CN116769919A - Specific tumor cell molecular marker composition for promoting ovarian cancer metastasis and application thereof - Google Patents
Specific tumor cell molecular marker composition for promoting ovarian cancer metastasis and application thereof Download PDFInfo
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- CN116769919A CN116769919A CN202310912767.0A CN202310912767A CN116769919A CN 116769919 A CN116769919 A CN 116769919A CN 202310912767 A CN202310912767 A CN 202310912767A CN 116769919 A CN116769919 A CN 116769919A
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Abstract
The application discloses a specific tumor cell molecular marker composition for promoting ovarian cancer metastasis and application thereof, and the application discovers that a group of tumor cell subgroups taking expressed S100A9 as a main characteristic exist in-situ tissues and metastatic tissues of ovarian cancer, and the tumor cell subgroup is positively correlated with the bad prognosis of ovarian cancer patients, and identifies the specific tumor cell molecular marker composition for promoting ovarian cancer metastasis: the S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48 genes are all expressed in a specific and significant manner. Inhibition of these molecular markers can significantly inhibit proliferation and metastasis of ovarian cancer cells in vitro, as well as malignant growth in vivo. The inhibitor can be used for preparing a pharmaceutical composition for preventing or treating ovarian cancer metastasis, and can be used for clinical applications such as gene therapy, drug therapy and the like of ovarian cancer. In addition, the kit provided by the application is used for auxiliary diagnosis and prognosis prediction analysis of ovarian cancer metastasis, and has important guiding significance for subsequent clinical treatment.
Description
Technical Field
The application relates to the technical field of tumor molecular biology, in particular to a tumor cell subset with S100A9 expression as a main characteristic, and further relates to application of a specific tumor cell molecular marker composition for promoting ovarian cancer metastasis.
Background
Ovarian cancer is one of the common malignant tumors of female reproductive organs, and the mortality rate is high at the top. According to the global cancer burden data issued by the international cancer research institute of the world health organization in 2021, the new occurrence of the global ovarian cancer is about 31 ten thousand, and the death cases are over 20 ten thousand, so that the life and the health of women are seriously threatened. Because the incidence of ovarian cancer is hidden, more than 70% of patients are found to be in late stage and abdominal cavity multi-site metastasis occurs more often, thus greatly impeding the feasibility and safety of the operation. The current treatment means is unsatisfactory, the survival rate of patients in the advanced stage for 5 years is always less than 40%, but the survival rate of patients without combined transfer for 5 years can reach more than 90%. The easy occurrence and metastasis of the ovarian cancer are important reasons for restricting the survival rate of patients with the ovarian cancer to be improved, and are also difficult treatment problems faced by clinicians. Thus, effective suppression of metastasis of ovarian cancer would help improve the poor prognosis of ovarian cancer patients.
The single-cell sequencing technology is a current hot spot research means, has obvious advantages compared with the traditional sequencing technology in the aspects of exploring tumor cell heterogeneity and cancer cell evolution track, analyzing complex tumor microenvironment, analyzing the interaction of tumor cells with tumor microenvironment cells such as interstitial cells, immune cells and the like, and is one of the major scientific breakthroughs of 2018 year 10. However, studies on ovarian cancer metastasis based on single cell sequencing remain to be explored further. Therefore, the patent study carries out deep single-cell transcriptome sequencing on tumor primary sites of 18 ovarian cancer primary patients and/or tumor tissues (34 samples in total) of different metastasis sites, and establishes high-resolution ovarian cancer in-situ and metastasis cell maps. The basic exploration of the ovarian cancer is assisted by utilizing a single cell sequencing technology, and the molecular characteristics of ovarian cancer metastasis are combined, so that the key tumor cell population in the disease evolution process is explored, the accurate targeted treatment is hopeful, and finally, the survival ending of an ovarian cancer patient is improved.
Disclosure of Invention
The application aims at overcoming the defects of the prior art and provides a specific tumor cell molecular marker composition for promoting ovarian cancer metastasis and application thereof.
