Growth Pattern Analysis of Murine Lung Neoplasms by Advanced Semi-Automated Quantification of Micro-CT Images

Computed tomography (CT) is a non-invasive imaging modality used to monitor human lung cancers. Typically, tumor volumes are calculated using manual or semi-automated methods that require substantial user input, and an exponential growth model is used to predict tumor growth. However, these measurement methodologies are time-consuming and can lack consistency. In addition, the availability of datasets with sequential images of the same tumor that are needed to characterize in vivo growth patterns for human lung cancers is limited due to treatment interventions and radiation exposure associated with multiple scans. In this paper, we performed micro-CT imaging of mouse lung cancers induced by overexpression of ribonucleotide reductase, a key enzyme in nucleotide biosynthesis, and developed an advanced semi-automated algorithm for efficient and accurate tumor volume measurement. Tumor volumes determined by the algorithm were first validated by comparison with results from manual methods for volume determination as well as direct physical measurements. A longitudinal study was then performed to investigate in vivo murine lung tumor growth patterns. Individual mice were imaged at least three times, with at least three weeks between scans. The tumors analyzed exhibited an exponential growth pattern, with an average doubling time of 57.08 days. The accuracy of the algorithm in the longitudinal study was also confirmed by comparing its output with manual measurements. These results suggest an exponential growth model for lung neoplasms and establish a new advanced semi-automated algorithm to measure lung tumor volume in mice that can aid efforts to improve lung cancer diagnosis and the evaluation of therapeutic responses

EPITHELIAL TO MESENCHYMAL TRANSITION AS A PREDICTOR OF RESPONSE TO POLO-LIKE KINASE 1 INHIBITION-INDUCED APOPTOSIS IN NON-SMALL CELL LUNG CARCINOMA

Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide. Outcomes are poor for patients with recurrent, advanced or metastatic NSCLC. Polo-like kinase 1 (PLK1), involved in the regulation of mitotic processes and the response to DNA damage, is overexpressed in NSCLC. Inhibiting PLK1 may be an effective treatment for NSCLC patients as it is involved in the mechanisms of resistance to several chemotherapy drugs. PLK1 inhibition or knock-down has various effects in cancer cells, including mitotic arrest, apoptosis, and senescence. Predictive biomarkers have not been identified to select those patients who are likely to respond to PLK1 inhibitors although a small subset of NSCLC patients respond well to single agent therapy. Our lab found that mesenchymal NSCLC cell lines were more sensitive to PLK1 inhibitors than the epithelial cell lines in vitro. The induction of an epithelial phenotype using miR-200 expression increased resistance to PLK1 inhibition, whereas the induction of a mesenchymal phenotype using ZEB1 expression or TGF-β increased PLK1 inhibition–induced apoptosis. To elucidate the mechanisms of resistance to PLK1 inhibition, our lab compared gene and protein expression in sensitive and resistant NSCLC cell lines and we identified β-Catenin, SMAD4 and PDK1 to be differentially regulated between epithelial and mesenchymal NSCLC cell lines after PLK1 inhibition. We tested the role of β-Catenin, SMAD4 and PDK1 in PLK1 inhibition induced apoptosis in NSCLC. Here, we demonstrate that mesenchymal NSCLC tumors are more sensitive to PLK1 inhibition compared to epithelial NSCLC in vivo in patient derived-xenograft (PDX) models as well as orthotopic mouse models in which the EMT properties are manipulable by modulating the miR200/ZEB1 axis. To facilitate analysis of these in vivo studies, we developed a novel semi-automated method of metastatic lung tumor burden calculation from computed tomography images by the calculation of the mass of the thoracic cavity. This method takes into account the aggregate tumor metastases in the thoracic cavity which significantly accounts for tumor burden in lung adenocarcinoma and provides details about the dynamic processes that occur in vivo over time

Early detection of pre-malignant lesions in a KRASG12D-driven mouse lung cancer model by monitoring circulating free DNA.

