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Background- Mediastinal staging is the rate-limiting step prior to initiation of lung cancer treatment and is essential in identifying the most appropriate treatment for the patient. However, this process is often complex and involves multiple imaging modalities including invasive and non-invasive methods for the assessment of lymph nodes in the mediastinum which are error prone. The use of Artificial Intelligence may be able to provide more accurate and precise measurements and eliminate error associated with medical imaging. Methods-This thesis was conducted in three parts. In Part 1, we synthesized and critically appraised the methodological quality of existing studies that use Artificial Intelligence to diagnosis and stage lung cancer from thoracic imaging based on lymph node features. In Part 2, we determined the inter-rater reliability of segmentation of the ultrasonographic lymph node features performed by an experienced endoscopist (manually) compared to NeuralSeg (automatically). In Part 3, we developed and validated a deep neural network through a clinical prediction model to determine if NeuralSeg could learn and identify ultrasonographic lymph node features from endobronchial ultrasound images in patients undergoing lung cancer staging. Results- In Part 1, there were few studies in the Artificial Intelligence literature that provided a complete and detailed description of the design, Artificial Intelligence architecture, validation strategies and performance measures. In Part 2, NeuralSeg and the experienced endosonographer possessed excellent inter-rater correlation (Intraclass Correlation Coefficient = 0.76, 95% CI= 0.70 – 0.80, p<0.0001). In Part 3, NeuralSeg’s algorithm had an accuracy of 73.78% (95% CI: 68.40% to 78.68%), a sensitivity of 18.37% (95% CI: 8.76% to 32.02%) and specificity of 84.34% (95% CI: 79.22% to 88.62%). Conclusions- Analysis of staging modalities for lung cancer using Artificial Intelligence may be useful for when results are inconclusive or uninterpretable by a human reader. NeuralSeg’s high specificity may inform decision-making regarding biopsy if results are benign. Prospective external validation of algorithms and direct comparisons through cut-off thresholds are required to determine their true predictive capability. Future work with a larger dataset will be required to improve and refine the algorithm prior to trials in clinical practice. / Thesis / Master of Science (MSc) / Before deciding on treatment for patients with lung cancer, a critical step in the investigation is finding out whether the lymph nodes in the chest contain cancer cells. This is accomplished through medical imaging of the lymph nodes or taking a biopsy of the lymph node tissue using a needle attached to a scope that is entered through the airway wall. The purpose of these tests is to ensure that lung cancer patients receive the optimal treatment option. However, imaging of the lymph nodes is heavily reliant on human interpretation, which can be error prone. We aimed to critically analyze and investigate the use of Artificial Intelligence to enhance clinician performance for image interpretation. We performed a search of the medical literature for the use of Artificial Intelligence to diagnosis lung cancer from medical imaging. We also taught a computer program, known as NeuralSeg, to learn and identify cancerous lymph nodes from ultrasound imaging. This thesis provides a significant contribution to the Artificial Intelligence literature and provides recommendations for future research.

Serotonin has been widely explored in the brain. Recently, there have been new findings on how serotonin works in the periphery. Serotonin is introduced to the periphery by the enterochromaffin cells and metabolized by the liver and lung. Studies have shown that serotonin plays a role in controlling lung cancer. However, the mechanism by which it initiates tumor formation has not been fully explored. Cell viability was measured in several lung adenocarcinoma cell lines treated with serotonin to study this effect. In GFP-labelled cells, fluorescence intensity was measured for quantification of cell viability. Our data showed an overall increase in viability when serotonin concentration was increased, which is significant because it shows that serotonin affects lung cancer progression. We will look at how serotonin works on tumor cells compared to endothelial cells and its effect on immune system activation. This study hopes to inspire future anti-angiogenesis and immunotherapy studies of lung cancer by understanding this interaction.

