Expression of periostin in potentially premalignant oral epithelial lesions and oral squamous cell carcinoma using qRT-PCR: A comparative study

Abstract

Background:

Oral squamous cell carcinoma (OSCC) accounts for over 90% of oral cavity malignancies, with the high mortality and limited therapeutic success due to challenges in early diagnosis. Periostin, a matricellular protein, is implicated in cancer progression, making it a potential diagnostic and therapeutic target. This study examines periostin expression in normal tissues, potentially premalignant oral epithelial lesions (PPOEL), and OSCC.

Aim:

To evaluate and compare periostin expression in normal tissues, PPOEL, and OSCC stage I/stage II and stage III/IV using quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR).

Materials and Methods:

This ex vivo comparative study included 80 subjects divided into four groups (20 per group): healthy controls, PPOEL, OSCC Stage I/II, and OSCC Stage III/IV. Ethical clearance and informed consent were obtained. Peripheral blood samples were processed for RNA extraction, quantified using Nanodrop spectrophotometry, and analysed via qRT-PCR for periostin and GAPDH (housekeeping gene).

Statistical Analysis:

Data normalcy was tested using the Shapiro-Wilk test. Parametric (ANOVA, post-hoc Bonferroni) and non-parametric (Mann-Whitney, Wilcoxon) tests were applied depending on data distribution. SPSS version 21 was used for analysis.

Results:

Periostin expression increased progressively from normal tissues to PPOEL, OSCC Stage I/II, and OSCC Stage III/IV. Significant differences in ΔΔCT and fold change values were observed between normal and OSCC stages, with advanced OSCC showing the highest periostin expression. However, differences between normal and PPOEL were not statistically significant.

Conclusion:

Periostin expression correlates with OSCC progression, highlighting its potential as a biomarker for early diagnosis and as a therapeutic target. Further large-scale studies are required to validate these findings.

INTRODUCTION

Oral cancer is currently recognized as one of the leading causes of death, particularly in developing countries where the incidence is rising with 77,003 new cases (Globacon 2012). The high mortality and morbidity associated with oral cancer are largely due to challenges in achieving prompt diagnosis and effective management.[1] Oral squamous cell carcinoma (OSCC) represents over 90% of all oral cavity malignancies, oral cancer is a significant contributor to global cancer mortality, with approximately 177,000 deaths reported annually. Oral cancer is known for its aggressive nature, with an overall 5-year survival rate of about 50%, which further decreases to less than 30% in advanced stages.[2]

The pathogenesis of OSCC is complex, involving multiple stages and various regulatory factors.[3] Despite extensive research, the molecular mechanisms driving this cancer remain poorly understood. Gaining insights into these mechanisms is crucial for identifying biomarkers specific to tumours that may aid as potential therapeutic targets, to improve overall early diagnosis and treatment outcomes.[4]

Periostin, a secreted protein with structural similarities to the axon guidance protein fasciclin I (FAS1) found in insects, was initially identified as osteoblast-specific factor-2 (Osf2). It shares significant homology with ßig-h3, a protein known to promote fibroblast adhesion and spreading. Recent studies have shown that Periostin is frequently overexpressed in various human cancers. Although its exact functions are not fully understood, it is believed that Periostin interacts with integrins through its FAS1 domain, playing a role in tumour development. Additionally, Periostin appears to support metastatic growth by enhancing cancer cell survival, invasion, and angiogenesis. As a result, Periostin is potential as a biomarker for predicting cancer progression.[5]

This study delves into the expression of serum periostin across normal tissues, Potentially premalignant oral epithelial lesions (PPOEL), and OSCC, exploring its relationship with clinical characteristics. The findings highlight periostin as a promising diagnostic marker and a potential therapeutic target for OSCC, paving the way for more precise and effective cancer treatments.

MATERIALS AND METHODS

Source of data

Peripheral Blood samples were collected from the Department of Oral Pathology and Microbiology, Government Dental College and Research Institute, Bangalore.

Ethical clearance for this study was obtained from the Institutional Ethical Committee, GDC and RI, Bangalore [GDCRI/IEC-ACM (2)/15/2022-23].

