A novel histopathological scoring system for patients with oral squamous cell carcinoma

Integrating lipid metabolite analysis with MRI-based transformer and radiomics for early and late stage prediction of oral squamous cell carcinoma

BACKGROUND

Oral Squamous Cell Carcinoma (OSCC) presents significant diagnostic challenges in its early and late stages. This study aims to utilize preoperative MRI and biochemical indicators of OSCC patients to predict the stage of tumors.

METHODS

This study involved 198 patients from two medical centers. A detailed analysis of contrast-enhanced T1-weighted (ceT1W) and T2-weighted (T2W) MRI were conducted, integrating these with biochemical indicators for a comprehensive evaluation. Initially, 42 clinical biochemical indicators were selected for consideration. Through univariate analysis and multivariate analysis, only those indicators with p-values less than 0.05 were retained for model development. To extract imaging features, machine learning algorithms in conjunction with Vision Transformer (ViT) techniques were utilized. These features were integrated with biochemical indicators for predictive modeling. The performance of model was evaluated using the Receiver Operating Characteristic (ROC) curve.

RESULTS

After rigorously screening biochemical indicators, four key markers were selected for the model: cholesterol, triglyceride, very low-density lipoprotein cholesterol and chloride. The model, developed using radiomics and deep learning for feature extraction from ceT1W and T2W images, showed a lower Area Under the Curve (AUC) of 0.85 in the validation cohort when using these imaging modalities alone. However, integrating these biochemical indicators improved the model's performance, increasing the validation cohort AUC to 0.87.

CONCLUSION

In this study, the performance of the model significantly improved following multimodal fusion, outperforming the single-modality approach.

CLINICAL RELEVANCE STATEMENT

This integration of radiomics, ViT models, and lipid metabolite analysis, presents a promising non-invasive technique for predicting the staging of OSCC.

Angelicin inhibits cell growth and promotes apoptosis in oral squamous cell carcinoma by negatively regulating DUSP6/cMYC signaling pathway

Angelicin has been reported to have antitumor effects on many types of cancer. However, few studies on angelicin in oral squamous cell carcinoma (OSCC) have been performed. We performed cell cycle and apoptosis analyses to assess the effect of angelicin on OSCC cells. We conducted RNA-seq studies to reveal differentially expressed genes (DEGs). Dual-specificity phosphatase 6 (DUSP6) and c-MYC were strongly down-regulated differential genes. Silencing RNA (siRNA) was used to knockdown DUSP6. The mouse xenograft model was used to mimic OSCC. Angelicin inhibited OSCC in vitro. We found that DUSP6 interacted with c-MYC. DUSP6 knockdown group and DUSP6 knockdown + angelicin group had similar effects of OSCC cells. Angelicin could reduce tumor formation, DUSP6, and c-MYC expression in vivo. Compared with paclitaxel, the tumor inhibition effect of the two drugs was similar. However, angelicin did not cause weight loss and had lower toxicity. In sum, Angelicin has antitumor effects on OSCC in vitro and vivo by negatively regulating the DUSP6 mediated c-MYC signaling pathway.

Perineural Invasion Is a Significant Prognostic Factor in Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis

(1) Objectives: This systematic review and meta-analysis aimed to summarize current evidence regarding the prognostic role of perineural invasion (PNI) in patients with oral squamous cell carcinoma (OSCC). (2) Methods: We searched Cochrane Central, ProQuest, PubMed, Scopus, Science Direct, and Web of Science, using relevant keywords to identify eligible articles. Two independent reviewers conducted two-stage screening, data extraction, and quality assessment. The risk of bias was assessed using the Newcastle-Ottawa Scale (NOS) criteria. All analyses were performed using comprehensive meta-analysis (CMA; version 3.3.070) software. (3) Results: The study included 101 published articles encompassing 26,062 patients. The pooled analyses showed that PNI was associated with significantly worse overall survival (OS; HR = 1.45, 95% CI: 1.32-1.58; p < 0.001), worse disease-specific survival (DSS; HR = 1.87, 95% CI: 1.65-2.12; p < 0.001), and worse disease-free survival (DFS; HR = 1.87, 95% CI: 1.65-2.12; p < 0.001). Similarly, both local recurrence-free survival (LRFS) and regional recurrence-free survival (RRFS) were worse in patients with PNI (HR = 2.31, 95% CI: 1.72-3.10, p < 0.001; and HR = 2.04, 95% CI: 1.51-2.74, p < 0.001), respectively. The random-effect estimate of three studies demonstrated that the presence of PNI was associated with worse failure-free survival (FFS; HR = 2.59, 95% CI: 1.12-5.98, p < 0.001). (4) Conclusions: The current evidence suggests that PNI can be used as an independent predictor of the prognosis for patients with OSCC. The presence of PNI was associated with worse OS, DFS, DSS, FFS, and with recurrence. Asian patients and patients with extra-tumoral or peripheral PNI invasion were associated with worse prognosis.

