CN105044361B - A kind of diagnostic marker and its screening technique for being suitable for esophageal squamous cell carcinoma early diagnosis - Google Patents

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

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CN105044361B
CN105044361B CN201510497914.8A CN201510497914A CN105044361B CN 105044361 B CN105044361 B CN 105044361B CN 201510497914 A CN201510497914 A CN 201510497914A CN 105044361 B CN105044361 B CN 105044361B
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cancer
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esophagus
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CN105044361A (en
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王家林
张涛
朱正江
薛付忠
赵德利
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Shandong Institute of Cancer Prevention and Treatment
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    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
    • G01N33/6848—Methods of protein analysis involving mass spectrometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/92—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving lipids, e.g. cholesterol, lipoproteins, or their receptors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N2030/022—Column chromatography characterised by the kind of separation mechanism
    • G01N2030/027—Liquid chromatography

Abstract

The invention discloses a kind of diagnostic marker and its screening technique for being suitable for esophageal squamous cell carcinoma early diagnosis, present invention finds 25 kinds of blood serum metabolic labels and 10 associated metabolic pathways.The diagnostic marker of esophagus cancer diagnosis is available for by the combination of this 25 kinds of blood serum metabolic labels.Diagnostic marker screening technique of the present invention is workable, and diagnostic model can be built using diagnostic marker, and the 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.The diagnostic model built using diagnostic marker of the present invention, only by taking blood to can be achieved with diagnosis, noninvasive, cost is low, it can be good at substituting invasive diagnostic mode interior now, significantly reduce the pain of patient, and present invention diagnosis is quick, convenient, required time is short, operating efficiency is improved, is conducive to early discovery, the early treatment of the 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 and its screening Method
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, the diagnostic model built based on the diagnostic marker, 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, 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, which 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 Life or the influence of eating habit (are fed containing the more food of nitrosamines, such as like pickling sauerkraut or the food that goes mouldy, long-term happiness 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 body vital movement, the material base of 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 It will play a significant role, while the screening and early diagnosis for complex disease provide brand-new technical method.
It is related functional gene first caused by polygenes and environmental factor interaction that the generation development of the cancer of the esophagus, which is, Expression change or be mutated, followed by a series of cellular signal transductions and protein synthesis change, finally with environmental factor Interaction is lower to cause metabolite to change.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 (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 Biome d Life Sci,2009,877(27):3111-7.), (Zhang J, the Bowers J, Liu such as Zhang L,et al.Esoph ageal cancer metabolite biomarkers detected by LC-MS and NMR methods.PLoS O ne,2012,7(1):E30181.), (Xu J, Chen Y, Zhang R, the et al.Global such as Xu and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers.Mol Cell Proteomics,2013,12 (5):1306-18.) all the cancer of the esophagus is studied using metabonomic technology.
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 a variety of metabolins It 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 studies the metabolic characteristics for disclosing pre-diabetic, and confirms aliphatic acid, tryptophan, uric acid, courage The metabolism change of juice acid etc., which betides disease, to be occurred before clinical symptoms in a very long time, is examination, the morning of metabolic disease Phase, which diagnoses and intervened, 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 seldom include early stage cancer of the esophagus case.Late esophagus cancer has occurred lymph node and turned at a distance 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, is only capable of preferably examining according to the difference of these metabolic profiles Break and late esophagus cancer, and can not 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, above-mentioned cancer of the esophagus metabolism group research 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).In addition, 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 Area AUC under the sensitivity of examination/diagnosis of esophageal cancer of the metabolin of part and unreported screening, specificity and ROC curve Value.
