RNA sequencing identified novel target genes for Adansonia digitata in breast and colon cancer cells

Abstract

Adansonia digitata exhibits numerous beneficial effects. In the current study, we investigated the anti-cancer effects of four different extracts of A. digitata (polar and non-polar extracts of fruit powder and fibers) on the proliferation of human colon cancer (HCT116), human breast cancer (MCF-7), and human ovarian cancer (OVCAR-3 and OVCAR-4) cell lines. RNA sequencing revealed the influence of the effective A. digitata fraction on the gene expression profiles of responsive cells. The results indicated that only the polar extract of the A. digitata fibers exhibited anti-proliferative activities against HCT116 and MCF-7 cells, but not ovarian cancer cells. Moreover, the polar extract of the fibers resulted in the modulation of the expression of multiple genes in HCT116 and MCF-7 cells. We propose that casein kinase 2 alpha 3 (CSNK2A3) is a novel casein kinase 2 (CSNK2) isoform in HCT116 cells and report, for the first time, the potential involvement of FYVE, RhoGEF, and PH domain-containing 3 (FGD3) in colon cancer. Together, these findings provide evidence supporting the anti-cancer potential of the polar extract of A. digitata fibers in this experimental model of breast and colon cancers.

Keywords

colon cancer RNA sequencing LC-HRMS cell proliferation HCT-116 MCF-7

Introduction

Adansonia (genus) digitata (species) (AD; also known as Gongolase or baobab) is a popular African tree that possesses both commercial and nutritional values. The tree is enriched with numerous ingredients, such as bioflavonoids, phytosterols, minerals, and amino acids.¹ AD belongs to the Malvaceae family (the mallows), which is mainly found in the woodlands of African savannah. It can tolerate high temperatures and survive long periods of drought. The tree is deciduous (sheds leaves seasonally) and known by many other names, such as the monkey-bread tree, the dead-rat tree (owing to its fruit shape), and the upside-down tree (branches resemble roots after the leaves fall off).^1,2 The fruit of this tree consists of powdery pulp and large seeds, which are surrounded by many fibers. Besides being edible, the leaves, fruit, seeds, stem, and bark of AD have a broad range of reported medicinal uses.² The beneficial biological effects exhibited by AD include its anti-inflammatory, antioxidant, and antimicrobial activities. Other uses have also been reported for this plant, including its use as an analgesic, immunostimulant, and insect repellent, which makes it a suitable alternative for various drugs.¹ Moreover, it was recently reported to exhibit an antihyperlipidemic effect.³ The leaf extract of AD inhibits pro-inflammatory responses via inhibition of the inducible form of nitric oxide synthase enzyme, which is mediated by the suppression of the nuclear factor kappa beta, without any cytotoxic effects.⁴

The AD fiber extract exhibits anti-inflammatory and analgesic effects, with its analgesic effect being comparable to that of the standard analgesic, aspirin.⁵ Researchers have also confirmed the anti-malarial potential of the AD stem and bark extract using an in vivo model.⁶ This finding was also supported by another study,⁷ which reported that the progression of malaria infection was inhibited by the AD stem-bark extract in a mouse model.⁷ In a similar context, numerous beneficial effects were recently reported for other natural products. For example, the crude extract of Selaginella repanda exhibited antibacterial and antioxidant effects and demonstrated anti-cancer activities against the breast (MCF-7), colon (HCT116), and lung cancer (A549) cell lines.⁸ Also, Manuka honey, which is rich in phenolic compounds, selectively inhibited the proliferation of colon cancer cell lines (HCT116 and LoVo) by inducing apoptosis and cell cycle arrest, without exerting similar effects in normal non-cancerous cells.⁹ Another recent report¹⁰ indicated the beneficial use of a transformed species of strawberry, in which the enzyme, anthocyanidin synthase, was overexpressed. The transgenic strawberry fruit extract exerted anti-cancer effects in human hepatic cancer cells by increasing the levels of free radicals and inducing cellular apoptosis. Likewise, another study reported the beneficial anti-cancer effects exhibited by the crude extracts of herbal ingredients, including their antioxidant, anti-angiogenic, and other medicinal properties that could aid in the prevention and treatment of cancer.¹¹

Based on the broad efficacy of AD extracts, we hypothesized that AD might exhibit anti-cancer effects. Therefore, in this study, we investigated the anti-cancer potential of the polar and non-polar extracts of the fruit powder and shell inner fibers of AD plant in cell line models of breast, colon, and ovarian cancers. RNA sequencing-based gene expression profiling and bioinformatic analyses were also performed to explore the potential underlying mechanisms associated with the anti-cancer activities of the effective extract.

Materials and methods

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis of plant extracts

The fruits of the AD tree were brought from Sudan by our co-investigator, Dr. Arafat Goja. The outer shells of the fruits were broken down and the fibers surrounding the fruit and the fruit powder were separated and collected. The fruit fibers and powder portions were then air-dried until the moisture conditions were stable.

Extraction

Approximately 5 g of the dried powdered plant materials (fibers or fruit powder) was separately extracted successively, first with dichloromethane (as a non-polar fraction) and then with methanol (as a polar fraction), using a Soxhlet apparatus. Each extract was evaporated under vacuum to form a residue. One milligram samples of each of the four residues (polar extract of the fruit powder (PEFP), non-polar extract of the fruit powder (NPEFP), polar extract of the fibers (PEF), and non-polar extract of the fibers (NPEF)) were accurately weighed and dissolved in 10 mL methanol. Thereafter, 1 mL of this solution was filtered through a 0.2 µm polytetrafluoroethylene filter into a high-performance liquid chromatography (HPLC) vial, and subjected to LC-HRMS analysis.

