Prognostic significance of cytoplasmic S100A2 overexpression in oral cancer patients

S100 proteins in head and neck squamous cell carcinoma (Review)

The most common tumor affecting the head and neck is head and neck squamous cell carcinoma (HNSCC). The characteristics of HNSCC include a rapid onset, a lack of early diagnosis, drug resistance, relapse and systemic adverse effects, leading to inadequate prevention, diagnosis and treatment. Notably, previous research suggests that there is an association between S100 proteins and HNSCC. S100A8, S100A9 and S100A14 interfere with tumor cell proliferation by blocking the cell cycle. The present review discusses this association. S100A4 enhances cancer stem cell properties, and interacts with actin and tropomyosin to promote tumor cell migration. S100A1, S100A8, S100A9, S100A10, S100A14 and S100P are involved in the initiation and progression of HNSCC via Hippo, nuclear factor κB, phosphatidylinositol kinase/protein kinase B/mammalian target of rapamycin and other signaling pathways. In addition, certain long non-coding RNAs and microRNAs are involved in regulating the expression of S100 proteins in HNSCC. Reducing the expression of certain members of the S100 protein family may enhance the chemosensitivity of HNSCC. Collectively, it is suggested that S100 proteins may function as markers and targets for the prevention, diagnosis and treatment of HNSCC.

Exploring the cellular and molecular differences between ovarian clear cell carcinoma and high-grade serous carcinoma using single-cell RNA sequencing and GEO gene expression signatures

The two most prevalent subtypes of epithelial ovarian carcinoma (EOC) are ovarian clear cell carcinoma (OCCC) and high-grade serous ovarian carcinoma (HGSC). Patients with OCCC have a poor prognosis than those with HGSC due to chemoresistance, implying the need for novel treatment target. In this study, we applied single-cell RNA sequencing (scRNA-seq) together with bulk RNA-seq data from the GEO (Gene Expression Omnibus) database (the GSE189553 dataset) to characterize and compare tumor heterogeneity and cell-level evolution between OCCC and HGSC samples. To begin, we found that the smaller proportion of an epithelial OCCC cell subset in the G2/M phase might explain OCCC chemoresistance. Second, we identified a possible pathogenic OCCC epithelial cell subcluster that overexpresses LEFTY1. Third, novel biomarkers separating OCCC from HGSC were discovered and subsequently validated on a wide scale using immunohistochemistry. Amine oxidase copper containing 1 (AOC1) was preferentially expressed in OCCC over HGSC, while S100 calcium-binding protein A2 (S100A2) was detected less frequently in OCCC than in HGSC. In addition, we discovered that metabolic pathways were enriched in the epithelial compartment of the OCCC samples. In vitro experiments verified that inhibition of oxidative phosphorylation or glycolysis pathways exerted direct antitumor effects on both OCCC and HGSC cells, while targeting glutamine metabolism or ferroptosis greatly attenuated chemosensitivity only in OCCC cells. Finally, to determine whether there were any variations in immune cell subsets between OCCC and HGSC, data from scRNA-seq and mass cytometry were pooled for analysis. In summary, our work provides the first holistic insights into the cellular and molecular distinctions between OCCC and HGSC and is a valuable source for discovering new targets to leverage in clinical treatments to improve the poor prognosis of patients with OCCC.

Protein expression of S100A2 reveals it association with patient prognosis and immune infiltration profile in colorectal cancer

PURPOSE

Colorectal cancer (CRC) is the third most diagnosed cancer worldwide. Despite a well-established knowledge of tumour development, biomarkers to predict patient outcomes are still required. S100 calcium-binding protein A2 (S100A2) has been purposed as a potential marker in many types of cancer, however, the prognostic value of S100A2 in CRC is rarely reported.

MATERIAL AND METHODS

In this study, immunohistochemistry (IHC) was performed to identify the prognostic role of S100A2 protein expression in the tumour core of the tissue microarrays (TMAs) in colorectal cancer patients (n=787). Bulk RNA transcriptomic data was used to identify significant genes compared between low and high cytoplasmic S100A2 groups. Multiplex immunofluorescence (mIF) was performed to further study and confirm the immune infiltration in tumours with low and high cytoplasmic S100A2.

