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. 2025 Jan 14;75(2):970–983. doi: 10.1016/j.identj.2024.09.035

TPPP3, a Good Prognostic Indicator, Suppresses Cell Proliferation and Migration in OSCC

Ting Xiao a, Omar Rahhal a, Liping Wang a, Zhiyuan Deng a, Ran Wang b, Xinghuanyu Xu a, Lu Qi a,⁎, Zhangui Tang a,⁎
PMCID: PMC11976587  PMID: 39814636

Abstract

Introduction and aims

Oral squamous cell carcinoma (OSCC) is one of the most prevalent malignancy of the head and neck. Early diagnosis of OSCC is difficult and the prognosis has not improved significantly. This study aims to explore the role of tubulin polymerisation promoting protein 3 (TPPP3) in the occurrence and development of OSCC and discover new diagnostic and prognostic markers for OSCC.

Methods

Using UALCAN, GEPIA, western blot, and quantitative real-time polymerase chain reaction, we studied TPPP3 expression and its relationship with tumour stage. Then, we detected the effect of TPPP3 on OSCC biological functions by CCK-8 and cell scratch assays, as well as correlations between TPPP3 expression and survival of different kinds of head and neck squamous cell carcinoma (HNSC) patients through Kaplan-Meier plotter. Besides, we explored coexpressed genes associated with TPPP3 in HNSC using LinkedOmics and protein-protein interaction networks of TPPP3 using STRING and Cytoscape. Furthermore, we explored possible molecular mechanisms that TPPP3 functions in HNSC using UALCAN, Kaplan-Meier plotter, and TIMER. Finally, we analysed promoter methylation level by UALCAN and mutation by cBioPortal of TPPP3 in HNSC.

Results

TPPP3 was less expressed in OSCC. The TPPP3 expression level was negatively correlated with tumour stage. Furthermore, TPPP3 significantly inhibited OSCC proliferation and migration. Besides, TPPP3 high expression was significantly associated with good prognosis in different kinds of HNSC patients. Additionally, TPPP3 may regulate the occurrence and development of OSCC through the PALMD/PI3K pathway. TPPP3 methylation level in HNSC decreased. Finally, we found that TPPP3 genetic alteration was involved in TPPP3 mRNA expression change in HNSC.

Conclusion

TPPP3 functions as a tumour suppressor in OSCC and is associated with good prognosis in HNSC patients. TPPP3 can be used as a potential biomarker for prognosis and diagnosis of OSCC.

Clinical relevance

TPPP3 can be used as a potential biomarker for prognosis and diagnosis of OSCC in clinical practice.

Key words: Oral squamous cell carcinoma, prognosis, tubulin polymerisation promoting protein 3, tumour suppressor, proliferation, migration

Introduction

Oral squamous cell carcinoma (OSCC) is one of the most prevalent malignancy of the head and neck.1, 2, 3 OSCC has a high incidence worldwide, with an estimated 377,713 new cases in 2020, most of which were in Asia.4 Around 50% of OSCC patients are already in advanced stages when they are diagnosed. The prognosis of OSCC has not significantly improved.5, 6, 7, 8 Therefore it is of great significance to discover new diagnostic and prognostic markers for OSCC.

The tubulin polymerisation promoting proteins (TPPPs) family includes 3 members: TPPP1, TPPP2, and TPPP3.9 Studies have shown that TPPP3 may specifically bind to microtubules in vivo and in vitro and play an important role in promoting microtubule aggregation, mitosis, and cell proliferation.10 With the increase in research on TPPP3, more and more studies have shown that TPPP3 is closely related to the occurrence and development of tumours. Studies have shown that TPPP3 was upregulated in a variety of tumours and had carcinogenic effects, such as liver cancer,11 non–small-cell lung cancer,12 breast cancer,13 glioblastoma,14 colorectal cancer,15 and endometrial cancer.16 A recent study confirmed that overexpression of TPPP3 was associated with the colony formation, migration, and antiapoptosis ability of liver cancer cells.11 Besides, the expression of TPPP3 in glioblastoma was higher than that in normal brain tissue, and the higher the expression of TPPP3, the higher the grade of glioblastoma.14 In addition, upregulation of TPPP3 expression can enhance the migration, invasion, and proliferation ability of glioblastoma cells in vitro and reduce cell apoptosis.14 Furthermore, some researchers found that myeloid subpopulations (Tppp3+ monocytes) played a key role in the formation and development of the breast cancer metastatic microenvironment, which may be due to the promotion of angiogenesis by Anxa 1 and Anxa 2 by TPPP3+ monocytes, thus having a protumour effect.13 However, Su Q et al17 found that TPPP3 was significantly less expressed in nasopharyngeal carcinoma tissues and cells. Overexpression of TPPP3 can inhibit the proliferation and invasion of nasopharyngeal carcinoma cells, suggesting that TPPP3 may be an antitumour agent in nasopharyngeal carcinoma. This may be because TPPP3 protein can exhibit different biological functions in different types of tumours under different physiological conditions and genetic backgrounds. However, does TPPP3 play a carcinogenic or anticancer role in OSCC?

