Investigating Regulation of LRP8 Expression in Breast Cancer
Investigating miR-409-5p Regulation of LRP8 Expression in Breast Cancer Cell Lines
Maria Izzi
Thomas Jefferson High School for Science and Technology
This paper was originally included in the 2019 print publication of the Teknos Science Journal.
Abstract
Cancer is a leading cause of death in the United States [5], and in 2018, there were over 41,000 deaths due to breast cancer in both males and females [12]. This study investigated the role of miR-409-5p in targeting the gene LRP8 in breast cancer, using cell lines T-47D, MCF-7, MCF-10A, MDA-MB-231, ZR-75-1, MDA-MB-468, and HS578T. It was hypothesized that the target gene was LRP8 using various identification tools. This was confirmed using a computer program exclusive to this project. Expression of the target gene in all cell lines, and later in lines transfected with miR-409-5p mimics and inhibitors was determined through quantitative real-time polymerase chain reactions. Proliferation in transfected cell lines was examined using MTT assays. Expression of miR-409-5p was found to be highest in HS578T, which confirms previous results. However, LRP8 expression, normalized to the 18S rRNA, was highest in both the metastatic cell line MDA-MB-468 and non-tumorigenic line MCF-10A, indicating that LRP8 may not have a direct correlation with breast cancer. Additionally, in MCF-7, the miRNA mimic decreased the proliferation, while in HS578T, proliferation increased. The inhibitor showed the same pattern, but it was not statistically significant. In lines MDA-MB-231 and T-47D, the MTT assay was inconclusive. Future steps for the study include more work with HS578T, identification of a new target gene, and Matrigel assays to assess invasiveness of the cancer in different conditions.
Introduction
Many breast cancer therapies target hormone receptors, but the receptor levels for these hormones differ amongst the sub-categories of breast cancer. Currently, breast cancer is divided into five sub-categories. While Luminal and HER2 enriched tumors have expression of at least two of the three hormone receptors, triple-negative breast cancers (TNBC) are estrogen-negative, progesterone-negative, and HER2-negative [4]. Therapies targeting these receptors are ineffective for TNBC.
One common post-transcriptional form of gene regulation is microRNAs, or miRNAs. These partially specific, short, non-coding sequences are known to bind to mRNAs and degrade them, down-regulating gene expression. However, miRNAs can also upregulate gene expression [2], and changes in expression of many miRNAs have been linked to various cancers. Triple-negative breast cancers may still be affected by miRNA expression and other gene regulation.
Materials and Methods
Cell Lines and Culture
Four cell lines were cultured: MCF-7, T-47D, MDA-MB-231, and HS578T. For lines MCF-10A, ZR-75-1, and BT-474, pre-isolated RNA was used. A medium consisting of nine parts Dulbecco’s Modified Eagle Medium (DMEM) (Corning Cellgro, Manassas, VA), one part fetal bovine serum, and one part penicillin-streptomycin antibiotics, was used to culture cells. A 37°C humidified incubator with 5% CO2 was used to grow the cells.
Total RNA Isolation
Trizol reagent (Life Technologies, Carlsbad, CA) was used to isolate total RNA from the cell lines, as per manufacturer’s instructions. Quantity and purification of the total RNA was assayed using the NanoDrop 1000 Spectrophotometer (Thermo Scientific).
Real-time Quantitative Reverse Transcription PCR (RT-qPCR)
To synthesize cDNA from miRNA, the TaqMan® MicroRNA Reverse Transcription Kit (LifeTechnologies, Foster City, CA) and TaqMan® MicroRNA Assays were used. microRNA qPCR was performed with the TaqMan® Universal Master Mix II, with no UNG (LifeTechnologies). RNU6B (U6 small nuclear 2) was used as a reference. Specifically, 100ng of the total RNA was used to start the miRNA reverse transcription (RT) step following manufacturer’s protocol. The RT reactions were carried out at 16°C for 30 minutes, 42°C for 30 minutes, 85°C for 5 minutes, and then held at 4°C.
For miRNA qPCR, each reaction mixture consisted of 10μl TaqMan Universal Master Mix II with no UNG, 1 μl of 20x TaqMan miR-409-5p PCR primer (LifeTechnologies), 1.33 μl RT products and 7.67 μl nuclease-free water, amounting to a final volume of 20 μl. The ABI 7300 Real-Time PCR System (Applied Biosystems) was used to perform the qPCR. The conditions for qPCR were 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds and 60° C for 60 seconds. The relative quantity of miRNA was normalized by U6 snRNA. Primer sequences are available on request.
Target gene cDNA was synthesized using the iScript™ Advanced cDNA Synthesis Kit for RT-qPCR (Bio-Rad, Hercules, CA). Target gene and internal control human 18S ribosomal RNA were performed using the Applied Biosystems PowerUp ™ SYBR® Green Master Mix (LifeTechnologies, Foster City, CA), according to the manual instructions. The expression (E) of each mRNA relative to the internal control was calculated based on the cycle threshold (Ct) as E=2–Δ(ΔCt), where ΔCt = Ct (target) - Ct (internal control).
miR-409-5p Mimic and Inhibitor Transfection
For transfection of miR-409-5p mimic or inhibitors, cells were seeded in a 96 or 48-well plate (4⨉104 cells/well) 24 hours before transfection. Cells were then transfected with 10 nM microRNA mimic or inhibitors using Lipofectamine® RNAiMAX Reagent according to the manufacturer’s instruction.