Procedure for LC-HRMS analysis

High-resolution mass spectrometry (MS) data were obtained using an LTQ Orbitrap mass analyzer coupled to an HPLC system (Photo diode array (PDA) detector, PDA Autosampler, and pump) (Thermo Fisher Scientific, Massachusetts, USA). The following conditions were used: capillary voltage, 45 V; capillary temperature, 260°C; auxiliary gas flow rate, 10−20 arbitrary units; sheath gas flow rate, 40−50 arbitrary units; spray voltage, 4.5 kV, and mass range 100−2000 emu (maximal resolution of 30,000). For LC-HRMS analysis, a SunFire C18 Analytical HPLC Column (5 μm, 4.6 × 150 mm (Waters™, Waters Corporation, Milford, Massachusetts, United States)) was used with a mobile phase of 0%–100% methanol (MeOH) over 30 min at a flow rate of 1 mL min⁻¹. Data analysis was performed using Xcalibur 3.0 (Thermo Fisher Scientific, Massachusetts, USA) and dereplication was carried out using the Dictionary of Natural Products Database v.23.1.

Cell proliferation assessment

MCF-7 (breast), HCT116 (colon), and OVCAR-3 and OVCAR-4 (ovarian cancer) cells (American Type Culture Collection (ATCC), Virginia, USA) were cultured in Dulbecco’s modified eagle’s medium (DMEM) (for HCT116 and MCF-7) and Roswell Park Memorial Institute (RPMI) medium (for OVCAR-3 and OVCAR-4) (both media were from Sigma-Aldrich, Missouri, USA). After being confluent, cells were sub-cultured, counted, and 1 × 10⁴ cells of each cell line were seeded in each well of 96-well tissue culture plates in triplicate. The cells were then incubated overnight at 37°C with 5% carbon dioxide (CO₂) in a humidified atmosphere. The next day, serial dilutions of the four AD extracts were prepared and all cell types were treated with increasing concentrations (0–200 µg/mL). One set of wells was used as the double negative control (medium only) and another set was used as the single negative control (cells + medium only). The treated cells were incubated under standard tissue culture conditions (37°C with 5% CO₂ in a humidified atmosphere) for 72 h. The Cell Counting Kit-8 (CCK-8) (#CC2012; MOLEQULE-ON^®, Auckland, New Zealand) reagent (10 µL) was then added to each well and the plates were re-incubated under the same conditions for 1–2 h. The absorbance was calculated at 450 nm using an ELx808 Microplate Reader (BioTek, Vermont, USA). The mean absorbance value of the double negative control was subtracted from that of the single negative control and the treated cells. The cell proliferation was calculated as a percentage of 100% cell proliferation (a single negative control). The data are presented as dose-response curves.

RNA isolation

The HCT116 and MCF-7 cells were subcultured, counted, and plated in 100 mm Petri dishes (three replicates) and incubated overnight under standard tissue culture conditions (37°C with 5% CO₂ in a humidified atmosphere) to adhere. The next day, the cells were treated with either the DMEM medium or PEF (100 µg/mL). The treated cells were then incubated overnight under standard culture conditions. The supernatant medium was then aspirated and the cells were washed twice in ice-cold phosphate-buffered saline (Sigma-Aldrich, Missouri, USA) before being lysed in the lysis buffer provided with the RNA extraction kit. Total RNA was then isolated according to the protocol described in the handbook of the RNeasy^® Mini Kit (#74104; QIAGEN^®, Hilden, Germany). The purity and quality of the RNA were assessed using a DS-11+ Spectrophotometer (DeNovix Inc., Wilmington, USA) and by performing gel electrophoresis before storing it at −20°C until sequencing.

RNA sequencing and bioinformatics analysis

The RNA sequencing technology^12,13 was employed to obtain the gene expression profiles of the control and treated MCF-7 and HCT116 cells. Data were first examined for quality to distinguish the clean and dirty raw reads. The dirty reads are reads containing adapter sequences, with a high content of unknown bases, and/or low quality. The clean reads were further subjected to multi-aspect quality control checks using different mapping matrices and alignment methods¹⁴ and were sorted in the FASTQ format.¹⁵ The clean reads were filtered using the SOAPnuke software v.1.5.2 (https://github.com/BGI-flexlab/SOAPnuke). The percentage of clean data in different samples and the quality control analysis results are provided in the Supplemental Tables S1 and S2. Genome mapping was performed according to the hierarchical indexing for spliced alignment of transcripts (HISAT) using the HISAT2 software v.2.0.4 (Parameters: –phred64 –sensitive -no-discordant –no-mixed -I 1 -X 1000; http://www.ccb.jhu.edu/software/hisat).

Gene expression quantification

The clean reads were mapped to the reference genome using the Bowtie2 biosource portal¹⁶ and Bowtie2 software v.2.2.5 (Parameters: -q –phred64 –sensitive –dpad 0 –gbar 99999999 –mp 1,1 –np 1 –score-min L,0,-0.1 -I 1 -X1000 –no-mixed –no-discordant -p 1 -k 200; http://bowtie-bio.sourceforge.net/Bowtie2/index.shtml). Gene expression was quantified using RNA-Seq by Expectation-Maximization (RSEM) software package v.1.2.12 (Parameters: default; http://deweylab.biostat.wisc.edu/RSEM)¹⁷ using the Fragments Per Kilobase of transcript per Million mapped reads (FPKM) to identify the upregulated and downregulated genes in each sample. The higher the FPKM value, the greater the number of fragments of the given gene, which indicates its high expression. Figure 1 shows the FPKM values in the control HCT116 cells (A), Gongolase-treated HCT116 cells (B), control MCF-7 cells (C), and Gongolase-treated MCF-7 cells (D). Differential gene expression analysis was performed according to the Poisson distribution.¹⁸

Figure 1.

Histogram distribution of gene expression levels in HCT-116 and MCF-7 cells. The X-axis is FPKM value (log-transformed). The Y-axis is the gene number of the corresponding FPKM.

