Gene expression for regulating cancer cells by using extracellular matrix based on 3D printing

Abstract

The invention provides an extracellular matrix for regulating gene expression of cancer cells based on 3D printing. Specifically, methacrylated gelatin, methacrylated hyaluronic acid and a photoinitiator LAP are used as bio-ink raw materials to construct an extracellular matrix with controllable hardness, and the extracellular matrix is used for regulating and controlling gene expression of cancer cells. And great convenience is provided for development and screening of lung cancer treatment drugs and formulation of treatment strategy and effect prediction.

Description

Technical Field

[0001] The present invention relates to the field of biomedicine, and in particular to a 3D-printed extracellular matrix for regulating gene expression of cancer cells. Background Art

[0002] Traditional 2D cell culture systems cannot accurately replicate the structure and physiochemical properties of the tumor microenvironment, especially the extracellular matrix (ECM) and its properties in cell behavior and drug penetration. To overcome these limitations, 3D in vitro tissue models have emerged as a valuable tool for studying tumor biology and improving the accuracy of drug screening. These models use cells and biomaterials to simulate the composition, morphology, structure and functional characteristics of natural tissues, as well as specific microenvironmental conditions in vivo. The construction of 3D in vitro tissue models is to manufacture personalized in vitro three-dimensional structural models of cells and biomaterials according to the requirements of biomimetic morphology, biological structure or biological function, cell-specific microenvironment, etc. Common methods for constructing 3D in vitro tissue models include stem cell-induced organoid technology, organ chips based on microfluidics technology, and biological 3D printed tissue-like models. Among them, tumor organoids cultured with commercial matrix gel (such as Matrigel) are the most widely studied 3D in vitro tumor models in recent years. However, this model still has certain defects. On the one hand, the tumor model constructed using commercial matrix gel has insufficient tissue hardness and it is difficult to form a specific tissue structure. On the other hand, commercial matrix gel is not adjustable and cannot meet the modeling and research needs of tumor microenvironments under different matrix physical and chemical properties. Therefore, it is impossible to accurately reproduce the tissue organoids of specific tumors in vitro.

[0003] Therefore, it is necessary to develop a method that can reproduce the characteristics of lung cancer tissue in patients as much as possible and be able to regulate the expression of different genes. Summary of the invention

[0004] In order to overcome the above-mentioned defects in the prior art, the first aspect of the present invention provides a use of a 3D-printed extracellular matrix for regulating gene expression of cancer cells.

[0005] In some embodiments, the composition of the 3D printed extracellular matrix is: 3.86% methacryloyl gelatin (GELMA), 0.25% methacryloyl hyaluronic acid (HAMA), and 0.1% photoinitiator phenyl-2,4,6-trimethylbenzoyl diphenyl lithium phosphonate (LAP).

[0006] In some embodiments, the cancer cells are lung cancer cells, preferably non-small cell lung cancer cells.

[0007] In some embodiments, the genes include CGB8, ATP1A2, LRRC19, PTGS1, MACC1, ICAM3, RASL10A, and ZNF681.

[0008] In some embodiments, the use of the 3D-printed extracellular matrix for regulating the CCN1 gene expression of lung cancer cells.

[0009] In some embodiments, a construction method based on a 3D-printed extracellular matrix includes the following steps:

[0010] S1. Prepare stock solutions of methacrylated gelatin, methacrylated hyaluronic acid, and photoinitiator LAP respectively, and configure them into a bioink working solution according to a certain ratio, and filter and sterilize.

[0011] S2. Mix the non-small cell lung cancer cell suspension with the working solution in S1 to obtain a mixed solution.

[0012] S3. Use a photocuring bio-3D printer for printing to obtain the product.

[0013] In some embodiments, the concentrations of the stock solutions of methacrylated gelatin, methacrylated hyaluronic acid, and photoinitiator LAP in step S1 are 10% (w / w), 5% (w / w), and 2% (w / w) respectively.

[0014] In some embodiments, the mixed solution in step S2 contains 3.86% methacrylated gelatin (GELMA), 0.25% methacrylated hyaluronic acid (HAMA), and 0.1% photoinitiator lithium phenyl-2,4,6-trimethylbenzoyl diphenylphosphate (LAP).

[0015] In some embodiments, the cells in step S2 are primary non-small cell lung cancer cells isolated from surgically resected tumor tissues; preferably, the non-small cell lung cancer is lung adenocarcinoma.

[0016] In some embodiments, the cells in step S2 are A549 cells or H1975 cells.

[0017] In some embodiments, in the mixed solution of step S2, the final concentration of the cells is 1×10 5 / mL to 1×10 8 / mL, preferably: 1×10 6 / mL to 5×10 7 / mL, more preferably: 2×10 6 / mL or 2.5×10 7 / mL.

