CN105044240B - A kind of diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis - Google Patents

A kind of diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis Download PDF

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CN105044240B
CN105044240B CN201510498042.7A CN201510498042A CN105044240B CN 105044240 B CN105044240 B CN 105044240B CN 201510498042 A CN201510498042 A CN 201510498042A CN 105044240 B CN105044240 B CN 105044240B
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acid
cancer
esophagus
metabolic
blood serum
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CN105044240A (en
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王家林
张涛
朱正江
薛付忠
赵德利
盛修贵
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Shandong Institute of Cancer Prevention and Treatment
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Abstract

It is two or more the combination in following 5 kinds of blood serum metabolic labels the invention discloses a kind of diagnostic marker for being suitable for cancer of the esophagus early diagnosis：L tyrosine (L Tyrosine), L tryptophans (L Tryptophan), glycocholic acid (Glycocholic Acid), taurocholate (Taurocholate) and cortisol (Cortisol).Diagnostic model can be built using diagnostic marker of the present invention, the modelling effect is good, and sensitivity is high, specificity is good, be adapted to the diagnosis of the early and late cancer of the esophagus, with good Clinical practice and promotional value.

Description

A kind of diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis
Technical field
The present invention relates to the diagnosis of esophageal squamous cell carcinoma, and in particular to a kind of esophageal squamous cell carcinoma diagnostic marker, The screening technique of diagnostic marker, based on the diagnostic marker build diagnostic model, and diagnostic model structure side Method, the diagnostic marker and diagnostic model all have good diagnosis effect for oesophagus carcinoma in situ, the early and late cancer of the esophagus, It is particularly suitable for cancer of the esophagus early diagnosis, belongs to esophageal squamous cell carcinoma diagnostic techniques field.
Background technology
The cancer of the esophagus (esophageal cancer) is the evil formed by the paraplasm of esophagus squameous epithelium or galandular epithelium Venereal disease becomes.Show according to World Health Organization's latest data：The whole world there are about 400,000 people and dies from the cancer of the esophagus every year, and China is the cancer of the esophagus Morbidity and mortality highest country, and the organization type of 90% patient is squamous cell carcinoma (ESCC).Incidence of Esophageal Cancer is hidden Hide, early stage, asymptomatic or symptom was not true to type very much, had been clinical end-stage during discovery, and universal prognosis is not good, and (survival rate is about within 5 years 13%).Therefore, early diagnosis and early treatment are to improve cancer of the esophagus prognosis, reduce the key of the death rate.At present, in the cancer of the esophagus The early diagnosis of district occurred frequently early controls platform and clinically conventional early screening and diagnostic method includes cytologic examination by esophageal abrasive balloon, X Line canel barium meal contrast examination, esophagus ultrasound scope, endoscopy of esophagus etc..But these methods are invasive inspection, complex operation and price It is high, limit its extensive use in cancer of the esophagus examination and early diagnosis.
Oesophagus carcinogenesis is related to multifactor, multistage, polygenic variation accumulation and the complexity interacted with environmental factor Process, including it is related to the change of numerous proto-oncogenes, tumor suppressor gene and protein on a molecular scale, and it is long-term bad (feed contains the more food of nitrosamines, such as likes pickling sauerkraut or the food that goes mouldy, long-term happiness for life or the influence of eating habit Enter to scald food, smoking, bad habit of drinking etc.).Metabolism group is to all points in biological sample (such as serum, urine, saliva) It is qualitative fixed that son amount is carried out less than 1000Da small molecule metabolites (such as aliphatic acid, amino acid, nucleosides and steroidal biological micromolecule) Amount detection, so as to monitor the metabolism response that body is made by endogenous material after the interference such as disease or hazards accumulation.In vivo Biological information by gene through transcription pass to protein, be finally presented as small molecule metabolites.Different from genomics and egg The organism inherent difference of Bai Zuxue reflections, the research field of metabolism group extend to influencing each other between body and environment And effect.Small molecule metabolites are not only the material base of body vital movement, biochemical metabolism, and some foeign elements are also presented Change to internal metabolism environment, thus the concentration of some unique metabolic things in fact reflects disease in interindividual difference Sick inherent performance and the external cause of disease.Recent study discovery, the disease such as metabolic disease and malignant tumour (oophoroma) In generation evolution, the metabolism of body basic biochemistry there occurs significant change, to the metabolic mechanism of human intelligible complex disease To play a significant role, while for the screening and early diagnosis of complex disease provide brand-new technical method.
It is related functional gene caused by polygenes and environmental factor interact that the generation development of the cancer of the esophagus is first Expression change or be mutated, followed by a series of cellular signal transductions and protein synthesis change, finally with environmental factor Interact lower so that metabolite changes.The generation of the cancer of the esophagus exactly environmental risk factors gradually accumulate not breakdown wound The result of each metabolic pathway stable state of body.At present, someone is studied the cancer of the esophagus using metabolism group, such as Wu etc. (Wu H,Xue R,Lu C,et al.Metabolomic study for diagnostic model of oesophageal cancer using gas chromatography/mass spectrometry.J Chromatogr B Analyt Technol Biomed Life Sci,2009,877(27):3111-7.), Zhang etc. (Zhang J, Bowers J, Liu L, et al.Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods.PLoS One,2012,7(1):E30181.), (Xu J, Chen Y, Zhang R, the et al.Global and such as Xu targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers.Mol Cell Proteomics,2013,12 (5):1306-18.) cancer of the esophagus is studied using metabonomic technology all.
The generation development of the cancer of the esophagus generally requires several years or even more than ten years, such as along with the change of internal various metabolins Can be found in the carcinogenesis stage, carry out early treatment, outcome can be effectively improved.And in fact, there are some researches prove Before disease incidence or hazards accumulation phase, endogenous material will make corresponding metabolism response.For example, Zhao etc. passes through Metabolic fingerprinting research discloses the metabolic characteristics of pre-diabetic, and confirms aliphatic acid, tryptophan, uric acid, courage The metabolism of juice acid etc. changes and betides disease and occur before clinical symptoms in a very long time, is examination, the morning of metabolic disease Phase diagnoses and intervenes and provides new possibility.However, the mainly advanced esophageal carcinoma that above-mentioned cancer of the esophagus metabolism group research is included Patient, and do not include mostly or little include early stage cancer of the esophagus case.There is lymph node and turned at a distance in late esophagus cancer Move, or even tumor cachexia state occur, now organism metabolism has changed a lot, therefore, these researchs are only capable of finding Metabolic profile difference of the Incidence of Esophageal Cancer late period compared with normal healthy controls, the difference according to these metabolic profiles is only capable of preferably examining Break and late esophagus cancer, and cannot be diagnosed for the early stage cancer of the esophagus, i.e., can not realize the early diagnosis of the cancer of the esophagus.Its Secondary, the research of above-mentioned cancer of the esophagus metabolism group only obtains the seldom part metabolin related to Incidence of Esophageal Cancer (from research level On only be metabolism target analysis, rather than metabolic profile or metabonomic analysis).Additionally, the studies above is not mostly from the cancer of the esophagus Objective Molecular screening/early diagnosis master pattern angle evaluate metabolism group translational medicine potentiality and application effect, greatly The sensitivity of the examination/diagnosis of esophageal cancer of part and the unreported metabolin for screening, specificity and area AUC under ROC curve Value.
Inventor's early stage has been carried out a series of researchs for the cancer of the esophagus, can using the technical research of metabolism group The metabonomic analysis model of cancer of the esophagus early screening is carried out, the technology finds for the people at highest risk of China Esophageal Cancer in High Risk Areas The application having and promotional value, at present in the pilot application of Shandong Feicheng.However, Esophageal Cancer group's examination and clinic Early diagnosis still has many differences.Esophageal Cancer in High Risk Areas examination is that the artificially observation with health or surface health of district occurred frequently is right As, it is therefore an objective to those surfaces health, but suspicious people's (high-risk individuals) with esophageal site lesion are found in the crowd of health, Screening tests positive must make further diagnosis or intervene；And it is in a clinical setting to see with patient or suspicious patient that diagnosis is Examine object, it is therefore an objective to distinguish whether patient has corresponding illness, timely, correct judgement is made to conditions of patients, to take phase Effective remedy measures are answered, clinically diagnosis positive will give and treat (such as operation, chemotherapy or radiotherapy).At present, hospital is universal Using having wound, complex operation and a high imageological examination clinical diagnosis cancer of the esophagus case of price, and patient is actively medical It has been mostly late period to be, therefore it is simple and effective for clinical esophagus cancer diagnosis (particularly early stage esophagus cancer diagnosis) still to lack energy Serum biomarker thing.Therefore, special, sensitive, economic and noninvasive cancer of the esophagus early diagnosis blood serum metabolic label is found, And set up a kind of safely and effectively cancer of the esophagus early molecule diagnostic model there is important clinical value.
The content of the invention
For esophageal squamous cell carcinoma in the prior art (the abbreviation cancer of the esophagus) diagnostic operation is complicated, expensive, invasive Wound property, current label is only high to late esophagus cancer sensitivity, it is impossible to realize the deficiencies such as the early diagnosis of the cancer of the esophagus, the present invention There is provided a kind of diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis, the diagnostic marker is in situ for oesophagus Cancer, the early stage cancer of the esophagus, late esophagus cancer all have preferable sensitivity and specificity, are used not only for examining for late esophagus cancer It is disconnected, additionally it is possible to be preferably used for the early diagnosis of esophageal squamous cell carcinoma, for improving esophageal squamous cell carcinoma prognosis, reducing dead The rate of dying has very important significance.
