TC2N promotes the proliferation and invasion of head and neck cancer cells with the p53-R175H

Introduction

Head and neck squamous cell carcinoma (HNSCC) are malignant tumors that develop in various regions of the head and neck, including the mouth, throat, tongue, vocal cords, buccal cavity, nasal cavity, and thyroid gland (1). These tumors are among the most prevalent malignancies globally and significantly affect patients’ quality of life and survival rates (2). It is currently known that the etiology of HNSCC is multifactorial, involving genetic predispositions, tobacco use, excessive alcohol consumption, and human papillomavirus (HPV) infection (3); however, the specific mechanisms of pathogenesis have not yet been fully elucidated. Therefore, exploring the molecular mechanisms that regulate the occurrence and development of HNSCC will help identify potential clinical targets and biomarkers, ultimately improving patient diagnosis and treatment.

p53 serves as a crucial transcription factor that contributes to tumor suppression by activating a variety of target genes (4). Unfortunately, it ranks among the most frequently mutated genes in human cancers, with mutations observed in 65–85% of cases of HNSCC (5,6). The predominant type of mutation in HNSCC is missense mutations, which result in the replacement of a single amino acid (7). These mutations not only compromise the tumor-suppressing capabilities of the wild-type p53 but also introduce new functions that can facilitate tumor recurrence and resistance to chemotherapy, a phenomenon referred to as gain-of-function (8). Research has indicated that the p53 protein, encoded by the TP53 gene, is commonly mutated in HNSCC (9). Consequently, understanding the pathogenic mechanisms associated with mutant p53 in HNSCC is vital for tailoring more individualized treatment approaches for the affected patients.

Tandem C2 domains, nuclear (TC2N) is a protein that contains C2 domains and is classified within the carboxyl-terminal type (C-type) tandem C2 protein family (10). Previously, we were the first to reveal the role and molecular mechanisms of this gene in lung cancer and breast cancer, confirming that it is a differentially expressed gene in malignant tumors. Subsequently, the oncogenic roles and molecular mechanisms of TC2N in various cancers, including glioma, liver cancer and gastric cancer, have been gradually revealed (11-17), highlighting its critical role in tumorigenesis and progression. In addition, Qureshi et al. analyzed TC2N expression, methylation levels, copy number variation (CNV), and other factors across pan-cancer using The Cancer Genome Atlas (TCGA) database. Notably, the methylation level of the TC2N promoter is significantly increased in HNSCC (15). Accumulated evidence suggest that low methylation levels can lead to genomic instability, thereby inducing tumorigenesis (18). Therefore, we speculate that TC2N may have potential functions in HNSCC, needing to be further investigated.

In this study, we utilized the TCGA database and multiple Gene Expression Omnibus (GEO) datasets to analyze and validate the expression of TC2N in HNSCC and adjacent tissues, and evaluated the correlation between the methylation of the TC2N promoter region and its expression. Additionally, through in vivo and in vitro experiments, we preliminarily elucidated the role of TC2N in promoting cell proliferation and invasion by amplifying the pro-cancer signals mediated by p53-R175H, thereby laying the experimental foundation for understanding the role and mechanism of TC2N in HNSCC. We present this article in accordance with the MDAR and ARRIVE reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2130/rc).

Methods

Cell line and cell culture

The human HNSCC cell line CAL33 and FaDu were purchased from Guangzhou CellCook Biological Technology Co., Ltd. (Guangzhou, China) and cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 1% penicillin-streptomycin, and 2 mM L-glutamine. Cells were maintained in a humidified incubator at 37 ℃ with 5% CO₂.

Cell transfection and lentiviral infection

For gene silencing experiments, we utilized Lipofectamine 2000 (Invitrogen, Carlsbad, USA) for transfection. Briefly, CAL33 and FaDu cells were seeded in 6-well plates at a density of 5×10⁵ cells per well and allowed to adhere overnight. The following day, 2 µg small interfering RNA (siRNA) for TP53 was mixed with 6 µL of Lipofectamine 2,000 in 200 µL of Opti-MEM medium (Invitrogen) and incubated for 15 minutes at room temperature. The DNA-Lipofectamine complex was then added dropwise to the cells, and they were incubated for 48 hours before assessing transfection efficiency.

