CN114878723B - Metabolic marker for rapidly diagnosing multiple myeloma and application thereof - Google Patents

Metabolic marker for rapidly diagnosing multiple myeloma and application thereof Download PDF

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CN114878723B
CN114878723B CN202210777997.6A CN202210777997A CN114878723B CN 114878723 B CN114878723 B CN 114878723B CN 202210777997 A CN202210777997 A CN 202210777997A CN 114878723 B CN114878723 B CN 114878723B
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bone marrow
phenylalanine
multiple myeloma
tyrosine
supernatant
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CN114878723A (en
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刘丽宏
沈国林
王晓雪
宫丽丽
刘爱军
成虎
程龙浩
余江灵
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China Japan Friendship Hospital
Chinese Academy of Inspection and Quarantine CAIQ
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Abstract

The invention provides a metabolic marker for rapidly diagnosing multiple myeloma and application thereof, wherein the metabolic marker comprises one or more of phenylalanine, tyrosine and tryptophan. Compared with the prior art, the invention has the following advantages: the invention provides a metabolic marker for rapidly diagnosing multiple myeloma and application thereof, wherein the marker is derived from one or more combinations of metabolites of bone marrow tissues and bone marrow supernatants of patients, and comprises phenylalanine, tyrosine and tryptophan; the detection of the metabolic marker level can be effectively used for early clinical diagnosis of multiple myeloma diseases, has high sensitivity, is rapid and convenient, has accurate and reliable results, can provide a basis for clinical decision, provides a certain basis for subsequent basic research and clinical research, and has potential application and research values.

Description

Metabolic marker for rapidly diagnosing multiple myeloma and application thereof
Technical Field
The invention relates to the technical field of biomedical detection, in particular to a metabolic marker for rapidly diagnosing multiple myeloma and application thereof.
Technical Field
Multiple Myeloma (MM) is a disease characterized by the secretion of monoclonal immunoglobulins, a clonal plasma cell tumor. The disease is better in middle-aged and elderly people, males are more common than females, and the incidence of MM is in a remarkably rising trend along with the problem that the population of China is aging. According to statistics, MM accounts for 1% of all cancers and 10% of malignant hematological tumors, and the median survival time is 3-5 years. Patients with MM often have hypercalcemia, renal failure, anemia, osteolytic bone lesions, and the like. Because the disease is hidden and the clinical symptoms are diversified, misdiagnosis and missed diagnosis are often caused, the misdiagnosis and missed diagnosis rate is close to 50 percent, the patient misses the best treatment opportunity, and the condition of an illness is delayed finally.
Metabonomics is a powerful means for researching the physiological and pathological states of organisms and the biochemical effect of the organisms on exogenous substances, and focuses on the change of small-molecule metabolites with the molecular weight of less than 1000 Da in metabolic pathways, wherein the small-molecule metabolites are downstream products of genes and proteins and reflect the generated state of the organisms, and the state is the result of the combined action of the genes and the environment and is closer to the phenotype of a human body. Considering the complexity of diseases, namely gene and environment interaction, the characteristics of metabolites enable metabonomics to have strong advantages and potentials in the aspects of disease diagnosis, treatment and the like.
Currently, the main diagnostics of MM include: hemogram index, plasma protein electrophoresis, immunoglobulin, bone imaging examination, bone marrow examination, etc., and combined with clinical manifestations of bone pain, dizziness, asthenia, etc. Because the clinical manifestations of MM are easily confused with other diseases, and laboratory diagnosis of MM is generally low in sensitivity, time-consuming, costly, and delayed, there is a strong need to develop a specific, rapid, economical method for early diagnosis, efficacy assessment, and disease progression assessment or screening of MM.
Disclosure of Invention
Aiming at the existing restriction limitation, the invention provides a metabolic marker for rapidly diagnosing multiple myeloma and an application thereof, and overcomes the defects in the background technology.
In order to realize the purpose, the invention adopts the following technical scheme:
the invention provides a metabolic marker for rapidly diagnosing multiple myeloma and application thereof, wherein the metabolic marker is an amino acid composition and comprises one or more of phenylalanine, tyrosine and tryptophan.
The combination of metabolic markers may be phenylalanine alone, tyrosine alone, tryptophan alone, phenylalanine + tyrosine, phenylalanine + tryptophan, tyrosine + tryptophan, and phenylalanine + tyrosine + tryptophan.
Most preferably, phenylalanine + tyrosine + tryptophan.
Levels of phenylalanine, tyrosine and tryptophan were significantly elevated in bone marrow tissue and bone marrow supernatant from multiple myeloma patients compared to healthy subjects.
Further, the product is a chip, test paper or kit for multiple myeloma detection or early diagnosis.
Further, the above application, the detection is quantitative determination of the content level of the metabolic marker in the biological sample of the subject and is used for judging the disease status of multiple myeloma in the subject.
Further, in the above-mentioned application, the biological sample is bone marrow tissue or bone marrow supernatant.
Further, in the above-mentioned use, the reagent detects the level of the metabolic marker in the biological sample by one or more of the following methods: chromatography, spectroscopy, mass spectrometry, chemical analysis.
