Use of reagents for detecting blood metabolites in the manufacture of a product for diagnosing colorectal cancer

Abstract

The application belongs to the technical field of disease diagnosis reagents, and particularly relates to application of a reagent for detecting blood metabolites in preparation of a product for diagnosing colorectal cancer, wherein the blood metabolites include one or more of BNO3, BP01, TLCA or LCA. The blood metabolites can distinguish healthy people from colorectal lesion patients, and can be used as a colorectal cancer diagnosis marker.

Description

Technical Field

[0001] This invention belongs to the field of disease diagnostic reagent technology, specifically relating to the application of a reagent for detecting blood metabolites in the preparation of products for diagnosing colorectal cancer. Background Technology

[0002] Colorectal cancer (CRC) is a common malignant tumor and one of the leading causes of death among cancer patients. Currently, colonoscopy is the primary method for CRC diagnosis and screening, but its invasiveness and patient compliance limit its widespread application. Fecal occult blood testing is a simple and rapid CRC screening method, and CEA is also a commonly used serological marker for CRC; however, their sensitivity and specificity still need improvement.

[0003] With the development of metabolomics analysis technology, metabolic markers identified by liquid chromatography-mass spectrometry (LC-MS / MS) are expected to become new indicators for colorectal cancer, such as lipid metabolites like fatty acids and bile acids.

[0004] Because blood metabolites have better advantages than fecal metabolites in terms of sample collection and direct influence from diet, the clinical application of blood metabolites in colorectal cancer has received more attention. Summary of the Invention

[0005] This invention has discovered that blood metabolites (one or more of BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BPO1 (myristoyl L-carnitine), TLCA (taurolcite) or LCA (lithocholic acid)) are related to the occurrence and development of colorectal cancer and can be used as markers for the diagnosis of colorectal cancer.

[0006] To achieve the above objectives, the present invention can adopt the following technical solutions:

[0007] In one aspect, this invention provides the application of a reagent for detecting blood metabolites in the preparation of products for diagnosing colorectal cancer, wherein the blood metabolites include one or more of BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BPO1 (myristoyl L-carnitine), TLCA (taurolcite), or LCA (lithocholic acid).

[0008] Preferably, in the above applications, the reagent for detecting blood metabolites is a reagent based on the LC-MS / MS detection method.

[0009] Preferably, in the above applications, the blood metabolites include BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone) and LCA (lithocholic acid).

[0010] Preferably, in the above applications, the colorectal cancer is in the abnormal stage of colorectal cancer, stage I colorectal cancer, or stage II colorectal cancer.

[0011] Preferably, in the above applications, the product is a test kit or test reagent.

[0012] The present invention also provides a system for diagnosing colorectal cancer, comprising:

[0013] The analysis unit is used to obtain the results of the subject's biomarkers, which include one or more of BN03 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BP01 (myristoyl L-carnitine), TLCA (taurol lithocholic acid), or LCA (lithocholic acid).

[0014] The assessment unit is used to assign corresponding assessment scores to the obtained biomarkers to obtain a total score; the output unit is used to output the subject's colorectal cancer diagnosis status based on the total score obtained by the assessment unit.

[0015] Preferably, in the above system, the biomarkers are BN03 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BP01 (myristoyl L-carnitine), TLCA (taurolliculic acid), and LCA (lithocholic acid); the total score y = (-8.24) + 2.0456 × BN03 + 0.0730 × BP01 + (-0.0078) × LCA + (-0.2206) × TLCA.

[0016] Preferably, the biomarkers in the above system also include CEA (carcinoembryonic antigen).

[0017] Preferably, the colorectal cancer in the above system is in the abnormal stage of colorectal cancer, stage I colorectal cancer, or stage II colorectal cancer.