Present invention also offers the screening technique of the above-mentioned diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis, Label as obtained by the method all has good sensitivity and specificity for the early and late cancer of the esophagus, especially fits The early diagnosis of the cancer of the esophagus is closed, has important clinical meaning for the treatment of the cancer of the esophagus.
Present invention also offers a kind of esophageal squamous cell carcinoma diagnostic model and the construction method of diagnostic model, the model structure Construction method is simple, can replace the diagnostic method of invasive now, convenient and swift, it is to avoid the pain of personnel to be tested, for oesophagus Carcinoma in situ, the early stage cancer of the esophagus, late esophagus cancer all have preferable sensitivity and specificity, are the early diagnosis of esophageal squamous cell carcinoma Early control there is provided effective technical support.
Present invention also offers a kind of method that esophageal squamous cell carcinoma is diagnosed using the diagnostic model, using mould of the present invention Type only can just be diagnosed by taking blood, convenient and swift, high especially for early stage cancer of the esophagus sensitivity without interior wound, specificity It is good, with good clinical value.
At present, screening esophageal squamous cell carcinoma diagnostic flag is studied in this area mostly in terms of gene and macro-molecular protein Thing, the present invention changes conventional Research Thinking, proposes to be examined using blood serum metabolic omics technology screening esophageal squamous cell carcinoma first The thinking of disconnected label, it was found that be particularly suitable for the label of esophageal squamous cell carcinoma early diagnosis, makes to be not easy to what is found Early stage esophageal squamous cell carcinoma has good diagnostic method." national cancer of the esophagus early diagnosis early controls Demonstration Base (mountain to present invention support Dong Sheng Feichengs) " cancer of the esophagus screening and follow-up crowd's queue, obtain oesophagus carcinoma in situ (abbreviation carcinoma in situ, 0 phase 39), early The phase cancer of the esophagus (abbreviation early carcinoma, I phases 17, II phases 11) and late esophagus cancer (abbreviation late cancer, III phases 30) patient's Serum specimen, and randomly select through determine without any esophageal lesion and other metabolic diseases (such as hyperthyroidism, first subtract, hypertension and sugar Urine disease, ephrosis etc.) healthy population be normal healthy controls, use UPLC-QTOF/MS 1466 metabolism of small molecule metabolites of acquisition Finger-print, by the contrast to patient with esophageal carcinoma and the Metabolic fingerprinting of the small molecule metabolites of health objects, analysis, Obtain being suitable for the diagnostic marker of esophageal squamous cell carcinoma early diagnosis, model construction is carried out with these diagnostic markers, obtain Whether to esophagus cancer diagnosis model, it is the cancer of the esophagus that can be quickly diagnosed to be using the model, especially may diagnose that early stage The cancer of the esophagus, sensitivity is high, specificity is good, with Clinical practice and promotional value.
In the present invention, the oesophagus carcinoma in situ referred to 0 phase in TNM stage standard, was referred in mucous epithelium layer or epiderm skin The holostrome of epithelium is involved in interior atypical hyperplasia (severe), but not yet invades brokenly basilar memebrane and infiltrate the cancer of growth downwards；Early stage eats Pipe cancer refers to I the and II phases in TNM stage standard, is referred to without lymph node involvement, being confined to after mucous membrane or under mucous membrane without DISTANT METASTASES IN The cancer of layer；Late esophagus cancer refers to III phases and IV phases in TNM stage standard, refers to and has involved muscle layer or up to beyond adventitia or adventitia, There is the cancer of part or distant place lymphatic metastasis.TNM stage standard is according to American joint Committee on Cancer (AJCC)TNM Classfication of Carcinoma of the Esophagus and Esophagogastric Junction(7th ed,2010)。
Diagnostic marker of the invention and diagnostic model can be by the unconspicuous early stage esophagus cancer diagnosis of asymptomatic or symptom Out, without interior invasive, the pain of tester is alleviated, and diagnosis process is succinct, quick, operating efficiency is improve, for oesophagus The early diagnosis of cancer is early controlled, the improvement of prognosis, the reduction of the death rate are all of great significance.Realize particular technique side of the invention Case is as follows：
A kind of diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis, is following 25 kinds of blood serum metabolic labels In any one or more than one combination：Beta- alanine-lysines (beta-Ala-Lys), L-Carnosine (L- ), Carnosine POA (cis-9-Palmitoleic acid), palmitic acid (Palmitic acid), oleic acid (Oleic Acid), lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), haemolysis lecithin Fat LysoPC (18:2 (9Z, 12Z)), lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphorus Fat PC (16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1(15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), linoleic acid (Linoleic acid), NADH (NADH), cortisol (Cortisol), TYR (L- ), Tyrosine L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid), taurocholate (Taurocholate), hypoxanthine (Hypoxanthine), allantoic acid (Allanto ic acid), inosine (Inosine), S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O- Sulfogalactosylceramide(d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/22:0).
Can be any one, or it in above-mentioned 25 kinds of blood serum metabolic labels in above-mentioned diagnostic marker Between two kinds or two or more be optionally combined.When the combination using two or more blood serum metabolic label During as diagnostic marker, the effect of diagnosis can be better than effect of the single blood serum metabolic label as diagnostic marker.
Further, above-mentioned diagnostic marker can be any one the blood serum metabolic label in following (a)-(h) Combination：A () can be the combination of beta- alanine-lysines (beta-Ala-Lys) and L-Carnosine (L-Carnosine)； (b) or it is POA (cis-9-Palmitoleic acid), palmitic acid (Palmitic acid) and oleic acid The combination of (Oleic Acid)；(c) or it is lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14: 0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)) and lysolecithin LysoPC (24:0) combination；(d) or it is Phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1(15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)) and linoleic acid (Linoleic acid) combination；(e) or it is nicotinamide adenine two The combination of nucleotides (NADH), TYR (L-Tyrosine) and L-Trp (L-Tryptophan)；(f) or it is cortex The combination of alcohol (Cortisol), glycocholic acid (Gl ycocholic Acid) and taurocholate (Taurocholate)；(g) Or be the combination of hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid) and inosine (Inosine)；(h) Or be S1P (Sphingosine 1-ph osphate), sulfogalactosylceramide 3-O- Sulfogalactosylceramide(d18:1/20:0) with galactosylceramide Lactosylceramide (d18:1/22:0) Combination.
Further, above-mentioned diagnostic marker can be following 15 kinds of blood serum metabolic labels in two or more Combination：Lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC(18:2 (9Z, 12Z)), lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC(16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1(15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), nicotinoyl amine gland Purine dinucleotides (NAD H), cortisol (Cortisol), L-Trp (L-Tryptophan), taurocholate (Taurocholate), hypoxanthine (Hypox anthine), inosine (Inosine), sulfogalactosylceramide 3- O-Sulfogalactosylceramide(d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/22: 0)。
Further, above-mentioned diagnostic marker can be following 7 kinds of blood serum metabolic labels in two or more Combination：Lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC(18:2 (9Z, 12Z)), lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC(16:0/18:2 (9Z, 12Z)) and phosphatide PC (24:1(15Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z)).
Further, above-mentioned diagnostic marker can be following 5 kinds of blood serum metabolic labels in two or more Combination：TYR (L-Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid), taurocholate (T aurocholate) and cortisol (Cortisol).
Preferably, above-mentioned diagnostic marker be following 25 kinds of blood serum metabolic labels combination (be designated as diagnostic marker A, Similarly hereinafter)：Beta- alanine-lysines (beta-Ala-Lys), L-Carnosine (L-Carnosine), POA (cis-9-Palmitoleic acid), palmitic acid (Palmitic acid), oleic acid (Oleic Acid), lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)), haemolysis Lecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)), phosphorus Fat PC (24:1(15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), linoleic acid (Linoleic acid), nicotinoyl amine gland is fast Nicotinamide adenine dinucleotide (NADH), cortisol (Cortisol), TYR (L-Tyrosine), L-Trp (L- ), Tryptophan glycocholic acid (Glycocholic Acid), taurocholate (Taurocholate), hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid), inosine (Inosine), S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O-Sulfogalactosylcer amide (d18:1/20:0), Galactosylceramide Lactosylceramide (d18:1/22:0).
Preferably, above-mentioned diagnostic marker be following 7 kinds of blood serum metabolic labels combination (be designated as diagnostic marker B, under Together)：Lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)), lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16: 0/18:2 (9Z, 12Z)) and phosphatide PC (24:1(15Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z)).
Preferably, above-mentioned diagnostic marker be following 5 kinds of blood serum metabolic labels combination (be designated as diagnostic marker C, under Together)：TYR (L-Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid), ox Sulphur cholate (T aurocholate) and cortisol (Cortisol).