The aim of the application is realized by the following technical scheme:
single cell transcriptome sequencing was performed on tumor tissue (34 samples total) taken from tumor primary sites and/or different metastasis sites of 18 ovarian cancer primary patients, and high resolution ovarian cancer in situ and metastasis maps were established. A small population of cell subsets characterized by expression of S100A9 was found in the map in situ tumor cells. The tumor cell subpopulation is positively correlated with a poor prognosis for ovarian cancer. The tumor cell subpopulations exist in different patients, not individual-specific, and their presence is common. The tumor cell subpopulation is also prevalent in tumor cells at the metastatic site of ovarian cancer. Through further analysis of the common molecular expression characteristics of S100deg.A < 9+ > tumor cells existing in-situ tumor tissues and metastatic tissues, a specific tumor cell molecular marker composition for promoting ovarian cancer metastasis is found, and the specific tumor cell molecular marker composition is remarkably and highly expressed. The specific tumor cell molecular marker composition is a characteristic molecule with obviously high expression specificity shared by tumor cell subsets with S100A9 as a main characteristic, and the molecule or the combination thereof is selected from any one or more of (a) - (j): (a) the S100A8 gene and its expression product; (b) the S100A9 gene and its expression product; (c) an ADGRF1 gene and its expression product; (d) CEACAM6 gene and its expression product; (e) CST6 gene and its expression product; (f) NDRG2 gene and its expression product; (g) MUC4 gene and its expression product; (h) PI3 gene and its expression product; (i) SDC1 gene and its expression product; (j) C15orf48 gene and its expression product.
Further, the gene ID encoding S100A8, NCBI database, is the sequence indicated by 6279;
the gene ID of NCBI database coding S100A9 is 6280;
the gene ID of NCBI database encoding ADGRF1 is 266977;
the gene ID of NCBI database coding CEACAM6 is 4680;
the gene ID of NCBI database encoding CST6 is 1474;
the gene ID of the NCBI database coding NDRG2 is a sequence shown as 57447;
the gene ID encoding MUC4, NCBI database, is the sequence shown as 4585;
the gene ID of NCBI database encoding PI3 is 5266;
the gene ID of NCBI database encoding SDC1 is 6382;
the gene ID of NCBI database encoding C15orf48 is 84419;
the S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48 genes and their expression products are all human sources.
Application of a specific tumor cell molecular marker composition reagent for identifying or detecting ovarian cancer metastasis promotion in preparation of medicines for diagnosing, detecting, monitoring or predicting the progress of ovarian cancer.
Further, the progression of ovarian cancer includes proliferation and metastasis of ovarian cancer cells in vitro, as well as malignant growth in vivo. The diagnosis includes: whether an ovarian cancer is a poor prognosis, wherein high expression is a poor prognosis of ovarian cancer; detecting, monitoring, or predicting the progression of ovarian cancer includes: detecting the expression of the molecular marker composition in the patient, wherein the high expression is proliferation and metastasis of ovarian cancer cells in vitro and the likelihood of malignant growth in vivo is greater.
Application of a reagent for inhibiting expression of a specific tumor cell molecular marker composition for promoting ovarian cancer metastasis in preparing medicines for treating or preventing ovarian cancer metastasis.
A kit for diagnosing, detecting, monitoring or predicting the progression of ovarian cancer, an agent that identifies or detects a marker molecule selected from the group consisting of S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48, or any combination thereof;
the progression of ovarian cancer includes proliferation and metastasis of ovarian cancer cells in vitro, as well as malignant growth in vivo.
Further, mRNA of a marker molecule or cDNA of the marker molecule is detected by a nucleic acid detection method; preferably, transcription analysis, real-time fluorescent quantitative PCR, nucleic acid hybridization or any combination thereof is employed. The reagents each independently comprise at least one primer or probe complementary to a portion of the nucleotide sequence of an mRNA or cDNA of the specific tumor cell molecular marker composition of the type that promotes metastasis of ovarian cancer. The kit at least comprises one or more of the following 10 primer pairs, and the primer sequences of the real-time quantitative reverse transcription PCR are shown in SEQ ID NO. 3-22.
A pharmaceutical composition for treating or preventing metastasis of ovarian cancer, the pharmaceutical comprising a substance that inhibits the S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and/or C15orf48 genes and expression products and/or reduced activity thereof, or any combination thereof.
Further, the inhibitor at least comprises a protein-specific antibody, an RNA interference molecule or antisense oligonucleotide aiming at gene mRNA, a small molecule inhibitor, siRNA and shRNA.
