CN114428173A - Exosome markers for diagnosing invasive breast cancer lymph node metastasis and application thereof - Google Patents
Exosome markers for diagnosing invasive breast cancer lymph node metastasis and application thereof Download PDFInfo
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Abstract
The invention discloses a group of exosome markers for diagnosing lymph node metastasis of invasive breast cancer and application thereof, wherein the exosome markers comprise up-regulated expression protein and down-regulated expression protein; the up-regulated expression protein comprises any one or more of PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, MATR3, KRT16 and CCT 6A; the downregulated expression protein comprises any one or more of TTYH3, KPNB1 and RANBP 2. The exosome marker combination provided by the invention has high identification accuracy for distinguishing invasive breast cancer lymph node metastasis and in-situ invasive breast cancer crowds, is efficient, practical and noninvasive, can be applied to preparation of a diagnostic reagent or a kit for diagnosing the invasive breast cancer lymph node metastasis, is easy for clinical popularization of medical institutions, and can avoid excessive tissue biopsy.
Description
Technical Field
The invention belongs to the technical field of detection and diagnosis, and particularly relates to a group of exosome markers for diagnosing lymph node metastasis of invasive breast cancer and application thereof.
Background
Breast Cancer (BC) is one of the most common cancers worldwide, accounting for 30% of women's cancers, and is the second leading cause of death from female cancers following lung cancer. Invasive breast cancer is the main pathological type of breast cancer, wherein axillary lymph node metastasis is the common metastatic site of invasive breast cancer, about 40% of patients with invasive breast cancer have an initial diagnosis with ipsilateral axillary lymph node metastasis, and the more lymph nodes have metastasis, the shorter the disease-free survival period and the shorter the overall survival period of the patients. Therefore, early detection and dynamic assessment of metastatic status in breast cancer patients has important clinical value for treatment and longitudinal analysis of cancer evolution in response to treatment.
Currently, sentinel lymph node biopsy and axillary lymph node cleaning in the operation are standard methods for diagnosing the metastasis state of axillary lymph nodes, but the methods are time-consuming and invasive, bring related operation complications and influence the life quality of patients. Compared to conventional tissue biopsy, fluid biopsy using biological information detected in the patient's blood is minimally invasive, reduces complications, and improves longitudinal monitoring capabilities. More importantly, fluid biopsies are more informative than single locally-restricted biopsies, providing unique information about tumor heterogeneity, clonal evolution, and pre-metastatic development of all cancer cells.
The exosome is one of liquid biopsy means, carries a large amount of biological information (protein, mRNA, lymph node cRNA and the like) of the occurrence and development of the breast cancer, and provides a good carrier resource for diagnosing the lymph node metastasis of the breast cancer. At present, no patient blood exosome molecule with high specificity and sensitivity is used for clinical diagnosis of breast cancer lymph node metastasis.
Disclosure of Invention
In order to solve the problem that in the prior art, no patient blood exosome molecule with high specificity and sensitivity is used for clinical diagnosis of invasive breast cancer lymph node metastasis, the invention provides a group of exosome markers for diagnosing invasive breast cancer lymph node metastasis and application thereof.
Based on the above, the invention firstly provides a group of exosome markers for diagnosing invasive breast cancer lymph node metastasis, wherein the exosome markers comprise up-regulated expression protein and down-regulated expression protein; the up-regulated expression protein comprises any one or more of PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, MATR3, KRT16 and CCT 6A; the downregulation expression protein comprises any one or more of TTYH3, KPNB1 and RANBP 2.
Preferably, the exosome marker comprises: PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, TTYH3, MATR3, KPNB1, KRT16, RANBP2, and CCT 6A.
The invention also provides application of any one of the exosome markers in preparation of a reagent or a kit for diagnosing the lymph node metastasis of invasive breast cancer.
In another aspect, the present invention provides a reagent for diagnosing lymph node metastasis from invasive breast cancer, wherein the reagent is capable of detecting the expression level of any one of the exosome markers in a sample.