[0018] In some embodiments, the printing parameters of step S3 are as follows: a DLP stereolithography bio-3D printer, a single-image static printing mode, a printing object thickness of 0.5 mm, and a light intensity of 50-180 mW / cm 2 , an exposure time of 10-30 s; preferably, a light intensity of 80-150 mW / cm 2 , and an exposure time of 16-20 s.

[0019] The beneficial effects achieved by the present invention are as follows:

[0020] (1) The present invention discovers that the stiffness and composition of the extracellular matrix (ECM) have a crucial impact on tumor heterogeneity and progression. There are significant differences in stiffness between lung adenocarcinoma tumor tissues and non-tumor tissues, and softer tissues may create conditions for tumor invasion and expansion.

[0021] (2) The present invention confirms through soft models that softer ECM enhances tumor invasion and proliferation. Preliminary exploration of the mechanism reveals that soft ECM promotes the expression of CCN1, and CCN1 mediates cell invasion and proliferation. Reducing the expression of CCN1 will be beneficial for inhibiting tumor invasion and proliferation. This also indicates that the 3D non-small cell lung cancer model of the present invention can be used for studying the mechanism of non-small cell lung cancer development and excavation of more intervention targets. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 Lung cancer cells exhibit different transcriptomes in 3D hard and soft models. A. Volcano plot of differentially expressed genes between the 3D hard model group and the 3D soft model group of A549 cells; B. Heat map of the top 20 differentially expressed genes between the 3D hard model group and the 3D soft model group of A549 cells; C. GO enrichment analysis map of highly expressed genes in the 3D hard model culture of A549 cells, including BP, MF, and CC terms; D. GO enrichment analysis map of highly expressed genes in the 3D soft model culture of A549 cells, including BP, MF, and CC terms.

[0023] Figure 2CCN1 regulates the proliferation and invasion of lung cancer cells in soft models. A. Immunofluorescence images for verifying the efficiency of CCN1 knockdown in A549 cells (scale bar: 100 μm); B. Confirming the efficiency of CCN1 knockdown in A549 cells by Western blot analysis; C. Schematic diagram of the invasion ability of A549 cells and KD-CCN1-A549 cells cultured in soft models on the seventh day (scale bar: 200 μm); D. Schematic diagram of the invasion ability of A549 cells and KD-CCN1-A549 cells cultured in hard models on the seventh day (scale bar: 200 μm); E. Schematic diagram of the proliferation ability of A549 cells and KD-CCN1-A549 cells cultured in soft models. F. Schematic diagram of the proliferation ability of A549 cells and KD-CCN1-A549 cells cultured in hard models; G. Schematic diagram of the cell cycle of A549 cells and KD-CCN1-A549 cells cultured in soft models; H. Schematic diagram of the cell cycle of A549 cells and KD-CCN1-A549 cells cultured in models. Data are presented as mean ± standard deviation. Detailed implementation manners

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] Cells

[0026] Lung cancer cell lines A549 and H1975: Purchased from Procell

[0027] Main reagents and instruments

[0028] Methacrylated gelatin (GelMA, high substitution degree, purchased from Shanghai Yuju Technology Co., Ltd.)

[0029] Methacrylated hyaluronic acid (HAMA, molecular weight about 150 kDa, purchased from Shanghai Yuju Technology Co., Ltd.) Lithium phenyl-2,4,6-trimethylbenzoyl diphenylphosphate (LAP, purchased from Shanghai Yuju Technology Co., Ltd.)

[0030] DLP photocuring biological 3D printer (Sailuo Intelligence, Azure-12)

[0031] Biological soft tissue nanoindentation instrument (Piuma Nanoindenter, Optics11, Netherlands)

[0032] Experimental methods:

[0033] Determination of tissue hardness

[0034] The mechanical properties of the tissue were evaluated using a Piuma nanoindenter and a 50-μm probe according to the manufacturer's immersion measurement method.

[0035] Lentivirus-transduced cell line

[0036] Lentivirus transduction of A549 cells with a fluorescent reporter gene was performed according to the following protocol: A549 cells were seeded in a 6-well plate at a density of 1×10 5 cells per well. The lentiviral vector (HBLV-ZsGreen-Luc-Puro) was added to the complete medium at an MOI of 30, and 6 μg / mL polybrene was added to improve the transduction efficiency. The cells were incubated for 72 h. After removing the viral supernatant, the cells were cultured in a medium containing 0.8 μg / mL puromycin for another 48 h to select successfully transduced cells. The transduction efficiency was evaluated using a fluorescence microscope and flow cytometry.