Further, the design of specific siRNAs for each of S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48 was used, and the siRNA sequences were as shown in SEQ ID NO.23-SEQ ID NO. 62. Or a construct capable of expressing or forming said siRNA.
In vitro functional experiments show that in OVCAR3 and CAOV3 ovarian cancer cells, inhibition of the expression of S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 or C15orf48 can significantly inhibit the proliferation activity and the metastasis capability of the ovarian cancer cells.
In vivo OVCAR3 nude mice subcutaneous transplantation tumor experiments show that inhibiting the expression of S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 or C15orf48 can obviously inhibit the growth capacity and metastasis related protein expression of nude mice subcutaneous transplantation tumor. The tumorigenic effects of S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48 in ovarian cancer cells were initially determined.
The beneficial effects of the application are as follows: the application separates out tumor cell subgroup with different functions through single cell group analysis, and identifies specific marker molecules of the subgroup. The application provides a specific tumor cell molecular marker composition for promoting ovarian cancer metastasis and application thereof. The molecular marker composition has the capability of obviously inhibiting proliferation and metastasis of ovarian cancer cells in vitro and malignant growth in vivo. The results show that the molecular marker composition is an important cancerogenic factor in ovarian cancer, can be used as an important index for diagnosing, detecting, monitoring or predicting the progress of ovarian cancer, and can be used as a therapeutic target and a prognostic index of ovarian cancer metastasis.
Drawings
Fig. 1: unsupervised cluster map of heterogeneous subpopulations present in ovarian cancer tissue. UMAP plots show that 22 different color-divided cell clusters are shown by differences in gene expression of the cells.
Fig. 2: schematic representation of major cell types in ovarian cancer in situ tissue and metastatic tissue. (A) UMAP plots show the major cell types in ovarian cancer in situ tissue and metastatic tissue. (B) The dot plot shows the expression level of a particular marker gene in each cell type. The size of the dot indicates the proportion of cells expressing a particular marker gene. The color spectrum represents the average expression level of the marker gene.
Fig. 3: unsupervised cluster map of heterogeneous subpopulations of tumor cells present in ovarian cancer tissue. (A) Ovarian cancer tumor cells are divided into six subgroups according to the gene expression difference and molecular characteristics of the tumor cells. (B) The survival analysis curve of the S100A9+ tumor cell subset shows that ovarian cancer patients with high expression of the S100A9 tumor cell subset (S100A 9-tumor cells are S100A9 negative tumor cells) have poorer prognosis. The Kaplan-Meier survival curve showed significant prognostic isolation. Analysis of total 5 year survival time (OS) from 373 patients with primary ovarian cancer based on the s100deg.A9+ tumor cell marker gene signature from single cell data.
Fig. 4: distribution of tumor cell subsets in individual patients with ovarian cancer. The s100deg.A 9+ tumor cell subpopulation is present in different patients, not individual-specific, and its presence is common.
Fig. 5: specific gene expression levels in each tumor cell subpopulation. The dot plot shows the expression level of the specific marker gene in each tumor cell subpopulation. The S100A9+ tumor cell subsets share the molecular expression characteristics, and S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48 are all expressed with high specificity.
Fig. 6: UMAP schematic representation of 10 heterogeneous subpopulations of tumor cells present in ovarian cancer metastasis tissue. A subset of s100deg.A 9+ tumor cells are also present in ovarian cancer metastasis tumor cells.
Fig. 7: distribution of tumor cell subsets in metastatic tissues of ovarian cancer at each group of metastatic sites. The s100deg.A 9+ tumor cell subsets were present in different metastatic tissues.
Fig. 8: designing schematic diagrams of knockdown efficiency results of two pairs of siRNAs in ovarian cancer cells for each gene respectively; (A) Knockdown efficiency results for each pair of siRNAs in human ovarian cancer cell line OVCAR 3. (B) Knockdown efficiency results for each pair of siRNAs in the human ovarian cancer cell line CAOV 3.
