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Article

Vitamin D Receptor and CYP450 Enzyme Dysregulation May Mediate Oral Cancer Responsiveness

by
Dustin Hunsaker
1,
James Landon Moore
2,
Katherine M. Howard
3 and
Karl Kingsley
3,*
1
Department of Advanced Education in Orthodontic Dentistry, School of Dental Medicine, University of Nevada-Las Vegas, 1700 West Charleston Blvd, Las Vegas, NV 89106, USA
2
Department of Clinical Sciences, School of Dental Medicine, University of Nevada-Las Vegas, 1700 West Charleston Blvd, Las Vegas, NV 89106, USA
3
Department of Biomedical Sciences, School of Dental Medicine, University of Nevada-Las Vegas, 1001 Shadow Lane, Las Vegas, NV 89106, USA
*
Author to whom correspondence should be addressed.
Targets 2025, 3(1), 6; https://doi.org/10.3390/targets3010006
Submission received: 27 December 2024 / Revised: 29 January 2025 / Accepted: 6 February 2025 / Published: 8 February 2025
(This article belongs to the Special Issue Multidisciplinary Approach to Oral Cavity Cancer: An Hard Enemy)
Browse Figures
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Abstract

:
Many health benefits are associated with Vitamin D (VitD), although deficiency is associated with poor health outcomes and the increased risk of cancer development. For example, many tissue-specific enzymes are involved in VitD metabolism, and mutations or deletions within Vitamin D receptor (VDR) genes are known to increase the cancer risk by altering their functions or bioavailability, although less is known about these phenomena in oral cancers. Using well-characterized, commercially available oral cell lines (OKF4, HGF-1, SCC4, SCC9, SCC15, SCC25, and CAL27), the mRNA expression of P450 cytochrome VitD metabolic enzymes and receptor genes by qPCR revealed differential results. One oral cancer line (SCC15) did not express either the Vitamin D receptor (VDR) or FOK1 polymorphism and was also least affected by VitD3 administration in growth assays. In contrast, most oral cancers were missing one or more hydrolase (CYP2R1 and CYP24A1) or hydrolate (CYP27A1 and CYP27B1) enzymes. SCC25 was missing both the hydrolate enzymes and was the most inhibited in the VitD3 growth assays, while SCC4 was missing both the hydroxylase enzymes and was the least inhibited by VitD2. These associations between mRNA expression (or lack thereof) and VitD3 and VitD2 responsiveness can be used to identify molecular targets, which may lead to effective screening tools for VitD-related, complementary and alternative therapies.

1. Introduction

Many health benefits are associated with Vitamin D (VitD) intake and supplementation [1,2]. For example, research has demonstrated that VitD plays a pivotal role in early development, with significant roles in maintaining the blood levels of calcium and phosphorus, as well as the development, growth, and maintenance of skeletal bones [3,4,5]. In addition, VitD has been shown to influence immunologic activity in both the innate and adaptive immune systems, with VitD sufficiency strongly associated with significant improvements in overall health and systemic function [6,7]. Moreover, adequate VitD levels have also been associated with a decrease in morbidity, as well as overall mortality rates [8,9,10].
However, research has also demonstrated that VitD3 deficiency may be strongly associated with poor health outcomes and the increased risk of the development of systemic diseases [11,12,13]. VitD3 deficiency has been associated more specifically with various negative health conditions, including diabetes and metabolic disease, infectious diseases, and cardiovascular disease through multiple inter-related pathways [14,15,16,17,18,19,20]. Additionally, VitD3 was found to have a strong inverse relationship with cancer development [21,22,23].
More specifically, VitD3 deficiency has been traditionally associated with skin cancers, although more recent systematic reviews have demonstrated further correlations with gastrointestinal, colorectal, pancreatic, and liver cancers that may be manifested in various metabolic and signaling pathways [24,25,26,27,28]. In addition, more evidence has linked VitD3 deficiency to the increased risk of breast and ovarian cancers through similar mechanisms [29,30,31]. Finally, this research has also demonstrated strong links with VitD3 deficiency and the development and progression of many types of oral and head and neck cancers, although less is known about the pathways and mechanisms responsible for these observations [32,33].
The mechanisms responsible for these links between VitD3 and cancer development may include Vitamin D receptors (VDR) or the VDR single-nucleotide polymorphism (SNP) identified as Flavobacterium okeanokoites endonuclease-1 (FOK1), which may exhibit polymorphisms, deletions, and mutations that are known to increase the cancer risk by altering their functions or bioavailable concentrations within the host [34,35,36]. Furthermore, many tissue-specific enzymes that are involved in VitD3 metabolism, including several CYP450 enzymes, such as CYP27A1, CYP2R1, CYP24A1, and CYP24SV, may also be subject to downregulation, mutations, deletion, as well as other types of dysregulation that similarly increase the risk of cancer development or progression [37,38,39]. These findings suggest that a more complete understanding of VDR gene dysfunction and VitD metabolism dysregulation may provide significant insights into whether a given patient may benefit from complementary or alternative treatments [40,41].
Despite the complexity and depth of research regarding VitD3 and cancer prevention or VitD3 deficiency and cancer risk, most of this research has involved the most common cancers, such as skin, breast, colorectal, and liver cancers [21,22,23]. Fewer studies have focused on these mechanisms and pathways, specifically regarding oral squamous cell carcinomas and other oral tumors [32,33]. An initial study from this group found differential effects of VitD3 supplementation on commercially available oral cancer cell lines, without the determination of the underlying mechanisms or pathways that might be responsible for these differing effects [42]. Based upon this lack of evidence, the main objective of this study was to determine if the mutations or deletions in the receptors and enzymes involved in VitD3 intake and metabolism were present and functional within well-characterized, commercially available oral cancer cell lines to determine the potential screening targets for VitD responsiveness.