This is an ex vivo comparative study with four balanced arms. 20 subjects as per the selection criteria were selected by purposive sampling technique. The subjects were categorized into four groups as follows:

• Group I: 20 Normal Healthy Individuals (control).

• Group II: 20 subjects with potentially premalignant oral epithelial lesions (PPOEL).

• Group III: 20 subjects with oral squamous cell carcinoma.(Stage I and II).

• Group IV: 20 subjects with oral squamous cell carcinoma. (Stage III and IV).

Inclusion criteria

• Gender: Both male and female

• Age group: 30–75 years

• Subjects with histopathologically diagnosed and untreated cases of OSCC (Stage I and II), untreated cases of Oral squamous cell carcinoma (Stage III and IV) and histopathologically diagnosed and untreated cases of PPOEL.

• Control group with healthy individuals without any habit.

• Subjects willing to give informed consent spontaneously were included.

Exclusion criteria

• Previous radiotherapy or chemotherapy.

• Controls with systemic and periodontal disease.

Methodology

• Before initiating the study, written consent was obtained from all participants after the procedure was explained to them in their native language.

• Sample Collection: Peripheral blood samples (5 mL) were collected from participants with PPOELS, OSCC [Figure 1a], and healthy controls in EDTA-filled vacutainer tubes. The samples were centrifuged to isolate the serum [Figure 1b], which was then transferred into 1.5 mL Eppendorf tubes [Figure 1c] and stored at –80°C after adding 1 mL of TRIzol [Figure 1d].

• RNA Extraction: The stored samples were thawed, 200 µL of chloroform was added to each sample and vortexed and kept at room temperature. After centrifugation 10,000 rpm for 15 min at 4°C, results in three layers namely upper aqueous (RNA) middle turbid white layer (coagulated proteins) bottom layer (TRIzol reagent) [Figure 2].

Figure 1.

(a) Sample Collection. (b) Centrifugation. (c) Serum in Eppendorf tube. (d) Storage of samples in –80°C

Figure 2.

Three phases formed viz. aqueus phase, interphase, organic phase

The upper aqueous layer was carefully transferred to a new centrifuge tube, after adding an equal volume of isopropanol and 1 µL of 20 mg/mL glycogen, samples were centrifuged at 15,000 rpm for 30 min at 4°C, forming a pellet at the bottom of the tube. The supernatant was discarded without disturbing the pellet [Figure 3a] and pellet is diluted with DEPC water [Figure 3b].

Figure 3.

(a) Pellet formation. (b) Pellet dilution with deep water. (c) RNA quantification with nanodrop spectrophotometer

• RNA Quantification: RNA quantification was performed using a Nanodrop spectrophotometer [Figure 3c].

• cDNA Synthesis: cDNA synthesis was carried out using a commercial cDNA synthesis kit, following the manufacturer’s protocol.

• qRT-PCR Setup: Primer sequences for GAPDH (housekeeping gene) and Periostin (gene of interest) were standardized using NCBI Primer-BLAST, and the sequences were obtained commercially. A 96-well plate was loaded with the following components per well:

  • 5 µL SYBR Green + 2 µL cDNA + 1 µL Primer + 2 µL Nuclease-free water.

  • The 96 wellplate was loaded [Figure 4a]. Amplification plot displayed [Figure 4b] and CT values were recorded following a standard qRT PCR run.

Figure 4.

(a) PCR set up with 96 well plate. (b) Amplification plot

Statistical analysis

SPSS (Statistical Package for Social Sciences) version 21. (IBM SPASS statistics [IBM corporation: NY, USA]) was used to perform the statistical analysis.

• Data was entered in the excel spread sheet.

• Descriptive statistics of the explanatory and outcome variables were calculated by mean, standard deviation/median and IQR (Inter-Quartile Range) for quantitative variables.

• Inferential statistics like:

  • Analysis of Variance (ANOVA) test/Kruskal-Wallis’s test (based on data distribution) was applied to compare the mean quantitative parameters among the groups with post-hoc Bonferroni/Mann-Whitney test (based on data distribution) for inter group comparison.