Further, the above applications, the chromatography includes high performance liquid chromatography, thin layer chromatography, gas chromatography; the spectroscopy comprises nuclear magnetic resonance spectroscopy, refractive index spectroscopy, ultraviolet spectroscopy and near infrared spectroscopy; the chemical analysis method comprises electrochemical analysis and radiochemical analysis.
Furthermore, in the application, the mass spectrometry is high-resolution mass spectrometry, and the method for rapidly and quantitatively detecting the metabolic markers by adopting the mass spectrometry comprises the steps of firstly carrying out gradient elution by adopting a chromatographic column and then collecting data in an electrospray ion source ESI positive and negative ion PRM mode;
in the chromatographic column gradient elution process, the specification of the chromatographic column is as follows: thermo Hypersil Gold C183 mu m, 2.1 x 100 mM, the temperature of a chromatographic column is 30 ℃, the temperature of an automatic sample injector is kept at 4 ℃, solution A is water containing 0.1% of formic acid and 2.5mM of ammonium acetate, solution D is acetonitrile, 0-0.5min, and 5% -10% of D is adopted; 0.5-1.0 min, 10% -30% D; 1.0-2.0min, 30% -95% D; 2.0-4.0 min, 95% -95% D; eluting in the process of 4.0-4.5 min, 95-5% D, 4.5-6.0min and 5-5% D, wherein the analysis time is 0-6.0min, 5 mu L of sample is fed each time, and the flow rate is 0.3 mL/min;
in the data acquisition process of an electrospray ion source (ESI) positive and negative ion PRM mode, the spray voltage is 3500V (+), 2500V (-), the evaporation temperature is 350 ℃, the sheath gas is 40Arb, the auxiliary gas is 10Arb, the temperature of a capillary tube is 350 ℃, the S-lens RF level is 50, and the NCE is 30; the internal standard tolbutamide is 269.09654/170.19791, phenylalanine is 166.08626/120.08100, tyrosine is 182.08117/136.07578, tryptophan is 205.09715/188.07057, and the internal standard propranolol is 260.16451/116.10709.
Further, in the application, in the mass spectrometry, a method of scanning positive ions and negative ions and analyzing all metabolic markers and internal standards by one-time sample injection is adopted for detection.
Further, in the above application, the pretreatment mode of the biological sample before detection is as follows: bone marrow tissue was treated with 50% methanol in ultrapure water at a ratio of 1:10, carrying out ultrasonic crushing to obtain bone marrow tissue crushing liquid; respectively sucking 100 mu L of bone marrow tissue crushing liquid and bone marrow supernatant, adding 500 mu L of precipitator containing internal standard, dissolving the internal standard by using methanol and acetonitrile which are mixed in equal proportion, uniformly mixing by vortex for 30s, centrifuging at 12000rpm for 10 min, and sucking the supernatant to obtain a test solution for quantitative analysis.
The second invention of the invention also provides the application of the product capable of effectively reducing the content of the amino acid composition in preparing a product for assisting in treating multiple myeloma, wherein the product refers to a composite product capable of effectively reducing the content of the amino acid composition in bone marrow tissues and bone marrow supernatants; the amino acid composition is the amino acid composition; the product is a food, a probiotic preparation or a pharmaceutical preparation.
Furthermore, the screening method of the product adopts the steps of detecting the content of the amino acid composition in bone marrow tissues and bone marrow supernatants before and after intervention of candidate food, probiotic preparation or pharmaceutical preparation, and screening by taking whether the amino acid composition is reduced or not as a standard.
The scheme of the metabolic marker screening process and mechanism research of the invention is shown in figure 1.
Compared with the prior art, the invention has the following advantages:
the invention provides a metabolic marker for rapidly diagnosing multiple myeloma and application thereof, wherein the marker is derived from one or more combinations of metabolites of bone marrow tissues and bone marrow supernatants of patients, and comprises phenylalanine, tyrosine and tryptophan; the detection of the metabolic marker level can be effectively used for early clinical diagnosis of multiple myeloma diseases, has high sensitivity, is rapid and convenient, has accurate and reliable results, can provide a basis for clinical decision, provides a certain basis for subsequent basic research and clinical research, and has potential application and research values.
Meanwhile, the amino acid composition can also be applied to the preparation of products for assisting in treating multiple myeloma, and the content of the amino acid composition in the organism is reduced through the intake of food, probiotic preparations or pharmaceutical preparations, so that the amino acid composition further becomes an auxiliary means for MM treatment.
Drawings
Figure 1 shows a basic flow diagram for the metabolomics mechanism study of multiple myeloma according to the present invention.
FIG. 2 shows the result of high resolution mass spectrometry of a sample according to an embodiment of the present invention.
Wherein, fig. 2A is a total ion current of positive ion full scan obtained by sample high resolution mass spectrometry detection; FIG. 2B is a total ion current of the negative ion full scan obtained by the sample high resolution mass spectrometry; FIG. 2C is a chromatogram of phenylalanine obtained from high resolution mass spectrometry of a sample; FIG. 2D shows the mass number and molecular formula of phenylalanine in a sample detected by high resolution mass spectrometry.