Lung cancer is the leading cause of cancer-related death. Two-thirds of cases are diagnosed at an advanced stage that is refractory to curative treatment. Therefore, strategies for the early detection of lung cancer are urgently sought. Total circulating free DNA (cfDNA) and tumour-derived circulating tumour DNA (ctDNA) are emerging as important biomarkers within a 'liquid biopsy' for monitoring human disease progression and response to therapy. Owing to the late clinical diagnosis of lung adenocarcinoma, the potential for cfDNA and ctDNA as early detection biomarkers remains unexplored. Here, using a Cre-regulated genetically engineered mouse model of lung adenocarcinoma development, driven by KrasG12D (the KrasLSL-G12D mouse), we serially tracked the release of cfDNA/ctDNA and compared this with tumour burden as determined by micro-computed tomography (CT). To monitor ctDNA, a droplet digital PCR assay was developed to permit discrimination of the KrasLox-G12D allele from the KrasLSL-G12D and KrasWT alleles. We show that micro-CT correlates with endpoint histology and is able to detect pre-malignant tumours with a combined volume larger than 7 mm3 Changes in cfDNA/ctDNA levels correlate with micro-CT measurements in longitudinal sampling and are able to monitor the emergence of lesions before the adenoma-adenocarcinoma transition. Potentially, this work has implications for the early detection of human lung adenocarcinoma using ctDNA/cfDNA profiling.A video abstract for this article is available at https://youtu.be/Ku8xJJyGs3UThis article has an associated First Person interview with the joint first authors of the paper.Medical Research Counci

Innovations in thoracic imaging:CT, radiomics, AI and x-ray velocimetry

In recent years, pulmonary imaging has seen enormous progress, with the introduction, validation and implementation of new hardware and software. There is a general trend from mere visual evaluation of radiological images to quantification of abnormalities and biomarkers, and assessment of 'non visual' markers that contribute to establishing diagnosis or prognosis. Important catalysts to these developments in thoracic imaging include new indications (like computed tomography [CT] lung cancer screening) and the COVID-19 pandemic. This review focuses on developments in CT, radiomics, artificial intelligence (AI) and x-ray velocimetry for imaging of the lungs. Recent developments in CT include the potential for ultra-low-dose CT imaging for lung nodules, and the advent of a new generation of CT systems based on photon-counting detector technology. Radiomics has demonstrated potential towards predictive and prognostic tasks particularly in lung cancer, previously not achievable by visual inspection by radiologists, exploiting high dimensional patterns (mostly texture related) on medical imaging data. Deep learning technology has revolutionized the field of AI and as a result, performance of AI algorithms is approaching human performance for an increasing number of specific tasks. X-ray velocimetry integrates x-ray (fluoroscopic) imaging with unique image processing to produce quantitative four dimensional measurement of lung tissue motion, and accurate calculations of lung ventilation

Eye-tracking the moving medical image: Development and investigation of a novel investigational tool for CT Colonography

Colorectal cancer remains the third most common cancer in the UK but the second leading cause of cancer death with >16,000 dying per year. Many advances have been made in recent years in all areas of investigation for colorectal cancer, one of the more notable being the widespread introduction of CT Colonography (CTC). CTC has rapidly established itself as a cornerstone of diagnosis for colonic neoplasia and much work has been done to standardise and assure quality in practice in both the acquisition and interpretation of the technique. A novel feature of CTC is the presentation of imaging in both traditional 2D and the ‘virtual’ 3D endoluminal formats. This thesis looks at expanding our understanding of and improving our performance in utilizing the endoluminal 3D view. We present and develop novel metrics applicable to eye-tracking the moving image, so that the complex dynamic nature of 3D endoluminal fly-through interpretation can be captured. These metrics are then applied to assess the effect of important elements of image interpretation, namely, reader experience, the effect of the use Computer Aided Detection (CAD) and the influence of the expected prevalence of abnormality. We review our findings with reference to the literature of eye tracking within medical imaging. In the co-registration section we apply our validated computer-assisted registration algorithm to the matching of 3D endoluminal colonic locations between temporally separate datasets, assessing its accuracy as an aid to colonic polyp surveillance with CTC