RESULTS

Low cytoplasmic protein expression of S100A2 in the tumour core was associated with poor survival (HR 0.539, 95%CI 0.394-0.737, P<0.001) and other adverse tumour phenotypes. RNA transcriptomic analysis showed a gene significantly associated with the low cytoplasmic S100A2 group (AKT3, TAGLN, MYLK, FGD6 and ETFDH), which correlated with tumour development and progression. GSEA analysis identifies the enriched anti-tumour and immune activity group of genes in high cytoplasmic S100A2. Additionally, mIF staining showed that high CD3+FOXP3+ and CD163+ inversely associated with low cytoplasmic S100A2 (P<0.001, P=0.009 respectively).

CONCLUSION

Our finding demonstrates a prognostic value of S100A2 together with the correlation with immune infiltration in CRC.

Influence of S100A2 in Human Diseases

S100 proteins are a family of low-molecular-weight proteins characterized by two calcium-binding sites with a helix-loop-helix (“EF-hand-type”) domain. The S100 family of proteins is distributed across various organs and can interact with diverse molecules. Among the proteins of the S100 family, S100 calcium-binding protein A2 (S100A2) has been identified in mammary epithelial cells, glands, lungs, kidneys, and prostate gland, exhibiting various physiological and pathological actions in human disorders, such as inflammatory diseases and malignant tumors. In this review, we introduce basic knowledge regarding S100A2 regulatory mechanisms. Although S100A2 is a tumor suppressor, we describe the various influences of S100A2 on cancer and inflammatory diseases.

High expression of S100A2 predicts poor prognosis in patients with endometrial carcinoma

Background

S100A2, a member of the S100 protein family, is abnormally expressed and plays a vital role in multiple cancers. However, little is known about the clinical significance of S100A2 in endometrial carcinoma.

Methods

Clinicopathological data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO), and Clinical Proteomic Tumor Analysis Consortium (CPTAC). First, the expression and prognostic value of different S100 family members in endometrial carcinoma were evaluated. Subsequently, the Kaplan–Meier plotter and Cox regression analysis were used to assess the prognostic significance of S100A2, while the association between S100A2 expression and clinical characteristics in endometrial carcinoma was also analyzed using logistic regression. A receiver operating characteristic (ROC) curve and a nomogram were constructed. The putative underlying cellular mechanisms were explored using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene set enrichment analysis (GSEA).

Results

Our results revealed that S100A2 expression was significantly higher in endometrial carcinoma tissue than in non-cancerous tissue at both the mRNA and protein levels. Analysis of Kaplan–Meier plotter data revealed that patients with high S100A2 expression had shorter overall survival (OS) and disease specific survival (DSS) compared with those of patients with low S100A2 expression. Multivariate Cox analysis further confirmed that high S100A2 expression was an independent risk factor for OS in patients with endometrial carcinoma. Other clinicopathologic features found to be related to worse prognosis in endometrial carcinoma included age, clinical stage, histologic grade, and tumor invasion. Importantly, ROC analysis also confirmed that S100A2 has a high diagnostic value in endometrial carcinoma. KEGG enrichment analysis and GSEA revealed that the estrogen and IL-17 signaling pathways were significantly upregulated in the high S100A2 expression group, in which estrogen response, JAK-STAT3, K-Ras, and TNFα/NF-κB were differentially enriched.

Conclusions

S100A2 plays an important role in endometrial carcinoma progression and may represent an independent diagnostic and prognostic biomarker for endometrial carcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09180-5.

The interaction between S100A2 and KPNA2 mediates NFYA nuclear import and is a novel therapeutic target for colorectal cancer metastasis

Nucleocytoplasmic transport of proteins is disrupted and dysregulated in cancer cells. Nuclear pore complexes and cargo proteins are two main transportation regulators. However, the mechanism regulating nucleocytoplasmic transport in cancer remains elusive. Here, we identified a S100A2/KPNA2 cotransport complex that transports the tumor-associated transcription factor NFYA in colorectal cancer (CRC). Through the S100A2/KNPA2 complex, depending on its interaction with S100A2, NFYA is transported to the nucleus and inhibits the transcriptional activity of E-cadherin, which in turn promotes CRC metastasis. Targeting the S100A2/KPNA2 binding sites with the specific inhibitor delanzomib is a potential therapeutic approach for CRC.

