Comparison of the Spatial Organization in Colorectal Tumors using Second-Order Statistics and Functional ANOVA

International audienceWe propose an automatic method to quantitatively describe the spatial organization governing populations of biological objects, such as cells, which exist in stationary histology images. This quantification is of prime importance when striving to compare different tumoral models in order to evaluate potential therapies. We compare two animal models of colorectal cancer. Our approach is based on the topographic map to automatically extract the location of the relevant biological objects. We describe their spatial organization along a continuous range of scales using second-order statistics. Using a functional analysis of variance test, we show that there are significant differences in these statistics depending on cancer model, and on the day after tumor implant

Morphological Features of Dysplastic Progression in Epithelium: Quantification of Cytological, Microendoscopic, and Second Harmonic Generation Images

Advances in imaging technology have led to a variety of available clinical and investigational systems. In this collection of studies, we tested the relevance of morphological image feature quantification on several imaging systems and epithelial tissues. Quantification carries the benefit of creating numerical baselines and thresholds of healthy and abnormal tissues, to potentially aid clinicians in determining a diagnosis, as well as providing researchers with standardized, unbiased results for future dissemination and comparison. Morphological image features in proflavine stained oral cells were compared qualitatively to traditional Giemsa stained cells, and then we quantified the nuclear to cytoplasm ratio. We determined that quantification of proflavine stained cells matched our hypothesis, as the nuclei in oral carcinoma cells were significantly larger than healthy oral cells. Proflavine has been used in conjunction with translational fluorescence microendoscopy of the gastrointestinal tract, and we demonstrated the ability of our custom algorithm to accurately (up to 85% sensitivity) extract colorectal crypt area and circularity data, which could minimize the burden of training on clinicians. In addition, we proposed fluorescein as an alternative fluorescent dye, providing comparable crypt area and circularity information. In order to investigate the morphological changes of crypts via the supporting collagen structures, we adapted our quantification algorithm to analyze crypt area, circularity, and an additional shape parameter in second harmonic generation images of label-free freshly resected murine epithelium. Murine models of colorectal cancer (CRC) were imaged at early and late stages of tumor progression, and we noted significant differences between the Control groups and the late cancer stages, with some differences between early and late stages of CRC progression

Colorectal Cancer Triple Co-culture Spheroid Model to Assess the Biocompatibility and Anticancer Properties of Polymeric Nanoparticles

Colorectal cancer (CRC) is the third most common and the second deadliest type of cancer worldwide, urging the development of more comprehensive models and of more efficient treatments. Although the combination of nanotechnology with chemo- and immuno-therapy has represented a promising treatment approach, its translation to the clinic has been hampered by the absence of cellular models that can provide reliable and predictive knowledge about the in vivo efficiency of the formulation. Herein, a 3D model based on CRC multicellular tumor spheroids (MCTS) model was developed by combining epithelial colon cancer cells (HCT116), human intestinal fibroblasts and monocytes. The developed MCTS 3D model mimicked several tumor features with cells undergoing spatial organization and producing extracellular matrix, forming a mass of tissue with a necrotic core. Furthermore, monocytes were differentiated into macrophages with an anti-inflammatory, pro-tumor M2-like phenotype. For a combined chemoimmunotherapy effect, spermine-modified acetalated dextran nanoparticles (NPs) loaded with the chemotherapeutic Nutlin-3a (Nut3a) and granulocyte-macrophage colony-stimulating factor (GM-CSF) were produced and tested in 2D cultures and in the MCTS 3D model. NPs were successfully taken-up by the cells in 2D, but in a significant less extent in the 3D model. However, these NPs were able to induce an anti-proliferative effect both in the 2D and in the 3D models. Moreover, Nut3a was able to partially shift the polarization of the macrophages present in the MCTS 3D model towards an anti-tumor M1-like phenotype. Overall, the developed MCTS 3D model showed to recapitulate key features of tumors, while representing a valuable model to assess the effect of combinatorial nano-therapeutic strategies in CRC. In addition, the developed NPs could represent a promising approach for CRC treatment.Peer reviewe

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

In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application

The Special Issue "In Vitro and In Vivo Models of Colorectal Cancer for Clinical Application", edited by Marta Baiocchi and Ann Zeuner for Cancers, collects original research papers and reviews, depicting the current state and the perspectives of CRC models for preclinical and translational research. Original research papers published in this issue focus on some of the hottest topics in CRC research, such as circulating tumor cells, epigenetic regulation of stemness states, new therapeutic targets, molecular CRC classification and experimental CRC models such as organoids and PDXs. Additionally, four reviews on CRC stem cells, immunotherapy and drug discovery provide an updated viewpoint on key topics linking benchtop to bedside research in CRC

UHRF1 coordinates DNA methylation and histone post-translational modifications in colon cancer .