2. Materials and Methods

2.1. Experimental Cell Lines

Each of the commercially available cell lines used in this study was obtained from the American Type Tissue Culture Collection or ATCC (Manassas, VA, USA). The cell lines included oral squamous cell carcinomas CAL 27 (CRL-2095), SCC-15 (CRL-1623), SCC-25 (CRL-1628), SCC-4 (CRL1624), and SCC-9 (CRL-1629) and the normal human oral gingival fibroblast line HGF-1 (CRL-2014). An additional normal oral cell line of oral keratinocytes (OKF4) was obtained from Lifeline Cell Technologies (Carlsbad, CA, USA). Cells were thawed and cultured according to the manufacturer’s recommendations, which included Dulbecco’s Modified Eagle’s Medium (DMEM) for CAL 27, OKF4, and HGF-1 cells and DMEM:F12 for SCC-15, SCC-25, SCC-4, and SCC-9 cells with the addition of 10% fetal bovine serum (FBS) and 1% Penicillin–Streptomycin antibiotic. DMEM, DMEM:F12, FBS, and the antibiotic were obtained from ThermoFisher Scientific (Fair Lawn, NJ, USA). The cell cultures were maintained in a biosafety level two (BSL-2) cabinet supplemented with 5% medical-grade carbon dioxide (CO2) as previously described [43,44].

2.2. Cell Line Verification

The verification of each cell line was performed using two protocols (Table 1). First, the International Cell Line Authentication Committee (ICLAC) database was searched to ensure none of the cell lines were among those currently known to be misidentified or cross-contaminated. Second, detailed evaluation of each cell line was provided by the manufacturer using short tandem repeat (STR) analysis and 18 loci from the ATCC database for cell line identification and validation.

2.3. Growth Assays

Vitamin D3 (CAS 67-97-0 or cholecalciferol, MW 384.648) and Vitamin D2 (CAS 11-101-9121 or ergocalciferol, MW 396.55) were obtained from Thermo Scientific Chemicals (Fair Lawn, NJ, USA). Growth assays were performed in designated media with and without the addition of VitD2 or VitD3 at 10, 20, 50, and 100 nmol, which is a concentration range that has been demonstrated to encompass physiological and bioavailable concentrations, as previously described [42,45]. These concentrations further enabled comparisons with other studies of these oral squamous cell carcinomas, which were found to use comparable dosages of 1 nmol, 10 nmol, and 100 nmol or 2.5 ng/mL, 25 ng/mL, and 250 ng/mL [46,47]. Growth assays were completed using Costar 96-well, tissue culture-treated assay plates from Corning (Corning, NY, USA) at standardized concentrations of 1.0 × 105 cells per mL and measured following three fixed time points of 24 h (1 day), 48 h (2 days), and 72 h (3 days). The changes in growth (outcome) induced by the addition of the independent variables (VitD2 and VitD3) were measured against baseline growth (cells plated in standard media without the addition of VitD or 0 nmol). The cells were fixed with 10% buffered formalin and stained using Gentian Violet 1% aqueous solution from Fisher Scientific (Fair Lawn, NJ, USA) as previously described [42,43,44]. Relative absorbance values were determined using an ELx808 microplate reader from BioTek (Winooski, VT, USA) at 630 nm. The data from three separate, independent replications of each experiment were then compiled, analyzed, and summarized using Microsoft Excel (Redmond, WA, USA).

2.4. RNA Isolation

Nucleic acid isolation was performed using the phenol–chloroform extraction method from all three separate, independent replications of each experiment. In brief, cell suspension (500 uL) was mixed with TRIzol reagent (500 uL) and chloroform (200 uL) from Invitrogen (Waltham, MA, USA). Following incubation on ice, the mixture was centrifuged at 10,000× gravity force (g) in a refrigerated microcentrifuge tube from Eppendorf 5425-R (Hamburg, Germany) for 15 min at 4 °C. The upper aqueous layer (300 uL) was removed and placed into a sterile microcentrifuge tube with an equal volume of isopropanol (300 uL) to precipitate nucleic acids and centrifuged for 10 min at 4 °C. Isopropanol was aspirated, and the pellet was washed with ethanol and centrifuged for an additional five minutes at 4 °C. Ethanol was removed, and the pellet was resuspended in nuclease-free water and stored at −80 °C. Genomic DNA was removed using DNAse I from Thermo Fisher Scientific (Fair Lawn, NJ, USA) according to the manufacturer’s protocol. Briefly, RNA was added to a sterile centrifuge tube with 10× Reaction Buffer (with MgCl2), DNase I (RNase-free), and diethyl pyrocarbonate (DEPC)-treated water and incubated at 37 °C for 30 min. Qualitative analysis was performed using a NanoDrop 2000 spectrophotometer from ThermoFisher Scientific (Fair Lawn, NJ, USA) with absorbances at A260 and A280 nm as previously described [43,44]. An A260 absorbance reading of 1.0 is equivalent to ~40 µg/mL single-stranded RNA, and all the samples were determined to have RNA yields greater than 10 µg/mL. An A260/A280 ratio from 1.8 to 2.1 is indicative of highly purified RNA, and all the samples were found to exhibit A260/A280 ratios between 1.81 and 2.01, which is acceptable for cDNA conversion and qPCR screening protocols.

