Assessment of a chemically induced model of lung squamous cell carcinoma in mice by 18F-FDG small-animal PET

Relationship between Lung Carcinogenesis and Chronic Inflammation in Rodents

Simple Summary

Lung cancer is the most common cause of cancer-related deaths worldwide. There are various risk factors for lung cancer, including tobacco smoking, inhalation of dust particles, chronic inflammation, and genetic factors. Chronic inflammation has been considered a key factor that promotes tumor progression via production of cytokines, chemokines, cytotoxic mediators, and reactive oxygen species by inflammatory cells. Here, we review rodent models of lung tumor induced by tobacco, tobacco-related products, and pro-inflammatory materials as well as genetic modifications, and discuss the relationship between chronic inflammation and lung tumor. Through this review, we hope to clarify the effects of chronic inflammation on lung carcinogenesis and help develop new treatments for lung cancer.

Abstract

Lung cancer remains the leading cause of cancer-related deaths, with an estimated 1.76 million deaths reported in 2018. Numerous studies have focused on the prevention and treatment of lung cancer using rodent models. Various chemicals, including tobacco-derived agents induce lung cancer and pre-cancerous lesions in rodents. In recent years, transgenic engineered rodents, in particular, those generated with a focus on the well-known gene mutations in human lung cancer (KRAS, EGFR, and p53 mutations) have been widely studied. Animal studies have revealed that chronic inflammation significantly enhances lung carcinogenesis, and inhibition of inflammation suppresses cancer progression. Moreover, the reduction in tumor size by suppression of inflammation in animal experiments suggests that chronic inflammation influences the promotion of tumorigenesis. Here, we review rodent lung tumor models induced by various chemical carcinogens, including tobacco-related carcinogens, and transgenics, and discuss the roles of chronic inflammation in lung carcinogenesis.

The Effect of Mouse Strain, Sex, and Carcinogen Dose on Toxicity and the Development of Lung Dysplasia and Squamous Cell Carcinomas in Mice

In order to translate new treatments to the clinic, it is necessary to use animal models that closely recapitulate human disease. Lung cancer develops after extended exposure to carcinogens. It has one of the highest mutation rates of all cancer and is highly heterogenic. Topical treatment with N-nitrosotris-(2-chloroethyl)urea (NTCU) induces lung squamous cell carcinoma (SCC) with nonsynonymous mutation rates similar to those reported for human non-small cell lung cancer. However, NTCU induces lung cancer with variable efficacy and toxicity depending on the mouse strain. A detailed characterization of the NTCU model is needed. We have compared the effect of three different NTCU doses (20, 30, and 40 mmol/L) in female and male of NIH Swiss, Black Swiss, and FVB mice on tumor incidence, survival, and toxicity. The main findings in this study are (1) NIH Swiss mice present with a higher incidence of SCC and lower mortality compared with Black Swiss and FVB mice; (2) 30 mmol/L NTCU dose induces SCC at the same rate and incidence as the 40 mmol/L dose with lower mortality; (3) female mice present higher grade and incidence of preinvasive lesions and SCC compared with males; (4) NTCU-induced transformation is principally within the respiratory system; and (5) NTCU treatment does not affect the ability to elicit a specific adaptive immune response. This study provides a reference point for experimental designs to evaluate either preventive or therapeutic treatments for lung SCC, including immunotherapies, before initiating human clinical trials.

Computer-aided pulmonary image analysis in small animal models

PURPOSE

To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models.

METHODS

The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors' system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next. The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters.

RESULTS

133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT'09 data set.

CONCLUSIONS

The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases.