For lentiviral infection, CAL33 and FaDu cells were seeded in 6-well plates at a density of 5×10⁵ cells per well. The next day, the cells were infected with lentiviral particles containing the desired gene or shRNA, along with 8 µg/mL of polybrene (Santa Cruz Biotechnology, Dallas, USA) to enhance infection efficiency. After 24 hours, the medium was replaced with fresh complete DMEM. Infected cells were selected using 2 µg/mL of puromycin (Sigma-Aldrich, St. Louis, USA) for 1–2 weeks to establish stable cell lines. The efficiency of both transfection and infection was confirmed by quantitative polymerase chain reaction (PCR) and Western blot (WB) analysis.

Downloading TCGA program and GEO datasets and gene set enrichment analysis (GSEA) analysis

The ribonucleic acid-sequencing data for lung cancer were obtained directly from TCGA website (https://www.cancer.gov/). Additionally, RNA expression profiles from the GEO database (https://www.ncbi.nlm.nih.gov/geo/) were downloaded, including datasets GSE23558, GSE37991 and GSE138206. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

GSEA is a computational approach used to assess whether a predefined set of genes exhibits statistically significant and consistent differences between two biological states. The data from TCGA can be organized into a ranked list based on their differential expression related to specific phenotypes. The GSEA software (version 4.3.2) was downloaded from the official GSEA website (https://www.gsea-msigdb.org/gsea/index.jsp). For analysis, the RNA-Seq data were converted into a “GCT” file format (gene.GCT) and subsequently uploaded to the “Load data” section of the software. In the “Run GSEA” section, parameters were set, including the gene set database: C5.go.bp.v2023.1.Hs.symbols.gmt (curated) or C5.go.reactome.v2023.1.Hs.symbols.gmt (curated); the number of permutations was set to 1,000; and phenotype labels were designated using TC2N as the phenotype. A P value of <0.05 and a false discovery rate (FDR) of <0.25 were considered statistically significant. The statistical parameters for these analyses from the TCGA database are detailed in https://cdn.amegroups.cn/static/public/tcr-24-2130-1.xlsx.

Protein extraction and WB analysis

Cells or tissues were lysed using sodium dodecyl sulfate (SDS) lysis buffer (Beyotime, Shanghai, China) supplemented with PMSF (Beyotime, Shanghai, China) to extract total protein. Protein quantification was performed using the bicinchoninic acid assay (BCA) quantification kit (Beyotime, Shanghai, China). WB analysis was carried out following established protocols as previously described (19). In brief, twenty micrograms of protein were separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) on either 8% or 10% gels. The separated proteins were then transferred to a polyvinylidene difluoride (PVDF) membrane (Millipore Corporation, Bedford, MA, USA). The membranes were blocked with 5% milk for 1 hour at room temperature and subsequently incubated overnight at 4 ℃ with primary antibodies. After washing, the membranes were incubated with a secondary antibody conjugated to horseradish peroxidase (HRP) and detected using a chemiluminescence detection system (Pierce, Rockford, IL, USA). The primary antibody against TC2N (Cat. #: HPA027549) was obtained from Sigma-Aldrich; c-Met (Cat. #: 25869-1-AP), phospho-c-Met (Cat. #: 30737-1-AP), p21 (Cat. #: 10355-1-AP), PUMA (Cat. #: 55120-1-AP), p53 (Cat. #: 10442-1-AP) and Actin (Cat. #: 66009-1-Ig) were purchased from Proteintech Group (Wuhan, China); secondary antibodies (Cat. #: A0216 and A0208) were obtained from Beyotime.