A series of researchs have been carried out for the cancer of the esophagus in inventor's early stage, can using the technical research of metabolism group The metabonomic analysis model of cancer of the esophagus early screening is carried out, the technology is found 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 the artificial observation pair with health or surface health of district occurred frequently 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 using patient or suspicious patient as sight to diagnose 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, which will be given, treats (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
It is complicated, expensive, invasive for the diagnostic operation of esophageal squamous cell carcinoma in the prior art (the abbreviation cancer of the esophagus) 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 this 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 diagnostic method 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 is convenient and swift only by taking blood with regard to that can be diagnosed, 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 examine 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 determining that (such as hyperthyroidism, first subtract, hypertension and sugar without any esophageal lesion and other metabolic diseases Urinate disease, nephrosis etc.) healthy population be normal healthy controls, use the metabolism of UPLC-QTOF/MS 1466 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, carry out model construction 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, can especially be diagnosed to be 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 refers to 0 phase in TNM stage standard, refers 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, refers to no 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 outer membrane or outer membrane, 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)。
The diagnostic marker and diagnostic model of the present invention 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 improved, 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 the particular technique side of the present 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 (OleicAcid), 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), cortisol (Cortisol), TYR (L- ), Tyrosine L-Trp (L-Tryptophan), glycocholic acid (GlycocholicAcid), taurocholate (Taurocholate), hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid), inosine (Inosine), 1- Phosphoric acid sphingol (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 blood serum metabolic label in following (a)-(h) Combination：(a) can for beta- alanine-lysines (beta-Ala-Lys) and L-Carnosine (L-Carnosine) combination； (b) or for POA (cis-9-Palmitoleic acid), palmitic acid (Palmitic acid) and oleic acid The combination of (Oleic Acid)；(c) or for 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 for nicotinamide adenine two The combination of nucleotides (NADH), TYR (L-Tyrosine) and L-Trp (L-Tryptophan)；(f) or for 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 two or more in following 15 kinds of blood serum metabolic labels 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 (NA DH), cortisol (Cortisol), L-Trp (L-Tryptophan), taurocholate (Taurocholate), hypoxanthine (Hypo xanthine), inosine (Inosine), sulfogalactosylceramide 3- O-Sulfogalactosylceramide(d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/22: 0)。
Further, above-mentioned diagnostic marker can be two or more in following 7 kinds of blood serum metabolic labels 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 two or more in following 5 kinds of blood serum metabolic labels Combination：TYR (L-Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid), taurocholate (T aurocholate) and cortisol (Cortisol).
It is preferred that, above-mentioned diagnostic marker for 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 it 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 (Inosin e), S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O-Sulfogalactos ylceramide (d18:1/20:0) and Galactosylceramide Lactosylceramide (d18:1/22:0).
It is preferred that, above-mentioned diagnostic marker for 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)).
It is preferred that, above-mentioned diagnostic marker for 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 a variety of 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 and 10 kinds of metabolic pathways are closely related.Wherein, Beta- 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 acid), palmitic acid (Palmitic acid) and oleic acid (OleicAcid) this 3 kinds of blood serum metabolic labels (Fatty acid biosynthesis) metabolic pathway is synthesized with aliphatic acid closely related；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) this 4 kinds of blood serum metabolic labels and glycerophosphatide metabolism (Glycerophospholipid 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 kinds of blood serum metabolics Label and glycerophosphatide metabolism (Glycerophospholipid metabolism) and linoleic acid metabolism (Linoleic Acid metabolism) both metabolic pathways are closely related；NADH (NADH) and oxidative phosphorylation (Oxidative phosphorylation) metabolic pathway is closely related；TYR (L-Tyrosine) and L-Trp (L- Tryptophan) this 2 kinds of blood serum metabolic labels and phenylalanine/tyrosine and tryptophan metabolism (Phenylalanine, Tyrosine and tryptophan biosynthesis) metabolic pathway is closely related；Glycocholic acid (GlycocholicAcid) closed with this 2 kinds of blood serum metabolic labels of taurocholate (Taurocholate) with primary bile acid It is closely related into (Primary bile acid biosynthesis) metabolic pathway；Cortisol (Cortisol) and cancer path It is closely related with choleresis (Pathways in cancer, and Bile secretion) metabolic pathway；Hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid) and this 3 kinds of blood serum metabolic labels of inosine (Inosine) and purine It is metabolized (Purine metabolism) metabolic pathway closely related；S1P (Sphingosine 1- Phosphate), sulfogalactosylceramide 3-O-Sulfogalactosylceramide (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, analysis sample, wherein esophagus squameous is used as 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 the original generation of esophageal squamous cell carcinoma serum sample and healthy serum sample Thank to finger-print and carry out collection of illustrative plates pretreatment respectively, obtain every behavioural analysis sample, be 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 subjected to principal component analysis and partial least squares discriminant analysis successively, obtains PLS- D A models, the PLS-DA models show that patients with esophageal squamous cell and healthy population have metabolic patterns difference and obvious point Class trend；
(5) according to PLS-DA models obtained above, scored and univariate by the PLS-DA variable importances modeled Non-parametric test carries out difference metabolin screening, and screening criteria is：VIP >=1, and through False discovery rate FDR multiple testing adjustment 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, 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, matched with existing n-compound, obtain 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 disease (such as hyperthyroidisms, first Subtract, hypertension and diabetes, nephrosis 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 pre-process is carried out before the analysis sample and Quality control samples sample introduction：
(1) 50 μ l analysis samples or Quality control samples are extracted with pipettor, is placed in the automatic sample processing systems of Bravo On 96 orifice plates；
(2) 150 μ l methanol are added to extract, vortex 30s, and hatched at -20 DEG C with protein precipitation；
(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, be 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 and is referred to：Use Masshunter softwares The original Metabolic fingerprinting of acquisition is converted into MZdata data files, MZdata data files are then used into XCMS softwares Bag carries out including retention time correction, peak identification, peak match and the pretreatment operation of 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 at peak, adduct and fragment ion.