Our previous research has verified the low expression of TPPP3 protein in OSCC tissues through immunohistochemistry and western blot (WB).18 This research group will further verify the expression level of TPPP3 mRNA or protein in OSCC tissues and cells and its impact on the biological functions of OSCC, as well as explore the role of TPPP3 in the occurrence and development of OSCC, so as to lay the foundation for discovering a new diagnostic and prognostic biomarker of OSCC.

Material and methods

The University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) and Gene Expression Profiling Interactive Analysis (GEPIA)

UALCAN is a comprehensive, user-friendly, and interactive web resource for analysing cancer OMICS data. It is built on PERL-CGI with high-quality graphics using JavaScript and CSS.19,20 UALCAN also provides a protein expression analysis option using data from Clinical Proteomic Tumor Analysis Consortium and the International Cancer Proteogenome Consortium datasets.21, 22, 23 We used UALCAN to evaluate the expression levels of proteins and methylation level of TPPP3 in head and neck squamous cell carcinoma (HNSC). GEPIA is a newly developed interactive web server for analysing the RNA sequencing expression data of 9736 tumours and 8587 normal samples from The Cancer Genome Atlas (TCGA) and the GTEx projects, using a standard processing pipeline.24 GEPIA provides customisable functions such as profiling according to pathological stages and so on.24

Quantitative real-time PCR

In total, 45 OSCC and adjacent normal oral mucosal tissues were provided by the Department of Oral and Maxillofacial Surgery (Xiangya Stomatological Hospital, Central South University). CAL27 and HN30 cell lines were obtained from the central laboratory of Xiangya Stomatological Hospital. RNA extraction reagent, chloroform, isopropyl alcohol, and 75% ethanol were added to tissues or cells in sequence to extract total RNA. RNA purity and concentration were analysed with an ultraviolet spectrophotometer. Reversing transcription into cDNA and quantitative real-time PCR (qRT-PCR) experiments were performed according to the instructions of the HiScript II Q RT SuperMix for qPCR (+gDNA wiper) kit and ChamQ Universal SYBR qPCR Master Mix kit. A fluorescence quantitative PCR instrument (Thermo Fisher) was used for qRT-PCR. After the completion of the qRT-PCR reaction, the relative expression of TPPP3 mRNA was calculated with the 2-ΔΔCt method with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as the reference gene. The TPPP3 and GAPDH primer sequences were designed through the NCBI website and synthesised by Shanghai Sangon Bioengineering Co., Ltd. This study was approved by the Medical Ethics Committee of Xiangya Stomatological Hospital, Central South University (20210045). The patients’ medical records were reviewed, and we ensured that identities were protected. Written informed consent was obtained from all participating adults and from parents or legal guardians for minors or incapacitated adults.

