Potential imaging targets in primary head and neck squamous cell carcinoma and lymph node metastases.

PURPOSE: To investigate glycoprotein nonmetastatic melanoma protein B (GPNMB) and vascular endothelial growth factor (VEGF) as potential fluorescent imaging markers by comparing their protein expression to epidermal growth factor receptor (EGFR). MATERIALS AND METHODS: Thirty-eight paired samples of untreated head and neck squamous cell carcinoma (HNSCC) primary tumours (PT) and corresponding synchronous lymph node metastases (LNM) were selected. After immunohistochemical staining, expression was assessed and compared by the percentage of positive tumour cells. Data were analysed using the Mann-Whitney test, effect sizes (ESr) and Spearman's correlation coefficient (r). RESULTS: GPNMB expression was observed in 100 % of PT, and median 80 % (range 5-100 %) of tumour cells, VEGF in 92 % and 60 % (0-100 %), EGFR in 87 % and 60 % (0-100 %) respectively. In corresponding LNM, GPNMB expression was observed in 100 % of LNM and median 90 % (20-100 %) of tumour cells, VEGF in 87 % and 65 % (0-100 %), and EGFR in 84 % and 35 % (0-100 %). A positive correlation was found between expression in PT and LNM for GPNMB (r = 0.548) and EGFR (r = 0.618) (p < 0.001), but not for VEGF (r = -0.020; p = 0.905). GPNMB expression was present in a higher percentage of tumour cells compared to EGFR in PT (p = 0.015, ESr = -0.320) and in LNM (p < 0.001, ESr = -0.478), while VEGF was not (p = 1.00, ESr = -0.109 and - 0.152, respectively). CONCLUSION: GPNMB expression is higher than EGFR in untreated HNSCC PT and corresponding LNM, while VEGF expression is comparable to EGFR. GPNMB is a promising target for fluorescent imaging in HNSCC.

Identification of new head and neck squamous cell carcinoma molecular imaging targets.

OBJECTIVES: Intraoperative fluorescence imaging (FI) of head and neck squamous cell carcinoma (HNSCC) is performed to identify tumour-positive surgical margins, currently using epidermal growth factor receptor (EGFR) as imaging target. EGFR, not exclusively present in HNSCC, may result in non-specific tracer accumulation in normal tissues. We aimed to identify new potential HNSCC FI targets. MATERIALS AND METHODS: Publicly available transcriptomic data were collected, and a biostatistical method (Transcriptional Adaptation to Copy Number Alterations (TACNA)-profiling) was applied. TACNA-profiling captures downstream effects of CNAs on mRNA levels, which may translate to protein-level overexpression. Overexpressed genes were identified by comparing HNSCC versus healthy oral mucosa. Potential targets, selected based on overexpression and plasma membrane expression, were immunohistochemically stained. Expression was compared to EGFR on paired biopsies of HNSCC, adjacent macroscopically suspicious mucosa, and healthy mucosa. RESULTS: TACNA-profiling was applied on 111 healthy oral mucosa and 410 HNSCC samples, comparing expression levels of 19,635 genes. The newly identified targets were glucose transporter-1 (GLUT-1), placental cadherin (P-cadherin), monocarboxylate transporter-1 (MCT-1), and neural/glial antigen-2 (NG2), and were evaluated by IHC on samples of 31 patients. GLUT-1 was expressed in 100 % (median; range: 60-100 %) of tumour cells, P-cadherin in 100 % (50-100 %), EGFR in 70 % (0-100 %), MCT-1 in 30 % (0-100 %), and NG2 in 10 % (0-70 %). GLUT-1 and P-cadherin showed higher expression than EGFR (p < 0.001 and p = 0.015). CONCLUSIONS: The immunohistochemical confirmation of TACNA-profiling results showed significantly higher GLUT-1 and P-cadherin expression than EGFR, warranting further investigation as HNSCC FI targets.

Addition of tumor microenvironment immune cell composition to improve the performance of a predictive model for oral squamous cell carcinoma.

BACKGROUND: Conventional clinicopathological characteristics insufficiently predict prognosis in oral squamous cell carcinoma (OSCC). We aimed to assess the added predictive value of tumor microenvironment immune cell composition (TMICC) in addition to conventional clinicopathological characteristics. METHODS: Primary tumor samples of 290 OSCC patients were immunohistochemically stained for CD4, CD8, CD20, CD68, CD163, CD57, FoxP3 and Programmed cell Death Ligand 1. Additionally, clinicopathological characteristics were obtained from patients' medical files. Predictive models were trained and validated by conducting Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses with cross-validation. To quantify the added predictive power of TMICC within models, receiver operating characteristic (ROC) analyses were used. RESULTS: Recurrence occurred in 74 patients (25.5%). Conventional clinicopathological characteristics (tumor localization, pathological T-stage, pathological N-stage, extracapsular spread, resection margin, differentiation grade, perineural invasion, lymphovascular invasion) and treatment modality, were used to build a LASSO logistic regression-based predictive model. Addition of TMICC to the model resulted in a comparable AUC of respectively 0.79 (±0.01) and 0.76 (±0.1) in the training and test sets. The model indicated that high numbers of CD4+ T cells protected against recurrence. Lymph node metastasis, extracapsular spread, perineural invasion, positive surgical margins and reception of adjuvant treatment were associated with increased risk for recurrence. CONCLUSIONS: The TMICC, specifically the number of CD4+ T cells, is an independent predictor , however, addition to conventional clinicopathological characteristics does not improve the performance of a predictive model for recurrence in OSCC.