In above-mentioned screening technique, when being analyzed using LC-MS blood serum metabolic omics technologies each analysis sample, liquid phase Chromatographic column used in chromatogram is WatersACQUITYUPLC HSS T3 chromatographic columns, and specification is 100mm × 2.1mm, 1.8 μm；Sample introduction Measure as 6 μ L, 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 that the A under 0.1wt% aqueous formic acids, anion ESI- models is 0.5mmol/L ammonium fluoride aqueous solutions, cation B under ESI+ patterns is that the B under the acetonitrile solution of 0.1wt% formic acid, anion ESI- models is pure acetonitrile；Chromatogram gradient elution Condition is：0-1min is 1%B, and 1-8min is that 1%B-100%B is gradually incremented by, and 10-10.1min is that 100%B is kept to rapidly 1% B, then 1%B continue 1.9min.
In above-mentioned screening technique, when being analyzed using LC-MS blood serum metabolic omics technologies 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 For 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 Enclose for 50~1200m/z, the scan frequency of collection is 0.25s.
In the preferred scheme of the present 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 the preferred scheme of the present 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, analysis sample, wherein esophagus squameous is used as 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 in advance to locate Reason, obtains every behavioural analysis sample, is often classified as the two-dimensional matrix of metabolin information, 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 refers to 0 phase in TNM stage standard, refers in mucous epithelium layer or skin The holostrome of epithelium is involved in the intraepidermal atypical hyperplasia of skin (severe), 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 no lymph node involvement, being confined to after mucous membrane 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 outer membrane or outside 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 the preferred scheme of the present invention, when building Random Forest model, modeling parameters ntree=5000.
During model construction, built based on following number of samples in the preferred scheme of the present 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 the preferred scheme of the present 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 diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis (is examined for the combination of 7 kinds of blood serum metabolic labels 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 The diagnostic marker of cancer early diagnosis for 5 kinds of blood serum metabolic labels combination (diagnostic marker C) when, the diagnostic model of gained Diagnosis dividing value (Threshold) be 0.4943.When the prediction numerical value that diagnostic model is provided 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 obtained.Ibid, in preferred scheme of the present invention, when the diagnosis mark used in diagnostic model When remembering thing for 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 subjected to 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, the number provided according to model The diagnosis dividing value (Threshold) of value and model, determines whether early stage esophageal squamous cell carcinoma.
In the preferred scheme of the present invention, when being suitable with the combination (diagnostic marker A) of 25 kinds of blood serum metabolic labels When the diagnostic marker that esophageal squamous cell carcinoma is early diagnosed, when the numerical value that diagnostic model is provided is more than or equal to 0.3552, The cancer of the esophagus is diagnosed as, otherwise not to be；When with the combination (diagnostic marker B) of 7 kinds of blood serum metabolic labels to be suitable for oesophagus During the diagnostic marker of squamous cell carcinoma early diagnosis, when the numerical value that diagnostic model is provided 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 the combination (diagnostic marker C) of 5 kinds of blood serum metabolic labels 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 is only by taking blood to can be achieved with diagnosis, nothing 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.
Fig. 3 A are the three-dimensional shot charts of PLS-DA that the metabolic profile of the cancer of the esophagus and normal healthy controls compares, the R2X=of modeling 0.167, R2Y=0.569, Q2Y=0.523；Fig. 3 B are the corresponding PLS-DA modeling proof diagrams based on random permutation method.Its Middle Normal is healthy serum sample, and ESCC is cancer of the esophagus serum sample.
The identity process figure of Fig. 4 L-Trps (L-Tryptophan), wherein figure (a)：M/z is 205.0974 chromatogram Retention time feature in figure；Scheme (b)：Retention time is 181.38s first mass spectrometric figure；Scheme (c)：Retention time is 181.38s, M/z is 205.0974 secondary ion MS/MS fragmentation patterns；Scheme (d)：Metabolin (RT：181.38s, m/z：205.0974) it is broken Piece cracks mechanism.