FIG. 3 shows a map created for the metabolic marker database.
FIG. 4 is a graph showing PCA model scores for a bone marrow supernatant sample and a bone marrow tissue sample, in accordance with one embodiment of the present invention.
Wherein, fig. 4A is a PCA model score plot of a bone marrow supernatant sample, red circles represent healthy control groups, green circles represent MM patients, and the results show that HC (healthy control) and MM patients can be well differentiated; fig. 4B is a PCA model score plot of bone marrow tissue samples with red circles representing healthy controls and green circles representing MM patients, showing that HC (healthy controls) and MM patients are better differentiated.
FIG. 5 is a graph showing OPLS-DA model scores for bone marrow supernatant samples and bone marrow tissue samples, in accordance with an embodiment of the present invention.
Wherein, fig. 5A is a bone marrow supernatant sample OPLS-DA model score plot, red circles represent healthy control groups, green circles represent MM patients, and the results show that HC (healthy control) and MM patients can be well differentiated; fig. 5B is a bone marrow tissue sample OPLS-DA model score plot, with red circles representing healthy controls and green circles representing MM patients, showing that HC (healthy controls) and MM patients can be better differentiated.
FIG. 6 shows the survival change of the culture medium of multiple myeloma cell line H929 in the absence of the respective metabolic marker, in accordance with an embodiment of the present invention.
Wherein, fig. 6A shows that the survival rate of the multiple myeloma cell line H929 is significantly decreased after the medium lacks phenylalanine; fig. 6B is a significant decrease in survival following a medium deficiency of tyrosine for multiple myeloma cell line H929; figure 6C is a significant decrease in survival following the absence of phenylalanine/tyrosine in the medium of multiple myeloma cell line H929; fig. 6D is a significant decrease in survival following tryptophan deficiency in the culture medium of multiple myeloma cell line H929; figure 6E is a significant decrease in survival following the absence of phenylalanine/tyrosine/tryptophan in the medium of multiple myeloma cell line H929.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below. It is to be understood that the description herein is only illustrative of the present invention and is not intended to limit the scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and the terminology used herein in the description of the present invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the present invention. The reagents and instruments used in the present invention are commercially available, and the characterization means involved can be referred to the description in the prior art, which is not repeated herein.
For a further understanding of the present invention, reference will now be made in detail to the preferred embodiments of the present invention.
Example 1
Screening of metabolic markers between bone marrow tissue and bone marrow supernatants in multiple myeloma patients and healthy humans:
1. sample source:
bone marrow tissue and bone marrow supernatant samples were collected from 20 HC (healthy controls) and 16 MM patients following informed consent from participants and approval by the ethical committee of the kyoto yang hospital, affiliated with the university of capital medical science. All participants were from the Beijing Kogyo Hospital affiliated to the university of capital medicine, all MM patients were diagnosed using the IMWG standard, all MM patients were within 4 courses of chemotherapy, and the study was conducted to find that the patients did not cause significant metabolic changes due to the course of treatment. The age and sex of HC were matched to MM patients to exclude metabolic differences due to sex and age. The time for collecting bone marrow tissue and bone marrow supernatant is in early morning and fasting state. All samples were stored at-80 ℃ until use.
2. The main reagents are as follows:
phenylalanine, tyrosine and tryptophan standards were purchased from Sigma-Aldrich, LC/MS grade acetonitrile from Merck, HPLC grade methanol from Merck, and formic acid from CNW. Other reagents were all commercially available analytical grade. Deionized water was prepared from a Milli-Q ultrapure water system from Millipore corporation.
3. And (3) screening different metabolites of bone marrow tissues and bone marrow supernatants by high-resolution mass spectrometry:
3.1 sample preparation:
sample pretreatment: bone marrow tissues (healthy control group and MM group) were subjected to ultrasonication using ultrapure water (containing 50% methanol) at a mass-to-volume ratio of 1:10(w/v) to obtain a bone marrow tissue disruption solution. Bone marrow tissue disruption solution and bone marrow supernatant (healthy control group and MM group) were aspirated 50. mu.L respectively, added with 450. mu.L of precipitant containing internal standard (methanol: acetonitrile =1:1), vortexed and mixed for 60s, centrifuged at 13000rpm for 10 min, and 100. mu.L aspirated for metabonomics analysis.
