p53siRNA therapy reduces cell proliferation, migration and induces apoptosis in triple negative breast cancer cells
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- Braicu, C., Pileczki, V., Irimie, A. et al. Mol Cell Biochem (2013) 381: 61. doi:10.1007/s11010-013-1688-5
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p53 protein is probably the best known tumor suppressor. Earlier reports proved that human breast cancer cells expressing mutant p53 displayed resistance to apoptosis. This study is intended to investigate, the potential applications of RNA interference (RNAi) to block p53 expression, as well as its subsequent effect on cell growth, apoptosis and migration on a triple negative human breast cancer cell line (Hs578T). p53siRNA significantly reduced cell index (CI) compared to the control and we observed an inhibition of cellular migration in the interval of time between 0 and 30 h, as shown in the data obtained by dynamic evaluation using the xCELLigence System. Also, by using PCR-array technology, a panel of 84 key genes involved in apoptosis was investigated. Our studies indicate that the knockdown of p53 expression by siRNA modulates several genes involved in cell death pathways and apoptosis, showing statistically significant gene expression differences for 22 genes, from which 18 were upregulated and 4 were downregulated. The present research also emphasizes the important role of BCL-2 pro-apoptotic family of genes (Bim, Bak, and Bax) in activating apoptosis and reducing cell proliferation by p53siRNA treatment. Death receptors cooperate with BCL-2 pro-apoptotic genes in reducing cell proliferation. The limited success may be due to the activation of the antiapoptotic gene Mcl-1, and it may be associated with the resistance of triple negative breast cancer cells to cancer treatment. Thus, targeting p53siRNA pathways using siRNA may serve as a promising therapeutic strategy for the treatment of breast cancers.
Keywordsp53siRNATriple negative breast cellsCell proliferationMigrationApoptosis
Cancer, including breast cancer, is usually associated with aberrant cell proliferation and defective apoptosis induction due to the activation of oncogenes and/or inactivation of tumor suppressor genes. These molecular processes often provide the candidate targets for the development of cancer therapy . One of the encouraging targets is p53, a well-established and frequently mutated tumor suppressor in human cancers. Ever since its original discovery as an oncogene in 1979, and moreover, after its rediscovery as a tumor suppressor gene in 1989 , p53 has been the hot spot gene for cancer biologists on a quest to explain the mechanisms of tumor formation, and to validate it as a potential cancer therapy target [1, 3].
Breast cancer remains a main factor of death in the world . Breast cancer is a heterogeneous group of diseases. Triple-negative breast cancer refers to any breast cancer cells that do not express the genes for the estrogen receptor (ER), progesterone receptor (PR) or Her2/neu, and affects 15–20 % of patients with breast cancer. Consequently, triple-negative breast cancer does not respond to hormonal therapy or therapies that target HER2 receptors, having the worse prognostic . There is a critical and urgent need for developing therapeutic agents for this disease. Tumoral breast cancer cells that are expressing mutant p53 displayed resistance to apoptosis [5, 6]. Breast tumors are expressing a high amount of mutant p53-tumour suppressor gene (as measured by IHC). Many recent studies have been focused on finding out whether, the accumulated p53 in tumor cells has any precise roles supporting cellular proliferation. Now there is compelling evidence that mutant p53 may not only have lost its tumor-suppressive functions, but at the same time has acquired additional oncogenic properties, leading to the theory that mutant p53 could have achieved novel oncogenic “gain-of-function” activities [7, 8].
RNA interference is a research instrument for specific silencing of genes in mammalian cells and organisms by using exogenous, double-stranded siRNAs (small interfering RNAs). siRNAs are non-coding RNAs 21–23 nucleotides long that negatively regulate gene expression at post-transcriptional level. siRNAs represent an encouraging new class of molecules for cancer treatment via targeting the mutation- or overexpression-activated oncogenes. Several recent investigations have shown that siRNA can efficiently suppress oncogene expression in cancer cells [9–12].
p53 plays a crucial role in mediating cell response to various stresses, mainly by causing or repressing a number of genes involved in cell cycle arrest, senescence, apoptosis, DNA repair, and angiogenesis. The transcriptional program responsible for p53siRNA mediated apoptosis is not yet clearly defined.