Role of deltaNp63(pos)CD44v(pos) cells in the development of N-nitroso-tris-chloroethylurea-induced peripheral-type mouse lung squamous cell carcinomas

The role of cells expressing stem cell markers deltaNp63 and CD44v has not yet been elucidated in peripheral-type lung squamous cell carcinoma (pLSCC) carcinogenesis. Female A/J mice were painted topically with N-nitroso-tris-chloroethylurea (NTCU) for induction of pLSCC, and the histopathological and molecular characteristics of NTCU-induced lung lesions were examined. Histopathologically, we found atypical bronchiolar hyperplasia, squamous metaplasia, squamous dysplasia, and pLSCCs in the treated mice. Furthermore, we identified deltaNp63(pos)CD44v(pos)CK5/6(pos)CC10(pos) clara cells as key constituents of early precancerous atypical bronchiolar hyperplasia. In addition, deltaNp63(pos)CD44v(pos) cells existed throughout the atypical bronchiolar hyperplasias, squamous metaplasias, squamous dysplasias, and pLSCCs. Overall, our findings suggest that NTCU induces pLSCC through an atypical bronchiolar hyperplasia-metaplasia-dysplasia-SCC sequence in mouse lung bronchioles. Notably, Ki67-positive deltaNp63(pos)CD44v(pos) cancer cells, cancer cells overexpressing phosphorylated epidermal growth factor receptor and signal transducer and activator of transcription 3, and tumor-associated macrophages were all present in far greater numbers in the peripheral area of the pLSCCs compared with the central area. These findings suggest that deltaNp63(pos)CD44v(pos) clara cells in mouse lung bronchioles might be the origin of the NTCU-induced pLSCCs. Our findings also suggest that tumor-associated macrophages may contribute to creating a tumor microenvironment in the peripheral area of pLSCCs that allows deltaNp63(pos)CD44v(pos) cancer cell expansion through activation of epidermal growth factor receptor signaling, and that exerts an immunosuppressive effect through activation of signal transducer and activator of transcription 3 signaling.

Preclinical anatomical, molecular, and functional imaging of the lung with multiple modalities

In vivo imaging is an important tool for preclinical studies of lung function and disease. The widespread availability of multimodal animal imaging systems and the rapid rate of diagnostic contrast agent development have empowered researchers to noninvasively study lung function and pulmonary disorders. Investigators can identify, track, and quantify biological processes over time. In this review, we highlight the fundamental principles of bioluminescence, fluorescence, planar X-ray, X-ray computed tomography, magnetic resonance imaging, and nuclear imaging modalities (such as positron emission tomography and single photon emission computed tomography) that have been successfully employed for the study of lung function and pulmonary disorders in a preclinical setting. The major principles, benefits, and applications of each imaging modality and technology are reviewed. Limitations and the future prospective of multimodal imaging in pulmonary physiology are also discussed. In vivo imaging bridges molecular biological studies, drug design and discovery, and the imaging field with modern medical practice, and, as such, will continue to be a mainstay in biomedical research.

Mouse models of lung squamous cell carcinomas

Although many mouse models of lung adenocarcinoma exist, only a few mouse lung squamous cell carcinoma models have been developed. Since most clinical chemoprevention trials of lung cancer are performed in subjects with bronchial dysplasia, development of a lung squamous cell carcinoma mouse model sufficient for chemoprevention studies is a high priority. We have shown that lung squamous cell carcinomas can be induced chemically in several strains of mice (1), and that this chemically induced lung squamous cell carcinoma model is applicable to cancer chemoprevention studies. Recently, Ji et al. (2) have shown that simultaneous activation of KrasG12D and inactivation of Lkb1 results in a broader histological range of lung tumors, with approximately 50 % of the lung tumors being squamous cell carcinomas. Here, we review the application of mouse lung squamous cell carcinoma models with different stages of squamous lesions and squamous cell carcinomas to cancer development and chemoprevention studies.

