CN115825414B

CN115825414B - Blood or urine metabolic marker and application thereof in endometrial cancer early screening

Info

Publication number: CN115825414B
Application number: CN202310030787.5A
Authority: CN
Inventors: 曹冬焱; 陈君宇; 孙伟; 刘晓燕; 孙海丹; 俞梅; 周慧梅
Original assignee: Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Current assignee: Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Priority date: 2023-01-09
Filing date: 2023-01-09
Publication date: 2023-04-25
Anticipated expiration: 2043-01-09
Also published as: CN115825414A

Abstract

The invention belongs to the field of biotechnology, and particularly relates to a blood or urine metabolic marker and application thereof in early screening of endometrial cancer, wherein the metabolic marker is selected from ADP-mannose, docosadienoic acid, hippuric acid or a combination thereof, and the metabolic marker can be used for early diagnosing endometrial cancer patients, so that the survival rate of the patients is improved, a new break is provided for clinical diagnosis of endometrial cancer, and the metabolic marker has a good clinical application prospect.

Description

Blood or urine metabolic marker and application thereof in endometrial cancer early screening

Technical Field

The invention belongs to the technical field of biology, and particularly relates to a blood or urine metabolic marker and application thereof in endometrial cancer early screening.

Background

Up to now, differential metabolites that have been found include 3-hydroxybutyric acid, linoleic acid, stearic acid, myristic acid, threonine and valine in serum, phosphorylcholine, C14:2, 14-dienyl l-carnitine, C6 and caproyl carnitine and the like in plasma, and porphobilinogen, acetylcysteine, n-acetylserine, imidazole acrylic acid and isobutyrylglycine and the like in urine can be used as predictors of Endometrial Cancer (EC). In addition, the research shows that the content of estrogen and the metabolite thereof in urine of an EC patient is higher than that of normal women, which suggests that the high expression of estrogen in the patient body is also possible to become a screening index of EC. However, a more well-established group of specific metabolites is not currently available. The reason for this may be that EC patients often incorporate multiple metabolic complications, which can have an impact on metabonomic analysis. And most of the research samples have less quantity, and the diagnostic efficiency of the screened markers is more than 90 percent, so that the effect is poor. In addition, different analytical technology platforms may also cause certain differences. Currently common metabonomics detection methods include mass spectrometry techniques and nuclear magnetic resonance (Nuclear Magnetic Resonance, NMR) techniques. Among them, NMR has the technical advantage of simple sample pretreatment steps, and can perform nondestructive and unbiased analysis on the sample, but has poor sensitivity and low resolution. Compared with NMR, the mass spectrum technology has higher sensitivity, resolution and specificity, and the standard substance gallery can identify, but the specificity is slightly worse, the identification power for a large number of spectrum peaks is not high, and the quantification of metabolites is easily affected by the ionization degree. Thus, mass spectrometry techniques are often used in combination with chromatographic techniques that are quantitatively accurate, have a high separation capacity, but have a somewhat weaker qualitative analysis capacity, including gas chromatography-mass spectrometry techniques (Gas Chromatography-Mass Spectrometry, GC-MS) and liquid chromatography-mass spectrometry techniques (Liquid Chromatography-Mass Spectrometry, LC-MS). Among them, GC-MS is mainly suitable for analyzing a sample having strong volatility, while LC-MS is mainly used for analyzing a sample having weak volatility and poor thermal stability. In view of this, the invention adopts ultra-high throughput liquid chromatography-mass spectrometry (Ultra performance liquid chromatography-mass spectrometry, UPLC-MS) to perform combined analysis of blood and urine metabonomics on the sample of the subject to be studied, find differential metabolites of EC patients and healthy controls, and build a diagnostic model to provide a new biomarker for early discovery and diagnosis of EC.

Disclosure of Invention

Based on the background, the invention provides a blood or urine metabolism marker and application thereof in early screening of endometrial cancer in order to solve the problems of no recognized marker, less sample size in most researches and poor diagnosis efficiency at present.

In order to achieve the above purpose, the present invention is realized by the following technical scheme:

the present invention provides the use of a blood or urine metabolite selected from ADP-mannose, docosadienoic acid, hippuric acid or a combination thereof as a diagnostic marker for the preparation of a product for early diagnosis of endometrial cancer.

Further, the product comprises a kit and a chip.

Further, the product is used for diagnosing endometrial cancer by detecting the content level of ADP-mannose, docosadienoic acid and hippuric acid.

Further, the detection method is mass spectrometry.

