Factors affecting surgical mortality of oral squamous cell carcinoma resection

A nomogram for predicting overall survival of patients with squamous cell carcinoma of the floor of the mouth: a population-based study

BACKGROUND

Floor of mouth squamous cell carcinoma (SCCFOM) is a rare but aggressive malignancy with 5-year overall survival (OS) rates below 40% in published studies. However, the clinicopathological predictors of the prognosis of SCCFOM remain undefined. We aimed to establish a model to predict the survival outcomes of SCCFOM.

METHODS

We searched the Surveillance, Epidemiology, and End Results (SEER) database for patients diagnosed with SCCFOM between 2000 and 2017. Data on patient demographics, treatment modalities, and survival outcomes were retrieved. Risk factors for OS were evaluated by survival and Cox regression analyses. A nomogram for OS was developed based on the multivariate model and split the patients into high- and low-risk cohorts based on cutoff values.

RESULTS

Overall, 2014 SCCFOM patients were included in this population-based study. Multivariate Cox regression showed that age, married status, grade, American Joint Committee on Cancer stage, radiotherapy, chemotherapy, and surgery were significant risk factors for survival. A nomogram was established using the regression model. The C-indices, areas under the receiver operating characteristic curves, and calibration plots demonstrated the reliable performance of the nomogram. Patients assigned to the high-risk group had a significantly lower survival rate.

CONCLUSIONS

The nomogram predicting survival outcomes of SCCFOM patients based on clinical information showed good discriminative ability and prognostic accuracy. Our nomogram could be used to predict the survival probabilities for SCCFOM patients at different timepoints.

The Predictive Model of Oral Squamous Cell Survival Carcinoma: A Methodology of Validation

Background

Cancer is primarily caused by smoking, alcohol, betel quit, a series of genetic alterations, and epigenetic abnormalities in signaling pathways, which result in a variety of phenotypes that favor the development of OSCC. Oral squamous cell carcinoma (OSCC) is the most common type of oral cancer, accounting for 80–90% of all oral malignant neoplasms. Oral cancer is relatively common, and it is frequently curable when detected and treated early enough. The tumor-node-metastasis (TNM) staging system is used to determine patient prognosis; however, geographical inaccuracies frequently occur, affecting management.

Objective

To determine the additional relationship between factors discovered by searching for sociodemographic and metastasis factors, as well as treatment outcomes, which could help improve the prediction of the survival rate in cancer patients. Material and Methods. A total of 56 patients were recruited from the ambulatory clinic at the Hospital Universiti Sains Malaysia (USM). In this retrospective study, advanced computational statistical modeling techniques were used to evaluate data descriptions of several variables such as treatment, age, and distant metastasis. The R-Studio software and syntax were used to implement and test the hazard ratio. The statistics for each sample were calculated using a combination model that included methods such as bootstrap and multiple linear regression (MLR).

Results

The statistical strategy showed R demonstrates that regression modeling outperforms an R-squared. It demonstrated that when data is partitioned into a training and testing dataset, the hybrid model technique performs better at predicting the outcome. The variable validation was determined using the well-established bootstrap-integrated MLR technique. In this case, three variables are considered: age, treatment, and distant metastases. It is important to note that three things affect the hazard ratio: age (β₁: -0.006423; p < 2e − 16), treatment (β₂: -0.355389; p < 2e − 16), and distant metastasis (β₃: -0.355389; p < 2e − 16). There is a 0.003469102 MSE for the linear model in this scenario.

Conclusion

In this study, a hybrid approach combining bootstrapping and multiple linear regression will be developed and extensively tested. The R syntax for this methodology was designed to ensure that the researcher completely understood the illustration. In this case, a hybrid model demonstrates how this critical conclusion enables us to better understand the utility and relative contribution of the hybrid method to the outcome. The statistical technique used in this study, R, demonstrates that regression modeling outperforms R-squared values of 0.9014 and 0.00882 for the predicted mean squared error, respectively. The conclusion of the study establishes the superiority of the hybrid model technique used in the study.

Exosomal LncRNA LBX1-AS1 Derived From RBPJ Overexpressed-Macrophages Inhibits Oral Squamous Cell Carcinoma Progress via miR-182-5p/FOXO3

Objectives

Macrophage-derived exosomes (Mφ-Exos) are involved in tumor onset, progression, and metastasis, but their regulation in oral squamous cell carcinoma (OSCC) is not fully understood. RBPJ is implicated in macrophage activation and plasticity. In this study, we assessed the role of Mφ-Exos with RBPJ overexpression (RBPJ-OE Mφ-Exos) in OSCC.

Materials and Methods

The long non-coding RNA (lncRNA) profiles in RBPJ-OE Mφ-Exos and THP-1-like macrophages (WT Mφ)-Exos were evaluated using lncRNA microarray. Then the functions of Mφ-Exo-lncRNA in OSCC cells were assessed via CCK-8, EdU, and Transwell invasion assays. Besides, luciferase reporter assay, RNA immunoprecipitation, and Pearson's correlation analysis were adopted to confirm interactions. Ultimately, a nude mouse model of xenografts was used to further analyze the function of Mφ-Exo-lncRNAs in vivo.

Results

It was uncovered that lncRNA LBX1-AS1 was upregulated in RBPJ-OE Mφ-Exos relative to that in WT Mφ-Exos. RBPJ-OE Mφ-Exos and LBX1-AS1 overexpression inhibited OSCC cells to proliferate and invade. Meanwhile, LBX1-AS1 knockdown boosted the tumor to grow in vivo. The effects of RBPJ-OE Mφ-Exos on OSCC cells can be reversed by the LBX1-AS1 knockdown. Additionally, mechanistic investigations revealed that LBX1-AS1 acted as a competing endogenous RNA of miR-182-5p to regulate the expression of FOXO3.

Conclusion

Exo-LBX1-AS1 secreted from RBPJ-OE Mφ inhibits tumor progression through the LBX1-AS1/miR-182-5p/FOXO3 pathway, and LBX1-AS1 is probably a diagnostic biomarker and potential target for OSCC therapy.