Integrated Bioinformatic Analysis to Decipher the Contribution of Bisphenol-A in Cervical Cancer

doi:10.21203/rs.3.rs-3547884/v1

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Integrated Bioinformatic Analysis to Decipher the Contribution of Bisphenol-A in Cervical Cancer

https://doi.org/10.21203/rs.3.rs-3547884/v1

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Bisphenol A (BPA) is a synthetic chemical widely used as a monomer for producing polycarbonate plastics. The present investigation employed an in-silico approach to identify BPA-responsive genes and comprehend the biological functions affected using in vitro studies. A Comparative Toxicogenomics Database search identified 29 BPA-responsive genes in cervical cancer (CC). Twenty-nine genes were screened using published datasets, and thirteen of those showed differential expression between normal and CC samples. Protein-Protein Interaction Networks (PPIN) analysis identified BIRC5, CASP8, CCND1, EGFR, FGFR3, MTOR, VEGFA, DOC2B, WNT5A, and YY1 as hub genes. KM-based survival analysis identified that CCND, EGFR, VEGFA, FGFR3, DOC2B, and YY1 might affect CC patient survival. SiHa and CaSki cell proliferation, migration, and invasion were all considerably accelerated by BPA exposure. Changes in cell morphology, remodelling of the actin cytoskeleton, increased number and length of filopodia, elevated intracellular reactive oxygen species and calcium, and lipid droplet accumulation were noted upon BPA exposure. BPA treatment upregulated the expression of epithelial to mesenchymal transition pathway members and enhanced the nuclear translocation of CTNNB1. We showed that the enhanced migration and nuclear translocation of CTNNB1 upon BPA exposure is a calcium-dependent process. The present study identified potential BPA-responsive genes and provided novel insights into the biological effects and mechanisms affected by BPA in CC. Our study raises concern over the use of BPA.

Carcinogen

Bisphenol A

Endocrine disruptor

Environmental toxicant

Human cancer

Cervical cancer

Cervical cancer (CC) contributed to more than 604 127 new cases and 341 831 fatalities in 2020 globally (Singh et al., 2023). Asian countries contributed to more than 58% of global CC cases. India accounted for 21% of all cases (123907) and 23% of deaths (77 348) due to CC (Singh et al., 2023). The CC is on the rise in several low- and middle-income countries. Advanced CC is very aggressive, with a propensity for metastasis and resistance to treatment. The overall (5-year) survival rate of CC patients with lymph node metastasis is only 20–30% (Li et al., 2016; Zorzato et al., 2021). In vitro studies have shown that environmental factors, including xenoestrogens, may act as risk factors for CC and can enhance its aggressiveness (Eve et al., 2020; Fucic et al., 2012). Hence, there is a need to understand the risk factors and mechanisms responsible for the development and progression of CC.

Bisphenol A (BPA) is a colourless synthetic and organic substance widely used as monomers in producing polycarbonate plastics, epoxy resins, water bottles, the lining of food cans and wrapping, thermal paper, and medical and dermal equipment (Abraham & Chakraborty, 2020; Kubwabo et al., 2009; Manzoor et al., 2022). BPA can easily leach from consumer goods into food and drinking water and enter the human body by inhalation and transdermal routes (Tsai, 2006). BPA has been detected in human tissues and physiological fluids (Inadera, 2015; Vandenberg et al., 2012). Studies have also examined how exposure to BPA may contribute to female reproductive system cancers. (Garnick, 1989; Medellin-Garibay et al., 2023; Vandenberg et al., 2012)Furthermore, BPA exposure may possibly increase the likelihood of a few cancers below the oral reference dose set by the Environmental Protection Agency (Khan et al., 2021; Seachrist et al., 2016). Regulatory organizations have now expressed concern over using BPA as a plasticizer because of its ability to cause diseases at extremely low doses.

Studies on BPA exposure and CC are few and limited to model systems. Bisphenol shows weak estrogenic activities. A previous study showed a link between BPA levels in the human body and incidences of CC. Women with CC show high levels of urinary mono-(2-ethyl-5-hexyl) phthalate and BPA in the Mexican population (Medellin-Garibay et al., 2023). Urinary BPA and mono-(2-ethyl-5-hexyl) phthalate concentrations in the early- and late-stage groups of CC are 3.1 and 1.9 and 151.1 and 92.8 µg L^− 1, respectively (Medellin-Garibay et al., 2023). BPA exposure has been shown to induce microtubule and centrosomal abnormalities in cervical adenocarcinoma cells (Khan et al., 2023). For example, HeLa cells exposed to 100 nM BPA for 5 hrs showed microtubule abnormalities, notably an increase in unaligned chromosomes and mitotic cells with multipolar spindles (Kim et al., 2019). Grimaldi and coworkers showed that treatment of HeLa cells transfected with ARE motifs with 1 nM to 10 µM BPA for 16 hrs antagonized R1881-induced androgen receptor activity (Grimaldi et al., 2015). Pregnan X receptor (PXR) activation by BPA in HeLa cells transfected with human PXR has also been reported (Sui et al., 2012). Another study showed that a nanomolar concentration of BPA modulated estrogen signaling to enhance the migration and invasion of CC cells in vitro (Ma et al., 2015). BPA exposure resulted in the upregulation of Matrix metallopeptidase 9 (MMP9) and FN without any significant change in MMP2, vimentin (VIM), and Cadherin-2 (CDH2) in SiHa and HeLa cells (Ma et al., 2015). Furthermore, NF-κB activation correlated with MMP9 and FN upregulation and cell migration. The presence of BPA is linked with proliferative lesions of the uterus and sarcoma of the cervix (Pivonello et al., 2020).

