From Research to Clinical Diagnostics: Developing and Validating Biomarkers and Artificial Intelligence for Pathology

In 2021, digital pathology was deployed in the hospitals of the western health region of Norway. Histological tissue specimens previously viewed under the microscope on glass slides, are now being scanned, and whole slide images (WSIs) are viewed digitally. Digitisation enables the use of advanced technologies to take over repetitive and timeconsuming tasks such as biomarker quantification. Furthermore, digital image analysis (DIA) and artificial intelligence (AI) can be used to perform complex tasks such as pattern recognition and classification, to assist healthcare professionals. The research presented in this thesis aims to explore methods which may improve current diagnostic and prognostic guidelines for breast cancer and endometrial hyperplasia in pathology. To challenge current limitations of visual assessments and investigate if addition of quantitative methodology and AI-assistance tools can improve reproducibility and accuracy of diagnosis and prognosis. The end goal to reduce the risk of under- and over-treatment of these patients. In Norway, 3,000 to 4,000 women will be diagnosed with endometrial hyperplasia every year. This condition is characterised by the excessive proliferation of endometrial glands in the uterine lining. The diagnosis of endometrial hyperplasia has undergone several important evolutions in recent decades. However, the prognostic evaluation, to assess the likelihood of this condition to progress to endometrial cancer, is still limited by subjective visual assessment of tissue morphology. In the first study, the biomarkers PTEN and PAX2 were evaluated for their prognostic value in endometrial carcinogenesis. A quantitative method assessing PAX2 protein expression revealed prognostic separation of patients diagnosed with endometrial intraepithelial neoplasia with low- and high-risk of progression to cancer. In a second study, an AI-based tool was developed, to detect and quantify morphological features of endometrial hyperplasia. The tool (ENDOAPP) was able to identify patients with low-risk and high-risk for progression. Furthermore, its accuracy was equal to and marginally superior to a semi-quantitative morphometric method (D-score) and traditional visual classifications (WHO94, WHO20, EIN), respectively. To state that the diagnosis and treatment of cancer has a long history would be an understatement. The arrival of new technology, molecular advances and AI continues to revitalise the way cancer is viewed in the clinic. The measurement of proliferation in breast cancer has undisputed prognostic implications. However, quantification of proliferation markers is controversial citing lack of standardisation. AI may provide a promising solution for the establishment of improved methods for objective, automated, reproducible quantification of proliferation markers such as mitotic count and Ki67. In the third study, in-house and commercial DIA tools were investigated alongside manual Ki67 quantification methods for their prognostic capability and variability. It was observed that DIA tools were superior to their manual counterparts with regards to their discriminative ability for separation of low-risk and high-risk for distant metastasis free progression. Furthermore, the cut-offs currently used for binary risk categorisation of proliferation markers should be carefully re-evaluated if we wish to standardise quantification of Ki67. In the final study, a deep learning tool was investigated for the detection and quantification of mitotic count in several cancers, including breast cancer. It was observed that automated mitotic count was prognostic in multiple cancer types in addition to breast cancer, where it is routinely performed. It is important to emphasise that the results presented in this thesis are limited to the datasets presented. These were retrospective datasets, and often confined to a single hospital, with the exception of the fourth study. Therefore, the methods run the risk of overfitting and hidden bias. It is therefore imperative that these tools are validated in external datasets to ensure their robustness, uncover any bias or overfitting, and to confirm their prognostic validity. Although the studies presented in this thesis suggest the validity of investigating AI-tools for clinical use, further study to critically evaluate their worth is still required

Plant protection using arbuscular mycorrhizal fungi

The interaction between several species of arbuscular mycorrhizal fungi, micropropagated strawberry plants and Phytophthora fragariae, the pathogen which causes red stele disease of strawberry plants, was investigated. The optimum temperature for germination of zoospore cysts of P. fragariae in vitro was found to be 15°C, and growth of the emerging germ tube was significantly orientated towards the strawberry root tip. Cyst germination was reduced in the presence of a mycorrhizal strawberry root. The method of inoculation of strawberry plants with P. fragariae and assessment of the resulting disease affected the results and the conclusions drawn from the experiments, depending on the virulence of the P. fragariae strain used and the susceptibility of the strawberry cultivar. Elsanta was more susceptible to P. fragariae than the cultivar Rhapsody. A low level o f colonisation of Elsanta with the arbuscular mycorrhizal fungi Glomus mosseae, Glomus intraradices or Glomus fistulosum resulted in a significantly greater amount of total phosphorus in plant shoots compared to non-mycorrhizal plants, although further increases in the percentage of root colonisation by the fungi had no effect on the plants. The presence of these mycorrhizal fungi had no effect on disease due to subsequent inoculation of the plants by P. fragariae. Increasing colonisation of Elsanta by Scutellospora nodosa was correlated with a significant increase in plant size and additional phosphorus uptake. However, these same plants exhibited greater levels o f disease due to the following inoculation with P. fragariae. A low level of root colonisation of Elsanta by Acaulospora scrobiculata caused significant increases in plant size and phosphorus uptake up to a threshold level o f root colonisation beyond which further increases had no affect on the plant. Examination of biochemical markers in the form o f isozyme banding patterns extracted from spores of arbuscular mycorrhizal fungi was explored to assess its potential for use in strain identification, and discussed in relation to other available techniques. The results are discussed in relation to the utilisation of specific strains o f arbuscular mycorrhizal fungi as inoculants of micropropagated strawberry plants of particular cultivars with the potential to increase plant growth and reduce the level of disease due to soil-borne plant pathogens

