Her2 challenge contest: a detailed assessment of automated her2 scoring algorithms in whole slide images of breast cancer tissues

Aims Evaluating expression of the Human epidermal growth factor receptor 2 (Her2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of the diagnostic assessment of BCa due to its recognised importance as a predictive and prognostic marker in clinical practice. However, visual scoring of Her2 is subjective and consequently prone to inter-observer variability. Given the prognostic and therapeutic implications of Her2 scoring, a more objective method is required. In this paper, we report on a recent automated Her2 scoring contest, held in conjunction with the annual PathSoc meeting held in Nottingham in June 2016, aimed at systematically comparing and advancing the state-of-the-art Artificial Intelligence (AI) based automated methods for Her2 scoring. Methods and Results The contest dataset comprised of digitised whole slide images (WSI) of sections from 86 cases of invasive breast carcinoma stained with both Haematoxylin & Eosin (H&E) and IHC for Her2. The contesting algorithms automatically predicted scores of the IHC slides for an unseen subset of the dataset and the predicted scores were compared with the “ground truth” (a consensus score from at least two experts). We also report on a simple Man vs Machine contest for the scoring of Her2 and show that the automated methods could beat the pathology experts on this contest dataset. Conclusions This paper presents a benchmark for comparing the performance of automated algorithms for scoring of Her2. It also demonstrates the enormous potential of automated algorithms in assisting the pathologist with objective IHC scoring

The Role of FOXD1 in Clear Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) is the 8th most common cancer in the United States, with the clear cell variant (ccRCC) being the most prevalent. Over 14,000 people die every year to RCC, with rates continuing to increase with an aging general population. Patients suffering from metastatic RCC (mRCC) have extremely poor prognoses, with a 5-year survival of only 11.2%. Current treatment options include resection of primary lesions, tyrosine kinase inhibition (Sunitinib, Pazopanib), mTOR inhibition (Temsirolimus, Everolimus), and immune checkpoint inhibition (Nivolumab, Atezolizumab). Recent attention has been drawn to inhibition of transcription factors like HIF2α (Belzutifan). There is a need to discover new targets, as well as gain better insight into the molecular signatures for patient specific drug response prediction. The work presented herein presents our investigations into the transcription factor FOXD1, and the role it plays in regulating ccRCC growth. We knocked out FOXD1 in a classic model ccRCC cell line, the 786-O (786-OFOXD1null). Loss of FOXD1 led to growth inhibition and reduced tumor forming capacity in vivo. We uncovered a cell-cycle specific role of FOXD1 in promoting progression through the G2/M phase and phosphorylation of Histone H3. Due to the limitations in vivo using 786-OFOXD1null, we designed an in vitro tumor model meant to recapitulate the human tumor microenvironment. This model was based on extracellular matrix profile of patient ccRCC tissue through proteomic analysis. Using this model, we were able to create tumor avatars containing heterogenous cell populations. In addition to this, the model system could be used to analyze 3D tumor growth of cell lines in response to drug treatments. We used this model system to examine how FOXD1 regulates the cell cycle and 3D tumor growth. An analysis pipeline was devised to delineate targets downstream of FOXD1 that utilized RNA sequencing, predicted transcription factor binding, toxicity screening, and cell cycle analysis. Using our newly devised 3D tumor model allowed us to confirm the applicability of this approach to a broader population of primary tumor cells. This pipeline uncovered novel signaling pathways regulating cell cycle progression in RCC lines and may have therapeutic implications

In Vivo Fluorescence Imaging of E-Selectin: Quantitative Detection of Endothelial Activation in Arthritis