Network-based protein-protein interaction prediction method maps perturbations of cancer interactome

The perturbations of protein-protein interactions (PPIs) were found to be the main cause of cancer. Previous PPI prediction methods which were trained with non-disease general PPI data were not compatible to map the PPI network in cancer. Therefore, we established a novel cancer specific PPI prediction method dubbed NECARE, which was based on relational graph convolutional network (R-GCN) with knowledge-based features. It achieved the best performance with a Matthews correlation coefficient (MCC) = 0.84±0.03 and an F1 = 91±2% compared with other methods. With NECARE, we mapped the cancer interactome atlas and revealed that the perturbations of PPIs were enriched on 1362 genes, which were named cancer hub genes. Those genes were found to over-represent with mutations occurring at protein-macromolecules binding interfaces. Furthermore, over 56% of cancer treatment-related genes belonged to hub genes and they were significantly related to the prognosis of 32 types of cancers. Finally, by coimmunoprecipitation, we confirmed that the NECARE prediction method was highly reliable with a 90% accuracy. Overall, we provided the novel network-based cancer protein-protein interaction prediction method and mapped the perturbation of cancer interactome. NECARE is available at: https://github.com/JiajunQiu/NECARE.

A systematic review of proteomic biomarkers in oral squamous cell cancer

BACKGROUND

Head and neck squamous cell cancer (HNSCC) is the most common cancer associated with chewing tobacco, in the world. As this is divided in to sites and subsites, it does not make it to top 10 cancers. The most common subsite is the oral cancer. At the time of diagnosis, more than 50% of patients with oral squamous cell cancers (OSCC) had advanced disease, indicating the lack of availability of early detection and risk assessment biomarkers. The new protein biomarker development and discovery will aid in early diagnosis and treatment which lead to targeted treatment and ultimately a good prognosis.

METHODS

This systematic review was performed as per PRISMA guidelines. All relevant studies assessing characteristics of oral cancer and proteomics were considered for analysis. Only human studies published in English were included, and abstracts, incomplete articles, and cell line or animal studies were excluded.

RESULTS

A total of 308 articles were found, of which 112 were found to be relevant after exclusion. The present review focuses on techniques of cancer proteomics and discovery of biomarkers using these techniques. The signature of protein expression may be used to predict drug response and clinical course of disease and could be used to individualize therapy with such knowledge.

CONCLUSIONS

Prospective use of these markers in the clinical setting will enable early detection, prediction of response to treatment, improvement in treatment selection, and early detection of tumor recurrence for disease monitoring. However, most of these markers for OSCC are yet to be validated.

S100 family members: potential therapeutic target in patients with hepatocellular carcinoma: A STROBE study

Proteins in S100 family exhibit different expressions patterns and perform different cytological functions, playing substantial roles in certain cancers, carcinogenesis, and disease progression. However, the expression and role of S100 family members in the prognosis of hepatocellular carcinoma (HCC) remains unclear. To investigate the effect of S100 family members for the prognosis of liver cancer, we assessed overall survival (OS) using a Kaplan-Meier plotter (KM plotter) in liver cancer patients with different situation. Our results showed that 15 members of the S100 family exhibited high levels of expression and these levels were correlated with OS in liver cancer patients. The higher expression of S100A5, S100A7, S100A7A, S100A12, S100Z, and S100G was reflected with better survival in liver cancer patients. However, worse prognosis was related to higher levels of expression of S100A2, S100A6, S100A8, S100A9, S100A10, S100A11, S10013, S100A14, and S100P. We then evaluated the prognostic values of S100 family members expression for evaluating different stages of AJCC-T, vascular invasion, alcohol consumption, and the presence of hepatitis virus in liver cancer patients. Lastly, we studied the prognostic values of S100 family members expression for patients after sorafenib treatment. In conclusion, our findings show that the proteins of S100 family members exhibit differential expression and may be useful as targets for liver cancer, facilitating novel diagnostic and therapeutic strategies in cancer.

miR-325-3p Promotes the Proliferation, Invasion, and EMT of Breast Cancer Cells by Directly Targeting S100A2

