CN107942074A - It is a kind of to establish liver cancer and normal person's diagnostic model and the diagnostic model of liver cancer and chronic liver disease - Google Patents
It is a kind of to establish liver cancer and normal person's diagnostic model and the diagnostic model of liver cancer and chronic liver disease Download PDFInfo
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Abstract
Liver cancer and normal person's diagnostic model and the diagnostic model of liver cancer and chronic liver disease are established the invention discloses a kind of, using SELDI-TOF-MS technologies, establishes liver cancer and normal person's diagnostic model and the diagnostic model of liver cancer and chronic liver disease；It has collected 48 liver cancer patients, 17 patients with chronic liver, 33 Healthy Human Serums；The effective tumor markers of present invention searching is detected to sample using SELDI TOF technologies to be of great significance for Carcinogenesis Mechanism research, the early diagnosis of disease and Index for diagnosis.Influence to tumor biological behavior after the expression of observation candidate gene is blocked or raises, orients the key protein of influence human liver cancer occurrence and development；By bioinformatic analysis, effect of these key proteins in system signal network is parsed；Verified again with MRM absolute quantitations, assess these liver cancer key protein Polypeptide Diagnostic liver cancer value and analysis and clinical correlation, propose their feasibilities in terms of the clinical practices such as the prevention, early diagnosis and Index for diagnosis of liver cancer.
Description
Technical field
Liver cancer is established the present invention relates to genetic transcription group and proteomics field, especially one kind to diagnose with normal person
The diagnostic model of model and liver cancer and chronic liver disease.
Background technology
20th century, primary carcinoma of liver had gone up as China second cancer killer, was only second to lung cancer in city, in rural area then
It is only second to stomach cancer[1].Guangxi has 3.5 ten thousand people or so to die of malignant tumour every year at present, wherein, that dies of liver cancer has a 1.2 ten thousand people left side
It is right, it is seen then that liver cancer is first, Guangxi cancer killer.In the range of Guangxi, liver cancer Harm is very unbalanced.Mortality of liver cancer
Higher county, city, focus primarily upon Southwest Guangxi area, the most occurred frequently with the Fusui on Nanning periphery, Longan, three county of Wuming, this
Density occurs for the liver cancer in some areas, reaches 50~60/,100,000, indivedual administrative villages therein, liver cancer occurs density and is up to 140 unexpectedly
~160,/10 ten thousand, such liver cancer incidence is also rare in the world.Not only incidence is high but also the death rate is also high for liver cancer,
It is " king of cancer " that the death rate of Guangxi Hepatocellular has increased to 27.31/10 ten thousand, accounts for whole mortality of malignant tumors
34.12%.Due to primary carcinoma of liver early stage generally without any symptom, once there is clinical manifestation, the state of an illness have been enter into mostly in, evening
Phase, and grade malignancy height, the fast, poor prognosis that is in progress, invasion are strong, therefore, find effective tumor markers and are used for canceration machine
Managing research, the design of drug targets, the early diagnosis of disease and the examination of people at highest risk becomes working as Guangxi province liver cancer research
Business is anxious.
At present, liver cancer discovery and diagnosis be by Serum AFP detection combine imageological examination.It is wherein clinical more to generally acknowledge
Diagnosing cancer of liver standard be：Serum concentration of AFP>400 μ g/L, for 4 weeks, iconography finds that liver has Solid lesion and can arrange
Except diseases such as hepatitis activity, reproduction embryonal tumors.But only rely on serum concentration of AFP and carry out diagnosing liver cancer, sensitivity is 39% ~ 64%
Between, specificity is 76% ~ 91%, and for positive predictive value only 9%~32%, this allows for many liver cancer patient missing inspections, or false positive
And false negative, directly affect the early diagnosis and therapy of liver cancer patient.
With the fast development of biotechnology and the completion of the Human Genome Project (HGP) genome sequencing, Ren Leijin
The genome times afterwards comprehensively are entered, the research of wherein proteomics has been to be concerned by more and more people.With proteomic techniques come
Detection, analysis and definite marker protein and target protein, the change for illustrating oncoprotein expression are different from tumor development
The correlation and its rule in stage, are the current best approach for solving early diagnosis of tumor problem；Meanwhile and tumour
And its newest and most strong means in drug screening research.
