A Combined Prediction Model for Lymph Node Metastasis Based on a Molecular Panel and Clinicopathological Factors in Oral Squamous Cell Carcinoma

Synergistic Phototherapy-Molecular Targeted Therapy Combined with Tumor Exosome Nanoparticles for Oral Squamous Cell Carcinoma Treatment

Oral squamous cell carcinoma (OSCC) contributes to more than 90% of all oral malignancies, yet the performance of traditional treatments is impeded by limited therapeutic effects and substantial side effects. In this work, we report a combinational treatment strategy based on tumor exosome-based nanoparticles co-formulating a photosensitizer (Indocyanine green) and a tyrosine kinase inhibitor (Gefitinib) (IG@EXOs) for boosting antitumor efficiency against OSCC through synergistic phototherapy-molecular targeted therapy. The IG@EXOs generate distinct photothermal/photodynamic effects through enhanced photothermal conversion efficiency and ROS generation, respectively. In vivo, the IG@EXOs efficiently accumulate in the tumor and penetrate deeply to the center of the tumor due to passive and homologous targeting. The phototherapy effects of IG@EXOs not only directly induce potent cancer cell damage but also promote the release and cytoplasmic translocation of Gefitinib for achieving significant inhibition of cell proliferation and tumor angiogenesis, eventually resulting in efficient tumor ablation and lymphatic metastasis inhibition through the synergistic phototherapy-molecular targeted therapy. We envision that the encouraging performances of IG@EXOs against cancer pave a new avenue for their future application in clinical OSCC treatment.

Cyclin D1 and Ki-67 expression and its correlation with histopathological parameters and cervical lymph node metastasis in oral squamous cell carcinoma

Background

Oral squamous cell carcinoma (OSCC) is the most common malignant tumor among oral cancers. Cyclin D1 and Ki-67 have associated with cell division. The aim of this study was to compare the expression of these markers in OSCC with and without cervical lymph node (LN) metastasis.

Materials and Methods

This cross-sectional study was performed on 40 OSCCs with and without cervical LN metastasis (20 in each group) that was recorded in the pathology archive of Ayatollah Kashani Hospital in Isfahan. Clinical information including age, gender, and location was collected. Some histopathological parameters including depth of invasion, lymphovascular invasion (LVI), perineural invasion (PNI), number of LN metastases, histopathological grade, and stage of disease were evaluated. Immunohistochemical staining was performed for cyclin D1 and Ki-67. All data were entered into SPSS24 software and were analyzed by Mann-Whitney, Kruskal-Wallis, Chi-square, Fisher's exact, and t-tests. P < 0.05 was considered statistically significant.

Results

Based on LVI and stage of disease, a significant correlation was found between the two groups (P < 0.001). There was a significant difference between the two groups based on cyclin D1 expression (P = 0.05). The expression of the Ki-67 showed a significant difference based on tumor location (P = 0.026) and PNI (P = 0.033).

Conclusion

The use of markers should be considered in determining the prognosis of OSCC, and the cyclin D1 marker is one of the useful markers for predictors of cervical LN metastasis.

A preoperative nomogram model for the prediction of lymph node metastasis in buccal mucosa cancer

OBJECTIVES

We sought to construct a nomogram model predicting lymph node metastasis (LNM) in patients with squamous cell carcinoma of the buccal mucosa based on preoperative clinical characteristics.

METHODS

Patients who underwent radical resection of a primary tumor in the buccal mucosa with neck dissection were enrolled. Clinical characteristics independently associated with LNM in multivariate analyses were adopted to build the model. Patients at low risk of LNM were defined by a predicted probability of LNM of less than 5%.

RESULTS

Patients who underwent surgery in an earlier period (January 2015-November 2019) were defined as the model development cohort (n = 325), and those who underwent surgery later (November 2019-March 2021) were defined as the validation cohort (n = 140). Age, tumor differentiation, tumor thickness, and clinical N stage assessed by computed tomography/magnetic resonance imaging (cN) were independent predictors of LNM. The nomogram model based on these four predictors showed good discrimination accuracy in both the model development and validation cohorts, with areas under the receiver-operating characteristic curve (AUC) of 0.814 and 0.828, respectively. LNM prediction by the nomogram model was superior to cN in AUC comparisons (0.815 vs. 0.753) and decision curve analysis of the whole cohort. Seventy-one patients were defined as having a low risk of LNM, among whom the actual metastasis rate was only 1.4%.

CONCLUSIONS

A robust nomogram model for preoperative LNM prediction is built.

