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 as 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. Results 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.
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.
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.
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