Mass-spectrometric technique is that the core of specific tumour marker is screened, identified in proteomic techniques, and common is surface
Strengthen laser desorption/ionization time of flight mass mass-spectrometric technique（surface-enhanced laserdesorption/
Inionation-time of flightmass spectrometry, SELDI-TOF-MS）With substance assistant laser desorpted electricity
From flight time mass spectrum（Matrix-Assisted Laser Desorption/ Ionization Time of Flight
Mass Spectrometry, MALDI-TOF-MS）.This seminar once utilizes SELDI-TOF-MS combination LC-MS HPLC/
MALDI-TOF-MS technologies analyze the blood serum sample of the relevant liver cancer of hepatitis B, chronic benign hepatopathy, normal person, obtain people
The specific serum marker NAP2 of class hepatitis B associated hepatocellular carcinoma（71）And NAP2（73）.There is similar detection using to SELDI
Principle but the preferable CLINPROT systems of repeatability, it is obvious in two groups of blood serum samples of liver cancer and normal person to screen two differences
Protein and peptide, one is accredited as from fibrinogen（Fibrinogen）A secretory piece, fibrinopeptide A
（Fibrinopeptide A）, this is completely the same with the result of Eduard etc.；Another peptide identification is kininogen
（Kininogen）.And the iTRAQ of new development over the past two years（isobaric tags for relative and absolute
Quantification, iTRAQ）Mark combines MALDI-TOF MS/MSF technologies, establishes in iTRAQ isotope labeling reagents
On the basis of, an including electrically charged reporter group, in addition an also peptide fragment reactive group and a balance group, wherein flat
Weigh group balance molecule amount, and it is all 145 that guarantee, which is combined the total relative molecular weight of rear iTRAQ reagents with each reporter gene, peptide
Section reactive group can measure E amino groups with the N-terminal and lysine of peptide fragment and react, and can so mark biological sample
All peptide fragments of middle generation, strengthen the peptide fragment coverage of any given albumen, while after remaining the translation of such as some albumen
The important feature information of modification, provides quantitative information so that seminar is new in liver cancer for the discovery and identification of disease marker
It is more further strengthened in terms of the screening of marker.
From 2005, liver cancer-specific marker screened through above-mentioned mass-spectrometric technique in this seminar, and a series of of acquirement grind
Study carefully achievement, the discovery and identification of these functional proteins and potential disease protein markers have benefited from Different Proteomics and grind
The development studied carefully, but the gene expression abundance of these protein how is further detected, to illustrate its function and the meaning in disease research
Justice, has become more and more important.At present, the research mode of marker discovery-verification-clinic confirmation has obtained researchers'
It is widely recognized as.Found in discovery phase from disease organism sample and the discrepant protein of normal sample；To Qualify Phase
The label screened is quantified, assesses its accuracy, specificity, scope etc., and the marker being verified is special with clinic
Sign, result are associated；The most possible candidate molecules for becoming biomarker that Qualify Phase is found out, into clinic in next step
Confirmation.This research mode makes the discovery of biomarker in body fluid and verification is more effective, science and rationally.
In above-mentioned research mode, the quantitative technique of target protein is the bridge that marker leads to verification from discovery.Matter
The high sensitivity of spectrum can help people to excavate into biological sample low-abundance protein, polypeptide letter in the discovery phase of marker
Breath, but in the quantitative verification stage, since complex component be total to the interference of effluent and the wide dynamic range up to more than 9 orders of magnitude,
It greatly affected quantitative detection of the mass spectrum to low abundance proteins, polypeptide in biological fluid.Although researchers attempt to use
A variety of methods, including chromatographic isolation as sufficient as possible, remove high-abundance proteins matter etc., but the preci-sion and accuracy of its result
Still far from the requirement for meeting analysis, until mass spectrum multiple-reaction monitoring (multiple reaction monitoring, MRM)
The appearance of technology.M R M technologies apply the advantages of above presenting its method in quantitative proteomics.