Rheumatoid arthritis (RA) is a chronic progressive systemic inflammatory disease, characterized by synovial inflammation and localized destruction of cartilage and bone. Heterogeneity in the clinical presentation of RA and uncertainty about which patients will respond to treatment makes diagnosis and management challenging. Fluorescent imaging in the near infrared (NIR) spectrum significantly decreases tissue autofluorescence offering unique potential to detect specific molecular targets in vivo. E-selectin or endothelial adhesion molecule-1 (ELAM-1), a 115kDa glycoprotein induced on endothelial cells in response to pro-inflammatory cytokines involved in RA, such as interleukin (IL)-1 beta and tumour necrosis factor alpha (TNF alpha). E-selectin has been well validated as a potential biomarker of disease activity. My study aimed to investigate whether E-selectin targeted optical imaging in vivo could be developed as a sensitive, specific and quantifiable preclinical molecular imaging technique, and also whether this approach could be used to delineate the molecular effects of novel therapies. I utilised anti-E-selectin antibody labelled with NIR fluorophore in a mouse model of paw swelling induced by intra-plantar injection of TNF alpha, and in acute collagen-induced arthritis (CIA) in DBA/1 mice, a widely used model of RA. E-selectin generated signal, localised to points of maximal clinical inflammation in the inflamed mouse paw in both models with significant differences to control antibody. Binding of anti-E-selectin antibody was also demonstrated by immunohistochemistry in both models. The ability of E-selectin targeted imaging to detect sub-clinical endothelial activation was also investigated, demonstrating that E-selectin may be an excellent way of determining subclinical vascular activation in CIA. Finally the effect of novel targeted therapy – RB200 which blocks epidermal growth factor (EGF) signalling was investigated. This demonstrated that E-selectin targeted signal could be absolutely abrogated to a level seen in unimmunised healthy control animals, following combination treatment with RB200 and the TNF alpha inhibitor etanercept. E-selectin targeted optical imaging is a viable in vivo imaging technique that can also be applied to quantify disease and investigate the effects of novel molecular therapies. It holds significant promise as a molecular imaging technique for future translation into the clinic for patients with rheumatoid arthritis and other inflammatory diseases

Immunohistochemistry image analysis : protein, nuclei and gland

This thesis focus on the analysis of digitized microscopic image, especially on IHC stained colour images. The corresponding contributions focused on the automatic detection of stain colour and glands, the segmentation and quantification of cell nuclei, the analysis of liver cirrhosis and the development of a semi-automatic toolbox. Colour is the most important feature in the analysis of immunostained images. We developed a statistical colour detection model for stain colour detection based on the histograms of collected colour pixels. This is acting on the approach "what you see is what you get" which outperforms the other methods on the detection of several kinds of stain colour. Verifying the presence of nuclei and quantifying positive nuclei is the foundation of cancer grading. We developed a novel seeded nuclei segmentation method which greatly improves the segmentation accuracy and reduces both over-segmentation and under-segmentation. This method has been demonstrated to be robust and accurate in both segmentation and quantification against manual labelling and counting in the evaluation process. The analysis of gland architecture, which reflects the cancer stage, has evolved into an important aspect of cancer detection. A novel morphology-based approach has been developed to segment gland structures in H-DAB stained images. This method locates the gland by focusing on its morphology and intensity characteristics, which covers variations in stain colours in different IHC images. The evaluation results have demonstrated the improvements of accuracy and efficiency. For the successive development of three methods, we put them in a semi-automatic toolbox for the aid of IHC image analysis. It can detect different kinds of stain colour and the basic components in an IHC image. The user created models and parameters can be saved and transferred to different users for the reproduction of detection results in different laboratories. To demonstrate the flexibility of our developed stained colour detection technique, the tool has been extended to the analysis of liver cirrhosis. It is a novel method based on our statistical colour detection model which greatly improves the analysis accuracy and reduces the time cost

Development of biomarkers for the risk stratification and targeted therapy of Barrett's oesophagus and oesophageal adenocarcinoma

Barrett's oesophagus is the most important risk factor for the development of oesophageal adenocarcinoma (OA), but progression is unpredictable. Dysplasia predicts which Barrett’s patients are at greatest risk for OA but achieving the diagnosis can be challenging. Immunohistochemistry with p53 is recommended as an adjunct to assist with dysplasia diagnosis. This thesis will examine if replication licensing factors and DNA ploidy status are as good if not better than p53 to assist in the diagnosis of dysplasia. Overexpression of HER2 in foregut cancer is an indication for HER2 targeted treatments. Its influence on prognosis is less understood. The relationships between clinicopathological variables, HER2 overexpression and prognosis will next be evaluated. Current ablative techniques for Barrett’s neoplasia are limited to superficial disease. Photodynamic therapy was a treatment for Barrett’s that could penetrate more deeply into diseased tissue but was limited by the side effects of off-target photosensitivity. Combining targeting vehicles such as antibodies to newer and more deeply penetrating photosensitiser drugs, may overcome the previous limitations of this technology. A photosensitive ADC against HER2 will be created and its efficacy in vitro and in vivo evaluated. However, even the most effective ADC against HER2 will not treat the majority of cancers, as we will show HER2 is only expressed in the minority of foregut tumours. The final experiments will look to characterise the mucin MUC1 in Barrett’s and associated neoplasia. Studies have previously shown it to be present in up to 100% of cancers while others say far fewer. We will show proof of principle data for the development of a MUC1 targeting photosensitive ADC in vitro and postulate how it may in future enable treatment of locoregional invasive tumours endoscopically

