The purpose of this study was to develop and validate a new software, HER2-CONNECT(TM), for digital image analysis of the human epidermal growth factor receptor 2 (HER2) in breast cancer specimens. The software assesses immunohistochemical (IHC) staining reactions of HER2 based on an algorithm evaluating the cell membrane connectivity. The HER2-CONNECT algorithm was aligned to match digital image scorings of HER2 performed by 5 experienced assessors in a training set and confirmed in a separate validation set. The training set consisted of 167 breast carcinoma tissue core images in which the assessors individually and blinded outlined regions of interest and gave their HER2 score 0/1+/2+/3+ to the specific tumor region. The validation set consisted of 86 core images where the result of the automated image analysis software was correlated to the scores provided by the 5 assessors. HER2 fluorescence in situ hybridization (FISH) was performed on all cores and used as a reference standard. The overall agreement between the image analysis software and the digital scorings of the 5 assessors was 92.1% (Cohen's Kappa: 0.859) in the training set and 92.3% (Cohen's Kappa: 0.864) in the validation set. The image analysis sensitivity was 99.2% and specificity 100% when correlated to FISH. In conclusion, the Visiopharm HER2 IHC algorithm HER2-CONNECT(TM) can discriminate between amplified and non-amplified cases with high accuracy and diminish the equivocal category and thereby provides a promising supplementary diagnostic tool to increase consistency in HER2 assessment.

These data support the use of the SLNB technique as an accurate and safe staging tool in patients with OSCC with a cN0 neck. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1033-E1040, 2016.

Intratumor heterogeneity may contribute to the ambiguous clinical results on PD-L1 status as a predictor for immunotherapy response in patients with HNSCC. This decreases the utility of PD-L1 expression from single tumour biopsies as a predictive biomarker. In this prospective study, intratumor heterogeneity of PD-L1 expression in HNSCC was investigated with both Tumour Proportion Score (TPS) and Combined Positive Score (CPS). Thirty-three whole surgical specimens from 28 patients with HNSCC were included. PD-L1 expression in six random core biopsies from each surgical specimen was used to assess the concordance between multiple biopsies and the negative predictive value of a single negative core biopsy. With 1% cut off, 36% of the specimens were concordant with TPS and 52% with CPS. With a 50% cut-off value the concordance was 70% with TPS and 55% with CPS. Defining a tumour as positive if just a single-one of the biopsies was positive, the negative predictive value (NPV) of a single negative core biopsy was 38.9 and 0% (1% cut off), and 79.9% and 62.8% (50% cut off) for TPS and CPS, respectively. In conclusion, PD-L1 positivity varies markedly within the tumour, both with TPS and CPS, challenging the utility of this biomarker.

Myofibroblastoma of the breast is a rare benign mesenchymal tumor. The literature describes relatively few cases of this type of tumor. We report on a new case of myofibroblastoma in a 65-year old man successfully managed at our institution. The purpose of this case report is to highlight characteristics and differential diagnosis of this rare neoplasm.

PurposeUrokinase-like Plasminogen Activator Receptor (uPAR) is overexpressed in a variety of carcinoma types, and therefore represents an attractive imaging target. The aim of this study was to assess the feasibility of two uPAR-targeted probes for PET and fluorescence tumor imaging in a human xenograft tongue cancer model.Experimental design and resultsTumor growth of tongue cancer was monitored by bioluminescence imaging (BLI) and MRI. Either ICG-Glu-Glu-AE105 (fluorescent agent) or 64Cu-DOTA-AE105 (PET agent) was injected systemically, and fluorescence imaging or PET/CT imaging was performed. Tissue was collected for micro-fluorescence imaging and histology. A clear fluorescent signal was detected in the primary tumor with a mean in vivo tumor-to-background ratio of 2.5. Real-time fluorescence-guided tumor resection was possible, and sub-millimeter tumor deposits could be localized. Histological analysis showed co-localization of the fluorescent signal, uPAR expression and tumor deposits. In addition, the feasibility of uPAR-guided robotic cancer surgery was demonstrated. Also, uPAR-PET imaging showed a clear and localized signal in the tongue tumors.ConclusionsThis study demonstrated the feasibility of combining two uPAR-targeted probes in a preclinical head and neck cancer model. The PET modality provided preoperative non-invasive tumor imaging and the optical modality allowed for real-time fluorescence-guided tumor detection and resection. Clinical translation of this platform seems promising.

The results of the present study are in accordance with previous studies, and shows that the proposed methodology for standardized evaluation of TILs renders an acceptable inter-observer agreement. The findings, however, indicate that assessment of TILs needs further refinement, and is in support of the latest St. Gallen Consensus, that routine reporting of TILs for early breast cancer is not ready for implementation in a clinical setting.

It is challenging to identify at diagnosis those patients with early oral squamous cell carcinoma (OSCC), who have a poor prognosis and those that have a high risk of harboring occult lymph node metastases. The aim of this study was to develop a standardized and objective digital scoring method to evaluate the predictive value of tumor budding. We developed a semi-automated image-analysis algorithm, Digital Tumor Bud Count (DTBC), to evaluate tumor budding. The algorithm was tested in 222 consecutive patients with early-stage OSCC and major endpoints were overall (OS) and progression free survival (PFS). We subsequently constructed and cross-validated a binary logistic regression model and evaluated its clinical utility by decision curve analysis. A high DTBC was an independent predictor of both poor OS and PFS in a multivariate Cox regression model. The logistic regression model was able to identify patients with occult lymph node metastases with an area under the curve (AUC) of 0.83 (95% CI: 0.78–0.89, P <0.001) and a 10-fold cross-validated AUC of 0.79. Compared to other known histopathological risk factors, the DTBC had a higher diagnostic accuracy. The proposed, novel risk model could be used as a guide to identify patients who would benefit from an up-front neck dissection.

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