The ROC curve figure of the external testing sample of Random Forest model constructed by 25 metabolic marker things of Fig. 5.
The external testing sample ROC of random forest early stage esophagus cancer diagnosis model constructed by 7 metabolic marker things of Fig. 6 Curve.
The external testing sample ROC of random forest early stage esophagus cancer diagnosis model constructed by 5 metabolic marker things of Fig. 7 Curve.
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) ", For the indicative biopsy object (confirming as goldstandard) 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, LC-MS blood serum metabolic group detection
Preservation in -80 DEG C of refrigerators is put in after the serum sample centrifugation of all collections, is joined using ultra performance liquid chromatography-mass spectrum It is metabolized with instrument (UPLC-QTOF/MS 6550, Agilent) and the automatic Pretreated systems (Agilent, USA) of Bravo Group learns detection (point 3 big batch detection, and carry out quality control), obtains the original generation comprising chromatogram and Information in Mass Spectra of sample Thank to finger-print.Concrete operations are as follows：
2.1 instrument and equipment
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；Bore 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：Methanol (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 every 10 and adds a Quality control samples.By early stage cancer of the esophagus serum sample, oesophagus cancer-serum in situ 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 the biased sample of 5 parts of healthy serum samples.Cancer of the esophagus serum sample, healthy serum sample and Quality control samples carry out pre- Processing, pretreatment includes following 4 steps：
(1) 50 μ l analysis samples or Quality control samples are extracted with pipettor, is placed in the automatic sample processing systems of Bravo On 96 orifice plates of (Agilent, USA)；
(2) 150 μ l methanol are added to extract, vortex 30s, and hatched at -20 DEG C with protein precipitation.
(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, be 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 is brought.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 that 100%B is kept to rapidly 1%B, and then 1%B continues 1.9min.Stream Speed is 0.5ml/min.Whole sample detection process maintains 4 DEG C.Wherein, A and B percentage composition refers to that volume basis contains Amount.
Mass Spectrometer Method uses Agilent quadrupole rod 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 Measure as 12L/min.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 is pre-processed
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 using the XCMS of R language Software kit carry out XCMS collection of illustrative plates pretreatments, pretreatment include retention time correction, peak identification, peak match, peak align, filter make an uproar, again 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-process, included in the data matrix of the UPLC-QTOF/MS spectrum generations of positive ion detection pattern through XCMS collection of illustrative plates 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 of preparation are arranged into 1 QC by every 10 analysis samples Uniformly in the order insertion analysis sample in so that the quality control during monitoring in real time from Sample pretreatment to pattern detection 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 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 between observation group are walked, Fig. 2 is seen.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
Obtained dimensional matrix data is randomly assigned into 4/5 as training sample training data, 1/5 makees in addition For external testing sample test data (being shown in Table 1).For deviation caused by gap in elimination group of trying one's best, more obvious point is obtained 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 PLS-DA variable importances modeled (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 False discovery rate FDR multiple testing adjustment.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 Propylhomoserin RT 181.38s, m/z 205.0974 qualification process, is shown in Fig. 4), carry out the identification of metabolic marker thing：
(1) distribution characteristics is cracked according to the first mass spectrometric of 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 the matching of second order mses figure fragment ion is carried out with compound candidate in database； The chromatogram and mass spectral characteristic for comparing compound standard sample library carry 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, the common name (Common Name) of this 25 serum size labels is respectively：beta-Ala-Lys；L- Carnosine；cis-9-Palmitoleic acid；Palmitic acid；OleicAcid；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；GlycocholicAcid；Taurocholate； Hypoxanthine；Allantoic acid；Inosine；Sphingosine 1-phosphate；3-O- Sulfogalactosylceramide(d18:1/20:0)；Lactosylceramide(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 to find, this is of great significance for diagnosis, the treatment of the early stage cancer of the esophagus.Wherein, beta-Ala-Lys Chinese is translated Entitled b eta- alanine-lysines, L-Carnosine Chinese translation is L-Carnosine, cis-9-Palmitoleic Acid Chinese translation is POA, and Palmitic acid Chinese translation is palmitic acid, Oleic Acid's Chinese translation is oleic acid, and LP A Chinese translation is lysophosphatidic acid, during LysoPC Chinese translation is lysolecithin, PC Literary translated name is phosphatide, and Li noleic acid Chinese translation is linoleic acid, and NADH Chinese translation is nicotinamide adenine two Nucleotides, Cortisol Chinese translation is cortisol, and L-Tyrosine Chinese translation is TYR, L-Tryptophan Chinese translation be L-Trp, Glycocholic Acid Chinese translation is glycocholic acid, Taurocholate Chinese Translated name is taurocholate, and Hy poxanthine Chinese translation is hypoxanthine, and Allantoic acid Chinese translation is Allantoic acid, Inosine Chinese translation is inosine, and Sphingosine 1-phosphate Chinese translation is 1- phosphoric acid sheath ammonia Alcohol, 3-O-Sulfogalactosylcer amide Chinese translation is sulfogalactosylceramide, Lactosylceramide Chinese translation is galactosylceramide, and each Chinese translation there may be deviation because of translation, with English Standard name is defined.