A novel image analysis approach to characterise the effects of dietary components on intestinal morphology and immune system in Atlantic salmon

The intestinal tract of salmonids provides a dynamic interface that not only mediates nutrient uptake but also functions as the first line of defence against ingested pathogens. Exposure of the immune system to beneficial microorganisms and different dietary immunostimulants via the intestine has been shown to prime the immune system and help in the development of immune competence. Furthermore, the morphology and function of teleostean intestines are known to respond to feed components and to ingested and resident bacterial communities. Histological appraisal is still generally considered to be the gold standard for sensitive assessment of the effects of such dietary modulation. The aim of the present study was to improve understanding of salmonid intestinal function, structure and dynamics and to use the knowledge gained to develop a model for analysis, which would allow intestinal health to be assessed with respect to different intestinal communities and feed components. Virtual histology, the process of assessing digital images of histological slides, is gaining momentum as an approach to supplement traditional histological evaluation methodologies and at the same time, image analysis of digitised histological sections provides a practical means for quantifiable assessment of structural and functional changes in tissues, being both objective and reproducible. This project focused on the development of a rapid, practical analytical methodology based on advanced image analysis, that was able to measure and characterise a range of features of the intestinal histology of Atlantic salmon in a quantitative manner. In the first research chapter, the development of a novel histological assessment system based upon advanced image analysis was described, this being developed with the help of a soybean feed model known to induce enteropathy in Atlantic salmon. This tool targeted the evaluation of the extent of morphological changes occurring in the distal intestine of Atlantic salmon following dietary modulation. The final analytical methodology arrived at, could be conducted with minimal user-interaction, allowing rapid and objective assessment of 12 continuous variables per histological frame analysed. The processing time required for each histological frame was roughly 20-25 min, which greatly improved the efficiency of conducting such a quantitative assessment with respect to the time taken for a subjective semi-quantitative alternative approach. Significant agreement between the fully automated and the manual morphometric image segmentation was achieved, however, the strength of this quantitative approach was enhanced by the employment of interactive procedures, which enabled the operator / observer to rectify preceding automated segmentation steps, and account for the specimen’s variations. Results indicated that image analysis provided a viable alternative to a pathologist’s manual scoring, being more practical and time-efficient. In the second research chapter, feeding Atlantic salmon a high inclusion level of unrefined SBM (25 %) produced an inflammatory response in the distal intestine as previously described by other authors. The model feed trial successfully generated differentiable states, although these were not, for the most part, systemically differentiable through the majority of standard immunological procedures used, being only detectable morphologically. Quantitation of morphometric parameters associated with histological sections using the newly developed image analysis tool successfully allowed identification of major morphological changes. Image analysis was thus shown to provide a powerful tool for describing the histomorphological structure of Atlantic salmon distal intestine. In turn, the semi-automated image analysis methods were able to distinguish normal intestinal mucosa from those affected by enteritis. While individual parameters were less discriminatory, use of multivariate techniques allowed better discrimination of states and is likely to prove the most productive approach in further studies. Work described in the third research chapter sought to validate the semi-automated image analysis system to establish that it was measuring the parameters it was purported to be measuring, and to provide reassurance that it could reliably measure pre-determined features. This study, using the same sections for semi-quantitative and quantitative analyses, demonstrated that the quantitative indices performed well when compared to analogous semi-quantitative descriptive parameters of assessment for enteritis prognosis. The excellent reproducibility and accuracy performance levels indicated that the image analysis system was a useful and reliable morphometric method for the quantification of SB-induced enteritis in salmon. Other characteristics such as rapidity, simplicity and adaptability favour this method for image analysis, and are particularly useful where less experienced interpreters are performing the analysis. The work described in the fourth research chapter characterised changes in the morphology of the intestinal epithelial cells occurring as a result of dietary modulation and aspects of inflammatory infiltration, using a selected panel of enzyme and IHC markers. To accomplish this, image analysis techniques were used to evaluate and systematically optimise a quantitative immunolabelling assessment protocol. Digital computer-assisted quantification of labelling for cell proliferation and regeneration; programmed cell death or apoptosis; EGCs and t-cell like infiltrates; mobilisation of stress-related protein regenerative processes and facilitation of nutrient uptake and ion transport provided encouraging results. Through the description of the intestinal cellular responses at a molecular level, such IHC expression profiling further characterised the inflammatory reaction generated by the enteropathic diet. In addition, a number of potential diagnostic parameters were described for fish intestinal health e.g. the relative levels of antigenicity and the spatial distribution of antigens in tissues. Work described in the final research chapter focused on detailed characterisation of intestinal MCs / EGCs in order to try to elucidate their functional role in the intestinal immune responses. Through an understanding of their distribution, composition and ultrastructure, the intention was to better characterise these cells and their functional properties. The general morphology, histochemical characteristics and tissue distribution of these cells were explored in detail using histochemical, IHC and immunogold staining / labelling, visualised using light, confocal and TEM microscopy. Despite these extensive investigations, their physiological function and the content of their granules still remain somewhat obscure, although a role as immunodulatory cells reacting to various exogeneous signals through a finely regulated process and comparable to that causing the degranulation of mammalian MCs is suggested. The histochemical staining properties demonstrated for salmonid MCs / EGCs seem to resemble those of mammalian mucosal mast cells, with both acidophilic and basophilic components in their granules, and a granule content containing neuromodulator / neurotransmitter-peptides such as serotonin, met-enkephalin and substance-p. Consequently, distinguishable bio-chromogenic markers have been identified that are of utility in generating a discriminatory profile for image analysis of such cells

