to-charge ratio peak that preliminary screening is come out is u-test relatively.
3, adopt bioinformatics to analyze to the mass spectrometric data that obtains:
(1) use minimum preceding 10 peaks of u-test p value as candidate markers, these 10 marks have 574 kinds of combinations, 574 SVM models that assessment is set up with these 574 kinds combinations;
(2) adopt leaving-one method crosscheck method, sample of each taking-up is set up the SVM diagnostic model with remaining sample as training set, tests a sample of taking-up with the SVM model that obtains, all sample standard deviations will be tested, and the accuracy rate of model is assessed by test result;
(3) select the highest combination of youden index (youden index=susceptibility+specificity-1) of test, as the final mark of setting up model.
(4) serum protein fingerprint of being set up (comprises phosphorylation by the protein that seven mass-to-charge ratioes (M/Z) are positioned at 4141Da, 4474Da, 3940Da, 4633Da, 4792Da, 3957Da, 4976Da, 5348Da, 4096Da and 5915Da; methylate, before the acetyl group modification or modify the back) form (seeing Fig. 1,2).
4, the checking of serum proteins mass spectra model:
The available recipient's operating characteristic of the relation of susceptibility and specificity (ROC curve) method figurative expression.With True Positive Rate (TPF) is the longitudinal axis, and false positive rate (FPF) is the transverse axis mapping, and the gained curve is the ROC curve.ROC is used for estimating the relative importance of each peak in diagnosis.ROC area under a curve (Az) value is big more, show that diagnosis effect is reliable more, so parameter Az can be used for characterizing the aggregate performance of distinguishing ability.It is generally acknowledged that Az is at 0.5～0.7 o'clock, the expression diagnostic accuracy is lower; Be 0.7～0.9 o'clock, the expression accuracy is medium; Be 0.9 to represent that diagnostic accuracy is higher when above.The result shows that the M/Z value surpasses 0.70 for the Az value of 3940Da, 4141Da, 4474Da and 4633Da, and total ROC area under curve is 0.86, shows that the serum protein fingerprint model of 7 M/Z peak combinations has diagnostic value (see figure 3) preferably.
Embodiment two
1, serum sample data:
86 routine serum specimens all pick up from 2nd Affiliated Hospital Zhejiang University School of Medicine year November in February, 2003～2003, under Ethics Committee of hospital and patient's informed consent, obtaining, the patients with gastric cancer that confirms from pathology of 45 examples wherein, 41 examples are the non-cancer of the stomach healthy volunteer that gastrocopy and pathology turn out to be chronic superficial gastritis or atrophic gastritis, no malignant tumour medical history.The male sex's 31 examples among the patient, women's 14 examples, 56.5 years old mean age (36 years old～76 years old), tumour UICC by stages: I phases 14 example, II phases 6 example, III phases 10 example, IV phases 15 example.Control group is with the pairing of age and sex, the male sex's 28 examples wherein, women's 13 examples, 52.6 years old mean age (38 years old～73 years old).All serum specimens all extract before the treatment in the morning on an empty stomach, and serum is stored in-80 ℃ of low temperature refrigerators.
2, instrument and analytical approach
PBS-II type SELDI-TOF-MS and test required SAX protein-chip and develop by U.S. Ciphergen company.Analysis software adopts Matlab6.5.The ROC analysis software adopts SPSS 11.0 (the SPSS Inc. U.S.).
3, serum sample is prepared:
3000rpm was centrifugal 5 minutes after the 10ul blood serum sample thawed in ice bath, with 20ul sex change damping fluid U9 (9M Urea, 2%CHARPS, 50mM Tris-HCl PH9) abundant mixing, getting wherein, 10ul adds abundant mixing in 110ul SAX binding buffer liquid (the 50mM Tris-HCl PH9) solution.The SAX chip is packed into behind the biochip processor with SAX binding buffer liquid pre-service 5 minutes * 2 times, and the blood serum sample 100ul that handles well is added to the Bioprocessor (U.S. Ciphergen) in 96 holes, and concussion is 60 minutes on the vibration platform.Get rid of the serum deprivation sample, every hole adds under the SAX binding buffer liquid 200ul room temperature shakes (400-600rpm) 5 minutes * 2 times, uses the washed with de-ionized water chip again 1 minute * 2 times, and dry back adds 0.5ul SPA (50%ACE+0.5%TFA) * 2.Last machine testing is collected mass signal with Ciphergen ProteinChip Software 3.2 (U.S. Ciphergen) software.
4, the collection of mass spectrometric data:
The laser intensity of setting SELDI-TOF-MS is 170, and sensitivity is 6, and the scope of collecting data is 1000～200000Da molecular weight protein matter, and assembling position is collected 20 times for average every from 20～80, and it is 140 times that collection is always counted.The molecular weight that rectifies an instrument and measure with all in one standard protein chip (U.S. Ciphergen) before collecting each experimental data, its error is less than 0.1%.Make repeatability with the Quality Control protein chip and detect, the coefficient of variation (CVs) of its peak value size and intensity thereof all is controlled in the error range (below 0.05% and 15%), has good repeatability.All raw data are done correction with Proteinchip Software 3.2 earlier: (homogenization of total ionic strength adjustment buffer degree and molecular weight).Mass-to-charge ratio is positioned at the peak value of 2000-20000Da, and with Biomarker Wizard filtering noise, it is 5 that initial noise filtering value is set, and secondary noise filtering value is 2, is that minimum threshold carries out cluster with 10%.Obtain results of preliminary screening, the burst data average that cancer of the stomach and normal control are done in the mass-to-charge ratio peak that preliminary screening is come out is u-test relatively.