Western blot

The mixed system was made according to the following ratio: radioimmunoprecipitation assay lysate and protease inhibitor phenylmethanesulfonyl fluoride = 100:1. After adding an appropriate amount of mixed system to tissue or cell culture dish for 30 minutes, the total protein was extracted by centrifugation. The concentration of the protein sample was detected using a bicinchoninic acid kit. The protein sample concentration was normalised by adding the loading buffer, and the protein was denatured by boiling it under 99°C for 10 minutes. Then, 5% concentrated gel and 12% separation gel were prepared according to the molecular weight of the target protein TPPP3. Electrophoresis was performed at 90 V for 30 minutes, then at 120 V for 60 minutes, and stopped when bromophenol blue crossed the bottom of the gel. Then the sandwich structure was made and put into the transfer slot, and the film was transferred under the constant current of 200 mA for 60 minutes. The polyvinylidene fluoride membrane was taken out to seal for 60 minutes at room temperature, and the first antibody (diluted ratio of TPPP3 antibody was 1:1000) was added and incubated overnight at 4°C. Then, sheep antirabbit IgG H&L was added to incubate for 60 minutes. Enhanced chemiluminescence developer was prepared and developed in a chemiluminescence image analysis system (Shanghai Tianneng Technology), and the images of protein bands were recorded. The grey value and relative expression of protein bands were analysed and calculated using GraphPad Prism 9.3, Adobe Photoshop 2021, and Image J v1.8.0 software.

Plasmid transfection in vitro

The cells were digested, resuspended, and counted, then diluted to an appropriate concentration and seeded into a 6-well culture plate. Then, 1 hour before transfection, the culture plate was washed with PBS buffer 2 times, and 1.5 mL DMEM was added to each well, following which the 6-hole culture plate was cultured in a constant temperature incubator. After mixing Opti-MEM with Lipofectamine 3000 transfection reagent, the mixture was incubated at room temperature for 5 minutes. After mixing Opti-MEM with plasmid DNA and P3000 reagent, the mixture was incubated for 5 minutes at room temperature. Then, the above two mixtures were mixed and incubated at room temperature for 10 to 15 minutes. After the completion of incubation, the transfection mixture was evenly drawn and added to the wells of the 6-hole culture plate, mixed, and placed in a constant temperature incubator. The TPPP3 overexpression plasmid and negative control plasmids were obtained from Shanghai Genechem Co., Ltd.

CCK-8 and cell scratch assay

CCK-8 experiment was used to detect the effect of TPPP3 on the proliferation ability of OSCC cells. The cells were digested with trypsin, resuspended and counted, diluted with complete culture medium to 20,000 cells/mL, and then seeded into a 96-well plate. In total, 2000 cells were inoculated in each well, and five multiple wells were set up in each group. The 96-well plate was cultured in a constant-temperature incubator. After 0 hours, 12 hours, 24 hours, 48 hours, and 72 hours of culture, 10 μL CCK8 reagent was added to each well. Then the 96-well plate was incubated in a constant temperature incubator to avoid light for 2 hours. Finally, the absorbance of each well was detected using an enzyme-labelling instrument under 450 nm.

Cell scratch assay was used to detect the effect of TPPP3 on the migration ability of OSCC cells. We drew horizontal lines on the bottom of the 6-well plate, with a distance of 0.5 to 1 cm between every two lines. The cells in the logarithmic phase were digested with trypsin, resuspended and counted. Then the cells were diluted to a suitable density and inoculated to 6-well culture plates. We placed the culture plate in a constant-temperature incubator for 24 hours and scratched it after the cells at the bottom of the culture dish were full. After cleaning, we added the serum-free DMEM medium to the culture plates and put them into the constant temperature incubator. After 0 hours and 12 hours, the scratch distance of cells in each group was recorded with an inverted microscope under 100× magnification. ImageJ v1.8.0 software was used to measure the scratch areas of cells in each group at the same position at each time point. GraphPad Prism 9.3 was used for statistical analysis, and there was a statistically significant difference when P < .05.

Kaplan-Meier plotter and TIMER analysis

The Kaplan-Meier plotter can be used to evaluate the correlation between the expression of all genes (mRNA, miRNA, protein, and DNA) and survival in more than 35,000+ samples from 21 tumour types.25,26 Through the Kaplan-Meier plotter, we evaluated the relationships between the expression of genes and the prognosis of HNSC patients. TIMER is a comprehensive resource for the systematic analysis of tumour immunological, clinical, and genomic features comprehensively. Using TIMER 2.0, we explored the correlation between genes in HNSC.27, 28, 29

LinkedOmics and protein-protein interaction (PPI) network analysis

LinkedOmics is a publicly available portal that includes multiomics data from all 32 TCGA cancer types and 10 Clinical Proteomic Tumor Analysis Consortium cancer cohorts.30 By using LinkedOmics, we analysed the related coexpression genes of TPPP3 in HNSC.