5-ethynyl-2'-deoxyuridine (EdU) detection by flow cytometry

To assess cell proliferation, the EdU incorporation assay was performed using the EdU Cell Proliferation Kit (Invitrogen). CAL33 and FaDu cells were treated with EdU (10 µM) for 2 hours to allow for incorporation during DNA synthesis. After the incubation, the cells were washed twice with phosphate-buffered saline (PBS) and then fixed with 4% paraformaldehyde for 15 minutes at room temperature. Subsequently, the cells were permeabilized with 0.5% Triton X-100 in PBS for 20 minutes. The EdU incorporation was detected using the Click-iT EdU Imaging Kit according to the manufacturer’s instructions. Briefly, the cells were incubated with the reaction cocktail containing the fluorescent azide for 30 minutes at room temperature in the dark. After washing with PBS, the cells were stained with 7-aminoactinomycin D (7-AAD) to assess cell viability and DNA content. Finally, the samples were analyzed using a flow cytometer (BD FACSCalibur or equivalent, Franklin Lakes, USA). Data were collected for at least 10,000 events, and the percentage of EdU-positive cells was calculated to determine the proliferation rate. The results were analyzed using FlowJo software (version 7.6).

Cell cycle analysis by flow cytometry

Cell cycle distribution was assessed using propidium iodide (PI) staining. CAL33 and FaDu cells were harvested and washed twice with PBS. The cells were then fixed in 70% ethanol at −20 ℃ for at least 2 hours or overnight to ensure complete fixation. After fixation, the cells were washed with PBS and resuspended in a staining solution containing 50 µg/mL PI and 100 µg/mL RNase A in PBS. The cells were incubated in the dark at room temperature for 30 minutes to allow for DNA staining. Following incubation, the samples were analyzed using a flow cytometer (BD FACSCalibur or equivalent). Data were collected for at least 10,000 events, and the cell cycle distribution was determined by analyzing the DNA content. The percentage of cells in the G0/G1, S, and G2/M phases of the cell cycle was calculated using FlowJo software. The results were presented as histograms showing the distribution of cells across different phases of the cell cycle.

Detection of cell apoptosis by flow cytometry

To evaluate serum-induced apoptosis, CAL33 and FaDu cells were cultured in serum-free medium for 24 hours to induce apoptosis. Following this incubation, the cells were harvested and washed twice with PBS. Apoptosis was assessed using the Annexin V-PE Apoptosis Detection Kit (Beyotime) according to the manufacturer’s instructions. The harvested cells were resuspended in 1X binding buffer at a concentration of 1×10⁶ cells/mL. Subsequently, 5 µL of Annexin V-PE was added to 100 µL of the cell suspension. The cells were gently mixed and incubated for 15 minutes at room temperature in the dark. After incubation, 400 µL of 1× binding buffer was added to each sample. The samples were analyzed using a flow cytometer (BD FACSCalibur or equivalent). Data were collected for at least 10,000 events, and the percentage of apoptotic or necrotic cells was determined. The results were analyzed using FlowJo software, and the data were presented as scatter plots to illustrate the distribution of apoptotic cells.

Colony formation assay

To assess the clonogenic potential of CAL33 and FaDu cells, a colony formation assay was performed. Cells were seeded in 6-well plates at a density of 200 cells per well in complete DMEM medium and allowed to adhere overnight. After 24 hours, the medium was replaced with fresh complete medium, and the cells were cocultured for 14 days. During the incubation period, the medium was changed every 3 days to maintain optimal growth conditions. At the end of the treatment period, the cells were fixed with 4% paraformaldehyde for 15 minutes at room temperature. Following fixation, the cells were stained with 0.5% crystal violet solution for 30 minutes to visualize the colonies. After staining, the plates were washed with PBS to remove excess dye, and the colonies were counted using a light microscope. A colony was defined as a cluster of at least 50 cells. The results were expressed as the number of colonies formed per well, and the plating efficiency was calculated by dividing the number of colonies by the number of cells initially seeded, multiplied by 100. This assay provides insight into the long-term survival and proliferative capacity of the cells under specific conditions.