Further, the mass spectrometry adopts a first-stage full-scan mode for screening and is combined with a second-stage targeting analysis. Specifically, the invention adopts ultra-high liquid chromatography-high resolution mass spectrometry (UPLC-MS) to detect blood or urine metabolites in a full scanning mode, wherein the full scanning mode is to collect all small molecule first-order information within the mass range of 50m/z to 1200m/z at the same time, then screen out differential metabolites through multivariate statistical analysis (principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA)), further perform targeted second-level fragmentation on the differential metabolites, and finally determine the structure of the differential metabolites by combining a database second-level spectrogram.

The invention also provides an identification reagent for early diagnosis of endometrial cancer, which is a reagent for detecting blood or urine metabolites.

Further, the blood or urine metabolite is selected from ADP-mannose, docosadienoic acid, hippuric acid, or a combination thereof.

The invention also provides a kit for early diagnosis of endometrial cancer, comprising an identification reagent for detecting ADP-mannose, docosadienoic acid, hippuric acid, or a combination thereof.

The invention also provides a chip for early diagnosis of endometrial cancer, comprising an identification reagent for detecting ADP-mannose, docosadienoic acid, hippuric acid, or a combination thereof.

Compared with the prior art, the invention has the following beneficial effects:

according to the invention, EC is researched through blood or urine combined metabonomics, the screened combined metabolic marker can distinguish EC from a control, the AUC value of the combined metabolic marker can reach 0.983, the combined metabolic marker has good sensitivity and specificity, and the combined metabolic marker can be used as a potential tumor marker after being well verified in a verification group. In the crowds such as abnormal menstruation, abnormal uterine bleeding, intrauterine space occupation, postmenopausal intimal thickening and the like, the blood or urine metabolic markers provided by the invention can be used for predicting the canceration risk, screening out real high-risk crowds, and actively performing invasive examination to obtain clear diagnosis of intimal pathology.

Drawings

FIG. 1 is a serum metabolic profile classification chart (panel A: PCA classification chart, panel B: OPLS-DA classification chart) of endometrial cancer group and normal control group;

FIG. 2 is a urine metabolic profile classification chart (panel A: PCA classification chart, panel B: OPLS-DA classification chart) of endometrial cancer group and normal control group;

FIG. 3 is a ROC curve of the joint prediction of three metabolites in example 1;

FIG. 4 is a ROC curve of the joint prediction of three metabolites in example 2.

Detailed Description

The present invention will be described more fully hereinafter in order to facilitate an understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

Example 1 screening for differential metabolites

1. Instrument and reagent

1) Instrument: waters ACQUITY H-Class liquid chromatograph (Waters Inc.), triple TOF 5600 mass spectrometer (Thermofisher Scientific Inc.).

2) The main reagent comprises: acetonitrile (Thermofisher Scientific company); c18 reverse phase chromatography column (3.0 mm. Times.100 mm, C18, 1.7 μm, waters Co.).

2. Sample collection

1) Blood and urine from 99 endometrial cancer patients and blood and urine from 41 age and sex matched normal control groups were selected from Beijing co-ordination hospitals.

2) Blood collection: the fasting venous blood was collected and centrifuged at 3000 g for 5min, and the supernatant was collected.

3) Urine collection: collecting fasting morning urine, centrifuging at 5000g for 30min, and removing precipitate.

3. Sample metabolite extraction

1) Blood metabolite extraction

Taking 50 mu L of serum sample, adding 150 mu L of mass spectrum water and 400 mu L of acetonitrile, swirling, and standing at-20 ℃ for 1 hour; centrifuging 14000g for 10min, collecting supernatant, centrifuging, concentrating, re-dissolving 50 μl of 2% acetonitrile water, centrifuging for 10min 14000g, filtering with 10kD filter membrane, and collecting 10 μl sample.

2) Urine metabolite extraction

200 mu L of urine supernatant is taken, 200 mu L of acetonitrile is added, vortex is carried out, standing is carried out at 4 ℃ for 30min, 14000g is centrifuged for 10min, supernatant is taken, centrifugal concentration is carried out, 200 mu L of 2% acetonitrile water is used for redissolution, 14000g is centrifuged for 10min, and 10 mu L of sample is taken after passing through a 10kD filter membrane.