VISUALIZING THE DYNAMICS OF IMMUNE SURVEILLANCE IN BRAIN TUMORS BY INTRAVITAL MULTIPHOTON MICROSCOPY

Visualizing the dynamics of immune surveillance in brain tumors by intravital multiphoton microscopy By Felix I. Nwajei, MD Supervisory Professor: Tomasz Zal, Ph.D. Brain tumors (BTs) generally have a bad prognosis despite conventional treatment strategies. Immunotherapy is a relatively novel treatment approach that has shown benefit for durable treatment of melanoma, and is a promising candidate for different tumor types including BTs. Immunotherapeutic strategies work by exploiting and/or enhancing natural anti-tumor immune response, a process that is critically dependent on adaptive immunity, T cell infiltration and surveillance of tumor. However, little is known about the dynamics and regulation of T cell surveillance in BTs. Resident immune cells of the myeloid lineage known as microglia are ubiquitous in the brain parenchyma while tissue-resident myeloid dendritic cells (DCs) known to activate T cells are relatively rare in the brain compared to DCs in other organs. Accumulating evidence indicates that myeloid cells infiltrate and create an immune suppressive microenvironment in BTs, but the identity of these myeloid cells and their role in the adaptive immune surveillance of BTs by T cells is unclear. Based on the predominance of microglia in the brain tissue, studies focused on understanding how BT immune surveillance is regulated, have been skewed toward microglia. Many conclusions regarding microglia function have been deduced from in vitro experiments. Nonetheless, in vivo studies in parallel models such as EAE indicate that DCs are superior to microglia in antigen presentation to T cells in the brain and to date, there is no direct in vivo evidence to suggest otherwise. In addition, DCs are well-established cellular regulators of T cell surveillance in extracranial tumors. Therefore, I hypothesized that DCs, rather than microglia, play a major role in regulating T cell surveillance in BTs. To address this hypothesis, I have developed experimental imaging systems for longitudinal intravital multiphoton microscopy of immune cell dynamics in BTs in living mice and used this approach to interrogate T cell behavior in orthotopic glioma and in experimental intracranial metastases in vivo. I found that the myeloid infiltration of BTs was dominated by CD11c+ DC cells rather than microglia. Quantitative in situ tissue cell image cytometry further revealed that myeloid-derived CCR2+ monocytes accumulated in the BT core, CD11c+ DCs at the tumor margin, and CX3CR1+ microglia outside the tumor. T cells formed clusters around CD11c+ DCs, but not the microglia. Within these clusters, T cells vigorously interacted directly with CD11c+ DCs. CD11c+ DCs retained T cells and controlled their motility patterns, indicating that CD11c+ DCs play a major role in regulating T cell retention and motility in BT. Corresponding to the preferential distribution of CD11c+ DCs at BT margins was expression of the neuronal chemokine Fractalkine (CX3CL1). Deficiency of the Fractalkine receptor CX3CR1 resulted in decreased CD11c+ DC recruitment. In addition, decreased CD11c+ DC recruitment was accompanied by decreased T cell recruitment, an increase in the spatial diffusion of the few BT-infiltrating T cells, and subsequent outgrowth of a fibrosarcoma BT, which spontaneously regresses in the brain of control wild type mice in a CD8 T cell dependent manner. In summary, by using novel intravital imaging systems for longitudinal visualization of BT immune surveillance across several types of cancer, I showed that the recruitment, migration and retention of tumor infiltrating T cells in the brain is mediated by incoming CD11c+ DCs rather than by the brain-resident CX3CR1 microglia, and identified the neuronal chemokine Fractalkine as a key molecule that promotes T cell surveillance in BTs by recruiting CD11c+ DCs. These findings suggest that the non-microglial tumor-associating CD11c+ myeloid cells and the fractalkine/CX3CR1 chemokine pathway control T cell surveillance in BT and represent attractive immunotherapeutic targets that could be modulated for guiding endogenous or adoptive transfer of T cells to BT sites and for therapeutic modulation to enhance immunity against BTs

Influence of adipose-derived mesenchymal stromal cells on osteosarcoma minimal residual disease