[0018] The beneficial effects of this invention include:

[0019] (1) When BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone) was used as a marker for the diagnosis of colorectal cancer, the area under the curve (AUC) for distinguishing colorectal lesions from apparent healthy individuals was 0.930 (95% CI: 0.899–0.962), and the AUC for distinguishing early colorectal cancer, high-risk adenomas from low-risk adenomas, and apparent healthy individuals was 0.882 (95% CI: 0.836–0.927). With a cutoff value of 3.865 ng / ml, its sensitivity and specificity were 85.62% and 91.95%, respectively, which were higher than the AUC of carcinoembryonic antigen (CEA) (0.778, 95% CI: 0.718–0.838).

[0020] (2) When BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone) was used in combination as a marker for the diagnosis of colorectal cancer by CEA, the sensitivity and specificity reached 89.31% and 85.87%, respectively.

[0021] (3) When LCA (lithocholic acid) is used as a marker for the diagnosis of colorectal cancer, the sensitivity is 50.33% and the specificity is 96.55% when LCA exceeds 88.09 ng / mL.

[0022] (4) When BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone) was combined with LCA (lithocholic acid) as a marker for the diagnosis of colorectal cancer, the sensitivity and specificity were improved to 86.93% and 89.66%, respectively, which was better than LCA alone as a marker. Attached Figure Description

[0023] Figure 1 The concentrations of BN03, BPO1, TLCA, and LCA in CRC patients;

[0024] Figure 2 The detection results of different markers combined;

[0025] Figure 3 This serves as a metabolic model for patients with colorectal abnormalities and healthy individuals. Detailed Implementation

[0026] The embodiments described are provided to better illustrate the present invention, but are not intended to limit the scope of the invention to the embodiments described. Therefore, non-essential improvements and adjustments made to the embodiments by those skilled in the art based on the above description are still within the scope of protection of the present invention.

[0027] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. Singular expressions include plural expressions unless they have a distinct meaning in the context. As used herein, it should be understood that terms such as “comprising,” “having,” “including,” are intended to indicate the presence of features, numbers, operations, components, parts, elements, materials, or combinations thereof. The terminology of the invention is disclosed in the specification and is not intended to exclude the possibility that one or more other features, numbers, operations, components, parts, elements, materials, or combinations thereof may be present or added. As used herein, “ / ” may be interpreted as “and” or “or,” depending on the context.

[0028] This invention provides an application of a reagent for detecting blood metabolites in the preparation of products for diagnosing colorectal cancer. The blood metabolites include one or more of BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BPO1 (myristoyl L-carnitine), TLCA (taurolcite), or LCA (lithocholic acid).

[0029] It should be noted that this invention found that, compared with healthy individuals, the concentrations of BN03, BPO1, TLCA, and LCA were significantly elevated in CRC (colorectal cancer) patients, indicating that BN03, BPO1, TLCA, and LCA can serve as biomarkers for diagnosing colorectal cancer. Among them, BN03 showed the best performance, with an area under the curve (AUC) of 0.930 (95% CI: 0.899-0.962) in distinguishing between colorectal lesions and apparent healthy individuals, and an AUC of 0.882 (95% CI: 0.836-0.927) in distinguishing between early colorectal cancer (including stage I and II), high-risk adenomas (which can be considered precancerous lesions), low-risk adenomas (which have a certain potential for malignant transformation), and apparent healthy individuals. With a cutoff value of 3.865 ng / ml, its sensitivity and specificity were 85.62% and 91.95%, respectively. In addition, this invention establishes a method for detecting lipid metabolites in serum based on LC-MS / MS and confirms that the detection performance meets CLSI requirements.

[0030] In some specific examples, in the above applications, the reagents for detecting blood metabolites are reagents based on LC-MS / MS detection methods.

[0031] It should be noted that the reagents used in this invention for detecting blood metabolites are all reagents known in the art that can detect the above-mentioned blood metabolites in blood samples, such as reagents based on LC-MS / MS detection methods, such as mobile phases or buffer solutions.

[0032] It should also be noted that LC-MS / MS is a commonly used method for metabolite analysis and can simultaneously measure multiple metabolites; blood metabolites identified by LC-MS / MS have a sensitivity of up to 93.6% and a specificity of up to 80.2% for CRC diagnosis.

[0033] In some specific examples, the blood metabolites mentioned above include BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone) and LCA (lithocholic acid).