• The level of significance is set at 5%

RESULTS

'The Shapiro–Wilk test is more appropriate method for small sample sizes (<50 samples) although it can also be handling on larger sample size while Kolmogorov–Smirnov test is used for n ≥ 50. For both above tests, null hypothesis states that data are taken from normal distributed population. If the P value of the Shapiro–Wilk Test is greater than 0.05, the data is normal. If it is below 0.05, the data significantly deviate from a normal distribution [Table 1].

Table 1.

Kolmogorov-Smirnov and Shapiro-Wilk test applied for Normal, PPOEL, OSCC Stage I and II and OSCC Stage III and IV group

Groups		Kolmogorov-Smirnova			Shapiro-Wilk
		Statistic	df	P	Statistic	df	P
Normal	GAPDH CT	0.152	20	0.200*	0.925	20	0.121
	PERIOSTIN CT	0.156	20	0.200*	0.942	20	0.259
	ΔCT	0.224	20	0.010	0.841	20	0.004
PPOEL	GAPDH CT	0.110	20	0.200*	0.976	20	0.880
	PERIOSTIN CT	0.141	20	0.200*	0.963	20	0.595
	ΔCT	0.195	20	0.045	0.920	20	0.100
	ΔΔCT	0.195	20	0.045	0.920	20	0.100
	FOLD INCREASE	0.151	20	0.200*	0.847	20	0.005
OSCC STAGE I and II	GAPDH CT	0.091	20	0.200*	0.975	20	0.849
	PERIOSTIN CT	0.129	20	0.200*	0.895	20	0.033
	ΔCT	0.176	20	0.103	0.923	20	0.111
	ΔΔCT	0.176	20	0.103	0.923	20	0.111
	FOLD INCREASE	0.221	20	0.012	0.859	20	0.008
OSCC STAGE III and IV	GAPDH CT	0.124	20	0.200*	0.929	20	0.148
	PERIOSTIN CT	0.137	20	0.200*	0.961	20	0.569
	ΔCT	0.113	20	0.200*	0.973	20	0.811
	ΔΔCT	0.113	20	0.200*	0.973	20	0.811
	FOLD INCREASE	0.153	20	0.200*	0.876	20	0.015

PPOEL=Potentially premalignant oral epithelial lesions; OSCC=Oral squamous cell carcinoma

Data was subjected to Normalcy test (Shapiro Wilk test). GAPDH CT, ΔΔCT showed normal distribution. Hence Parametric tests (ANOVA with post hoc Bonferroni) were applied for these parameters [Tables 2 and 3]. Data (Delta CT, Fold increase, Periostin CT) showed skewed distribution. Hence non-parametric tests (Kruskal Wallis and Mann-whitney test) were applied for these parameters.[Tables 4 and 5].

Table 2.

Comparison of the mean GAPDH CT and ΔΔCT among the groups using ANOVA

GAPDH CT	Normal	23.038	26.869	25.350	1.073	0.001*
	PPOEL	22.289	26.493	24.406	1.139
	OSCC Stage I and II	21.801	26.001	24.242	1.022
	OSCC Stage III and IV	21.957	24.679	23.104	0.876
ΔΔCT	Normal	0.000	0.000	0.000	0.000	0.001*
	PPOEL	–2.925	3.606	–0.250	1.724
	OSCC Stage I and II	–2.933	–0.066	–1.624	0.899
	OSCC Stage III and IV	–3.864	–0.451	–2.1618	0.8330

*Significant. PPOEL=Potentially premalignant oral epithelial lesions; OSCC=Oral squamous cell carcinoma

Table 3.

Inter-group comparison of GAPDH CT and ΔΔCT using post-hoc Bonferroni test

Normal vs. PPOEL	0.9445	0.030*	0.249575	1.000
Normal vs. OSCC Stage I and II	1.108	0.007*	1.624	0.001*
Normal vs. OSCC Stage III and IV	2.2459	0.001*	2.161	0.001*
PPOEL vs. OSCC Stage I and II	0.164000	1.000	1.374	0.001*
PPOEL vs. OSCC Stage III and IV	1.301	0.001*	1.912	0.001*
OSCC Stage I and II vs. OSCC Stage III and IV	1.1374	0.005*	0.537740	0.672

*Significant. PPOEL=Potentially premalignant oral epithelial lesions; OSCC=Oral squamous cell carcinoma

Table 4.