A prognostic model for oral squamous cell carcinoma patients with type 2 diabetes mellitus

OBJECTIVE

To build a prognostic model for oral squamous cell carcinoma patients with type 2 diabetes mellitus.

DESIGN

Oral squamous cell carcinoma patients with type 2 diabetes mellitus in Xiangya Hospital were studied. Patients during January 2011 to January 2015 were included in training set (n = 146), and those during January 2017 to December 2020 were included in test set (n = 81). Univariate and multivariate Cox regressions were used to screen independent prognostic variables. Nomogram was used to show the model. C-index, internal bootstrap resampling and external validation were used to evaluate the model.

RESULTS

Six independent prognostic factors (T stage, N stage, pathological grade, metformin use, sulfonylureas use, and fasting blood glucose) were screened from training set. Based on the six variables, nomogram was constructed to predict the prognosis of oral squamous cell carcinoma patients with type 2 diabetes mellitus. C-index value was 0.728, and result of internal bootstrap resampling showed better prediction efficiency for one-year survival. All patients were divided into two groups according to total points calculated based on the model. Group with low total points experienced better survival than that with high total points both in training set and test set.

CONCLUSIONS

The model provides a relatively accurate method to predict the prognosis of oral squamous cell carcinoma patients with type 2 diabetes mellitus.

Preoperative Prediction of the Aggressiveness of Oral Tongue Squamous Cell Carcinoma with Quantitative Parameters from Dual-Energy Computed Tomography

Objectives

To determine whether quantitative parameters derived from dual-energy computed tomography (DECT) were predictive of the aggressiveness of oral tongue squamous cell carcinoma (OTSCC) including the pathologic stages, histologic differentiation, lymph node status, and perineural invasion (PNI).

Methods

Between August 2019 and March 2021, 93 patients (mean age, 54.6 ± 13.8 years; 66 men) with pathologically diagnosed OTSCC were enrolled in this prospective study. Preoperative DECT was performed and quantitative parameters (e.g., slope of the spectral Hounsfield unit curve [λ_Hu], normalized iodine concentration [nIC], normalized effective atomic number [nZ_eff], and normalized electron density [nRho]) were measured on arterial phase (AP) and venous phase (VP) DECT imaging. Quantitative parameters from DECT were compared between patients with different pathologic stages, histologic differentiation, lymph node statuses, and perineural invasion statuses. Logistic regression analysis was utilized to assess independent parameters and the diagnostic performance was analyzed by the receiver operating characteristic curves (ROC).

Results

λ_Hu and nIC in AP and λ_Hu, nZ_eff, and nIC in VP were significantly lower in stage III–IV lesions than in stage I–II lesions (p < 0.001 to 0.024). λ_Hu in VP was an independent predictor of tumor stage with an odds ratio (OR) of 0.29, and area under the curve (AUC) of 0.80. λ_Hu and nIC were higher in well-differentiated lesions than in poorly differentiated lesions (p < 0.001 to 0.021). The nIC in VP was an independent predictor of histologic differentiation with OR of 0.31, and AUC of 0.78. λ_Hu and nIC in VP were lower in OTSCCs with lymph node metastasis than those without metastasis (p < 0.001 to 0.005). λ_Hu in VP was the independent predictor of lymph node status with OR of 0.42, and AUC of 0.74. No significant difference was found between OTSCCs without PNI and those with PNI in terms of the quantitative DECT parameters.

Conclusion

DECT can be a complementary means for the preoperative prediction of the aggressiveness of OTSCC.

Prognostic impact of perineural invasion in oral cancer: a systematic review

Introduction

Numerous studies have evaluated the prognostic significance of perineural invasion (PNI) in oral cancer; however, the results are inconclusive.

Purpose

To identify the prognostic value of PNI in oral cancer through a metanalysis.

Methods

A literature review was carried out, searching the MedLine databases via Pubmed, Scielo, Lilacs, Cochrane and Websco.