Preferably, the sample is a serum sample.
Preferably, the reagent determines whether a subject with invasive breast cancer has lymph node metastasis by detecting the expression level of the exosome marker in the serum of the subject.
The invention also provides a kit for diagnosing the lymph node metastasis of the invasive breast cancer, and the kit comprises the reagent.
Preferably, the kit further comprises an extraction reagent and a standard for the exosome marker of any preceding claim.
Compared with the prior art, the invention has the beneficial effects that:
(1) according to the invention, a group of proteins is excavated from a large amount of proteins for diagnosing the lymph node metastasis of invasive breast cancer through sEVs proteome analysis and differential protein molecular identification, and the exosome marker can be used for distinguishing the lymph node metastasis of invasive breast cancer and the detection and diagnosis of in-situ invasive breast cancer.
(2) The invention excavates and verifies a classifier consisting of 12 proteins based on the working procedures of DIAMS analysis, classifier construction, verification and the like, and the classifier has the advantages of good specificity, high sensitivity, high efficiency, practicability, no wound, easy clinical popularization of medical institutions and capability of avoiding excessive tissue biopsy.
Drawings
FIG. 1 shows the screening of proteins differentially expressed in IBC _ LN group and IBC _ Pure group, wherein,
a represents Principal Component Analysis (PCA) of 1116 proteins in 105 samples;
b represents the differentially expressed protein between invasive breast cancer lymph node metastasis and in situ breast cancer samples;
FIG. 2 is the results of a gene set enrichment analysis of differentially expressed upregulated proteins, wherein,
a represents GSEA of proteomic data of 105 samples showing that adipogenesis is significantly upregulated in the IBC _ LN population;
b represents a unique tumor microenvironment between IBC _ Pure and IBC _ LN;
FIG. 3 is a study of the lymph node transfer mechanism of invasive breast cancer; wherein,
a represents the comparison of scores of the Wilcoxon test of adipocytes in the IBC _ LN group and IBC _ Pure group;
b represents the comparison of scores of the Wilcoxon test of pluripotent progenitor cells of IBC _ LN group and IBC _ Pure group;
c represents the score comparison of the platelet Wilcoxon test of the IBC _ LN group and the IBC _ Pure group;
d represents the correlation between adipogenesis and adipocyte;
e represents the correlation between adipocytes and VEGF signaling pathway;
f represents the Wilcoxon test comparing the positive control score for VEGF production between IBC _ LN and IBC _ Pure;
g indicates the association of the VEGF signaling pathway with pluripotent progenitor cells;
h represents the correlation between pluripotent progenitor cells and the coagulation pathway;
i represents the correlation between platelets and the coagulation pathway;
j represents the expression profile of molecules highly associated with platelets in IBC _ Pure and IBC _ LN;
k represents a molecule highly associated with platelets;
l represents a pattern diagram of the important role of adipocytes in lymph node metastasis in invasive breast cancer.
FIG. 4 is a detection result of the classifier for distinguishing IBC _ LN people from IBC _ Pure people;
a represents the classification error matrix of the training set (70%) and the test set (30%) of 12 proteins of the random forest classifier;
b represents a classification error matrix of an external verification set of 12 proteins of the random forest classifier;
c represents the protein with the highest predictive value when random forests classify IBC _ Pure and IBC _ LN samples.
Detailed Description
The technical solution of the present invention will be further described with reference to the accompanying drawings and examples.
Description of the terms
The "exosomes", "exosome proteins", "shevs proteins", "sEV" described herein are used interchangeably.
As described above, in view of the deficiencies of the prior art, the present invention firstly provides a set of exosome markers for diagnosing lymph node metastasis of invasive breast cancer, the exosome markers comprising an up-regulated expression protein and a down-regulated expression protein;
the up-regulated expression protein comprises any one or more of PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, MATR3, KRT16 and CCT 6A;
the downregulated expression protein comprises any one or more of TTYH3, KPNB1 and RANBP 2.