[0034] It should be noted that the present invention found that when BN03 is combined with LCA as a biomarker for the diagnosis of colorectal cancer, the sensitivity and specificity are improved to 86.93% and 89.66%, respectively, which is superior to LCA alone as a biomarker.

[0035] In some specific examples, the colorectal cancer mentioned above is referred to as colorectal abnormality stage, stage I colorectal cancer, or stage II colorectal cancer.

[0036] In some specific examples, the products in the above applications are test kits or test reagents.

[0037] It should be noted that the product for diagnosing colorectal cancer in this invention can be a test kit or a test reagent, generally a test kit, which is easier to transport and store.

[0038] This invention also provides a system for diagnosing colorectal cancer, comprising:

[0039] The analysis unit is used to obtain the results of the subject's biomarkers, which include one or more of BN03 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BP01 (myristoyl L-carnitine), TLCA (taurol lithocholic acid), or LCA (lithocholic acid).

[0040] The evaluation unit is used to assign corresponding evaluation scores to the obtained markers to obtain a total score; the output unit is used to output the colorectal cancer diagnosis status of the subject based on the total score obtained by the evaluation unit.

[0041] In some specific examples, the biomarkers in the above system are BN03 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BP01 (myristoyl L-carnitine), TLCA (taurolactic acid), and LCA (lithocholic acid); the total score y = (-8.24) + 2.0456 × BN03 + 0.0730 × BP01 + (-0.0078) × LCA + (-0.2206) × TLCA.

[0042] In some specific examples, the biomarkers in the above systems also include CEA.

[0043] It should be noted that when the CEA cutoff value is 5 ng / ml, the sensitivity and specificity are 33.33% and 98.85%, respectively; when BN03 is combined with the CEA index, the sensitivity and specificity reach 89.31% and 85.87%, respectively.

[0044] It should also be noted that this invention establishes a method for detecting lipid metabolites in serum based on LC-MS / MS and confirms that the detection performance meets CLSI requirements. It was also found that the combined detection of BNO3 and CEA can improve the detection sensitivity.

[0045] In some specific examples, the colorectal cancer in the above system is in the abnormal stage of colorectal cancer, stage I colorectal cancer, or stage II colorectal cancer.

[0046] To better understand the present invention, specific examples are provided below to further illustrate the content of the present invention, but the content of the present invention is not limited to the examples below.

[0047] In the following examples, HPLC-grade acetonitrile (ACN), methanol (MeOH), isopropanol (IPA), ammonium formate, and formic acid (FA) were purchased from Thermo Fisher Scientific. Deionized water (>18.2 mC) was from Watsons; lithocholic acid (GLCA), glycocholic acid (GCA), deoxycholic acid (DCA), cholic acid (CA), tauride-deoxycholic acid (TUDCA), ursodeoxycholic acid (UDCA), tauride-deoxycholic acid (TCA), glycodeoxycholic acid (GCDCA), tauride-deoxycholic acid monohydrate (GDCA), lithocholic acid (LCA), chenodeoxycholic acid (CDCA), glycodeoxycholic acid (GUDCA), (±) 15-HETE (BN01), 12,13-D iHome (BN02), 9, 12, 13-TriHOME (BN03), myristoyl-L-carnitine (BP01), trans-2-octanoyl-L-carnitine (BP02), trans-2-hexadecene-1-L-carnitine (BP03), and (±)-hexenoyl chloride (BP04) were obtained from Shanghai Yuanye Biotechnology, AlfaAesar, China National Institutes for Food and Drug Control, zzstandard, BePuro, ISOREAG, MCE, Sigma, and TRC, respectively; and purchased from ISOREAG and BePure.

[0048] In the following examples, the 22 blood metabolites are GLCA, GCA, DCA, CA, TUDCA, TCA, TDCA, GCDCA, TCDCA, GDCA, LCA, CDCA, GUDCA, TLCA, BN01, BN02, BN03, BP01, BP02, BP03, and BP04; specific information is shown in Table 1 below.