2.5. cDNA Synthesis

Total RNA was used to create cDNA using the Verso One-Step Reverse Transcription Polymerase Chain Reaction (RT-PCR) kit from ThermoFisher Scientific (Fair Lawn, NJ, USA) using the manufacturer’s recommended protocol. Briefly, 25 uL of 2X ReddyMix, 20 uL of nuclease-free water, 2.0 uL of sample, and 1.0 each of forward and reverse Universal Primers for the amplification of human mRNA to cDNA were mixed and processed in a gradient thermocycler from Eppendorf (Hamburg, Germany). This was completed using the recommended protocol for one cycle of 30 min at 47 °C to reverse transcribe, one cycle of five minutes at 72 °C for the final extension, and one cycle of two minutes at 95 °C for inactivation. The analysis of final products was completed using the NanoDrop 2000 spectrophotometer from ThermoFisher Scientific (Fair Lawn, NJ, USA) with absorbances of A260 and A280 nm as previously described [43,44].

2.6. qPCR Screening

The samples were screened using the SYBR Green qPCR Master Mix from ThermoFisher Scientific (Fair Lawn, NJ, USA) and the QuantStudio Real-Time Polymerase Chain Reaction (PCR) system from Applied Biosciences (Waltham, MA, USA). In brief, each cDNA or DNA sample reaction contained a total volume of 25 uL that consisted of 2X SYBR Green Fast Master Mix (12.5 uL), nuclease-free water (7.5 uL), forward and reverse primers (1.75 uL), and screening sample (2.0 uL) diluted to 100 ng/uL. Each reaction was screened using the manufacturer’s recommended protocol, which involved enzyme activation at 95 °C for 15 min, followed by 40 cycles of denaturation at 95 °C for 15 s and annealing at primer-specific temperature for 30 s, and a final extension at 72 °C for 30 s. The QuantStudio system from Applied Biosciences (Waltham, MA, USA) was used to determine the cycle threshold (CT) utilizing the delta-delta Ct method as previously described [43,44]. Relative quantification (RQ) was then determined by normalizing the CT expression results with the internal positive control glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as previously described [43,44]. Each qPCR screening reaction was performed in triplicate (n = 3) from each of the three independent experimental trials (total n = 9) and averaged prior to normalization with the internal positive control. The primer pairs and melting temperatures (Tm) included the following:
  • Positive controls
  • GAPDH primers (metabolic control)
  • GAPDH forward: 5′-ATCTTCCAGGAGCGAGATCC-3′; Tm: 66 °C
  • GAPDH reverse: 5′-ACCACTGACACGTTGGCAGT-3′; Tm: 70 °C
  • VitD Receptor primers
  • VDR (Vitamin D receptor)
  • VDR forward: 5′-CCAAACACTTCGAGCACAAGG-3′; Tm: 67 °C
  • VDR reverse: 5′-AGAGCAGAGTTCCAAGCAGAGG-3′; Tm: 69 °C
  • FOK1 primers
  • FOK1 forward: 5′-CCAGCTATGTAGGGCGAATC-3′; Tm: 69 °C
  • FOK1 reverse: 5′-CCTTCACAGGTCATAGCATTGA-3′; Tm: 64 °C
  • P450 metabolic enzyme primers
  • CYP2R1 (hydroxylase) primers
  • CYP2R1 forward: 5′-AGAGGGAAGAGCAATGACATG-3′; Tm: 59 °C
  • CYP2R1 reverse: 5′-TTAAGCCATCAGATTGGTGG-3′; Tm: 62 °C
  • CYP24A1 (hydroxylase) primers
  • CYP24A1 forward: 5′-GCAGCCTAGTGCAGATTT-3′; Tm: 62 °C
  • CPR24A1 reverse: 5′-ATTCACCCAGAACTGTTG-3′; Tm: 59 °C
  • CYP27A1 (hydroxylate) primers
  • CYP27A1 forward: 5′-GGAAAGTACCCAGTACGG-3′; Tm: 61 °C
  • CYP27A1 reverse: 5′-AGCAAATAGCTTCCAAGG-3′; Tm: 59 °C
  • CYP27B1 (hydroxylate) primers
  • CYP27B1 forward: 5′-GCGGACTGCTCACTGCGGAA-3′; Tm: 73 °C
  • CYP27B1 reverse: 5′-GCCGCACAAGGTCGCAGACT-3′; Tm: 74 °C

2.7. Statistical Analysis

The data generated from the cell growth assays were exported into Microsoft Excel (Redmond, WA, USA) and analyzed using two-tailed Student’s t-tests, which are appropriate for continuous parametric data analysis. The data from three independent experiments were compiled using n = 8 replicates for each cell line for each experimental condition and concentration (total n = 24 cell line/condition). Data normality was confirmed using the Shapiro–Wilk test, which is designed for parametric data analysis and verified using single-factor analysis of variance (ANOVA) using the online software package of Prism, Version 9, from GraphPad (San Diego, CA, USA) as previously described [43,44]. Significant differences were identified using an alpha level of less than p = 0.05.
The data generated from the cycle threshold (CT) counts obtained from real-time qPCR screening were averaged from the reactions performed in triplicate (n = 3) for each cell line from each of three experimental trials (total n = 9). Relative quantification (RQ) was then determined by normalizing the CT expression results with the internal positive control glyceraldehyde 3-phosphate dehydrogenase (GAPDH) from each cell line from the three experimental trails as previously described [43,44].