Genome-wide screenings of CC cell lines and clinical samples produced massive molecular data. It has been proven that reanalysing these enormous volumes of information may yield molecular markers and new cancer treatment targets. In vitro and a few association studies suggested a potential link between BPA and CC. However, it is still unclear how BPA exposure alters the biological function and signaling pathways in CC. Hence, we aimed to identify and analyse the genes potentially regulated by BPA exposure and clarify their function using an in-silico approach and in vitro biochemical experiments. The Cancer Genome Atlas Cervical Cancer (TCGA-CESC) dataset and Comparative Toxicogenomics databases (CTD) were used to identify the genes that may be impacted by BPA exposure concerning CC. In addition, we built a map of protein‒protein interactions and found putative hub genes linked to BPA exposure. On a mechanistic level, BPA exposure increased the tumor-promoting characteristics and boosted the aggressiveness of CC cells. Morphological changes increased intracellular reactive oxygen species (ROS) and calcium (Ca²⁺), and an accumulation of intracellular lipid droplets were other notable changes observed upon BPA exposure. BPA upregulated epithelial-to-mesenchymal transition (EMT) and WNT signaling pathway members. More beta-catenin nuclear translocation and increased TOP flash activity was noted upon incubation with BPA. Moreover, we showed that BPA-induced migration, EMT, Wnt signaling activation, and nuclear translocation of beta-catenin are calcium-dependent processes. Collectively, our study identified the potential genes and pathways connected to BPA exposure in SiHa and CaSki cells.

2.1. CC datasets and BPA interactive genes (BIG).

We queried the Comparative Toxicogenomics Database using the search term "Bisphenol A" to discover the potential BIGs (Davis et al., 2023). We used the "sort and filter function" in Microsoft Excel to identify the genes relevant to BPA exposure and CC. We mined the TCGA-CESC dataset via the TACOO (http://tacco.life.nctu.edu.tw/) tool to retrieve the differentially expressed genes specific to CC. The gene lists from both databases were compared using Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/) to identify the potential BIGs.

2.2. Bioinformatic analysis

The BPA-responsive genes identified above were analysed using the ShinyGO v0.741 tool (Ge et al., 2020). ShinyGO is an online tool that provides information for gene ontology (GO) and pathways. We built a PPIN of BIG using STRING V11.5 with a confidence score above 0.4 (Szklarczyk et al., 2019). We used the cytoHubba plugin to identify and build the hub gene network. We utilized Cytoscape 3.9.1 software to depict the network (Chin et al., 2014). We used a KM plotter to predict the correlation between BIG expression and overall survival. PanDrugs, STITCH-5, and Drug-Gene Interaction Database 3.0 were used to predict interactions and drug prioritization and to create a network of drug-gene interactions. (Cotto et al., 2018; Szklarczyk et al., 2016). We estimated the immune cell abundance using the GSCA online tool (Chen et al., 2022).

2.3. Cell line maintenance and BPA treatments

SiHa and CaSki cells (NCCS, Pune) used in the study were cultured in 10% fetal bovine serum (FBS) containing phenol-red-free Dulbecco′s Modified Eagle′s Medium (DMEM) and Roswell Park Memorial Institute (RPMI) media in a CO₂ incubator. The cells were exposed to 1 pM, 1 nM, 1 µM, and 10 µM BPA in serum-free media for the indicated time points. Unexposed and DMSO-treated cells were kept as controls.

2.4. MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assay

An MTT assay was conducted where cells cultured in 96-well plates were exposed to different BPA concentration (1 mM, 1 µM, 1 nM, and 1 pM) in FBS-free media. At the end of 48 hrs, each well received 100 µg of MTT reagent (Sigma, USA). After 4 hours of MTT incubation, the absorbance of solubilized formazan crystals was assessed at 570 nm using a microplate reader (Thermo Fisher, USA). We calculated the percentage cell viability using the absorption data (Plumb et al., 1989).

2.5. Cell proliferation assay

A 5-day growth curve analysis quantified the cell proliferation rate. We cultured 50000 cells in a 35 mm dish and exposed them to multiple concentrations of BPA. Cells were detached by trypsin after 24 hours, 72 hours, and 120 hours. They were subsequently stained with trypan blue stain, and the number of viable cells was calculated with a haemocytometer (Kabekkodu et al., 2014).

2.6. Wound healing assay

Cells were cultured in complete media until they reached 80% confluency in a 6-well plate in FBS-free media for 24 hrs. We created a cell-free area in the middle of the cell culture dish using a 200 µl sterile tip. We washed the scratch area with phosphate-buffered saline (PBS) and activated cell migration by adding complete media containing the indicated concentration of BPA. Cells moving into the scratch area were monitored continuously until the wound was completely covered with cells using a microscope (CKX41, Olympus, Japan). We used ImageJ software (https://imagej.nih.gov/ij/) to determine the rate of wound closure by deducting the wound area at 0 hr from the wound area at various time points (Khan et al., 2022).

2.7. Agarose spot invasion assay

We dissolved low-melting agarose to prepare a 0.5% agarose solution. The agarose solution was cooled down and mixed with 50 ng/mL EGF. Using a micropipette, 10 µL of the agarose-EGF mix was placed in a 6-well plate and air-dried. SiHa and CaSki cells were detached by trypsinization, washed with FBS-free medium, and seeded onto agarose spot-containing wells. We maintained the cells in FBS-free media with various BPA concentrations. The cells cultured in agarose-EGF spots without BPA served as controls. The cells moving inside the agarose spot were monitored using a bright field microscope to calculate the extent of invasion (Ahmed et al., 2017; Wiggins & Rappoport, 2010).