3.2 chromatography/Mass Spectrometry conditions:
and (3) detecting by using a high-resolution mass spectrometer QE-Orbitrap. Chromatographic mobile phase: the mobile phase A is an aqueous solution containing 0.1 percent of formic acid and 2mmoL/L of ammonium formate, and the mobile phase D is acetonitrile. Gradient elution procedure for sample determination: 0-1.0min, 95% A; 1.0-5.0 min, 95% -40% A; 5.0-8.0min, 40% -0% A; 8.0-11.0 min, 0% A; 11.0-14.0 min, 0% -40% A; 14.0-15.0 min, 40% -95% A; 15.0-18.0 min, 95% A, analysis time 0-18 min, 5 μ L per sample injection, flow rate 0.25mL/min, chromatographic column: ACQUITY BEH C181.7 μm, 2.1X 50 mm, column temperature 30 deg.C, and autosampler temperature 4 deg.C. Data were collected in electrospray ion source (ESI) positive and negative ion mode, spray voltage: 3000V; evaporation temperature: 350 ℃; capillary temperature: 350 ℃; s-lens RF: 50; resolution of one-level Full scan (Full scan): 70000, scan range: 70-1050 m/z. Secondary data dependent scan (Full MS/dd-MS 2): resolution ratio: 17500 (mm); AGC target: 1e 5; maximun TT: 50 ms; NCE: 20, 40, 60.
The high resolution mass spectrometry results are shown in fig. 2.
3.3 metabolic pathway analysis:
analyzing the difference of endogenous metabolites in bone marrow tissues (a healthy control group and a MM group) and bone marrow supernatants (a healthy control group and a MM group) by using Metabionalyst 5.0, finding out endogenous metabolites with VIP values larger than 1 and P values smaller than 0.05, analyzing the differential metabolic pathways of the bone marrow tissues and the bone marrow supernatants by using Pathway Analysis in a Metabionalyst 5.0 website, and selecting the metabolic pathways with the Impact value larger than 0.1 as main differential metabolic pathways of the bone marrow tissues and the bone marrow supernatants.
4. Data processing and statistical analysis:
the metabolic marker database establishment process is shown in fig. 3. Identification of endogenous metabolites the accurate mass number of the decimal point 5 of each endogenous metabolite is obtained by using a high resolution mass spectrum mzCloud, identified by the molecular formula of each endogenous metabolite, and a database of the endogenous metabolites is established by using Tracefinder software. And then automatically acquiring peak areas of corresponding endogenous metabolites by using a database established by Tracefinder software, analyzing by using MetabioAnalyst 5.0 website, drawing PCA and OPLS-DA model diagrams, finding out the metabolic mode difference and obvious classification trend of healthy people and MM patients, and finally selecting the metabolic markers with the difference according to the standards of VIP >1 and P < 0.05.
5. As a result:
PCA and OPLS-DA were calculated using the MetabioAnalyst 5.0 website. The results of PCA (fig. 4A) showed the difference between the bone marrow tissue of the male healthy control group and the bone marrow tissue of the male MM group, and the results of PCA (fig. 4B) showed the difference between the bone marrow supernatant of the male healthy control group and the bone marrow supernatant of the male MM group. The results of OPLS-DA (FIGS. 5A and 5B) show that the male bone marrow tissue (healthy control versus MM) and the male bone marrow supernatant (healthy control versus MM) were completely separated. However, the bone marrow tissues and bone marrow supernatants of the female healthy control group and the female MM group have no obvious difference, and PCA and OPLS-DA operation analysis can not be carried out. Endogenous substances with VIP >1 and P values less than 0.05 were simultaneously selected as the major differential metabolic pathways for further analysis of male bone marrow tissue and bone marrow supernatants. Table 1 shows the rate of change of different metabolites in bone marrow supernatants obtained using the OPLS-DA model. The results in table 1 show that there are a total of 33 different metabolites in the bone marrow supernatant of men, and the ratio of 19 endogenous substances in MM group is mainly increased and 14 are mainly decreased compared to the healthy control group. Table 2 shows the rate of change of different metabolites in bone marrow tissue obtained using the OPLS-DA model. The results in table 2 show that the total number of the differential metabolites of the bone marrow tissue of the male is 14, compared with the healthy control group, the proportion of 5 endogenous substances in the MM group is mainly increased, and the other 9 endogenous substances mainly have a descending trend, which indicates that the metabolic secretion of the endogenous substances of the bone marrow tissue and bone marrow supernatant is influenced after the bone marrow tissue is subjected to tumor lesion, so that the content of the endogenous substances is obviously changed, and the main changed component is amino acid substances.