Statistical and bioinformatics analyses

Statistical analysis was performed using the GraphPad Prism software v.7. Analysis of variance (ANOVA) was used for multiple comparisons and the difference between the groups was considered significant at p ≤ 0.05. Bioinformatics analysis was performed using the filtration, mapping, and referencing methods, as indicated in the Materials and Methods section. The RSEM software package (v.1.2.12 )¹⁷ was used for the quantification of gene expression.

Results

LC-HRMS analysis

LC-HRMS analysis of the four different extracts of AD was performed to identify the potential bioactive compounds; the data are summarized in Table 1. Figures 2 and 3 show the chromatograms obtained from LC-HRMS analysis, displaying the relative abundance values of individual ingredients identified in the non-polar (Figure 2) and polar (Figure 3) extracts of the inner (fruit powder) and the outer (fiber) portions of the AD fruit. Among all the four extracts, PEF contained the kaempferol-3-O-p-coumaroyl-β-D-glucopyranoside, which was only identified in this fraction, albeit at a low relative abundance. In addition, the outer portion (fibers) contained other ingredients that were common in both the polar and non-polar extracts, the concentrations of which varied considerably between the different fractions as revealed by the chromatograms (Figures 2 and 3).

Table 1.

LC-HRMS analysis of the polar and non-polar extracts of the Adansonia fruit portions.

Rt (min)	Accurate m/z	Quasi-form	Suggested formula^a	Tentative identification^b	PEFP	PEF	NPEFP	NPEF
4.41	291.0852	[M + H]⁺	C₁₅H₁₄O₆	Catechin	–	+	–	+
4.70	579.1469	[M + H]⁺	C₃₀H₂₆O₁₂	Procyanidin B1	–	+	–	+
5.02	581.1508	[M + H]⁺	C₂₆H₂₈O₁₅	Kaempferol-3-O-sambubioside	–	+	–	+
5.99	579.1462	[M + H]⁺	C₃₀H₂₆O₁₂	Kaempferol-3-O-p-coumaroyl-β-D-glucopyranoside	–	+	–	–
8.40	595.1415	[M + H]⁺	C₃₀H₂₆O₁₃	Gallocatechin-4,8-epicatechin	+	–	–	–
8.65	595.1651	[M + H]⁺	C₂₇H₃₀O₁₅	Kaempferol-3-O-rutinoside	+	–	–	–
12.54	273.1126	[M + H]⁺	C₁₆H₁₆O₄	Mansonone M	–	–	+	–
12.90	275.1270	[M + H]⁺	C₁₆H₁₈O₄	Gossyvertin	–	–	+	–
14.28	279.1221	[M + H]⁺	C₁₅H₁₈O₅	Populene G	+	–	+	–
14.54	285.0755	[M + H]⁺	C₁₆H₁₂O₅	Genkwanin	+	+	+	+
15.01	289.1792	[M + H]⁺	C₁₈H₂₄O₃	Populene D	–	–	+	–
15.26	289.0703	[M + H]⁺	C₁₅H₁₂O₆	Dihydrokaempferol	+	–	+	–
15.58	289.0554	[M + H]⁺	C₁₅H₁₀O₆	Kaempferol	+	+	+	+
16.36	301.0700	[M + H]⁺	C₁₆H₁₂O₆	Chrysoeriol	+	+	+	+
16.93	303.0501	[M + H]⁺	C₁₅H₁₀O₇	Quercetol	+	+	+	+
17.24	374.1592	[M + H]⁺	C₂₀H₂₃NO₆	Hibiscusamide	–	–	–	+
17.80	455.3525	[M + H]⁺	C₃₀H₄₆O₃	3-Oxooleanolic acid	–	–	+	–
18.68	433.1132	[M + H]⁺	C₂₁H₂₀O₁₀	Apigenin-7-O-glucoside	+	–	–	–
20.77	431.3880	[M + H]⁺	C₂₉H₅₀O₂	Tocopherol	–	–	–	+
22.89	414.2483	[M + H]⁺	C₂₁H₃₅NO₇	Glyphaeaside C	+	–	+	–
24.68	401.3774	[M + H]⁺	C₂₈H₄₈O	Campesterol	–	–	+	+
24.93	413.3781	[M + H]⁺	C₂₉H₄₈O	Stigmasterol	–	–	+	+

PEFP: polar extract of fruit powder; PEF: polar extract of fibers; NPEFP: non-polar extract of fruit powder; NPEF: non-polar extract of fibers.

High Resolution Electrospray Ionization Mass Spectrometry (HRESIMS) using Xcalibur 3.0 and allowing for M+H and M+Na adducts.

The suggested compound according to Dictionary of Natural Products (DNP 23.1, 2015 on DVD).

Figure 2.

LC-HRMS chromatogram of the non-polar extract of A. digitata fruit. Retention time was 0–32 s; extraction was performed using dichloromethane (DCM). The relative abundance of each identified constituent is represented on the Y axis.

Figure 3.

LC-HRMS chromatogram of the polar extract of A. digitata fruit. Retention time was 0–32 s; extraction was performed using methanol (MeOH). The relative abundance of each identified constituent is represented on the Y axis.

Cell proliferation

The effects of AD extracts on cancer cell proliferation were examined to assess their potential anti-cancer effects. Incubation of HCT116 (colon), MCF-7 (breast), OVCAR-3 (ovarian), and OVCAR-4 (ovarian) human cancer cell lines with increasing concentrations of each individual extract of the AD fruit powder and fiber portions indicated that an anti-proliferative activity was mainly observed with PEF, albeit only in the HCT116 and MCF-7 cell lines and only at the highest applied concentrations. The anti-proliferative effect of PEF was statistically significant compared to that of the control (100% cell proliferation) in HCT116 cells at 25, 50, 100, and 200 µg/mL (p < 0.001) (Figure 4(a)), while the anti-proliferative activity was only observed at 200 µg/mL in MCF-7 cells (p < 0.01) (Figure 4(a)). In contrast, the other three fractions had no impact on cancer cell proliferation at any concentration in any of the tested cell lines (Figure 4(b)–(d)).

Figure 4.