p53 may favor the recovery of cells damaged by therapy [13, 14], therefore, acting as a survival factor preventing mitotic catastrophe, thus, p53 inhibitory therapies should be envisaged. This research was focused on exploring whether, p53 can become a novel therapeutic target, and whether siRNA-based approach can effectively treat p53-overexpressing triple-negative breast cancer. For this, we used p53siRNA to target p53 overexpression, and assessed its ability to suppress triple negative breast cancer growth by means of the xCELLigence system and PCR-array technology, by exploring a panel of 84 key genes involved in apoptosis. This study is based on preliminary optimization steps, which were conducted in order to establish the highest amount of p53siRNA gene inhibition with no toxic effects and no unspecific alteration of gene expression modulated by the transfection agent.
Materials and methods
The triple negative breast carcinoma cell line (Hs578T) was grown at 37 °C in a humidified atmosphere with 5 % CO2 in DMEM with 4500 mg/l glucose, that was supplemented with 10 % fetal bovine serum (Sigma-Aldrich), 2 mM glutamine, 100 UI/ml penicillin, and 100 mg/ml streptomycin (Sigma-Aldrich).
siRNA preparation and transfection
A volume of 5 ml siPORT NeoFX transfection agent was mixed in Opti-MEM (Gibco-Invitrogen), to a total volume of 100 ml, and then incubated for 10 min at room temperature. The p53siRNA was then diluted in 100 ml OPTI-MEM medium, to achieve a final concentration in the cell culture medium of 50 nM. Then, the diluted siRNA was mixed with the diluted siPORT NeoFX transfection agent; the mixture was incubated for 10 min at room temperature and dispensed into a culture plate; the cells were incubated until further assays.
Dynamic scanning of changes in cellular parameters and cell migration using the xCELLigence System
The xCELLigence system displays phenotypic changes in living cells by quantifying the electrical impedance across the electrodes at the bottom of each well of the tissue cultures plates. Impedance changes reflect cell numbers, viability, morphology and degree of adhesion, and are represented as cell index (CI) values. For the cell proliferation was used E-Plate 16, meanwhile, for migration assay was used a basic protocol for the RTCA DP instrument using CIM-Plate 16, with fetal bovine serum (FBS) as chemoattractant. Results shown are mean ± S.D. (n = 2) and are representative for two different experiments.
Apoptosis evaluation by flow cytometry and Hoechst 33342 staining
Post treatment cells were trypsinized washed twice with pre-chilled PBS, resuspended in 1× binding buffer at 1 × 106 cells/ml, and then incubated with Annexin V-FITC and Propidium Iodide (PI) (Becton–Dickinson, Germany) according to the manufacturer’s instructions. The mixed solution was gently vortexed and incubated in the dark on ice for 15 min. The apoptosis rate of cells was detected by a FacsCantoII flow cytometer using FACSDiva Software (Becton–Dickinson, Germany).
For Hoechst 33342 staining Hs578T cells were plated in 6-well plates and incubated 24 h with p53siRNA, in parallel with untreated cells. Then cells were washed once with PBS, and stained with 5 μg/ml Hoechst 33342 for 30 min at 37 °C in the dark. Following staining, cells were washed three times with PBS. The morphological features of apoptosis were observed by fluorescence microscopy with the magnification ×200.
Protein evaluation by immunoblotting
Cells were resuspended in 150 μl lysis buffer (20 mM Tris–HCl pH 7.5, 150 mM NaCl, 1 mM Na2EDTA, 1 mM EDTA, 1 % Triton, Complete Protease Inhibitor Cocktail (Roche, Bucharest Romania), then were sonicated for 30 s. The homogenates were centrifuged at 20 000×g for 10 min at 4 °C to remove insoluble fragments. Protein (30 μg) was subjected to 12 % SDS-PAGE, transferred on nitrocellulose membrane, and evaluate the protein expression level for p53siRNA, BNIP2, BAK1 using specific antibodies, 1:500 dilution (Cell Signalling, USA), in parallel with bactine evaluation (R&D, Bucharest, Romania), 1:1000 dilution.