Cell Proliferation Assay
The cell growth inhibition of cells transfected using the method above was examined using the MTT Cell Proliferation Assay Kit (Abnova, Walnut, CA), according to the instructions of the manual. Color development was measured using a spectrophotometer at 490 nm on a plate reader (BIO-TEK Instruments). Each group has 3 or 4 wells.
Results
miR-409-5p Predicted Target Identification
To identify potential targets of miR-409-5p, four prediction programs were used: TargetScan, TargetMiner, DIANA Tools, and miRDB. These were compared manually using a Venn diagram, and a computer program was created to confirm the comparison.
Figure 1. Target gene identification for miR-409-5p based on four tools. Genes labeled in blue were identified by TargetMiner.
Figure 2. Target gene confirmation using computer program to isolate commonly identified genes from various programs. DIANA tools, miRDB, TargetScan, and TargetMiner were entered.
Expression of miR-409-5p in Cell Lines
A quantitative real-time polymerase chain reaction (qRT-PCR) test was conducted in six cell lines, to identify if miR-409-5p expression was differed between various cell lines. HS578T was found to have the highest expression, so work was continued with that triple-negative line, along with others, including MDA-MB-231, MDA-MB-468, MCF-7.
Figure 3. Expression of miR-409-5p using a qRT-PCR. Expression is highest in HS578T, which is a triple-negative breast cancer.
Expression of LRP8 in Cell Lines
Another qRT-PCR test was conducted in the same six lines for expression of LRP8, the selected target gene. If the expression of LRP8 was also highest in HS578T, that would show a correlation and likely link between miR-409-5p and LRP8, confirmable with other assays, such as the Luciferase assay. However, it was found that LRP8 expression was high in MDA-MB-468 and MCF-10A, indicating that while miR-409-5p has a probable link to breast cancer, LRP8 is not related to the miRNA.
Figure 4. Expression of LRP8 target gene using quantitative real-time polymerase chain reaction. Expression is highest in MDA-MB-468 and MCF-10A. MDA-MB-468 is a triple-negative breast cancer, and MCF-10A is normal-like.
MTT Assays for Proliferation of Cells After Transfection of Mimics and Inhibitors
To determine how miR-409-5p affects cell proliferation in various cell lines, a MTT assay was conducted for cell lines MDA-MB-231 and T-47D, but the results were inconclusive, since inducing the miRNA had the same effect as inhibiting it. The mimics should have had the same effect as the actual miRNA, while the inhibitors should have had the opposite effect. The mocks were controls showing the difference between the effects of the miRNA and the presence of a miRNA-like substance with no functionality. The same test was then conducted for two other cell lines, and it was found that in MCF-7, the miRNA statistically significantly decreased proliferation, and that the inhibitor followed a similar trend, although not statistically significant. In HS578T, the miRNA statistically significantly increased proliferation, and the inhibitor followed the pattern without statistical significance.
Figure 5. MTT assay in MCF-7 cells transfected with miR-409-5p mimic-mock, mimic, inhibitor-mock, and inhibitor. Since the mimic has statistically significantly lower expression than the mimic-mock and the inhibitor has higher expression than the inhibitor-mock, we can conclude that miR-409-5p decreases proliferation of MCF7 cells. MCF7 is a luminal A breast cancer, meaning it is ER+ and PR+ but HER2-.
Figure 6. MTT assay in HS578T cells transfected with miR-409-5p mimic-mock, mimic, inhibitor-mock, and inhibitor. Since the mimic is statistically significantly higher than its mock, and the inhibitor is lower than the inhibitor-mock, we can conclude that miR-409-5p increases proliferation of HS578T cells. HS578T is a triple-negative breast cancer, so it is ER-, PR-, and HER2-.
Discussion
The expression of miR-409-5p, based on my qRT-PCR, was highest in cell line HS578T, consistent with previous data from the lab. However, the expression of target gene LRP8 was highest in MDA-MB-468 and MCF-10A, inconsistent with prior data since MDA-MB-468 was tumorigenic while MCF-10A was normal-like. LRP8 was not expressed equally in all cell lines either, so from this data, it was concluded that while miR-409-5p was likely related to breast cancer, LRP8 may not have been.
From the MTT assays in cells transfected with mimics and inhibitors of miR-409-5p, MDA-MB-231 and T-47D were inconclusive. However, in mimics in MCF-7, miR-409-5p decreased proliferation of the cells, while in mimics in HS578T, the miRNA increased proliferation. If the proliferation changes were cell line-specific, the other non-TNBC lines would have shown a similar trend to MCF-7, and the triple-negative lines would be similar to HS578T. However, since this was not the case, while the proliferation changes may have been cell line-specific, they are probably not subtype-specific. The results from the mimics were statistically significant, showing that when the miRNA is present, a certain change in proliferation occurs. However, while the inhibitors followed the same trend, the data was not significant. This data still shows that the miRNA had noteworthy effects on cancer cell multiplication.