STRING is a database of known and predicted protein-protein interactions. Interactions include direct (physical) and indirect (functional) associations; they arise from computational predictions, knowledge transfer between organisms, and interactions aggregated from other (primary) databases. Interactions in STRING are derived from five main sources: genomic context predictions, high-throughput laboratory experiments, (conserved) coexpression, automated text mining, and prior knowledge in databases. The STRING database currently covers 59,309,604 proteins from 12,535 organisms.31, 32, 33 Cytoscape is a software that focuses on open-source network analysis and visualisation. Its core objective is to provide a basic functional layout and query network and to build a protein-protein PPI network based on the combination of basic data into a visualisation network. After downloading the data from the STRING database, we used the plug-in Molecular Complex assay of Cytoscape software to identify the paramount modules in the PPI network (MCODE score > 5, Find Clusters = In Whole Network, Degree Cutoff  =  2, Max. Depth = 100, K-Core =  2, Node Score Cutoff  = 0.2).

cBioPortal analysis

cBioPortal for Cancer Genomics is a resource for interactively exploring multidimensional cancer genomics data sets.34 cBioPortal provides rapid, intuitive, and high-quality access to the molecular spectrum and clinical properties of large-scale cancer genomics projects.35,36 We used cBioPortal to explore the mutation of TPPP3 in HNSC.

Statistical analysis

The experimental data was analysed using SPSS23.0 or GraphPad Prism 9.3 software. The counting data was calculated by Fisher's exact probability method or chi-square test. A t test (nonparametric test) was used for two groups of measurement data, and one-way ANOVA (nonparametric test) was used for more than two groups of measurement data. All bioinformatics online tools automatically performed statistical analyses. P < .05 was considered significant.

Results

The expression level of TPPP3 in OSCC and the correlation between TPPP3 expression level and tumour stage

UALCAN analysis showed that the expression level of TPPP3 protein in HNSC was significantly lower than that in normal tissues (P < .0001, Figure 1A). In addition, we used qRT-PCR technology to detect the relative expression level of TPPP3 mRNA in OSCC (n = 45) and adjacent normal oral mucosal tissues (n = 45). The results showed that the expression level of TPPP3 mRNA in OSCC tissues was significantly lower than that in adjacent normal oral mucosal tissues (P < .01, Figure 1B). Furthermore, to explore TPPP3 mRNA and protein expression levels in OSCC cell lines, WB and qRT-PCR were used to detect the expression levels of TPPP3 in human OSCC cell lines and HACAT cell line. The results showed that the relative expression levels of TPPP3 protein in OSCC cell lines were significantly lower than that in the HACAT cell line (P < .05, Figure 1C). Besides, the relative expression levels of TPPP3 mRNA in OSCC cell lines were significantly lower than that in the HACAT cell line, and the difference was statistically significant (P < .0001, Figure 1D). Subsequently, we evaluated the expression of TPPP3 in different stages of HNSC. The results showed that the expression level of TPPP3 in stage IV was predominantly lower than that in stages I, II and III. The expression levels of TPPP3 in stage IVC and stage IVB were predominantly lower than those in stage IVA (Figure 1E). The results showed that the expression level of TPPP3 may be related to the tumour stage in HNSC.

Fig. 1.

Fig 1

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A, The expression of TPPP3 protein was significantly decreased in HNSC. CPTAC, Clinical Proteomic Tumor Analysis Consortium datasets. B, Using qRT-PCR to study TPPP3 mRNA expression levels in 45 OSCC and adjacent normal oral mucosal tissues; **P < .01. C, Relative expression levels of TPPP3 protein in HN30, CAL27, H157, SCC9, and HACAT cell lines; *P < .05; **P < .01; ***P < .001. D, Relative expression levels of TPPP3 mRNA in HN30, CAL27, H157, SCC9, and HACAT cell lines; ****P < .0001. E, TPPP3 expression levels at different stages of HNSC.