[0037] Knockdown of CCN1 in the A549 cell line was performed according to the following protocol: A549 cells were seeded in a 6-well plate at a density of 5×10 4 cells per milliliter and cultured for 16 - 24 h until reaching 20 - 30% confluence. 40 μL / well of 25× concentrated infection medium (HiTransG P) was added. The amount of virus to be added was calculated based on the MOI of A549 cells (MOI = 10) and the virus titer (3.5×10 9 / mL) using the following formula: virus volume = (MOI × cell count) / virus titer. After incubation for 16 h, the medium was replaced with complete medium and the cells were cultured for up to 24 h. Puromycin was added at a final concentration of 0.8 μg / mL, and the cells were cultured for another 24 - 48 h. Then, the medium was refreshed, and the infection efficiency was evaluated using a fluorescence microscope and Western blot analysis.

[0038] 3D gel preparation and mechanical property determination

[0039] A PBS solution containing appropriate concentrations of methacrylated gelatin, methacrylated hyaluronic acid, and LAP was prepared to obtain a bioink. After sterilizing the bioink through a 0.22-μm filter membrane, 20 μL of the bioink was added to a 24-well plate. Printing was performed using a DLP bioprinter in a single-image stationary printing mode with a thickness of 0.5 mm. The light intensity and time were optimized to solidify the bioink into a hydrogel, which was then rinsed with 1 mL of PBS and immersed in PBS.

[0040] 3D bioprinting of a cell line lung cancer model

[0041] A549 or H1975 cells were seeded at 2×10 6Suspended at a final concentration of cells / mL in the bioink. Add 20 μL of the cell-containing bioink into a 24-well plate, and print it using a DLP photocuring bio-3D printer in a single-image stationary printing mode with a thickness of 0.5 mm. Optimize the composition of the bioink and the light exposure parameters to print soft and hard models, and then culture them in complete medium.

[0042] Statistical analysis

[0043] Data on cell proliferation and drug sensitivity tests were obtained in quadruplicate and analyzed using GraphPad software. The IC50 value of PDT under the influence of drugs was obtained by non-linear regression of the data obtained from the CellTiter-Glo 3D assay. One-way ANOVA was used for significance analysis, and P < 0.05 was considered statistically significant. Biomarker data detected by Luminex Assay were performed in triplicate.

[0044] The experimental methods in the following examples are all conventional methods unless otherwise specified; the test materials used in the following examples are all obtained from commercial channels unless otherwise specified.

[0045] Example 1 Optimization of 3D printing formulation and parameters

[0046] Replace collagen with gelatin methacrylate (GelMA), hyaluronic acid with hyaluronic acid methacrylate (HAMA), and add the photoinitiator lithium phenyl-2,4,6-trimethylbenzoyl diphenylphosphate (LAP) to formulate the bioink. NMR spectroscopy confirmed the successful modification of GelMA and HAMA.

[0047] Prepare PBS stock solutions containing gelatin methacrylate and LAP. The concentrations of the PBS stock solutions of gelatin methacrylate, hyaluronic acid methacrylate, and the photoinitiator LAP are 10% (w / w), 5% (w / w), and 2% (w / w) respectively, and then obtain the bioink by mixing. By adjusting the different concentrations of the bioink and adjusting printing parameters such as light intensity and exposure time during the crosslinking process, 3D printed gel matrices with different hardnesses are obtained.

[0048] Based on the optimized bioink formulation and printing parameters (see Table 2), two hardness models can be obtained. One simulates the hardness of well-differentiated tumor tissues (soft model, soft), and the other simulates the hardness of poorly-differentiated tumor tissues (hard model, stiff).

[0049] Table 2. Formulation and printing parameters

[0050]

[0051]

[0052] 3D Bioprinting of the Cell Line Lung Cancer Model in Example 3

[0053] The lung cancer model of A549 or H1975 cell line was constructed according to the following steps:

[0054] S1. Prepare the PBS stock solutions of 10% (w / w) methacrylated gelatin, 5% (w / w) methacrylated hyaluronic acid and 2% (w / w) photoinitiator LAP respectively. After mixing them in proportion, obtain the bioink working solution and filter it through a 0.22 μm filter membrane for sterilization.

[0055] S2. Add A549 or H1975 cells at a final concentration of 2×10 6 / mL to the bioink, so that the final concentration of the materials in the bioink is as shown in Table 2;

[0056] S3. Add 20 μL of the bioink containing tumor cells to a 24-well plate. Use the single-image stationary printing mode of the DLP photocuring bio-3D printer, set the thickness of the printed object to 0.5 mm, and print the soft model and the hard model respectively according to the printing parameters in Table 2. After adding the cells, culture them in the complete medium.