The invention provides the diagnostic marker that various serum protein moteblites or serum protein moteblites combination are constituted, above-mentioned diagnosis mark Note thing is related to 25 kinds of blood serum metabolic labels altogether, and this 25 kinds of blood serum metabolic labels are closely related with 10 kinds of metabolic pathways.Wherein, B eta- alanine-lysines (beta-Ala-Lys) and this 2 kinds of blood serum metabolic labels of L-Carnosine (L-Carnosine) with Beta alanine metabolism (beta-Alanine metabolism) metabolic pathway is closely related；POA (cis- 9-Palmitoleic ac id), palmitic acid (Palmitic acid) and oleic acid (Oleic Acid) this 3 kinds of blood serum metabolics marks Thing is closely related with aliphatic acid synthesis (Fatty a cid biosynthesis) metabolic pathway；Lysophosphatidic acid LPA (18:1 (9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)) and haemolysis lecithin Fat LysoPC (24:0) this 4 kinds of blood serum metabolic labels are metabolized (Glycerophospholipid with glycerophosphatide Metabolism) metabolic pathway is closely related；Phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2(9Z, 12Z)), phosphatide PC (24:1(15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)) and linoleic acid (Linoleic acid) this 4 Blood serum metabolic label is planted with glycerophosphatide metabolism (Glycerophospholipid metabo lism) and linoleic acid metabolism (Linoleic acid metabolism) both metabolic pathways are closely related；NADH (NADH) with Oxidative phosphorylation (Oxidative phosphorylation) metabolic pathway is closely related；TYR (L-Tyrosine) and This 2 kinds of blood serum metabolic labels of L-Trp (L-Tryptophan) and phenylalanine/tyrosine and tryptophan metabolism (Phen Ylalanine, tyrosine and tryptophan biosynthesis) metabolic pathway is closely related；Glycocholic acid (Glycocholic Ac id) and this 2 kinds of blood serum metabolic labels of taurocholate (Taurocholate) and primary bile acid Synthesis (Primary bile acid b iosynthesis) metabolic pathway is closely related；Cortisol (Cortisol) and cancer Path and choleresis (Pathways in cancer, and Bile secretion) metabolic pathway are closely related；Secondary Huang is fast Purine (Hypoxanthine), allantoic acid (Allantoic acid) and this 3 kinds of blood serum metabolic labels of inosine (Inosine) with it is fast Purine metabolism (Purine metabolism) metabolic pathway is closely related；S1P (Sphingosine 1- Phosphate), sulfogalactosylceramide 3-O-Sulfogalactosylcerami de (d18:1/20:0) it is and newborn Glycosyl ceramide Lactosylceramide (d18:1/22:0) this 3 kinds of blood serum metabolic labels are metabolized with sphingolipid (Sphingolipid metabolism) metabolic pathway is closely related.
Present invention also offers the screening of the above-mentioned various diagnostic markers for being suitable for esophageal squamous cell carcinoma early diagnosis Method, comprises the following steps：
(1) patients with esophageal squamous cell and healthy population serum sample are collected, as analysis sample, wherein esophagus squameous Cell cancer serum sample includes oesophagus carcinoma in situ serum sample, early stage cancer of the esophagus serum sample and late esophagus cancer serum sample；
(2) each analysis sample is analyzed using UPLC-QTOF/MS blood serum metabolic omics technologies, obtains each serum The original Metabolic fingerprinting of sample；
(3) R language XCMS software kits are used by esophageal squamous cell carcinoma serum sample and the original generation of healthy serum sample Thank to finger-print carries out collection of illustrative plates pretreatment respectively, obtains every behavioural analysis sample, is often classified as the two-dimensional matrix of metabolin information, and Metabolin peak mark is carried out to two-dimensional matrix using the CAMERA software kits of R language, for further statistical analysis；
(4) two-dimensional matrix of step (3) is carried out into principal component analysis and partial least squares discriminant analysis successively, obtains PLS- D A models, PLS-DA models display patients with esophageal squamous cell has metabolic patterns difference and obvious point with healthy population Class trend；
(5) according to PLS-DA models obtained above, the variable importance modeled by PLS-DA scores and univariate Non-parametric test carries out difference metabolin screening, and screening criteria is：VIP >=1, and through the multiple testing adjustment of False discovery rate FDR Q values are less than 0.05 afterwards；
(6) the difference metabolin for obtaining above-mentioned screening determines the standard point of difference metabolin according to the CAMERA bags of R language Daughter ion, adduct and Isotope Information, obtain potential metabolic marker thing；
(7) on the basis of above-mentioned potential metabolic marker thing, one-level, the second order mses letter with reference to potential metabolic marker thing Breath, quasi-molecular ion information, adduct information and Isotope Information, thus it is speculated that the molecular mass and molecular formula of diagnostic marker, and Contrasted with existing n-compound, matched, obtained blood serum metabolic label.Single blood serum metabolic label or serum The combination of metabolic marker thing can be used as being suitable for the diagnostic marker of esophageal squamous cell carcinoma early diagnosis.
In above-mentioned screening technique, the healthy population is without Lesions in Upper Gastrointestinal Tract and other metabolic diseases (such as hyperthyroidism, first Subtract, hypertension and diabetes, ephrosis etc.) crowd.
In above-mentioned screening technique, when carrying out the analysis of LC-MS blood serum metabolics omics technology, every 10 analyses sample adds one Quality control samples, for Real Time Monitoring sample from sample introduction pre-treatment to analysis during quality control situation, it is described Quality control samples are the biased sample of 5 parts of cancer of the esophagus serum samples and 5 parts of healthy serum samples.
In above-mentioned screening technique, following pretreatment is carried out before the analysis sample and Quality control samples sample introduction：
(1) 50 μ l are extracted with pipettor and analyzes sample or Quality control samples, be placed in the automatic sample processing systems of Bravo On 96 orifice plates；
(2) 150 μ l methyl alcohol are added to extract, vortex 30s, and hatch with protein precipitation at -20 DEG C；
(3) 20min and then in supercentrifuge are centrifuged with 4000 revs/min at 4 DEG C；
(4) supernatant of step (3) is poured into LC-MS sample injection bottles, is stored at -80 DEG C in case LC-MS is detected.
In above-mentioned screening technique, collection of illustrative plates pretreatment is carried out to original Metabolic fingerprinting refers to：Use Masshunter softwares The original Metabolic fingerprinting for obtaining is converted into MZdata data files, MZdata data files are then used into XCMS softwares Bag include the pretreatment operation of retention time correction, peak identification, peak match and peak alignment, obtains two-dimensional matrix.
In above-mentioned screening technique, metabolin peak mark is carried out to two-dimensional matrix using R software kits CAMERA includes isotope The metabolin peak mark of peak, adduct and fragment ion.
In above-mentioned screening technique, when being analyzed using LC-MS blood serum metabolic omics technologies to each analysis sample, liquid phase Chromatographic column used by chromatogram is WatersACQUITYUPLC HSS T3 chromatographic columns, and specification is 100mm × 2.1mm, 1.8 μm；Sample introduction It is 6 μ L to measure, and injector temperature is 4 DEG C, and flow velocity is 0.5ml/min；Chromatogram flow phase includes two kinds of solvent orange 2 As and B：Cation ESI+ moulds A under formula is 0.1wt% aqueous formic acids, and the A under anion ESI- models is 0.5mmol/L ammonium fluoride aqueous solutions, cation B under ESI+ patterns is the acetonitrile solution of 0.1wt% formic acid, and the B under anion ESI- models is pure acetonitrile；Chromatogram gradient elution Condition is：0-1min is 1%B, and 1-8min is gradually incremented by for 1%B-100%B, and 10-10.1min is kept to 1% rapidly for 100%B B, then 1%B continue 1.9min.
In above-mentioned screening technique, when being analyzed using LC-MS blood serum metabolic omics technologies to each analysis sample, mass spectrum Detection uses quadrupole rod time-of-flight mass spectrometry instrument Q-TOF, and using the positive ion mode ESI+ and anion of electric spray ion source Pattern ESI-, ion source temperature is 400 DEG C, and taper hole throughput is 12L/min, and desolventizing temperature is 250 DEG C, desolventizing gas flow It is 16L/min；Capillary voltage is respectively+3kV and -3kV under cation and negative ion mode, and taper hole voltage is 0V；Just Ion mode lower cone hole pressure is 20psi, and negative ion mode lower cone hole pressure is 40psi；The mass-to-charge ratio model of spectrum data collection It is 50~1200m/z to enclose, and the scan frequency of collection is 0.25s.
In preferred scheme of the invention, the people of oesophagus carcinoma in situ patient 39 used during screening, the people of early stage patient with esophageal carcinoma 28, The people of late esophagus cancer patient 30, the people of healthy population 105.
In preferred scheme of the invention, R2X=0.167, the R2Y=0.569 of the PLS-DA models obtained in screening process, Q2Y=0.523.