Chemotherapy-associated thrombosis is a common complication in cancer patients. Cancer patients have a 5- to 7-fold increased risk for a thrombotic event compared to healthy individuals. While the overall risk for a thrombotic event in lung cancer patients is approximately 1.4%, the rates of thrombosis vary depending on the stage of the disease and the chemotherapeutic agents used. Activation of coagulation after initiation of chemotherapy has been reported in clinical studies. However, the mechanisms by which lung cancer chemotherapy agents modulate coagulation in lung cancer patients are not completely understood. The focus of this thesis is to investigate the mechanisms by which chemotherapy agents cisplatin, carboplatin, gemcitabine, and paclitaxel (in platinum-based combinations) induce procoagulant effects utilizing in vitro and in vivo approaches. First, we investigated the mechanisms by which lung cancer chemotherapy modulates cell-surface tissue factor (TF) activity on endothelial cells (HUVEC), monocytes, and non-small cell lung carcinoma (NSCLC) A549 cells. We observed that treatment of all three cell lines with platinum-based lung cancer chemotherapy increased cell surface TF activity. We found that the increased TF activity on chemotherapy-treated monocytes was due to increased phosphatidylserine (PS) exposure, whereas the increased TF activity on HUVEC and A549 cells was due to protein disulfide isomerase (PDI)-mediated decryption of TF. These studies demonstrate that lung cancer chemotherapy agents can exert procoagulant effects by increasing PS exposure and by inducing TF decryption on healthy and tumour cells. Next, we determined the effects of lung cancer chemotherapy on the generation of microparticles (MP) and the impact of MPs on thrombin generation. Our in vitro and in vivo studies demonstrate that lung cancer chemotherapy agents increase the generation of TF- and PS-positive MPs from tumour cells and that the MPs contribute to thrombin generation in a FVII-dependent manner. We also investigated the role of cell-free DNA (CFDNA) in mediating procoagulant effects induced by lung cancer chemotherapy agents. We found that lung cancer chemotherapy agents induce CFDNA release from healthy host neutrophils and that this leads to additional generation of thrombin by the intrinsic pathway of coagulation. Lastly, CFDNA levels have been shown to increase in cancer models through formation of neutrophil extracellular traps (NETs). Formation of NETs by NETosis, a process by which neutrophils release extracellular web-like structures composed of DNA, histones, and granular proteins, is dependent on histone citrullination by protein arginine deaminase-4 (PAD-4). In addition, PAD4 inhibition prevents NET formation. Therefore, we wanted to demonstrate that the neutrophil-derived CFDNA release induced by lung cancer chemotherapy is PAD4-dependent. Chemotherapy treatment of PAD4 knockout mice failed to increase CFDNA levels. Furthermore, chemotherapy-treatment did not increase thrombin generation in PAD4 knockout mice. This suggests that chemotherapy-induced CFDNA release occurs through NETosis. In conclusion, lung cancer chemotherapy leads to increased thrombin generation which occurs through increased TF decryption, MP generation, and CFDNA release. Therefore, lung cancer chemotherapy results in simultaneous activation of the extrinsic and intrinsic pathways of coagulation. These studies provide novel insight into the mechanisms of lung cancer chemotherapy-associated thrombosis. / Thesis / Doctor of Philosophy (PhD)

High-resolution computed tomography (HRCT) of the chest is commonly used in the diagnosis of a variety of lung diseases. Structural changes associated with clinical characteristics of disease may also define specific disease-associated physiologic states that may provide insights into disease pathophysiology. Gene expression profiling is potentially a useful adjunct to HRCT to identify molecular correlates of the observed structural changes. However, it is difficult to directly access diseased distal airway or lung parenchyma routinely for profiling studies. Previously, we have profiled bronchial airway in normal-appearing epithelial cells at the mainstem bronchus, detecting distinct gene expression alterations related to the clinical diagnosis of chronic obstructive pulmonary disease (COPD) and lung cancer. These gene expression alterations offer insights into the molecular events related to diseased tissue at more distal airways and in the parenchyma, which we hypothesize are due to a field-of-injury effect. Here, we expand this prior work by correlating airway gene expression to COPD and bronchiectasis phenotypes defined by HRCT to better understand the pathophysiology of these diseases. Additionally, we classified pulmonary nodules as malignant or benign by combining HRCT nodule imaging characteristics with gene expression profiling of the nasal airway. First, we collected brushing samples from the main-stem bronchus and assessed gene expression alterations associated with COPD phenotypes defined by K-means clustering of HRCT-based imaging features. We found three imaging clusters, which correlated with incremental severity of COPD: preserved, interstitial predominant, and emphysema predominant. 357 genes were differentially expressed between the normal and the emphysema predominant clusters. Functional analysis of the differentially expressed genes suggests a possible induction of inflammatory processes and repression of T-cell related biologic pathways, in the emphysema predominant cluster. We then discovered gene expression alterations associated with radiographic evidence of bronchiectasis (BE), an underdiagnosed obstructive pulmonary disease with unclear pathophysiology. We found 655 genes were differentially expressed in bronchial epithelium from individuals with radiographic evidence of BE despite none of the study participants having a clinical BE diagnosis. In addition to biological pathways that had been previously associated with BE, novel pathways that may play important roles in BE initiation were also discovered. Furthermore, we leveraged an independent single-cell RNA-sequencing dataset of the bronchial epithelium to explore whether the observed gene expression alterations might be cell-type dependent. We computationally detected an increased presence of ciliated and deuterosomal cells, as well as a decreased presence of basal cells in subjects with widespread radiographic BE, which may reflect a shift in the cellular landscape of the airway during BE initiation. Finally, we identified gene expression alterations within the nasal epithelium associated with the presence of malignant pulmonary nodules. A computational model was constructed for determining whether a nodule is malignant or benign that combines gene expression and imaging features extracted from HRCT. Leveraging data from single-cell RNA sequencing, we found genes increased in patients with lung cancer are expressed at higher levels within a novel cluster of nasal epithelial cells, termed keratinizing epithelial cells. In summary, we leveraged gene expression profiling of the proximal airway and discovered novel biological pathways that potentially drive the structural changes representative of physiologic states defined by chest HRCT in COPD and BE. This approach may also be combined with chest HRCT to detect weak signals related to malignant pulmonary nodules. / 2024-02-03T00:00:00Z

