Tumor growth curves are classically modeled by means of ordinary differential equations. In analyzing the Gompertz model several studies have reported a striking correlation between the two parameters of the model, which could be used to reduce the dimensionality and improve predictive power. We analyzed tumor growth kinetics within the statistical framework of nonlinear mixed-effects (population approach). This allowed the simultaneous modeling of tumor dynamics and inter-animal variability. Experimental data comprised three animal models of breast and lung cancers, with 833 measurements in 94 animals. Candidate models of tumor growth included the exponential, logistic and Gompertz models. The exponential and—more notably—logistic models failed to describe the experimental data whereas the Gompertz model generated very good fits. The previously reported population-level correlation between the Gompertz parameters was further confirmed in our analysis (R^2> 0.92 in all groups). Combining this structural correlation with rigorous population parameter estimation, we propose a reduced Gompertz function consisting of a single individual parameter (and one population parameter). Leveraging the population approach using Bayesian inference, we estimated times of tumor initiation using three late measurement timepoints. The reduced Gompertz model was found to exhibit the best results, with drastic improvements when using Bayesian inference as compared to likelihood maximization alone, for both accuracy and precision. Specifically, mean accuracy (prediction error) was 12.2% versus 78% and mean precision (width of the 95% prediction interval) was 15.6 days versus 210 days, for the breast cancer cell line. These results demonstrate the superior predictive power of the reduced Gompertz model, especially when combined with Bayesian estimation. They offer possible clinical perspectives for personalized prediction of the age of a tumor from limited data at diagnosis. The code and data used in our analysis are publicly available at https://github.com/cristinavaghi/plumky. Mathematical models for tumor growth kinetics have been widely used since several decades but mostly fitted to individual or average growth curves. Here we compared three classical models (exponential, logistic and Gompertz) using a population approach, which accounts for inter-animal variability. The exponential and the logistic models failed to fit the experimental data while the Gompertz model showed excellent descriptive power. Moreover, the strong correlation between the two parameters of the Gompertz equation motivated a simplification of the model, the reduced Gompertz model, with a single individual parameter and equal descriptive power. Combining the mixed-effects approach with Bayesian inference, we predicted the age of individual tumors with only few late measurements. Thanks to its simplicity, the reduced Gompertz model showed superior predictive power. Although our method remains to be extended to clinical data, these results are promising for the personalized estimation of the age of a tumor from limited measurements at diagnosis.

Large animal models, such as the dog, are increasingly being used for studying diseases including gastrointestinal (GI) disorders. Dogs share similar environmental, genomic, anatomical, and intestinal physiologic features with humans. To bridge the gap between commonly used animal models, such as rodents, and humans, and expand the translational potential of the dog model, we developed a three-dimensional (3D) canine GI organoid (enteroid and colonoid) system. Organoids have recently gained interest in translational research as this model system better recapitulates the physiological and molecular features of the tissue environment in comparison with two-dimensional cultures. Organoids were derived from tissue of more than 40 healthy dogs and dogs with GI conditions, including inflammatory bowel disease (IBD) and intestinal carcinomas. Adult intestinal stem cells (ISC) were isolated from whole jejunal tissue as well as endoscopically obtained duodenal, ileal, and colonic biopsy samples using an optimized culture protocol. Intestinal organoids were comprehensively characterized using histology, immunohistochemistry, RNA in situ hybridization, and transmission electron microscopy, to determine the extent to which they recapitulated the in vivo tissue characteristics. Physiological relevance of the enteroid system was defined using functional assays such as optical metabolic imaging (OMI), the cystic fibrosis transmembrane conductance regulator (CFTR) function assay, and Exosome-Like Vesicles (EV) uptake assay, as a basis for wider applications of this technology in basic, preclinical and translational GI research. We have furthermore created a collection of cryopreserved organoids to facilitate future research. We establish the canine GI organoid systems as a model to study naturally occurring intestinal diseases in dogs and humans, and that can be used for toxicology studies, for analysis of host-pathogen interactions, and for other translational applications.

Identifying appropriate animal models is critical in developing translatable in vitro and in vivo systems for therapeutic drug development and investigating disease pathophysiology. These animal models should have direct biological and translational relevance to the underlying disease they are supposed to mimic. Aging dogs not only naturally develop a cognitive decline in many aspects including learning and memory deficits, but they also exhibit human-like individual variability in the aging process. Neurodegenerative processes that can be observed in both human and canine brains include the progressive accumulation of β-amyloid (Aβ) found as diffuse plaques in the prefrontal cortex (PFC), including the gyrus proreus (i.e., medial orbital PFC), as well as the hippocampus and the cerebral vasculature. Tau pathology, a marker of neurodegeneration and dementia progression, was also found in canine hippocampal synapses. Various epidemiological data show that human patients with neurodegenerative diseases have concurrent intestinal lesions, and histopathological changes in the gastrointestinal (GI) tract occurs decades before neurodegenerative changes. Gut microbiome alterations have also been reported in many neurodegenerative diseases including Alzheimer’s (AD) and Parkinson’s diseases, as well as inflammatory central nervous system (CNS) diseases. Interestingly, the dog gut microbiome more closely resembles human gut microbiome in composition and functional overlap compared to rodent models. This article reviews the physiology of the gut-brain axis (GBA) and its involvement with neurodegenerative diseases in humans. Additionally, we outline the advantages and weaknesses of current in vitro and in vivo models and discuss future research directions investigating major human neurodegenerative diseases such as AD and Parkinson’s diseases using dogs.

Prior studies have failed to detect a convincing association between histologic lesions of inflammation and clinical activity in dogs with inflammatory bowel disease (IBD). We hypothesized that use of a simplified histopathologic scoring system would improve the consistency of interpretation among pathologists when describing histologic lesions of gastrointestinal inflammation. Our aim was to evaluate the correlation of histopathologic changes to clinical activity in dogs with IBD using this new system. Forty-two dogs with IBD and 19 healthy control dogs were enrolled in this retrospective study. Endoscopic biopsies from the stomach, duodenum, ileum, and colon were independently scored by 8 pathologists. Clinical disease activity was scored using the Canine Inflammatory Bowel Disease Activity Index (CIBDAI) or the Canine Chronic Enteropathy Clinical Activity Index (CCECAI), depending on the individual study center. Summative histopathological scores and clinical activity were calculated for each tissue (stomach, duodenum, ileum, and colon) and each tissue histologic score (inflammatory/morphologic feature). The correlation between CCECAI/CIBDAI and summative histopathologic score was significant (P < .05) for duodenum (r = 0.42) and colon (r = 0.33). In evaluating the relationship between histopathologic scores and clinical activity, significant (P < .05) correlations were observed for crypt dilation (r = 0.42), lamina propria (LP) lymphocytes (r = 0.40), LP neutrophils (r = 0.45), mucosal fibrosis (r = 0.47), lacteal dilation (r = 0.39), and villus stunting (r = 0.43). Compared to earlier grading schemes, the simplified scoring system shows improved utility in correlating histopathologic features (both summative histology scores and select histologic scores) to IBD clinical activity.