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
In addition, being enriched with (enrichment) and metabolic pathway (pathway) analysis by KEGG, above-mentioned 25 serum is found Metabolic marker thing and following 10 metabolic pathways are closely related：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 Be acidified (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 It is metabolized (Purine metabolism), sphingolipid metabolism (Sphingolipid metabolism).This proves Incidence of Esophageal Cancer This 10 metabolic pathways are disturbed 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 believed to screen difference of the 25 obtained blood serum metabolic labels 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), 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 (GlycocholicAcid), allantoic acid (Allantoic acid), inosine (Inosine) and S1P (Sphingosine1-phosphate) it is significantly raised compared to health group expression quantity in cancer of the esophagus group, and other metabolic markers Thing is substantially reduced in cancer of the esophagus group compared to health group expression quantity.
FDR is the False discovery rate corrected based on 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 for 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 of note 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 It can be two or more the combination in following blood serum metabolic labels to remember thing：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-Tryptophan), taurocholate (Taurocholate), hypoxanthine (Hypoxanthine), inosine (Inosine), sulfogalactosylceramide 3-O- Sulfogalactosylceramide(d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/22:0).
It is also an option that two or more the combination in the good following blood serum metabolic labels of AUC effects：Haemolysis Phosphatidic 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)).
It is also an option that two or more the combination in the good following blood serum metabolic labels of AUC effects：L- junket Propylhomoserin (L-Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (GlycocholicAcid), taurocholate And cortisol (Cortisol) (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, the further application effect of 3 kinds of preferred diagnostic markers of the invention is itemized, other diagnostic markers Applicable cases will not enumerate herein.
8th, cancer of the esophagus early diagnosis model and external certificate
8.1 using the combination of 25 blood serum metabolic labels 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 outside data (out-of-bag, OOB)；
(2) it is provided with mallIndividual variable, then randomly select m at each node of every one treetryIndividual variable (mtry＜ ＜ mall), then in mtryThe variable of middle selection one most classification capacity, the threshold value of variable classification is by checking that each is classified Point is determined；
(3) each classification tree in random forest is binary tree, and it, which is generated, follows top-down recurrence division principle, Training set is divided successively since root node.Each tree is grown to greatest extent, and any trimming is not done.
(4) many classification trees of generation are constituted into random forest, new data differentiated with random forest grader With classification, classification results by 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 built 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 more than or equal to diagnosis dividing value, then are determined as that diagnosis is positive (suffering from esophageal squamous cell carcinoma), If less than diagnosis dividing value, being determined as 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 table 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, imitated for evaluating diagnosis of the diagnostic model to the different cancer of the esophagus by stages Really.Random Forest model see the table below for area AUC under the sensitivity of the different cancer of the esophagus by stages, specificity and ROC curve 4, as can be seen from the table：With the further deterioration of the cancer of the esophagus, AUC and specificity, which have, increases 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 obtained blood serum metabolic label 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 suffers from the cancer of the esophagus, and It is not only good to the diagnosis effect of late esophagus cancer, for the degree of accuracy, sensitivity and specificity of 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 Morning discovery, early treatment in the cancer of the esophagus, have good help 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：
Obtained dimensional matrix data is randomly assigned into 4/5 as training sample training data, 1/5 makees in addition For external testing sample test data (being shown in Table 1).Only with lysophosphatidic acid LPA (18:1(9Z)/0:0), lysolecithin Lyso PC(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 Fores t) builds cancer of the esophagus early diagnosis model.Random forest uses randomForest software kits in R language Realize, modeling parameters ntree=5000, random forest modeling procedure is ibid.