Comparison of the periostin CT, ΔCT and fold increase among the groups using Kruskal-Wallis

Parameters	Groups	Minimum	Maximum	Median	IQR	P
Periostin CT	Normal	31.234	35.882	34.076	1.881	0.001*
	PPOEL	29.068	37.817	32.098	3.430
	OSCC Stage I and II	27.429	32.819	31.232	1.327
	OSCC Stage III and IV	27.978	30.907	29.332	1.240
ΔCT	Normal	5.207	9.878	8.563	0.985	0.001*
	PPOEL	5.586	12.117	7.929	2.229
	OSCC Stage I and II	5.578	8.445	7.034	1.748
	OSCC Stage III and IV	4.647	8.060	6.335	1.114
Fold increase	Normal	-	-	-	-	0.001*
	PPOEL	0.082	7.595	1.497	2.305
	OSCC Stage I and II	1.047	7.637	2.785	4.158
	OSCC Stage III and IV	1.367	14.561	4.521	3.712

*Significant. PPOEL=Potentially premalignant oral epithelial lesions; OSCC=Oral squamous cell carcinoma

Table 5.

Inter-group comparison of periostin CT, ΔCT and fold increase using post-hoc Mann-Whitney test

	Periostin CT	ΔCT	Fold increase
Normal vs. PPOEL	0.049	0.149	0.108
Normal vs. OSCC Stage I and II	0.001*	0.001*	0.001*
Normal vs. OSCC Stage III and IV	0.001*	0.001*	0.001*
PPOEL vs. OSCC Stage I and II	0.038*	0.011*	0.11*
PPOEL vs. OSCC Stage III and IV	0.001*	0.001*	0.001*
OSCC Stage I and II vs. OSCC Stage III and IV	0.001*	0.076	0.076

*Significant. PPOEL=Potentially premalignant oral epithelial lesions; OSCC=Oral squamous cell carcinoma

GAPDH CT values

The Glyceraldehyde 3 Phosphate dehydrogenase (GAPDH) CT (cycle threshold) values varied significantly among the groups, as indicated by a P value of 0.001. The mean GAPDH CT for the normal group was the highest at 25.350 ± 1.073, followed by the PPOEL group (24.406 ± 1.139) and OSCC Stage I and II group (24.242 ± 1.022). The OSCC Stage III and IV group exhibited the lowest mean GAPDH CT at 23.104 ± 0.876. The decreasing trend in the mean values suggests a potential association between GAPDH CT levels and disease progression [Figure X].

Figure X.

Mean GAPDH CT among the groups

ΔΔCT values

For ΔΔCT, significant differences were also observed among the groups (P = 0.001). The normal group served as the baseline, with a mean ΔΔCT of 0.000. In contrast, the PPOEL group had a mean ΔΔCT of –0.250 ± 1.724, while the OSCC Stage I and II group showed a greater reduction with a mean of –1.624 ± 0.899. The OSCC Stage III and IV group exhibited the most pronounced reduction, with a mean ΔΔCT of –2.162 ± 0.833. These findings suggest a progressive decline in ΔΔCT with advancing disease stages [Figure Y].

Figure Y.

Mean Δ Δ CT among the groups

The analysis highlights significant differences in both GAPDH CT and ΔΔCT values across the groups. The trends observed in the means of these parameters may reflect the progression of OSCC (oral squamous cell carcinoma) stages and could be indicative of underlying molecular changes associated with disease severity.

Intergroup comparison [Table 3]

GAPDH CT

• Normal vs. PPOEL: The mean difference was 0.9445, with a P value of 0.030, indicating a statistically significant difference.

• Normal vs. OSCC Stage I and II: The mean difference was 1.108, with a P value of 0.007, showing a significant difference.

• Normal vs. OSCC Stage III and IV: The largest mean difference of 2.2459 was observed, with a P value of 0.001, signifying high significance.

• PPOEL vs. OSCC Stage I and II: The mean difference was 0.164, with a P value of 1.000, indicating no significant difference.

• PPOEL vs. OSCC Stage III and IV: The mean difference was 1.301, with a P value of 0.001, highlighting statistical significance.

• OSCC Stage I and II vs. OSCC Stage III and IV: The mean difference was 1.1374, with a P value of 0.005, confirming significance.