3. Results

3.1. Vitamin D3 Growth Assays

The cells were plated with and without the addition of VitD3 in three independent experiments (Figure 1). These data demonstrated that the normal, non-cancerous cell lines exhibited an increase in growth over three days at all the concentrations evaluated, including HGF-1 (from 10 nmol +11.7%, p = 0.047, to 100 nmol +19.3%, p = 0.042) and OKF4 (from 10 nmol +10.6%, p = 0.047, to 100 nmol +13.1%, p = 0.046) compared to that of the baseline control cells (0 nmol). However, differential results were observed with the oral cancer cell lines. More specifically, the SCC15 cell line exhibited minimal effects on growth with reductions between −0.4%, p = 0.881, at 10 nmol and −3.9%, p = 0.441, at 100 nmol compared to those of the baseline control cells (0 nmol). More moderate effects on cell growth were observed with the SCC4 (from −6.6%, p = 0.083, at 10 nmol to −12.8%, p = 0.051, at 100 nmol), SCC9 (from −7.8%, p = 0.067, at 10 nmol to −13.2%, p = 0.045, at 100 nmol), and CAL27 (from −9.9%, p = 0.046, at 10 nmol to −17.9%, p = 0.0422, at 100 nmol) cells over three days compared to those of the baseline control cells (0 nmol). However, differential inhibition was observed with the SCC25 cell line (−6.1%, p = 0.731, at 10 nmol), with more significant and robust inhibition (−31.2%, p = 0.021, at 20 nmol, −39.2%, p = 0.017, at 50 nmol, and −43.1%, p = 0.003, at 100 nmol) compared with that of the baseline controls (0 nmol).

3.2. Vitamin D Receptor Expression

To evaluate the potential for the receptor-mediated intake of VitD3 among these cell lines, the expression of the Vitamin D receptor (VDR) and the most important polymorphism (FOK1) were evaluated (Figure 2). These data demonstrated that expression of the VDR was observed within the normal, non-cancerous cell lines HGF-1 and OKF4, as well as SCC4, SCC9, and CAL27, although no expression was observed among either the SCC15 or SCC25 cells. Cycle threshold (CT) expression was normalized to the internal endogenous control (GAPDH), which revealed the expression of the VDR was relatively consistent and stable across these cell lines, ranging from 0.97 (CAL27) to 1.09 (SCC9). The expression of the FOK1 polymorphism was observed among most of the cell lines evaluated, including SCC4, SCC9, SCC25, and CAL27, as well as both HGF-1 and OKF4, but not among the SCC15 cells. The normalized expression data revealed more variable expressions of FOK1, ranging from 0.59 (CAL27) to 1.04 (SCC9).

3.3. CYP450 Enzyme Expression

To more closely assess the effects of VitD3 within each cell line, the major hydroxylase enzymes for this pathway were evaluated (Figure 3). These results revealed that CYP2R1 was expressed in all the cell lines evaluated (SCC9, SCC15, SCC25, CAL27, OKF4, and HGF-1), with the exception of SCC4. The evaluation of normalized expression to GAPDH revealed consistent results across each cell line, ranging from 0.88 (SCC15) to 0.97 (SCC25). In contrast, the expression of CYP24A1 was only found among SCC25, SCC15, and HGF-1, with no expression observed among the CAL27, SCC9, or SCC4 cells. The normalized data for the expression results ranged between 0.67 (SCC25) and 1.13 (HGF-1).
The further evaluation of the VitD3 pathways within each cell line was accomplished through the analysis of the major hydroxylate enzymes (Figure 4). This evaluation demonstrated that CYP27A1 was only expressed in the SCC4, OKF4 and HGF-1 lines, with no expression observed among SCC9, SCC15, SCC25, and CAL27. The evaluation of expression normalized to GAPDH revealed results ranging from 0.94 (HGF-1) to 1.02 (SCC4). However, the expression of CYP27B1 was expressed in all the cell lines (SCC4, SCC9, SCC15, CAL27, OKF4, and HGF-1), except the SCC25 cells. Normalized expression for CYP27B1 ranged from 0.87 (HGF-1) to 1.03 (SCC4).
The evaluation of the effects of VitD3 administration on cellular growth was cross-referenced with the expression of the key experimental variables from this study (Figure 5). These data clearly demonstrated that the normal, non-cancerous cell line HGF-1, which responded with increased growth at all the concentrations of VitD3 administration evaluated, expressed the main entry mechanisms for VitD3 (VDR and FOK1), as well as the major metabolic conversion pathways, including hydroxylase (CYP2R1 and CYP24A1) and hydroxylate (CYP27A1 and CYP27B1) enzymes. Although differential results were observed among each of the oral cancer cell lines individually, two unique expression differences were identified among the oral cancers that exhibited the least and most responsive inhibition to VitD3 administration, SCC15 and SCC25, respectively. More specifically, each of the oral cancers expressed either VDR, FOK1, or both, except for the least responsive cell line (SCC15), which did not express either of these receptor or entry-related mRNAs. In addition, each of the cell lines expressed one or both of the major hydroxylate enzymes (CYP27A1 and CYP27B1), with the exception of the most responsive cell line (SCC25), which was missing both of these major metabolic pathway enzymes. One additional finding was the expression of one or both of the major hydroxylase enzymes (CYP2R1 and CYP24A1) among each of the cell lines evaluated, with the exception of SCC4.