When being diagnosed using the stochastic model of structure, 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 more than or equal to diagnosis dividing value, is determined as diagnosis Positive (suffering from esophageal squamous cell carcinoma), if less than diagnosis dividing value, being determined as 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 table 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, imitated for evaluating diagnosis of the diagnostic model to the different cancer of the esophagus by stages Really.Random Forest model see the table below for area AUC under the sensitivity of the different cancer of the esophagus by stages, specificity and ROC curve 5, as can be seen from the table：With the further deterioration of the cancer of the esophagus, AUC and sensitivity, which 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 obtained blood serum metabolic label in the early stage cancer of the esophagus even carcinoma in situ Just there are metabolic alterations in stage.
It can be seen from the data in table the diagnostic model of 7 blood serum metabolic label information architectures 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 to suffer from the cancer of the esophagus, it is and not only good to the diagnosis effect of late esophagus cancer, for the early stage cancer of the esophagus and carcinoma in situ The degree of accuracy, sensitivity and specificity are also preferable, 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, prognosis, reduction oesophagus for improving the cancer of the esophagus The death rate of cancer has good help, 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：
Obtained dimensional matrix data is randomly assigned into 4/5 as training sample training data, 1/5 makees in addition For 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 uses randomForest software kits in R language to realize, modeling Parameter ntree=5000, random forest modeling procedure is ibid.
When being diagnosed using the stochastic model of structure, 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 more than or equal to diagnosis dividing value, is determined as diagnosis Positive (suffering from esophageal squamous cell carcinoma), if less than diagnosis dividing value, being determined as 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 table 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, imitated for evaluating diagnosis of the diagnostic model to the different cancer of the esophagus by stages Really.Random Forest model see the table below for area AUC under the sensitivity of the different cancer of the esophagus by stages, specificity and ROC curve 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.
It can be seen from the data in table the diagnostic model of 5 blood serum metabolic label information architectures 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 being diagnosed to be suffers from the cancer of the esophagus, and not only good to the diagnosis effect of late esophagus cancer, for the early stage cancer of the esophagus and original The position degree of accuracy of cancer, sensitivity and specificity are also preferable, 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, prognosis, drop for improving the cancer of the esophagus The death rate of the low cancer of the esophagus has good help, 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 Upper diagnostic marker and diagnostic model using the present invention carries out the diagnosis of the cancer of the esophagus, and step is as follows：
(1) serum to be checked is gathered, uses step (1)-(4) in above-mentioned 2.2 to pre-process serum 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 subjected to 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, the numerical value and model provided according to model Diagnosis dividing value (Threshold), determine whether esophageal squamous cell carcinoma.When the numerical value that model is provided is more than or equal to diagnosis circle During value, it is determined as that diagnosis is positive (suffering from esophageal squamous cell carcinoma), if less than diagnosis dividing value, being determined as 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 gathered simultaneously, and be numbered, by multiple samples This disposable LC-MS detections, collection of illustrative plates pretreatment, metabolic peak mark, the screening of diagnostic marker two-dimensional matrix and data of carrying out is imported.
In actual applications, more samples can be chosen according to modeling method of the present invention to be modeled, increase model The degree of accuracy.It is above non-limiting to the description of patent of the present invention, based on the other embodiment of patent thought of the present invention, exists Among the scope of the present invention.

Claims (14)

1. a kind of diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis, it is characterized in that including：
Blood serum metabolic label A：Phosphatide PC (14:1(9Z)/P-18:1 (11Z)), and
Blood serum metabolic label B：Phosphatide PC (24:1(15Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z)).
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 of the label C in 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 (16:0/18:2 (9Z, 12Z)), 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 (Allantoic acid), Inosine (Inosine), S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3- O-Sulfogalactosylceramide (d18:1/20:0), galactosylceramide Lactosylceramide (d18:1/ 22:0)。
3. diagnostic marker according to claim 2, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more of the label C in 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 (16:0/18:2 (9Z, 12Z)), NADH (NADH), cortisol (Cortisol), L- colors Propylhomoserin (L-Tryptophan), taurocholate (Taurocholate), hypoxanthine (Hypoxanthine), inosine (Inosine), sulfogalactosylceramide 3-O-Sulfogalactosylceramide (d18:1/20:0), lactose Ceramide Lactosylceramide (d18:1/22:0).