Present invention also offers a kind of construction method of esophageal squamous cell carcinoma diagnostic model, comprise the following steps：
(1) patients with esophageal squamous cell and healthy population serum sample are collected, as analysis sample, wherein esophagus squameous Cell cancer serum sample includes oesophagus carcinoma in situ serum sample, early stage cancer of the esophagus serum sample and late esophagus cancer serum sample；
(2) each analysis sample is analyzed using LC-MS blood serum metabolic omics technologies, obtains the original of each serum sample Metabolic fingerprinting；
(3) collection of illustrative plates is carried out respectively to the original Metabolic fingerprinting of each serum sample using R language XCMS software kits to locate in advance Reason, obtains every behavioural analysis sample, the two-dimensional matrix of metabolin information is often classified as, while using R software kits CAMERA to two dimension Matrix carries out metabolin peak mark, for further statistical analysis；
(4) present invention is filtered out from two-dimensional matrix according to mass-to-charge ratio and retention time and is suitable for esophageal squamous cell carcinoma morning The information of the diagnostic marker of phase diagnosis, obtains diagnostic marker two-dimensional matrix；
(5) according to the diagnostic marker two-dimensional matrix, random forest is built using randomForest software kits in R language Model, obtains esophageal squamous cell carcinoma diagnostic model.
In above-mentioned construction method, the oesophagus carcinoma in situ referred to 0 phase in TNM stage standard, was referred in mucous epithelium layer or skin The intraepidermal atypical hyperplasia of skin (severe) involves the holostrome of epithelium, but not yet invades brokenly basilar memebrane and infiltrate the cancer of growth downwards； The early stage cancer of the esophagus refers to I the and II phases in TNM stage standard, refer to being confined to after mucous membrane without lymph node involvement, without DISTANT METASTASES IN or The cancer of submucosa；Late esophagus cancer refers to III phases and IV phases in TNM stage standard, refers to and has involved muscle layer or up to adventitia or outward Beyond film, there is the cancer of part or distant place lymphatic metastasis.TNM stage standard is according to American joint Committee on Cancer(AJCC)TNM Classfication of Carcinoma of the Esophagus and Esophagogastric Junction(7th ed,2010)。
In preferred scheme of the invention, when building Random Forest model, modeling parameters ntree=5000.
During model construction, built based on following number of samples in preferred scheme of the invention：Used states oesophagus The people of carcinoma in situ patient 39, the people of early stage patient with esophageal carcinoma 28, the people of late esophagus cancer patient 30, the people of healthy population 105.
In preferred scheme of the invention, when the diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis is 25 kinds of blood When combination (the diagnostic marker A) of label thanks in the Qing Dynasty, the diagnosis dividing value (Threshold) of the diagnostic model of gained is 0.3552；When the combination that the diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis is 7 kinds of blood serum metabolic labels (is examined Disconnected label B) when, the diagnosis dividing value (Threshold) of the diagnostic model of gained is 0.7431；When being suitable for esophageal squamous cell When the diagnostic marker of cancer early diagnosis is combination (the diagnostic marker C) of 5 kinds of blood serum metabolic labels, the diagnostic model of gained Diagnosis dividing value (Threshold) be 0.4943.When the prediction numerical value that diagnostic model is given is more than or equal to diagnosis dividing value, explanation With esophageal squamous cell carcinoma, when less than diagnosis dividing value, illustrate not suffering from esophageal squamous cell carcinoma.
Present invention also offers a kind of esophageal squamous cell carcinoma diagnostic model, the diagnostic model is thin according to above-mentioned esophagus squameous The construction method of born of the same parents' cancer diagnostic model builds and obtains.Ibid, in preferred scheme of the present invention, when the diagnosis mark used by diagnostic model When note thing is diagnostic marker A, the diagnosis dividing value of diagnostic model is 0.3552；When for diagnostic marker B, diagnostic model is examined Disconnected dividing value is 0.7431；When for diagnostic marker C, the diagnosis dividing value of diagnostic model is 0.4943.
It is present invention also offers a kind of application method of esophageal squamous cell carcinoma diagnostic model, i.e., thin using the esophagus squameous The method that born of the same parents' cancer diagnostic model diagnoses esophageal squamous cell carcinoma, comprises the following steps：
(1) serum sample to be checked is taken, sample introduction requirement is reached by pretreatment, pretreated serum sample to be checked is used LC-MS blood serum metabolic omics technologies are analyzed, and obtain the original Metabolic fingerprinting of the serum sample to be checked；
(2) the original Metabolic fingerprinting is carried out into collection of illustrative plates pretreatment using R language XCMS software kits, and carries out metabolin Peak is identified, and obtains can be used for the two-dimensional matrix of statistical analysis；
(3) present invention is filtered out from two-dimensional matrix according to mass-to-charge ratio and retention time and is suitable for esophageal squamous cell carcinoma morning The information of the diagnostic marker of phase diagnosis, obtains diagnostic marker two-dimensional matrix；
(4) diagnostic marker two-dimensional matrix is brought into esophageal squamous cell carcinoma diagnostic model, according to the number that model is given The diagnosis dividing value (Threshold) of value and model, determines whether early stage esophageal squamous cell carcinoma.
In preferred scheme of the invention, when being suitable with the combination (diagnostic marker A) of 25 kinds of blood serum metabolic labels When the diagnostic marker of esophageal squamous cell carcinoma early diagnosis, when the numerical value that diagnostic model is given is more than or equal to 0.3552, The cancer of the esophagus is diagnosed as, otherwise not to be；When with 7 kinds of combinations (diagnostic marker B) of blood serum metabolic label to be suitable for oesophagus During the diagnostic marker of squamous cell carcinoma early diagnosis, when the numerical value that diagnostic model is given is more than or equal to 0.7431, it is diagnosed as The cancer of the esophagus, otherwise not to be；When thin to be suitable for esophagus squameous with 5 kinds of combinations (diagnostic marker C) of blood serum metabolic label During the diagnostic marker of born of the same parents' cancer early diagnosis, when the numerical value that diagnostic model is provided is more than or equal to 0.4943, the cancer of the esophagus is diagnosed as, Otherwise it is not to be.
Advantage of the present invention is：The present invention is suitable for using blood serum metabolic omics technology and data statistic analysis technology The diagnostic marker and esophageal squamous cell carcinoma diagnostic model of esophageal squamous cell carcinoma early diagnosis, and it was found that marked with diagnosis Note thing has 10 closely related metabolic pathways.Diagnostic marker screening technique of the present invention is workable, model building method Simply, gained diagnostic model works well, and sensitivity is high, and specificity is good, is not only suitable for the diagnosis of late esophagus cancer, is also adapted to The diagnosis of the early stage cancer of the esophagus, is particularly suitable for the early diagnosis of the cancer of the esophagus.The present invention only can be achieved with diagnosis, nothing by taking blood Create, spend low, can be good at substituting invasive diagnostic mode interior now, significantly reduce the pain of patient, and present invention diagnosis Quickly, convenient, required time is short, improves operating efficiency, is conducive to early discovery, the early treatment of the cancer of the esophagus, faces with good Bed value for applications.
Brief description of the drawings
(LC-QTOF/MS ,+ESI are positive ion mode to the total ion chromatogram of the original Metabolic fingerprintings of Fig. 1, and-ESI is Negative ion mode), transverse axis is retention time (Retention Time, min), and the longitudinal axis is metabolin relative concentration, and Normal is Healthy serum sample, ESCC is cancer of the esophagus serum sample.
The PCA shot charts of Fig. 2 metabolic profile preanalysis, wherein Normal is healthy serum sample, and ESCC is cancer of the esophagus blood Final proof sheet, QC represents Quality control samples.
The PLS-DA three-dimensional shot charts that Fig. 3 A compare for the metabolic profile of the cancer of the esophagus and normal healthy controls, the R2X=of modeling 0.167, R2Y=0.569, Q2Y=0.523；Fig. 3 B are that the PLS-DA based on random permutation method models proof diagram accordingly.Its Middle Normal is healthy serum sample, and ESCC is cancer of the esophagus serum sample.
The identity process figure of Fig. 4 .L- tryptophans (L-Tryptophan), wherein figure (a)：M/z is 205.0974 chromatogram Retention time feature in figure；Figure (b)：Retention time is the first mass spectrometric figure of 181.38s；Figure (c)：Retention time is 181.38s, M/z is 205.0974 secondary ion MS/MS fragmentation patterns；Figure (d)：Metabolin (RT：181.38s, m/z：205.0974) broken Piece cracks mechanism.
The ROC curve figure of the external testing sample of the Random Forest model constructed by Fig. 5 .25 metabolic marker things.
The external testing sample ROC of the random forest early stage esophagus cancer diagnosis model constructed by Fig. 6 .7 metabolic marker things Curve.
The external testing sample ROC of the random forest early stage esophagus cancer diagnosis model constructed by Fig. 7 .5 metabolic marker things Curve.
Specific embodiment
Below, the present invention is further explained by detailed description below, and advantage of the present invention is carried out It is further to prove.
The screening of diagnostic marker of the present invention, the construction method of diagnostic model and compliance test result are as follows：
1st, research object
This research relies on the cancer of the esophagus screening platform of " national cancer of the esophagus early diagnosis early controls Demonstration Base (Feicheng, Shandong Province) ", (confirm as goldstandard) for the indicative biopsy object of iodine staining under the gastroscope of Feicheng, Shandong Province 40-69 Sui, collection oesophagus is former Position cancer (0 phase 39), the early stage cancer of the esophagus (I phases 17, II phases 11) and late esophagus cancer (III phases 30)；And randomly select Iodine staining negative subject is the health objects 105 without Lesions in Upper Gastrointestinal Tract as healthy sample under gastroscope in screening.