[0057] Cell Transcriptome of Soft and Hard Models in Example 4

[0058] To clarify the molecular mechanism of hardness regulating cell phenotype, transcriptome sequencing was performed on A549 cells in 3D soft and hard models. The results showed that under these two conditions, there were significant differences in the gene expression profiles, showing the molecular adaptation of tumor cells to hardness dependence ( Figure 1 A).

[0059] The top 20 differentially expressed genes significantly up-regulated in the hard model included HRH4, SPARC, ZFP91-CNTF, KRT20, TM4SF19-TCTEX1D2, ARMCX1, MIA-RAB4B and NPHP3-ACAD11. The high expression of histamine receptor H4 (HRH4) may inhibit cell proliferation, which is consistent with the observed slowdown of tumor cell proliferation in the hard model.

[0060] The genes most up-regulated in the soft model included CGB8, ATP1A2, LRRC19, PTGS1, MACC1, ICAM3, RASL10A and ZNF681 ( Figure 1 B).

[0061] KEGG-GO enrichment analysis showed that in A549 cells cultured in the hard model, multiple metabolic pathways (including steroid metabolism, cholesterol metabolism, secondary alcohol metabolism, and regulation of oxidoreductase activity) showed significantly increased activities (Figure 1 C-D). In contrast, in A549 cells cultured in the soft model, activities related to cell division, ATP hydrolysis, and DNA helicase activity were significantly enhanced.

[0062] The RNA sequencing results were consistent with the phenotypic differences observed between the soft and hard models. Cells in the soft model showed increased proliferation, which was supported by the upregulation of genes involved in cell division and energy production. In contrast, the hard model promoted enhanced metabolic activity and extracellular signaling, indicating a more secretory and metabolically active tumor state.

[0063] Example 5 CCN1 Regulates the Proliferation and Invasion of Lung Cancer Cells in the Soft Model

[0064] Further, the expression of CCN1 was knocked down in A549 cells ( Figure 2 A-B), and using a multi-region lung cancer cell line model, the effects of CCN1 on tumor cell proliferation and invasion in soft / hard ECM were characterized.

[0065] In the soft model, A549 cells with CCN1 knockdown (KD-CCN1) showed significantly reduced invasive ability ( Figure 2 C). This indicates that CCN1 plays a key role in promoting tumor invasion in the soft ECM environment. In contrast, in the hard model, KD-CCN1 had no significant effect on invasiveness ( Figure 2 D). Since the expression of CCN1 is already low in the hard model, this may indicate that the regulatory function of CCN1 on invasion depends on ECM stiffness and has a significant effect in a softer matrix.

[0066] Consistent with previous results, tumor cells cultured in the soft model showed higher proliferative ability than those in the hard model. Knocking down the expression of CCN1 significantly reduced cell proliferation in the soft model, while no significant change was observed in the hard model ( Figure 2 E-F). The results indicate that CCN1 is a key regulator of the increased proliferation observed under soft ECM conditions.

[0067] Cell cycle analysis showed that in the soft model, knocking down CCN1 led to a decrease in the proportion of A549 cells in the G2-M phase, from 69.3% and 67.6% in the untransfected and negative control groups, respectively, to 63.8% in the KD-CCN1 group ( Figure 2 G). This indicates that CCN1 helps regulate the cell cycle progression in the soft model, acting by slightly promoting entry into or passage through the G2-M phase. In contrast, knocking down CCN1 in the hard model did not change the cell cycle distribution ( Figure 2 H), which further confirmed the stiffness-dependent role of CCN1 in tumor cell regulation.

[0068] Unless otherwise defined, all professional and scientific terms used herein have the same meaning as those familiar to those skilled in the art. In addition, any methods and materials similar or equivalent to the described content can be applied to the present invention. The preferred methods and materials described herein are for illustrative purposes only and do not limit the content of this application.

Claims

1. Use of an extracellular matrix fabricated by 3D printing for regulating gene expression of cancer cells, characterized in that, The composition of the 3D-printed extracellular matrix is as follows: 3.86% methacrylated gelatin (GELMA), 0.25% methacrylated hyaluronic acid (HAMA), and 0.1% photoinitiator lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP).

2. The use according to claim 1, characterized in that, The cancer cells are lung cancer cells, preferably non-small cell lung cancer cells.

3. The use according to claim 1, characterized in that, The genes include CGB8, ATP1A2, LRRC19, PTGS1, MACC1, ICAM3, RASL10A, and ZNF681.

4. The use according to claim 1, characterized in that, Use of the 3D-printed extracellular matrix for regulating the expression of CCN1 gene in lung cancer cells.

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