In some embodiments, the exosome marker comprises: PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, TTYH3, MATR3, KPNB1, KRT16, RANBP2, and CCT 6A.
The invention also provides application of the exosome marker in preparation of a reagent or a kit for diagnosing the lymph node metastasis of invasive breast cancer.
In another aspect, the present invention provides a reagent for diagnosing lymph node metastasis of invasive breast cancer, wherein the reagent is capable of detecting the expression level of the exosome marker according to any one of the preceding items in a sample.
Preferably, the sample is a serum sample.
Preferably, the reagent determines whether a subject with invasive breast cancer has lymph node metastasis by detecting the expression level of the exosome marker in the serum of the subject.
The invention also provides a kit for diagnosing the lymph node metastasis of the invasive breast cancer, which comprises the reagent.
Preferably, the kit further comprises an extraction reagent and a standard for the exosome marker of any preceding claim.
In order to obtain exosome markers for people who correctly diagnose the lymph node metastasis of invasive breast cancer and in-situ invasive breast cancer, the exosome markers are obtained by collecting serum exosome proteins of 2 people, sEVs proteome analysis and differential protein molecule identification are carried out, and a group of markers with high sensitivity and specificity for diagnosing the lymph node metastasis of invasive breast cancer is finally provided by constructing a classifier and verifying the diagnostic performance of the classifier, wherein the specific experimental process comprises the following steps:
example 1
The process of screening for exosome markers for diagnosing lymph node metastasis of invasive breast cancer will be described in detail below.
(I) extraction and identification of exosomes
1. Collection of serum samples
Serum samples of invasive breast cancer lymph node metastasis (IBC LN group) were from 51 patients confirmed at the first human hospital in the Shanghai city affiliated with the Shanghai university of transportation medical school; serum samples of in situ invasive breast cancer (IBC Pure group) were also obtained from 54 patients at the first national hospital of Shanghai school of medicine, affiliated Shanghai university of transportation. These serum samples were placed in a-80 ℃ freezer for testing.
2. Exosome extraction
1mL of serum was thawed on ice and centrifuged at 3000rcf for 10min at 4 ℃; taking the supernatant, centrifuging for 20min by 10000g, diluting the supernatant by 25mL PBS, and filtering by a 0.22 μm centrifugal filter device to remove any large polluted vesicles; ultracentrifugation of the filtered serum at 15 ten thousand rcf for 4h, removal of the supernatant; resuspending the precipitate with 25mL PBS, centrifuging at 4 deg.C for 2h at 15 ten thousand rcf, adding 0.01M PBS to the residual 200 μ L, resuspending the precipitate, separating a small amount for exosome identification, and storing at 4 deg.C for use; storing at-80 deg.C.
3. Identification of exosomes
And for the extracted exosomes, observing and analyzing the morphology and particle size of the extracted exosomes by adopting a Transmission Electron Microscope (TEM) and Nanoparticle Tracking Analysis (NTA), wherein the NTA shows that the separated exosomes are in a uniform vesicle structure with the size range of 30-150nm, conform to the particle size range of the exosomes and are surrounded by a double-layer membrane. Meanwhile, indexes such as exosome markers CD9, CD63, TSG101 and ALIX on the surface of the protein are detected by a western blotting method, and WB results show that the separated exosomes express specific marker molecules such as CD9, CD63, TSG101 and ALIX.
(II) analysis and screening of exosome protein differential expression molecules
And performing LC-MS detection on the extracted sEVs protein to obtain a serum sEVs protein map of the subject, and performing a series of statistical analysis on the data obtained by detection.
1. Detection method
(1) Liquid chromatography: the polypeptides were separated on a 150 μm I.D.. times.15 cm column at a flow rate of 600nL/min over 75 minutes using an EASY-nLC 1200 ultra high pressure liquid chromatography system (Thermo Fisher Scientific) and a 1.9 μm repsil-pur 120C18-AQ column (Dr. Maisch) packed with a laser pull-spray emitter. Mobile phase a was water (containing 0.1 vol% formic acid) and mobile phase B was acetonitrile (containing 0.1 vol% formic acid), and mobile phase B was linearly increased from 15% to 30% over 75min for gradient elution.