Dose response curves showing the effect of AD polar and non-polar extracts on cell proliferation. A significant anti-proliferative influence was only observed for the PEF on HCT-116 and MCF-7 cells, but not the ovarian cancer cell types (a). There was no significant effect of the PEFP (b), NPEF (c), and NPEFP (d).

RNA sequencing-based gene expression profiles

We compared the gene expression profiles of the control (untreated) and PEF-treated MCF-7 and HCT116 cells using RNA sequencing. Gene expression was quantified using the RNA-Sequencing by Expectation-Maximization (RSEM) software package.¹⁷ The total number of genes expressed in each sample, as retrieved from the reference library, is shown in Figure 5.

Figure 5.

The number of expressed genes in the control and treated samples of HCT-116 and MCF-7 cells. The proportion of gene expression (the percentage shown in the bar chart) was calculated by dividing the number of expressed genes in each sample by the total number of genes in the database.

Correlation analysis

To ensure comparability between the gene expression profiles of the control and corresponding drug-treated MCF-7 and HCT116 cell lines, a correlation heat map was constructed (Figure 6). The correlation coefficient between the control and PEF-treated HCT116 cells was 0.963, indicating a strong positive correlation. In MCF-7 cells, the correlation coefficient between the control and PEF-treated MCF-7 cells was 0.61, suggesting a moderate positive correlation.

Figure 6.

Correlation heat map showing the consistency of gene expression patterns between samples. The higher the Pearson coefficient value (r) on the heat map, the more similar the gene expression profiles between samples.

Clustering and differential gene expression analysis

Genes were clustered in all four samples (PEF-treated HCT116 cells, untreated (control) HCT116 cells, PEF-treated MCF-7 cells, and untreated (control) MCF-7 cells) according to their expression levels, which were estimated using the FPKM values for each gene. High FPKM values reflect high gene expression levels. Clustering of gene expression data was performed using the open source clustering software programs (cluster 3.0) (http://bonsai.hgc.jp/~mdehoon/software/cluster/), Cluster analysis and display of genome-wide expression patterns and Java Treeview (V.3) (http://jtreeview.sourceforge.net/) (Figure 7(a)). In addition, the commonly expressed genes in different samples were displayed using a Venn diagram (Figure 7(b)).

Figure 7.

Clustering and differentially expressed genes in HCT-116 and MCF-7 cells. Java Treeview (a) and Venn diagram (b) showing the commonly expressed genes in HCT-116 and MCF-7 samples. The total number of the up- and downregulated genes are shown in C.

Poisson distribution analysis¹⁸ was performed to evaluate the number of differentially expressed genes in the PEF-treated cells in comparison to their corresponding controls, which revealed the number of upregulated and downregulated genes in the treated cells. In the PEF-treated HCT116 cells, 353 genes were upregulated and 277 genes were downregulated, while in the PEF-treated MCF-7 cells, 1,921 genes were upregulated and 1240 genes were downregulated (Figure 7(c)).

The RNA sequencing database of both HCT116 and MCF-7 cells was sorted from the most to the least statistically significant and the top 200 significant genes in the database were then searched using the following keywords: “cell cycle,”“apoptosis,”“metastasis or cell migration,”“programmed cell death,” and “cell proliferation.” We investigated the expression status of genes involved in the regulation of these cancer-related cellular processes to obtain clues regarding the impact of PEF on the modulation of the expression levels of these genes. Genes were clustered into groups based on their functions, as shown in Tables 2 and 3, to determine whether PEF treatment resulted in the upregulation or downregulation of genes (fold change was calculated for each gene), along with a brief explanation of the gene functions.

Table 2.

The most significant differentially expressed genes in the PEF-treated HCT-116 cells.

Gene name	Up/down regulation	Cluster	Remarks	Log2 foldchange	Fold change(2^{log2fold change})
Casein kinase 2, alpha 3 polypeptide	Down	Cell cycle/cell proliferation	Positive regulator of cell cycle/cell proliferation and growth	−11.7	0.0003
Inhibitor of DNA binding 2, dominant negative helix-loop-helix protein	Down		Negative regulation of cell proliferation/positive regulation of cell differentiation	−1.94	0.26
MAD2 mitotic arrest deficient-like 1 (yeast)	Down		Positive regulator of cell cycle/negative regulator of apoptosis	−1.02	0.49
Threonine–tyrosine protein kinase	Down		Cell proliferation	−1.02	0.49
Insulin-like growth factor binding protein 6	Up		Inhibits angiogenesis as well as proliferation and survival	1.54	2.9
Inhibitor of DNA binding 3, dominant negative helix-loop-helix protein	Down		Negative regulation of cell proliferation/ positive regulation of cell differentiation	−1.97	0.25
BCL2-interacting killer (apoptosis-inducing)	Up	Programmed cell death/apoptosis	Induction of apoptosis/release of cytochrome C from mitochondria	1.5	2.82
FYVE, RhoGEF and PH domain containing 3	Up		Induction of apoptosis	1.83	3.5
Bcl2 modifying factor	Up		Induction of apoptosis /release of cytochrome C from mitochondria	1.09	2.12
Serum/glucocorticoid regulated kinase family, member 3	Down		Negative regulation of apoptosis	−1.2	0.43

Negative values: downregulation.

Table 3.

The most significant differentially expressed genes in the PEF-treated MCF-7 cells.