2nd, the blood serum metabolic group detection of LC-MS
It is put in -80 DEG C of refrigerators after the serum sample centrifugation of all collections and is preserved, is joined using Ultra Performance Liquid Chromatography-mass spectrum Use instrument
The automatic Pretreated system (Agilent, USA) of (UPLC-QTOF/MS 6550, Agilent) and Bravo is carried out Metabolism group detection (point 3 big batch detections, and carry out quality control), obtain the original comprising chromatogram and Information in Mass Spectra of sample Beginning Metabolic fingerprinting.Concrete operations are as follows：
2.1 instrument and equipments
Experimental facilities includes：The systems of UPLC-QTOF/MS 6550 (Agilent, USA), Bravo systems (Agilent, USA), high speed low temperature centrifugal machine, vibration scroll machine, nitrogen drying device, 4 DEG C of cold storage refrigerators (Haier), pure water meters (Siemens).
Experiment consumptive material includes：Waters ACQUITYHSS T3(particle size,1.8μm；100mm (length) × 2.1mm) chromatographic column, liquid nitrogen, High Purity Nitrogen；Cone bottom sample injection bottle, 2ml centrifugal rotors, 2ml centrifuge tubes (round bottom), shifting Liquid device, 1000 μ l pipette tips, 200 μ l pipette tips, marking pen, emgloves, mouth mask.
Experiment reagent includes：Methyl alcohol (enlightening horse, HPLC grades pure), acetonitrile (enlightening horse, HPLC grades pure), formic acid (recovery precise treatment Learn research institute, Tianjin), pure water (TOC<10ppb).
2.2 serum samples are pre-processed
Before serum sample pretreatment, 21 parts of Quality control samples (QC) are prepared, by all early stage cancer of the esophagus serum samples, food Pipe carcinoma in situ serum sample, late esophagus cancer serum sample, healthy serum sample and Quality control samples carry out random number, with Early stage cancer of the esophagus serum sample, oesophagus carcinoma in situ serum sample, late esophagus cancer serum sample, healthy serum sample are used as analysis Sample, analyzes sample and adds a Quality control samples every 10.By early stage cancer of the esophagus serum sample, oesophagus original position cancer-serum Sample and late esophagus cancer serum sample are referred to as cancer of the esophagus serum sample, and Quality control samples are 5 parts of cancer of the esophagus serum samples With 5 parts of biased samples of healthy serum sample.Cancer of the esophagus serum sample, healthy serum sample and Quality control samples carry out pre- Treatment, pretreatment includes following 4 steps：
(1) 50 μ l are extracted with pipettor and analyzes sample or Quality control samples, be placed in the automatic sample processing systems of Bravo On 96 orifice plates of (Agilent, USA)；
(2) 150 μ l methyl alcohol are added to extract, vortex 30s, and hatch with protein precipitation at -20 DEG C.
(3) 20min and then in supercentrifuge are centrifuged with 4000 revs/min at 4 DEG C；
(4) supernatant of step (3) is poured into LC-MS sample injection bottles, is stored at -80 DEG C in case LC-MS is detected；
2.3 serum UPLC-QTOF/MS are detected
The pretreated sample of 6 μ L aliquots is injected ACQUITY UPLC by UPLC systems (1290series, Agilent) HSS T3(particle size,1.8μm；100mm (length) × 2.1mm) chromatographic column (Waters, Milford, USA).Enter Sample order is completely random sample introduction, to exclude the bias that Loading sequence brings.Chromatogram flow phase includes two kinds of solvents：A is 0.1wt% formic acid (water dilutes, cation ESI+) or 0.5mM ammonium fluorides (water dilutes, anion ESI-), B is 0.1wt% formic acid (dilution in acetonitrile, cation ESI+) or 100% acetonitrile (anion ESI-).Chromatogram gradient is：0-1min is 1%B, and 1-8min is 1%B-100%B is gradually incremented by, and then 10-10.1min is kept to rapidly 1%B for 100%B, and then 1%B continues 1.9min.Stream Speed is 0.5ml/min.Whole sample detection process maintains 4 DEG C.Wherein, the percentage composition of A and B refers to volume basis and contains Amount.
Mass Spectrometer Method uses Agilent quadrupole rods time-of-flight mass spectrometry instrument Q-TOF (6550, Agilent), and uses EFI The positive ion mode (ESI+) and negative ion mode (ESI-) of mist ion gun.Ion source temperature is set as 400 DEG C, and taper hole air-flow It is 12L/min to measure.Meanwhile, desolventizing temperature is set as 250 DEG C, and desolventizing gas flow 16L/min.In cation and anion Capillary voltage is respectively+3kV and -3kV under pattern, and taper hole voltage is 0V.Taper hole pressure be 20psi (cation) and 40psi (anion).The mass charge ratio range of spectrum data collection is 50~1200m/z, and the scan frequency of collection is 0.25s.MS/ In MS second mass analysis, high-purity nitrogen is used to generate object ion fragment as collision gas, collision energy is set to 10, 20 or 40eV.
3rd, XCMS collection of illustrative plates pretreatment
The original Metabolic fingerprinting data of UPLC-QTOF/MS serum cation ESI+ and anion ESI- detection acquisition (see Fig. 1), Mzdata data files are converted into by the Masshunter softwares of Agilent companies, then use the XCMS of R language Software kit carries out XCMS collection of illustrative plates pretreatments, and pretreatment includes that retention time correction, peak identification, peak match, peak alignment, filter are made an uproar, weighed Folded peak parsing, threshold value selection, standardization etc..XCMS pretreatment relevant parameter be：The waist peak width of peak half is 10 (fwhm=10), is protected Time window is stayed to be set to 10 (bw=10), and other specification is default value.Obtain can be used for statistical after the pretreatment of XCMS collection of illustrative plates The two-dimensional matrix of analysis, where each row is sample (observation), is often classified as metabolin (variable), and matrix intermediate value is that corresponding metabolin is dense Degree.And each metabolin peak uses retention time (retention time, RT) and mass-to-charge ratio (mass-to-charge Ratio, m/z) it is qualitative.Then the two-dimensional matrix using R software kits CAMERA carry out metabolin peak mark (including isotopic peak, Adduct and fragment ion).Sample is standardized before statistical analysis, retention time range set to be analyzed is 0.5 ~10min.Pre-processed through XCMS collection of illustrative plates, included in the data matrix of the UPLC-QTOF/MS spectrum generations of positive ion detection pattern 981 metabolin peaks, anionic textiles pattern is 485 metabolin peaks, has 1466 metabolin peaks.
4th, LC-MS quality control of the experiment
When serum sample carries out metabolism group detection, the QC samples that will be prepared arrange 1 QC by every 10 analysis samples Uniformly in the order insertion analysis sample in so that real-time monitoring from Sample pretreatment to pattern detection during quality control Situation.After the original Metabolic fingerprinting of gained is pre-processed through XCMS collection of illustrative plates, %RSD value of each metabolin in QC samples is calculated (coefficient of variation), the %RSD values of most metabolins are controlled below 30%, illustrate that Sample pretreatment was surveyed to sample product examine Quality control in journey is all right, and the metabolism group data for being obtained are genuine and believable.
5th, the metabolic profile preanalysis based on PCA
The use of unsupervised analysis method is that principal component analysis (principal component analysis, PCA) comes just Classification trend and outlier, are shown in Fig. 2 between step observation group.The repeatability of QC samples can be shown that LC-MS quality control of the experiment is good in figure It is good.From this figure it can be seen that between the cancer of the esophagus and normal healthy controls have certain classification trend, but still have partial intersection, it is necessary to Further classification is realized using supervised learning method.
6th, the metabolic profiling analysis based on PLS-DA
The dimensional matrix data that will be obtained is randomly assigned into 4/5 as training sample training data, and 1/5 makees in addition It is external testing sample test data (being shown in Table 1).It is the deviation that gap in elimination group of trying one's best causes, obtains more obvious point Group trend, further directed to training sample using there is supervision analysis method i.e. partial least squares discriminant analysis (partial least Squares-discriminant analysis, PLS-DA) display the cancer of the esophagus and normal healthy controls between metabolic profile difference and Classification trend.As shown in figure 3, the cancer of the esophagus is classified trend between metabolic patterns difference and obvious group with having between normal healthy controls, its The R2X=0.167 of modeling, R2Y=0.569, Q2Y=0.523.
The baseline and clinical pathologic characteristic of the metabolism group research of the cancer of the esophagus of table 1. early diagnosis
7th, the screening of difference metabolin and chemical substance identification of cancer of the esophagus early diagnosis
To filter out the difference metabolin of early stage esophagus cancer diagnosis, we are commented by means of the variable importance of PLS-DA modelings (VIP) and univariate non-parametric test (nonparametric Kruskal-Wallis rank sum test) is divided to be sieved Choosing.Variable Selection standard is：VIP≥1；And q values are less than 0.05 after the multiple testing adjustment of False discovery rate FDR.According to this mark Standard, filters out the differential expression blood serum metabolic group echo thing 551 between the cancer of the esophagus and normal healthy controls, further according to R languages altogether The CAMERA bags of speech determine quasi-molecular ion, adduct and the Isotope Information of difference metabolin, exclude chemical signal and human body It is interior without, obtain 242 potential metabolic marker things.