Human papillomavirus in oral squamous cell carcinoma using p16 and its co-relationship with cervical lymph node metastasis and clinicopathological parameters

Background

Due to the increasing prevalence of oral squamous cell carcinoma (OSCC) in Iran and especially in young people, this study aimed to identify human papillomavirus (HPV) using p16 in OSCC.

Materials and Methods

In this descriptive-analytical cross-sectional study, 40 samples from the archives of the Pathology Department of Kashani Hospital were selected by a definitive diagnosis of OSCC with neck dissection. Demographic information including age, gender, location, and size of the lesion was obtained. Samples were divided into two groups based on lymph node (LN) metastasis. Immunohistochemical staining was performed for p16. Data were entered into SPSS 24 software and statistically analyzed by t-test, ANOVA, and Spearman nonparametric test. P <0.05 was statistically significant.

Results

The mean age of patients was 59.7 ± 17.11 which in terms of age and gender there was no significant difference between the two groups including with and without cervical LN metastasis (P > 0.05). There was no significant difference between the two groups based on the grade of tumor, perninural invasion, tumor size and location (P > 0.05). The only significant difference between the two groups was based on lymphovascular invasion and disease stage (P < 0.05). The p16 expression also showed a significant difference between the two groups (P < 0.05).

Conclusion

In OSCCs without cervical LN metastasis, a significant increase in p16 expression was observed compared to samples with cervical LNs metastasis. The presence of HPV was higher in samples with less LNs metastasis and possibly a better prognosis.

A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using metabolic and pathological variables

BACKGROUND

The efficacy of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) Positron Emission Tomography/Computed Tomography(PET/CT) in evaluating the neck status in clinically node-negative (cN0) oral squamous cell carcinoma(OSCC) patients was still unsatisfying. We tried to develop a prediction model for nodal metastasis in cN0 OSCC patients by using metabolic and pathological variables.

METHODS

Consecutive cN0 OSCC patients with preoperative ¹⁸F-FDG PET/CT, subsequent surgical resection of primary tumor and neck dissection were included. Ninety-five patients who underwent PET/CT scanning in Shanghai ninth people's hospital were identified as training cohort, and another 46 patients who imaged in Shanghai Universal Medical Imaging Diagnostic Center were selected as validation cohort. Nodal-status-related variables in the training cohort were selected by multivariable regression after using the least absolute shrinkage and selection operator (LASSO). A nomogram was constructed with significant variables for the risk prediction of nodal metastasis. Finally, nomogram performance was determined by its discrimination, calibration, and clinical usefulness.

RESULTS

Nodal maximum standardized uptake value(nodal SUVmax) and pathological T stage were selected as significant variables. A prediction model incorporating the two variables was used to plot a nomogram. The area under the curve was 0.871(Standard Error [SE], 0.035; 95% Confidence Interval [CI], 0.787-0.931) in the training cohort, and 0.809(SE, 0.069; 95% CI, 0.666-0.910) in the validation cohort, with good calibration demonstrated.

CONCLUSIONS

A prediction model incorporates metabolic and pathological variables has good performance for predicting nodal metastasis in cN0 OSCC patients. However, further studies with large populations are needed to verify our findings.

Expression Profiles of CDKN2A, MDM2, E2F2 and LTF Genes in Oral Squamous Cell Carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is one of the most commonly detected neoplasms worldwide. Not all mechanisms associated with cell cycle disturbances are known in OSCC. Examples of genes involved in the control of the cell cycle are CDKN2A, MDM2, E2F2 and LTF. The aim of this study was to examine the possible association between CDKN2A, MDM2, E2F2 and LTF mRNA expression and influence on clinical variables.

METHODS

The study group consisted of 88 Polish patients. The gene expression levels were assessed by quantitative reverse transcription PCR.

RESULTS

We found no statistically significant differences in the expression level of CDKN2A, MDM2, E2F2 and LTF genes in tumour samples compared to margin samples. No association was found between the gene expression levels and clinical parameters, except E2F2. The patients with G2 tumours had a significantly higher gene expression level of E2F2 than patients with low-grade G1 tumours.

CONCLUSIONS

We have not demonstrated that a change in expression profiles of genes has a significant impact on the pathogenesis of OSCC. It may also be useful to conduct further studies on the use of E2F2 expression profile changes as a factor to describe the invasiveness and dynamics of OSCC development.

