Retrospective Evaluation of Periradicular Biopsies: An 18-Year Study

INTRODUCTION

Radiographic findings in periradicular areas are repeatedly associated with infected root canal systems. Although non-odontogenic lesions in teeth are reported to be low, they often mimic periapical pathoses, and consequently, histopathologic examinations after surgical revisions are nurtured.

METHODS

Biopsies submitted to the College of Dentistry between 2003 and 2021 were reviewed. Clinicopathologic characteristics were collected, including age, sex, medical history, location, sensibility tests, and clinic impressions from each specimen. Histopathologic diagnosis and gross description were also part of our database.

RESULTS

A total of 72,055 pathology reports were reviewed, of which 10,031 lesions (13.9%) met the criterion of being intraosseous lesions at the periradicular area. Among those 10,031 lesions, 7.94% (n = 796) were of non-endodontic origin, 7153 were documented as non-vital, and 2.36% (n = 169) of these non-vital teeth were diagnosed with a non-endodontic origin. A total of 5707 lesions were obtained from surgeries within the periapical tissues, primarily performed by endodontists (94.02%). Non-endodontic lesions were reported in 1.09% of the cases. Odontogenic keratocyst was the most common non-endodontic diagnosis, followed by nasopalatine duct cyst and benign fibro-osseous lesion, respectively.

CONCLUSIONS

Pathologic findings of the periradicular tissues are not always from endodontic origin. The probability of encountering non-endodontic lesions is almost 8%. Even in clinically reported teeth with pulp necrosis, 1%-3% of biopsies were confirmed as non-endodontic lesions.

Prognostic Role of Combined EGFR and Tumor-Infiltrating Lymphocytes in Oral Squamous Cell Carcinoma

Background

Epidermal growth factor receptor (EGFR) is well known as a general prognostic biomarker for head and neck tumors, however the specific prognostic value of EGFR in oral squamous cell carcinoma (OSCC) is controversial. Recently, the presence of tumor-infiltrating T cells has been associated with significant survival advantages in a variety of disease sites. The present study will determine if the inclusion of T cell specific markers (CD3, CD4 and CD8) would enhance the prognostic value of EGFR in OSCCs.

Methods

Tissue microarrays containing 146 OSCC cases were analyzed for EGFR, CD3, CD4 and CD8 expression using immunohistochemical staining. EGFR and T cell expression scores were correlated with clinicopathological parameters and survival outcomes.

Results

Results showed that EGFR expression had no impact on overall survival (OS), but EGFR-positive (EGFR+) OSCC patients demonstrated significantly worse progression free survival (PFS) compared to EGFR-negative (EGFR-) patients. Patients with CD3, CD4 and CD8-positive tumors had significantly better OS compared to CD3, CD4 and CD8-negative patients respectively, but no impact on PFS. Combined EGFR+/CD3+ expression was associated with cases with no nodal involvement and significantly more favorable OS compared to EGFR+/CD3- expression. CD3 expression had no impact on OS or PFS in EGFR- patients. Combinations of EGFR/CD8 and EGFR/CD4 expression showed no significant differences in OS or PFS among the expression groups.

Conclusion

Altogether these results suggest that the expression of CD3+ tumor-infiltrating T cells can enhance the prognostic value of EGFR expression and warrants further investigation as prognostic biomarkers for OSCC.

Dataset-chemokines, cytokines, and biomarkers in the saliva of children with Sjögren's syndrome

Sjögren's syndrome is an autoimmune disease that can also occur in children. The disease is not well defined and there is limited information on the presence of chemokines, cytokines, and biomarkers (CCBMs) in the saliva of children that could improve their disease diagnosis. In a recent study [1], we reported a large dataset of 105 CCBMs that were associated with both lymphocyte and mononuclear cell functions [2] in the saliva of 11 children formally diagnosed with Sjögren's syndrome and 16 normal healthy children. Here, we extend those findings and use the Mendeley dataset [2] to identify CCBMs that have predictive power for Sjögren's syndrome in female children. Datasets of CCBMs from all saliva samples and female children saliva samples were standardized. We used machine learning methods to select Sjögren's syndrome associated CCBMs and assessed the predictive power of selected CCBMs in these two datasets using receiver operating characteristic (ROC) curves and associated areas under curve (AUC) as metrics. We used eight classifiers to identify 16 datasets that contained from 2 to 34 CCBMs with AUC values ranging from 0.91 to 0.94.