[0049] Table 122 Information on Blood Metabolites

[0050] Metabolites English name Chinese name GLCA Lithocholylglycine Lithochoylglycine GCA glycocholic acid Glycinecholic acid DCA deoxycholicacid Deoxycholic acid CA cholicacid cholic acid TUDCA tauroursodeoxycholicacid Tauroursodeoxycholic acid UDCA ursodeoxycholicacid Ursodeoxycholic acid TCA taurocholicacid Taurolcholic acid TDCA taurodeoxycholicacid Taurine deoxycholic acid GCDCA glycochenodeoxycholicacid Glycine chenodeoxycholic acid TCDCA taurochenodeoxycholicacid Taurine chenodeoxycholic acid GDCA glycodeoxycholicacidmonohydrate Glycine deoxycholic acid monohydrate LCA lithocholicacid Lithocholic acid CDCA chenodeoxycholicacid chenodeoxycholic acid GUDCA glycoursodeoxycholicacid Glycineursodeoxycholic acid TLCA Taurolithocholicacid Taurol cholic acid BN01 (±)15-HETE 15-Hydroxyeicosatetraenoic acid BN02 12,13-DiHOME 12,13-Dihydroxy-9-octadecenoic acid lactone BN03 9,12,13-TriHOME 9,12,13-Trihydroxy-9-octadecenoic acid lactone BP01 myristoyl-L-carnitine Myristoyl L-carnitine BP02 trans-2-octenoyl-L-carnitine trans-2-octenyl L-carnitine BP03 trans-2-hexadecenoy-1-L-carnitine trans-2-hexadecenoyl-L-carnitine BP04 (±)-hexanoylcamitine chloride (±)-Hexanoylcarnitine chloride

[0051] In the following example, serum metabolites were detected according to the following steps:

[0052] (1) Sample preparation: Serum metabolite extraction: Add 10 μL of internal standard mixture (internal standard mixture of the above metabolites, which is the isotopic labeling substance corresponding to these compounds) to 80 μL of serum, add 150 μL of acetonitrile and isopropanol mixture (acetonitrile and isopropanol volume ratio 4:1, Thermo Fisher) and 50 μL of ammonium formate (0.5 g / mL), vortex centrifuge at 17949×g for 10 min, and dilute 60 μL of supernatant with 150 μL of HPLC grade water before use.

[0053] (2) Liquid Chromatography-Mass Spectrometry Tandem Analysis Procedure: LC-MS / MS was performed using ABSCIEXTripleQuad TM 4500 system; injection volume for each mode was 10 μL; mass spectrometry parameters (see Table 2 below) for each metabolite were optimized by electrospray ionization (ESI) in positive and negative ion modes by infusion of the corresponding standards. Serum metabolites were eluted from a Shim-packvelox column (C18, 2.7 μm, 50 x 2.1 mm) at a flow rate of 0.075 mL / min; gradient elution was performed using mobile phase A (water containing 0.1% formic acid) and mobile phase B (acetonitrile containing 0.1% formic acid): 0–0.2 min: 25% B phase, 0.2–0.8 min: 25%–40% B phase, 0.8–2 min: 40%–45% B phase, 2–2.5 min: 45%–60% B phase, 2.5 min–3.6 min: 60%–70% B phase.

[0054] 3.6 min - 5 min: 70% - 98% B phase; 5 min - 5.1 min: 98% - 25% B phase; the metabolite peaks were integrated using Sciex Analyst 1.6.3 and multiQuant 3.0.2 software.

[0055] Table 2 Mass spectrometer parameters for each metabolite

[0056]

[0057]

[0058] In the following examples, statistical analyses were performed as follows: normally distributed data are presented as mean ± standard deviation, and non-normally distributed results are presented as median ± interquartile range; the Shapiro-Wilk test was used for normal distributions. Pairwise comparisons among the three groups of non-normally distributed data were performed using the Kruskal-Wallistest test, with post-hoc Bonferroni correction; statistical analysis and plotting were performed using GraphPadPrism (9.5) or R; *, p < 0.05; **, p < 0.01; ***, p < 0.001; n, no significance.