3.4. Vitamin D2 Growth Assays

Due to the observation that the hydroxylase enzymes (CYP2R1 and CYP24A1) responsible for the conversion of VitD2 were not expressed in the SCC4 cells, growth and viability assays were performed with and without the addition of VitD2 in three additional independent experiments (Figure 6). These data demonstrated the normal, non-cancerous cell lines HGF-1 and OKF4 exhibited an increase in growth over three days at all the concentrations evaluated (HGF-1 range: from +8.8%, p = 0.055, at 10 nmol to 13.0%, p = 0.048, at 100 nmol; OKF4 range: from +10.4%, p = 0.0468, to 11.3%, p = 0.049, at 100 nmol) compared with that of the baseline control cells (0 nmol). In addition, differential results were then observed with the oral cancer cell lines with minimal effects observed in growth with both SCC15 (−0.8%, p = 0.711, at 10 nmol and −3.6%, p = 0.339, at 100 nmol) as well as the SCC4 cells (from −1.1% to −1.6%, p = 0.49) over the concentration range of 10 nmol to 100 nmol. More moderate effects on cell growth were observed with the SCC9 (from −6.2% to −10.0%, p = 0.052) and CAL27 (from −12.1% to −15.5%, p = 0.046) cells with the most robust inhibition observed among the SCC25 cell line (from −8.6% to −37.1%, p = 0.032).

3.5. Comparison of Vitamin D2 and Vitamin D3 Growth Assays

To more accurately assess any differences in cellular responses to VitD administration, the differences between cell growth induced by VitD2 and VitD3 from each experiment were compiled (Figure 7). No significant differences were observed with the comparison of responses to VitD2 compared with those to VitD3 among the normal cell lines HGF-1 (range: from 10 nmol +1.8%, p = 0.52, to 100 nmol +6.5%, p = 0.082) and OKF4 (range: from 10 nmol +0.2%, p = 0.881, to 100 nmol +2.7%, p = 0.44). Although, these data demonstrated that non-significant differences were observed between the responses of SCC4 to VitD2 compared with VitD3 at lower concentrations of 10 nmol (+5.5%, p = 0.11) and 20 nmol (+7.8%, p = 0.067), significant differences were revealed at higher concentrations of 50 nmol (+11.0%, p = 0.048) and 100 nm (+11%, p = 0.041).
No significant differences were observed within the comparative responses among most of the oral cancer cell lines, including SCC9 (from 10 nmol −0.4%, p = 0.881, to 100 nmol −1.6%, p = 0.521), SCC15 (from 10 nmol +0.4%, p = 0.091, to 100 nmol −2.2%, p = 0.472), SCC25 (from 10 nmol +2.5% to 100 nmol −6.0%, p = 0.73), and CAL27 (from 10 nmol +2.2%, p = 0.49, to 100 nmol −3.6%, p = 0.45).

4. Discussion

The primary objective of this project was to evaluate the receptors and enzymes involved in VitD intake and metabolism that were present and functional within these well-characterized, commercially available normal and oral cancer cell lines. These results clearly demonstrated differential cellular responses to VitD3 with increased growth observed among the normal, non-cancerous cell line HGF-1 and growth inhibition observed among the oral cancers, confirming the previous studies of phenotypic responses [41,42]. Moreover, these observations also confirm studies of oral, breast, and prostate cancers that demonstrated similar differential response patterns to VitD3 administration [46,47,48,49].
These findings present some of the first evidence that may explain the differential and significantly weakened response of the SCC15 cell line to VitD3 administration due to the low-to-undetectable levels of both VDR and FOK1 expression within this cell line [42,46,50]. These observations expand the only study to date that evaluated the SCC4, SCC9, SCC15, and SCC25 expression of VDR and the cellular responses not only by the addition of CAL27 and normal HGF-1 and OKF4 cell lines, but also by the addition of screening for expression of FOK1 that has been demonstrated to significantly influence VitD3 uptake among cancers [46,51,52]. This may explain the functional significance of these findings, as both of the major VitD3 intake mechanisms may be significantly impaired within this cell line. These impairments would likely affect most (if not all) of the downstream intracellular effects [42,46].
The results of this study also provided a significant expansion of the cell lines evaluated for expression of CYP2R1, which was previously only available for SCC1, SCC11B, and SCC14A [52,53]. In addition, the other VitD hydroxylase CYP24A1 was also evaluated in this study. Although some differences in expression were found among each cell line evaluated, only SCC4 appeared not to express either. This information may provide significant novel information regarding these targets as VitD2 is converted to alternative useful cellular forms through the activity of the CYP2R1 and CYP24A1 hydroxylase enzymes, which may explain the lack of SCC4 response to VitD2, but not VitD3 administration; these molecular targets have not been elucidated in any previous study of oral cells and tissues [42,46].
Also noteworthy were the results for CYP27A1 and CYP27B1 hydroxylate enzymes, which participate in the conversion of VitD2 and VitD3 into other physiological pathways [54,55]. Although many studies have investigated the expression (or lack of) in colorectal and other cancers, only one previous study had investigated these genes among oral cancers [56]. The current results of this study may be the first to identify the association between lack of both CYP27A1 and CYP27B1 expression with the most robust response to VitD3 administration and the most significant inhibition of oral cancer growth observed. These results may be among the first to demonstrate these targets may be responsible for a potential lack of modification and the subsequent shuttling of these molecules through other biological pathways in the SCC25 cells, which might explain, in part, the susceptibility of these cells to the activity of all forms of VitD administration and may be an important target for future clinical screening studies to validate and confirm these observations [42,46].
Despite the fact that these results may be useful to aid in the development and design of future diagnostic or screening models to determine whether VitD may be useful as a complementary or alternative therapy for oral cancers (VDR/FOK1, CYP27A1/CYP27B1, and CYP2R1/CYP24A1), there are some limitations associated with this type of study that should be considered. For example, this study was designed to use well-characterized and commercially available cell lines in order to facilitate in-depth understanding of the molecular and functional pathways associated with VitD3 or VitD2 intake and metabolism. Although there are standards and verifications of each cell line that may limit variability and increase the consistency of results, there may be a possibility that cellular behaviors differ among some of the isolates derived from each cell line and that other modifications, such as genetic mutations or genetic drift could be potential confounding variables. In addition, the limited scope of this study did not allow for the large-scale screening of clinical patient samples (ex vivo) or direct patient (in vivo) analysis that would be needed to validate and confirm these results among larger patient populations [33,34,35,36,37]. Furthermore, there may be other oral cancer cell lines not available to this study’s authors in the United States (US) that could be screened for further validation of these results. Finally, there are VitD-related pathways, such as TGF/SMAD, E-cadherin/Beta catenin, and EGFR/Ras-Raf-ERK-MEK, and other mechanisms, including the VitD-induced effects on cellular adhesion and migration) to inhibit oral cancer growth, that have not yet been evaluated by this study that could be incorporated into future studies and screening protocols [57,58].