For above-mentioned 242 potential metabolic marker things, according to following chemical substance authentication step (such as metabolic marker thing L- colors The qualification process of propylhomoserin RT 181.38s, m/z 205.0974, is shown in Fig. 4), carry out the identification of metabolic marker thing：
(1) the first mass spectrometric cracking distribution characteristics according to potential metabolic marker thing, with reference to the CAMERA software kits of R language (CAMERA is R language package software kit Collection of annotation related methods for mass Spectrometry data, http://bioconductor.org/packages/release/bioc/html/ CAMERA.html quasi-molecular ion, adduct and the Isotope Information of potential metabolic marker thing) are determined, thus it is speculated that potential metabolism mark Remember the molecular mass and molecular formula of thing；
(2) online people's metabolite database HMDB (http are searched according to molecular mass://www.hmdb.ca/) and METLIN(http://metlin.scripps.edu/), determine some compound candidates；
(3) RRLC-QTOF/MS/MS second order mses experiments are carried out to 242 potential metabolic marker things, further obtains generation Thank to the corresponding mass ions patch information of thing, and second order mses figure fragment ion is carried out with compound candidate in database and match； Comparing the chromatogram and mass spectral characteristic of compound standard sample library carries out final material determination.
According to above-mentioned authentication method, successful identification goes out 25 serum altogether in the case of being confirmed by second order mses or standard items Metabolic marker thing, this 25 common names of serum size label (Common Name) are respectively：beta-Ala-Lys；L- Carnos ine；cis-9-Palmitoleic acid；Palmitic acid；Oleic Acid；LPA(18:1(9Z)/0:0)； LysoPC(14:0/0:0)；LysoPC(18:2(9Z,12Z))；LysoPC(24:0)；PC(14:1(9Z)/P-18:1(11Z))； PC(16:0/18:2(9Z,12Z))；PC(24:1(15Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z))；Linoleic acid；NADH；Cortisol；L-Tyrosine；L-Tryptophan；Glycocholic Acid；Taurocholate； Hypoxanthine；Allantoic ac id；Inosine；Sphingosine 1-phosphate；3-O- Sulfogalactosylceramide(d18:1/20:0)；Lact osylceramide(d18:1/22:0).
Document has been delivered in contrast, and this 25 blood serum metabolic labels of the invention are first in early stage esophageal squamous cell carcinoma Middle discovery, this for the early stage cancer of the esophagus diagnosis, treatment be of great significance.Wherein, the Chinese of beta-Ala-Lys is translated Entitled beta- alanine-lysines, the Chinese translation of L-Carnosine is L-Carnosine, cis-9-Palmitoleic acid Chinese translation be POA, the Chinese translation of Palmitic acid is palmitic acid, and the Chinese of OleicAcid is translated Entitled oleic acid, the Chinese translation of LPA is lysophosphatidic acid, and the Chinese translation of LysoPC is lysolecithin, the Chinese translation of PC It is phosphatide, the Chinese translation of Linoleic acid is linoleic acid, and the Chinese translation of NADH is NADH, The Chinese translation of Cortisol is cortisol, and the Chinese translation of L-Tyrosine is TYR, the Chinese of L-Tryptophan Translated name is L-Trp, and the Chinese translation of GlycocholicAcid is glycocholic acid, and the Chinese translation of Taurocholate is ox Sulphur cholate, the Chinese translation of Hypoxanthine is hypoxanthine, and the Chinese translation of Allantoic acid is allantoic acid, The Chinese translation of Inosine is inosine, and the Chinese translation of Sphingosine 1-phosphate is S1P, 3-O- The Chinese translation of Sulfogalactosylceramide is sulfogalactosylceramide, Lactosylceramide's Chinese translation is galactosylceramide, and each Chinese translation there may be deviation because of translation, is defined by English standard name.
Database retrieval information of the above-mentioned 25 blood serum metabolic labels in HMDB and METLIN is as shown in table 2 below, this Art personnel can be in following table HMDB ID, METLIN ID obtain the detailed of this 25 blood serum metabolic labels Thin information, such as chemical structural formula：
Database retrieval information of the 2 25 blood serum metabolic labels of table in HMDB and METLIN
Additionally, being enriched with (enrichment) and metabolic pathway (pathway) analysis by KEGG, above-mentioned 25 serum is found Metabolic marker thing is closely related with following 10 metabolic pathways：Glycerophospholipid metabolism；Linoleic acid metabolism；beta-Alanine metabolism；Fatty acid biosynthesis；Oxidative phosphorylation；Phenylalanine,tyrosine and tryptophan biosynthesis；Primary bile acid biosynthesis；Pathways in cancer,and Bile secretion；Purine metabolism；Sphingolipid metabolism.Above-mentioned 10 metabolic pathways are the standard name in metabolic pathway KEGG (http://www.genome.jp/kegg/), its corresponding Chinese translation is：Glycerophosphatide is metabolized (Glycerophospholipid metabolism), linoleic acid metabolism (Linoleic acid metabolism), beta third Propylhomoserin metabolism (beta-Alanine metabolism), aliphatic acid synthesis (Fatty acid biosynthesis), phosphorous oxide Acidifying (Oxidative phosphorylation), phenylalanine/tyrosine and tryptophan metabolism (Phenylalanine, Tyrosine and tryptophan biosynthesis), primary bile acid synthesis (Primary bile acid Biosynthesis), cancer path and choleresis (Pathways in cancer, and Bile secretion), purine Metabolism (Purine metabolism), sphingolipid metabolism (Sphingolipid metabolism).This proves Incidence of Esophageal Cancer This 10 metabolic pathways there occurs disturbance in early days, and this discovery of the invention has very for the prevention of the cancer of the esophagus and the research and development of medicine Good directive function.
Table 3 below is the difference letter for screening the 25 blood serum metabolic labels for obtaining in patient with esophageal carcinoma and healthy population Breath, wherein being found that L-Tryptophan under positive and negative two ion modes.FC is the change that the cancer of the esophagus is compared with normal healthy controls Change multiple (fold change), be can be seen that according to FC information：Beta- alanine-lysines (beta-Ala-Lys), haemolysis Phosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), phosphatide PC (16:0/18:2(9Z,12Z))、 NADH (NADH), TYR (L-Tyrosine), L-Trp (L-Tryptophan), sweet ammonia courage Sour (Glycoch olic Acid), allantoic acid (Allantoic acid), inosine (Inosine) and S1P (Sphingosine 1-phosphat e) is significantly raised compared to health group expression quantity in cancer of the esophagus group, and other metabolism marks Note thing is substantially reduced in cancer of the esophagus group compared to health group expression quantity.
FDR is the False discovery rate based on the correction of non-parametric test Multiple range test, and its value is respectively less than 0.05；AUC is single generation Area AUC under the ROC curve of the Evaluating Diagnostic Tests for thanking to group echo thing, this 25 blood serum metabolic marks are can be seen that from the value When thing carries out the diagnosis of the cancer of the esophagus and the non-cancer of the esophagus separately as label, minimum AUC is 0.61, and highest AUC is 0.85.It can thus be seen that for as the diagnostic marker of one-component, 25 blood serum metabolic marks that present invention screening is obtained The diagnosis effect for remembering thing is more significant, and carrying out diagnosis with single blood serum metabolic label has certain clinical research valency Value.
In order that diagnosis effect is more preferably, the combination of blood serum metabolic label can be used, for example can be according to serum Relation between metabolic marker thing and metabolic pathway is combined, and forms following 8 kinds of diagnostic markers：(a) beta- alanine- The combination of lysine (beta-Ala-Lys) and L-Carnosine (L-Carnosine)；(b) POA (cis-9- Palmitoleic acid), the combination of palmitic acid (Palmitic acid) and oleic acid (OleicAcid)；(c) lysophosphatidic acid LPA(18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)) and Lysolecithin LysoPC (24:0) combination；(d) phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1(15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)) and linoleic acid (Linoleic Acid combination)；(e) NADH (NADH), TYR (L-Tyrosine) and L-Trp (L- Tryptophan combination)；(f) cortisol (Cortisol), glycocholic acid (GlycocholicAcid) and taurocholate (Taurocholate) combination；(g) hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid) and inosine (Inosine) combination；(h) S1P (Sphingosine 1-phosphate), sulfuric acid galactosyl acyl group sheath ammonia Alcohol 3-O-Sulfogalactosylceramide (d18:1/20:0) with galactosylceramide Lactosylceramide (d18: 1/22:0) combination.
It is also an option that the good several metabolic marker things of AUC effects are combined to form diagnostic marker, for example, diagnosis mark Note thing can be two or more the combination in following blood serum metabolic labels：Lysophosphatidic acid LPA (18:1(9Z)/ 0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)), lysolecithin LysoPC(24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1(15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), NADH (NADH), cortisol (Cortisol), L-Trp (L-Trypto phan), taurocholate (Taurocholate), hypoxanthine (Hypoxanthine), inosine (Inosine), sulfogalactosylceramide 3-O- Sulfogalactosylceramide(d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/22:0).
It can also be two or more the combination in following 7 kinds of blood serum metabolic labels：Lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)), haemolysis Lecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)) and phosphorus Fat PC (24:1(15Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z)).
It can also be two or more the combination in following 5 kinds of blood serum metabolic labels：TYR (L- Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid), taurocholate And cortisol (C ortisol) (Taurocholate).
