Actin dynamics regulation by TTC7A/PI4KIIIα limits DNA damage and cell death under confinement

Background: The actin cytoskeleton has a crucial role in the maintenance of the immune homeostasis by controlling various cellular processes, including cell migration. Mutations in TTC7A have been described as the cause of a primary immunodeficiency associated to different degrees of gut involvement and alterations in the actin cytoskeleton dynamics. Objectives: This study investigates the impact of TTC7A deficiency in immune homeostasis. In particular, the role of the TTC7A/phosphatidylinositol 4 kinase type III α pathway in the control of leukocyte migration and actin dynamics. Methods: Microfabricated devices were leveraged to study cell migration and actin dynamics of murine and patient-derived leukocytes under confinement at the single-cell level. Results: We show that TTC7A-deficient lymphocytes exhibit an altered cell migration and reduced capacity to deform through narrow gaps. Mechanistically, TTC7A-deficient phenotype resulted from impaired phosphoinositide signaling, leading to the downregulation of the phosphoinositide 3-kinase/AKT/RHOA regulatory axis and imbalanced actin cytoskeleton dynamics. TTC7A-associated phenotype resulted in impaired cell motility, accumulation of DNA damage, and increased cell death in dense 3-dimensional gels in the presence of chemokines. Conclusions: These results highlight a novel role of TTC7A as a critical regulator of lymphocyte migration. Impairment of this cellular function is likely to contribute to the pathophysiology underlying progressive immunodeficiency in patients.</p

The role of EMT inducer Zeb1 in the invasive tumour stroma during colon cancer progression