TABLE 1
No. Metabolites VIP P value Peak area ratio (%)
1 6-aminonicotinamide 2.0907 2.85E-12 11.6±9.7 ↓
2 Acryloyl carnitine 1.1501 2.33E-10 22.8±13.6↓
3 2, 4-diaminobutyric acid 2.1233 8.74E-12 4.6±1.8↓
4 Propionaldehyde 1.4354 1.96E-09 6.3±3.3↓
5 LysoPC(22:5(7Z，10Z，13Z，16Z，19Z)) 1.0139 0.0002 190.3±73.2↑
6 LysoPC(18:0) 7.2119 0.0004 153.5±37.2↑
7 LysoPC(18:1(11Z)) 5.7246 0.0003 160.2±45.0↑
8 Dihydrouracil 1.6940 9.23E-08 10.6±7.3↓
9 Citrulline 1.4290 1.09E-07 12.1±5.3↓
10 LysoPC(16:0) 10.3548 8.19E-05 147.8±25.5↑
11 Cytosine 1.3530 4.02E-07 3.6±2.3↓
12 2, 4-dimethyl benzaldehyde 1.1820 3.6E-06 24.2±12.1↓
13 LysoPC(18:2(9Z，12Z)) 7.1350 0.0020 158.0±55.3↑
14 LysoPE(0:0/18:2(9Z，12Z)) 1.4083 0.0026 183.5±84.9↑
15 LysoPC(20:3(5Z，8Z，11Z)) 2.1808 0.0005 205.2±93.8↑
16 PC(14:0/P-18:0) 1.0680 0.0002 59.8±24.6↓
17 Histamine 2.8857 8.36E-06 32.1±24.9↓
18 SM(d18:0/24:1(15Z)) 1.8409 9.72E-05 129.7±15.9↑
19 LysoPC(16:1(9Z)) 1.4863 0.0026 161.1±57.0↑
20 SM(d18:1/24:0) 1.3097 0.0004 134.1±22.2↑
21 Palmitic acid 2.0643 0.0005 46.9±28.3↓
22 PC(14:0/22:5(4Z，7Z，10Z，13Z，16Z)) 2.1714 0.0086 149.8±60.1↑
23 Phenylalanine 1.7092 0.0059 138.6±33.0↑
24 LysoPC(20:4(8Z，11Z，14Z，17Z)) 3.1740 0.0036 158.0±55.8↑
25 Cholesterol sulfate 1.4187 0.0274 129.5±42.9↑
26 LysoPC(17:0) 1.5050 0.0146 163.4±74.2↑
27 SM(d18:1/22:0) 2.0420 5.16E-05 130.3±18.4↑
28 PC(20:3(5Z，8Z，11Z)/20:3(5Z，8Z，11Z)) 2.2486 0.0022 149.6±54.7↑
29 Carnitine 3.8629 0.0067 76.5±18.0↓
30 PC(o-18:0/20:4(8Z，11Z，14Z，17Z)) 1.3489 0.0008 71.7±20.0↓
31 PC(14:1(9Z)/20:0) 5.7459 0.0189 136.6±50.2↑
32 Alanine 1.0858 0.0006 137.0±30.9↑
33 Acetyl carnitine 4.3102 0.0273 55.3±11.8↓
TABLE 2
No. Metabolites VIP P Peak area ratio (%)
1 Phenylalanine 2.3313 0.0010 143.1±41.1↑
2 4' -methoxyacetophenone 2.5913 0.0065 68.5±28.7↓
3 Creatinine 2.2272 0.0143 135.8±48.6↑
4 Nicotinamide 3.1493 0.0197 117.3±23.0↑
5 Lactic acid 5.5128 0.0212 138.5±52.8↑
6 Succinic acid 3.5313 0.0213 69.7±38.0↓
7 Dihydrouracil 2.8424 0.0225 75.4±34.6↓
8 Alanine 4.5515 0.0240 24.6±8.8↓
9 Cytosine 1.8839 0.0287 62.1±37.7↓
10 Malonic acid ethyl ester 4.2573 0.0299 71.5±38.2↓
11 3-hydroxy-3-methyl-2-oxobutanoic acid 4.3666 0.0308 71.5±39.2↓
12 3-methoxybenzaldehyde 1.1602 0.0367 72.6±38.9↓
13 1, 5-anhydro-D-glucitol 1.5578 0.0381 64.7±46.9↓
14 PC(20:1(11Z)/14:1(9Z)) 3.3360 0.0487 179.0±34.7↑
Study of differences in endogenous metabolic pathways in bone marrow tissue and bone marrow supernatants:
table 3 is a metabolic pathway analysis of bone marrow supernatants and tissues using metaboanalyst 5.0. The results in table 3 show that metabolic pathways with an Impact value greater than 0.1 are significantly different in male bone marrow tissues (healthy control group and MM group) and male bone marrow supernatants (healthy control group and MM group), wherein the number of the metabolic pathways with the difference in the bone marrow supernatants is mainly 5, and the number of the metabolic pathways with the difference in the bone marrow tissues is mainly 3, which show that the metabolic pathways mainly affect the synthesis of phenylalanine, tyrosine and tryptophan, and the metabolism of phenylalanine, and the analysis results show that the metabolism and the synthesis of amino acid are affected after the bone marrow tissues are subjected to tumor lesions, so that the endogenous substance content of the bone marrow tissues and the endogenous substance content of the supernatant are changed, and therefore phenylalanine, tyrosine and tryptophan are finally selected as metabolic markers for distinguishing normal bone marrow tissues, tumor cells and bone marrow supernatants thereof.