(2) Mass spectrometry: the samples were analyzed by Q-exact-HF mass spectrometer (Thermo Fisher Scientific) and nanoelectrospray ion source (Thermo Fisher Scientific). The mass spectrometer was operated in data independent mode for ion mobility enhanced spectral library generation. Typically, 75% of the sample is injected. The peptide fragment was dissolved in 12 μ L (0.1% formic acid) of loading buffer, 9 μ L was loaded onto a 100 μm i.d. × 2.5cm C18 column with a maximum pressure of 280bar (hydraulic units) and solvent a of 0.1% formic acid. The DIA method includes MS1 scanning 300-1400 m/z, 60k resolution (AGC target 4e5 or 50 MS). Then, 30 DIA segments were obtained at 15k resolution with AGC targeting 5e4 or a maximum injection time of 22 ms. The "injection of all available parallel time" setting is enabled. HCD fragmentation was set at 30% normalized collision energy. The spectra were recorded in profile mode. The default charge state for the MS2 scan is set to 3.
2. Statistical analysis
(1) Peptide identification and protein quantification: all data were processed using Firmiana. The UniProt human protein database was searched for DIA data using FragPipe (v.12.1) and MSFragger (2.2). The mass deviation of the precursor was 20ppm, and the mass deviation of the product ion was 50 mmu. A maximum of two cleavage sites is allowed. The search engine uses cysteine aminomethylation as the fixed modification and N-acetylation and oxidation of methionine as the variable modification. The precursor ion score charge is limited to +2, +3, and + 4. The data was also searched with the bait database to bring the False Discovery Rate (FDR) for protein identification to within 5%.
DIA data was analyzed using DIANN (v1.7.0). The quantification of the determined polypeptide was calculated as the average chromatographic fragment ion peak area of all reference spectral libraries. The label-free protein quantification was calculated using the label-free, intensity-based absolute quantification (iBAQ) method. We calculated peak area values as part of the corresponding protein. The total ratio (FOT) is used to represent the normalized abundance of a particular protein in a sample. FOT is defined as the iBAQ of one protein divided by the total iBAQ of all identified proteins in one sample. For ease of illustration, the FOT value is multiplied by 105The deficiency value is classified as 10-5. The raw proteomics data file is hosted by iProX.
(2) Statistical analysis: to enter proteomic data, we first screened more than 50% of the identified proteins in each group and split the data into two parts. When the protein detection rate was < 50%, the deletion value was replaced by one tenth of the minimum value. There is no application liability for these proteins. When the protein detection rate is > 50%, the missing value may be due to the limitation of the LC/MS detection accuracy. In this case, the deletion probability of a protein is first calculated using the R package "impute" based on the K-NN algorithm. Survival marker discovery and validation based on meta-analysis was performed using a Kaplan-Meier plotter.
(3) Principal Component Analysis (PCA): the input data was normalized using the LogNorm algorithm. And realizing unsupervised clustering analysis by using a PCA function of the R packet 'factextratra'. The 95% confidence coverage is represented by a colored ellipse for each group and is calculated based on the mean and covariance of the different group points.
(4) Global heatmap: in all samples, each gene expression value in the global proteome expression matrix was converted to z-score. The z-score transformed matrix is clustered using the R-package "pheatmap".
(5) And (3) path enrichment analysis: pathway enrichment analysis was performed using DAVID and consensus spathdb, with categorical annotation by Fisher's exact test according to KEGG, GOBP and Reactome.
3. Results
(1) Screening for differentially expressed proteins
The present application first constructed a proteomic profile of serum sEV and identified 1116 proteins from 105 samples analyzed, with a False Discovery Rate (FDR) of less than 5% at the protein and peptide levels. PCA was further used to observe the population distribution between samples, with the results shown in a of fig. 1: PCA clearly distinguished samples of both populations at the protein level, highlighting the different proteomic patterns between sEV in the invasive breast cancer lymph node metastasis samples and in situ invasive breast cancer samples.