Gene name	Up/downregulation	Cluster	Remarks	Log2 foldchange	Fold Change(2^^{log2 fold change} )
Cyclin-dependent kinase inhibitor 1A (p21, Cip1)	Up	Cell cycle/cellproliferation	Cell cycle arrest	2.3	4.9
Dihydrofolate reductase	Down		Required for DNA synthesis/cell proliferation	−1.6	0.33
High mobility group box 1	Down		Positive regulation of mitotic cell cycle and proliferation	−1.63	0.32
Heat shock protein 90 kDa alpha (cytosolic), class A member 1	Down		Required for cell cycle process	−1.3	0.4
Ferritin, heavy polypeptide 1	Up		Control of cell proliferation	1.01	2
High mobility group box 2	Down		Positive regulation of mitotic cell cycle and proliferation	−2.07	0.28
RAD21 homolog (S. pombe)	Down	Programmed celldeath/apoptosis	Inhibits programmed cell death/required for mitosis	−1.3	0.4
CSE1 chromosome segregation 1-like (yeast)	Down		Inhibits programmed cell death	−1.2	0.43
Myeloid/lymphoid or mixed-lineage leukemia (trithorax homolog, Drosophila)	Up		Induces programmed cell death	1.27	2.4
TPX2, microtubule-associated, homolog (X. laevis)	Down		Induces Programmed cell death	−1.46	0.36

Negative values: downregulation.

Discussion

The results of the current study present a constellation of findings regarding the anti-proliferative effects of the AD extract on the cell line models of breast (MCF-7), colon (HCT116), and ovarian (OVCAR-3 and OVCAR-4) cancers. In addition, it was found that the active extract concentrate exerted a remarkable effect on the transcriptome of the breast and colon cancer cells. The anti-proliferative effects reported here were observed solely with PEF, which was different from the other residues in having one unique ingredient (kaempferol-3-O-p-coumaroyl-β-D-glucopyranoside), albeit at a relatively low abundance, as revealed by LC-HRMS analysis (Table 1). Although the outer portion (fibers) contained other ingredients that were common in both the polar and non-polar extracts, the anti-proliferative effect was only observed for the PEF fraction. Notably, the anti-proliferative potential of PEF was only observed in the HCT116 and MCF-7 cells (Figure 4(a)); this fraction did not affect the proliferation of the two ovarian cancer cell lines. Furthermore, the other three fractions did not show measurable potential to reduce the cancer cell proliferation of any of the tested cell lines (Figure 4(b)–(d)).

To understand the mechanisms underlying the anti-proliferative effects of PEF, we investigated the effect of the extract on the gene expression profiles of HCT116 and MCF-7 cells using RNA sequencing technology. The results revealed a large number of differentially expressed genes in the HCT116 and MCF-7 cells treated with PEF compared to the corresponding control cells. The top 200 most statistically significant differentially expressed genes were then screened using the following keywords: “cell cycle,”“apoptosis,”“metastasis or cell migration,”“programmed cell death,” and “cell proliferation” to identify the genes that are involved in the regulation of these cancer-related biological processes (Tables 2 and 3). Moreover, this tactic allowed the identification of novel genes that were regulated by PEF. Evaluation of the potential functions of these genes in HCT116 and MCF-7 cells may provide a comprehensive view of the AD PEF-regulated genes, which may be validated as therapeutic targets to develop novel agents for the treatment of colon cancer and breast cancer in the future.

Casein kinase 2 was originally identified as an enzyme consisting of two closely related catalytic polypeptides, alpha 1 and alpha 2, which are both functional in the presence or absence of a regulatory subunit, casein kinase 2 beta (CSNK2B).¹⁹ To the best of our knowledge, casein kinase 2 alpha 3 (CSNK2A3), which was significantly downregulated in HCT116 cells by PEF, constitutes a novel isoform that has not been previously reported in human cancers. The casein kinase 2 (CSNK2) gene has been shown to positively regulate the progression of cell cycle, inhibit apoptosis, and play a role in numerous putative functions associated with both transcription and translation processes, suggesting that the gene is directly involved in cell proliferation and growth, which implies its potential tumorigenic role. The anti-apoptotic role of CSNK2 could be attributed to its recognition motif being similar to that of caspases. It has also been reported that overexpression of the CSNK2 enzyme in cancer cells can promote carcinogenesis by supporting cell survival.¹⁹ It was also recently reported that CSNK2 is a promising candidate for CSNK2 inhibitor clinical trials for validation as a therapeutic target in ovarian cancer.²⁰ It is also involved in the metastatic mechanisms of colon cancer through its role in the stabilization of endothelin-1 converting enzyme, which is required for the synthesis of endothelin-1, a pro-metastatic factor.²¹

Mitotic arrest deficient 2 (Mad2) is a spindle checkpoint protein and a positive cell cycle regulator that exhibits pro-survival potential by facilitating mitotic exit through the initiation of anaphase, consequently promoting cell proliferation and potentially cell viability.²² In the present study, we found that PEF could downregulate Mad2 in HCT116 cells. This aligns with the previously reported findings that the deleterious effects of withaferin A in colorectal cancer cells were mediated by the degradation of the Mad2-cell division cycle 20 (Cdc20) complex.²² In this context, there is significant overexpression of Mad2 in the colon cancer tissues relative to that in the normal mucosal tissues, with a ratio higher than 2 in patients with metastasis to lymph nodes.²³ In addition, it was recently suggested that Mad2 may play important roles in the early stages as well as the initiation of gastric cancer.²⁴

The TTK gene was also downregulated by PEF, which reinforces the anti-proliferative potential of the AD extract, as TTK is a carcinogenic enzyme required for cell proliferation and has been reported as a pro-survival biomarker in triple-negative breast cancer cells.²⁵ Moreover, TTK levels were found to be elevated in the malignant hepatic tissues compared to normal tissues in a cohort of patients with liver cancer.²⁶ The tumorigenic role of TTK has also been reported in pancreatic cancer, where it acts as a promoter of cell proliferation and cell transformation. The authors reported that the knockdown of this enzyme successfully reduced cell proliferation and increased apoptosis.²⁷ TTK mutations that enhance its mRNA stability have been reported to occur at a high frequency in microsatellite-unstable colorectal cancer.²⁸ Therefore, the ability of PEF to downregulate this enzyme in the HCT116 colon cancer cells indicates another strategy by which this extract could combat colon cancer.