Fig. 9: results of inhibiting the effect of expression of specific molecular marker compositions on the proliferative capacity of human ovarian cancer cell line OVCAR3 schematic (a) and statistical graph (B)
Fig. 10: results of inhibition of expression of specific molecular marker compositions on proliferation potency of human ovarian cancer cell line CAOV3 schematic (A) and statistical (B)
Fig. 11: results of inhibiting the effect of expression of a specific molecular marker composition on the migration ability of human ovarian cancer cell line OVCAR3 schematic (a) and statistical graph (B).
Fig. 12: results of inhibiting the effect of expression of a specific molecular marker composition on the invasive capacity of the human ovarian cancer cell line OVCAR3 schematic (a) and statistical graph (B).
Fig. 13: results of inhibition of expression of specific molecular marker compositions on the ability of the human ovarian cancer cell line CAOV3 to migrate are shown schematically (a) and statistically (B).
Fig. 14: results of inhibition of expression of specific molecular marker compositions on the invasive capacity of the human ovarian cancer cell line CAOV3 are shown in schematic (a) and statistical (B).
Fig. 15: human ovarian cancer cell line OVCAR3 nude mice subcutaneous engrafting tumor model different groups of engrafting tumors were photographed by digital cameras (a) and growth curves of nude mice subcutaneous engrafting tumors (B).
Fig. 16: immunohistochemical staining schematic (a) and statistical (B) of the pathological section cell proliferation marker protein Ki67 of different groups of human ovarian cancer cell line OVCAR3 nude mice subcutaneous engrafting tumor model.
Fig. 17: immunohistochemical staining schematic (A) and statistical chart (B) of different groups of pathological section cell transfer related protein Vimentin of human ovarian cancer cell line OVCAR3 nude mice subcutaneous transplantation tumor model.
Fig. 18: immunohistochemical images of different groups of pathological sections of human ovarian cancer cell line OVCAR3 nude mice subcutaneous engrafting tumor model. (A) Immunohistochemical staining of different groups of pathological sections was performed with antibodies to S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 or C15orf48, respectively. (B) Different groups of pathological sections were subjected to immunohistochemical staining statistics with antibodies to S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 or C15orf48, respectively.
Fig. 19: in vivo OVCAR3 model H & E pathological section images of major organs (heart, liver, spleen, lung, kidney) collected from different treatment groups.
Detailed Description
The application will be further described with reference to examples and figures
Example 1: single cell sequencing analysis found s100deg.A 9+ tumor cell subpopulation, illustrating its characteristics and specific molecular expression profile 1. Single cell isolation: ovarian cancer tissue and metastatic tissue samples were surgically excised and minced into small pieces (about 1 mm) on ice 3 Size). Subsequently, collagenase I (Sigma), collagen was usedEnzyme IV (Sigma) and DNase I (Worthington) were digested in a water bath at 37℃for 30 minutes. After digestion, the samples were passed through a 40 μm cell filter and centrifuged at 300 Xg for 5 minutes. For ascites, cells in the ascites were directly filtered through a 40 μm cell filter and then centrifuged at 300×g for 5 minutes. The supernatant was discarded and the pellet resuspended in erythrocyte lysis buffer (Solarbio) to remove erythrocytes. The cells were then resuspended in RPMI1640 complete medium and filtered through a 35 μm cell filter. Isolated single cells were stained with acridine orange/propidium iodide (AO/PI) and cell viability was assessed using a Countstar fluorescent cell analyzer. Single cell RNA sequencing was then performed using 10X Genomics Chromium Controller Instrument to collect single cell suspensions and analyzed as follows:
the scRNA-seq data is filtered out of the adapter sequence using default parameters, removing low quality reads, and obtaining clean data. The reads were then compared to the human genome (GRCh 38 ensembl: v 91) to generate a characteristic barcode matrix. Based on the barcode reading of each cell of each sample, a downsampling analysis is performed on the sequenced samples and an aggregation matrix is generated as a final output. Cells expressing more than 200 genes and having a mitochondrial UMI rate below 20% pass the quality filter criteria, mitochondrial genes are excluded from the expression table.
