Medullary breast cancer (MBC) is a rare, diagnostically difficult, pathological subtype. Despite being high grade, it has a good prognosis. MBC patients have an excess of BRCA1 germ-line mutation and reliable identification of MBC could help to identify patients at risk of carrying germline BRCA1 mutations or in whom chemotherapy could be avoided. The aim of this study was therefore to improve diagnosis by establishing an MBC protein expression profile using immunohistochemistry (IHC) on tissue-microarrays (TMA). Using a series of 779 breast carcinomas ('EC' set), diagnosed initially as MBC, a double-reading session was carried out by several pathologists on all of the histological material to establish the diagnosis as firmly as possible using a 'medullary score'. Only MBCs with high scores, i.e. typical MBC (TMBC) (n=44) and non-TMBC grade III with no or low scores (n=160), were included in the IHC study. To validate the results obtained on this first set, a control series of TMBC (n=17) and non-MBC grade III cases (n=140) ('IPC' set) was studied. The expression of 18 proteins was studied in the 61 TMBCs and 300 grade III cases from the two sets. The global intra-observer concordance of the first reading for the diagnosis of TMBC was 94%, with almost perfect kappa (kappa) of 0.815. TMBC was characterized by a high degree of basal/myoepithelial differentiation. In multivariate analysis with logistic regression, TMBC was defined by the association of P-cadherin (R=2.29), MIB1 > 50 (R=3.80), ERBB2 negativity (R=2.24) and p53 positivity (RR=1.45).

Histopathological diagnosis of lymphomas represents a challenge requiring either expertise or centralised review, and greatly depends on the technical process of tissue sections. Hence, we developed an innovative deep-learning framework, empowered with a certainty estimation level, designed for haematoxylin and eosin-stained slides analysis, with special focus on follicular lymphoma (FL) diagnosis. Whole-slide images of lymph nodes affected by FL or follicular hyperplasia were used for training, validating, and finally testing Bayesian neural networks (BNN). These BNN provide a diagnostic prediction coupled with an effective certainty estimation, and generate accurate diagnosis with an area under the curve reaching 0.99. Through its uncertainty estimation, our network is also able to detect unfamiliar data such as other small B cell lymphomas or technically heterogeneous cases from external centres. We demonstrate that machine-learning techniques are sensitive to the pre-processing of histopathology slides and require appropriate training to build universal tools to aid diagnosis.

Poorer functional results are significantly associated with an elevation in the JL compared to the contralateral healthy knee. In those patients with a suitable contralateral knee the JL level to restore can be assessed by the distance between the femoral condyle and the apex of the fibular head of the contralateral knee.

Background:CD70 is a costimulatory molecule of the tumour necrosis factor family expressed in activated immune cells and some solid tumours. In lymphocytes CD70 triggers T cell-mediated cytotoxicity and mitogen-activated protein kinase phosphorylation.Methods:We evaluated the expression of CD70 in biopsies and melanoma cell lines. Using melanoma cell lines positive or not for CD70, we analysed CD70 function on melanoma progression.Results:We report CD70 expression in human melanoma cell lines and tumour cells from melanoma biopsies. This expression was observed in 95% of primary melanomas but only 37% of metastases. Both monomeric and trimeric forms of CD70 were detected in tumour cell membrane fractions, whereas cytoplasmic fractions contained almost exclusively monomeric CD70. In vitro and in vivo experiments demonstrated that CD70 expression inhibited melanoma cell migration, invasion and pulmonary metastasis implantation independently of the tumour immune microenvironment. Increasing the levels of the trimeric form of CD70 through monoclonal antibody binding led to an increase in CD70+ melanoma cell invasiveness through MAPK pathway activation, RhoE overexpression, ROCK1 and MYPT1 phosphorylation decrease, and stress fibres and focal adhesions disappearance.Conclusions:Our results describe a new non-immunological function of melanoma-expressed CD70, which involves melanoma invasiveness through MAPK pathway, RhoE and cytoskeletal modulation.

BackgroundWhen invasive components are discovered at mastectomy for vacuum-assisted biopsy (VAB)-diagnosed ductal carcinoma in situ (DCIS), the only option available is axillary lymph node dissection (ALND). The primary aim of this prospective multicenter trial was to determine the benefit of performing upfront sentinel lymph node (SLN) biopsy for these patients. The secondary aim was to determine DCIS factors associated with microinvasion or invasion.MethodsThe SLN procedure was performed during mastectomy, and for positive SLN an ALND was performed during the same intervention. A tissue microarray containing DCIS lesions from the mastectomy specimens was subsequently performed.ResultsFrom May 2008 to December 2010, 228 patients were enrolled from 14 French cancer centers, including 192 eligible patients with pure DCIS on VAB and successful SLN procedures. ALND was avoided for 51 [67 %; 95 % confidence interval (CI), 56–77 %] of all the patients who had microinvasive DCIS or DCIS associated with invasive carcinoma at mastectomy and a negative SLN. Of the 192 patients, 76 (39 %) with VAB-diagnosed DCIS were upgraded after mastectomy to micro (n = 20) or invasive disease (n = 56). The rate of positive SLN for patients with DCIS on VAB was 14 %. High nuclear grade of DCIS was associated with greater risk of microinvasion and invasion, and HER2-amplified DCIS was associated with greater risk of invasion.ConclusionsUnderestimation of invasive components is high when DCIS is diagnosed by VAB in patients undergoing mastectomy. Upfront SLN for patients with VAB-diagnosed extensive DCIS avoids unnecessary ALND for two-thirds of patients with micro or invasive disease on mastectomy.Electronic supplementary materialThe online version of this article (doi:10.1245/s10434-015-4476-5) contains supplementary material, which is available to authorized users.