Expression of the fluorescent protein and verification of the overexpression of TPPP3 by WB and qRT-PCR after plasmid transfection in vitro

We used TPPP3 overexpression plasmid and negative control plasmid to transfect CAL27 and HN30 cells, respectively, as overexpression experimental groups (CAL27-TPPP3, HN30-TPPP3) and negative control groups (CAL27-NC, HN30-NC). The cell groups without in vitro plasmid transfection were used as the blank control groups (CAL27, HN30). After transfection of plasmid in vitro for 24 hours, DMi8 inverted fluorescence microscope was used to observe the efficiency of green fluorescent protein in cells and take pictures. The results showed that strong fluorescence could be observed in the overexpression experimental group and negative control group (Figure 2). Besides, through WB and qRT-PCR, the results showed that the expression levels of TPPP3 mRNA and protein in the CAL27-TPPP3 group were significantly higher than those in the CAL27-NC group and CAL27 group (P < .05, Figure 3A and C). Compared with the HN30 group and HN30-NC group, the expression level of TPPP3 mRNA in the HN30-TPPP3 group also increased (Figure 3B). In addition, the expression level of TPPP3 protein in the HN30-TPPP3 group was significantly higher than that in the HN30-NC group and HN30 group (P < .001, Figure 3D).

Fig. 2.

Fig 2

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Fluorescence and white light images (100×) after 24 hours of plasmid transfection under an inverted fluorescence microscope of different groups.

Fig. 3.

Fig 3

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Verification of the overexpression of TPPP3 at mRNA and protein levels. A, Expression levels of TPPP3 mRNA in CAL27-TPPP3, CAL27-NC, and CAL27 groups; *P < .05; **P < .01. B, Expression levels of TPPP3 mRNA in HN30-TPPP3, HN30-NC, and HN30 groups; ns P > .05. C, Expression levels of TPPP3 protein in CAL27-TPPP3, CAL27-NC, and CAL27 groups; *P < .05; **P < .01. D, Expression levels of TPPP3 protein in HN30-TPPP3, HN30-NC, and HN30 groups; ***P < .001; ****P < .0001.

The overexpression of TPPP3 significantly inhibited the proliferation and migration of OSCC cells

CCK-8 was used to detect the effect of TPPP3 expression on the proliferation of OSCC cells. The results showed that there was no significant difference in optical density value between the CAL27-TPPP3 group and CAL27-NC group at 0 hours. In the CAL27-TPPP3 group, the proliferation of cells was significantly inhibited at 12 hours, 24 hours, 48 hours, and 72 hours (Figure 4A). There was no significant difference in optical density value between the HN30-TPPP3 group and HN30-NC group at 0 hours and 12 hours, but the HN30-TPPP3 group cell proliferation was significantly inhibited at 24 hours, 48 hours, and 72 hours (Figure 4B). The results showed that TPPP3 could regulate the proliferation of OSCC cells, and the overexpression of TPPP3 could significantly inhibit the proliferation of OSCC cells. Next, cell scratch test was used to detect the effect of TPPP3 on the migration ability of OSCC cells. The results showed that after 12 hours of scratch treatment, the cell migration rate in the CAL27-TPPP3 group was significantly lower than that in the CAL27-NC group and CAL27 group (P < .0001, Figure 5A and C). 12 hours after scratch treatment, the cell migration rate in the HN30-TPPP3 group was significantly lower than that in the HN30 group (P < .05, Figure 5B and D). The results showed that TPPP3 could regulate the migration of OSCC cells, and the overexpression of TPPP3 could significantly inhibit the migration ability of OSCC cells (Figure 5).

Fig. 4.

Fig 4

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CCK-8 assay detecting the ability of cell proliferation in (A) CAL27-TPPP3, CAL27-NC, and CAL27 groups, and (B) HN30-TPPP3, HN30-NC, and HN30 groups; ns P > .05; *P < .05; **P < .01; ***P < .001; ****P < .0001.

Fig. 5.

Fig 5

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Wound healing test was used to detect the cell migration ability of (A, C) CAL27-TPPP3, CAL27-NC, and CAL27 groups, and (B, D) HN30-TPPP3, HN30-NC, and HN30 groups (100×); ns P > .05; *P < .05; ****P < .0001.