Transwell migration and invasion assay

The Transwell migration and invasion assays were conducted to evaluate the migratory and invasive capabilities of CAL33 and FaDu cells. For the migration assay, 24-well Transwell plates with 8 µm pore size inserts (Corning, Corning, USA) were used. CAL33 and FaDu cells were serum-starved for 24 hours before the experiment to synchronize the cells. A total of 2×10³ cells were resuspended in serum-free DMEM and added to the upper chamber of the Transwell insert. The lower chamber was filled with complete DMEM containing 10% FBS as a chemoattractant. After 24 hours of incubation at 37 ℃ in a humidified atmosphere with 5% CO₂, non-migrated cells on the upper surface of the membrane were gently removed with a cotton swab. The migrated cells on the lower surface of the membrane were fixed with 4% paraformaldehyde for 15 minutes and stained with 0.1% crystal violet solution for 30 minutes. After washing with PBS, the stained cells were counted under a light microscope in five random fields at 200× magnification. For the invasion assay, the Transwell inserts were pre-coated with Matrigel (BD Biosciences, San Jose, USA) according to the manufacturer’s instructions. The procedure was similar to the migration assay, with the exception that the cells were added to the upper chamber on top of the Matrigel layer. The results were expressed as the number of migrated or invaded cells per field, and the experiments were performed in triplicate to ensure reproducibility.

Subcutaneous tumor formation in nude mice and organ collection for histological analysis

To evaluate the tumorigenic potential of CAL33 and FaDu cells in vivo, a subcutaneous tumor formation experiment was conducted using nude mice (female mice, 3–4 weeks old) which were provided by Chengdu Yaokang Biotechnology Co., Ltd. (Chengdu, China). A total of 2×10⁶ CAL33 and FaDu cells were resuspended in 100 µL of sterile PBS and injected subcutaneously into the right flank of each mouse. The mice were monitored for tumor growth, and tumor size was measured using calipers every 5 days. The volume of the tumors was calculated using the formula: 0.5 × (length × width²). After 38 days, the mice were euthanized by cervical dislocation, and the tumors were excised for further analysis. The lung, live and kidneys were also collected to assess potential metastasis. The harvested organs were fixed in 10% formalin for 24 hours and then embedded in paraffin. Tissue sections (5 µm thick) were prepared and stained with hematoxylin and eosin (HE) to evaluate histopathological changes. The sections were examined under a light microscope to assess the presence of tumor cells in each organ, and the extent of metastasis was recorded. This experiment provided insights into the metastatic behavior of CAL33 cells in vivo and the potential organ-specific tropism of the tumors. All animal experiments were performed under a project license (No. AMUWEC20245267) granted by the Animal Ethics Committee of Third Military Medical University, in compliance with national guidelines for the care and use of animals. A protocol was prepared before the study without registration.

Statistical analysis

Statistical analyses were performed using GraphPad Prism software (version 9.0) and SPSS (version 25.0). Data were presented as mean ± standard deviation (SD) or mean ± standard error of the mean (SEM) as appropriate. Comparisons between two groups were conducted using Student’s t-test, while multiple groups were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test for pairwise comparisons. For correlation analyses, Pearson’s and Spearman’s correlation coefficients were calculated to assess the relationship between variables. A P value of less than 0.05 was considered statistically significant. All experiments were conducted in triplicate, and the results were confirmed in independent experiments to ensure reproducibility. The statistical significance of the findings is indicated in the figures and tables, with asterisks denoting the level of significance (*, P<0.05; **, P<0.01; ***, P<0.001).

Results

TC2N is downregulated in HNSSC, and its expression is associated with its methylation status

To assess the potential role of TC2N in HNSCC, we first analyzed the expression of TC2N in tumor and adjacent normal tissues using the TCGA database. We found that the messenger RNA (mRNA) levels of TC2N were significantly downregulated in HNSCC (Figure 1A), and this result was further validated using three independent GEO datasets (Figure 1B-1D). At the protein level, we examined the expression of TC2N in HNSCC tissues and adjacent normal tissues using The Human Protein Atlas database (https://www.proteinatlas.org/), revealing that TC2N expression was significantly lower in tumors compared to normal tissues (Figure 1E).