TABLE 3
No. Bone marrow supernatant Total Hits FDR Impact
1 Phenylalanine, tyrosine and tryptophan biosynthesis 4 1 1 0.5000
2 Metabolism of phenylalanine 10 1 1 0.3571
3 Arginine biosynthesis 14 1 1 0.2284
4 Histidine metabolism 16 1 1 0.1885
5 Metabolism of glycerophospholipids 36 2 1 0.1118
No. Bone marrow tissue Total Hits FDR Impact
1 Phenylalanine, tyrosine and tryptophan organismsSynthesis of 4 1 0.9 0.5000
2 Metabolism of phenylalanine 10 1 0.9 0.3571
3 Niacin and nicotinamide metabolism 15 1 0.9 0.1943
Example 2:
clinical analysis of specific cases:
sample collection:
bone marrow tissue and bone marrow supernatant samples were collected from 20 HC (healthy controls) and 16 suspected MM patients. All participants were from the Beijing Chaoyang Hospital affiliated with the university of capital medical science. The age and sex of HC were matched to suspected MM patients to exclude metabolic differences due to sex and age. The blood sampling time is in the early morning with empty stomach. Collecting fasting plasma sample of the subject, and storing in a refrigerator at-80 ℃ for later use. The diagnosis of all suspected MM patients was confirmed using the following clinical diagnostic criteria.
1. Symptoms and signs:
the most common symptoms and signs in MM patients are associated with bone destruction, anemia, renal insufficiency, hypercalcemia, or infection. Common symptoms and characterizations of MM are shown in table 4, and are common:
(1) skeletal symptoms: bone pain, local mass, pathological fracture and paraplegia.
(2) Anemia: orthocellular orthopigmentary anemia; some patients combine leukopenia and/or thrombocytopenia.
(3) Impairment of renal function: tubulose nephropathy, caused by obstruction of the tubules by the light chain, is the most common cause of renal failure.
(4) Hypercalcemia: there are symptoms such as vomiting, weakness, confusion, polyuria or constipation.
(5) And (3) immunity reduction: recurrent bacterial pneumonia and/or urinary tract infection, sepsis; fungal infections, viral infections are also visible.
(6) High viscosity syndrome: can be used for treating dizziness, vertigo, dim eyesight, tinnitus, disturbance of consciousness, numbness of fingers, coronary insufficiency, and chronic heart failure. In addition, the M component of some patients is cryoglobulin, which causes microcirculatory disturbance and reynolds phenomenon.
(7) And others: patients with amyloidosis may present with tongue hypertrophy, parotid enlargement, enlarged heart, diarrhea or constipation, hepatosplenomegaly, peripheral neuropathy, etc.; patients in advanced stages may have a tendency to bleed.
TABLE 4
Increased blood calcium levels Correcting serum calcium above normal upper limit value of 0.25mmol/L [1mg/dL ]]Above or below>2.8 mmol/L[11.5mg/dl]
Impairment of renal function Blood creatinine>176.8μmol/L[2mg/dl]
Anemia (anemia) Hemoglobin < 100g/L or more than 20g/L lower than the normal value
Destruction of bone mass Osteolytic lesions or osteoporosis with compression fracture
Others Symptomatic hyperviscosity blood, amyloidosis, repeated bacterial infections (more than or equal to 2 times per year)
2. Auxiliary inspection:
(1) blood picture: the morbid period is different, the anemia degree is different, and the erythrocytes in the blood smear have rouleaux phenomenon; the classification should take care of the presence or absence of plasma cells. The blood sedimentation rate is remarkably increased.
(2) Bone marrow examination: bone marrow contains >10% of plasma cells and either plasma or plasma blasts, which are seen as binuclear or multinucleated plasma cells.
(3) Plasma protein electrophoresis and immunoglobulin assay: the disease is characterized by hyperglobulinemia and individual Ig (M protein) with narrow bottom and peak of the globin zone shown by electrophoresis. Immunoelectrophoresis can determine the type and amount of abnormal Ig, such as IgG, IgA, IgM, IgD, IgE, and light chain K or lambda types, with double clones being coupled. This disease indicates that some igs are elevated monoclonally while others are inhibited at lower levels than normal.
(4) X-ray inspection: the change of osteolysis can be seen, and the change of osteolysis can be seen in the bone defect, such as the skull; diffuse osteoporosis; pathological fractures are usually seen in the rib, chest, lumbar vertebra, etc.
3. And (3) diagnosis:
diagnostic criteria:
(ii) (requirement for 3 rd + 1 st/2 nd) diagnosis criteria for asymptomatic (smoldering) myeloma:
1. the serum clone M protein is more than or equal to 30 g/L, and the urinary light chain is more than or equal to 0.5 g in 24 h;
2. the proportion of the marrow monoclonal plasma cells is 10% -59%;
3. no damage to related organs and tissues (no terminal organ damage such as SLiM-CRAB);
note: SLiM-CRAB expression is detailed in the "diagnostic criteria for symptomatic (active) multiple myeloma" section.
(II) symptomatic (active) multiple myeloma diagnosis criteria (requirement for satisfaction of any 1 of items 1 and 2, plus item 3):
1. the proportion of the marrow monoclonal plasmacytoma is more than or equal to 10 percent and/or the tissue biopsy proves that the plasmacytoma exists;
2. the serum and/or urine presents monoclonal M protein a;
3. myeloma-induced related manifestations:
(1) target organ damage manifestation (CRAB) b:
[C] correcting serum calcium c to be more than 2.75 mmol/L;
[ R ] impairment of renal function (creatinine clearance 177. mu. mol/L);
[A] anemia (hemoglobin below the lower normal limit of 20 g/L);
[B] osteolytic destruction, showing 1 or more osteolytic lesions by imaging (X-ray, CT or PET ⁃ CT);
(2) no damage of target organs is shown, but the following 1 or more indexes are abnormal (SLiM) [ S ] the proportion of marrow monoclonal plasma cells is more than or equal to 60 percent d:
[ Li ] the ratio of free light chains of the affected/unaffected serum is more than or equal to 100 e;
[ M ] focal bone destruction of more than 5mm occurs at >1 site in MRI examination.