M R M technologies are based on Given information or assume information setting Mass Spectrometer Method rule, to legal ion into
Row signal records, and removal is not largely inconsistent the interference of normally ion signal, so as to obtain a kind of data recipient of Information in Mass Spectra
Formula.Specifically, it is according to polypeptide parent ion mass number and fragment ion masses number, selects parent ion-daughter ion pair, permits
The parent ion for being permitted to meet setting enters collision cell, and after the completion of collision, only record sets daughter ion signal.By parent ion and son from
The selection twice of son, removes interfering ion, reduces Chemical Background, improves sensitivity.When carrying out MRM analyses, Modern Mass Spectrometry instrument
Large batch of sample can be monitored by MRM scan patterns, check whether mother-daughter ion of this arrangement to occurring.If letter
Number occur, it was demonstrated that this molecule exists in the sample, and instrument will automatically switch to MS/MS scan patterns, determines the broken of this parent ion
Piece ion information, and identify again and confirm the structure of the molecule.If in MRM scanning works, expected mother/daughter is not found
Ion pair, just illustrates that the molecule is not present in this sample.Since MRM scan patterns are efficiently quick, and there is high sensitivity,
Therefore it is very suitable for high throughput verification and validation biomarker.In addition, the high-throughout feature of MRM technologies, is also more hatching eggs
Condition is quantitatively provided while white matter.M R M technologies are right by being combined with isotope-dilution analysis or m T R A Q technologies
True peptide fragment in internal standard peptide fragment and sample that known quantity adds is marked respectively, selects different mother-daughter ions to obtaining not
Same chromatography detecting signal, compares both signals, so as to produce absolute quantitation result[15].At present, by the blood of MRM quantitative verifications
Clear marker is the best way for avoiding false positive marker.
Therefore, this research is intended sieving seminar with SELDI-TOF-MS protein chips, iTRAQ isotope labelling techniques in advance
The liver cancer-specific protein marker of choosing, it is clear and definite using real-time fluorescence quantitative RT-PCR and immunoblotting analysis Western blot technologies
The expression and positioning of the new protein marker of liver cancer, and goal in research is further selected；Transfected using eucaryon, SiRNA
Perturbation technique observes influence of the new marker of liver cancer to hepatoma cell strain biological characteristics, while using in nude mice lotus knurl model
Its effect in invasion in HCC transfer of experimental observation；By bioinformatic analysis, parse these key proteins and believe in system
Effect in number network；The absolute quantitation that large sample is finally carried out with MRM technologies is verified, assesses these liver cancer key protein polypeptides
Diagnosing liver cancer is worth and analysis and clinical correlation, proposes that they face in prevention, early diagnosis and Index for diagnosis of liver cancer etc.
The feasibility of bed application aspect, this research will be that finally filtering out liver cancer key protein/polypeptide establishes solid foundation.
The content of the invention
Liver cancer and the diagnosis of normal person's diagnostic model and liver cancer and chronic liver disease are established the object of the present invention is to provide a kind of
Model.
It is this to establish liver cancer and normal person's diagnostic model and the diagnostic model of liver cancer and chronic liver disease,
Comprise the steps of：
Using SELDI-TOF-MS technologies, liver cancer and normal person's diagnostic model and the diagnosis mould of liver cancer and chronic liver disease are established
Type；
It has collected 48 liver cancer patients, 17 patients with chronic liver, 33 Healthy Human Serums；Using SELDI-TOF technologies to sample
Originally it is detected, it turns out that：
1. liver cancer group and normal person group detect 126 protein peaks altogether, wherein 65 have in liver cancer with difference that normal person organizes it is aobvious
Write meaning (P<0.05)；There is 21 marker molecules are high to express compared with normal human serum protein spectrum, in In Sera of Patients With Hepatocarcinoma, 44
A marker molecule low expression（As shown in Figure 1）；Using the data of the albumen of 7 in this 65 differential proteins different mass-to-charge ratioes, build
Vertical discrimination model, the sensitivity of its diagnosing liver cancer is 100% (33/33), and specificity is 96.97% (32/33)；Utilize the model
Blind detection, accuracy rate 98.8% (80/81), sensitivity 100% (48/48), specificity 96.97% are carried out to 81 samples
(32/33)；
2. liver cancer group detects 125 protein peaks altogether with chronic liver disease group, wherein 38 difference in liver cancer and chronic liver disease group
Significance (P<0.05)；Compared with chronic liver disease group Serum protein profiling, there are 18 marker molecules in In Sera of Patients With Hepatocarcinoma
Height expression, 20 marker molecule low expressions；Using the data of the albumen of 11 in this 38 differential proteins different mass-to-charge ratioes, establish
Discrimination model, the sensitivity of its diagnosing liver cancer is 93.9% (31/33), and specificity is 94.1% (16/17)；Utilize the model pair
65 samples carry out blind detection, accuracy rate 81.5% (53/65), sensitivity 81.3% (39/48), specificity 82.4% (14/
17)；
3. wherein mass-to-charge ratio is that the albumen of 7789Da expresses highest in liver cancer group（21.66±9.00）, in chronic benign hepatopathy
Expression is taken second place in group（12.99±9.09）, expressed in normal group minimum（8.83±6.78）, the difference between 3 groups has notable meaning
Justice（P<0.01）.