Further comparative screening was performed using Student's t-test and nominal p-value cut-off, 30 significantly differentially expressed sEVs-derived proteins were identified in invasive breast cancer lymph node samples (fold change >2, Student's t-test p <0.05), and the results were visualized using a volcano plot, as shown in B of FIG. 1: there are 18 proteins with significant up-regulation, such as COL15a1, ESYT1, PEPD, CCT6A, ACAN, GAA, ACTA2, ACTG2, MATR3, PAPR1, etc., and 12 proteins with significant down-regulation, such as STX7, KPNB1, TTYH3, GSPG4, ZYX, VDAC1, RRPB1, RANBP2, etc.
(2) Gene set enrichment analysis of differentially expressed upregulated proteins
Further clustering and cluster-specific enrichment analysis of up-regulated proteins using Gene Set Enrichment Analysis (GSEA) resulted in the finding that the lymph node metastasis samples from invasive breast cancer are characterized by proteins that correlate with adipogenesis characteristics (a of fig. 2).
Based on the above findings, in order to elucidate the mechanism of lymph node metastasis in invasive breast cancer, the present application also studies the immune landscape of in situ invasive breast cancer and lymph node metastasis of invasive breast cancer: based on sEV proteomic data extracted from the blood of the aforementioned 105 invasive breast cancer samples, the abundances of 16 different cell types were calculated using xCell (a tool that calculates their individual cell type enrichment scores from gene expression profiles). As a result, it was found that B cells, basophils, CD4 were present in the group of in situ invasive breast carcinomas+T cell, CD4+The enrichment fraction of naive T cells, DCs, mesangial cells, activated dendritic cells (aDCs) and Immature Dendritic Cells (iDCs) is higher than that of the lymph node metastasis group of invasive breast cancer; on the other hand, Adipocytes (Adipocytes), CD8, in the lymph node metastasis group of invasive breast cancer+T cell, CD8+The enrichment fraction of primitive T cells, pluripotent progenitors (MPPs), macrophages, megakaryocytes, Platelets (Platelets) and sebocytes was higher than that of the in situ invasive breast cancer group (fold change)>1.5 Student T test p<0.05) (B of fig. 2 and A, B, C of fig. 3).
Among them, the increase in the fat cell enrichment fraction in the invasive breast cancer lymph node metastasis group attracts the attention of the applicant of the present invention, and furthermore, Spearman correlation analysis was performed on the cells with increased enrichment fraction and adipogenesis, VEGF signaling pathway, coagulation pathway, and the like. As a result, it was found that there was a positive correlation between adipogenesis and adipocytes (Spearman rho 0.188, p 5.507 e)-02) (D of FIG. 3); adipocytes were associated with VEGF signaling pathway (E of FIG. 3), and VEGF signaling pathway was upregulated in the lymph node metastasis group of invasive breast cancer (F of FIG. 3); in addition, VEGF signaling pathway is associated with pluripotent progenitor cells (MPPs) (G of FIG. 3), MPPs inUp-regulated in the lymph node metastasis group of invasive breast cancer and positively correlated with the coagulation pathway (Spearman rho 0.295, p 2.216 e)-03) (H of fig. 3); meanwhile, platelets are positively correlated with the coagulation pathway (Spearman rho 0.209, p 3.225 e)-02) (I in FIG. 3), the platelet-rich fraction in the lymph node metastasis group of invasive breast cancer appeared to be up-regulated. Platelets have been shown to be active participants in all steps of tumorigenesis, including cancer growth, cancer cell extravasation and metastasis, and the Spearman-related analysis of the invention has also found that: many of the molecules highly associated with platelets are angiogenesis and metastasis associated molecules (e.g., PLCB2, ATP6V1C1, BCAP31, GP6, GP5, ANXA3, NCKAP1, VWF, PARK7, MMP3, etc.) (J and K of fig. 3).