2.8. Flow cytometry

We cultured the cells in FBS-free media containing different concentrations of BPA for 48 hrs. The cells were stained by incubating with 5 µM 2'-7'-Dichlorodihydrofluorescein diacetate (H2DCFDA) (Molecular Probes, USA) for 30 min at 37°C for ROS estimation. We incubated the cells with Fluo3AM dye (5 µM Molecular Probes, USA) in Hanks' balanced salt solution (HBSS) buffer deprived of Ca²⁺ and Mg²⁺ containing 0.02% Pluronic F-127 for intracellular calcium estimation. The cells unexposed to BPA served as a control. The mean fluorescence intensity of 10000 cells was computed using FACS Caliber (Becton Dickerson, USA) and BD Cell Quest software for estimating ROS and intracellular calcium (Khan et al., 2022).

2.9. Actin phalloidin staining.

Serum-starved SiHa and CaSki cells were grown in the presence of varying BPA concentrations for 48 hours on sterile coverslips in a 12-well plate. Cells were incubated for 5 min with 4% paraformaldehyde, washed 2 times with sterile PBS, and incubated with TRITC-labelled phalloidin (0.5 µg/mL, Sigma‒Aldrich, USA) and Hoechst (1 µg/mL, Sigma‒Aldrich, USA). After removing the excess stain and performing two PBS washes, we mounted the sample on a glass slide by applying a mountant (Vector Laboratories, USA). We imaged actin phalloidin-positive cells using a DMi8-TCS-SP8 confocal microscope (63x Oil immersion, objectives, Leica Microsystems, Germany) (Adiga et al., 2022; Khan et al., 2022).

2.10. Intracellular lipid droplet estimation

We cultured SiHa and CaSki cells on a polymer coverslip (8-well, chambered slide; Ibidi, Germany) in FBS-free medium with different concentrations of BPA for 48 hrs. We kept the cells in 4% paraformaldehyde for 5 min and stained them using 5 µg/mL Nile Red dye (Thermo Fisher Scientific, USA). After two washes with PBS, stained cells were imaged under a confocal microscope (63x oil immersion objective; excitation: 552 nm and emission: 636 nm). The amount of lipid droplets was quantified using LAS-X software (Adiga et al., 2023).

2.11. β-Catenin nuclear translocation

We cultured SiHa and CaSki cells on a sterile coverslip in FBS-free medium with the indicated concentration of BPA for 48 hrs. Cells were preincubated with 10 µM 1,2-bis(o-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid (BAPTA)-AM (Sigma‒Aldrich, USA) to reduce intracellular calcium levels (Bhat et al., 2022). Cells were fixed and permeabilized using 4% paraformaldehyde and 0.1% Triton X-100 for 5 minutes and then blocked with 5% Bovine serum albumin (BSA) for 1 hour. Cells were first incubated with 1:300 diluted anti-CTNNB1 antibody for 16 hrs at 4°C and then with 1:5000 diluted FITC-labelled secondary antibodies for 2 hrs at room temperature. Both antibodies were procured from CST, USA. The coverslips were counterstained with 1 µg/mL Hoechst (Sigma‒Aldrich, USA) and mounted onto a glass slide (Vector Laboratories, USA). The nuclear translocation of CTNNB1 was confirmed by DMi8-TCS-SP8 confocal microscopy. The images were processed using LASX software (Adiga et al., 2022).

2.12. Western blot analysis

Cells exposed to BPA for 48 hours in FBS-free media were washed with chilled PBS and subsequently lysed in radioimmunoprecipitation assay buffer (RIPA) buffer containing a protease inhibitor cocktail to extract protein. We estimated the protein concentration using a BSA kit (Sigma, USA). Approximately 30 to 40 µg of extracted protein was separated by PAGE and blotted onto a Nitran membrane from GE Healthcare, USA. After blocking with 5% BSA-TBST solution, membranes were probed with appropriate primary and HRP-conjugated secondary antibodies. The membranes were incubated with SuperSignal™ West Pico Chemiluminescent Substrate (Thermo Scientific, USA). The densitometric assessment of the Western blot images was carried out employing ImageJ software (Adiga et al., 2023).

2.13 TOP-FLASH/FOP-FLASH reporter assay

We used 20 ng of the pRL-SV40 (Promega, USA) vector and 500 ng/well of either TOP-FLASH vector or FOP-FLASH vector (Upstate Biotechnology, USA) to transfect SiHa and CaSki cells in a 12-well plate. Four hours post transfection, we exposed the transfected cells to FBS-free media containing different concentrations of BPA. We measured TCF/LEF transcriptional activity using the Dual Luciferase™ Reporter assay kit (Promega, USA). The luciferase reporter activity was normalized against Renilla luciferase activity (Adiga et al., 2022).

2.14. Statistical Analysis

The findings of the studies are depicted as the mean ± SD of experiments performed in duplicate and repeated three times. *p values < 0.05 were reported as statistically significant. Microsoft Office and GraphPad Prism were used for statistical analysis.

3.1. Identification of BIG

Figure 1 summarizes the study design used to discover the potential BIG in the CC via an in-silico approach. CTD database mining using “Bisphenol A” identified 5,809 disease associations. Filtering of 5,809 disease associations for cancer identified 473 cancer-related associations, including “uterine cervical neoplasms”. Our analysis identified 29 potential BPA-responsive genes (APOBEC3B, BIRC5, CASP8, CCND1, CLPTM1L, CTNNB1, CYLD, EGFR, ERCC1, FGFR3, DOC2B, HES1, HLA-DPB2, HOTAIR, JAK2, MTHFR, MTOR, MYC, NOTCH1, NOTCH2, PIAS3, POU4F1, RARB, STAT3, TERT, VEGFA, WNT2, WNT5A, and YY1). Thus, BPA exposure can induce aberrant expression of genes that are frequently upregulated in CC.