Yes / Objectives; To evaluate radiation doses for all low-dose CT scans performed during the first year of a lung screening trial. Methods; For all lung screening scans that were performed using a CT protocol that delivered image quality meeting the RSNA QIBA criteria, , radiation dose metrics, participant height, weight, gender and age were recorded. Values of CTDIvol and DLP were evaluated as a function of weight in order to assess the performance of the scan protocol across the participant cohort. Calculated effective doses were used to establish the additional lifetime attributable cancer risks arising from trial scans. Results; Median values of CTDIvol, DLP and effective dose (IQR) from the 3521 scans were 1.1mGy (0.70), 42.4mGycm (24.9) and 1.15mSv (0.67), whilst for 60-80kg participants the values were 1.0mGy (0.30), 35.8mGycm (11.4) and 0.97mSv (0.31). A statistically significant correlation between CTDIvol and weight was identified for males (r=0.9123, p<0.001) and females (r=0.9052, p<0.001), however the effect of gender on CTDIvol was not statistically significant (p=0.2328) despite notable differences existing at the extremes of the weight range. The additional lifetime attributable cancer risks from a single scan were in the range 0.001-0.006%. Conclusions; Low radiation doses can be achieved across a typical lung screening cohort using scan protocols that have been shown to deliver high levels of image quality. The observed dose levels may be considered as typical values for lung screening scans on similar types of scanner for an equivalent participant cohort. Advances in Knowledge; Presentation of typical radiation dose levels for CT lung screening examinations in a large UK trial. Effective radiation doses can be of the order of 1mSv for standard sized participants. Lifetime attributable cancer risks resulting from a single LDCT scan did not exceed 0.006%. / The Yorkshire Lung Screening Trial is funded by Yorkshire Cancer Research (award reference L403).

published_or_final_version / abstract / Surgery / Doctoral / Doctor of Philosophy

Vaults, recently discovered in 1986, are multi-subunit organelles with a molecular mass of ,--,13 MDa. The specific function of vaults is unknown, although they are believed to be involved in internal transport. These ribonucleoproteins are composed of the major vault protein, which comprises ' 70% of the vault's mass, two minor proteins, TEP1 and vPARP, and untranslated RNA(s). It is believed that the protein components of the vault are structural while the RNAs are the functional components. Implications of the vault's involvement in multi-drug resistance in cancer have been made. In some resistant cancer cells, the major vault protein and vRNA(s) are up-regulated up to 15 times when cells are exposed to a cytotoxic drug. Cytotoxic drugs such as doxorubicin are administered as a cancer treatment, but may be ineffective because the drug is actively pumped out of the cell. Multi-drug resistance is the most common failure of chemotherapeutic cancer treatment. In order to prevent the development of multi-drug resistance this research employed the use of small interfering RNA technology to down-regulate the expression of one of the vault RNAs, vRNA3, in cultured GLC4 cells, a small-cell lung cancer cell line. If the vRNA(s) are the functional portion of the vault and a cloned siRNA prevents their up-regulation after drug exposure, the cells should lose their multi-drug resistance, stimulating apoptosis. If successful, this approach may provide an alternative approach to cancer treatment in cells which respond to chemotherapy by increasing the number of vault particles.Initially, the transfection of a plasmid into GLC4 cells was optimized. The best transfection efficiency (N20%) was obtained by using GeneTherapySystems' GenePORTER2 transfection reagent in serum free conditions. To determine if the vault RNAs are the functional portion of the vault complex that confers multi-drug resistance to a cell, a small interfering RNA fragment was designed to specifically knock-down the expression of human vault RNA 3. The siRNA sequence homologous to a portion of vault RNA3 was cloned into an expression vector, and using optimized transfection protocols was transfected into GLC4/REV cells. A Western analysis using caspase-8 antibodies showed no difference in caspase-8 expression in doxorubicin treated and untreated cells. Preliminary results yielded by reverse transcriptase polymerase chain reaction amplification of isolated RNA indicated that the vRNAs were not down-regulated by the siRNAs. / Department of Biology