The relationship between TPPP3 expression and prognosis of different kinds of HNSC patients

Next, we evaluated the correlation between TPPP3 expression and survival of different kinds of HNSC patients. We used the Kaplan-Meier plotter to explore the relationships between TPPP3 expression and overall survival of HNSC patients with different genders, stages, grades, mutation burden, and neoantigen loads. The results showed that high TPPP3 expression is significantly correlated with good prognosis in male (hazard ratio [HR] = 0.68, log-rank P = 0.022), female (HR = 0.45, log-rank P = 0.0019), grade 2 (HR = 0.65, log-rank P = 0.015), grade 3 (HR = 0.44, log-rank P = 0.0022), stage 2 (HR = 0.42, log-rank P = 0.05), stage 3 (HR = 1.92, log-rank P = 0.095), stage 4 (HR = 0.6, log-rank P = 0.0047), high mutation burden (HR = 0.57, log-rank P = 0.0023), and high neoantigen load HNSC patients (HR = 0.57, log-rank P = 0.0018) (Figure 6A-I).

Fig. 6.

Fig 6

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The correlations between TPPP3 expression and prognosis of HNSC patients with different genders, stages, grades, mutation burden, and neoantigen loads. The relationships between TPPP3 expression and prognosis of (A) male HNSC patients, (B) female HNSC patients, (C-D) grade 2-3 HNSC patients, (E-G) stage 2-4 HNSC patients, (H) high mutation burden HNSC patients, and (I) high neoantigen load HNSC patients. HR, hazard ratio.

Related coexpression genes of TPPP3 and the establishment of PPI networks in HNSC

The mRNA sequences of 520 patients with TCGA HNSC were analysed using the functional module method. From the volcano map, it can be seen that the number of genes positively correlated with TPPP3 was more than that negatively correlated with TPPP3 (Figure 7A). Figure 7B and C show the first 50 genes with positive and negative relations to TPPP3. Besides, the results showed that TPPP3 showed strong positive relationships with insulin-like growth factor binding protein 6 (IGFBP6, Pearson correlation = 0.5434, P = 2.752E-41), family with sequence similarity 25 member B (FAM25B, Pearson correlation  =  0.4677, P  =  1.282E-29), family with sequence similarity 25 member A (FAM25A, Pearson correlation  =  0.4532, P = 1.045E-27), hes family bHLH transcription factor 5 (HES5, Pearson correlation  = 0.4452, P =  1.119E-26), and palmdelphin (PALMD, Pearson correlation  = 0.4311, P  =  6.086E-25) (Figure 7D-H). Next, we found that PALMD was significantly less expressed in HNSC using UALCAN (P < .001). Same as TPPP3, through the Kaplan-Meier plotter, the results showed that high expression of PALMD was associated with good prognosis of HNSC patients (P < .0001). In addition, our research results indicated that PI3K was significantly positively related to PALMD, and PI3K high expression was related to good prognosis of HNSC by TIMER and Kaplan-Meier plotter (P < .01). These findings suggested that TPPP3 may inhibit the proliferation and migration of OSCC cells through the PALMD/PI3K pathway (Figure 7I-L).

Fig. 7.

Fig 7

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A, Volcano plot of coexpressed genes related to TPPP3. B, Heat map of coexpressed genes significantly positively related to TPPP3. C, Heat map of coexpressed genes significantly negatively related to TPPP3. D, The Pearson correlation coefficient between TPPP3 and IGFBP6. E, The Pearson correlation coefficient between TPPP3 and FAM25B. F, The Pearson correlation coefficient between TPPP3 and FAM25A. G, The Pearson correlation coefficient between TPPP3 and HES5. H, The Pearson correlation coefficient between TPPP3 and PALMD. I, The expression of PALMD protein was significantly decreased in HNSC. J, The correlation between PALMD expression and prognosis of HNSC patients. K, The correlation between PALMD and PI3K in HNSC. L, The correlation between PI3K expression and prognosis of HNSC patients.

Subsequently, the PPI network map of TPPP3 was constructed by STRING. Complex network graphs represent the data of protein-protein interactions, in which nodes correspond to proteins and edges represent protein-protein interactions. Even antagonistic proteins may be functionally related, such as activators and inhibitors in the pathway. (Figure 8A). The PPI network formed by each gene was analysed using Cytoscape software, and the first 5 genes most associated with other nodes were THBS3, CCDC153, SCGB3A2, RSPH1, and PIFO (Figure 8B). These findings will help to elucidate the pathogenesis of HNSC and identify prognostic and therapeutic biomarkers.