4. diagnostic marker according to claim 3, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to one or more of the label C in following blood serum metabolic label：Lysolecithin LysoPC (18:2(9Z,12Z))、 Lysolecithin LysoPC (24:0), NADH (NADH), cortisol (Cortisol), taurocholate (Taurocholate), 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 of the label C in following blood serum metabolic label：Lysolecithin LysoPC (18:2(9Z,12Z))、 Lysolecithin LysoPC (24:0), taurocholate (Taurocholate), galactosylceramide Lactosylceramide (d18:1/22:0)。
6. 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 of the label C in 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 (16:0/18:2(9Z,12Z)).
7. 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 of the label C in 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 (16:0/18:2 (9Z, 12Z)) and linoleic acid (Linoleic acid) combination；
Combination five：NADH (NADH), TYR (L-Tyrosine) and L-Trp (L- Tryptophan combination)；
Combination six：Cortisol (Cortisol), glycocholic acid (Glycocholic Acid) and taurocholate (Taurocholate) combination；
Combination seven：The group of hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid) and inosine (Inosine) Close；
Combination eight：S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O- Sulfogalactosylceramide (d18:1/20:0) with galactosylceramide Lactosylceramide (d18:1/22: 0) combination.
8. diagnostic marker according to claim 1, it is characterized in that：Also include blood serum metabolic label C, the serum generation Thank to the combination that label C is following 23 kinds of blood serum metabolic labels：It is beta- alanine-lysines (beta-Ala-Lys), left-handed 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 (16:0/18:2(9Z, 12Z)), linoleic acid (Linoleic acid), NADH (NADH), cortisol (Cortisol), L- junket Propylhomoserin (L-Tyrosine), L-Trp (L-Tryptophan), glycocholic acid (Glycocholic Acid), taurocholate (Taurocholate), hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid), inosine (Inosine), 1- Phosphoric acid sphingol (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O- Sulfogalactosylceramide (d18:1/20:0) with galactosylceramide Lactosylceramide (d18:1/22: 0)。
9. diagnostic marker according to claim 7, it is characterized in that：Beta- alanine-lysines (beta-Ala-Lys) It is close with L-Carnosine (L-Carnosine) and beta alanine metabolism (beta-Alanine metabolism) metabolic pathway It is related；
POA (cis-9-Palmitoleic acid), palmitic acid (Palmitic acid) and oleic acid It is closely related that (Oleic Acid) synthesizes (Fatty acid biosynthesis) metabolic pathway with aliphatic acid；
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) it is 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) and glycerophosphatide metabolism (Glycerophospholipid metabolism) and linoleic acid metabolism (Linoleic acid metabolism) both Metabolic pathway is closely related；
NADH (NADH) and oxidative phosphorylation (Oxidative phosphorylation) metabolic pathway It is closely related；
TYR (L-Tyrosine) and L-Trp (L-Tryptophan) and phenylalanine/tyrosine and tryptophan It is metabolized (Phenylalanine, tyrosine and tryptophan biosynthesis) metabolic pathway closely related；
Glycocholic acid (Glycocholic Acid) and taurocholate (Taurocholate) are synthesized with primary bile acid (Primary bile acid biosynthesis) metabolic pathway is closely related；
Cortisol (Cortisol) and cancer path and choleresis (Pathways in cancer, and Bile Secretion) metabolic pathway is closely related；
Hypoxanthine (Hypoxanthine), allantoic acid (Allantoic acid) and inosine (Inosine) and purine metabolism (Purine metabolism) metabolic pathway is closely related；
S1P (Sphingosine 1-phosphate), sulfogalactosylceramide 3-O- Sulfogalactosylceramide (d18:1/20:0) with galactosylceramide Lactosylceramide (d18:1/22: 0) it is closely related with sphingolipid metabolism (Sphingolipid metabolism) metabolic pathway.