25 kinds of blood serum metabolic labels of differential expression between the cancer of the esophagus of table 3. and normal healthy controls
FDR is False discovery rate (Multiple range test)；AUC is area under ROC curve；FC is that fold change change multiple； RSD% is the coefficient of variation calculated based on quality control sample.
Below, 3 kinds of further application effects of preferred diagnostic marker of the invention are itemized, other diagnostic markers Applicable cases will not enumerate herein.
8th, the cancer of the esophagus early diagnosis model and external certificate
8.1 using 25 combinations of blood serum metabolic label of above-mentioned identification as diagnostic marker, the base in training sample Cancer of the esophagus early diagnosis model is built in random forest (random Forest).Random forest is used in R language RandomForest software kits realize that modeling parameters ntree=5000 (is equal to following b).
Random forest modeling procedure is as follows：
(1) sample content of original training set is N, has using bootstrap methods randomly select new self-service of b with putting back to Sample set, and thus build b classification tree, the sample not being pumped to every time constitute b bag outward data (out-of-bag, OOB)；
(2) it is provided with mallIndividual variable, then randomly select m at each node of every one treetxyIndividual variable (mtry＜ ＜ mall), then in mtryThe variable of middle selection one most classification capacity, the threshold value of variable classification is classified by checking each Point determines；
(3) each classification tree in random forest is binary tree, and its generation follows top-down recurrence division principle, Training set is divided successively since root node.Each tree is grown to greatest extent, and any pruning is not done.
(4) many classification trees that will be generated constitute random forest, and new data are differentiated with random forest grader With classification, classification results press Tree Classifier ballot it is how many depending on.
(5) the diagnosis dividing value of diagnosis can and then with the ballot score and the analysis of actual classification situation row ROC curve be obtained (Threshold).The diagnosis dividing value (Threshold) of this model is 0.3552.
The Random Forest model of above-mentioned structure may act as esophagus cancer diagnosis model, when using the random forest mould for building When type is diagnosed, the data message of 25 blood serum metabolic labels in test serum is imported in Random Forest model, such as The voting results of fruit model classifiers are then judged to that diagnosis is positive (suffering from esophageal squamous cell carcinoma) more than or equal to diagnosis dividing value, If less than diagnosis dividing value, being judged to that diagnosis is negative (being not suffering from esophageal squamous cell carcinoma).
The dimensional matrix data of 25 blood serum metabolic labels of external testing sample is substituted into the random gloomy of above-mentioned foundation In woods model, the cancer of the esophagus P predicted value of test sample is obtained, and with actual pathological examination (cancer of the esophagus or health) phase Than doing ROC curve analysis (see Fig. 5), area AUC under sensitivity, specificity and the ROC curve of Random Forest model, knot are obtained Fruit is shown in Table 4.From Fig. 5 and Biao 4 as can be seen that the esophagus cancer diagnosis modelling effect of above-mentioned structure of the invention is good, it is used for oesophagus Area AUC is 0.895 (0.784~1) under the ROC curve of cancer diagnosis, and sensitivity is 85.00%, and specificity is 90.48%.
Further, by the different cancer of the esophagus P predicted values by stages of test sample and actual pathological examination (food Pipe cancer or health) compared to ROC curve analysis is done respectively, for evaluating diagnosis effect of the diagnostic model to the different cancer of the esophagus by stages Really.For the sensitivity of the different cancer of the esophagus by stages, specificity and under ROC curve, area AUC see the table below Random Forest model 4, as can be seen from the table：With the further deterioration of the cancer of the esophagus, AUC and specificity have and increase trend, and sensitivity is in the original location During cancer and late cancer preferably, declined in early carcinoma, on the whole diagnosis effect of the model for late esophagus cancer Preferably, but the diagnosis effect (AUC) of carcinoma in situ and the early stage cancer of the esophagus can also reach acceptable more than 0.85, it may have The value of early diagnosis, while also illustrating that the present invention screens the blood serum metabolic label for obtaining in the early stage cancer of the esophagus even carcinoma in situ Just there are metabolic alterations in stage.
Carcinoma in situ is that, than early stage in (I the and II phases) cancer of the esophagus early stage, the diagnosis early stage of the cancer of the esophagus is more difficult to, late period phase To easily.Seen by the data in table, whether diagnostic model of the invention can be good at being diagnosed to be with the cancer of the esophagus, and Diagnosis effect not only to late esophagus cancer is good, the degree of accuracy, sensitivity and specificity for the early stage cancer of the esophagus and carcinoma in situ Preferably, the unconspicuous carcinoma in situ of symptom and the early stage cancer of the esophagus can be effectively diagnosed to be, cancer rate of missed diagnosis is reduced, it is highly beneficial In morning discovery, the early treatment of the cancer of the esophagus, there is help well for improving the prognosis of the cancer of the esophagus, the death rate of the reduction cancer of the esophagus, With good Clinical practice and promotional value.
The outside ROC analysis results promoted of the esophagus cancer diagnosis model of table 4.
8.2 are modeled using the combination of 7 blood serum metabolic labels as diagnostic marker, and for diagnosis of esophageal cancer, It is specific as follows：
The dimensional matrix data that will be obtained is randomly assigned into 4/5 as training sample training data, and 1/5 makees in addition It is external testing sample test data (being shown in Table 1).Only with lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC(14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)), lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)) and phosphatide PC (24:1(15Z)/22:6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)) 7 kinds of metabolic marker things, as diagnostic marker, are based on random forest in training sample (random Forest) builds cancer of the esophagus early diagnosis model.Random forest uses randomForest software kit realities in R language It is existing, modeling parameters ntree=5000, random forest modeling procedure is ibid.
When being diagnosed using the stochastic model for building, the data of 7 blood serum metabolic labels in test serum are believed Breath is imported in Random Forest model, if the voting results of model classifiers are judged to diagnosis more than or equal to diagnosis dividing value Positive (suffering from esophageal squamous cell carcinoma), if less than diagnosis dividing value, being judged to that diagnosis is negative (being not suffering from esophageal squamous cell carcinoma). The diagnosis dividing value (Threshold) of this model is 0.7431.
The dimensional matrix data of 7 blood serum metabolic labels of external testing sample is substituted into the random forest of above-mentioned foundation In model, the cancer of the esophagus P predicted value of test sample is obtained, and compared with actual pathological examination (cancer of the esophagus or health) ROC curve analysis is done (see Fig. 6), area AUC under sensitivity, specificity and the ROC curve of Random Forest model is obtained, as a result It is shown in Table 5.From Fig. 6 and Biao 5 as can be seen that the esophagus cancer diagnosis modelling effect of above-mentioned structure of the invention is good, it is used for the cancer of the esophagus The AUC of diagnosis is 0.876 (0.752~1), and sensitivity is 90%, and specificity is 85.71%.
Further, by the different cancer of the esophagus P predicted values by stages of test sample and actual pathological examination (food Pipe cancer or health) compared to ROC curve analysis is done respectively, for evaluating diagnosis effect of the diagnostic model to the different cancer of the esophagus by stages Really.For the sensitivity of the different cancer of the esophagus by stages, specificity and under ROC curve, area AUC see the table below Random Forest model 5, as can be seen from the table：With the further deterioration of the cancer of the esophagus, AUC and sensitivity have increases trend, and specificity is in the original location During cancer and late cancer preferably, declined in early carcinoma, on the whole diagnosis effect of the model for late esophagus cancer Preferably, but the diagnosis effect (AUC) of carcinoma in situ and the early stage cancer of the esophagus can also reach acceptable more than 0.83, it may have The value of early diagnosis, while also illustrating that the present invention screens the blood serum metabolic label for obtaining in the early stage cancer of the esophagus even carcinoma in situ Just there are metabolic alterations in stage.
By the data in table can be seen that 7 diagnostic models of blood serum metabolic label information architecture of the invention compared to Diagnostic model effect using 25 blood serum metabolic label information architectures is weaker, but the diagnostic model also can be good at examining Break and whether with the cancer of the esophagus, and diagnosis effect not only to late esophagus cancer is good, for the early stage cancer of the esophagus and carcinoma in situ The degree of accuracy, sensitivity and specificity also preferably, can effectively be diagnosed to be the unconspicuous carcinoma in situ of symptom and the early stage cancer of the esophagus, drop Low cancer rate of missed diagnosis, be very beneficial for the cancer of the esophagus it is early find, early treatment, for improving the prognosis of the cancer of the esophagus, reducing oesophagus The death rate of cancer has help well, with good Clinical practice and promotional value.
The outside ROC analysis results promoted of the esophagus cancer diagnosis model of table 5
8.3rd, the combination using 5 blood serum metabolic labels is modeled as diagnostic marker, and for diagnosis of esophageal cancer, It is specific as follows：
The dimensional matrix data that will be obtained is randomly assigned into 4/5 as training sample training data, and 1/5 makees in addition It is external testing sample test data (being shown in Table 1).Using TYR (L-Tyrosine), L-Trp (L- Tryptophan), glycocholic acid (GlycocholicAcid), taurocholate (Taurocholate) and cortisol (Cortisol) 5 kinds of blood serum metabolic labels are based on random forest (random as diagnostic marker in training sample Forest cancer of the esophagus early diagnosis model) is built.Random forest is realized using randomForest software kits in R language, modeled Parameter ntree=5000, random forest modeling procedure is ibid.
