Derivation and Validation of a Prognostic Scoring Model Based on Clinical and Pathological Features for Risk Stratification in Oral Squamous Cell Carcinoma Patients: A Retrospective Multicenter Study

Management of Stage III Oral Cavity Squamous Cell Carcinoma in Light of the New Staging System: a Critical Review

PURPOSE OF REVIEW

Oral squamous cell carcinoma (OSCC) patients have a poor prognosis, especially in advanced stages. AJCC/UICC staging system 8th edition (TNM8) included depth of invasion (DOI) as part of T staging and stage III has become a heterogeneous group of lesions, composed of patients with larger DOI and/or width. Additionally, stage III includes N1, regardless of the primary tumor width or DOI. The real prognostic value of each of these characteristics and the need for adjuvant treatment for stage III patients is not well established.

RECENT FINDINGS

TNM8 stratified OSCC into prognostic groups based on overall survival. Extranodal extension, positive or close margins, pT3 or pT4 tumors, pN2 or pN3 nodal disease, nodal disease in levels IV or V, perineural invasion, vascular invasion, and lymphatic invasion are the main adverse features for OSCC, and adjuvant treatment is largely recommended for these patients. Stage III patients should be addressed with caution. So far, there is no significant evidence for recommending or excluding adjuvant treatment for stage III OSCC without adverse features. The authors largely recommend adjuvant radiotherapy for these cases, especially because pT3 without adverse features is rare. Further studies on this topic are necessary.

Integrated risk scores from N6-methyladenosine-related lncRNAs are potential biomarkers for predicting the overall survival of bladder cancer patients

Background: N6-methyladenosine (m6A) is the most common form of mRNA- and long noncoding RNA (lncRNA)-specific internal modification encountered in eukaryotes, with important effects on mRNA stability, translation, and splicing. The role of m6A-modified lncRNAs (m6A-lncRNAs) in bladder cancer (BLCA) is rarely reported. This study aimed to evaluate an efficient prognostic model of BLCA in patients, based on m6A-lncRNAs, and to discover potential biological targets.

Methods: Differentially expressed lncRNAs were investigated in 433 BLCA samples derived from The Cancer Genome Atlas (TCGA) database. Kaplan–Meier and univariate Cox regression analyses were performed to screen for m6A-lncRNAs with prognostic roles in BLCA. We implemented Pearson correlation analysis to analyze 18 potentially prognostic lncRNAs and 20 known m6A-associated genes. Next, the data were imputed using least absolute shrinkage and selection operator (LASSO) Cox regression to establish an m6A-lncRNA prognostic signature.

Results: We established an integrated risk score (RS) containing five m6A-lncRNAs and constructed a nomogram that had the ability to forecast the overall survival (OS) of patients with BLCA. We showed that the predictive accuracy of the RS for BLCA prognosis was high, which was confirmed by the area under the receiver operating characteristic (ROC) curve. We analyzed the correlation between tumor immune infiltrating cells and RS in high- and low-risk patients with BLCA and used tumor immune dysfunction and exclusion to predict the effect of immunotherapy. We screened out the most relevant modules of RS through the weighted gene co-expression network analysis network and explored their potential biological functions using GO and KEGG analyses.

Conclusion: Our findings demonstrate that, compared with nomograms constructed using a single prognostic factor, the integrated RS represents a superior model for predicting survival in patients with BLCA, which may improve the clinical management of BLCA.

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.

The Ratio of Preoperative Serum Biomarkers Predicts Prognosis in Patients With Oral Squamous Cell Carcinoma

Background

Dynamic changes in circulating immune-inflammatory cells have been regarded as simple and convenient prognostic biomarkers in various cancers. However, studies on the prognostic values of their ratios in oral squamous cell carcinoma (OSCC) remain limited.

Materials and Methods

A total of 493 OSCC patients were included in the present study. Here, we investigated the prognostic values of the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), neutrophil-to-white blood cell ratio (NWR), and lymphocyte-to-white blood cell ratio (LWR) in OSCC. The correlations of the NLR, LMR, NWR, and LWR with clinicopathological characteristics were statistically analyzed using the Chi-square test, Kaplan-Meier curves, and univariate and multivariate Cox regression models.

Result

Kaplan-Meier analyses revealed that OSCC patients with a high LMR and low NWR had prolonged overall survival (OS, P<0.001) and disease-free survival (DFS, P<0.001 and P=0.003, respectively), but there were no significant differences in metastasis-free survival (MFS, P=0.053 and P=0.052, respectively). In contrary, a high NLR and low LWR were associated with poor OS (P<0.001 and P=0.0016, respectively), DFS (P=0.0014 and 0.0012, respectively) and MFS (P=0.021 and 0.008, respectively). Additionally, Cox multivariate analyses showed that the LMR was an independent prognostic factor for both OS (P=0.007) and DFS (P=0.017), while the LWR was an independent prognostic factor for MFS (P=0.009).

Conclusion

Preoperative NLR, LMR, NWR, and LWR in the peripheral blood are significant prognostic factors for OSCC and might be helpful in predicting OSCC progression.