RNA extraction and quality control
The total RNA from treated (50 nm p53siRNA) and untreated Hs578T cells was isolated using TriReagent (Sigma-Aldrich), according to the manufacturer’s recommendations for each triplicate sample, from three different experiments. The extracted RNA was treated with DNase and purified using the RNeasy Mini kit (Qiagen). The RNA concentrations were measured using the NanoDrop-1100 spectrophotometer. The quality of RNA was assessed using the Agilent 2100 Bioanalyzer. All of the samples had a RIN score of 8–10.
RT2 Profiler™ PCR array technology
The 84 genes that are involved in apoptosis were simultaneously assessed using the Human Apoptosis RT2 Profiler™ PCR Array (SABiosciences). The total RNA (350 ng) from all the samples was reverse transcribed using the RT2 First Strand kit (SABiosciences). RT2SYBR Green qPCR Master Mix (SABiosciences) in a 96-well plate (the Human Apoptosis RT2Profiler™ PCR Array) was used for cDNA synthesis. The PCR-array reaction was done on the LightCycler 480 instrument (Roche) as follows: 10 min at 95 °C for enzyme activation, followed by 45 cycles of 15 s at 95 °C and 1 min at 60 °C for the amplification step.
PCR array data analysis
The data were analyzed using the software package for the PCR Array System with the ΔΔCt method. The statistical analysis was performed to compare the gene expression values for the treated and untreated groups. P < 0.05 was considered statistically significant. The following housekeeping genes were used: B2M, HPRT1, and GAPDH. The ΔΔCt method was used to calculate the fold change. The genes with a fold change of ≤−1.25 or ≥1.25 were considered to be genes of interest, from three different experiments.
All experiments were performed at least in triplicate. All of the data were expressed as the average ± standard error of the mean (SEM). The differences were assessed using the t test. P < 0.05 was considered to be statistically significant. The mRNA levels were analyzed using the PCR array data analysis software with the ΔΔCt method, which is based on fold change calculations after normalizing the values for all genes to those of the housekeeping genes.
The anti-proliferative effect of p53siRNA measured using xCELLigence System
Apoptosis evaluation by flow cytometry and Hoechst 33342 staining
Protein evaluation by immunoblotting
Quantitative PCR array technology was used to evaluate the transcript on 84 key genes involved in apoptosis in p53siRNA transfected cells Hs578T cells versus untransfected cells, as shown in Table 1. No significant gene expression differences were observed in the case of the transfection reagent.
The candidate genes whose expression is altered in the p53siRNA versus control group
BCL2-associated agonist of cell death
BCL2-like 11 (apoptosis facilitator)
Myeloid cell leukemia sequence 1 (BCL2-related)
BCL2/adenovirus E1B 19 kDa interacting protein 2
Tumor necrosis factor receptor superfamily, member 1A
Tumor necrosis factor (ligand) superfamily, member 10
Tumor protein p53
Triple-negative breast cancer is one of the cancers which are most difficult to treat, due to the lack of a specific molecular target for existing treatment strategies . In our study, we evaluated the effects of p53-siRNA gene silencing in a triple negative breast cancer cell line. The downregulation of mutant-p53 by RNA interference (RNAi) partially inhibits cell proliferation as observed in the xCELLigence data after treatment.
Apoptosis is a completely regulated process, with an important and central role in the development and homeostasis of multicellular organisms. The apoptosis deregulation participates directly in the carcinogenesis process, being associated with the overexpression of anti-apoptotic genes, which leads to a selective survival advantage that promotes the proliferation of tumoral cells.
p53siRNA alters the expression of the genes related to cell death, cell morphology or cellular function and maintenance
Fold Regulation Up/down
BAD plays a unique role in survival signaling of cancer cells, this might be illustrated by the fact that BAD is a death regulator, which may stimulate tumor cell death pathways. BAD overexpression is related to enhanced survival in breast cancer patients.
BAK1 promotes programmed cell death by binding to, and counteracting the anti- apoptotic action of BCL2. Also, the up-regulation of BAK1 may lead to intensified sensitivity to chemotherapy.
BCL2L11 (Bim) has proven to have a essential role in the apoptosis answer in epithelial cell lines, including in Hs578T.
Mcl-1 is an antiapoptotic member of the Bcl2 family. Mcl-1 is crucially implicated in the regulation of cell survival and therefore subject to regulation by numerous mechanisms; thus, by gene knockdown, it can be used as a possible therapeutic target in triple negative breast cancer and leading to an increased response to treatment.