5. Conclusions

This study provides some of the first evidence to describe the molecular mechanisms, such as VDR/FOK1, as well as CYP450 hydroxylate and hydroxylase expression, that may explain the differential responses of well-characterized oral cancer cell lines to VitD administration and greatly expands the range of oral cancer cell lines evaluated. These data are important for future studies that could expand and validate these findings among clinical samples and patient populations, which would be important to develop screening targets and protocols for the use of this non-toxic complementary and alternative methods for oral cancer therapy. Further research may be needed to determine how to effectively prevent damage to these pathways to enable VitD-induced growth reduction in oral cancers or to selectively inhibit other pathways that may alter oral cancer growth responsiveness to the effects of VitD administration.

Author Contributions

Conceptualization, K.K. and K.M.H.; methodology, K.K. and K.M.H.; formal analysis, D.H. and J.L.M.; investigation, D.H. and J.L.M.; resources, K.K. and K.M.H.; data curation, D.H., J.L.M. and K.K; writing—original draft preparation, K.K., D.H. and J.L.M.; writing—review and editing, K.M.H. and K.K.; supervision, K.M.H. and K.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable; this study did not involve humans or animals.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are presented in full, and any other supporting data are available upon request from the corresponding author.

Acknowledgments

The authors would like to acknowledge the presentation of preliminary data from this project by J.L.M. at the American Association for Dental Oral and Craniofacial Research (AADOCR) annual conference. The authors would also like to thank the Department of Advanced Education in Pediatric Dentistry for their assistance with this project.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Effects of VitD3 administration on cellular growth. Growth of normal cell lines HGF-1 and OKF4 increased at all concentrations evaluated (range: from 10.6% to 19.3%) compared to that of baseline control cells (0 nmol). Differential inhibition was observed with the oral cancer cell lines, including SCC15 (range: from −0.4% to −3.9%), SCC4 (range: from −6.6% to −12.8%), SCC9 (from −7.8% to −13.2%), CAL27 (from −9.9% to −17.9%), and SCC25 (from −6.1% to −43.1%).
Figure 1. Effects of VitD3 administration on cellular growth. Growth of normal cell lines HGF-1 and OKF4 increased at all concentrations evaluated (range: from 10.6% to 19.3%) compared to that of baseline control cells (0 nmol). Differential inhibition was observed with the oral cancer cell lines, including SCC15 (range: from −0.4% to −3.9%), SCC4 (range: from −6.6% to −12.8%), SCC9 (from −7.8% to −13.2%), CAL27 (from −9.9% to −17.9%), and SCC25 (from −6.1% to −43.1%).
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Figure 2. Screening for expression of Vitamin D receptor (VDR) and FOK1 polymorphism. Expression of VDR was observed among HGF-1, OKF4, SCC4, SCC9, and CAL27 cells, but not found within SCC15 or SCC25 cells. Expression normalized to internal control GAPDH revealed consistent VDR expression, ranging from 0.97 (CAL27) to 1.09 (SCC9). FOK1 polymorphism expression was observed among SCC4, SCC9, SCC25, CAL27, OKF4, and HGF-1 cells, but not among SCC15 cells. Normalized expression data revealed more variable expressions of FOK1, ranging from 0.59 (CAL27) to 1.04 (SCC9). ** denotes below limit of qPCR screening detection. Relative quantity (RQ) is the cycle threshold (CT) value normalized to internal positive control (GAPDH).
Figure 2. Screening for expression of Vitamin D receptor (VDR) and FOK1 polymorphism. Expression of VDR was observed among HGF-1, OKF4, SCC4, SCC9, and CAL27 cells, but not found within SCC15 or SCC25 cells. Expression normalized to internal control GAPDH revealed consistent VDR expression, ranging from 0.97 (CAL27) to 1.09 (SCC9). FOK1 polymorphism expression was observed among SCC4, SCC9, SCC25, CAL27, OKF4, and HGF-1 cells, but not among SCC15 cells. Normalized expression data revealed more variable expressions of FOK1, ranging from 0.59 (CAL27) to 1.04 (SCC9). ** denotes below limit of qPCR screening detection. Relative quantity (RQ) is the cycle threshold (CT) value normalized to internal positive control (GAPDH).
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Figure 3. Screening for expression of VitD3 hydroxylase enzymes. Expression of CYP2R1 was found in all cell lines (SCC9, SCC15, SCC25, CAL27, OKF4, and HGF-1) except SCC4, with normalized expression values (GAPDH) ranging from 0.88 (SCC15) to 0.97 (SCC25). However, CYP24A1 expression was only found among SCC25, SCC15, OKF4, and HGF-1 cells, but not CAL27, SCC9 or SCC4 cells, with normalized expression values ranging between 0.67 (SCC25) and 1.13 (HGF-1). ** denotes below limit of qPCR screening detection.