A computational pipeline for quantification of pulmonary infections in small animal models using serial PET-CT imaging

Background

Infectious diseases are the second leading cause of death worldwide. In order to better understand and treat them, an accurate evaluation using multi-modal imaging techniques for anatomical and functional characterizations is needed. For non-invasive imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), there have been many engineering improvements that have significantly enhanced the resolution and contrast of the images, but there are still insufficient computational algorithms available for researchers to use when accurately quantifying imaging data from anatomical structures and functional biological processes. Since the development of such tools may potentially translate basic research into the clinic, this study focuses on the development of a quantitative and qualitative image analysis platform that provides a computational radiology perspective for pulmonary infections in small animal models. Specifically, we designed (a) a fast and robust automated and semi-automated image analysis platform and a quantification tool that can facilitate accurate diagnostic measurements of pulmonary lesions as well as volumetric measurements of anatomical structures, and incorporated (b) an image registration pipeline to our proposed framework for volumetric comparison of serial scans. This is an important investigational tool for small animal infectious disease models that can help advance researchers’ understanding of infectious diseases.

Methods

We tested the utility of our proposed methodology by using sequentially acquired CT and PET images of rabbit, ferret, and mouse models with respiratory infections of Mycobacterium tuberculosis (TB), H1N1 flu virus, and an aerosolized respiratory pathogen (necrotic TB) for a total of 92, 44, and 24 scans for the respective studies with half of the scans from CT and the other half from PET. Institutional Administrative Panel on Laboratory Animal Care approvals were obtained prior to conducting this research. First, the proposed computational framework registered PET and CT images to provide spatial correspondences between images. Second, the lungs from the CT scans were segmented using an interactive region growing (IRG) segmentation algorithm with mathematical morphology operations to avoid false positive (FP) uptake in PET images. Finally, we segmented significant radiotracer uptake from the PET images in lung regions determined from CT and computed metabolic volumes of the significant uptake. All segmentation processes were compared with expert radiologists’ delineations (ground truths). Metabolic and gross volume of lesions were automatically computed with the segmentation processes using PET and CT images, and percentage changes in those volumes over time were calculated. (Continued on next page)(Continued from previous page) Standardized uptake value (SUV) analysis from PET images was conducted as a complementary quantitative metric for disease severity assessment. Thus, severity and extent of pulmonary lesions were examined through both PET and CT images using the aforementioned quantification metrics outputted from the proposed framework.

Results

Each animal study was evaluated within the same subject class, and all steps of the proposed methodology were evaluated separately. We quantified the accuracy of the proposed algorithm with respect to the state-of-the-art segmentation algorithms. For evaluation of the segmentation results, dice similarity coefficient (DSC) as an overlap measure and Haussdorf distance as a shape dissimilarity measure were used. Significant correlations regarding the estimated lesion volumes were obtained both in CT and PET images with respect to the ground truths (R²=0.8922,p<0.01 and R²=0.8664,p<0.01, respectively). The segmentation accuracy (DSC (%)) was 93.4±4.5% for normal lung CT scans and 86.0±7.1% for pathological lung CT scans. Experiments showed excellent agreements (all above 85%) with expert evaluations for both structural and functional imaging modalities. Apart from quantitative analysis of each animal, we also qualitatively showed how metabolic volumes were changing over time by examining serial PET/CT scans. Evaluation of the registration processes was based on precisely defined anatomical landmark points by expert clinicians. An average of 2.66, 3.93, and 2.52 mm errors was found in rabbit, ferret, and mouse data (all within the resolution limits), respectively. Quantitative results obtained from the proposed methodology were visually related to the progress and severity of the pulmonary infections as verified by the participating radiologists. Moreover, we demonstrated that lesions due to the infections were metabolically active and appeared multi-focal in nature, and we observed similar patterns in the CT images as well. Consolidation and ground glass opacity were the main abnormal imaging patterns and consistently appeared in all CT images. We also found that the gross and metabolic lesion volume percentage follow the same trend as the SUV-based evaluation in the longitudinal analysis.