The insulin-like growth factor-binding protein 6 (IGFBP6) gene was upregulated in the HCT116 cells treated with PEF. The upregulation of IGFBP6 in the clinical samples of nasopharyngeal carcinoma was associated with a better prognosis and higher overall survival rates. There is experimental evidence supporting this in vitro and in vivo animal models, which suggests that IGFBP6 could reduce the cancer cell growth potential and inhibit metastasis.²⁹ Consistent with our findings, it was recently reported that treating HCT116 and SW480 colon cancer cell lines with high doses of IGFBP6 significantly inhibited cell proliferation, induced G₀/G₁ cell cycle arrest, and attenuated the metastatic potential of cells.³⁰ Notably, the tumorigenic influence of insulin-like growth factor II (IGF-II) has been reported in colorectal cancer cells that overexpress the growth factor as a result of epigenetic modulation and increased gene copy number.³¹ Therefore, regulating the activity of the insulin-like growth factor-binding proteins (IGFBPs), particularly IGFBP6, may be beneficial for cancer patients, thereby reinforcing our findings.

FYVE, RhoGEF, and PH domain-containing 3 (FGD3) is a guanine exchange factor with a reported prognostic value in breast cancer. High expression of FGD3 inhibits cell migration and is associated with better clinical outcomes in different cohorts of patients with breast cancer.³² This finding was also supported by another study,³³ which highlighted the gene as a prognostic marker for the overall survival rate of patients. Functionally, FGD3 plays a role in the regulation of apoptotic signaling cascades. It is also suggested to be one of the genes contributing to the mutation signature of lung adenocarcinoma.³⁴ To the best of our knowledge, the role of FGD3 in colon cancer has not previously been reported. The upregulation of the FGD3 gene by PEF in HCT116 cells compared to the corresponding control suggests that this gene might be downregulated in colon cancer and highlights it as a novel prognostic and diagnostic biomarker for the disease.

There is controversy regarding the role of the inhibitor of DNA binding 3 (ID3) gene as it is reported to exhibit both pro- and anti-cancer effects. ID3 upregulation induces apoptosis and consequently reduces the proliferation of human lung cancer cell lines.³⁵ These findings support the tumor-suppressing potential of ID3. ID3, together with the inhibitor of DNA binding 1 (ID1), contributes to the self-renewal of colon cancer cells due to its role in the regulation of cell cycle progression via modulation of the activity of p21. This finding suggests that both ID1 and ID3 are involved in the recurrence of colon cancer after remission. They have also been implicated in chemoresistance, which further highlights their oncogenic functions.³⁶ Therefore, the role of this gene may be cancer-specific. The downregulation of ID3 in colon cancer might serve as an anti-tumor intervention strategy. This concords with the results of our study, in which there was PEF-mediated downregulation of ID3 in the HCT116 colon cancer cells; however, this requires further investigation in future studies.

Recently, Guo et al.³⁷ proposed that the oncogenic role of inositol polyphosphate 4-phosphatase type II (INPP4B) in human colon cancer might, at least in part, be mediated by the serum- and glucocorticoid-inducible kinase 3 (SGK3) as the silencing of INPP4B completely inhibits SGK3 activation and derails the growth of colon cancer xenografts. Moreover, SGK3 functions in concert with protein kinase B (Akt) downstream to the pro-survival signaling cascade of the phosphoinositide 3-kinase (PI3K) pathway to promote hepatocellular carcinoma development.³⁸ It has also been reported that overexpression of the CSNK2 enzyme can promote carcinogenesis in specific cell lines.³⁸ Another carcinogenic effect for SGK3 is observed in breast cancer, wherein it is responsible for the acquired resistance to aromatase inhibitors as well as mediation of the signaling of the estrogen receptor alpha.³⁹ Therefore, the ability of PEF to downregulate this gene in HCT116 cells provides additional evidence supporting its anti-tumor potential.

PEF also resulted in the upregulation of two B cell lymphoma-2 (BCL-2) family-related genes, BCL-2 interacting killer (BIK) and BCL-2 modifying factor (BMF), both of which function as positive regulators of apoptosis. Both BCL-2 family members induce apoptosis by directly interacting with the pro-survival BCL-2 family members and promoting the release of cytochrome C to initiate intrinsic apoptotic signaling.⁴⁰ As the BCL-2 family proteins have been well covered in the literature, they are not further discussed here.

PEF treatment also resulted in the downregulation of p21 in MCF-7 cells compared to the corresponding control cells. p21 is a renowned cell cycle regulator that induces cell cycle arrest. The upregulation of p21 induces cell cycle arrest in colon cancer cells.⁴¹ It is also associated with the anti-tumor effects of the acetyltransferase p300/CBP-associated factor (PCAF) in HCT116 colon cancer cells.⁴² Additional in vitro evidence regarding the anti-tumor effects of p21 in MCF-7 cells was provided in a recent study,⁴³ which highlighted the increased level of p21 downstream to AMPK activation resulting in the induction of cell cycle arrest and augmentation of the apoptotic process. Such finding suggests that PEF exerts a hallmark anti-cancer effect by upregulating p21, a well-established target for the treatment and suppression of cancer.

The enzyme dihydrofolate reductase (DHFR) converts dihydrofolate to tetrahydrofolate, which is required for DNA synthesis, and consequently promotes cell cycle progression and cell proliferation. Overexpression of dihydrofolate reductase has been reported in many human cancers and it acts as the target of the anti-cancer drug methotrexate; however, the influence of this drug can be overcome via the increased expression of DHFR in cancer cells.⁴⁴ A DHFR 19-base pair deletion polymorphism is associated with an elevated risk of breast cancer in women under multivitamin supplementation.⁴⁵ Additionally, overexpression of DHFR in the Chinese hamster ovary (CHO) cells has been reported to be involved in cell transformation and faster proliferation of cancer cells. Similarly, a single nucleotide polymorphism in the microRNA binding site of the DHFR gene abolished the capacity of microRNA to bind to DHFR and regulate its expression, leading to DHFR overexpression and transformation of the rat kidney cells (RK3) cells and murine fibroblast cells (NIH3T3) both in vivo and in vitro.⁴⁶ In this respect, the ability of PEF to downregulate this gene in MCF-7 cells confirms its anti-tumor potential in a breast cancer cell line model.