10. the diagnostic marker for being suitable for esophageal squamous cell carcinoma early diagnosis any one of a kind of claim 1-9 Screening technique, it is characterized in that, comprise the following steps：
（1）Patients with esophageal squamous cell and healthy population serum sample are collected, analysis sample, wherein esophageal squamous cell is used as 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, the original metabolism of each serum sample is obtained Finger-print；
（3）The original metabolism of esophageal squamous cell carcinoma serum sample and healthy serum sample is referred to using R language XCMS software kits Line collection of illustrative plates 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 uses R software kits CAMERA carries out metabolin peak mark to two-dimensional matrix, for further statistical analysis；
（4）By step（3）Two-dimensional matrix carry out principal component analysis and partial least squares discriminant analysis successively, obtain PLS-DA moulds Type, the PLS-DA models show that patients with esophageal squamous cell and healthy population have metabolic patterns difference and obvious classification to become Gesture；
（5）According to PLS-DA models obtained above, by the PLS-DA variable importance scorings modeled and univariate non-ginseng Number, which is examined, carries out difference metabolin screening, and screening criteria is：VIP >=1, and the q values after False discovery rate FDR multiple testing adjustment Less than 0.05；
（6）The difference metabolin that above-mentioned screening is obtained according to the CAMERA bags of R language determine difference metabolin quasi-molecule from Son, adduct and Isotope Information, obtain potential metabolic marker thing；
（7）On the basis of above-mentioned potential metabolic marker thing, with reference to the one-level, second order mses information, standard of potential metabolic marker thing Molecular ion information, adduct information and Isotope Information, thus it is speculated that the molecular mass and molecular formula of diagnostic marker, and with it is existing N-compound contrasted, matched, obtain being suitable for the diagnostic marker of esophageal squamous cell carcinoma early diagnosis.
11. screening technique according to claim 10, it is characterized in that：When carrying out the analysis of LC-MS blood serum metabolics omics technology, Every 10 analyses sample adds a Quality control samples, for Real Time Monitoring sample from sample introduction pre-treatment to analysis process In quality control situation, the Quality control samples are the aggregate sample of the healthy serum samples of 5 parts of cancer of the esophagus serum samples and 5 parts Product.
12. screening technique according to claim 10, it is characterized in that：Before the analysis sample and Quality control samples sample introduction Carry out following pre-process：
（1）50 μ l analysis samples or Quality control samples are extracted with pipettor, 96 holes of the automatic sample processing systems of Bravo are placed in On plate；
（2）The extraction of 150 μ l methanol, vortex 30s are added, and is hatched at -20 DEG C with protein precipitation；
（3）Then 20min are centrifuged with 4000 revs/min at 4 DEG C in supercentrifuge；
（4）By step（3）Supernatant pour into LC-MS sample injection bottles, be stored at -80 DEG C in case LC-MS detect.
13. screening technique according to claim 10, it is characterized in that：Collection of illustrative plates pretreatment is carried out to original Metabolic fingerprinting Refer to：The original Metabolic fingerprinting of acquisition is converted into MZdata data files with Masshunter softwares, then will Mzdata data files carry out including the pre- place that retention time correction, peak are recognized, peak match and peak align using XCMS software kits Reason operation, obtains two-dimensional matrix；Using R software kits CAMERA two-dimensional matrix is carried out metabolin peak mark include isotopic peak, The metabolin peak mark of adduct and fragment ion.
14. screening technique according to claim 10, it is characterized in that：LC-MS blood serum metabolics are used to each analysis sample When omics technology is analyzed, chromatographic column used in liquid chromatogram is Waters ACQUITY UPLC HSS T3 chromatographic columns, specification For the mm of 100 mm × 2.1,1.8 μm;Sample size is 6 μ L, and injector temperature is 4 DEG C, and flow velocity is 0.5 ml/min；Chromatogram flows Mutually include two kinds of solvent orange 2 As and B：A under cation ESI+ patterns is the A under 0.1wt% aqueous formic acids, anion ESI- models For 0.5mmol/L ammonium fluoride aqueous solutions, the B under cation ESI+ patterns is the acetonitrile solution of 0.1wt% formic acid, anion ESI- B under model is pure acetonitrile；Chromatogram condition of gradient elution is：0-1min is 1%B, and 1-8min is that 1%B-100%B is gradually incremented by, 10-10.1min is that 100%B is kept to rapidly 1%B, and then 1%B continues 1.9min；
Mass Spectrometer Method uses quadrupole rod time-of-flight mass spectrometry instrument Q-TOF, and using the positive ion mode ESI+ of electric spray ion source With negative ion mode ESI-, ion source temperature is 400 DEG C, and taper hole throughput is 12L/min, and desolventizing temperature is 250 DEG C, precipitation Agent throughput is 16L/min；Capillary voltage is respectively+3kV and -3kV under cation and negative ion mode, and taper hole voltage is equal For 0V；Positive ion mode lower cone hole pressure is 20psi, and negative ion mode lower cone hole pressure is 40psi；The matter of spectrum data collection Lotus is 50~1200 m/z than scope, and the scan frequency of collection is 0.25s.
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