Figure 1 TC2N is downregulated in HNSCC, and its expression is associated with methylation in the promoter region. (A) The mRNA level data of TC2N in HNSCC and adjacent tissues was showed by analyzing TCGA database. (B) The mRNA level data of TC2N in HNSCC and adjacent tissues was showed by analyzing GSE23558 dataset. (C) The mRNA level data of TC2N in HNSCC and adjacent tissues was showed by analyzing GSE37991 dataset. (D) The mRNA level data of TC2N in HNSCC and adjacent tissues was showed by analyzing GSE138206 dataset. (E) The protein level data of TC2N in HNSCC and normal tissues was showed by analyzing Human Protein Atlas database. The URL for salivary gland group: https://www.proteinatlas.org/ENSG00000165929-TC2N/tissue/salivary+gland; The URL for esophagus group: https://www.proteinatlas.org/ENSG00000165929-TC2N/tissue/esophagus; The URL for tumor group: https://www.proteinatlas.org/ENSG00000165929-TC2N/cancer/head+and+neck+cancer#IHC. (F) The methylation levels of TC2N CpG islands between HNSCC and adjacent tissues. (G) The correlation between the methylation levels of CpG islands cg01576142 and cg24633648 and TC2N mRNA levels. ns, no significance; *, P<0.05; **, P<0.01; ***, P<0.001. CpG, cytosine-phosphate-guanine; HNSCC, head and neck squamous cell carcinoma; GDC, Genomic Data Commons; IHC, immunohistochemical; TC2N, tandem C2 domains, nuclear; TCGA, The Cancer Genome Atlas.

DNA methylation is one of the important epigenetic modifications that contribute to gene silencing (20). Previous study has preliminarily analyzed the negative correlation between TC2N promoter methylation levels and its expression using the TCGA database (15), however, which cytosine-phosphate-guanine (CpG) island is involved remain unclear. We further analyzed the methylation levels of different CpG islands in the promoter region of TC2N in tumor and adjacent normal tissues using the TCGA database. We found that the methylation levels of cg01576142 and cg24633648 were significantly higher in tumor tissues than in adjacent normal tissues (Figure 1F), suggesting that these two CpG islands are potential sites mediating the regulation of TC2N expression. Indeed, correlation analysis indicated that the methylation levels of these two sites were significantly negatively correlated with TC2N mRNA levels (Figure 1G), indicating that the reduced expression of TC2N in HNSCC is influenced by the high methylation of cg01576142 and cg24633648.

TC2N expression is associated with cell proliferation, apoptosis, and cell junction processes, and is linked to mutant p53-mediated p53 signaling pathway in HPV-negative HNSSC

Next, we conducted GSEA analysis based on the TCGA database to explore the biological processes associated with TC2N. The results indicated that TC2N expression was positively correlated with several processes related to cell proliferation and junction, while it was negatively correlated with apoptosis (Figure 2A). Reactome pathway analysis revealed potential signaling pathways associated with TC2N, showing a connection between TC2N and the p53 signaling pathway (Figure 2B). Interestingly, TC2N and TP53 also exhibited a positive correlation at the mRNA level (Figure 2C), suggesting that TC2N may promote p53-related signaling pathways. Given the high mutation rate of TP53 in HNSCC and numerous studies indicating that mutant p53 can facilitate tumor growth and metastasis (21-23), we hypothesize that TC2N may drive HNSCC growth and metastasis by promoting pro-cancer signals mediated by mutant p53.

Figure 2 TC2N expression is positively correlated with the mutant p53-mediated signaling pathway in HPV− HNSCC. (A) GSEA analysis showed that TC2N expression is associated with cell proliferation, cell junction, and apoptosis processes. (B) GSEA analysis showed that TC2N expression is associated with p53 relevant signaling pathway. (C) In HNSCC, the mRNA levels of TC2N are positively correlated with the mRNA levels of TP53. (D) The correlation between TC2N and mutant TP53, as well as its known downstream target molecules, at the mRNA level in HNSCC with TP53 mutations. (E) GSEA analysis showed that TC2N expression is associated with p53 relevant signaling pathway in TP53 mutated HNSCC. (F) The mRNA expression of TC2N between HPV-positive and HPV-negative HNSCC. (G) GSEA analysis showed the association of TC2N expression with p53 relevant signaling pathway in HPV− and HPV+ HNSCC. (H) GSEA analysis showed the association of TC2N expression with p53 relevant signaling pathway in HPV− HNSCC with mutant or wild type TP53. ns, no significance. HNSCC, head and neck squamous cell carcinoma; HPV, human papillomavirus; GDC, Genomic Data Commons; GSEA, gene set enrichment analysis; NES, normalized enrichment score; TC2N, tandem C2 domains, nuclear; TCGA, The Cancer Genome Atlas.