ΔΔCT

• Normal vs. PPOEL: The mean difference was 0.2496, with a P value of 1.000, indicating no significant difference.

• Normal vs. OSCC Stage I and II: The mean difference was 1.624, with a P value of 0.001, demonstrating significant variation.

• Normal vs. OSCC Stage III and IV: The mean difference was 2.161, with a P value of 0.001, indicating high significance.

• PPOEL vs. OSCC Stage I and II: The mean difference was 1.374, with a P value of 0.001, showing statistical significance.

• PPOEL vs. OSCC Stage III and IV: The mean difference was 1.912, with a P value of 0.001, also significant.

• OSCC Stage I and II vs. OSCC Stage III and IV: The mean difference was 0.5377, with a P value of 0.672, indicating no significant difference.

Significant differences in GAPDH CT and ΔΔCT were observed between the Normal group and advanced disease stages (OSCC Stage I and II, and OSCC Stage III and IV). GAPDH CT and ΔΔCT values for PPOEL showed significant differences compared to OSCC Stage III and IV but not OSCC Stage I and II for GAPDH CT. There was no significant difference in ΔΔCT values between OSCC Stage I and II and OSCC Stage III and IV, indicating similar expression profiles at these stages.

• Periostin CT: The median Periostin CT value decreased progressively from the Normal group (34.076, IQR: 1.881) to PPOEL (32.098, IQR: 3.430), OSCC Stage I and II (31.232, IQR: 1.327), and OSCC Stage III and IV (29.332, IQR: 1.240), indicating lower Periostin expression with disease progression [Figure Z].

• ΔCT: The median ΔCT value was highest in the Normal group (8.563, IQR: 0.985) and gradually declined through PPOEL (7.929, IQR: 2.229), OSCC Stage I and II (7.034, IQR: 1.748), and OSCC Stage III and IV (6.335, IQR: 1.114), reflecting increasing Periostin expression relative to GAPDH as the disease advanced [Figure A].

• Fold Increase: Fold increase values were not applicable for the Normal group but showed a progressive rise across PPOEL (median: 1.497, IQR: 2.305), OSCC Stage I and II (median: 2.785, IQR: 4.158), and OSCC Stage III and IV (median: 4.521, IQR: 3.712), with the highest median fold increase observed in OSCC Stage III and IV [Figure B].

Figure Z.

Periostin CT

Figure A.

Δ CT

Figure B.

Fold increase

These findings highlight a significant association between increasing Periostin expression and the progression from normal tissue through PPOEL to advanced OSCC stages, underscoring its potential role in disease pathogenesis and progression.

Intergroup comparison [Table 5]

The inter-group comparisons of Periostin CT, ΔCT, and fold increase using the post-hoc Mann-Whitney test. Significant differences were observed in Periostin CT and ΔCT values between Normal and advanced OSCC stages (Stage I and II and Stage III and IV; P = 0.001), as well as between PPOEL and OSCC Stage III and IV (P = 0.001). Similarly, fold increase significantly differed between Normal and OSCC stages (P = 0.001) and between PPOEL and OSCC Stage III and IV (P = 0.001). However, no significant differences were found for Periostin CT or fold increase between Normal and PPOEL (P = 0.049 and 0.108, respectively), or for ΔCT between OSCC Stage I and II and OSCC Stage III and IV (P = 0.076). These results highlight a progressive increase in Periostin expression with disease severity, with marked differences becoming evident between premalignant and malignant stages, particularly in advanced OSCC.

DISCUSSION

HNSCC ranks among the most common cancers, with OSCC accounting for about half of these cases.[4] The presence of metastasis to cervical lymph nodes is a key prognostic factor in patients with OSCC. Recent molecular research has laid the groundwork for new strategies in the early detection, prevention, and treatment of this disease. Identifying the genes that drive metastasis is crucial for predicting OSCC behaviour at an early stage.[6]

PPOELs include a variety of oral conditions, such as leukoplakia, erythroplakia, lichen planus, and oral submucous fibrosis.[7] Early detection and management of PPOELs could greatly enhance the success of secondary prevention of OSCC, thereby potentially reducing both morbidity and mortality.[8]