Figure 3. Screening for expression of VitD3 hydroxylase enzymes. Expression of CYP2R1 was found in all cell lines (SCC9, SCC15, SCC25, CAL27, OKF4, and HGF-1) except SCC4, with normalized expression values (GAPDH) ranging from 0.88 (SCC15) to 0.97 (SCC25). However, CYP24A1 expression was only found among SCC25, SCC15, OKF4, and HGF-1 cells, but not CAL27, SCC9 or SCC4 cells, with normalized expression values ranging between 0.67 (SCC25) and 1.13 (HGF-1). ** denotes below limit of qPCR screening detection.
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Figure 4. Screening for expression of VitD3 hydroxylate enzymes. CYP27A1 was only expressed in SCC4, OKF4, and HGF-1 lines, with no expression observed among (SCC9, SCC15, SCC25, and CAL27) with normalized expression data ranging between 0.94 (HGF-1) and 1.02 (SCC4). In contrast, expression of CYP27B1 was expressed among cell lines (SCC4, SCC9, SCC15, CAL27, OKF4, and HGF-1), with exception of SCC25 cells. Normalized expression for CYP27B1 ranged between 0.87 (HGF-1) and 1.03 (SCC4). ** denotes below limit of qPCR screening detection.
Figure 4. Screening for expression of VitD3 hydroxylate enzymes. CYP27A1 was only expressed in SCC4, OKF4, and HGF-1 lines, with no expression observed among (SCC9, SCC15, SCC25, and CAL27) with normalized expression data ranging between 0.94 (HGF-1) and 1.02 (SCC4). In contrast, expression of CYP27B1 was expressed among cell lines (SCC4, SCC9, SCC15, CAL27, OKF4, and HGF-1), with exception of SCC25 cells. Normalized expression for CYP27B1 ranged between 0.87 (HGF-1) and 1.03 (SCC4). ** denotes below limit of qPCR screening detection.
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Figure 5. Effects of VitD3 administration cross-referenced with experimental study variables. All of cell lines evaluated expressed either VDR, FOK1, or both (receptor/entry), except for least responsive cell line (SCC15), which expressed neither. In addition, each the cell lines expressed one or both of major hydroxylate enzymes (CYP27A1 and CYP27B1), with exception of most responsive cell line (SCC25), which did not express either. All cell lines expressed one or both of major hydroxylase enzymes (CYP2R1 and CYP24A1), with exception of SCC4, which was missing both.
Figure 5. Effects of VitD3 administration cross-referenced with experimental study variables. All of cell lines evaluated expressed either VDR, FOK1, or both (receptor/entry), except for least responsive cell line (SCC15), which expressed neither. In addition, each the cell lines expressed one or both of major hydroxylate enzymes (CYP27A1 and CYP27B1), with exception of most responsive cell line (SCC25), which did not express either. All cell lines expressed one or both of major hydroxylase enzymes (CYP2R1 and CYP24A1), with exception of SCC4, which was missing both.
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Figure 6. Effects of VitD2 administration of cellular growth. Growth of normal cell lines HGF-1 and OKF4 increased at all concentrations evaluated (8.8% to 13.0%, p = 0.048) compared to that of baseline control cells (0 nmol). Differential inhibition was observed with oral cancer cell lines, including SCC15 (between −0.8% and −3.6%, p = 0.33), SCC4 (from −1.1% to −1.6%, p = 0.49), SCC9 (from −6.2% to −10.0%, p = 0.052), CAL27 (from −12.1% to −15.5%, p = 0.046), and SCC25 (from −8.6% to −37.1%, p = 0.032).
Figure 6. Effects of VitD2 administration of cellular growth. Growth of normal cell lines HGF-1 and OKF4 increased at all concentrations evaluated (8.8% to 13.0%, p = 0.048) compared to that of baseline control cells (0 nmol). Differential inhibition was observed with oral cancer cell lines, including SCC15 (between −0.8% and −3.6%, p = 0.33), SCC4 (from −1.1% to −1.6%, p = 0.49), SCC9 (from −6.2% to −10.0%, p = 0.052), CAL27 (from −12.1% to −15.5%, p = 0.046), and SCC25 (from −8.6% to −37.1%, p = 0.032).
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Figure 7. Differences in cellular responses to VitD2 and VitD3 administration among oral cell lines. (A) Positive, but non-significant differences were observed in growth among cell lines HGF-1 (range from +1.8% to +6.5%, p > 0.05), OKF4 (range: from 0.2% to 2.7%, p > 0.05), and SCC4 cells at lower concentrations, but significant differences were revealed with SCC4 at higher concentrations of 50 and 100 nm (+11% and +11%, respectively, p = 0.041). (B) No significant differences were observed among other oral cancer cell lines, including SCC9 (range: from −0.4% to −1.6%, p > 0.05), SCC15 (range: from +0.4% to −2.2%, p > 0.05), SCC25 (from +2.5% to −6.0%, p > 0.05), and CAL27 (from +2.2% to−3.6%, p > 0.05) across concentrations evaluated (from 10 to 100 nmol).