Cell normalization and regression were then performed according to the expression table, while taking into account UMI counts and percentage of mitochondrial genes for each sample, resulting in scaled data. And carrying out principal component analysis on the scale data by using the first 2000 high-variable genes, and selecting the first 10 principal components for Uniform Manifold Approximation and Projection (UMAP) construction. By adopting the graph-based clustering method, unsupervised cell clustering is obtained based on the first 10 principal components of PCA. Determining the marker genes of each cluster using the criteria of 1) log values of fold differences (lnFC) > 0.25; 2) Assumed value < 0.05; 3) Minimum percentage (min. Pct) > 0.1. To further determine a particular cell type, clusters representing the same cell type are selected for subsequent re-UMAP analysis, graph-based clustering, and marker analysis.
2. Survival analysis: the total survival of ovarian cancer patients was studied from a large amount of mRNA-seq data obtained from the cancer genomic profile (TCGA) database.
3. Results: the high resolution cell patterns of tumor primary and/or metastatic sites of 18 patients with ovarian cancer initiation are shown in fig. 1-2, and as shown in fig. 3, a small group of cell subsets mainly characterized by expressing S100A9 exist in-situ tumor cells (fig. 3A), and TCGA ovarian cancer database prognosis analysis shows that s100deg.A9+ tumor cell subsets are positively correlated with the poor prognosis of ovarian cancer (fig. 3B). As shown in fig. 4, the s100deg.A 9+ tumor cell subpopulations were present in different patients, not individual-specific, and their presence was common. As shown in FIG. 5, a class of specific tumor cell molecular marker compositions for promoting ovarian cancer metastasis is identified by further analyzing the expression characteristics of S100deg.A 9+ tumor cell common molecules: S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48 genes, and are all remarkably high in specificity. s100deg.A 9+ tumor cells were also present in tumor cells at the metastatic sites of ovarian cancer (FIG. 6), and were present at different metastatic sites (FIG. 7).
Example 2 Effect of inhibitors of molecular marker compositions on proliferation and invasion of ovarian cancer cells
1. Conventional cell culture: human ovarian cancer cell line CAOV3 was cultured in DMEM medium containing 10vol% FBS, human ovarian cancer cell line OVCAR3 was cultured in RPMI-1640 medium containing 10vol% FBS and placed in 5vol% CO 2 Conventional culture in a 37 ℃ cell incubator, liquid exchange every 2-3 days, passage every time the cell fusion degree reaches 90%, and taking the cells in the logarithmic growth phase for subsequent experiments.
2. Cell transfection:
1) siRNA synthesis: and selecting action targets for different molecules, designing according to the principle of determining sequences, and synthesizing siRNA for different molecules.
Table 1 the sequences of siRNA.
2) The CAOV3 or OVCAR3 cells were seeded at a density of 50 ten thousand per well in six well plates and transfected when the cells had fused to about 50% -60% of the adherent growth. Taking 1-well liquid addition amount of a six-well plate as an example:
and (3) solution A: 2.5. Mu.L of siRNA and 97.5. Mu.L of OPTI-MEM were mixed;
and (2) liquid B: 2.5. Mu.L of DharmaFECT and 97.5. Mu.L of OPTI-MEM were mixed;
and (3) after standing at room temperature for 5min, uniformly mixing the solution A and the solution B, standing at room temperature for 20min, preparing a working solution, and then uniformly mixing without vigorous blowing. After adding 0.8ml of the medium to the six-well plate, 200. Mu.L of the above working solution was slowly added dropwise so as not to cause too much stimulation to cells. CO at 37 DEG C 2 After 24 hours of incubation in the incubator, 2ml of complete medium was changed per well, and the knockdown efficiency was detected at 48 hours, and the subsequent functional experiments.
Rna extraction: six well plates were added with 1mL Trizol per well, allowed to stand at room temperature for 15 minutes for lysis, and transferred to RNase-free centrifuge tubes. 200. Mu.L of chloroform was added to each 1mL of Trizol, and the mixture was mixed upside down for 15s, left at room temperature for 15 minutes, and centrifuged at 14000rpm at 4℃for 15 minutes. After centrifugation, the liquid is divided into three layers, wherein the upper layer is a colorless transparent layer, namely RNA; the bottom layer is red organic phase, and the middle flocculent precipitate layer is mainly DNA. The upper aqueous phase was aspirated into another clean centrifuge tube, taking care not to aspirate the middle pellet. Add 500. Mu.L of isopropanol to the aspirated supernatant, mix upside down for 15s, incubate at room temperature for 15 minutes, centrifuge at 12000rpm at 4℃for 15 minutes. After centrifugation, a white precipitate was evident at the bottom of the tube, the supernatant was discarded, and the RNA pellet was washed twice with 1mL of pre-chilled 75vol% ethanol and centrifuged at 7500rpm for 5 minutes at 4 ℃. The EP tube was inverted and dried on clean absorbent paper, and 10. Mu.L-50. Mu.L DEPC water was added to dissolve the RNA well depending on the size of the pellet. 1 mu L of RNA solution is taken to detect the concentration and purity of RNA by a micro nucleic acid quantitative analyzer, and the OD260/OD280 of the RNA with better quality is between 1.8 and 2.2. Preserving in a refrigerator at-80deg.C.