High mobility group box 1 (HMGB1) constitutes a non-histone chromatin modulating protein that is expressed in almost all tissues except neurons.⁴⁷ PEF downregulated HMGB1 in MCF-7 cells, an effect that counteracts the oncogenic properties of this protein. In concordance with our findings, it has been reported that silencing the expression of HMGB1 in MCF-7 cells induced apoptosis and abolished the invasion and migration capacities of the cells, which led to the loss of their metastatic potential.⁴⁸ Conversely, the overproduction of HMGB1 is observed in MCF-7 cells that are exposed to the chemotherapeutic agent, irinotecan. In addition, the release of HMGB1 from its nuclear location makes it functions as an extracellular indicator during carcinogenesis.⁴⁹ Furthermore, the oncogenic effects of HMGB1 are reported in colorectal cancer, in which its increased expression was associated with the metastasis of cancer cells to the lymphatic system along with an overall poor prognosis. These oncogenic effects are mediated by the activation of the protein kinase R (PKR)-like endoplasmic reticulum kinase (pERK) and cellular-inhibitor of apoptosis 2 (c-IAP2).⁵⁰ Hence, the modes of action of HMGB1 in human cancers may vary according to the cellular conditions, with it functioning either as a tumor suppressor gene or an oncogene.

As its function is similar to that of HMGB1, high mobility group box 2 (HMGB2) has been proposed to be involved in the malignancy of human cancers. High expression of HMGB2 in the in vitro and in vivo models of breast cancer is positively associated with a large tumor mass and advanced stage of cancer. The ability of HMGB2 to reprogram cancer cell metabolism to favor anaerobic metabolism (the Warburg effect) is suggested to be a pivotal mechanism that drives this correlation, thereby placing HMGB2 as another prognostic biomarker in breast cancer.⁵¹ Moreover, the loss of HMGB2 function in the colorectal cancer cell lines, HCT116 and HT-29, can sensitize these cells to radiotherapy. Furthermore, p53 can downregulate the HMGB2 gene expression, which prevents the cancer cells from obtaining the benefits of the involvement of HMGB2 for the repair of their damaged DNA.⁵² The effect of PEF on HMGB2 was similar to that reported above for HMGB1.

Heat shock protein 90 alpha family class A member 1 (HSP90AA1), an inducible molecular chaperone that belongs to the heat shock protein 90 (HSP90) family⁵³ and represents one of the cytoplasmic isoforms of HSP90, is correlated with the progression, poor prognosis, and cancer-related deaths in breast cancer.⁵⁴ High expression of HSP90AA1 and other HSP90 isoforms is also associated with an augmented risk of metastasis and disease relapse in different subtypes of breast cancer.⁵⁴ Moreover, the stabilization of HSP90AA1 downstream to the proto-oncogene, MYC, is involved in the progression of hepatocellular carcinoma, which confirms its oncogenic activity.⁵⁵ Perotti et al. (reviewed in).⁵³have reported the induction of HSP90AA1 in breast cancer by prolactin via the signal transducer and activator of transcription 5 (STAT5) signaling cascade. A similar oncogenic influence of HSP90AA1 is observed in osteosarcoma, indicating its involvement in autophagy and the drug resistance of cancer cells.⁵⁶ Together, these observations suggest that the downregulation of HSP90AA1 by PEF represents a promising anti-tumor effect in breast cancer, which may also occur in other human malignancies.

The anti-tumor role of ferritin heavy chain 1 (FTH1), a subunit of the well-studied iron metabolism protein, ferritin, has been proposed in previous studies; however, it has not been well understood. The anti-tumor potential of FTH1 was investigated in patients with triple-negative breast cancer and was found to be associated with immunoregulatory mechanisms and cluster of differentiation 8 (CD8)⁺-mediated cell death.⁵⁷ It has also been reported that MCF-7, along with other epithelial breast cancer cell lines, expresses low levels of FTH1. As reviewed by Chekhun et al.,⁵⁸ variable expression of FTH1 is observed in the more aggressive MDA-MB-231 breast cancer cell line due to the low levels of microRNA-200b (mir-200b), which is responsible for the regulation of the ferritin heavy chain (FTH) in this cell line. Moreover, FTH1 is downregulated in MCF-7 cells with acquired resistance to doxorubicin but is upregulated in the cisplatin-resistant MCF-7 cells.⁵⁸ PEF upregulates FTH1 in MCF-7 cells compared to the corresponding control cells. Therefore, the role of FTH1 in breast cancer may be cell line-dependent and further research is needed to ascertain its exact contribution to the malignancy of breast cancer as well as other human cancers.

RAD21 plays important roles in the DNA repair and chromosome segregation processes during cell division. Increased expression of RAD21 has been reported in multiple human malignant conditions, including breast and colorectal cancers. Overexpression of RAD21 is associated with the amplification of the gene copy number and correlated with poor prognosis and chemoresistance in different subclasses of breast cancer.⁵⁹ Josephine et al. (reviewed in).⁶⁰ have reported that the predisposition to breast cancer may increase as a result of a RAD21 single nucleotide polymorphism and silencing the expression of RAD21 in MCF-7 cells helps to overcome the chemoresistance to etopside and bleomycin. Therefore, downregulation of RAD21 in human cancer is considered as a promising anti-tumor approach, which is consistent with the results of our study involving PEF treatment.