Conclusions

We explored the feasibility of using PET and CT imaging modalities in three distinct small animal models for two diverse pulmonary infections. We concluded from the clinical findings, derived from the proposed computational pipeline, that PET-CT imaging is an invaluable hybrid modality for tracking pulmonary infections longitudinally in small animals and has great potential to become routinely used in clinics. Our proposed methodology showed that automated computed-aided lesion detection and quantification of pulmonary infections in small animal models are efficient and accurate as compared to the clinical standard of manual and semi-automated approaches. Automated analysis of images in pre-clinical applications can increase the efficiency and quality of pre-clinical findings that ultimately inform downstream experimental design in human clinical studies; this innovation will allow researchers and clinicians to more effectively allocate study resources with respect to research demands without compromising accuracy.

N-nitroso-tris-chloroethylurea induces premalignant squamous dysplasia in mice

Squamous cell carcinoma (SCC) and premalignant endobronchial lesions have been difficult to study in murine models. In this study, we evaluate the topical N-nitroso-tris-chloroethylurea (NTCU) murine SCC model, determine the extent to which resulting premalignant airway dysplasia develops, discuss clinicopathologic grading criteria in lesion progression, and confirm that immunohistochemical (IHC) staining patterns are consistent with those observed in human endobronchial dysplasia and SCC. Male and female FVB mice were treated biweekly with topical NTCU (4, 8, or 40 mmol/L) or vehicle for 32 weeks. Following sacrifice, squamous cell lesions were enumerated and categorized into the following groups: flat atypia, low-grade dysplasia, high-grade dysplasia, and invasive SCC. The 40 mmol/L NTCU concentration produced the entire spectrum of premalignant dysplasias and squamous cell carcinomas, but was associated with poor survival. Concentrations of 4 and 8 mmol/L NTCU were better tolerated and produced only significant levels of flat atypia. Squamous origin of the range of observed lesions was confirmed with IHC staining for cytokeratin 5/6, p63, thyroid transcription factor-1 (TTF-1), and Napsin-A. This study shows that topical application of high-dose NTCU produces endobronchial premalignant lesions with classic squamous characteristics and should allow for improved preclinical evaluation of potential chemopreventive agents.

Micro-computed tomography of pulmonary fibrosis in mice induced by adenoviral gene transfer of biologically active transforming growth factor-β1

Background

Micro-computed tomography (micro-CT) is a novel tool for monitoring acute and chronic disease states in small laboratory animals. Its value for assessing progressive lung fibrosis in mice has not been reported so far. Here we examined the importance of in vivo micro-CT as non-invasive tool to assess progression of pulmonary fibrosis in mice over time.

Methods

Pulmonary fibrosis was induced in mice by intratracheal delivery of an adenoviral gene vector encoding biologically active TGF-ß1 (AdTGF-ß1). Respiratory gated and ungated micro-CT scans were performed at 1, 2, 3, and 4 weeks post pulmonary adenoviral gene or control vector delivery, and were then correlated with respective histopathology-based Ashcroft scoring of pulmonary fibrosis in mice. Visual assessment of image quality and consolidation was performed by 3 observers and a semi-automated quantification algorithm was applied to quantify aerated pulmonary volume as an inverse surrogate marker for pulmonary fibrosis.

Results

We found a significant correlation between classical Ashcroft scoring and micro-CT assessment using both visual assessment and the semi-automated quantification algorithm. Pulmonary fibrosis could be clearly detected in micro-CT, image quality values were higher for respiratory gated exams, although differences were not significant. For assessment of fibrosis no significant difference between respiratory gated and ungated exams was observed.

Conclusions

Together, we show that micro-CT is a powerful tool to assess pulmonary fibrosis in mice, using both visual assessment and semi-automated quantification algorithms. These data may be important in view of pre-clinical pharmacologic interventions for the treatment of lung fibrosis in small laboratory animals.