5, adopt bioinformatics to analyze to the mass spectrometric data that obtains:
SVM be a kind of with between sample certain apart from as the mode identification method of dividing foundation, it solved well the medium and small sample pattern of pattern-recognition generalization, Model Selection, cross fit, problem such as dimension disaster.
The present invention uses minimum preceding 10 peaks of u-test p value as candidate markers, and these 10 marks have 574 kinds of combinations, 574 SVM models that assessment is set up with these 574 kinds combinations.Adopt leaving-one method crosscheck method, take out a sample at every turn, set up the SVM diagnostic model with remaining sample as training set, use the SVM model that obtains to test a sample of taking-up, all sample standard deviations will be tested, and the accuracy rate of model is assessed by test result.Select the highest combination of youden index (youden index=susceptibility+specificity-1) of test, as the final mark of setting up model.
6, the checking of serum proteins mass spectra model:
The available recipient's operating characteristic of the relation of susceptibility and specificity (ROC curve) method figurative expression.With True Positive Rate (TPF) is the longitudinal axis, and false positive rate (FPF) is the transverse axis mapping, and the gained curve is the ROC curve.ROC is used for estimating the relative importance of each peak in diagnosis.ROC area under a curve (Az) is the parameter of the most frequently used evaluation ROC curve characteristic, and it can represent on the whole what of image amount of information, and its value is big more, illustrates that resulting image amount of information is many more.The ROC curve location of making in unit square is high more, and the Az value is big more, show that diagnosis effect is reliable more, so parameter Az can be used for characterizing the aggregate performance of distinguishing ability.It is generally acknowledged that Az is at 0.5～0.7 o'clock, the expression diagnostic accuracy is lower; Be 0.7～0.9 o'clock, the expression accuracy is medium; Be 0.9 to represent that diagnostic accuracy is higher when above.
7, result:
(1) serum proteins mass spectrogram
Utilize the preliminary cluster analysis common property of Biomarker Wizard to give birth to the serum proteins mass spectrum peak value collection of illustrative plates of 48 different M/Z, and non-cancer of the stomach and two groups of mass spectrometric datas of cancer of the stomach are carried out the average comparison u-test of data in groups.Discovery has 10 P values＜0.05 protein peak, and meaningful to differentiating cancer of the stomach and non-cancer of the stomach, its M/Z is respectively 4141Da, 4474Da, 3940Da, 4633Da, 4792Da, 3957Da, 4976Da, 5348Da, 4096Da and 5915Da (seeing Table 1).
Table 1 cancer of the stomach and non-cancer of the stomach haemocyanin mass spectrum be the data u-test in groups
| ??M/Z | ??P | ??Mean-N | ??SD-N | ??Mean-T | ??SD-T |
| ??4141 | ??4.24E-05 | ??1.468593 | ??0.939244 | ??3.005907 | ??2.221048 |
| ??4474 | ??6.6E-05 | ??2.180118 | ??0.932624 | ??3.616931 | ??2.572711 |
| ??3940 | ??9.14E-05 | ??2.062003 | ??0.977344 | ??3.514105 | ??2.115201 |
| ??4633 | ??0.00015 | ??2.007012 | ??0.793028 | ??2.972182 | ??1.413002 |
| ??4792 | ??0.000758 | ??2.008361 | ??1.057694 | ??3.395566 | ??2.820583 |
| ??3957 | ??0.002512 | ??2.948333 | ??1.023729 | ??2.306918 | ??0.976154 |
| ??4976 | ??0.003239 | ??3.925347 | ??2.605212 | ??5.971184 | ??3.906912 |
| ??5348 | ??0.010619 | ??5.103952 | ??2.371478 | ??7.198868 | ??3.967897 |
| ??4096 | ??0.012013 | ??10.50988 | ??4.364763 | ??13.8145 | ??5819009 |
| ??5915 | ??0.012925 | ??15.0621 | ??6.727995 | ??19.55231 | ??8.84957 |
(2) foundation of serum proteins mass spectra model:
In 574 SVM models with the foundation of above-mentioned 10 significant M/Z peaks, find 7 models that the M/Z peak value is the composition of 3940Da, 4633Da, 4792Da, 3957Da, 4976Da, 5348Da and 4096Da, prediction effect is best, its diagnostic sensitivity is 84.4%, specificity is 87.8%, and positive predictive value is 88.4%.The mass-spectrogram at 7 M/Z peaks and electrophoresis pattern are seen Fig. 1,2.Fig. 2 is the mass spectrogram (left side) and the corresponding simulation electrophoretogram (right side) of 7 mass-to-charge ratioes (M/Z) serum proteins of being positioned at 3940Da (A), 3957Da (A), 4096Da (A), 4633Da (B), 4792Da (B), 4976.06Da (C) and 5348Da (C), wherein 1,2,3 is patients with gastric cancer; 4,5,6 is healthy people.