Invention beneficial effect：
The present invention finds effective tumor markers and is used for Carcinogenesis Mechanism research, the early diagnosis of disease and Index for diagnosis with weight
Want meaning.To the new protein marker of liver cancer filtered out, by gene knock-in, knock out that the inside and outside such as to test with transplanted tumor in nude mice real
Test, observe candidate gene expression be blocked or raise after influence to tumor biological behavior, orient influence human liver cancer
The key protein of occurrence and development；By bioinformatic analysis, effect of these key proteins in system signal network is parsed；
Verified again with MRM absolute quantitations, assess these liver cancer key protein Polypeptide Diagnostic liver cancer value and analysis and clinical correlation,
It is proposed their feasibilities in terms of the clinical practices such as the prevention, early diagnosis and Index for diagnosis of liver cancer.
Brief description of the drawings
Fig. 1 is the schematic diagram of the present invention.
The 7789Da albumen of Fig. 1 arrow meanings is expressed liver cancer group is high, and in normal person low expression difference egg
In vain.
Embodiment
Embodiment：
Comprise the steps of：
Using SELDI-TOF-MS technologies, liver cancer and normal person's diagnostic model and the diagnosis mould of liver cancer and chronic liver disease are established
Type；
It has collected 48 liver cancer patients, 17 patients with chronic liver, 33 Healthy Human Serums；Using SELDI-TOF technologies to sample
Originally it is detected, it turns out that：
1. liver cancer group and normal person group detect 126 protein peaks altogether, wherein 65 have in liver cancer with difference that normal person organizes it is aobvious
Write meaning (P<0.05)；There is 21 marker molecules are high to express compared with normal human serum protein spectrum, in In Sera of Patients With Hepatocarcinoma, 44
A marker molecule low expression（As shown in Figure 1）；Using the data of the albumen of 7 in this 65 differential proteins different mass-to-charge ratioes, build
Vertical discrimination model, the sensitivity of its diagnosing liver cancer is 100% (33/33), and specificity is 96.97% (32/33)；Utilize the model
Blind detection, accuracy rate 98.8% (80/81), sensitivity 100% (48/48), specificity 96.97% are carried out to 81 samples
(32/33)；
2. liver cancer group detects 125 protein peaks altogether with chronic liver disease group, wherein 38 difference in liver cancer and chronic liver disease group
Significance (P<0.05)；Compared with chronic liver disease group Serum protein profiling, there are 18 marker molecules in In Sera of Patients With Hepatocarcinoma
Height expression, 20 marker molecule low expressions；Using the data of the albumen of 11 in this 38 differential proteins different mass-to-charge ratioes, establish
Discrimination model, the sensitivity of its diagnosing liver cancer is 93.9% (31/33), and specificity is 94.1% (16/17)；Utilize the model pair
65 samples carry out blind detection, accuracy rate 81.5% (53/65), sensitivity 81.3% (39/48), specificity 82.4% (14/
17)；
3. wherein mass-to-charge ratio is that the albumen of 7789Da expresses highest in liver cancer group（21.66±9.00）, in chronic benign hepatopathy
Expression is taken second place in group（12.99±9.09）, expressed in normal group minimum（8.83±6.78）, the difference between 3 groups has notable meaning
Justice（P<0.01）.