Note: a, if the amount of the M protein in blood and urine is not limited, if the M protein is not detected (MM is not secreted in diagnosis), myeloma monoclonal plasma cells are required to be more than or equal to 30 percent or the plasma cell tumor is obtained by biopsy; b other types of end organ damage also occur occasionally, further supporting diagnosis and classification if damage to these organs is confirmed to be associated with myeloma; c correcting serum calcium (mmol/L) = total serum calcium (mmol/L) -0.025 times serum albumin concentration (g/L) + 1.0 (mmol/L), or correcting serum calcium (mg/dl) = total serum calcium (mg/dl) -serum albumin concentration (g/L) + 4.0 (mg/dl); d, the monoclonality of the plasma cells can be identified by using flow cytometry, immunohistochemistry and immunofluorescence methods to identify the light chain kappa/lambda restriction expression, the bone marrow plasma cell ratio is judged to be counted by adopting a bone marrow cell smear and bone marrow biopsy method instead of flow cytometry, and when the puncture and biopsy ratios are inconsistent, a numerical value with a high plasma cell ratio is selected; e requires a number of affected light chains of at least 100 mg/L.
(II) sample detection:
1. instrument information:
name of mass spectrum: thermo Q activity, liquid phase name: DIONEX Ultimate 3000 ultra high performance liquid chromatograph.
2. Sample pretreatment: bone marrow tissues (healthy control group and MM group) were subjected to ultrasonication with ultrapure water (containing 50% methanol) at a mass/volume ratio of 1:10(w/v) to obtain a bone marrow tissue disruption solution. Respectively sucking 100 mu L of bone marrow tissue crushing liquid and bone marrow supernatant (healthy control group and MM group), adding 500 mu L of precipitator containing internal standard (methanol: acetonitrile =1:1), whirling and mixing uniformly for 30s, centrifuging at 12000rpm for 10 min, and sucking supernatant to obtain a test solution for quantitative analysis.
3. The instrument parameters are as follows:
chromatographic conditions are as follows: a: water (containing 0.1% formic acid and 2.5mM ammonium acetate), D: acetonitrile; gradient elution, wherein the gradient elution procedure is 0-0.5min and is 5% -10% of D; 0.5-1.0 min, 10% -30% D; 1.0-2.0min, 30% -95% D; 2.0-4.0 min, 95% -95% D; 4.0-4.5 min, 95-5% D, 4.5-6.0min, 5-5% D. The analysis time is 0-6.0min, 5 mu L of sample introduction is carried out each time, the flow rate is 0.3mL/min, and the chromatographic column: thermo Hypersil Gold C183 μm, 2.1X 100 mm, the column temperature was 30 ℃, and the temperature of the autosampler was maintained at 4 ℃.
Mass spectrum conditions: data were collected in electrospray ion source (ESI) positive and negative ion PRM mode, spray voltage: 3500V (+), 2500V (-); evaporation temperature: c, 350 ℃; sheath gas: 40 Arb; auxiliary gas: 10 Arb; capillary temperature: c, 350 ℃; s-lens RF: 50; NCE: 30. tolbutamide (internal standard): 269.09654/170.19791, phenylalanine: 166.08626/120.08100, tyrosine: 182.08117/136.07578, tryptophan: 205.09715/188.07057, propranolol (internal standard): 260.16451/116.10709.
(III) analyzing results:
the results of the average contents of the three metabolic markers in the bone marrow tissues and bone marrow supernatants of 20 HC (healthy controls) and 16 suspected MM patients are shown in Table 5, and the detection results and clinical diagnosis results of the bone marrow tissues and bone marrow supernatants of the 16 suspected MM patients obtained by the method are consistent, so that the accuracy of the method can reach 100%.
TABLE 5
Bone marrow supernatant Phenylalanine (ng/ml) Tyrosine (ng/ml) Tryptophan (ng/ml)
Healthy control group 61009.8±23835.3 61022.3±32404.4 56712.7±33874.2
MM group 87611.9±11688.5** 207544.2±57513.1** 92322.4±18498.1**
Bone marrow tissue Phenylalanine (ng/ml) Tyrosine (ng/ml) Tryptophan (ng/ml)
Healthy control group 1479.5±426.3 1265.0±438.0 428.7±157.3
MM group 2089.4±756.6* 1507.0±378.2 563.6±187.6*
Example 3:
cell validation analysis:
the multiple myeloma cells H929 (purchased from the cell resource center of the institute of basic medicine, national academy of medical sciences) used in this experiment were derived from pleural effusion of a 62 year old myeloma patient. H929 cells are cultured by 1640 culture medium and 10% FBS, centrifuged at 1000rpm for 5min, counted, cultured by 1640 culture medium which is normal and lacks phenylalanine, tyrosine, tryptophan, phenylalanine/tyrosine and phenylalanine/tyrosine/tryptophan respectively for 48 hours, and the survival rate of the cells is detected by CCK 8. FIG. 6 shows that the survival of H929 cells decreased significantly after the medium lacked phenylalanine, tyrosine, tryptophan, phenylalanine/tyrosine/tryptophan, respectively.