Periostin, also known as osteoblast-specific factor 2, is a matricellular protein involved in various aspects of cancer development and progression. The human Periostin gene is located on chromosome 13q13.3. This protein is overexpressed in several types of cancer, including prostate, lung, pancreatic, and breast cancers.[9] Emerging evidence suggests that Periostin could serve as a biomarker for malignant transformation and plays a crucial role in tumour growth, invasion, angiogenesis, and metastasis.[10]

In a study published by Siriwardena et al.[6] they examined the role of periostin in oral cancer. Immunohistochemical analysis was used to detect and quantify periostin in cancerous tissues compared to normal oral mucosa. The results demonstrated that periostin is frequently overexpressed in oral cancer tissues. Their findings revealed that periostin significantly contributes to both cancer invasion and angiogenesis and provides a pathway for metastasis. Our study results were consistent with this study showing increased expression of periostin in Stage III, IV OSCC than Stage I, II OSCC when compared to normal however there is no significant fold change seen in PPOEL and normal.

Another study by researchers Lv et al.,[9] who investigated the role of periostin in ESCC, they focused on the relationship between periostin expression and epithelial-mesenchymal transition (EMT), a process crucial for cancer progression and metastasis. The researchers analysed periostin levels in ESCC tissues and assessed their correlation with key indicators of EMT. Their findings revealed that elevated periostin expression is significantly associated with markers of EMT, suggesting that periostin may contribute to the invasive and metastatic behaviour of ESCC. Moreover, the study explored the clinical implications of periostin expression, noting its potential as a prognostic biomarker. High levels of periostin were linked to poorer clinical outcomes, including reduced overall survival and increased risk of metastasis. The results of our study align with those of this research, demonstrating higher serum periostin expression in Stage III and IV OSCC compared to Stage I and II OSCC, in relative to normal tissue but there was no significant difference between fold change in PPOEL and normal, this may implicate periostin plays an important role in EMT.

One more study that our research results can be compared was published by Kang et al.,[4] they investigated the role of periostin in the development of OSCC with IHC technique and found that periostin was significantly overexpressed in cancerous tissues compared to normal oral tissues. Additionally, the researchers noted a correlation between elevated periostin expression and poorer clinical outcomes in OSCC patients.

The other study, conducted by Toshimasa Okazaki and colleagues, explores the role of periostin in non-small cell lung cancer (NSCLC) and its potential as a prognostic factor. The study found that periostin expression was significantly higher in NSCLC tissues compared to normal lung tissues and they found a better prognosis for patients with low rather than high periostin, even in cases of advanced-stage cancer, as seen in our study that higher expression of periostin was seen with advanced stages of OSCC.[11]

A cohort study by Cattrini et al.[12] consisting of 48 patients with metastatic castration-resistant prostate cancer (mCRPC) using circulating tumour cells isolated from plasma samples were tested for Periostin, protein expression using a dot blot assay that resulted in mRNA overexpression in primary tumours. Also, higher Periostin plasma levels were positively correlated with androgen-receptor variant and were associated with shorter overall survival. Even these results are in accordance with our study where in overexpression of periostin was noted as the tumour progressed.

Given the overexpression of serum periostin in ascending order normal and PPOEL, Stage I/II OSCC, and Stage III/IV OSCC, periostin shows a promise as an early diagnostic marker, potentially reducing the need for invasive biopsies and as a therapeutic target in OSCC. However, further large-scale studies are essential to validate these findings.

CONCLUSION

In conclusion, this study provides valuable insights into the role of serum periostin in the context of PPOEL and OSCC. The research demonstrates that periostin expression is significantly elevated in OSCC, particularly in advanced Stages (III and IV), compared to earlier Stages (I and II) and PPOEL. This marked increase underscores the potential of periostin as a reliable diagnostic marker for distinguishing between different stages of cancer and as a prognostic tool for assessing disease progression. Additionally, the study suggests that periostin could be targeted for therapeutic strategies, offering a promising avenue for more effective treatment of OSCC. However, with more studies involving huge sample size, the findings advocate for the integration of periostin measurement into clinical practice to enhance diagnostic accuracy and therapeutic outcomes for patients with oral cancer.

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Funded by Rajiv Gandhi University of Health Sciences, Bangalore, Karnataka