In the future, I primarily plan to look into the identification and confirmation of a new target gene. I will begin with TRPS1 out of the many genes that were commonly found as it also may be related to breast cancer. Then, I will design a new primer for the gene and repeat the tests I have conducted with LRP8. I also plan to work more with HS578T, since both the PCR for miR-409-5p and the MTT assays have found significant results in this line which match previous work with this miRNA. I also plan to use Matrigel invasion assays to assess invasiveness of the cancer in different conditions. For pharmaceutical companies to create medicines that target the cancer-causing genes, it is helpful to ensure that there is a direct relationship between the miRNA and the target gene. This prevents unintentional consequences that harm the patient. For this, I plan on using the Luciferase assay. The miRNA had noteworthy effects on breast cancer lines, and further experimentation can confirm current results, as well as find more connections between the miRNA, target genes, and their impact on the breast cancer cells to provide medicinal therapies for TNBC.
References
[1] Abstract P3-10-41: Quantitative Immunohistochemical Analysis and Prognostic Significance of TRPS-1, a New GATA Transcription Factor Family Member, in Breast Cancer
[2] Ayla Valinezhad Orang, Reza Safaralizadeh, and Mina Kazemzadeh-Bavili, “Mechanisms of miRNA-Mediated Gene Regulation from Common Downregulation to mRNA-Specific Upregulation,” International Journal of Genomics, vol. 2014, Article ID 970607, 15 pages, 2014. https://doi.org/10.1155/2014/970607.
[3] Chen, J. Q., Bao, Y., Litton, J., Xiao, L., Zhang, H., Warneke, C. L., . . . Radvanyi, L. (2011). Expression and Relevance of TRPS-1: A New GATA Transcription Factor in Breast Cancer. Hormones and Cancer,2(2), 132-143. doi:10.1007/s12672-011-0067-5
[4] Dai, X., Li, T., Bai, Z., Yang, Y., Liu, X., Zhan, J., & Shi, B. (2015). Breast cancer intrinsic subtype classification, clinical use and future trends. American Journal of Cancer Research. Retrieved February 6, 2019.
[5] FastStats - Leading Causes of Death. (n.d.). Retrieved from https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm
[6] Hong, J., Sun, J., & Huang, T. (2013). Increased Expression of TRPS1 Affects Tumor Progression and Correlates with Patients Prognosis of Colon Cancer. BioMed Research International,2013, 1-6. doi:10.1155/2013/454085
[7] Hu, J., Su, P., Jiao, M., Bai, X., Qi, M., Liu, H., . . . Han, B. (2018). TRPS1 Suppresses Breast Cancer Epithelial-mesenchymal Transition Program as a Negative Regulator of SUZ12. Translational Oncology,11(2), 416-425. doi:10.1016/j.tranon.2018.01.009
[8] Lin, H., Zeng, D., Liang, Y., Wei, X., & Chen, C. (2017). GATA3 and TRPS1 are distinct biomarkers and prognostic factors in breast cancer: Database mining for GATA family members in malignancies. Oncotarget,8(21). doi:10.18632/oncotarget.16160
[9] Pencheva, N., Tran, H., Buss, C., Huh, D., Drobnjak, M., Busam, K., & Tavazoie, S. (2012). Convergent Multi-miRNA Targeting of ApoE Drives LRP1/LRP8-Dependent Melanoma Metastasis and Angiogenesis. Cell,151(5), 1068-1082. doi:10.1016/j.cell.2012.10.028
[10] Serandour, A. A., Mohammed, H., Miremadi, A., Mulder, K. W., & Carroll, J. S. (2018). TRPS1 regulates oestrogen receptor binding and histone acetylation at enhancers. Oncogene,37(39), 5281-5291. doi:10.1038/s41388-018-0312-2
[11] Shiang, C., Qi, Y., Wang, B., Broom, B., & Pusztai, L. (2011). P3-17-01: ApoE and Its Receptors (LRP8, VLDLR) Function as Growth Signals for Triple-Negative Breast Cancer and Represent a Novel Therapeutic Target. Cancer Research,71(24 Supplement). doi:10.1158/0008-5472.sabcs11-p3-17-01
[12] Siegel, R. L., Miller, K. D., & Jemal, A. (2018). Cancer statistics, 2018. CA: A Cancer Journal for Clinicians,68(1), 7-30. doi:10.3322/caac.21442
[13] Wu, L., Wang, Y., Liu, Y., Yu, S., Xie, H., Shi, X., . . . Chen, L. (2014). A central role for TRPS1 in the control of cell cycle and cancer development. Oncotarget,5(17). doi:10.18632/oncotarget.2291
[14] Zhang, J., Zhang, X., Zhang, L., Zhou, F., Dinther, M. V., & Dijke, P. T. (2012). LRP8 mediates Wnt/β-catenin signaling and controls osteoblast differentiation. Journal of Bone and Mineral Research,27(10), 2065-2074. doi:10.1002/jbmr.1661