Results

A total of 56 studies were included. The results indicate that PNI in oral cancer has an incidence of 28% (95% confidence interval (CI) 24-31%); 5-year survival with relative risk (RR) 0.67 (0.59-0.75); 5-year disease-free survival RR 0.71 (0.68-0.75); locoregional recurrence with RR 2.09 (1.86-2.35).

Conclusions

PNI is a negative prognostic factor in oral cancer.

Identification of oral precancerous and cancerous tissue by swept source optical coherence tomography

BACKGROUND AND OBJECTIVES

Distinguishing cancer from precancerous lesions is critical and challenging in oral medicine. As a noninvasive method, optical coherence tomography (OCT) has the advantages of real-time, in vivo, and large-depth imaging. Texture information hidden in OCT images can provide an important auxiliary effect for improving diagnostic accuracy. The aim of this study is to explore a reliable and accurate OCT-based method for the screening and diagnosis of human oral diseases, especially oral cancer.

MATERIALS AND METHODS

Fresh ex vivo oral tissues including normal mucosa, leukoplakia with epithelial hyperplasia (LEH), and oral squamous cell carcinoma (OSCC) were imaged intraoperatively by a homemade OCT system, and 58 texture features were extracted to create computational models of these tissues. A principal component analysis algorithm was employed to optimize the combination of texture feature vectors. The identification based on artificial neural network (ANN) was proposed and the sensitivity/specificity was calculated statistically to evaluate the classification performance.

RESULTS

A total of 71 sites of three types of oral tissues were measured, and 5176 OCT images of three types of oral tissues were used in this study. The superior classification result based on ANN was obtained with an average accuracy of 98.17%. The sensitivity and specificity of normal mucosa, LEH, and OSCC are 98.17% / 98.38%, 93.81% / 98.54%, and 98.11% / 99.04%, respectively.

CONCLUSION

It is demonstrated from the high accuracies, sensitivities, and specificities that texture-based analysis can be used to identify oral precancerous and cancerous tissue in OCT images, and it has the potential to help surgeons in diseases screening and diagnosis effectively.

The combined detection of Amphiregulin, Cyclin A1 and DDX20/Gemin3 expression predicts aggressive forms of oral squamous cell carcinoma

Background

Large-scale genetic and epigenetic deregulations enable cancer cells to ectopically activate tissue-specific expression programmes. A specifically designed strategy was applied to oral squamous cell carcinomas (OSCC) in order to detect ectopic gene activations and develop a prognostic stratification test.

Methods

A dedicated original prognosis biomarker discovery approach was implemented using genome-wide transcriptomic data of OSCC, including training and validation cohorts. Abnormal expressions of silent genes were systematically detected, correlated with survival probabilities and evaluated as predictive biomarkers. The resulting stratification test was confirmed in an independent cohort using immunohistochemistry.

Results

A specific gene expression signature, including a combination of three genes, AREG, CCNA1 and DDX20, was found associated with high-risk OSCC in univariate and multivariate analyses. It was translated into an immunohistochemistry-based test, which successfully stratified patients of our own independent cohort.

Discussion

The exploration of the whole gene expression profile characterising aggressive OSCC tumours highlights their enhanced proliferative and poorly differentiated intrinsic nature. Experimental targeting of CCNA1 in OSCC cells is associated with a shift of transcriptomic signature towards the less aggressive form of OSCC, suggesting that CCNA1 could be a good target for therapeutic approaches.

Circular RNA circFOXO3 regulates KDM2A by targeting miR-214 to promote tumor growth and metastasis in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is a pathological type of oral cancer, which accounts for over 90% of oral cancers. It has been widely shown that circRNA is involved in the regulation of multiple malignant oral diseases including OSCC. However, the mechanism underlying how circRNA regulates OSCC is still not clearly elucidated. In this article, we report circFOXO3 promotes tumor growth and invasion of OSCC by targeting miR‐214 which specifically degrades the lysine demethylase 2A (KDM2A). CircRNA sequencing was conducted in OSCC tumor and tumor‐side tissues, and the expression of circFOXO3 is found to be markedly increased in tumor tissues. CircFOXO3 is also highly expressed in several OSCC cell lines compared with human oral keratinocytes. Transwell assay and colony formation showed that knockdown of circFOXO3 prevents the invasion and proliferation of oral cancer cells. Via bioinformatic research, miR‐214 was found to be the target of circFOXO3 and correlate well with circFOXO3 both in vitro and in vivo. KDM2A was then validated by database analysis and luciferase assay to be the direct target of miR‐214. KDM2A helps to promote tumor invasiveness and proliferation of OSCC. Collectively, our results proved that circFOXO3 sponges miR‐214 to up‐regulate the expression of KDM2A, thus promotes tumor progression in OSCC.