Based on the results of the Spearman correlation analysis described above, we speculate that: adipocytes play an important role in lymph node metastasis of invasive breast cancer, and the mechanism that leads to lymph node metastasis of invasive breast cancer is shown in L of FIG. 3, which is a schematic diagram showing that adipocytes activate MPPs by positively regulating VEGF production and finally promote platelet production, which helps breast cancer cells migrate to lymph nodes.
Example 2 creation and validation of classifiers
Based on the research, the invention adopts a random forest classification method to construct a molecular classifier for distinguishing the lymph node metastasis of the invasive breast cancer and the in-situ invasive breast cancer, and introduces the 30 sEVs protein data with significant differential expression into a random forest classification model so as to determine the sEVs protein subset for accurately distinguishing the lymph node of the invasive breast cancer and the pure compartment of the invasive breast cancer. For training and subsequent testing of the model, the aforementioned sEVs samples of 2 types of population were first evenly divided, with 70% of the samples used as the training set and the remaining 30% used as independent test sets.
The results are shown in FIG. 4: the combination of 12 sEV proteins (PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, MATR3, KRT16, CCT6A, TTYH3, KPNB1 and RANBP2) was applied to a training set for 5-fold cross validation, and a classifier with an optimal recognition effect on invasive breast cancer lymph node metastasis and in situ invasive breast cancer lymph node metastasis was constructed, with a sensitivity of 100% and a specificity of 100% in diagnosing invasive breast cancer lymph node metastasis (A, C in FIG. 4). When these 12 protein identifiers were applied to sEV samples of the independent test set, the model achieved 81% sensitivity and 81% specificity in diagnosing lymph node metastasis from invasive breast cancer (FIG. 4A).
In addition, the present invention also used the CPTAC breast cancer data set (n ═ 80) as an external validation test set, and obtained a sensitivity of 97% and a specificity of 97% (B of fig. 4).
In conclusion, a group of exosome markers for diagnosing invasive breast cancer lymph node metastasis is excavated from a large number of proteins through sEVs proteome analysis and differential protein analysis, and the diagnosis performance of the markers is verified through constructing a classifier.
While the present invention has been described in detail with reference to the preferred embodiments, it should be understood that the above description should not be taken as limiting the invention. Various modifications and alterations to this invention will become apparent to those skilled in the art upon reading the foregoing description. Accordingly, the scope of the invention should be determined from the following claims.
Claims (8)
1. A set of exosome markers for diagnosing invasive breast cancer lymph node metastasis, the exosome markers comprising an up-regulated expression protein and a down-regulated expression protein;
the up-regulated expression protein comprises any one or more of PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, MATR3, KRT16 and CCT 6A;
the downregulated expression protein comprises any one or more of TTYH3, KPNB1 and RANBP 2.
2. The set of exosome markers for diagnosing invasive breast cancer lymph node metastasis according to claim 1, comprising: PEPD, NCL, PARP1, ACTA2, ACTG2, TBCA, TTYH3, MATR3, KPNB1, KRT16, RANBP2, and CCT 6A.
3. Use of an exosome marker according to any one of claims 1-2 in the preparation of a reagent or kit for diagnosing lymph node metastasis from invasive breast cancer.
4. An agent for diagnosing lymph node metastasis from invasive breast cancer, wherein the agent is capable of detecting the expression level of the exosome marker according to any one of claims 1-2 in a sample.
5. The reagent for diagnosing lymph node metastasis from invasive breast cancer according to claim 4, wherein said sample is a serum sample.
6. The reagent of claim 5, wherein the reagent is used for determining whether a lymph node metastasis occurs in a subject with invasive breast cancer by detecting the expression level of the exosome marker in the serum of the subject.
7. A kit for diagnosing lymph node metastasis of invasive breast cancer, comprising the reagent according to claim 4.
8. The kit of claim 7, further comprising an extraction reagent and a standard of the exosome marker of any of claims 1-2.
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