A distinguishing profile of chemokines, cytokines, and biomarkers in the saliva of children with Sjögren's syndrome

Objective

SS is an autoimmune disease most commonly diagnosed in adults but can occur in children. Our objective was to assess the presence of chemokines, cytokines and biomarkers (CCBMs) in saliva from these children that were associated with lymphocyte and mononuclear cell functions.

Methods

Saliva was collected from 11 children diagnosed with SS prior to age 18 years and 16 normal healthy children. A total of 105 CCBMs were detected in multiplex microparticle-based immunoassays. ANOVA and t test (0.05 level) were used to detect differences. Ingenuity Pathway Analysis (IPA) was used to assess whether elevated CCBMs were in annotations associated with immune system diseases and select leukocyte activities and functions. Machine learning methods were used to evaluate the predictive power of these CCBMs for SS and were measured by receiver operating characteristic (ROC) curve and area under curve (AUC).

Results

Of the 105 CCBMs detected, 43 (40.9%) differed in children with SS from those in healthy study controls (P < 0.05) and could differentiate the two groups (P < 0.05). Elevated CCBMs in IPA annotations were associated with autoimmune diseases and with leukocyte chemotaxis, migration, proliferation, and regulation of T cell activation. The best AUC value in ROC analysis was 0.93, indicating that there are small numbers of CCBMs that may be useful for diagnosis of SS.

Conclusion

While 35 of these 43 CCBMs have been previously reported in SS, 8 CCBMs had not. Additional studies focusing on these CCBMs may provide further insight into disease pathogenesis and may contribute to diagnosis of SS in children.

HBD3 Induces PD-L1 Expression on Head and Neck Squamous Cell Carcinoma Cell Lines

Human β-defensin 3 (HBD3) is an antimicrobial peptide up-regulated in the oral tissues of individuals with head and neck squamous cell carcinomas (HNSCC) and oral squamous cell carcinomas (SCC) and present in high concentrations in their saliva. In this study, we determined if HBD3 contributes to HNSCC pathogenesis by inducing programmed death-ligand 1 (PD-L1) expression on HNSCC cell lines. For this, SCC cell lines SCC4, SCC15, SCC19, SCC25, and SCC99 (5.0 × 10⁴ viable cells) were used. Cells were incubated with IFNγ (0.6 µM) and HBD3 (0.2, 2.0, or 20.0 µM) for 24 h. Cells alone served as controls. Cells were then treated with anti-human APC-CD274 (PD-L1) and Live/Dead Fixable Green Dead Cell Stain. Cells treated with an isotype antibody and cells alone served as controls. All cell suspensions were analyzed in a LSR II Violet Flow Cytometer. Cytometric data was analyzed using FlowJo software. Treatment with IFNγ (0.6 µM) increased the number of cells expressing PD-L1 (p < 0.05) with respect to controls. Treatment with HBD3 (20.0 µM) also increased the number of cells expressing PD-L1 (p < 0.05) with respect to controls. However, treatment with IFNγ (0.6 µM) was not significantly different from treatment with HBD3 (20.0 µM) and the numbers of cells expressing PD-L1 were similar (p = 1). Thus, HBD3 increases the number of cells expressing PD-L1. This is a novel concept, but the role HBD3 contributes to HNSCC pathogenesis by inducing PD-L1 expression in tumors will have to be determined.

Computational Models Accurately Predict Multi-Cell Biomarker Profiles in Inflammation and Cancer