Fig. 8.

Fig 8

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A, The PPI network map of TPPP3 constructed by STRING. Complex network graphs represent the data of protein-protein interactions, in which nodes correspond to proteins and edges represent protein-protein interactions. B, The PPI network formed by each gene was analysed by Cytoscape software. C, Analysis of the promoter methylation level of TPPP3 in HNSC by UALCAN. D, The mutation frequencies of TPPP3 in different datasets of HNSC. E, The relationship between TPPP3 mRNA expression and genetic alteration of TPPP3 in HNSC. F, The mutation site in TPPP3 gene in HNSC. G, The frequency and types of TPPP3 alteration in HNSC.

Analysis of promoter methylation level of TPPP3 in HNSC

DNA methylation can affect the occurrence and progression of cancer.37 We explored the DNA methylation of TPPP3 using the UALCAN database, and the results showed that the level of TPPP3 methylation in HNSC tissues decreased compared with normal tissues (Figure 8C).

TPPP3 mutation analysis

We analysed the TPPP3 gene mutations and CNAs of HNSC and OSCC samples from 6 datasets by using the cBioPortal database. The results showed that there was one mutation site in the TPPP3 gene (Figure 8F). In addition, TPPP3 has different mutation frequencies in different datasets, with the gene altered in 1.08% of 279 cases (TCGA, Nature 2015), 0.94% of 530 cases (TCGA, Firehose Legacy), and 0.57% of 523 cases (TCGA, PanCancer Atlas) (Figure 8D). Besides, based on the sequencing data of HNSC patients in the TCGA database, we used cBioPortal to determine the frequency and type of TPPP3 alterations in HNSC. The results showed that the frequency of TPPP3 changes in HNSC was 0.7% (of the 1476 HNSC patients, 11 had TPPP3 changes) (Figure 8G). These mutations included 8 cases of amplification, 2 cases of missense mutation, and 1 case of deep deletion, so amplification was the most common type of TPPP3 mutation in HNSC (Figure 8G). Then, we searched the TPPP3 expression data of the HNSC dataset (TCGA, PanCancer Atlas) and found that TPPP3 was gained along with high mRNA expression (Figure 8E). These results suggested that genetic alteration of TPPP3 in HNSC was involved in the change of TPPP3 mRNA expression, which is worthy of further study.

Discussion

Multiple studies showed that TPPP3 was upregulated in a variety of tumours and has carcinogenic effects, such as liver cancer,11 non–small-cell lung cancer,12 breast cancer,13 glioblastoma,14 colorectal cancer,15 and endometrial cancer.16 A recent study confirmed that overexpression of TPPP3 was associated with colony formation, migration, and antiapoptosis ability of liver cancer cells.11 Besides, the expression of TPPP3 in glioblastoma was higher than that in normal brain tissue, and the higher the expression of TPPP3, the higher the grade of glioblastoma.14 In addition, upregulation of TPPP3 expression can enhance the migration, invasion, and proliferation ability of glioblastoma cells in vitro and reduce cell apoptosis.14 In contrast to these findings, our research demonstrated that TPPP3 played a tumour suppressor role in OSCC.

Since OSCC accounts for more than 60% of HNSC cases in the TCGA database, the conclusions in HNSC have a high reference value for OSCC. This study found that the expression level of TPPP3 protein in HNSC was significantly decreased through bioinformatics analysis. Furthermore, we confirmed that TPPP3 was significantly less expressed in OSCC tissues and cells through WB and qRT-PCR. Therefore we further conducted cell biofunctional experiments, and the results suggested that TPPP3 could significantly inhibit the proliferation and migration of OSCC cells. To conclude, TPPP3 functions as a tumour suppressor in OSCC and TPPP3 can be used as a potential diagnostic biomarker for OSCC.