4. Reverse transcription and qPCR: reverse transcription was performed using ABScript Neo RT Master Mix for qPCR with gDNA Remover (abclon, RK 20433). Amplification reactions were performed using 2X Universal SYBR Green Fast qPCR Mix (ABclonal, RK 21203) on a Light cycle 480 instrument (Roche). The primer sequences of specific targets are shown in Table 2. Obtaining CT value of each sample according to 2 -ΔΔCT The method calculates the relative expression of the target gene.
Table 2: RT-PCR detection fragment primer sequence
5. Cell clone proliferation assay: each group had a cell density of 1 x 10 at 48 hours post transfection 3 Well, inoculated in 6-well plate. After 14 days of incubation at 37℃the cells were washed, fixed and stained with 0.5wt% crystal violet dissolved in 20vol% methanol. Cell colony formation per well was counted.
6. Statistical analysis: statistical analysis was performed using Graphpad Prism 8.0.1 software. Results are expressed as mean±sd. Data with normal distribution and uneven variance were compared using Student's t, and data with normal distribution and uneven variance were compared using Welch's correction unpaired t-test. Non-normal distribution experimental data was tested using the non-parametric Mann-Whitney test. P <0.05 is statistically significant for the differences.
7. Results: siRNA transfection efficiency was examined and the results are shown in FIG. 8 to be statistically significant in terms of knockdown efficiency in both ovarian cancer cells OVCAR3 (FIG. 8A) and CAOV3 (FIG. 8B). After knocking down the expression of the corresponding molecules, the clonogenic capacity of both ovarian cancer cells OVCAR3 (fig. 9) and CAOV3 (fig. 10) was significantly reduced. It is shown that inhibiting any molecular expression of the molecular marker composition can significantly inhibit ovarian cancer cell proliferation.
Example 3 effect of inhibitors of molecular marker compositions on migration and invasion of ovarian cancer cells.
Tranwell cell invasion assay: spreading glue: BD matrigel was boiled on ice in advance, and a 1.5ml sterile EP tube, a tip box with 200. Mu.L tips, and a Transwell plate were placed in a refrigerator for pre-cooling. Mixing BD matrigel and precooled OPTI-MEM at a volume ratio of 1:10, taking 100 μL, adding into an upper chamber in a Transwell plate, taking out the Transwell plate after slightly placing into an incubator for standing for 30min, carefully sucking the upper layer non-coagulated liquid, and coating BD gel. Cells were harvested by digestion 48h after cell transfection and resuspended in serum-free medium; 20 ten thousand cells were resuspended in 200 μl of serum-free medium in the upper chamber; the lower chamber was placed with a high concentration medium containing 20vol% FBS. CAOV3 cells were incubated in an incubator at 37℃for 24h, after incubation of OVCAR3 cells for 12h, 0.5wt% crystal violet was fixed and stained for 20min, gently rinsed with clear water, and the upper cells were carefully wiped off with a cotton swab, photographed and counted.
2. Migration experiment: cells were harvested by digestion 48h after cell transfection and resuspended in serum-free medium; 10 ten thousand cells were resuspended in 200 μl of serum-free medium in the upper chamber; the lower chamber was placed with a high concentration medium containing 20vol% FBS. CAOV3 cells were incubated in an incubator at 37℃for 24h, after incubation of OVCAR3 cells for 12h, 0.5wt% crystal violet was fixed and stained for 20min, gently rinsed with clear water, and the upper cells were carefully wiped off with a cotton swab, photographed and counted.