The EMT-transcription factor ZEB1 has been intensively studied in solid cancers, where it is expressed at the invasive front and in cancer-associated fibroblasts (CAFs). In tumour cells, ZEB1 has been involved in multiple steps of cancer progression including stemness, metastasis and therapy resistance, yet its role in the tumour-microenvironment is largely unknown. Here, the role of Zeb1 in CAFs was investigated using mouse models reflecting different tumour stages in immunocompetent fibroblast specific Zeb1 KO mice. Fibroblast-specific depletion of Zeb1 accelerated tumour growth in the inflammation driven AOM/DSS tumour initiation model, reduced tumour growth and invasion in the sporadic AOM/P53 model and reduced liver metastasis in a progressed orthotopic transplantation model. Immunohistochemical and single cell RNA-sequencing analysis showed that Zeb1 ablation resulted in attenuated expression of the myofibroblast marker aSMA and reduced ECM deposition, indicating a shift among fibroblast subpopulations. Modulation of CAFs was furthermore associated with increased inflammatory signaling in fibroblasts resulting in immune infiltration into primary tumours and exaggerated inflammatory signaling in T cells, B cells and macrophages. These changes in the tumour microenvironment were associated with increased efficacy of immune checkpoint inhibition therapy. In summary, Zeb1 expression in CAFs was identified as a potential target to block immunosuppression and metastatic dissemination in colon cancer.Eine große Herausforderung bei der Behandlung von Darmkrebs (CRC) ist die starke inter- und intratumorale Heterogenität, die zu diversem Ansprechen auf Behandlungen und häufigen Rückfällen bei initial ansprechenden Patienten führt. Um die zugrundeliegenden Mechanismen besser zu verstehen, wurden kürzlich Tumore anhand ihres transkriptomischen Profils in 4 molekulare Subtypen (consensus molecular subtypes / CMS) eingeteilt [Guinney et al. 2015]. Dabei zeichnet sich der CMS4-Subtyp mit der schlechtesten Prognose und einer Anreicherung von TGFβ- und stromalen Signaturen aus. Diese Signaturen, die durch die Präsenz und Aktivierung von krebsassoziierten Fibroblasten (cancer-associated fibroblasts, CAFs) verursacht sind, betonen die Wichtigkeit des Tumormikromilieu (tumor microenvironment, TME) zusätzlich zu den intrinsischen Eigenschaften der Tumorzellen. Es ist bekannt, dass CAFs das Tumorwachstum durch die Sekretion von Wachstumsfaktoren, den Umbau der extrazellulären Matrix (ECM) oder die Etablierung eines immunsuppressiven TME unterstützen [Sahai et al. 2020]. Eine Verringerung der CAF-Aktivierung durch Hemmung des TGFβ-Signalwegs erlaubte im Mausmodell eine verbesserte Therapieantwort [Tauriello et al. 2018]. Im Pankreaskarzinom wurde in CAFs jedoch ein hohes Maß an transkriptioneller und funktioneller Plastizität beobachtet [Öhlund et al. 2017, Biffi et al. 2021], was die Identifizierung von geeigneten pharmakologischen Zielen zur klinischen Translation erschwert. Eine weitere Signatur, die in CMS4-Tumoren angereichert ist, ist die epitheliale-mesenchymale Transition (EMT). Während zunächst angenommen wurde, dass die metastatische Progression der Tumorzellen für diese Muster verantwortlich ist, wurden in mehreren Studien CAFs als Hauptquelle dieser Signatur identifiziert [Isella et al. 2015, Calon et al. 2015, Li et al. 2017]. EMT wird durch mehrere Master-Transkriptionsfaktoren (Zeb1/2, Snai1/2, Twist1) reguliert, die die Expression epithelialer Schlüsselgene wie E-Cadherin und Cytokeratine hemmen und stattdessen die Expression mesenchymaler Gene wie Vimentin und N-Cadherin induzieren, was zu einer Modulation der Zellpolarität und einer erhöhten Zellmotilität führt [Huang et al. 2012a, Lamouille et al. 2014]. EMT-Tanskriptionsfaktoren (EMT-TFs) wurden in Epithelzellen eingehend untersucht, wo sie in der Regel verstärkt an der invasiven Front von Tumoren exprimiert werden und dadurch die Initiierung der Metastasierung vermitteln und Therapieresistenz induzieren können [Chang et al. 2011, Krebs et al. 2017]. EMT-TFs weisen jedoch auch eine heterogene Expression in Stromazellen im gesamten Tumor auf und bis jetzt ist die Funktion dieser Expression in Stromazellen unklar. In dieser Arbeit wurde die Rolle des EMT-Masterregulators Zeb1 in krebsassoziierten Fibroblasten während der Darmkrebs-Progression untersucht. Dazu wurde in Zusammenarbeit mit der Gruppe von Thomas Brabletz (Uni Erlangen) Mausmodelle analysiert, die entweder die entzündungsgetriebene Tumorinitiation widerspiegeln (AOM/DSS, AOM/P53) [Neufert et al. 2007] oder in Transplantationsmodellen das Voranschreiten des sporadischen CRC nachbilden (subkutan, orthotop) [Fumagalli et al. 2017]. Die Tumorzell-Transplantation in syngene Mäuse mit Fibroblasten-spezifischer induzierbarer Cre-Expression (Col1a2-CreERT2) und einem loxP flankierten Zeb1 Alle [Brabletz et al. 2017], ermöglichte die Untersuchung von Zeb1 in CAFs während unterschiedlicher Phasen der CRC-Initiierung und -Progression in einem immunkompetenten Hintergrund. In vivo Ergebnisse wurden in Mono- und Kokulturen von primären Fibroblasten mit CRISPR/Cas9-manipulierten Tumororganoiden und transgenen T Zellen mechanistisch untersucht

Dynamic Formation of Microvillus Inclusions During Enterocyte Differentiation in Munc18-2–Deficient Intestinal OrganoidsSummary