Reaping the Benefits of Conservation Tillage: Implications of Increased Soil Organic Matter and Aggregation in Surface Soils

In light of the US Department of Agriculture’s initiatives to reduce herbicide application on agricultural lands by 10% and increase soil carbon sequestration by 15%, the agriculture industry is in need of a cultivation practice that allows for more efficient herbicide application and fosters soil carbon accumulation. Our study presents a broad evaluation of the ability of conservation tillage techniques to meet the demands of this goal while maintaining high crop yields. We investigate the implications of increased organic matter and improved soil structure in conservation tillage soils for the protection and storage of soil carbon within stable microaggregates and the retention of herbicide chemicals in the bulk soil. To do so, we complete a soil respiration study to analyze carbon storage in different soil size fractions and design a novel column system to analyze herbicide transport through surface soils. The results of this preliminary study suggest that conservation tillage is a viable method of fulfilling the USDA’s initiatives to ensure the sustainability of the agriculture industry in the face of climate change

Microbes in the Middle: Elevation Gradients Reveal Drivers of Belowground Ecosystem Processes with Climate Change

Elevation gradients are an excellent tool that allow scientists to investigate the impacts of temperature change within a single system. While the effects of elevation on aboveground plant communities have been well studied, the effects on microbially-mediated ecosystem function remain unclear. Here, we review how belowground ecosystem processes are affected both directly by temperature variation and indirectly through plant functional trait differences across elevation. A better understanding of the mechanisms that drive belowground ecosystem function will enable more accurate predictions of how ecosystems as a whole will respond to climate change

Laser enhanced high-intensity focused ultrasound thrombolysis: An in vitro study

This is the Published Version made available with the permission of the publisher. Copyright, Ecological Society of America.Laser-enhanced thrombolysis by high intensity focused ultrasound (HIFU) treatment was studied in vitro with bovine blood clots. To achieve laser-enhanced thrombolysis, laser light was employed to illuminate the sample concurrently with HIFU radiation, and ultrasound and laser parameters were optimized to achieve better thrombolysis efficiency. The results indicated that the thrombolysis efficiency increased when pulse length of HIFU wave, HIFU pressure, or laser fluence increases. Also, with the presence of laser, an enhanced effect of thrombolysis was observed.This study was supported in part byNIH Grant No. 1R03EB015077-01A1

Gelatinase-A (MMP-2), gelatinase-B (MMP-9) and membrane type matrix metalloproteinase-1 (MT1-MMP) are involved in different aspects of the pathophysiology of malignant gliomas

Matrix metalloproteinases (MMPs) have been implicated as important factors in gliomas since they may both facilitate invasion into the surrounding brain and participate in neovascularization. We have tested the hypothesis that deregulated expression of gelatinase-A or B, or an activator of gelatinase-A, MT1-MMP, may contribute directly to human gliomas by quantifying the expression of these MMPs in 46 brain tumour specimens and seven control tissues. Quantitative RT-PCR and gelatin zymography showed that gelatinase-A in glioma specimens was higher than in normal tissue; these were significantly elevated in low grade gliomas and remained elevated in GBMs. Gelatinase-B transcript and activity levels were also higher than in normal brain and more strongly correlated with tumour grade. We did not see a close relationship between the levels of expression of MT1-MMP mRNA and amounts of activated gelatinase-A. In situ hybridization localized gelatinase-A and MT1-MMP transcripts to normal neuronal and glia, malignant glioma cells and blood vessels. In contrast, gelatinase-B showed a more restricted pattern of expression; it was strongly expressed in blood vessels at proliferating margins, as well as tumour cells in some cases. These data suggest that gelatinase-A, -B and MT1-MMP are important in the pathophysiology of human gliomas. The primary role of gelatinase-B may lie in remodelling associated with neovascularization, whereas gelatinase-A and MT1-MMP may be involved in both glial invasion and angiogenesis. © 1999 Cancer Research Campaig