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High attrition-rates entailed by drug testing in 2D cell culture and animal models stress the need for improved modeling of human tumor tissues. In previous studies our 3D models on a decellularized tissue matrix have shown better predictivity and higher chemoresistance. A single porcine intestine yields material for 150 3D models of breast, lung, colorectal cancer (CRC) or leukemia. The uniquely preserved structure of the basement membrane enables physiological anchorage of endothelial cells and epithelial-derived carcinoma cells. The matrix provides different niches for cell growth: on top as monolayer, in crypts as aggregates and within deeper layers. Dynamic culture in bioreactors enhances cell growth. Comparing gene expression between 2D and 3D cultures, we observed changes related to proliferation, apoptosis and stemness. For drug target predictions, we utilize tumor-specific sequencing data in our in silico model finding an additive effect of metformin and gefitinib treatment for lung cancer in silico, validated in vitro. To analyze mode-of-action, immune therapies such as trispecific T-cell engagers in leukemia, as well as toxicity on non-cancer cells, the model can be modularly enriched with human endothelial cells (hECs), immune cells and fibroblasts. Upon addition of hECs, transmigration of immune cells through the endothelial barrier can be investigated. In an allogenic CRC model we observe a lower basic apoptosis rate after applying PBMCs in 3D compared to 2D, which offers new options to mirror antigen-specific immunotherapies in vitro. In conclusion, we present modular human 3D tumor models with tissue-like features for preclinical testing to reduce animal experiments.
Rationale
While brain serotonin (5-HT) function is implicated in gene-by-environment interaction (GxE) impacting the vulnerability-resilience continuum in neuropsychiatric disorders, it remains elusive how the interplay of altered 5-HT synthesis and environmental stressors is linked to failure in emotion regulation.
Objective
Here, we investigated the effect of constitutively impaired 5-HT synthesis on behavioral and neuroendocrine responses to unpredictable chronic mild stress (CMS) using a mouse model of brain 5-HT deficiency resulting from targeted inactivation of the tryptophan hydroxylase-2 (Tph2) gene.
Results
Locomotor activity and anxiety- and depression-like behavior as well as conditioned fear responses were differentially affected by Tph2 genotype, sex, and CMS. Tph2 null mutants (Tph2\(^{−/−}\)) displayed increased general metabolism, marginally reduced anxiety- and depression-like behavior but strikingly increased conditioned fear responses. Behavioral modifications were associated with sex-specific hypothalamic-pituitary-adrenocortical (HPA) system alterations as indicated by plasma corticosterone and fecal corticosterone metabolite concentrations. Tph2\(^{−/−}\) males displayed increased impulsivity and high aggressiveness. Tph2\(^{−/−}\) females displayed greater emotional reactivity to aversive conditions as reflected by changes in behaviors at baseline including increased freezing and decreased locomotion in novel environments. However, both Tph2\(^{−/−}\) male and female mice were resilient to CMS-induced hyperlocomotion, while CMS intensified conditioned fear responses in a GxE-dependent manner.
Conclusions
Our results indicate that 5-HT mediates behavioral responses to environmental adversity by facilitating the encoding of stress effects leading to increased vulnerability for negative emotionality.
Background
Published models predicting nasal colonization with Methicillin-resistant Staphylococcus aureus among hospital admissions predominantly focus on separation of carriers from non-carriers and are frequently evaluated using measures of discrimination. In contrast, accurate estimation of carriage probability, which may inform decisions regarding treatment and infection control, is rarely assessed. Furthermore, no published models adjust for MRSA prevalence.
Methods
Using logistic regression, a scoring system (values from 0 to 200) predicting nasal carriage of MRSA was created using a derivation cohort of 3091 individuals admitted to a European tertiary referral center between July 2007 and March 2008. The expected positive predictive value of a rapid diagnostic test (GeneOhm, Becton & Dickinson Co.) was modeled using non-linear regression according to score. Models were validated on a second cohort from the same hospital consisting of 2043 patients admitted between August 2008 and January 2012. Our suggested correction score for prevalence was proportional to the log-transformed odds ratio between cohorts. Calibration before and after correction, i.e. accurate classification into arbitrary strata, was assessed with the Hosmer-Lemeshow-Test.
Results
Treating culture as reference, the rapid diagnostic test had positive predictive values of 64.8% and 54.0% in derivation and internal validation corhorts with prevalences of 2.3% and 1.7%, respectively. In addition to low prevalence, low positive predictive values were due to high proportion (> 66%) of mecA-negative Staphylococcus aureus among false positive results. Age, nursing home residence, admission through the medical emergency department, and ICD-10-GM admission diagnoses starting with “A” or “J” were associated with MRSA carriage and were thus included in the scoring system, which showed good calibration in predicting probability of carriage and the rapid diagnostic test’s expected positive predictive value. Calibration for both probability of carriage and expected positive predictive value in the internal validation cohort was improved by applying the correction score.
Conclusions
Given a set of patient parameters, the presented models accurately predict a) probability of nasal carriage of MRSA and b) a rapid diagnostic test’s expected positive predictive value. While the former can inform decisions regarding empiric antibiotic treatment and infection control, the latter can influence choice of screening method.
Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRAS\(^{G12C}\) or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRAS\(^{G12C}\) inhibitor in KRAS\(^{G12C}\) mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.