3. The results are shown in fig. 11-12, which demonstrate that inhibiting any molecular expression of the molecular marker composition can significantly inhibit the migration (fig. 11) and invasion (fig. 12) ability of ovarian cancer cells OVCAR3, and as such, inhibiting any molecular expression of the molecular marker composition can significantly inhibit the migration (fig. 13) and invasion (fig. 14) ability of ovarian cancer cells CAOV 3.
Example 4 Effect of inhibitors of molecular marker compositions on the growth of ovarian cancer cell nude mice subcutaneous transplantations
1. Establishment of nude mice subcutaneous transplantation tumor: OVCAR3 cells were transfected with different siRNAs (si-NC, si-S100A8, si-S100A9, si-ADGRF1, si-CEACAM6, si-CST6, si-NDRG2, si-MUC4, si-PI3, si-SDC1 and si-C15orf 48), centrifuged after 24h and washed twice with PBS to wash out serum. Resuspension counts of 1 x 10 per nude mice per group of 4 mice 7 Cells were subcutaneously injected under the axilla of female nude mice (4 week old, BALB/c nude mice). Tumor formation was observed 1 week after injection of cells, and tumor volume (V) was monitored weekly by measuring long diameter (L) and wide diameter (W) of the tumor seeds every other week and calculated using formula v=0.5×l×w×w. After 14 days, 1nmol of siRNA (si-NC, si-S100A8, si-S100A9, si-ADGRF1, si-CEACAM6, si-CST6, si-NDRG2, si-MUC 4),si-PI3, si-SDC1, and si-C15orf 48). Mice were euthanized after 28 days, tumors were removed, their volumes were measured and the volume and weight sizes of tumors were weighed against the control and experimental groups. Collecting viscera (heart, liver, spleen, lung, and kidney), soaking tumor tissue and viscera in 4vol% paraformaldehyde solution for subsequent hematoxylin and eosin (H)&E) Staining and immunohistochemical staining. Animal experiments were performed according to guidelines approved by the committee for laboratory animal management and ethics.
2. Hematoxylin and eosin staining and immunohistochemical staining: paraffin embedding after tissue sample fixation. Hematoxylin and eosin (H & E) staining observed the histopathological features of each organ (heart, liver, spleen, lung, kidney). Immunohistochemical staining was performed on tumor sections. Sections were dewaxed, hydrated, permeabilized, blocked, then depurated with primary antibodies Ki-67 (Proteintech, 27309-1-AP,1:400 dilution), vimentin (Abcam, ab92547,1:400 dilution), S100A8 (Proteintech, 15792-1-AP,1:400 dilution), S100A9 (HUABIO, ET1702-73,1:200 dilution), ADGRF1 (Affinity Biosciences, DF2796,1:100 dilution), CEACAM6 (HUABIO, EM 1-68,1:500 dilution), CST6 (Proteintech, 17076-1-AP,1:200 dilution), NDRG2 (HUABIO, ER1802-94,1:100 dilution), MUC4 (HUABIO, ET1705-13,1:100 dilution), PI3 (Proteintech, 15961-AP, 1:100 dilution), SDC1 (HUIO, 1703-42,1:500 dilution) and Ab 190-1:200 dilution (Abcalif, 23:200 dilution). Sections were stained with hematoxylin to label the nuclei and observed under a microscope. For the Ki-67 analysis, image j was used to evaluate the percentage of positive cells. For other proteins, IHC scores were determined by multiplying the scores of the two components. First score: the percentage of positive cells was scored 0-25% 1,26-50% 2,51-75% 3,76-100% 4. Second score: the staining intensity was scored negative for 1, weak for 2, medium for 3, and strong for 4. At least 5 fields of view are analyzed per slice and the scores of the 5 fields of view are averaged to obtain a final score.
4. As shown in fig. 15, any of the molecular marker compositions inhibited expression significantly inhibited the growth ability of subcutaneous transplantation tumor in nude mice. As shown in fig. 16-17, any one of the molecular marker compositions can significantly inhibit the expression of ki67 (fig. 16) and the expression of vimentin (fig. 17) in the nude mice subcutaneous transplantation tumor, which indicates that any one of the molecular marker compositions can significantly inhibit the proliferation and the transfer capacity of the nude mice subcutaneous transplantation tumor. As shown in FIG. 18, any of the molecules using the siRNA inhibiting molecular markers had significant knockdown efficiency at the protein expression level. As shown in fig. 19, the use of siRNA inhibitors did not cause significant damage to important organs including heart, liver, spleen, lung and kidney of nude mice, and had good biosafety.