Risk Stratification in Oral Cancer: A Novel Approach

Background

Oral squamous cell carcinoma (OSCC) is a common head and neck cancer with high morbidity and mortality. Currently, treatment decisions are guided by TNM staging, which omits important negative prognosticators such as lymphovascular invasion, perineural invasion (PNI), and histologic differentiation. We proposed nomogram models based on adverse pathological features to identify candidates suitable for treatment escalation within each risk group according to the National Comprehensive Cancer Network (NCCN) guidelines.

Methods

Anonymized clinicopathologic data of OSCC patients from 5 tertiary healthcare institutions in Asia were divided into 3 risk groups according to the NCCN guidelines. Within each risk group, nomograms were built to predict overall survival based on histologic differentiation, histologic margin involvement, depth of invasion (DOI), extranodal extension, PNI, lymphovascular, and bone invasion. Nomograms were internally validated with precision–recall analysis and the Kaplan–Meier survival analysis.

Results

Low-risk patients with positive pathological nodal involvement and/or positive PNI should be considered for adjuvant radiotherapy. Intermediate-risk patients with gross bone invasion may benefit from concurrent chemotherapy. High-risk patients with positive margins, high DOI, and a high composite score of histologic differentiation, PNI, and the American Joint Committee on Cancer (AJCC) 8th edition T staging should be considered for treatment escalation to experimental therapies in clinical trials.

Conclusion

Nomograms built based on prognostic adverse pathological features can be used within each NCCN risk group to fine-tune treatment decisions for OSCC patients.

A robust and interpretable gene signature for predicting the lymph node status of primary T1/T2 oral cavity squamous cell carcinoma

Oral cavity squamous cell carcinoma (OSCC) affects more than 30 000 individuals in the United States annually, with smoking and alcohol consumption being the main risk factors. Management of early-stage tumors usually includes surgical resection followed by postoperative radiotherapy in certain cases. The cervical lymph nodes (LNs) are the most common site for local metastasis, and elective neck dissection is usually performed if the primary tumor thickness is greater than 3.5 mm. However, postoperative histological examination often reveals that many patients with early-stage disease are negative for neck nodal metastasis, posing a pressing need for improved risk stratification to either avoid overtreatment or prevent the disease progression. To this end, we aimed to identify a primary tumor gene signature that can accurately predict cervical LN metastasis in patients with early-stage OSCC. Using gene expression profiles from 189 samples, we trained K-top scoring pairs models and identified six gene pairs that can distinguish primary tumors with nodal metastasis from those without metastasis. The signature was further validated on an independent cohort of 35 patients using real-time polymerase chain reaction (PCR) in which it achieved an area under the receiver operating characteristic (ROC) curve and accuracy of 90% and 91%, respectively. These results indicate that such signature holds promise as a quick and cost effective method for detecting patients at high risk of developing cervical LN metastasis, and may be potentially used to guide the neck treatment regimen in early-stage OSCC.

The neuropeptide calcitonin gene-related peptide links perineural invasion with lymph node metastasis in oral squamous cell carcinoma

Objective

Although perineural invasion (PNI) is well-known to be correlated with and able to predict lymph node metastasis (LNM) in oral squamous cell carcinoma (OSCC), the clinical and molecular correlation between PNI and LNM has not been elucidated, and preoperative biomarkers for LNM prediction in OSCC are urgently needed.

Materials and methods

The correlation between PNI and LNM was retrospectively evaluated using a cohort of 218 patients diagnosed with OSCC. Candidate neuropeptides were screened based on TCGA database and verified via immunohistochemistry and Western blot analyses. ELISA was used to detect calcitonin gene-related peptide (CGRP) in patient plasma. In vitro assays were used to explore the effects of CGRP on OSCC cells.

Results

OSCC patients with PNI had a higher incidence of LNM (69.86% vs. 26.2%, P < 0.0001, n = 218). CGRP expression was upregulated in the PNI niche and in metastatic lymph nodes, and was correlated with poor overall survival of OSCC patients. Preoperative plasma CGRP levels were higher in OSCC patients (n = 70) compared to healthy donors (n = 60) (48.59 vs. 14.58 pg/ml, P < 0.0001), and were correlated with LNM (P < 0.0001) and PNI (P = 0.0002). Preoperative plasma CGRP levels alone yielded an AUC value of 0.8088 to predict LNM, and CGRP levels combined with preoperative T stage reached an AUC value of 0.8590. CGRP promoted proliferation and migration abilities of OSCC cells, which could be antagonized by either pharmacological or genetic blockade of the CGRP receptor.

Conclusions

The neuropeptide CGRP links PNI and LNM in OSCC, and preoperative plasma CGRP levels can be used to predict LNM in OSCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08998-9.