[0059] In the following example, serum metabolite extraction includes: adding 10 μL of internal standard mixture to 80 μL of serum (or blank matrix plasma), adding 150 μL of acetonitrile:isopropanol (volume ratio 4:1, Thermo Fisher) and 50 μL of ammonium formate (0.5 g / mL), centrifuging at 17949 × g for 10 min, and diluting 60 μL of supernatant with 150 μL of HPLC-grade water before use.

[0060] I. Biomarker Screening

[0061] This invention analyzed blood metabolites from serum samples of 50 colorectal cancer patients and healthy controls who visited the Cancer Hospital of the Chinese Academy of Medical Sciences (CICAMS) between March and July 2024. The results showed that, compared with healthy individuals, the concentrations of BN03, BPO1, TLCA, and LCA were significantly elevated in CRC patients, indicating that BN03, BPO1, TLCA, and LCA have the potential to serve as biomarkers for diagnosing CRC patients.

[0062] II. Marker Validation

[0063] (a) Clinical specimens

[0064] Serum samples were collected from 247 patients with colorectal cancer who visited the Cancer Hospital of the Chinese Academy of Medical Sciences (CICAMS) between March and July 2024, and from healthy controls (different from the 50 samples screened for the aforementioned biomarkers). The samples were stored at -80℃ before testing, and the CEA test results for each individual were recorded. All patients with colorectal cancer were newly diagnosed and untreated, and those with secondary colorectal cancer or a history of other tumors were excluded. Baseline characteristics of all patients and apparent healthy controls are shown in Table 3.

[0065] Table 3 Baseline characteristics of all patients and apparent healthy controls

[0066] CRC (N=117) CRA (N=36) NC (N=87) Gender Male 75 18 48 Female 42 18 39 Age (Average ± SD) 61.55±11.33 64.08±10.11 52.79±12.59 Stage I-II 28 III-IV 32 unknow 57

[0067] The concentrations of 18 blood metabolites (BN02, BN03, BPO1, BPO4, CA, DCA, CDCA, GCA, GUDCA, GLCA, TCA, TDCA, TCDCA, TUDCA, and TLCA) in 247 samples were detected using the aforementioned serum metabolite detection method. The results showed that all these serum metabolites met the standards for linear range, limit of quantitation, precision, and accuracy. Furthermore, compared with healthy individuals, the concentrations of BN03, BPO1, TLCA, and LCA in CRC patients were significantly increased (P<0.05, see Table 4). Figure 1This indicates that BN03, BP01, TLCA, and LCA can serve as biomarkers for diagnosing CRC patients.

[0068] Table 4. Concentrations of BN03, BPO1, TLCA, and LCA in CRC patients.

[0069] blood metabolites NC AA CRC BN03 2.05-5.26 5.77(4.10-10.68) 7.65(4.29-10.72) BP01 4.42-15.27 12.23(7.79-16.07) 11.16(7.87-14.35) TLCA 0.00-4.61 0.98(0.00-1.51) 1.24(0.40-1.87) LCA 0.00-121.40 40.76(0.00-325.50) 103.80(22.06-346.40)

[0070] (II) AUC Value Calculation

[0071] The AUC values ​​of the four biomarkers (BN03, BP01, TLCA, and LCA) were analyzed separately. The results showed that among these four differentially expressed metabolites, BN03 had the area under the curve (AUC) of 0.930 (95% CI: 0.899–0.962) distinguishing between colorectal abnormalities and normal controls (NC), which was higher than that of carcinoembryonic antigen (CEA) (0.778, 95% CI: 0.718–0.838). Figure 2 A); In addition, the AUC of BN03 in distinguishing early CRC (stage I / II) from NC was 0.825 (95% CI: 0.759–0.869). Figure 2 B). Furthermore, adenomas can be classified into high-grade and low-grade adenomas, with high-grade adenomas being more likely to progress to CRC and requiring greater clinical intervention. In differentiating between colorectal abnormalities and non-colorectal nephropathy (NC), BN03 had an AUC of 0.882 (95% CI: 0.759–0.869), superior to CEA (AUC: 0.783, 95% CI: 0.723–0.842). Figure 2 C).