Longitudinal assessment of lung cancer progression in the mouse using in vivo micro-CT imaging

PURPOSE

Small animal micro-CT imaging is being used increasingly in preclinical biomedical research to provide phenotypic descriptions of genomic models. Most of this imaging is coincident with animal death and is used to show the extent of disease as an end point. Longitudinal imaging overcomes the limitation of single time-point imaging because it enables tracking of the natural history of disease and provides qualitative and, where possible, quantitative assessments of the effects of an intervention. The pulmonary system is affected by many disease conditions, such as lung cancer, chronic obstructive pulmonary disease, asthma, and granulomatous disorders. Noninvasive imaging can accurately assess the lung phenotype within the living animal, evaluating not only global lung measures, but also regional pathology. However, imaging the lung in the living animal is complicated by rapid respiratory motion, which leads to image based artifacts. Furthermore, no standard mouse lung imaging protocols exist for longitudinal assessment, with each group needing to develop their own systematic approach.

METHODS

In this article, the authors present an outline for performing longitudinal breath-hold gated micro-CT imaging for the assessment of lung nodules in a mouse model of lung cancer. The authors describe modifications to the previously published intermittent isopressure breath-hold technique including a new animal preparation and anesthesia protocol, implementation of a ring artifact reduction, variable scanner geometry, and polynomial beam hardening correction. In addition, the authors describe a multitime-point data set registration and tumor labeling and tracking strategy.

RESULTS

In vivo micro-CT data sets were acquired at months 2, 3, and 4 posturethane administration in cancer mice (n = 5) and simultaneously in control mice (n = 3). 137 unique lung nodules were identified from the cancer mice while no nodules were detected in the control mice. A total of 411 nodules were segmented and labeled over the three time-points. Lung nodule metrics including RECIST, Ortho, WHO, and 3D volume were determined and extracted. A tumor incidence rate of 30.44 +/- 1.93 SEM for n = 5 was found with identification of nodules as small as 0.11 mm (RECIST) and as large as 1.66 mm (RECIST). In addition, the tumor growth and doubling rate between months 2-3 and 3-4 were calculated. Here, the growth rate was slightly higher in the second period based on the 3D volume data (0.12 +/- 0.13 to 0.13 +/- 0.17 microl) but significantly less based on the linear diameter metrics [RECIST (0.33 +/- 0.19 to 0.17 +/- 0.18 mm); Ortho (0.24 +/- 0.15 to 0.16 +/- 0.15 mm)], indicating the need to understand how each metric is obtained and how to correctly interpret change in tumor size.

CONCLUSIONS

In conclusion, micro-CT imaging provides a unique platform for in vivo longitudinal assessment of pulmonary lung cancer progression and potentially tracking of therapies at very high resolutions. The ability to evaluate the same subject over time provides for a sensitive assay that can be carried out on a smaller sample size. When integrated with image processing and analysis routines as detailed in this study, the data acquired from micro-CT imaging can now provide a very powerful assessment of pulmonary disease outcomes.

In vivo two-photon imaging reveals monocyte-dependent neutrophil extravasation during pulmonary inflammation

Immune-mediated pulmonary diseases are a significant public health concern. Analysis of leukocyte behavior in the lung is essential for understanding cellular mechanisms that contribute to normal and diseased states. Here, we used two-photon imaging to study neutrophil extravasation from pulmonary vessels and subsequent interstitial migration. We found that the lungs contained a significant pool of tissue-resident neutrophils in the steady state. In response to inflammation produced by bacterial challenge or transplant-mediated, ischemia-reperfusion injury, neutrophils were rapidly recruited from the circulation and patrolled the interstitium and airspaces of the lung. Motile neutrophils often aggregated in dynamic clusters that formed and dispersed over tens of minutes. These clusters were associated with CD115(+) F4/80(+) Ly6C(+) cells that had recently entered the lung. The depletion of blood monocytes with clodronate liposomes reduced neutrophil clustering in the lung, but acted by inhibiting neutrophil transendothelial migration upstream of interstitial migration. Our results suggest that a subset of monocytes serve as key regulators of neutrophil extravasation in the lung and may be an attractive target for the treatment of inflammatory pulmonary diseases.