Immunohistochemistry image analysis : protein, nuclei and gland

This thesis focus on the analysis of digitized microscopic image, especially on IHC stained colour images. The corresponding contributions focused on the automatic detection of stain colour and glands, the segmentation and quantification of cell nuclei, the analysis of liver cirrhosis and the development of a semi-automatic toolbox. Colour is the most important feature in the analysis of immunostained images. We developed a statistical colour detection model for stain colour detection based on the histograms of collected colour pixels. This is acting on the approach "what you see is what you get" which outperforms the other methods on the detection of several kinds of stain colour. Verifying the presence of nuclei and quantifying positive nuclei is the foundation of cancer grading. We developed a novel seeded nuclei segmentation method which greatly improves the segmentation accuracy and reduces both over-segmentation and under-segmentation. This method has been demonstrated to be robust and accurate in both segmentation and quantification against manual labelling and counting in the evaluation process. The analysis of gland architecture, which reflects the cancer stage, has evolved into an important aspect of cancer detection. A novel morphology-based approach has been developed to segment gland structures in H-DAB stained images. This method locates the gland by focusing on its morphology and intensity characteristics, which covers variations in stain colours in different IHC images. The evaluation results have demonstrated the improvements of accuracy and efficiency. For the successive development of three methods, we put them in a semi-automatic toolbox for the aid of IHC image analysis. It can detect different kinds of stain colour and the basic components in an IHC image. The user created models and parameters can be saved and transferred to different users for the reproduction of detection results in different laboratories. To demonstrate the flexibility of our developed stained colour detection technique, the tool has been extended to the analysis of liver cirrhosis. It is a novel method based on our statistical colour detection model which greatly improves the analysis accuracy and reduces the time cost

Studies of the increased gastrin release associated with Helicobacter pylori infection in duodenal ulcer disease

Duodenal ulcer disease is strongly associated with infection of the gastric antrum by Helicobacter pylori (H. pylori), possibly through the exaggerated plasma gastrin response associated with this organism. The work described in this thesis investigates aspects of both the cause and the effect of this increase in gastrin secretion in duodenal ulcer patients. Chapter 2 provides further evidence that H pylori is responsible for the exaggerated gastrin response since when duodenal ulcers are healed by sucralfate, which does not eradicate H pylori, the gastrin response is unchanged. However, unexpectedly, this treatment decreased basal gastric acid secretion. The results of studies described in chapter 3 suggest that the exaggerated gastrin response occurs by a mechanism independent of luminal pH and with no apparent change in the meal-stimulated secretion of acid or pepsin. Despite the fall in meal-stimulated gastrin the peak acid output also remained unchanged a year after the eradication of H pylori (chapter 4) but the basal acid output appeared to decrease in this small study. The work described in chapter 5 confirms this fact; successful eradication of the organism decreased both basal plasma gastrin concentrations and basal acid secretion, without altering the sensitivity of the parietal cell to circulating gastrin. This may be how the eradication of H pylori prevents ulcer recurrences. The cause of the hypergastrinaemia was addressed in the final chapters. Methods were developed to measure somatostatin mRNA from endoscopic biopsies as a surrogate marker of local somatostatin release. It was then established that the hypergastrinaemia seen in pernicious anaemia is associated with a deficiency of somatostatin mRNA (chapter 6). Finally, an increase in both somatostatin-secreting cells and somatostatin mRNA was found after the eradication of H pylori, implying that this bacterium increases gastrin release by the depletion of somatostatin