To validate this hypothesis, we further analyzed the expression correlation of TC2N with TP53 and its known downstream target genes in HNSCC samples with TP53 mutations. We found that TC2N was positively correlated with several pro-cancer molecules downstream of mutant p53, while its correlation with TP53 was not significant (Figure 2D). Additionally, the GSEA results also suggested that TC2N is associated with the p53 signaling pathway in TP53-mutated HNSCC (Figure 2E). TP53 mutations frequently occur in HPV-negative HNSCC (24). Therefore, we further analyzed TC2N expression and its correlation with p53 signaling separately in HPV+ and HPV− samples. The results showed no significant difference in TC2N expression between HPV+ and HPV− tumor tissues (Figure 2F). However, in HPV− samples, TC2N expression was correlated with the p53 signaling pathway, whereas no such correlation was observed in HPV+ samples (Figure 2G). Furthermore, TC2N was associated with p53 signaling in TP53-mutant HNSCC but showed no significant correlation in TP53 wild-type HNSCC within HPV− tissues (Figure 2H). These findings indicate that the regulatory effect of TC2N on mutant TP53 signaling exists only in HPV-TP53-mutant samples.

Overexpression of TC2N promotes proliferation and invasion of HNSCC cells carrying p53-R175H but not those carrying p53-R248 in vitro

To investigate the regulatory effect of TC2N on mutant TP53 cells, we selected two HPV-negative HNSCC cell lines, CAL33 and FaDu, which carry the common TP53 mutations R175H (25) and R248 (26), respectively, and established cell models with differential TC2N expression (Figure 3A). First, through in vitro EdU proliferation assays, we found that overexpression of TC2N significantly promoted proliferation, while silencing TC2N inhibited proliferation of CAL33 cells but did not exert its function in FaDu cells (Figure 3B). Flow cytometry analysis of the cell cycle and apoptosis revealed that overexpression of TC2N accelerated cell cycle progression and inhibited apoptosis, whereas interfering with its expression led to cell cycle arrest and promoted apoptosis in CAL33 but nor in FaDu (Figure 3C,3D). Colony formation assays also demonstrated that overexpression of TC2N enhanced colony formation, while silencing TC2N suppressed it in CAL33 cells (Figure 3E). Furthermore, the Transwell assay demonstrated that TC2N significantly promotes migration and invasion in CAL33 cells, however, this phenomenon was not observed in FaDu cells (Figure 3F).

Figure 3 TC2N promotes the proliferation and invasion of HNSCC cells with p53-R175H mutations. (A) WB identification of the CAL33 and FaDu stable cell lines with differentially expressed TC2N. (B) The effect of differentially expressed TC2N on EdU-positive cells. (C) The effect of differentially expressed TC2N on cell cycle. (D) The effect of differentially expressed TC2N on cell apoptosis. (E) The effect of differentially expressed TC2N on colony formation. Cell clones were stained with crystal violet. (F) The effect of differentially expressed TC2N on cell migration and invasion. The migrated/invaded cells were stained with crystal violet. ns, no significance; *, P<0.05; **, P<0.01; ***, P<0.001. EdU, 5-ethynyl-2'-deoxyuridine; HNSCC, head and neck squamous cell carcinoma; NC, negative control; TC2N, tandem C2 domains, nuclear; WB, Western blot.