This study was designed to investigate the precise mechanisms of miR-325-3p/S100A2 axis in breast cancer (BC). In this study, we found that the level of miR-325-3p was dramatically increased in BC tissues and cell lines, and the expression of S100A2 was significantly decreased. Also, the high level of miR-325-3p was closely associated with low expression of S100A2 in BC tissues. Moreover, introduction of miR-325-3p significantly promoted proliferation, invasion, and EMT of BC cells. Bioinformatics analysis predicted that the S100A2 was a potential target gene of miR-325-3p. Luciferase reporter assay demonstrated that miR-325-3p could directly target S100A2. In addition, miR-325-3p overexpression had similar effects with knockdown of S100A2 on BC cells. Overexpression of S100A2 in BC cells partially reversed the promoted effects of miR-325-3p mimic. Overexpression of miR-325-3p promoted cell proliferation, invasion, and EMT of BC cells by directly downregulating S100A2 expression.

Comprehensive analysis of the expression and prognosis for S100 in human ovarian cancer: A STROBE study

S100 family members are frequently deregulated in human malignancies, including ovarian cancer. However, the prognostic roles of each individual S100 family member in ovarian cancer (OC) patients remain elusive. In the present study, we assessed the prognostic roles and molecular function of 20 individual members of the S100 family in OC patients using GEPIA, Kaplan-Meier plotter, SurvExpress, GeneMANIA and Funrich database. Our results indicated that the mRNA expression levels of S100A1, S100A2, S100A4, S100A5, S100A11, S100A14, and S100A16 were significantly upregulated in patients with OC, and high mRNA expression of S100A1, S100A3, S100A5, S100A6, and S100A13 were significantly correlated with better overall survival, while increased S100A2, S100A7A, S100A10, and S100A11 mRNA expressions were associated with worse prognosis in OC patients. In stratified analysis, the trends of high expression of individual S100 members were nearly the same in different pathological grade, clinical stage, TP53 mutation status, and treatment. More importantly, S100 family signatures may be useful potential prognostic markers for OC. These findings suggest that S100 family plays a vital role in prognostic value and could potentially be an S100-targeted inhibitors for OC patients.

Single-cell infrared phenomics: phenotypic screening with infrared microspectroscopy

We conceptually demonstrate single-cell infrared phenomics as a novel strategy of phenotypic screening with infrared microspectroscopy. Based on this development, the cancer cell HepG2 glycocalyx was first identified as a potential target of protopanaxadiol, an herbal medicine. These findings provide a powerful tool to accurately evaluate the cell stress response and to largely expand the phenotypic screening toolkit for drug discovery.

Identification of cisplatin-resistant factor by integration of transcriptomic and proteomic data using head and neck carcinoma cell lines

Cisplatin is an important drug for the treatment of head and neck squamous cell carcinoma (HNSCC). Determining chemoresistant factors prior to treatment will lead to great benefits for clinicians and patients. Here, we evaluated chemoresistant factors by integrating proteomic and transcriptomic data using HNSCC cell lines to identify a more precise chemoresistant factor in HNSCC. We used four HNSCC cell lines: cisplatin-sensitive, acquired cisplatin resistance, naturally cisplatin-resistant, and acquired 5-FU resistance. Proteomic analysis was performed using iTRAQ, tandem mass spectrometry, and liquid chromatography-electrospray ionization-tandem mass spectrometry. Transcriptomic analysis was performed using microarrays. By integrating these independent data, common factors were addressed and functional analysis was performed using small interfering RNAs (siRNAs) to change the chemosensitivity. Using iTRAQ analysis, 7 proteins were identified as specific for cisplatin chemoresistance factors. Transcriptomic analysis revealed hundreds of potential candidate factors. By combining and integrating these data, S100A2 was identified as a potential cisplatin-specific chemoresistance factor. Functional analysis with siRNA revealed that the expression of S100A2 was reduced and cisplatin sensitivity recovered in the acquired and naturally cisplatin-resistant cell lines, but not in the cisplatin-sensitive cell lines. S100A2 was identified as a cisplatin-specific chemoresistance factor by integrating the transcriptomic and proteomic results obtained using HNSCC cell lines. This is a novel technique that allows for a precise identification, also known as a comprehensive analysis. Our findings indicate that these proteins could be used as biomarkers of HNSCC treatments, providing physicians with new treatment strategies for patients with HNSCC, showing chemoresistance.