In Colorectal cancer (CRC) genetic and epigenetic alterations are tightly connected, although these interactions on the patient\u2019s outcome are not clearly understood. A peculiar subclass of sporadic CRC tumors, is characterized by Microsatellite instability (MSI), due to hyper-methylated promoter of MHL1 gene and subsequent inactivation of the mismatch repair (MMR) mechanism, and the hypermethylation of CpG islands phenotype (CIMP), mediated by the hyper-methylation of promoter regions of several tumor suppressor genes (TSGs). This subclass carries a good prognosis and presents an inverse correlation with genomic and chromosome instability (CIN), together with a higher levels of DNA methylation at global level, compared to other CRCs. Among the epigenetic alterations, DNA methylation and histone modifications rearrangements are extremely important steps during tumorigenesis. UHRF1 is a key master epigenetic regulator that couples the maintenance of DNA methylation through the cell cycle with the histone-modification pattern. It monoubiquitinates H3K18/23 enabling the correct localization and activation of DNMT1 on the specific sites. UHRF1 is overexpressed in several cancer types mediating the hypermethylation of promoter regions of the TSGs and coordinating their heterochromatic silencing. Relying on the idea that UHRF1 could play a crucial role in the modulation of DNA methylation changes, the overall aim of this PhD thesis was to evaluate the role of UHRF1 in the coordination of DNA methylation and histone post-translational modifications both at genome-wide and at locus specific level in CRCs. Unexpectedly, we found that in CRC tissues UHRF1 was higher in tumors with microsatellite instability (MSI CRC), which have a better prognosis, compared to the stable ones (MSS CRC). MSI tumors were also characterized by higher levels of DNA methylation compared to the MSS. The UHRF1 knock-down in a MSI CRC cell line (RKO cells) induced an overall decrease in DNA methylation (RRB-seq analysis, pyrosequencing and MS-MLPA) both at global level and at gene promoters without affecting DNMTs levels, as observed by WB and RNA-seq analysis. ChIP experiments showed that UHRF1 depletion reduces DNMT1 binding to both repetitive elements (LINE-1) and specific gene promoters (MLH1, CDH1), decreasing H3K9me3 and increasing H3K4me3 on those hypo-methylated loci. RNA-seq data analysis showed that UHRF1 loss interferes with several important pathways, among others cell cycle, growth and proliferation. SILAC LC-MS/MS analysis showed that in RKO cells, UHRF1 loss decreases the overall presence of H3K23ub (\ubb 30%) and H3K18ub (\ubb 8%). These results, together with the published findings, led us to hypothesize a model in which the loss of UHRF1 directly impairs the DNA methylation maintenance by reducing H3K18/K23ub and consequently DNMT1 activity and, indirectly, impairs the binding of Suv39H1, the histone methyl transferase (HMT) responsible for H3K9me3, to both genome-wide and promoter specific loci. These changes led to a severe chromatin rearrangement of heterochromatic signatures toward a more open and transcriptionally accessible structure, probably due to the disruption of the axis UHRF1-H3ub-DNMT1-HMTs. Our molecular data, together with the analysis performed on CRC samples, led us to speculate that the better prognosis correlated with MSI-CRC model, could reside in the UHRF1-high levels that result in a sort of protective condition for the genome integrity, maintaining the global DNA methylation level closer to the normal mucosae, and probably counteracting the hyper-methylation of TSGs

Quantitative chemical imaging: A top-down systems pathology approach to predict colon cancer patient survival

Colon cancer is the second deadliest cancer, affecting the quality of life in older patients. Prognosis is useful in developing an informed disease management strategy, which can improve mortality as well as patient comfort. Morphometric assessment provides diagnosis, grade, and stage information. However, it is subjective, requires multi-step sample processing, and annotations by pathologists. In addition, morphometric techniques offer minimal molecular information that can be crucial in determining prognosis. The interaction of the tumor with its surrounding stroma, comprised of several biomolecular factors and cells is a critical determinant of the behavior of the disease. To evaluate this interaction objectively, we need biomolecular profiling in spatially specific context. In this work, we achieved this by analyzing tissue microarrays using infrared spectroscopic imaging. We developed supervised classification algorithms that were used to reliably segment colon tissue into histological components, including differentiation of normal and desmoplastic stroma. Thus, infrared spectroscopic imaging enabled us to map the stromal changes around the tumor. This supervised classification achieved >0.90 area under the curve of the receiver operating characteristic curve for pixel level classification. Using these maps, we sought to define evaluation criteria to assess the segmented colon images to determine prognosis. We measured the interaction of tumor with the surrounding stroma containing activated fibroblast in the form of mathematical functions that took into account the structure of tumor and the prevalence of reactive stroma. Using these functions, we found that the interaction effect of large tumor size in the presence of a high density of activated fibroblasts provided patients with worse outcome. The overall 6-year probability of survival in patient groups that were classified as “low-risk” was 0.73 whereas in patients that were “high-risk” was 0.54 at p-value <0.0003. Remarkably, the risk score defined in this work was independent of patient risk assessed by stage and grade of the tumor. Thus, objective evaluation of prognosis, which adds to the current clinical regimen, was achieved by a completely automated analysis of unstained patient tissue to determine the risk of 6-year death. In this work, we demonstrate that quantitative chemical imaging using infrared spectroscopic imaging is an effective method to measure tumor-tumor microenvironment interactions. As a top-down systems pathology approach, our work integrated morphometry based spatial constraints and biochemistry based stromal changes to identify markers that gave us mechanistic insights into the tumor behavior. Our work shows that while the tumor microenvironment changes are prognostic, an interaction model that takes into account both the extent of microenvironment modifications, as well as the tumor morphology, is a better predictor of prognosis. Finally, we also developed automated tumor grade determination using deep learning based infrared image analysis. Thus, the computational models developed in this work provide an objective, processing-free and automated way to predict tumor behavior