[0072] (III) Combined analysis of metabolites and CEA based on LC-MS / MS technology

[0073] To further explore the clinical efficacy of BN03 in combination with other indicators, the ability of BN03, LCA, and CEA to distinguish between colorectal abnormalities and healthy individuals at their respective cutoff values ​​was analyzed. The results showed:

[0074] like Figure 2 As shown in Figure D, when BNO3 exceeds the critical value of 3.865 ng / mL, the sensitivity is 85.62% and the specificity is 91.95%; when LCA exceeds 88.09 ng / mL, the sensitivity is 50.33% and the specificity is 96.55%; when CEA reaches the critical value of 5 ng / mL, the sensitivity is 33.33% and the specificity is 98.85%. The combined analysis of BNO3 and LCA improves the sensitivity and specificity to 86.93% and 89.66%, respectively, which is superior to using LCA alone; when BNO3 is used in combination with CEA, the sensitivity is 89.31% and the specificity is 85.87%.

[0075] In addition, such as Figure 2 As shown in Figure E, among 86 CEA-negative CRC patients, 72 showed elevated BNO3 levels; among 22 BNO3-negative CRC patients, 8 showed elevated CEA levels. Therefore, the combined analysis of BNO3 and CEA improved the sensitivity and specificity of CRC detection.

[0076] (iv) Construction of metabolic characteristics

[0077] A metabolic model was constructed using LASSO regression analysis to distinguish between patients with colorectal abnormalities and healthy individuals. Figure 3 The metabolic model formula is as follows: y=(-8.24)+2.0456×BN03+0.0730×BP01+(-0.0078)×LCA+(-0.2206)×TLCA; where BN03, BP01, LCA and TLCA are the corresponding detection concentrations; the coefficients of each metabolite were calculated using the R software package "glmnet".

[0078] The model's AUC for distinguishing colorectal abnormalities from colorectal necrotic syndrome (NC) was 0.939 (95% CI: 0.907–0.970), with a sensitivity of 92.00% and a specificity of 87.00%. Furthermore, the AUC for the model constructed using four metabolites, combined with CEA analysis, was 0.969 (95% CI: 0.949–0.988), with a sensitivity of 92.00% and a specificity of 90.70%. These results indicate that combined analysis of CRC-related blood metabolites quantified by LC-MS / MS technology can improve the accuracy of colorectal abnormality diagnosis.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. Application of reagents for detecting blood metabolites in the preparation of products for differentiating colorectal cancer from healthy subjects, wherein the blood metabolites are BNO3 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BP01 (myristoyl L-carnitine), TLCA (taurolcite), and LCA (lithocholic acid); and the colorectal cancer is defined as colorectal abnormality, stage I, or stage II.

2. The application according to claim 1, characterized in that, The reagents for detecting blood metabolites are based on the LC-MS / MS detection method.

3. The application according to claim 1 or 2, characterized in that, The product is a test kit or test reagent.

4. A system for distinguishing between colorectal cancer patients and healthy subjects, characterized in that, include: The analysis unit is used to obtain the results of the subjects' biomarkers, which are BN03 (9,12,13-trihydroxy-9-octadecenoic acid lactone), BP01 (myristoyl L-carnitine), TLCA (taurol lithocholic acid) and LCA (lithocholic acid). An evaluation unit is used to assign a corresponding evaluation score to the obtained marker to obtain a total score. The total score y = (-8.24) + 2.0456 × BN03 + 0.0730 × BP01 + (-0.0078) × LCA + (-0.2206) × TLCA; The output unit is used to output the subject's colorectal cancer diagnosis based on the total score obtained from the evaluation unit. Colorectal cancer is classified into stage I (abnormal colorectal stage), stage II (colorectal cancer stage), or stage II (colorectal cancer stage).

5. The system according to claim 4, characterized in that, Biomarkers also include CEA.

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