TC2N accelerates tumor growth and metastasis in vivo

Next, we established a nude mouse xenograft model using the CAL33 cells with differential expression of TC2N to further evaluate the in vivo function of TC2N. The results showed that the subcutaneous tumors in the TC2N overexpression group grew faster (Figure 4A), with a significant increase in tumor size and weight (Figure 4B,4C). To more intuitively assess tumor growth rate in vivo, we performed immunohistochemical analysis of the proliferation marker Ki67 in the transplanted tumor tissues and found that the Ki67 expression in the TC2N overexpression group was higher than that in the TC2N low expression group (Figure 4D). Furthermore, after dissecting the nude mice, we further analyzed the metastasis of tumor cells to various organs and found that high expression of TC2N significantly promoted the metastasis of CAL33 cells to the lungs, liver, and kidneys (Figure 4E). These results demonstrate that TC2N can promote tumor growth and metastasis.

Figure 4 TC2N promotes tumor growth and metastasis. (A) Growth curve of subcutaneous tumors after differential expression of TC2N. (B) The photographs were taken before and after tumor dissection. (C) The weight of tumors in each group. (D) The HE and IHC staining were performed on tumor tissues. Scale bar represents 100 µm. (E) Using HE staining to observe tumor metastases in various organs. Scale bar represents 100 µm. ns, no significance; *, P<0.05. HE, hematoxylin and eosin; IHC, immunohistochemical; NC, negative control; TC2N, tandem C2 domains, nuclear.

TC2N augments the oncogenic signals mediated by mutant TP53 (R175H)

Previous studies have reported that TP53 R175H can promote HNSCC cell proliferation and resistance to apoptosis by inhibiting the expression of p21 and PUMA (27), and it can facilitate metastasis by inducing Met phosphorylation (28). Therefore, we examined the expression of TP53 R175H and the changes in its downstream target molecules. We found that overexpression of TC2N could upregulate R175H expression, downregulate p21 and PUMA, and upregulate phosphorylated Met, while silencing TC2N resulted in the opposite results (Figure 5A). Interestingly, overexpression of TC2N in FaDu cells also upregulates the level of p53-R248 (Figure 5B). To demonstrate that TC2N regulates Met, p21, and PUMA through an R175H-mediated mechanism, we further analyzed the changes in downstream molecules after silencing p53 expression with siRNA. We discovered that silencing p53 significantly counteracted the changes in downstream target molecules induced by TC2N overexpression (Figure 5C). These results indicate that in HNSCC cells with p53-R175H mutations, TC2N can promote tumor growth and metastasis through a signaling pathway mediated by mutant TP53 (Figure 5D).

Figure 5 TC2N activates p53-R175H-mediated pro-cancer signals. (A) TC2N augmented pro-cancer signals regulated by p53-R175H. (B) TC2N upregulated p53-R248 protein expression. (C) Interference with p53-R175H counteracted the changes in the phosphorylation of Met and the expression of p21 and PUMA induced by TC2N overexpression. (D) Schematic diagram of TC2N promoting HNSCC growth and invasion through p53-R175H. HNSCC, head and neck squamous cell carcinoma; NC, negative control; PUMA, p53 upregulated modulator of apoptosis; TC2N, tandem C2 domains, nuclear.

Discussion

TC2N is a newly discovered tumor-associated gene that has been reported to have oncogenic effects in various cancers, including lung cancer, liver cancer, gastric cancer, and glioma. In lung cancer, TC2N promotes tumor growth by inhibiting wild-type p53-mediated signaling pathways and facilitates distant metastasis by activating the NF-κB signaling pathway. In liver cancer, TC2N enhances Wnt/β-catenin signaling to promote tumor progression. On the other hand, TC2N acts as a tumor suppressor gene in breast cancer, inhibiting tumor growth and metastasis by suppressing the PI3K-AKT signaling pathway and fatty acid synthesis. These studies confirm the significant role of TC2N in various tumors, warranting further investigation.