Includes bibliographical references.2015 Summer.Introduction: Mesenchymal stromal cells (MSCs) have been shown to improve bone integration and healing in several preclinical studies and have therapeutic potential in limb salvage following massive bone loss due to tumor resection. However, MSCs have also been shown to promote primary and pulmonary metastatic tumor growth when injected in the presence of gross tumor or when co-injected with tumor cells in rodent models. While these results raise concerns about the safety of using MSCs in sarcoma patients, MSCs are unlikely to be utilized in a clinical setting when gross tumor is present. The objective of this dissertation project was to develop murine models of minimal residual osteosarcoma following primary tumor removal then to utilize these models to determine whether the administration of adipose-derived MSCs with or without chemotherapy treatment in a minimal residual disease setting would promote either pulmonary metastatic osteosarcoma progression or local disease recurrence. We hypothesized that surgical site or intravenous administration of MSCs will influence either osteosarcoma pulmonary metastatic burden or local disease recurrence in a minimal residual disease setting. Materials & Methods: Two syngeneic, orthotopic models of luciferase-expressing osteosarcoma were developed. In the first model, tumor-bearing mice underwent a coxofemoral amputation and were followed to assess development of pulmonary metastases. In the second model, a femorotibial amputation was performed in order to develop a model of consistent local tumor recurrence. In this model, all gross tumor was removed, however, microscopic tumor remained at the surgical margin. In this dissertation project, three principle projects were completed to test our hypothesis. The first project explored the use of MSCs delivered either to the surgical site or intravenously to ascertain their influence on pulmonary disease burden. A follow-on pilot explored concurrent MSC and chemotherapy treatment on development of pulmonary disease. The second project evaluated the use of MSCs delivered either to the surgical site or intravenously on local recurrence of osteosarcoma at the surgical site. Gross recurrent tumor size was measured for comparison between treatment groups. The third project examined the use of cisplatin and MSCs on survival of mice following removal of primary osteosarcoma. Data were expressed in mean +/- SD or median with 95% CI. ANOVA test, Kruskal-Wallis test, Fisher’s Exact test, Welch’s test, t-test, and Mann Whitney test were used for statistical analysis. Significance was set at p<0.05. Results: Mice treated with intravenous MSCs had a faster time to first pulmonary metastatic disease detection than mice treated with MSCs injected into the surgical site or control mice (no MSCs) (p=0.022). No treatment effect was seen between groups with respect to time to tumor recurrence or size of recurrent tumor in the second study. Survival curves were significantly different when comparing cisplatin, cisplatin and MSC treatment, MSC alone treatment and untreated mice (p<0.001) as well as in pairwise comparisons. Mice treated with MSCs had a 73% chance of earlier death than untreated controls. Discussion/Conclusion: Intravenous administration of MSCs in a minimal residual osteosarcoma environment resulted in a faster time to first detection of pulmonary disease and in a higher chance of earlier death compared to untreated mice. However, administration of MSCs locally in a surgical site following sarcoma excision appears to be safe, even in the setting of known residual microscopic disease. Further, the use of cisplatin treatment appeared to ameliorate the effects of intravenous MSCs on survival. Based on these results, further study is warranted to evaluate the influence of intravenously administered MSCs on minimal residual pulmonary metastatic disease

Dynamic Contrast Enhanced Computed Tomography Measurement of Perfusion in Hepatic Cancer

ABSTRACT In recent years, the incidence and mortality rate for hepatocellular carcinoma (HCC) have increased due to the emergence of hepatitis B, C and other diseases that cause cirrhosis. The progression from cirrhosis to HCC is characterized by abnormal vascularization and by a shift from a venous to an arterial blood supply. A knowledge of HCC vascularity which is manifested as alterations in liver blood flow may distinguish among different stages of liver disease and can be used to monitor response to treatment. Unfortunately, conventional diagnostic imaging techniques lack the ability to accurately quantify HCC vascularity. The purpose of this thesis was to validate and assess the diagnostic capabilities of dynamic contrast enhanced computed tomography (DCE-CT) and perfusion software designed to measure hepatic perfusion. Chapter 2 described a study designed to evaluate the accuracy and precision of hepatic perfusion measurement. The results showed a strong correlation between hepatic artery blood flow measurement with DCE-CT and radioactive microspheres under steady state in a rabbit model for HCC (VX2 carcinoma). Using repeated measurements and Monte Carlo simulations, DCE-CT perfusion measurements were found to be precise; with the highest precision in the tumor rim. In Chapter 3, we used fluorine-18 fluoro-2-deoxy-D-glucose (FDG) positron emission tomography and DCE-CT perfusion to determined an inverse correlation between glucose utilization and tumor blood flow; with an R of 0.727 (P \u3c 0.05). This suggests a limited supply of oxygen (possibly hypoxia) and that the tumor cells were surviving via anaerobic glycolysis. in In Chapter 4, hepatic perfusion data showed that thalidomide caused a reduction of tumor perfusion in the responder group during the first 8 days after therapy, P \u3c 0.05; while perfusion in the partial responder and control group remained unchanged, P \u3e 0.05. These changes were attributed to vascular remodeling and maturation resulting in a more functional network of endothelial tubes lined with pericytes. The results of this thesis demonstrate the accuracy and precision of DCE-CT hepatic perfusion measurements. It also showed that DCE-CT perfusion has the potential to enhance the functional imaging ability of hybrid PET/CT scanners and evaluate the efficacy of anti-angiogenesis therapy