BNIP2 is implicated in the suppression of cell death, also may have an important role in apoptosis, by interacting with BCL-2 family of genes.
Overexpression of Casp1 is enough to induce programmed cell death in mammalian cells. Inflammatory marker, caspase-1 acts as a regulator of the proteolytic maturation of pro-interleukin-1 beta (IL1B) and its release during inflammation.
Inflammatory marker, caspase-4 was found to be upregulated in apoptosis-independent cell death processes.
TNFRSF1A has an significant role in death signal transduction, leading to the initiation of apoptosis in breast cancer cells.
Tumor necrosis factor (ligand) superfamily, member 10 (TNFSF10; TRAIL) is a tumor necrosis factor superfamily member, and causes apoptosis by crosstalk through intrinsic and death receptor-mediated apoptosis pathway.
TP53 tumor suppressor gene is a vital regulator of tissue homeostasis, and its inactivation at the gene or protein level conducts to oncogenesis and cancer progression. Perturbations of the p53 pathway are correlated with further aggressive and therapeutically refractory tumors.
BAD is a pro-apoptotic gene that is connected with death ligands. BAD connects upstream signal transduction pathways with the Bcl-2 family, modulating this checkpoint for apoptosis. Once BAD is activated, imbalance of Bcl-2 family members protein can trigger apoptosis via the intrinsic pathway [16, 19, 20].
Mcl1 is critically involved in the regulation of cell survival, and is therefore subjected to regulation by multiple mechanisms ; the present study reveals that p53siRNA negatively regulates the expression of the Mcl1 gene. Studies of stress response have demonstrated that Mcl1 plays an important role in the sensitization of cells to apoptotic signals. Mcl1 depletion sensitizes human breast cancer cells to respond to chemotherapy, as indicates related in vitro or in vivo data . The down-regulation achieved by p53siRNA may have important implications in triple negative breast cancer cells. Down-regulation of Mcl-1––but not of other antiapoptotic Bcl-2 members––is essential for the initiation of apoptosis. To increase efficiency of p53siRNA treatment, Mcl1 inhibitors should be used in parallel. Up to date, ten major caspases have been identified, being classified into the following categories: initiators (caspase-2,-8,-9,-10), effectors or executioners (caspase-3,-6,-7) and inflammatory caspases (caspase-1,-4,-5) . Antiapoptotic proteins BCL-2 family of genes may activate inflammatory caspases (Casp1 and Casp5), leading to interleukin-1b (IL-1b) production, as shown in a recent study . These two inflammatory caspases are able to modulate NFκB activation during the proinflammatory cytokine response 21 and inflammasome. These observations imply that, by association with other agents that are able to suppress NF-kB pathways, they may have an important role in the treatment of triple negative breast cancer . TNFRSF1A is one of the major receptors for the tumor necrosis factor-alpha (TNF-a), and is able to activate NFkB or to interact with BCL-2 protein family. Mcl-1 may serve as a direct substrate for TRAIL-activated inflammatory caspases, implying the existence of a novel TRAIL/caspase-1,4/Mcl1/Bim communication mechanism or “cross-talk” phenomenon between the extrinsic and the intrinsic apoptotic pathways, as was shown in similar previous studies .
These findings suggest that, by blocking the gene expression of mutant p53, the activation of other pro-apoptotic genes is promoted, leading to the activation and upregulation of different intracellular signaling pathways, including BCL-2 gene family, inflammatory caspases and death receptors. These signaling pathways promote autocrine and paracrine cell mediated death.
p53 could promote the convergence of the extrinsic and intrinsic apoptotic pathways, including in triple negative breast cancer cells. The present study provides early insight into the mechanisms of p53 pathways in triple negative breast cancer, as the PCR-array data show. Manipulating the expression of the p53 mutant gene is required for the induction of apoptosis by different Bcl-2 gene family members, as shown here.
This study was partially financed by a grant from the Romanian National University Research Council project PD 533/28.07.2010 “Combining chemotherapeutic effects of flavan-3-ols with RNA interference target therapy in cancer” and partially by a POSCCE 709/2010 Grant with title: “Clinical and economical impact of proteome and transcriptome molecular profiling in neoadjuvant therapy of triple negative breast cancer (BREAST IMPACT)”.
Conflict of interest
The authors report no conflicts of interest in this study.