The chromosome segregation 1 like (CSE1L) gene, also known as cellular apoptosis susceptibility (CAS), has been reported to function as an oncogene with elevated expression in human cancers. CSE1L is considered to be an important contributor to cancer metastasis and cell migration, which might serve as a tool for the screening, diagnosis, and monitoring of the response to chemotherapy in cancer, particularly in metastatic tumors.⁶¹ Similarly, CSE1L is also involved in tumor metastasis downstream of the Ras-extracellular signal-regulated kinase (Ras-ERK) signaling pathway.⁶² CSE1L also induces the formation of microvesicles in the MCF-7 breast cancer cell line and HT-29 colorectal cancer cell line.⁶² Therefore, the ability of PEF to downregulate CSE1L in MCF-7 cells confirmed its anti-tumorigenic effect.

Being involved in the formation of spindle fibers, the targeting protein for Xklp2 (TPX2) is classified as a crucial mitotic modulator that plays an essential role in chromosome segregation and cell multiplication. Consistently, TPX2 overexpression is associated with aneuploidy and chromosomal instability in human cancers.⁶³ Moreover, the roles of TPX2 in metastasis and poor prognosis have been proposed in numerous human cancers, including breast cancer.⁶⁴ The upregulation of TPX2 contributes to carcinogenesis and promotes the cell migration and invasiveness in the MCF-7 cell line along with other breast cancer cell lines.⁶⁵ Our results have shown that PEF downregulated the expression TPX2 in MCF-7 cells, thereby providing another strategy for tackling the carcinogenesis of breast cancer.

Conclusion

Overall, the current study provides evidence supporting the potent anti-proliferative potential of the PEF fraction of AD in two human cancer cell lines, MCF-7 (breast cancer) and HCT116 (colon cancer). This was indicated primarily by the anti-proliferative effect of PEF (Figure 4) and was later confirmed by its ability to regulate the expression of numerous genes as revealed by RNA sequencing analysis. Our results further revealed that CSNK2A3 is a novel isoform of CSNK2 in colon cancer, which requires further investigations in patients with colon cancer to estimate its clinical value. Moreover, we highlighted FGD3 as another novel biomarker in colon cancer, whose role, to the best of our knowledge, has never been reported in this disease. Finally, we concluded that the ability of AD PEF to regulate a variety of genes, either in the MCF-7 or HCT116 cell lines, demonstrates the potential of this natural product to act as a potent and pleiotropic anti-cancer agent, which could be used in developing synergistic and additive anti-tumor strategies. However, it should be noted that its action is cancer-specific. Nevertheless, our findings will aid other researchers in further investigating the anti-tumor effects of this AD extract in various types of human cancers and potentially lead to the development of an effective anti-cancer drug in the future.

Supplemental Material

sj-pdf-1-sci-10.1177_00368504211032084 – Supplemental material for RNA sequencing identified novel target genes for Adansonia digitata in breast and colon cancer cells

Supplemental material, sj-pdf-1-sci-10.1177_00368504211032084 for RNA sequencing identified novel target genes for Adansonia digitata in breast and colon cancer cells by Omar S. El-Masry, Arafat Goja, Mostafa Rateb, Amani Y Owaidah and Khaldoon Alsamman in Science Progress

Footnotes

Acknowledgements

We would like to thank the Deanship of Scientific Research, Imam Abdulrahman Bin Faisal University, Saudi Arabia, for their continuous support.

Author contributions

OSE: generated the study design and rationale, performed the cell proliferation assessment, and drafted the manuscript. AG: Provided the fruits and extracts and approved the final draft. MR: Performed liquid chromatography-high-resolution mass spectrometry analysis and approved the final draft. AYO: Contributed to experimental design and critically reviewed the manuscript. KA: Contributed to the experimental design, analyzed the RNA sequencing data, and approved the final draft.

ORCID iD

Omar S. El-Masry

Data availability

All relevant data generated in this study are included in the manuscript.

Supplemental material

Supplemental material for this article is available online.

Author biographies

Omar S. El-Masry obtained his master degree in 2006 from the Medical Research institute, University of Alexandria and his PhDin 2012 from themedical school, faculty of medicine dentistry & health, University of Sheffield, UK. Dr. El-Masry has joined college of applied medical sciences in 2014 as an assistant professor of clinical chemistry, department of Clinical Laboratory Sciences, Imam Abdulrahman Bin Faisal University. Dr. El-Masry research focus is cancer biology and therapeutic targeting of neoplastic diseases.

Arafat Goja is an associate professor at the department of clinical nutrition, Imam Abdulrahaman Bin Faisal University. Dr. Goja has MSC and PhD from the University of Khartoum and completed his post-doctoral Studies at Tshwane University of Technology in 2010 and Huazhong Agricultural University, Chinafrom 2012-2013. Dr. Goja has many publications on the beneficial uses of naturally occurring substances and their medicinal uses.

Mostafa Rateb received his PhD in natural product chemistry at University of Aberdeen 2011, worked as postdoctoral Research Fellow at The Scripps Research Institute from 2011-2013, then Senior Research Fellow at University of Aberdeen from 2013-2015 and joined the University of the West of Scotland as an assistant professor in 2015. Dr.Rateb has obtained University of Aberdeen Certificate of Excellence Award for Research & Engagement in 2019 and University of the West of Scotland Star Award for Research and Enterprise in 2020.

Amani Y Owaidah has BSC in medical laboratory sciences and received her PhD in 2014 in cellular and molecular medicine from the University of Bristol, UK. Dr. Owaidah research focus is stem cell biology and cartilage tissue engineering. Dr. Owaidah has joined King Fahd Specialist Hospital as a research scientist from 2015-2016 and currently is an assistant professor at the department of clinical laboratory sciences,college of applied medical sciences, Imam Abdulrahman bin Faisal University and the Vice-Dean of Studies, Development and Community Service.

Khaldoon Alsamman obtained his BSC and master degrees from University of Abertay Dundee, Scotland. Dr. Alsamman has obtained his PhD in molecular genetics from the University of Edinburgh, Scotland, UK in 2012. Dr. Alsamman is currently an associate professor at the department of clinical laboratory sciences and vice-dean of academic affairs, college of applied medical sciences, Imam Abdulrahman bin Faisal University. Dr. Alsamman research interest is molecular biology of cancer.

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