Introduction: Immunohistochemical Ki67 labelling index (Ki67 LI) reflects proliferative activity and is a potential prognostic/predictive marker of breast cancer. However, its clinical utility is hindered by the lack of standardized measurement methodologies. Besides tissue heterogeneity aspects, the key element of methodology remains accurate estimation of Ki67-stained/counterstained tumour cell profiles. We aimed to develop a methodology to ensure and improve accuracy of the digital image analysis (DIA) approach. Methods: Tissue microarrays (one 1-mm spot per patient, n = 164) from invasive ductal breast carcinoma were stained for Ki67 and scanned. Criterion standard (Ki67-Count) was obtained by counting positive and negative tumour cell profiles using a stereology grid overlaid on a spot image. DIA was performed with Aperio Genie/Nuclear algorithms. A bias was estimated by ANOVA, correlation and regression analyses. Calibration steps of the DIA by adjusting the algorithm settings were performed: first, by subjective DIA quality assessment (DIA-1), and second, to compensate the bias established (DIA-2). Visual estimate (Ki67-VE) on the same images was performed by five pathologists independently. Results: ANOVA revealed significant underestimation bias (P < 0.05) for DIA-0, DIA-1 and two pathologists’ VE, while DIA-2, VE-median and three other VEs were within the same range. Regression analyses revealed best accuracy for the DIA-2 (R-square = 0.90) exceeding that of VE-median, individual VEs and other DIA settings. Bidirectional bias for the DIA-2 with overestimation at low, and underestimation at high ends of the scale was detected. Measurement error correction by inverse regression was applied to improve DIA-2-based prediction of the Ki67-Count, in particular for the clinically relevant interval of Ki67-Count < 40%. Potential clinical impact of the prediction was tested by dichotomising the cases at the cut-off values of 10, 15, and 20%. Misclassification rate of 5-7% was achieved, compared to that of 11-18% for the VE-median-based prediction. Conclusions: Our experiments provide methodology to achieve accurate Ki67-LI estimation by DIA, based on proper validation, calibration, and measurement error correction procedures, guided by quantified bias from reference values obtained by stereology grid count. This basic validation step is an important prerequisite for high-throughput automated DIA applications to investigate tissue heterogeneity and clinical utility aspects of Ki67 and other immunohistochemistry (IHC) biomarkers.

By allowing intercellular communication between cells, tunneling nanotubes (TNTs) could play critical role in cancer progression. If TNT formation is known to require cytoskeleton remodeling, key mechanism controlling their formation remains poorly understood. The cells of human bronchial (HBEC-3, A549) or mesothelial (H2452, H28) lines are transfected with different siRNAs (inactive, anti-RASSF1A, anti-GEFH1 and / or anti-Rab11). At 48 h post-transfection, i) the number and length of the nanotubes per cell are quantified, ii) the organelles, previously labeled with specific tracers, exchanged via these structures are monitored in real time between cells cultured in 2D or 3D and in normoxia, hypoxia or in serum deprivation condition. We report that RASSF1A, a key-regulator of cytoskeleton encoded by a tumor-suppressor gene on 3p chromosome, is involved in TNTs formation in bronchial and pleural cells since controlling proper activity of RhoB guanine nucleotide exchange factor, GEF-H1. Indeed, the GEF-H1 inactivation induced by RASSF1A silencing, leads to Rab11 accumulation and subsequent exosome releasing, which in turn contribute to TNTs formation. Finally, we provide evidence involving TNT formation in bronchial carcinogenesis, by reporting that hypoxia or nutriment privation, two almost universal conditions in human cancers, fail to prevent TNTs induced by the oncogenic RASSF1A loss of expression. This finding suggests for the first time that loss of RASSF1A expression could be a potential biomarker for TNTs formation, such TNTs facilitating intercellular communication favoring multistep progression of bronchial epithelial cells toward overt malignancy.

RASSF1A, a tumor suppressor gene, is frequently inactivated in lung cancer leading to a YAP-dependent epithelial-mesenchymal transition (EMT). Such effects are partly due to the inactivation of the anti-migratory RhoB GTPase via the inhibitory phosphorylation of GEF-H1, the GDP/GTP exchange factor for RhoB. However, the kinase responsible for RhoB/GEF-H1 inactivation in RASSF1A-depleted cells remained unknown. NDR1/2 inactivation by siRNA or shRNA effects on epithelial-mesenchymal transition, invasion, xenograft formation and growth in SCID−/− Beige mice, apoptosis, proliferation, cytokinesis, YAP/TAZ activation were investigated upon RASSF1A loss in human bronchial epithelial cells (HBEC). We demonstrate here that depletion of the YAP-kinases NDR1/2 reverts migration and metastatic properties upon RASSF1A loss in HBEC. We show that NDR2 interacts directly with GEF-H1 (which contains the NDR phosphorylation consensus motif HXRXXS/T), leading to GEF-H1 phosphorylation. We further report that the RASSF1A/NDR2/GEF-H1/RhoB/YAP axis is involved in proper cytokinesis in human bronchial cells, since chromosome proper segregation are NDR-dependent upon RASSF1A or GEF-H1 loss in HBEC. To summarize, our data support a model in which, upon RASSF1A silencing, NDR2 gets activated, phosphorylates and inactivates GEF-H1, leading to RhoB inactivation. This cascade induced by RASSF1A loss in bronchial cells is responsible for metastasis properties, YAP activation and cytokinesis defects.

The following paper gives a detailed description of the oogenesis cycle for the European Plaice (Pleuronectes platessa), from oogonia to post-ovulatory follicle, including ovarian follicle and zona pellucida sizes. Noteworthy particularities were the difficulty in identifying cortical alveoli due to their very small size. Quantitative histology (stereology) on histological slides was used to determine a first size at maturity for females from the English Channel, which was found to be smaller compared to the literature (19 cm). Stereology also determined a first spawning event starting in January, with a peak in February and ongoing until March. Moreover, the use of stereology showed misclassifications for individuals categorized into a maturity phase using a macroscopic visual method. Misclassifications were found with individuals that had spawned (D) but were put under the immature (A) phase, and individuals in development (B) classified under D.