Salivary biomarkers in oral squamous cell carcinoma

In disease diagnostics and health surveillance, the use of saliva has potential because its collection is convenient and noninvasive. Over the past two decades, the development of salivary utilization for the early detection of cancer, especially oral cavity and oropharynx cancer has gained the interest of the researcher and clinician. Until recently, the oral cavity and oropharynx cancers are still having a five-year survival rate of 62%, one of the lowest in all major human cancers. More than 90% of oral cancers are oral squamous cell carcinoma (OSCC). Despite the ease of accessing the oral cavity in clinical examination, most OSCC lesions are not diagnosed in the early stage, which is suggested to be the main cause of the low survival rate. Many studies have been performed and reported more than 100 potential saliva biomarkers for OSCC. However, there are still obstacles in figuring out the reliable OSCC salivary biomarkers and the clinical application of the early diagnosis protocol. The current review article discusses the emerging issues and is hoped to raise awareness of this topic in both researchers and clinicians. We also suggested the potential salivary biomarkers that are reliable, specific, and sensitive for the early detection of OSCC.

Role of Salivary Biomarkers in Oral Cancer Detection

Oral cancers are the sixth most frequent cancer with a high mortality rate. Oral squamous cell carcinoma accounts for more than 90% of all oral cancers. Standard methods used to detect oral cancers remain comprehensive clinical examination, expensive biochemical investigations, and invasive biopsy. The identification of biomarkers from biological fluids (blood, urine, saliva) has the potential of early diagnosis. The use of saliva for early cancer detection in the search for new clinical markers is a promising approach because of its noninvasive sampling and easy collection methods. Human whole-mouth saliva contains proteins, peptides, electrolytes, organic, and inorganic salts secreted by salivary glands and complimentary contributions from gingival crevicular fluids and mucosal transudates. This diagnostic modality in the field of molecular biology has led to the discovery and potential of salivary biomarkers for the detection of oral cancers. Biomarkers are the molecular signatures and indicators of normal biological, pathological process, and pharmacological response to treatment hence may provide useful information for detection, diagnosis, and prognosis of the disease. Saliva's direct contact with oral cancer lesions makes it more specific and potentially sensitive screening tool, whereas more than 100 salivary biomarkers (DNA, RNA, mRNA, protein markers) have already been identified, including cytokines (IL-8, IL-1b, TNF-α), defensin-1, P53, Cyfra 21-1, tissue polypeptide-specific antigen, dual specificity phosphatase, spermidine/spermineN1-acetyltransferase , profilin, cofilin-1, transferrin, and many more. However, further research is still required for the reliability and validation of salivary biomarkers for clinical applications. This chapter provides the latest up-to-date list of known and emerging potential salivary biomarkers for early diagnosis of oral premalignant and cancerous lesions and monitoring of disease activity.

Programmed death-ligand 1 expression by digital image analysis advances thyroid cancer diagnosis among encapsulated follicular lesions

Recognition of noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) that distinguishes them from invasive malignant encapsulated follicular variant of papillary thyroid carcinoma (EFVPTC) can prevent overtreatment of NIFTP patients. We and others have previously reported that programmed death-ligand 1 (PD-L1) is a useful biomarker in thyroid tumors; however, all reports to date have relied on manual scoring that is time consuming as well as subject to individual bias. Consequently, we developed a digital image analysis (DIA) protocol for cytoplasmic and membranous stain quantitation (ThyApp) and evaluated three tumor sampling methods [Systemic Uniform Random Sampling, hotspot nucleus, and hotspot nucleus/3,3'-Diaminobenzidine (DAB)]. A patient cohort of 153 cases consisting of 48 NIFTP, 44 EFVPTC, 26 benign nodules and 35 encapsulated follicular lesions/neoplasms with lymphocytic thyroiditis (LT) was studied. ThyApp quantitation of PD-L1 expression revealed a significant difference between invasive EFVPTC and NIFTP; but none between NIFTP and benign nodules. ThyApp integrated with hotspot nucleus tumor sampling method demonstrated to be most clinically relevant, consumed least processing time, and eliminated interobserver variance. In conclusion, the fully automatic DIA algorithm developed using a histomorphological approach objectively quantitated PD-L1 expression in encapsulated thyroid neoplasms and outperformed manual scoring in reproducibility and higher efficiency.