Claims (10)
1. A specific tumor cell molecular marker composition for promoting ovarian cancer metastasis, which is characterized by being a characteristic molecule with remarkably high expression specificity shared by tumor cell subsets with S100A9 as a main characteristic, wherein the molecule or the combination thereof is selected from any one or more of (a) - (j): (a) the S100A8 gene and its expression product; (b) the S100A9 gene and its expression product; (c) an ADGRF1 gene and its expression product; (d) CEACAM6 gene and its expression product; (e) CST6 gene and its expression product; (f) NDRG2 gene and its expression product; (g) MUC4 gene and its expression product; (h) PI3 gene and its expression product; (i) SDC1 gene and its expression product; (j) C15orf48 gene and its expression product.
2. The specific tumor cell molecular marker composition for promoting metastasis of ovarian cancer according to claim 1, wherein the specific tumor cell molecular marker composition is characterized by: the gene ID of NCBI database encoding S100A8 is 6279;
the gene ID of NCBI database coding S100A9 is 6280;
the gene ID of NCBI database encoding ADGRF1 is 266977;
the gene ID of NCBI database coding CEACAM6 is 4680;
the gene ID of NCBI database encoding CST6 is 1474;
the gene ID of the NCBI database coding NDRG2 is a sequence shown as 57447;
the gene ID encoding MUC4, NCBI database, is the sequence shown as 4585;
the gene ID of NCBI database encoding PI3 is 5266;
the gene ID of NCBI database encoding SDC1 is 6382;
the gene ID of NCBI database encoding C15orf48 is 84419;
the S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and C15orf48 genes and their expression products are all human sources.
3. Use of a reagent for identifying or detecting a specific tumor cell molecular marker composition for promoting metastasis of ovarian cancer according to claim 1 or 2 in the preparation of a medicament for diagnosing, detecting, monitoring or predicting the progression of ovarian cancer.
4. The use of claim 3, wherein the progression of ovarian cancer comprises proliferation and metastasis of ovarian cancer cells in vitro, and malignant growth in vivo.
5. A molecular composition kit for diagnosing, detecting, monitoring or predicting the progression of ovarian cancer, said kit comprising a reagent for identifying or detecting a specific tumor cell molecular marker composition for promoting metastasis of ovarian cancer according to claim 1 or 2.
6. The kit according to claim 5, wherein the reagent detects mRNA or cDNA of the specific tumor cell molecular marker composition for promoting metastasis of ovarian cancer according to claim 1 or 2 by a nucleic acid detection method; the nucleic acid detection method is transcription analysis, real-time fluorescence quantitative PCR, nucleic acid hybridization or any combination thereof; the reagents each independently comprise at least one primer or probe complementary to a portion of the nucleotide sequence of an mRNA or cDNA of the specific tumor cell molecular marker composition for promoting metastasis of ovarian cancer of the type described in claim 1 or 2.
7. The kit according to claim 6, wherein the kit comprises at least one or more of the following 10 primer pairs, and the primer pair sequences of the real-time quantitative reverse transcription PCR are shown in SEQ ID NO. 3-22.
8. A pharmaceutical composition for treating or preventing metastasis of ovarian cancer, comprising a substance that inhibits the S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and/or C15orf48 genes and expression products and/or reduced activity thereof, or any combination thereof.
9. The pharmaceutical composition of claim 8, wherein the agent that inhibits S100A8, S100A9, ADGRF1, CEACAM6, CST6, NDRG2, MUC4, PI3, SDC1 and/or C15orf48 genes and expression products and/or reduced activity thereof comprises a protein specific antibody, an RNA interfering molecule or antisense oligonucleotide directed against a gene mRNA, a small molecule inhibitor, siRNA or shRNA. The siRNA sequence is shown as SEQ ID NO.23-SEQ ID NO. 62.
10. The pharmaceutical composition of claim 8, wherein the pharmaceutical composition comprises an effective amount of a gene inhibitor and a pharmaceutically acceptable carrier.
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