4. Liquid phase analysis

Liquid phase analysis was performed using a Waters acquisition H-Class model ultra high performance liquid chromatography system under the following conditions: chromatographic column: waters HSS T3C 18 (3.0 mm x 100mm, 1.8 um), column temperature 40 ℃; the mobile phase A is 0.2 per mill formic acid water, the mobile phase B is 0.2 per mill formic acid acetonitrile solution, the elution mode is gradient elution, the elution time is 15 minutes, the flow rate is 0.5 mL/min, and the specific sample injection volume is 10uL. Specific information is shown in table 1 below.

5. Mass spectrometry identification

Eluted blood or urine metabolites were analyzed using a Triple TOF 5600 mass spectrometer with data format DDA format. The parameters are as follows: the primary full scanning range is 50-1200m/z, the accumulation time is 0.25s, the secondary accumulation time is 0.1s, the GS1 is 55, the GS2 is 55, the Curtain Gas is 35, and the temperature is set to be 550,Ionspray Voltage Floating and 4500.

Raw data obtained from UPLC-LTQ orbitrap was processed using the Progenesis QI (Version 2.0, nonlinear Dynamics, UK) commercial group analysis software from Waters. The software can automatically complete the preprocessing procedures such as peak alignment, peak identification, peak correction and the like, and finally outputs a three-dimensional matrix, namely, a spectrum peak index variable consisting of retention time and accurate mass-to-charge ratio, a sample name and peak intensity/area. The obtained data matrix is imported into multivariate statistical software SIMCA-P software 14.0 (Umetrics AB, umeas, sweden) for PCA analysis, and the inter-group variation trend is visualized. Variables with non-parametric test p-values less than 0.05 were considered as significant differences between groups and were screened as early potential markers for endometrial cancer. The screened differential variables were subjected to secondary fragmentation, and 204060eV energy was selected for the specific metabolite using HCD (High collision dissociation) fragmentation. The secondary fragments were deconvolved using progenesis QI software, searching HMDB (HUMAN METABOLOME DATABASE) database, and determining the differential metabolite structure.

6. Screening results

Blood metabolites: the unsupervised PCA plot shows that endometrial cancer groups and normal control groups exhibit a degree of differentiation (see fig. 1A); further, the supervision OPLS-DA is used for constructing a model, and the two groups of distinction degree is more obvious (see FIG. 1B). 39 differential metabolites were screened between endometrial cancer group and normal control group.

Urine metabolites: PCA panels showed that endometrial cancer groups were clearly differentiated from normal control groups (see FIG. 2A), and OPLS-DA showed that both groups were more clearly differentiated (see FIG. 2B). 78 differential metabolites were screened between endometrial cancer group and normal control group.

And carrying out targeted dipolar analysis on the differential metabolites obtained by preliminary screening of blood or urine metabolites to determine 3 metabolite structures, namely ADP-mannose, docosadienoic acid and hippuric acid. And the 3 metabolites are combined to distinguish endometrial cancer groups from normal control groups by adopting a logistic regression method to obtain a better prediction effect, the AUC value of an ROC curve is 0.983 (see figure 3), and the sensitivity and the specificity are shown in table 2.

Example 2 validation of the differential metabolites screened

The 3 metabolites screened were validated as markers for early diagnosis of endometrial cancer.

Alternatively, 47 endometrial cancer patients and 18 benign control patients were sampled for blood or urine metabolites, and the procedure for extracting the blood or urine metabolites was the same as in example 1. Performing full scan mode detection on blood or urine metabolites by using UPLC-MS, and quantitatively analyzing the primary spectrum peak area based on the markers to obtain three different metabolites between endometrial cancer groups and benign control groups: ADP-mannose, docosadienoic acid, hippuric acid. The predictive effect of three metabolites on endometrial cancer was assessed using ROC curves. The results show that the AUC value for the combined prediction of the three metabolites is 0.971 (see fig. 4), the prediction is good and significantly better than the prediction of the single metabolite.

The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.

Claims

1. Use of blood or urine metabolites as diagnostic markers for the preparation of a product for early diagnosis of endometrial cancer, characterized in that: the blood or urine metabolites are a combination of ADP-mannose, docosadienoic acid, and hippuric acid.

2. The use according to claim 1, characterized in that: the product comprises a kit and a chip.

3. The use according to claim 1, characterized in that: the product can be used for diagnosing endometrial cancer by detecting the content level of ADP-mannose, docosadienoic acid and hippuric acid.

4. A use according to claim 3, characterized in that: the detection method is mass spectrometry.

5. The use according to claim 4, characterized in that: the mass spectrum identification method adopts a first-stage full-scanning mode for screening and combines a second-stage targeting analysis.