3.2. Analysis of BPA-responsive gene expression in CC

BGI specific to CC was identified by comparing the genes identified in CTD with differentially expressed genes from the TCGA-CESC and GEO databases to identify the BIG in CC. Among the 29 BIGs, APOBEC3B, BIRC5, CASP8, CLPTM1L, EGFR, FGFR3, HLA-DPB2, MTOR and YY1 were upregulated. The CTNNB1, CYLD, ERCC1, DOC2B, HES1, HOTAIR, JAK2, MTHFR, MYC, NOTCH1, NOTCH2, PIAS3, POU4F1, RARB, STAT3, TERT, VEGFA, WNT2 and WNT5A genes showed no changes between normal and tumor samples. Collectively, our in-silico analysis suggests that BPA exposure and CC share common genes.

3.3. Potential relationship between BIG and metastasis in CC

CC shows metastases to the vagina, bladder, rectum, uterus, and lymph nodes (Bhatla et al., 2021; Guimaraes et al., 2022). Metastatic illness develops in 15 to 61% of CC patients, often within the first two years of starting treatment (Li et al., 2016). CC that has spread to other body parts is typically incurable and shows a high recurrence rate, resistance to therapy, and high mortality rate. Hence, determining the genes that can cause metastasis is crucial. We performed a literature search for differentially expressed BPA-responsive genes to identify the metastatic association. We found that abnormal expression of genes such as BIRC5 (Lu et al., 2012), CASP8 (Mandal et al., 2023), EGFR (Yan et al., 2016), FGFR3 (Choi et al., 2016), and MTOR (Xu et al., 2022) correlated with metastasis in CC. Thus, BPA exposure may participate in metastasis by enhancing the expression of pro-metastasis genes in CC.

3.4. Functional Enrichment Analysis

Functional enrichment analysis of BIG (Fig. 2A-2D) identified the top 10 biological processes (Fig. 2A), cellular components (Fig. 2B), and molecular functions (Fig. 2C) enriched concerning BPA exposure. The top 10 pathways connected to BIG are shown in Fig. 2D. Disease association of BPA-interactive genes by DisGeNET analysis using Enrichr KG (https://maayanlab.cloud/enrichr-kg) showed a strong association with CC (P < 3.3086e-23) (Fig. 3C). Our results suggest that abnormally expressed BPA-responsive genes identified in our study are already connected to well-established tumor-promoting pathways and strongly associated with CC.

3.5. PPIN construction and hub gene identification

The PPIN of BIG generated using STRING identified the crucial genes of the network. The PPINs of 13 genes showed strong interactions consisting of 13 nodes and 15 edges with an enrichment p value of 0.0142 (Fig. 2E). The cytoHubba tool identified BIRC5, CASP8, CCND1, EGFR, FGFR3, MTOR, VEGFA, DOC2B, WNT5A, and YY1 as the top ten HGs of the PPIN network. The HG network consisted of 10 nodes and 15 edges with an enrichment p value of 0.00632 (Fig. 2F). Our analysis identified key genes modulated in response to BPA and targeting them could be attempted for CC management.

3.6. Prognostic utility of BIG

The prognostic utility of the BPA interactive gene was tested using the TACCO tool (Supplementary Fig. 1). The impact of abnormal expression of BIG EGFR, VEGFA, FGFR3, and DOC2B on overall survival was predicted using Cox regression and Kaplan‒Meier analysis for TCGA-CESC datasets (Supplementary Fig. 2).

3.7. Drug-Gene Interaction analysis

To find prospective drugs and the genes that they target, we carried out an investigation of drug-gene interactions. Analysis of 10 BIGs identified 9 genes and 20 drugs (Fig. 3A). We carried out a pandrug analysis to ascertain which approved medications are most likely to be repurposed. The pandrug analysis identified 20 approved drugs. Finally, we used the STITCH-5 tool to identify the interaction between BPA response genes and small molecules. The STITCH-5 interaction analysis showed 19 nodes and 79 edges (p < 5.8e-13, Fig. 3A).

3.8. BPA-responsive genes and immune infiltration

It has been demonstrated that the tumor microenvironment and immune cell infiltration influence tumor development, prognosis, and therapeutic response (Chen et al., 2022). Therefore, utilizing the TCGA-CESC cohort, we employed the GSCA method to investigate the relationship between BIG and immune cell enrichment and their capacity to infiltrate CC. Our study shows that BPA exposure could modulate the expression of genes related to immune infiltration (Fig. 3B)

3.9. BPA effect on CC cell viability

To examine the impact of BPA on the viability of SiHa and CaSki cells, we used the MTT assay. Our findings showed that 1 nM and 1 µM BPA enhanced cell viability in both cell types compared to control cells. The high BPA concentration (1 mM) showed a toxic effect on both cell lines (Fig. 4A).

3.10. BPA effect on the proliferation ability of CC cells

The results showed that exposure to 1 pM, 1 nM, and 1 µM BPA significantly enhanced SiHa and CaSki cell proliferation, with the highest increase observed with 1 µM BPA. In contrast, a 1 mM concentration of BPA showed the highest cell toxicity in both cell lines. BPA thus showed a pro-proliferative effect on CC cells at a low concentration (Fig. 4A & 4B).

3.11. BPA exposure enhances in vitro cell migration

The effect of BPA exposure on CC cell migration was tested by scratch wound assay. BPA-exposed cells showed a higher migration rate than unexposed cells (Fig. 5A). The rate of unexposed control SiHa cell migration was 25%, 39%, and 66% for 24 hrs, 48 hrs, and 72 hrs, respectively. The SiHa cells exposed to 1 pM BPA showed migration rates of 31%, 54%, and 78% for 24 hrs, 48 hrs, and 72 hrs, respectively. The SiHa cells exposed to 1 nM BPA showed migration rates of 39%, 70%, and 88% for 24 hrs, 48 hrs, and 72 hrs, respectively. The SiHa cells exposed to 1 µM BPA showed migration rates of 32%, 59%, and 60% for 24 hrs, 48 hrs, and 72 hrs, respectively. The migration rates of unexposed CaSki cells were 12%, 13%, 28%, and 39% after 24 hr, 48 hr, and 72 hr, respectively. CaSki cells exposed to 1 pM BPA showed migration rates of 10%, 21%, 41%, and 58% for periods of 24 hrs, 48 hrs, and 72 hrs, respectively. CaSki cells exposed to 1 nM BPA showed migration rates of 12%, 23%, 49%, and 70% for 24 hrs, 48 hrs, and 72 hrs, respectively. CaSki cells exposed to 1 µM BPA for 24 hrs, 48 hrs, and 72 hrs displayed migration rates of 17%, 28%, 43%, and 67%, respectively. Thus, low-dose BPA exposure can enhance the migration of CC cells.