The foregoing is only a preferred embodiment of the present invention, but protection scope of the present invention be not limited thereto,
Any one skilled in the art the invention discloses technical scope in, technique according to the invention scheme and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (1)
1. a kind of establish liver cancer and normal person's diagnostic model and the diagnostic model of liver cancer and chronic liver disease, it is characterised in that：By with
Lower step composition：
Using SELDI-TOF-MS technologies, liver cancer and normal person's diagnostic model and the diagnosis mould of liver cancer and chronic liver disease are established
Type；
It has collected 48 liver cancer patients, 17 patients with chronic liver, 33 Healthy Human Serums；Using SELDI-TOF technologies to sample
Originally it is detected, it turns out that：
1. liver cancer group and normal person group detect 126 protein peaks altogether, wherein 65 have in liver cancer with difference that normal person organizes it is aobvious
Write meaning (P<0.05)；There is 21 marker molecules are high to express compared with normal human serum protein spectrum, in In Sera of Patients With Hepatocarcinoma, 44
A marker molecule low expression（As shown in Figure 1）；Using the data of the albumen of 7 in this 65 differential proteins different mass-to-charge ratioes, build
Vertical discrimination model, the sensitivity of its diagnosing liver cancer is 100% (33/33), and specificity is 96.97% (32/33)；Utilize the model
Blind detection, accuracy rate 98.8% (80/81), sensitivity 100% (48/48), specificity 96.97% are carried out to 81 samples
(32/33)；
2. liver cancer group detects 125 protein peaks altogether with chronic liver disease group, wherein 38 difference in liver cancer and chronic liver disease group
Significance (P<0.05)；Compared with chronic liver disease group Serum protein profiling, there are 18 marker molecules in In Sera of Patients With Hepatocarcinoma
Height expression, 20 marker molecule low expressions；Using the data of the albumen of 11 in this 38 differential proteins different mass-to-charge ratioes, establish
Discrimination model, the sensitivity of its diagnosing liver cancer is 93.9% (31/33), and specificity is 94.1% (16/17)；Utilize the model pair
65 samples carry out blind detection, accuracy rate 81.5% (53/65), sensitivity 81.3% (39/48), specificity 82.4% (14/
17)；
3. wherein mass-to-charge ratio is that the albumen of 7789Da expresses highest in liver cancer group（21.66±9.00）, in chronic benign hepatopathy
Expression is taken second place in group（12.99±9.09）, expressed in normal group minimum（8.83±6.78）, the difference between 3 groups has notable meaning
Justice（P<0.01）.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111693621A (en) * | 2020-05-29 | 2020-09-22 | 中国医学科学院肿瘤医院 | Establishment method and application of pancreatic cancer diagnosis model based on serum peptide |
| CN111751549A (en) * | 2020-06-08 | 2020-10-09 | 郑州大学第一附属医院 | Protein molecule prognosis method in liver cancer diagnosis and application thereof |
| CN117604108A (en) * | 2024-01-23 | 2024-02-27 | 杭州华得森生物技术有限公司 | Biomarker for liver cancer diagnosis and prognosis and application thereof |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101393217A (en) * | 2008-09-27 | 2009-03-25 | 中国人民解放军第二军医大学 | Detection kit for schistosomiasis japonica blood serum designated object |
| CN101403740A (en) * | 2008-11-13 | 2009-04-08 | 毅新兴业（北京）科技有限公司 | Mass spectrum model used for detecting liver cancer characteristic protein and preparation method thereof |
| CN105301259A (en) * | 2015-10-10 | 2016-02-03 | 广西医科大学 | Serum RBP4 (retinol binding protein 4) albumen as liver cancer patient serum marker and application of serum RBP4 albumen |
-
2017
- 2017-11-22 CN CN201711172015.6A patent/CN107942074A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101393217A (en) * | 2008-09-27 | 2009-03-25 | 中国人民解放军第二军医大学 | Detection kit for schistosomiasis japonica blood serum designated object |
| CN101403740A (en) * | 2008-11-13 | 2009-04-08 | 毅新兴业（北京）科技有限公司 | Mass spectrum model used for detecting liver cancer characteristic protein and preparation method thereof |
| CN105301259A (en) * | 2015-10-10 | 2016-02-03 | 广西医科大学 | Serum RBP4 (retinol binding protein 4) albumen as liver cancer patient serum marker and application of serum RBP4 albumen |
Non-Patent Citations (3)
| Title |
|---|
| MIN HE ET AL.: "Detection and identification of NAP-2 as a biomarker in hepatitis B-related hepatocellular carcinoma by proteomic approach", 《PROTEOME SCIENCE》 * |
| 张志勇 等: "应用SELDI-TOF-MS技术筛选肝癌血清标志物的研究", 《现代预防医学》 * |
| 覃健 等: "SELDI-TOF-MS技术在筛选肝癌患者血清标记物中的应用", 《广西医科大学学报》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111693621A (en) * | 2020-05-29 | 2020-09-22 | 中国医学科学院肿瘤医院 | Establishment method and application of pancreatic cancer diagnosis model based on serum peptide |
| CN111693621B (en) * | 2020-05-29 | 2022-08-23 | 中国医学科学院肿瘤医院 | Establishment method and application of pancreatic cancer diagnosis model based on serum peptide |
| CN111751549A (en) * | 2020-06-08 | 2020-10-09 | 郑州大学第一附属医院 | Protein molecule prognosis method in liver cancer diagnosis and application thereof |
| CN117604108A (en) * | 2024-01-23 | 2024-02-27 | 杭州华得森生物技术有限公司 | Biomarker for liver cancer diagnosis and prognosis and application thereof |
| CN117604108B (en) * | 2024-01-23 | 2024-04-09 | 杭州华得森生物技术有限公司 | Biomarker for liver cancer diagnosis and prognosis and application thereof |
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