Previous studies found that TPPP3 high expression was associated with poor prognosis of patients with non–small-cell lung carcinoma, with shorter overall survival and disease-free survival.12 In addition, glioblastoma patients with high expression levels of TPPP3 had worse overall survival and disease-free survival.38 Nevertheless, our research group found that high expression of TPPP3 was significantly associated with good prognosis of HNSC patients.18 Our study further confirmed that high expression of TPPP3 was significantly associated with good prognosis of male, female, grade 2-3, stage 2-4, high mutation burden, and high neoantigen load HNSC patients. Previous research showed that high expression of TPPP3 was positively correlated with tumour stage in non–small-cell lung cancer.39 In contrast, we found that TPPP3 high expression was negatively correlated with tumour stage in HNSC, which suggests that high TPPP3 expression may be related to good prognosis of HNSC. Together, these findings highlighted that TPPP3 can be used as a potential diagnostic and prognostic biomarker for HNSC.

Next, we analysed the co-expressed genes most related to TPPP3. The results showed that PALMD was significantly positively correlated with TPPP3. Besides, PALMD was significantly less expressed in HNSC. Similar to TPPP3, the high expression of PALMD was associated with good prognosis in HNSC patients. The results suggested that TPPP3 may be involved in the occurrence and development of HNSC through PALMD. Previous research found that PALMD was downregulated in ovarian cancer, and PALMD overexpression inhibited the proliferation and migration of ovarian cancer cells.40 In addition, the overexpression of PALMD inhibited breast cancer cell proliferation by suppressing the PI3K/Akt pathway.41 In addition, our research results indicated that PI3K was significantly positively related to PALMD, and PI3K high expression was related to good prognosis of HNSC patients. These findings suggested that TPPP3 may inhibit the proliferation and migration of OSCC cells through the PALMD/PI3K pathway.

Some studies have shown that abnormal DNA methylation changes are associated with a variety of diseases such as cancer, mental illness, hypertension, and autoimmune diseases.37,42, 43, 44 Hypermethylation and hypomethylation are both the main causes of tumorigenesis, and reviewing methylation profiles could help in cancer detection and treatment.37,45 Therefore the methylation level of TPPP3 in OSCC needs further study. Our research found that TPPP3 methylation level in HNSC decreased, which may affect the occurrence and progression of HNSC. We further explored the mutation status of TPPP3 for HNSC. The results showed that the frequency of TPPP3 changes in HNSC was 0.7% and amplification was the most common type of TPPP3 mutation in HNSC. Besides, we found that there was one mutation site (D140N) in the TPPP3 gene and TPPP3 was gained along with high mRNA expression. These findings suggested that TPPP3 genetic alteration was involved in TPPP3 mRNA expression change, which is worthy of further study.

In summary, TPPP3 may become a molecular marker for OSCC proliferation and migration. TPPP3 functions as a tumour suppressor in OSCC, and TPPP3 high expression is associated with good prognosis in HNSC patients. TPPP3 can be used as a potential biomarker for the prognosis and diagnosis of OSCC, providing a new research direction for genetic diagnosis and prognosis prediction of OSCC. However, our research lacks in vivo research and cellular experiments to validate molecular mechanisms, so we will further improve it in the future.

Conclusions

In conclusion, TPPP3 functions as a tumour suppressor in OSCC and is associated with good prognosis in HNSC patients. TPPP3 can be used as a potential biomarker for prognosis and diagnosis of OSCC.

Conflict of interest

None disclosed.

Acknowledgments

Acknowledgements

None.

Author contributions

Ting Xiao: Writing—Original Draft Preparation; Writing—Review and Editing; Conceptualisation. Omar Rahhal: Writing—Review and Editing; Conceptualisation. Liping Wang: Writing—Review and Editing; Conceptualisation. Zhiyuan Deng: Writing—Review and Editing; Conceptualisation. Ran Wang: Writing—Review and Editing; Conceptualisation. Xinghuanyu Xu: Writing—Review and Editing; Conceptualisation. Zhangui Tang: Methodology; Conceptualisation; Writing—Review and Editing. Lu Qi: Conceptualisation; Writing—Review and Editing. All authors have approved the final article.

Funding

This work was supported by the National Natural Science Foundation of China [grant number 82170972].

Ethics statement

All procedures were performed in compliance with relevant laws and institutional guidelines and have been approved by the Medical Ethics Committee of Xiangya Stomatology Hospital, Central South University (20210045). Informed consent was obtained for experimentation with human subjects. The privacy rights of human subjects must always be observed.

Contributor Information

Lu Qi, Email: kidd85215954@163.com.

Zhangui Tang, Email: tangzhangui@aliyun.com.

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