3.12. BPA exposure induced in vitro invasion of SiHa and CaSki cells

We performed an agarose spot invasion assay to test the effect of BPA on CC invasion. Our findings show that low-dose BPA exposure significantly enhanced the invasive ability of CC cells (Fig. 4C). The average number of unexposed SiHa cells invading the agarose spot was 182, 340, and 465 for 24 hrs, 48 hrs, and 72 hrs, respectively. The average number of SiHa cells exposed to 1 nM BPA invading the agarose spot was 242, 439, and 516 for 24 hrs, 48 hrs, and 72 hrs, respectively. The average number of SiHa cells exposed to 1 µM BPA invading the agarose spot was 201, 410, and 493 for 24 hrs, 48 hrs, and 72 hrs, respectively. The average number of CaSki cells showing invasion in the absence of BPA was 2, 22, and 38 for 24 hrs, 48 hrs, and 72 hrs, respectively. The average number of CaSki cells exposed to 1 nM BPA invading the agarose spot was 4, 68, and 82 for 24 hrs, 48 hrs, and 72 hrs, respectively. The average number of CaSki cells exposed to 1 µM BPA invading the agarose spot was 3, 35, and 60 for 24 hrs, 48 hrs, and 72 hrs, respectively. Furthermore, we also measured the average depth of invasion by measuring the distance moved by the cells from the boundary of the agarose spot to the inside. We observed that the average depth of cells invading the agarose spot was significantly greater in 1 nM and 1 µM BPA-exposed SiHa and CaSki cells at 48 hr and 72 hr compared to the control group. Thus, BPA exposure can boost the invasive capacity of both cell lines.

3.13. BPA exposure increases intracellular ROS levels

We stained the BPA-exposed SiHa and CaSki cells (1 pM, 1 nM, and 1 µM BPA for 48 hr) with DCFDA and performed flow cytometry to understand the impact of BPA exposure on intracellular ROS levels. SiHa and CaSki cells showed an increase in ROS upon BPA exposure (Fig. 5B). The mean fluorescence intensities of unexposed and DMSO-exposed SiHa cells were 112.71 and 107.44, respectively. The exposure of SiHa cells to 1 pM, 1 nM, and 1 µM BPA resulted in mean fluorescence intensities of 116.88, 154.97 and 134.20, respectively. The mean fluorescence intensities of unexposed and DMSO-exposed CaSki cells were 86.16 and 96.27, respectively. The exposure of CaSki cells to 1 pM, 1 nM, and 1 µM BPA resulted in mean fluorescence intensities of 104.85, 176.06 and 194.95, respectively. Collectively, we showed that BPA exposure could elevate intracellular ROS levels in SiHa and CaSki cells.

3.14. BPA-enhanced intracellular calcium (Ca²⁺) in SiHa and CaSki cells

To determine how BPA exposure impacts intracellular Ca²⁺ levels, we stained BPA-exposed SiHa and CaSki cells with Fluo-3 AM and used flow cytometry. Intracellular calcium levels were measured by flow cytometry using Flow3AM dye. Our results showed that SiHa and CaSki cells exposed to 1 pM, 1 nM, and 1 µM BPA showed significantly higher intracellular Ca²⁺ than their respective unexposed cells (Fig. 5C).

3.15. BPA exposure alters SiHa and CaSki cell morphology

Changes in cell adhesion properties and cell shape can enhance the aggressive properties of cancer cells (Morgado-Diaz et al., 2022; Zhang et al., 2012). SiHa and CaSki cells exposed to BPA for 48 hrs were stained with actin phalloidin and imaged using confocal microscopy. BPA exposure altered the morphology and increased the cell scattering and number of irregularly shaped cells. In addition, BPA exposure increased the number of hair-like projections or filopodia (Fig. 6A). Exposure to 1 nM and 1 µM BPA showed the greatest changes in morphology and filopodia (Fig. 6A). Thus, low-dose exposure to BPA can induce morphological changes that may enhance the aggressive behaviour of SiHa and CaSki cells.

3.16. BPA exposure increased intracellular lipid droplet accumulation in SiHa and CaSki cells

Increasing evidence shows that lipid droplets play an active role in cancer cell proliferation, growth, and survival (Li et al., 2020; Petan et al., 2018). Therefore, we investigated the impact of 48 hours of exposure to 1 nM and 1 µM BPA on lipid droplets in SiHa and CaSki cells using Nile red staining and confocal imaging. We found that BPA exposure significantly enhanced Nile Red fluorescence intensity in both SiHa and CaSki cells compared with the corresponding unexposed cells (Fig. 6B). Unexposed, 1 nM BPA-exposed, and 1 µM BPA-exposed SiHa cells had mean fluorescence intensities of 0.662, 1.034, and 1.403, respectively. Unexposed, 1 nM BPA-exposed, and 1 µM BPA-exposed CaSki cells had mean fluorescence intensities of 4.533, 8.072, and 6.585, respectively.