When being diagnosed using the stochastic model for building, the data of 5 blood serum metabolic labels in test serum are believed Breath is imported in Random Forest model, if the voting results of model classifiers are judged to diagnosis more than or equal to diagnosis dividing value Positive (suffering from esophageal squamous cell carcinoma), if less than diagnosis dividing value, being judged to that diagnosis is negative (being not suffering from esophageal squamous cell carcinoma). The diagnosis dividing value (Threshold) of this model is 0.4943.
The dimensional matrix data of 5 blood serum metabolic labels of external testing sample is substituted into the random forest of above-mentioned foundation In model, the cancer of the esophagus P predicted value of test sample is obtained, and compared with actual pathological examination (cancer of the esophagus or health) ROC curve analysis is done (see Fig. 7), area AUC under sensitivity, specificity and the ROC curve of Random Forest model is obtained, as a result It is shown in Table 6.From Fig. 7 and Biao 6 as can be seen that the esophagus cancer diagnosis modelling effect of above-mentioned structure of the invention is good, it is used for the cancer of the esophagus The AUC of diagnosis is 0.84 (0.703~0.978), and sensitivity is 95%, and specificity is 76.19%.
Further, by the different cancer of the esophagus P predicted values by stages of test sample and actual pathological examination (food Pipe cancer or health) compared to ROC curve analysis is done respectively, for evaluating diagnosis effect of the diagnostic model to the different cancer of the esophagus by stages Really.For the sensitivity of the different cancer of the esophagus by stages, specificity and under ROC curve, area AUC see the table below Random Forest model 6, as can be seen from the table：This 5 kinds of blood serum metabolic labels show different to become for carcinoma in situ, early carcinoma and late cancer Gesture.
By the data in table can be seen that 5 diagnostic models of blood serum metabolic label information architecture of the invention compared to Diagnostic model effect using 25 and 7 blood serum metabolic label information architectures is weaker, but the diagnostic model also can be very Whether good is diagnosed to be with the cancer of the esophagus, and diagnosis effect not only to late esophagus cancer is good, for the early stage cancer of the esophagus and original The position degree of accuracy of cancer, sensitivity and specificity also preferably, can effectively be diagnosed to be the unconspicuous carcinoma in situ of symptom and early stage eats Pipe cancer, reduces cancer rate of missed diagnosis, is very beneficial for early discovery, the early treatment of the cancer of the esophagus, for the prognosis, the drop that improve the cancer of the esophagus The death rate of the low cancer of the esophagus has help well, with good Clinical practice and promotional value.
The outside ROC analysis results promoted of the cancer of the esophagus of table 6 early diagnosis model
9th, conclusion
9.1 the present invention gained 25 blood serum metabolic labels in any one as diagnosis of esophageal cancer diagnostic marker All there is preferable diagnosis effect, but the effect of multiple blood serum metabolic label combination applications is more preferable.
The diagnostic model of 9.2 currently preferred 3 kinds of diagnostic markers (diagnostic marker A, B, C) and structure is for food Pipe cancer has good diagnosis effect, with clinical value.
By checking, present invention gained diagnostic marker and diagnostic model have good application value, can be in clinic The upper diagnosis that the cancer of the esophagus is carried out using diagnostic marker of the invention and diagnostic model, step is as follows：
(1) serum to be checked is gathered, serum is pre-processed using step (1)-(4) in above-mentioned 2.2 after centrifugation, in case Sample detection；
(2) pretreated serum sample to be checked is obtained into original metabolism according to LC-MS detections are carried out the step of above-mentioned 2.3 Finger-print；
(3) original Metabolic fingerprinting is carried out into collection of illustrative plates pretreatment according to the method for above-mentioned steps 3, and carries out metabolin peak Mark, obtains the two-dimensional matrix of the serum to be checked；
(4) corresponding diagnostic marker (diagnostic marker is filtered out from two-dimensional matrix according to mass-to-charge ratio and retention time A, B or C) information, obtain diagnostic marker two-dimensional matrix；
(5) diagnostic marker two-dimensional matrix is brought into corresponding diagnostic model, according to numerical value and model that model is given Diagnosis dividing value (Threshold), determine whether esophageal squamous cell carcinoma.When the numerical value that model is given is more than or equal to diagnosis circle During value, it is judged to that diagnosis is positive (suffering from esophageal squamous cell carcinoma), if less than diagnosis dividing value, being judged to that diagnosis feminine gender (is not suffering from Esophageal squamous cell carcinoma).
In addition, in order to accelerate efficiency, the serum sample of many people can be simultaneously gathered, and is numbered, by multiple samples This disposably carries out LC-MS detections, collection of illustrative plates pretreatment, metabolic peak mark, the screening of diagnostic marker two-dimensional matrix and data and imports.
In actual applications, more samples can be chosen according to modeling method of the present invention to be modeled, increases model The degree of accuracy.
It is more than non-limiting to the description of patent of the present invention, based on the other embodiment of patent thought of the present invention, Among the scope of the present invention.

Claims (9)

1. it is a kind of to be suitable for the diagnostic marker that esophageal squamous cell carcinoma is early diagnosed, it is characterized in that including：
Blood serum metabolic label A：Taurocholate (Taurocholate), and
Blood serum metabolic label B：Cortisol (Cortisol).
2. diagnostic marker according to claim 1, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more during label C is selected from following blood serum metabolic label：TYR (L-Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid).
3. diagnostic marker according to claim 2, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to the combination that label C is following 3 kinds of blood serum metabolic labels：TYR (L-Tyrosine), L-Trp (L- Tryptophan), glycocholic acid (Glycocholic Acid).
4. diagnostic marker according to claim 1, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more during label C is selected from following blood serum metabolic label：Beta- alanine-lysines (beta-Ala- Lys), L-Carnosine (L-Carnosine), POA (cis-9-Palmitoleic acid), palmitic acid (Palmitic acid), oleic acid (Oleic Acid), lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC(14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)), lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1(15Z)/22:6(4Z,7Z, 10Z, 13Z, 16Z, 19Z)), linoleic acid (Linoleic acid), NADH (NADH), TYR (L-Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid), hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid), inosine (Inosine), S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O-Sulfogalactosylceramide (d18:1/20:0)、 Galactosylceramide Lactosylceramide (d18:1/22:0).
5. diagnostic marker according to claim 4, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more during label C is selected from following blood serum metabolic label：Lysophosphatidic acid LPA (18:1(9Z)/0:0) it is, molten Blood lecithin LysoPC (14:0/0:0), lysolecithin LysoPC (18:2 (9Z, 12Z)), lysolecithin LysoPC (24: 0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1(15Z)/ 22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), NADH (NADH), L-Trp (L- Tryptophan), hypoxanthine (Hypoxanthine), inosine (Inosine), sulfogalactosylceramide 3-O- Sulfogalactosylceramide (d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/22: 0)。
6. diagnostic marker according to claim 5, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more during label C is selected from following blood serum metabolic label：Lysolecithin LysoPC (18:2(9Z,12Z))、 Lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (24:1(15Z)/22:6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), NADH (NADH), sulfogalactosylceramide 3-O- Sulfogalactosylceramide (d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/22: 0)。
7. diagnostic marker according to claim 6, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more during label C is selected from following blood serum metabolic label：Lysolecithin LysoPC (18:2(9Z,12Z))、 Lysolecithin LysoPC (24:0), phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (24:1(15Z)/22:6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z)), galactosylceramide Lactosylceramide (d18:1/22:0).
8. diagnostic marker according to claim 1, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more during label C is selected from following combination：
Combination one：The combination of beta- alanine-lysines (beta-Ala-Lys) and L-Carnosine (L-Carnosine)；
Combination two：POA (cis-9-Palmitoleic acid), palmitic acid (Palmitic acid) and oil The combination of sour (Oleic Acid)；
Combination three：Lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin LysoPC (14:0/0:0), lysolecithin LysoPC(18:2 (9Z, 12Z)) and lysolecithin LysoPC (24:0) combination；
Combination four：Phosphatide PC (14:1(9Z)/P-18:1 (11Z)), phosphatide PC (16:0/18:2 (9Z, 12Z)), phosphatide PC (24:1 (15Z)/22:6 (4Z, 7Z, 10Z, 13Z, 16Z, 19Z)) and linoleic acid (Linoleic acid) combination；
Combination five：NADH (NADH), TYR (L-Tyrosine) and L-Trp (L- Tryptophan combination)；
Combination six：The group of hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid) and inosine (Inosine) Close；
Combination seven：S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O- Sulfogalactosylceramide (d18:1/20:0) with galactosylceramide Lactosylceramide (d18:1/22: 0) combination.
9. diagnostic marker according to claim 1 and 2, it is characterized in that：TYR (L-Tyrosine) and L- color ammonia Sour (L-Tryptophan) and phenylalanine/tyrosine and tryptophan metabolism (Phenylalanine, tyrosine and Tryptophan biosynthesis) metabolic pathway is closely related；Glycocholic acid (Glycocholic Acid) and taurocholate Salt (Taurocholate) is close with primary bile acid synthesis (Primary bile acid biosynthesis) metabolic pathway It is related；Cortisol (Cortisol) and cancer path and choleresis (Pathways in cancer, and Bile Secretion) metabolic pathway is closely related.
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