In the study by Qureshi et al., TC2N exhibited a significant increase in CNV in HNSCC, which contradicts the observed downregulation of its expression in HNSCC (15). This suggests that TC2N expression in HNSCC is not regulated, or at least not entirely regulated by CNV. From an epigenetic perspective, both Qureshi et al.’s analysis and ours showed that the methylation level of the TC2N promoter region in HNSCC is lower than that in adjacent normal tissues, and its methylation degree is negatively correlated with expression, indicating that the gene is regulated by methylation. Building on this, we further explored the specific CpG islands that regulate TC2N methylation (15). Of course, the current data are limited to correlation analysis, and we plan to conduct further experiments to validate the role of methylation in regulating TC2N expression.

Subsequent analyses indicated a positive correlation between TC2N expression and the p53 signaling pathway, suggesting that TC2N may have a tumor-suppressive role in HNSCC. Due to the frequent occurrence of TP53 mutations in HNSCC, where mutant TP53 loses its tumor-suppressive function and behaves as an oncogene, we propose that TC2N may promote HNSCC growth and metastasis through signaling pathways mediated by mutant TP53. After establishing TP53-mutant HNSCC cell lines with differential TC2N expression, we analyzed their malignant phenotypes and found that TC2N promoted proliferation and invasion only in R175H cells (CAL33), but showed ineffective in R248 cells (FaDu). Detection of the expression levels of different p53 mutants in the two cell lines revealed that both R175H and R248 protein levels were upregulated following TC2N overexpression. R175H is a typical oncogenic protein, whereas the oncogenic role of R248 remains controversial. Study suggests that although the p53-R248 mutant partially loses DNA-binding activity, it still retains some tumor suppressor functions (29). In other words, R248 exhibits both oncogenic and tumor-suppressive effects in HNSCC. Previously, Hao et al. discovered that TC2N not only inhibits the activity of wild-type p53 but may also promote lung cancer growth through oncogenic signals mediated by mutant TP53 (R273H) (12). Therefore, we speculate that in HNSCC, when the p53 mutant acts as an oncogenic protein, TC2N may promote tumor progression by amplifying mutant p53 signaling; however, when the p53 mutant has dual functions, TC2N’s contradictory effects mediated through mutant p53 may offset each other. Of course, this is only a hypothesis, and we plan to further investigate the regulatory roles and mechanisms of TC2N on different p53 mutants in future studies.

In terms of mechanism, there seems to be a significant difference in how TC2N regulates wild-type p53 and mutant p53. In lung cancer, after upregulating TC2N expression, there was no significant change in the expression of wild-type TP53; however, its phosphorylation level decreased, leading to reduced activity and suppression of downstream target genes such as P21 and BAX. In contrast, in HNSCC, overexpression of TC2N resulted in an increase in the expression of p53-R175H and p53-R248, indicating that the mechanisms by which TC2N regulates wild-type and mutant TP53 are different. Since TC2N is not correlated with mutant TP53 at the mRNA level and is not a transcription factor, it is unlikely to directly transcribe TP53. Therefore, we speculate that TC2N upregulates mutant TP53 at the post-transcriptional level. Additionally, based on previous reports indicating that TC2N plays an important role in regulating protein phosphorylation and ubiquitination (12), we lean towards the idea that TC2N is involved in regulating the post-translational modification processes of mutant p53; however, this requires further in-depth analysis.

Conclusions

In summary, we have revealed for the first time the expression pattern of TC2N in HNSCC and found that its expression is associated with oncogenic signals mediated by mutant TP53. Through in vitro and in vivo experiments, we demonstrated that TC2N promotes HNSCC growth and metastasis by enhancing TP53 R175H-mediated signaling. This preliminary study provides firsthand information on the role and mechanism of TC2N in TP53-mutated HNSCC and enriches the existing reports on the function of TC2N in tumors.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR and ARRIVE reporting checklists. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2130/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2130/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2130/prf

Funding: This work was supported by grants from the Part 73: China Postdoctoral Science Foundation (No. 2023M734255), the Youth Training Program of the Second Affiliated Hospital of the Army Medical University (No. 2022YQB048), and the Famous Army Teacher project of the Army Medical University (No. 417Z143).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2130/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. All animal experiments were performed under a project license (No. AMUWEC20245267) granted by the Animal Ethics Committee of Third Military Medical University, in compliance with national guidelines for the care and use of animals.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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