3.17. BPA induced CTNNB1 nuclear translocation in CC cells

CTNNB1 activation and nuclear translocation promote invasion and metastasis in certain cancers (Clevers, 2006; Tian et al., 2011). We next tested whether BPA exposure increases the nuclear translocation of CTNNB1 in CC cells. Immunofluorescence microscopy analysis showed that SiHa and CaSki cells exposed to 1 nM and 1 µM BPA for 48 hrs showed increased nuclear accumulation of CTNNB1 compared with the corresponding unexposed cells (Fig. 7A).

BPA exposure increases EMT and WNT signaling pathway gene expression.

We finally assessed the expression of EMT and WNT signaling pathway members before and after exposure to BPA. We found that exposure to 1 nM and 1 µM BPA reduced CDH1 expression in both SiHa and CaSki cells. Exposure to 1 µM BPA upregulated the expression of c-Myc, CDH2, SLUG, VIM, and CCNE1 in both cell lines tested. Exposure to 1 nM BPA upregulated the expression of SLUG and c-Myc in both cell lines tested (Fig. 8A). Our data show the upregulation of key EMT and WNT signaling pathway members in response to BPA exposure, particularly at a 1 µM dose of BPA.

3.18. BPA increased the TOP FLASH activity in CC cells

We conducted a dual luciferase assay to evaluate the effect of BPA on TOPFLASH / FOPFLASH activity (Fig. 8C). TOPFLASH activity increased from 1 to 1.22 ± 0.22 and 1.42 ± 0.07-fold in 1nM and 1µM BPA exposed SiHa cells respectively, TOPFLASH fold change was reduced to 0.49 ± 0.04 and 0.73 ± 0.10 in 10µM BPATA and 1µM BPA + 10µM BPATA co-treated SiHa cells. Similarly, the fold change of TOPFLASH increased to 2.43 ± 0.13, 1.3 ± 0.15 and 2.01 ± 0.14 in 1nM, 1µM BPA and 1µM BPA + 10µM BPATA co-treated CaSki cells respectively. No significant difference 1.00 ± 0.09 was seen in 10µM BPATA treated CaSki cells. The results were adjusted to a Renilla luciferase reporter activity generated by SV40.

BPA is a synthetic compound used during the manufacturing of consumer goods. Humans are constantly exposed to BPA due to the widespread use of plasticized plastics. Several studies have associated BPA exposure with health problems, including reproductive disorders, obesity, diabetes, cardiovascular disease, and cancer (Khan et al., 2021; Khan et al., 2023; Liu et al., 2021; Seachrist et al., 2016; Xia et al., 2022). BPA exposure is associated with increased breast, ovarian, and prostate cancer incidence (Gao et al., 2015). Due to its tumor-promoting characteristics, BPA can be considered probably carcinogenic to humans. Furthermore, due to growing health concerns, BPA is banned in several countries. CC affects the well-being of women living in several developing and underdeveloped countries. Few studies have shown that BPA exposure might have an oncogenic role in CC. It is yet unknown how exposure to BPA affects cellular and molecular alterations and how these changes relate to CC. Hence, we sought to understand the genes and pathways associated with BPA exposure and CC using in silico analysis and in vitro biochemical experiments.

It has been demonstrated by us and others that reanalysing genome-wide data using an in-silico method aided in the discovery of possible cancer-causing genes and associated pathways. Nevertheless, the use of an in-silico approach to identify genes and pathways is limited in the toxicology field. Here, we investigated the involvement of putative genes and pathways that may have changed in response to BPA exposure and their relationship with CC by merging genome-wide data from the CTD, TCGA-CESC, and GEO datasets. Using functional enrichment analysis, we discovered the ontological terms and potential pathways that might be enriched in response to BPA exposure. We generated PPIN and hub genes relevant to BPA exposure and CC. Moreover, we analysed the metastatic potential of BIGs and potential drugs that can be repurposed against CC. Perhaps this study uses a computation approach to look at the potential of BIGs in CC.

Our integrated bioinformatic analysis identified potential genes whose expression can be modulated by BPA exposure. Thirteen out of 29 BPA-responsive genes showed significant differential expression between normal and tumor samples. Gene ontology analysis suggested the enrichment of growth- and proliferation-related genes. This observation is consistent with our data showing that BPA exposure enhances the proliferation of SiHa and CaSki cells. HPV infection is a key event in CC development (Burd, 2003). Human papilloma infection emerged as one of the top 10 enriched pathways. Thus, BPA exposure may promote HPV infection by modulating CASP8, CCND1, WNT5A, EGFR, MTOR, and VEGFA expression. The relationship between aberrant expression of CASP8, CCND1, WNT5A, EGFR, MTOR, and VEGFA with HPV infection is well established. We constructed the PPIN of 13 differentially expressed genes and identified BIRC5, CASP8, CCND1, EGFR, FGFR3, MTOR, VEGFA, DOC2B, WNT5A, and YY1 as hub genes of the PPIN network. Prior research has demonstrated that abnormal expression of ten hub genes can contribute to CC. For example, BIRC5 is an anti-apoptotic gene, and its overexpression promotes cell survival. CASP8 downregulation may inhibit apoptosis and promote metastasis and drug resistance. CCND1 is a cell cycle regulator, and its overexpression is reported in CC. Few studies have shown that overexpression of EGFR, FGFR3, VEGFA, and YY1 contributes to poor prognosis and negatively impacts CC patient survival. In CC, mTOR signaling is active, and this activity is associated with CC cell survival. DOC2B downregulation promoted EMT and WNT signaling activation, senescence inhibition, and mitochondrial dysfunction in CC. WNT5A overexpression negatively affects overall survival and promotes metastasis in CC. Collectively, our data suggest that BPA-responsive genes are abnormally expressed and can impact patient survival.