Individual computational models of single myeloid, lymphoid, epithelial, and cancer cells were created and combined into multi-cell computational models and used to predict the collective chemokine, cytokine, and cellular biomarker profiles often seen in inflamed or cancerous tissues. Predicted chemokine and cytokine output profiles from multi-cell computational models of gingival epithelial keratinocytes (GE KER), dendritic cells (DC), and helper T lymphocytes (HTL) exposed to lipopolysaccharide (LPS) or synthetic triacylated lipopeptide (Pam3CSK4) as well as multi-cell computational models of multiple myeloma (MM) and DC were validated using the observed chemokine and cytokine responses from the same cell type combinations grown in laboratory multi-cell cultures with accuracy. Predicted and observed chemokine and cytokine responses of GE KER + DC + HTL exposed to LPS and Pam3CSK4 matched 75% (15/20, p = 0.02069) and 80% (16/20, P = 0.005909), respectively. Multi-cell computational models became ‘personalized’ when cell line-specific genomic data were included into simulations, again validated with the same cell lines grown in laboratory multi-cell cultures. Here, predicted and observed chemokine and cytokine responses of MM cells lines MM.1S and U266B1 matched 75% (3/4) and MM.1S and U266B1 inhibition of DC marker expression in co-culture matched 100% (6/6). Multi-cell computational models have the potential to identify approaches altering the predicted disease-associated output profiles, particularly as high throughput screening tools for anti-inflammatory or immuno-oncology treatments of inflamed multi-cellular tissues and the tumor microenvironment.

Matrix metalloproteinase (MMP) and immunosuppressive biomarker profiles of seven head and neck squamous cell carcinoma (HNSCC) cell lines

BACKGROUND

Biomarkers like programmed death ligand-1 (PDL1) have become a focal point for immunotherapeutic checkpoint inhibition in head and neck squamous cell carcinoma (HNSCC). However, it's only part of the total immunosuppressive biomarker profile of HNSCC cells. Matrix metalloproteinases (MMPs) are enzymes that break down the basement membrane allowing cancer cells to metastasize and play an important role in the tumor microenvironment. MMPs can also activate certain cytokines, growth factors, and chemokines post-translationally. The objective of this study was to determine MMP and biomarker profiles of seven different HNSCC cell lines.

METHODS

Authenticated cell lines were grown in minimal media at 1×106 viable cells/mL and incubated at 37 °C. After 24 hrs supernatants were collected, and adhering cells were lysed. Multiplex immunoassays were used to determine MMP1, MMP7, MMP9, IL-6, VEGFA, IL-1α, TNF-α, GM-CSF, IL-1RA, and IL-8 concentrations in supernatants. ELISAs were used to determine PDL1, CD47, FASL, and IDO concentrations in cell lysates. A one-way ANOVA was fit to examine log-transformed concentrations of biomarkers between seven HNSCC cell lines, and pairwise group comparisons were conducted using post- hoc Tukey's honest significance test (α=0.05).

RESULTS

Significant differences (P<0.05) in MMP and biomarker concentrations were found between the seven HNSCC cell lines. For example, MMP9 was highest in SCC25 and UM-SCC99, MMP7 was highest in SCC25 and UM-SCC19, and MMP1 was highest in SCC25.

CONCLUSIONS

These results suggest different patients' HNSCC cells can express distinct profiles of select biomarkers and MMPs, which could be due to metastatic stage of the cancer, primary tumor site, type of tissue the tumor originated from, or genomic differences between patients. MMP and biomarker expression profiles should be considered when choosing cell lines for future studies. The results support the reason for personalized medicine and the need to further investigate how it can be used to treat HNSCC.

Cell genomics and immunosuppressive biomarker expression influence PD-L1 immunotherapy treatment responses in HNSCC-a computational study

OBJECTIVES

Programmed death-ligand 1 (PD-L1) expression is correlated with objective response rates to PD-1 and PD-L1 immunotherapies. However, both immunotherapies have only demonstrated 12%-24.8% objective response rates in patients with head and neck squamous cell carcinoma (HNSCC), demonstrating a need for a more accurate method to identify those who will respond before their therapy. Immunohistochemistry to detect PD-L1 reactivity in tumors can be challenging, and additional methods are needed to predict and confirm PD-L1 expression. Here, we hypothesized that HNSCC tumor cell genomics influences cell signaling and downstream effects on immunosuppressive biomarkers and that these profiles can predict patient clinical responses.

STUDY DESIGN

We identified deleterious gene mutations in SCC4, SCC15, and SCC25 and created cell line-specific predictive computational simulation models. The expression of 24 immunosuppressive biomarkers were then predicted and used to sort cell lines into those that would respond to PD-L1 immunotherapy and those that would not.

RESULTS

SCC15 and SCC25 were identified as cell lines that would respond to PD-L1 immunotherapy treatment and SCC4 was identified as a cell line that would not likely respond to PD-L1 immunotherapy treatment.