Magnetic resonance imaging and the development of vascular targeted treatments for cancer.

The main subject of the work presented in this thesis is the further development of magnetic resonance imaging (MRI) as a non-invasive method of investigating tumour microcirculation. Two different MR techniques were used: dynamic contrast enhanced (DCE)-MRI and Blood Oxygen Level Dependent (BOLD)-MRI. Intravital microscopy was used to help interpret BOLD-MRI results. The ultimate aims were to determine whether MRI methods could be relied upon to define a drug as having vascular disrupting activity and to develop techniques to predict the effectiveness of vascular disruptive agents (VDA). In DCE-MRI, tissue enhancement is continuously monitored over several minutes after intravenous injection of contrast medium. Modelling of contrast agent kinetics generates quantitative parameters related to tissue blood flow rate and permeability, e.g. Ktrans (transfer constant). In a clinical study, patients had DCE-MRI examinations before and 24 hours after cytotoxic chemotherapy to establish whether any acute ami-vascular effects could be detected. No acute reductions in Ktrans were seen. In this project, the acute effects of the VDA, combretastatin A-4-phosphate, were investigated using DCE-MRI in SW1222 tumours in mice. Responses were seen both at a clinically relevant dose and at higher doses, and a dose-response relationship established. BOLD-MRI can detect changes in oxygenation and blood flow within tumours using deoxygenated haemoglobin as an intrinsic contrast agent. Tumours contain a variable proportion of immature vessels, which may explain differential sensitivity to VDAs. In this project, BOLD-MRI was used to assess tumour vessel maturity using consequent vasoreactivity to angiotensin II and carbon dioxide (as air-5%C02 or as carbogen) in an animal model. Intravital microscopy was used to directly observe response to these agents in mouse window chambers. Results suggest that response to vasoactive agents is useful for assessing vascular maturity in tumours but that more sensitive non-invasive imaging methods than BOLD-MRI are required for clinical use

First-order statistical speckle models improve robustness and reproducibility of contrast-enhanced ultrasound perfusion estimates

Contrast-enhanced ultrasound (CEUS) permits the quantification and monitoring of adaptive tumor responses in the face of anti-angiogenic treatment, with the goal of informing targeted therapy. However, conventional CEUS image analysis relies on mean signal intensity as an estimate of tracer concentration in indicator-dilution modeling. This discounts additional information that may be available from the first-order speckle statistics in a CEUS image. Heterogeneous vascular networks, typical of tumor-induced angiogenesis, lead to heterogeneous contrast enhancement of the imaged tumor cross-section. To address this, a linear (B-mode) processing approach was developed to quantify the change in the first-order speckle statistics of B-mode cine loops due to the incursion of microbubbles. The technique, named the EDoF (effective degrees of freedom) method, was developed on tumor bearing mice (MDA-MB-231LN mammary fat pad inoculation) and evaluated using nonlinear (two-pulse amplitude modulated) contrast microbubble-specific images. To improve the potential clinical applicability of the technique, a second-generation compound probability density function for the statistics of two-pulse amplitude modulated contrast-enhanced ultrasound images was developed. The compound technique was tested in an antiangiogenic drug trial (bevacizumab) on tumor bearing mice (MDA-MB-231LN), and evaluated with gold-standard histology and contrast-enhanced X-ray computed tomography. The compound statistical model could more accurately discriminate anti-VEGF treated tumors from untreated tumors than conventional CEUS image. The technique was then applied to a rapid patient-derived xenograft (PDX) model of renal cell carcinoma (RCC) in the chorioallantoic membrane (CAM) of chicken embryos. The ultimate goal of the PDX model is to screen RCC patients for de novo sunitinib resistance. The analysis of the first-order speckle statistics of contrast-enhanced ultrasound cine loops provides more robust and reproducible estimates of tumor blood perfusion than conventional image analysis. Theoretically this form of analysis could quantify perfusion heterogeneity and provide estimates of vascular fractal dimension, but further work is required to determine what physiological features influence these measures. Treatment sensitivity matrices, which combine vascular measures from CEUS and power Doppler, may be suitable for screening of de novo sunitinib resistance in patients diagnosed with renal cell carcinoma. Further studies are required to assess whether this protocol can be predictive of patient outcome