CTD database analysis suggested a strong association between BPA and CC. We built a prognostic model based on 13 differentially expressed BPA-responsive genes, as the abnormal expression of some of these genes has already been reported to influence patient survival. Random forest analysis suggested that the expression analysis of hub genes could help predict patient survival. The expression of EGFR, VEGFA, FGFR3, and DOC2B affected the duration of overall survival of CC patients. We also identified a set of genes (CCND1, DOC2B, and YY1) whose deregulated expression contributed to the recurrence-free survival of CC patients. Furthermore, a few BPA-responsive genes, BIRC5, CASP8, EGFR, FGFR3, and MTOR, even have the potential to promote or inhibit metastasis. Therefore, by activating these genes and pathways, BPA exposure could foster metastasis, affecting patient survival. More detailed functional investigations are required to unravel the role played by BIGs in metastasis. The development of therapy resistance is a key problem affecting patient survival in CC. The use of new targets and the repurposing of drugs may help overcome therapy resistance in cancers. Hence, we scanned potential drugs against BPA-responsive genes using an in-silico approach. We identified new targets and drugs that can be repurposed against CC. In addition, we also noted that the abnormal expression of BPA-responsive genes can also participate in pathways leading to immune infiltration.

A previous study showed that BPA exposure enhanced the migration and invasive ability of CC cell lines (Ma et al., 2015). We subjected SiHa and CaSki cells to a variety of cell biology and biochemical studies to comprehend the biological function and signaling pathways modulated by BPA. Our results align with research by Ma and colleagues, who found that BPA exposure enhances the proliferative, migratory, and invasive ability of CC cells. The motility and invasive behaviour of cancer cells are intricately connected with morpho dynamics. Actin cytoskeletal networks are critical for regulating morpho dynamics (Burke et al., 2014; Manich et al., 2018). Hence, upon BPA treatment, we analysed the morphological changes and actin cytoskeletal arrangements in CC cells by actin-phalloidin staining. BPA treatment induced significant changes in cell morphology by actin cytoskeletal rearrangements in CC cells. BPA exposure increased the number and length of filopodia, particularly at 1 µM in SiHa cells and 1 nM and 1 µM in CaSki cells. Filopodia are hair-like projections in the cell surface used by cells for cell migration (Meyen et al., 2015). Filopodia promote cell migration, and cancer cells have denser filopodia (Arjonen et al., 2011; Kyykallio et al., 2020). Hence, we propose that the accelerated cell migration and invasion in response to BPA treatment may have been influenced by changes in cell shape and an increase in the number and length of filopodia.

To foster metastasis, cancer cells undergo EMT, which is characterized by altered cell shape, enhanced cell motility, and invasion. The cells undergoing EMT show a loss of epithelial markers with a simultaneous increase in mesenchymal markers and EMT transcription factors (Serrano-Gomez et al., 2016). CDH1 is a tumor suppressor gene often downregulated during EMT (Pecina-Slaus, 2003; Shenoy, 2019). In contrast to CDH1 downregulation, cells programmed for EMT often show upregulation of CDH2, SNAI1, SLUG, VIM, c-MYC, and CCNE1. The abnormal expression of these genes is well established in CC. The role of these genes in cell proliferation, migration, and invasion is well established in CC. CTNNB1 is a member of the WNT signaling pathway whose cytoplasmic accumulation and subsequent nuclear translocation promote proliferation, migration, and invasion via activation of c-MYC (Gao et al., 2018; Liu et al., 2022). BPA exposure increased nuclear accumulation of the active form of CTNNB1. Thus, the increase in c-MYC expression may be due to a significant increase in the nuclear translocation of the active form of CTNNB1 in response to BPA exposure.

Earlier studies have shown that BPA induces ROS in several cancer cell lines (Gassman, 2017; Khan et al., 2023; Nguyen et al., 2022). Considering the crucial function that ROS play in cancer, we analysed intracellular ROS upon BPA treatment. The findings from our study provide compelling evidence that BPA exposure-mediated disruption in ROS homeostasis may be linked to enhancing the aggressive behaviour of SiHa and CaSki cells. Hence, more detailed investigations are needed to unravel the role played by elevated intracellular ROS in enhancing the aggressive behaviour of CC cells. In addition to ROS, we also noted a significant increase in intracellular calcium in SiHa and CaSki cells upon BPA treatment. Cancer cells show alterations in intracellular calcium homeostasis. Elevation in intracellular calcium levels significantly increased the proliferative, migratory and invasive behaviour of cancer cells (Stewart et al., 2015; Zheng et al., 2023). We demonstrated that the BPA-induced migration and nuclear accumulation of CTNNB1 were greatly decreased by the depletion of intracellular calcium using BAPTA. Cancer cells modify their lipid metabolism to support uncontrolled growth and proliferation and, hence, accumulate more lipid droplets (Antunes et al., 2022). Furthermore, lipid droplets promote cell survival and foster tumor progression by ensuring energy production (Petan, 2023). When exposed to BPA, lipid droplet density was enhanced, as evidenced by Nile red staining and confocal imaging. The increase in lipid droplet accumulation upon BPA treatment may have contributed to the increased proliferation and migration of CC cells. To comprehend the function of BPA in lipid droplet accumulation and its contribution to controlling the biological behaviour of CC cells, more in-depth mechanistic studies are needed.

We investigated the potential genes and pathways that are common between BPA exposure and CC using in silico analysis and in vitro biochemical experiments. In-depth research is needed to determine the functional relevance of known and new BIGs identified in the present study. The increase in proliferation, migration, and invasion of SiHa and CaSki cells upon BPA treatment could be linked to increased intracellular ROS, calcium, and lipid droplet accumulation. BPA exposure activated EMT and nuclear accumulation of CTNNB1 in SiHa and CaSki cells. Our research raised the possibility of a connection between BPA-responsive genes and genes expressed differently during CC. BPA exposure could be a risk factor for developing CC. To support our findings, more in-depth epidemiological and mechanistic research is needed.