Melatonin and regulation of miRNAs: novel targeted therapy for cancerous and noncancerous disease

miRNAs, small noncoding RNAs with crucial diagnostic and prognostic capabilities, play essential therapeutic roles in different human diseases. These biomarkers are involved in several biological mechanisms and are responsible for the regulation of multiple genes expressions in cells. miRNA-based therapy has shown a very bright future in the case of clinical interventions. Melatonin, the main product of the pineal gland, is a multifunctional neurohormone with numerous therapeutic potentials in human diseases. Melatonin is able to regulate miRNAs in different pathologies such as malignant and nonmalignant diseases, which can be considered as a novel kind of targeted therapy. Herein, this review discusses possible therapeutic utility of melatonin for the regulation of miRNAs in various pathological conditions.

Prognostic value of log odds of positive lymph nodes in patients with resectable oral squamous cell carcinoma

OBJECTIVES

Log odds of positive lymph nodes (LODDS) was reported to be significantly associated with prognosis in several malignant tumors. However, few are the studies on the correlation between LODDS and overall survival (OS) in patients with oral squamous cell carcinoma (OSCC).

MATERIALS AND METHODS

A retrospective study including 233 patients with OSCC during 2009 to 2013 was conducted. We probed the correlation between clinicopathological factor, LODDS, lymph node ratio (LNR), pN and OS. The potential prognostic factor and the independent factor were calculated using univariate analysis and multivariate analysis respectively. The goodness of fit and the discriminability was analyzed with Somer's D value, Nagelkerke R2 index, and Akaike information criterion (AIC). Kaplan-Meier survival curve of OS was contrasted by log-rank test in LODDS, LNR and pN, respectively.

RESULTS

According to the X-tile, the cut-off values are -1.491 and -0.763 for LODDS, 0.024 and 0.133 for LNR. LODDS, LNR and pN were significantly correlated with OS by univariate analysis (P < 0.001). Multivariate analysis demonstrated LODDS, LNR and pN as an independent prognostic factors for OS (P < 0.01). Compared with pN and LNR models, LODDS showed the strongest predictive power. LODDS was superior to LNR and pN in predicting outcomes in patients with no positive lymph nodes and inadequate neck dissection.

CONCLUSION

LODDS would be incorporated into future N classification, which may be conducive to discern the prognosis of OSCC and make a decision of adjuvant therapy in clinical practice.

Functional and Clinical Impact of CircRNAs in Oral Cancer

The increasing number of recently published works regarding the role of circular RNAs (circRNAs) in oral cancer highlights the key contribution of this novel class of endogenous noncoding RNAs as regulators of critical signaling pathways and their clinical value as novel biomarkers. This review summarizes and puts into context the existing literature in order to clarify the relevance of circRNAs as novel mediators of oral cancer pathogenesis as well as their potential usefulness as predictors of clinical outcome and response to therapy in this disease.

Splicing factor derived circular RNA circUHRF1 accelerates oral squamous cell carcinoma tumorigenesis via feedback loop

Emerging evidences have suggested the vital roles of circular RNA (circRNA) in the human cancers. However, the underlying biological functions and biogenesis of circRNA in the oral squamous cell carcinoma (OSCC) is still ambiguous. Here, we investigate the oncogenic roles and biogenesis of the novel identified circRNA, circUHRF1 (hsa_circ_0002185), in the OSCC tumorigenesis. Results showed that circUHRF1 was markedly upregulated in the OSCC cells and tissue, besides, the overexpression was closely correlated with the poor prognosis of OSCC patients. Functionally, circUHRF1 promoted the proliferation, migration, invasion, and epithelial mesenchymal transformation (EMT) in vitro and the tumor growth in vivo. Mechanically, circUHRF1 acted as the sponge of miR-526b-5p, thereby positively regulating c-Myc. Transcription factor c-Myc could accelerate the transcription of TGF-β1 and ESRP1. Moreover, splicing factor ESRP1 promoted the circularization and biogenesis of circUHRF1 by targeting the flanking introns, forming the circUHRF1/miR-526b-5p/c-Myc/TGF-β1/ESRP1 feedback loop. In conclusion, our research identified the oncogenic roles of circUHRF1 in the OSCC tumorigenesis and EMT via circUHRF1/miR-526b-5p/c-Myc/TGF-β1/ESRP1 feedback loop, shedding light on the pathogenic mechanism of circUHRF1 for OSCC and providing the potential therapeutic target.