CONCLUSIONS

This approach, when applied to HNSCC cells, has the ability to predict PD-L1 expression and predict PD-1- or PD-L1-targeted treatment responses in these patients.

Predicting PD-L1 expression on human cancer cells using next-generation sequencing information in computational simulation models

PURPOSE

Interaction of the programmed death-1 (PD-1) co-receptor on T cells with the programmed death-ligand 1 (PD-L1) on tumor cells can lead to immunosuppression, a key event in the pathogenesis of many tumors. Thus, determining the amount of PD-L1 in tumors by immunohistochemistry (IHC) is important as both a diagnostic aid and a clinical predictor of immunotherapy treatment success. Because IHC reactivity can vary, we developed computational simulation models to accurately predict PD-L1 expression as a complementary assay to affirm IHC reactivity.

METHODS

Multiple myeloma (MM) and oral squamous cell carcinoma (SCC) cell lines were modeled as examples of our approach. Non-transformed cell models were first simulated to establish non-tumorigenic control baselines. Cell line genomic aberration profiles, from next-generation sequencing (NGS) information for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines, were introduced into the workflow to create cancer cell line-specific simulation models. Percentage changes of PD-L1 expression with respect to control baselines were determined and verified against observed PD-L1 expression by ELISA, IHC, and flow cytometry on the same cells grown in culture.

RESULT

The observed PD-L1 expression matched the predicted PD-L1 expression for MM.1S, U266B1, SCC4, SCC15, and SCC25 cell lines and clearly demonstrated that cell genomics play an integral role by influencing cell signaling and downstream effects on PD-L1 expression.

CONCLUSION

This concept can easily be extended to cancer patient cells where an accurate method to predict PD-L1 expression would affirm IHC results and improve its potential as a biomarker and a clinical predictor of treatment success.

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells

Long-chain bases, found in the oral cavity, have potent antimicrobial activity against oral pathogens. In an article associated with this dataset, Poulson and colleagues determined the cytotoxicities of long-chain bases (sphingosine, dihydrosphingosine, and phytosphingosine) for human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), dendritic cells (DC), and squamous cell carcinoma (SCC) cell lines [1]. Poulson and colleagues found that GE keratinocytes were more resistant to long-chain bases as compared to GF, DC, and SCC cell lines [1]. In this study, we assess the susceptibility of DC to lower concentrations of long chain bases. 0.2–10.0 µM long-chain bases and GML were not cytotoxic to DC; 40.0–80.0 µM long-chain bases, but not GML, were cytotoxic for DC; and 80.0 µM long-chain bases were cytotoxic to DC and induced cellular damage and death in less than 20 mins. Overall, the LD₅₀ of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections.

Differential cytotoxicity of long-chain bases for human oral gingival epithelial keratinocytes, oral fibroblasts, and dendritic cells

Long-chain bases are present in the oral cavity. Previously we determined that sphingosine, dihydrosphingosine, and phytosphingosine have potent antimicrobial activity against oral pathogens. Here, we determined the cytotoxicities of long-chain bases for oral cells, an important step in considering their potential as antimicrobial agents for oral infections. This information would clearly help in establishing prophylactic or therapeutic doses. To assess this, human oral gingival epithelial (GE) keratinocytes, oral gingival fibroblasts (GF), and dendritic cells (DC) were exposed to 10.0-640.0 μM long-chain bases and glycerol monolaurate (GML). The effects of long-chain bases on cell metabolism (conversion of resazurin to resorufin), membrane permeability (uptake of propidium iodide or SYTOX-Green), release of cellular contents (LDH), and cell morphology (confocal microscopy) were all determined. GE keratinocytes were more resistant to long-chain bases as compared to GF and DC, which were more susceptible. For DC, 0.2-10.0 μM long-chain bases and GML were not cytotoxic; 40.0-80.0 μM long-chain bases, but not GML, were cytotoxic; and 80.0 μM long-chain bases induced cellular damage and death in less than 20 min. The LD50 of long-chain bases for GE keratinocytes, GF, and DC were considerably higher than their minimal inhibitory concentrations for oral pathogens, a finding important to pursuing their future potential in treating periodontal and oral infections.