BAPTA: 1,2-bis(o-aminophenoxy)ethane-N,N,N′,N′-tetraacetic acid; BPA: Bisphenol A; BSA: Bovine serum albumin; BIRC5: Baculoviral IAP Repeat Containing 5; Ca2+: Calcium; CAPS8: Caspase-8; CC: cervical cancer; CDH2: Cadherin-2; CCNE1: Cyclin E1; CCND1: Cyclin D1; CTD: Comparative Toxicogenomics databases; CTNNB1: catenin Beta 1; DCFDA: 2'-7'-Dichlorodihydrofluorescein diacetate; DOC2B: Double C-2 like domain beta; EGFR: epidermal growth factor receptor; EMT: Epithelial-to-mesenchymal transition; FGFR3: Fibroblast growth factor receptor 3; MTOR: Mammalian target of rapamycin; PBS: Phosphate-buffered saline; PPIN: Protein-protein interaction networks; ROS: Reactive oxygen species; TCF/LEF: T-cell factor/lymphoid enhancer factor; TACCO: Transcriptome Alterations in CanCer Omnibus; TCGA: The Cancer Genome Atlas; VEGFA: Vascular Endothelial Growth Factor A; VIM: vimentin; WNT5A: Wnt Family Member 5A; YY1: Yin Yang 1.

Funding

Directorate of Minorities Fellowship for Minority Students, Government of Karnataka, India (Grant Number: DOM/FELLOWSHIP/CR-10/2019-20).

Consent for publication

All authors read and approved the final manuscript.

Ethical approval

Not applicable.

Consent for participation

Not applicable.

Competing Interests

“The authors have no relevant financial or non-financial interests to disclose.”

Availability of data and materials

All the data retrieved and analysed in this study are included in the manuscript, and additional information has been provided as supplementary files.

Author Contributions

“All authors contributed to the study conception and design. Shama Prasada Kabekkodu: Conceptualization, Writing – review & editing, Supervision, Funding acquisition; Nadeem Khan G: Methodology, Visualization, Validation, Formal analysis, Investigation, Writing – original draft; Divya Adiga: Methodology, Validation, Investigation, Writing – original draft; Padmalatha S Rai: Formal analysis, Writing - review & editing; All authors read and approved the final manuscript.”

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No competing interests reported.

SupplimentaryTable1.docx
Supplementary Table 1: List of antibodies used in the present study.
Supplimentaryfigure1.tif
Supplementary Figure 1: A) The model built from the BPA and its target genes revealed the T staging. The classification prediction values are on the x-axis. Patients are expected to be in the T1, T2 group or the T3, T4 group, depending on whether their prediction value is more than 0.5 or less than 0.5. B) The BPA and its target genes were used to build a model, which produced results for normal staging. Prediction values for classification are represented on the x-axis. Patients are expected to belong to the N0 group and the N1, N2, and N3 groups, respectively, depending on their prediction value, which might be more or lower than 0.5. C) The categorization of the M stage (distant metastasis) using the BPA and its target genes. The prediction values for classification are on the x-axis. Patients with prediction values above and below 0.5 are anticipated to belong to the M1 group and the M0 group, respectively. D) Prediction of overall survival model for cervical cancer patients on BPA which exploits it in order to divide samples into high- and low-risk categories. Kaplan-Meier survival plot along with the number of patients that were still surviving at every specific time point E) Prediction of disease-free survival model for cervical cancer patients on BPA which exploits it in order to divide samples into high- and low-risk categories. Kaplan-Meier survival plot along with the number of patients that were still surviving at every specific time point.
Supplimentaryfigure2.tif
Supplementary Figure 2: Overall survival analysis for the top 10 hub genes.

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Integrated Bioinformatic Analysis to Decipher the Contribution of Bisphenol-A in Cervical Cancer

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Abstract

Figures

1. INTRODUCTION

2. MATERIALS AND METHODS

2.1. CC datasets and BPA interactive genes (BIG).

2.2. Bioinformatic analysis

2.3. Cell line maintenance and BPA treatments

2.4. MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assay

2.5. Cell proliferation assay

2.6. Wound healing assay

2.7. Agarose spot invasion assay

2.8. Flow cytometry

2.9. Actin phalloidin staining.

2.10. Intracellular lipid droplet estimation

2.11. β-Catenin nuclear translocation

2.12. Western blot analysis

2.13 TOP-FLASH/FOP-FLASH reporter assay

2.14. Statistical Analysis

3. RESULTS

3.1. Identification of BIG

3.2. Analysis of BPA-responsive gene expression in CC

3.3. Potential relationship between BIG and metastasis in CC

3.4. Functional Enrichment Analysis

3.5. PPIN construction and hub gene identification

3.6. Prognostic utility of BIG

3.7. Drug-Gene Interaction analysis

3.8. BPA-responsive genes and immune infiltration

3.9. BPA effect on CC cell viability

3.10. BPA effect on the proliferation ability of CC cells

3.11. BPA exposure enhances in vitro cell migration

3.12. BPA exposure induced in vitro invasion of SiHa and CaSki cells

3.13. BPA exposure increases intracellular ROS levels

3.14. BPA-enhanced intracellular calcium (Ca2+) in SiHa and CaSki cells

3.15. BPA exposure alters SiHa and CaSki cell morphology

3.16. BPA exposure increased intracellular lipid droplet accumulation in SiHa and CaSki cells

3.17. BPA induced CTNNB1 nuclear translocation in CC cells

3.18. BPA increased the TOP FLASH activity in CC cells

4. DISCUSSION

5. CONCLUSION

Abbreviations

Declarations

References

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Supplementary Files

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3.14. BPA-enhanced intracellular calcium (Ca²⁺) in SiHa and CaSki cells