It should be noted that the M/Z peak value be 3957Da be unique one normal high expressed promptly with the albumen of cancer of the stomach negative correlation, albumen is obviously relevant with cancer of the stomach and be 3940Da with its M/Z peak value that differs 17Da.
(3) the ROC result at M/Z peak:
The ROC area under a curve (Az) at 7 M/Z peaks the results are shown in Figure 3, Fig. 3 is ROC area under a curve (Az) result (A) and total ROC area under curve (B) at 7 M/Z peaks, wherein the Az value of 3940Da, 4141Da, 4474Da and 4633Da surpasses 0.70, and total ROC area under curve is 0.86, shows that the serum protein fingerprint model of 7 M/Z peak combinations has diagnostic value preferably.And molecular weight differs the ROC area under curve of ratio at M/Z peak of two 3940Da, the 3957Da of 17Da is 0.78.
Need not further to elaborate, believe and adopt the disclosed content in front, those skilled in the art can use the present invention to greatest extent.Therefore, the embodiment of front is interpreted as only illustrating, but not limits the scope of the invention by any way.
Claims (3)
1. the method for an early detecting gastric cancer from serum is to detect by serum protein fingerprint, it is characterized in that: this method realizes by following steps:
1. serum is prepared;
2. the collection of mass spectrometric data;
3. adopt bioinformatics to analyze to the mass spectrometric data that obtains;
1. described step adopts the sex change damping fluid is scaling agent, is reinforcing yin essence ion-exchange surface binding buffer liquid with 50mM Tris-HCl, and adopts reinforcing yin essence ion-exchange surface chip;
2. described step is to utilize surface-enhancing laser desorption-ionization-time of flight mass spectrometry instrument to carry out mass spectrometric data to collect, and laser intensity is 170, and detection sensitivity is 6;
3. described step is the mass spectra model of forming according to the human serum protein that is positioned at 4141Da, 4474Da, 3940Da, 4633Da, 4792Da, 3957Da, 4976Da, 5348Da, 4096Da and 5915Da by seven mass-to-charge ratioes, and utilizes bioinformatic analysis to obtain testing result.
2. as claimed in claim 1 a kind of from serum the method for early detecting gastric cancer, it is characterized in that: described bioinformatic analysis is to adopt support vector machine to set up model, and carries out cross validation with leaving-one method.
3. as claimed in claim 1 a kind of from serum the method for early detecting gastric cancer, it is characterized in that: the sex change damping fluid that 1. step adopts is by 9M Urea, 2% CHARPS, 50mMTris-HCl, PH9 preparation.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101329348A (en) * | 2007-06-18 | 2008-12-24 | 许洋 | Optimizing mass spectrogram model for detecting stomach cancer characteristic protein and preparation method and application thereof |
| CN101021468B (en) * | 2006-04-26 | 2010-08-11 | 安萍 | Method for detecting intracellular arginase |
| CN101451975B (en) * | 2008-12-29 | 2012-01-25 | 浙江大学 | Method for detecting cancer of stomach prognosis and staging blood serum protein |
| CN102344956A (en) * | 2010-08-04 | 2012-02-08 | 上海交通大学医学院附属第九人民医院 | Gene chip based method for detecting tumour tissue and screening tumour serum marker |
| CN102495146A (en) * | 2011-11-16 | 2012-06-13 | 上海交通大学 | Compound fingerprint atlas model used in early-stage gastric cancer diagnosis/early warning, and establishing method thereof |
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2005
- 2005-05-25 CN CN 200510049824 patent/CN1707258A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101021468B (en) * | 2006-04-26 | 2010-08-11 | 安萍 | Method for detecting intracellular arginase |
| CN101329348A (en) * | 2007-06-18 | 2008-12-24 | 许洋 | Optimizing mass spectrogram model for detecting stomach cancer characteristic protein and preparation method and application thereof |
| CN101451975B (en) * | 2008-12-29 | 2012-01-25 | 浙江大学 | Method for detecting cancer of stomach prognosis and staging blood serum protein |
| CN102344956A (en) * | 2010-08-04 | 2012-02-08 | 上海交通大学医学院附属第九人民医院 | Gene chip based method for detecting tumour tissue and screening tumour serum marker |
| CN102495146A (en) * | 2011-11-16 | 2012-06-13 | 上海交通大学 | Compound fingerprint atlas model used in early-stage gastric cancer diagnosis/early warning, and establishing method thereof |
| WO2013071677A1 (en) * | 2011-11-16 | 2013-05-23 | 上海交通大学 | Compound fingerprint atlas-spectrum model used for early gastric cancer diagnosis/early-warning, and model establishing |
| CN102495146B (en) * | 2011-11-16 | 2014-07-02 | 上海交通大学 | Compound fingerprint atlas model used in early-stage gastric cancer diagnosis/early warning, and establishing method thereof |
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