Figure 7. Differences in cellular responses to VitD2 and VitD3 administration among oral cell lines. (A) Positive, but non-significant differences were observed in growth among cell lines HGF-1 (range from +1.8% to +6.5%, p > 0.05), OKF4 (range: from 0.2% to 2.7%, p > 0.05), and SCC4 cells at lower concentrations, but significant differences were revealed with SCC4 at higher concentrations of 50 and 100 nm (+11% and +11%, respectively, p = 0.041). (B) No significant differences were observed among other oral cancer cell lines, including SCC9 (range: from −0.4% to −1.6%, p > 0.05), SCC15 (range: from +0.4% to −2.2%, p > 0.05), SCC25 (from +2.5% to −6.0%, p > 0.05), and CAL27 (from +2.2% to−3.6%, p > 0.05) across concentrations evaluated (from 10 to 100 nmol).
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Table 1. Cell line verification.
Table 1. Cell line verification.
HGF-1
(CRL-2014)		SCC-15
(CRL-1623)		SCC-25
(CRL-1628)		SCC-4
(CRL-1624)		SCC-9
(CRL-1629)		CAL 27
(CRL-2095)
TypeHuman gingival fibroblastOral squamous cell carcinomaOral squamous cell carcinomaOral squamous cell carcinomaOral squamous cell carcinomaOral squamous cell carcinoma
TissueGingivaTongueTongueTongueTongueTongue
Donor age28 years55 years70 years55 years25 years56 years
Donor sexMaleMaleMaleMaleMaleMale
STR match100%94%100%92%100%93%
STR analysis (ATCC.com)Amelogenin: X,Y
CSF1PO: 11
D13S317: 8,12
D16S539: 11,13
D5S818: 12
D7S820: 10
TH01: 6,7
TPOX: 8,11
vWA: 17,18
D3S1358: 17
D21S11: 28,29
D18S51: 16,20
Penta_E: 17,20
Penta_D: 13
D8S1179: 12,13
FGA: 24
D19S433: 12,14
D2S1338: 17,24		Amelogenin: X,Y
CSF1PO: 10,13
D13S317: 9,14
D16S539: 12,15
D5S818: 12
D7S820: 10,11
TH01: 9,9.3
TPOX: 8
vWA: 15,17
D3S1358: 16
D21S11: 30,31.2
D18S51: 16
Penta_E: 7,13
Penta_D: 9,13
D8S1179: 10,13
FGA: 19,24
D19S433: 15
D2S1338: 16,23		Amelogenin: X
CSF1PO: 10
D13S317: 13
D16S539: 11,12
D5S818: 12
D7S820: 12
TH01: 8
TPOX: 8,12
vWA: 17,19
D3S1358: 17
D21S11: 30
D18S51: 16
Penta_E: 14,15
Penta_D: 13
D8S1179: 13
FGA: 20,24
D19S433: 13,14
D2S1338: 17,19		D3S1358: 18
TH01: 9.3
D21S11: 32.2
D18S51: 15
Penta_E: 14
D5S818: 13
D13S317: 11,13
D7S820: 9,11
D16S539: 12
CSF1PO: 11
Penta_D: 12
Amelogenin: X,Y
vWA: 15,17
D8S1179: 14
TPOX: 8
FGA: 21,22
D19S433: 12,14
D2S1338: 16,24		Amelogenin: X,Y
CSF1PO: 11
D13S317: 9
D16S539: 10,11
D5S818: 12
D7S820: 8
TH01: 8,9
TPOX: 9,11
vWA: 17
D3S1358: 15
D21S11: 28
D18S51: 12,14
Penta_E: 11
Penta_D: 9
D8S1179: 13
FGA: 20,25
D19S433: 12,14
D2S1338: 19,21		D3S1358: 16
TH01: 6,9.3
D21S11: 28,29
D18S51: 13
Penta_E: 7
D5S818: 11,12
D13S317: 10,11
D7S820: 10
D16S539: 11,12
CSF1PO: 10,12
Penta_D: 9,10
Amelogenin: X
vWA: 14,17
D8S1179: 13,15
TPOX: 8
FGA: 25
D19S433: 14,15.2
D2S1338: 23,24
Additional characteristics:HGF-1 cells exhibit fibroblast morphology and demonstrate expression of Bradykinin.SCC15 cells express epidermal keratins (including 40 kD keratin), as well as detectable levels of involucrin.SCC25 cells demonstrate expression of epidermal keratins as well as low levels of involucrin.SCC4 cells have been characterized as epithelial, with positive expression of. epidermal keratins (including 40 kD keratin).SCC9 cells demonstrate expression of epidermal keratins as well as low levels of involucrin.CAL27 cells have been characterized as epithelial, with a cytoplasm that is highly granular. Immunohistochemistry has revealed positive staining with anti-keratin antibodies.
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Hunsaker, D.; Moore, J.L.; Howard, K.M.; Kingsley, K. Vitamin D Receptor and CYP450 Enzyme Dysregulation May Mediate Oral Cancer Responsiveness. Targets 2025, 3, 6. https://doi.org/10.3390/targets3010006

AMA Style

Hunsaker D, Moore JL, Howard KM, Kingsley K. Vitamin D Receptor and CYP450 Enzyme Dysregulation May Mediate Oral Cancer Responsiveness. Targets. 2025; 3(1):6. https://doi.org/10.3390/targets3010006

Chicago/Turabian Style

Hunsaker, Dustin, James Landon Moore, Katherine M. Howard, and Karl Kingsley. 2025. "Vitamin D Receptor and CYP450 Enzyme Dysregulation May Mediate Oral Cancer Responsiveness" Targets 3, no. 1: 6. https://doi.org/10.3390/targets3010006

APA Style

Hunsaker, D., Moore, J. L., Howard, K. M., & Kingsley, K. (2025). Vitamin D Receptor and CYP450 Enzyme Dysregulation May Mediate Oral Cancer Responsiveness. Targets, 3(1), 6. https://doi.org/10.3390/targets3010006

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