Example 4:
to verify the detection effect of the metabolic markers, the following grouping experiments were designed:
in the same manner as in example 2, the metabolic markers in the bone marrow tissue and bone marrow supernatant of 16 suspected MM patients were repeatedly tested 10 times, and the metabolic markers were grouped as follows:
1) phenylalanine alone test group;
2) a tyrosine single detection group;
3) a tryptophan separate detection group;
4) phenylalanine + tyrosine simultaneous detection group;
5) phenylalanine + tryptophan simultaneous detection group;
6) a tyrosine and tryptophan simultaneous detection group;
7) phenylalanine + tyrosine + tryptophan were detected simultaneously.
In view of individual differences, instrument and reagent errors in the detection process, and other reasons, in the detection process of the actually operated metabolic markers, missed detection is usually generated, so that adverse consequences such as delay are caused to the disease condition of the patient, and based on this, the missed detection rates of the 7 groups of metabolite detection are counted in the present embodiment, and specific results are shown in table 6.
TABLE 6
Grouping Number of missed detections in 10 replicates Rate of missed examination
Phenylalanine single detection group 3 30%
Tyrosine single detection group 2 20%
Tryptophan individual detection group 3 30%
Phenylalanine + tyrosineSimultaneous detection group 1 10%
Phenylalanine + tryptophan simultaneous detection group 2 20%
Group for simultaneously detecting tyrosine and tryptophan 2 20%
Phenylalanine + tyrosine + tryptophan simultaneous detection group 0 0%
As can be seen from table 6, simultaneous detection of three metabolic markers (amino acid composition) can effectively reduce the missed detection rate for multiple myeloma diseases.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents or improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (2)

1. Use of an amino acid composition as a metabolic marker for the manufacture of a kit for diagnosing multiple myeloma, characterized in that said amino acid composition is phenylalanine + tyrosine + tryptophan; quantitatively detecting the content level of the metabolic marker in a biological sample of a subject and judging the disease state of the multiple myeloma in the subject; the biological sample is bone marrow tissue or bone marrow supernatant;
the pretreatment mode of the biological sample before detection is as follows: mixing bone marrow tissue with ultrapure water containing 50% methanol, and ultrasonically crushing to obtain bone marrow tissue crushing liquid; respectively sucking bone marrow tissue crushing liquid and bone marrow supernatant, adding a precipitator containing an internal standard, dissolving the internal standard by using methanol and acetonitrile which are mixed in equal proportion, uniformly mixing by vortex, centrifuging, and sucking the supernatant to obtain a test solution for quantitative analysis of liquid chromatography-mass spectrometry.
2. The use according to claim 1, wherein the biological sample is pretreated before detection by: bone marrow tissue was treated with 50% methanol in ultrapure water at a ratio of 1:10, carrying out ultrasonic crushing to obtain bone marrow tissue crushing liquid; respectively sucking 100 mu L of bone marrow tissue crushing liquid and bone marrow supernatant, adding 500 mu L of precipitator containing internal standard, dissolving the internal standard by using methanol and acetonitrile which are mixed in equal proportion, uniformly mixing by vortex for 30s, centrifuging at 12000rpm for 10 min, sucking supernatant, and obtaining a test solution for quantitative analysis of liquid chromatography-mass spectrometry;
chromatographic conditions are as follows: a: water containing 0.1% formic acid and 2.5mM ammonium acetate, D: acetonitrile; gradient elution, wherein the gradient elution program is 0-0.5min and 5% -10% of D; 0.5-1.0 min, 10% -30% D; 1.0-2.0min, 30% -95% D; 2.0-4.0 min, 95% -95% D; 4.0-4.5 min, 95-5% D, 4.5-6.0min, 5-5% D; the analysis time is 0-6.0min, 5 mu L of sample introduction is carried out each time, the flow rate is 0.3mL/min, and the chromatographic column: thermo Hypersil Gold C183 mu m, 2.1 x 100 mm, chromatographic column temperature 30 ℃, automatic sample injector temperature maintained at 4 ℃;
mass spectrum conditions: data were collected in the electrospray ion source positive and negative ion PRM mode, spray voltage: 3500V positive ion mode and 2500V negative ion mode; evaporation temperature: 350 ℃; sheath gas: 40 Arb; auxiliary gas: 10 Arb; capillary temperature: 350 ℃; s-lens RF: 50; NCE: 30; phenylalanine: 166.08626/120.08100, tyrosine: 182.08117/136.07578, tryptophan: 205.09715/188.07057.
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