Advances of Salivary Proteomics in Oral Squamous Cell Carcinoma (OSCC) Detection: An Update

Oral cancer refers to malignancies that have higher morbidity and mortality rates due to the late stage diagnosis and no early detection of a reliable diagnostic marker, while oral squamous cell carcinoma (OSCC) is amongst the world’s top ten most common cancers. Diagnosis of cancer requires highly sensitive and specific diagnostic tools which can support untraceable hidden sites of OSCC, yet to be unleashed, for which plenty of biomarkers are identified; the most recommended biomarker detection medium for OSCC includes biological fluids, such as blood and saliva. Saliva holds a promising future in the search for new clinical biomarkers that are easily accessible, less complex, accurate, and cost effective as well as being a non-invasive technique to follow, by analysing the malignant cells’ molecular pathology obtained from saliva through proteomic, genomic and transcriptomic approaches. However, protein biomarkers provide an immense potential for developing novel marker-based assays for oral cancer, hence this current review offers an overall focus on the discovery of a panel of candidates as salivary protein biomarkers, as well as the proteomic tools used for their identification and their significance in early oral cancer detection.

Large-Scale Analysis of Gene Expression Data Reveals a Novel Gene Expression Signature Associated with Colorectal Cancer Distant Recurrence

Colorectal cancer (CRC) is the fourth-ranked cause of cancer-related deaths worldwide. Despite recent advances in CRC management, distant recurrence (DR) remains the major cause of mortality in patients with preoperative chemotherapy and radiotherapy, underscoring a need to precisely identify novel gene signatures for predicting the risk of systemic relapse. Herein, we integrated two independent CRC gene expression datasets: the GSE71222 dataset, including 26 patients who developed DR and 126 patients who did not develop DR, and the GSE21510 dataset, including 23 patients who developed DR and 76 patients who did not develop DR. Our data revealed 37 common upregulated genes (fold change (FC) ≥ 1.5, P < 0.05) and three common downregulated genes (FC ≤ 1.5, P < 0.05) between DR and non-recurrent patients from the two datasets. We subsequently validated the upregulated gene panel in the Cancer Genome Atlas CRC datasets (379 patients), which identified a five-gene signature (S100A2, VIP, HOXC6, DACT1, KIF26B) associated with poor overall survival (OS, log-rank test P-value: 1.19 × 10⁻⁴) and poor disease-free survival (DFS, log-rank test P-value: 0.002). In a Cox proportional hazards multiple regression model, the five-gene signature and tumor stage retained their significance as independent prognostic factors for CRC DFS and OS. Therefore, our data identified a novel DR gene expression signature associated with worse prognosis in CRC.

End Binding 1 (EB1) overexpression in oral lesions and cancer: A biomarker of tumor progression and poor prognosis

INTRODUCTION

Oral squamous cell carcinoma (OSCC) patients are at high risk of loco-regional recurrence and despite the improvement in treatment strategy, 5-year survival rates are about 50%. Identification of patients at high risk of recurrence may enable rigorous personalized post-treatment management. In an earlier proteomics study we observed overexpression of End Binding Protein (EB1) in OSCC. In the present study we investigated the diagnostic and prognostic significance of alterations in expression of EB1 in oral cancer.

METHODS

In this retrospective study, the expression of EB1 protein was evaluated in 259 OSCCs, 41 dysplasia, 166 hyperplasia and 126 normal tissues using immunohistochemistry and correlated with clinical-pathological parameters and prognosis of OSCC patients over a follow-up period of up to 91months.

RESULTS

Significantly higher expression of cytoplasmic EB1 was observed in hyperplasia [p<0.001, OR=7.2, 95% CI=4.1-12.8], dysplasia (p<0.001, OR=21.8, CI=8.8-50.2) and OSCCs (p<0.001, OR=10.1, CI=5.8-17.4) in comparison with normal mucosa. Univariate analysis revealed cytoplasmic EB1 association with tumor grade, tumor size and recurrence of the disease. Kaplan Meier survival analysis of EB1 expression showed significantly reduced disease free survival (DFS) (p=0.003). Notably, OSCC patients showing cytoplasmic EB1 overexpression demonstrated significantly reduced DFS (p=0.004, HR=2.1).

CONCLUSION

EB1 overexpression is an early event in oral tumorigenesis and cytoplasmic EB1 accumulation is associated with poor prognosis and tumor recurrence in OSCC patients.