Background & Aims: Microvillus inclusion disease (MVID) is a congenital intestinal malabsorption disorder caused by defective apical vesicular transport. Existing cellular models do not fully recapitulate this heterogeneous pathology. The aim of this study was to characterize 3-dimensional intestinal organoids that continuously generate polarized absorptive cells as an accessible and relevant model to investigate MVID. Methods: Intestinal organoids from Munc18-2/Stxbp2-null mice that are deficient for apical vesicular transport were subjected to enterocyte-specific differentiation protocols. Lentiviral rescue experiments were performed using human MUNC18-2 variants. Apical trafficking and microvillus formation were characterized by confocal and transmission electron microscopy. Spinning disc time-lapse microscopy was used to document the lifecycle of microvillus inclusions. Results: Loss of Munc18-2/Stxbp2 recapitulated the pathologic features observed in patients with MUNC18-2 deficiency. The defects were fully restored by transgenic wild-type human MUNC18-2 protein, but not the patient variant (P477L). Importantly, we discovered that the MVID phenotype was correlated with the degree of enterocyte differentiation: secretory vesicles accumulated already in crypt progenitors, while differentiated enterocytes showed an apical tubulovesicular network and enlarged lysosomes. Upon prolonged enterocyte differentiation, cytoplasmic F-actin–positive foci were observed that further progressed into classic microvillus inclusions. Time-lapse microscopy showed their dynamic formation by intracellular maturation or invagination of the apical or basolateral plasma membrane. Conclusions: We show that prolonged enterocyte-specific differentiation is required to recapitulate the entire spectrum of MVID. Primary organoids can provide a powerful model for this heterogeneous pathology. Formation of microvillus inclusions from multiple membrane sources showed an unexpected dynamic of the enterocyte brush border. Keywords: Microvillus Atrophy, Disease Modeling, Brush Border Formation, Apical Vesicular Transpor

Immune escape of colorectal tumors via local LRH-1/Cyp11b1-mediated synthesis of immunosuppressive glucocorticoids.

Control of tumor development and growth by the immune system critically defines patient fate and survival. What regulates the escape of colorectal tumors from destruction by the immune system is currently unclear. Here, we investigated the role of intestinal synthesis of glucocorticoids in the tumor development during inflammation-induced mouse model of colorectal cancer. We demonstrate that the local synthesis of immunoregulatory glucocorticoids has dual roles in the regulation of intestinal inflammation and tumor development. In the inflammation phase LRH-1/Nr5A2-regulated and Cyp11b1-mediated intestinal glucocorticoid synthesis prevents tumor development and growth. In established tumors, however, tumor-autonomous Cyp11b1-mediated glucocorticoid synthesis suppresses anti-tumor immune responses and promotes immune escape. Transplantation of glucocorticoid synthesis-proficient colorectal tumor organoids into immunocompetent recipient mice resulted in rapid tumor growth, whereas transplantation of Cyp11b1-deleted and glucocorticoid synthesis-deficient tumor organoids was characterized by reduced tumor growth and increased immune cell infiltration. In human colorectal tumors, high expression of steroidogenic enzymes correlated with the expression of other immune checkpoints and suppressive cytokines, and negatively correlated with overall patients' survival. Thus, LRH-1-regulated tumor-specific glucocorticoid synthesis contributes to tumor immune escape and represents a novel potential therapeutic target

Network analysis in systems nutrition

Network analysis can be useful to put the results of genetics analyses into biological context. This chapter reviews approaches to network analysis and their usefulness in integrating different data types in the study of the impact of nutritional interventions on biological systems. It details some of the most common networks, such as metabolic networks, protein-protein interaction networks, gene co-expression networks, and regulatory networks. Metabolic networks can be found in the Kyoto Encyclopedia of Genes and Genomes (KEGG), HumanCyc, Edinburgh Human Metabolic Network (EHMN), and Human Metabolic Reconstruction (Recon2) databases. Metabolomic data were associated with each single-nucleotide polymorphism (SNP) in the genetic dataset using genome-wide association study (GWAS), then significant SNP results were used as input to the VEGAS algorithm to determine gene-level R-values from SNP-level data. The chapter describes different studies in which network analysis was useful in analyzing results from GWAS, expression quantitative trait loci (eQTL), transcriptomics data and multi-omics studies

Supplementary Figures 1-12 from Colorectal Cancer Organoid–Stroma Biobank Allows Subtype-Specific Assessment of Individualized Therapy Responses

Supplementary Figure S1 shows light microscopic images of CRC organoids and CAFs. Supplementary Figure S2 shows immunostaining and RNA sequencing analysis of cultured CAFs. Supplementary Figure S3 shows chromosomal copy number changes in tumors and matched organoids. Supplementary Figure S4 shows the transcriptional variation among tumors and organoids. Supplementary Figure S5 shows the classification of cancer intrinsic subtypes (CRIS) in tumors, matched organoids and xenotransplants. Supplementary Figure S6 shows the tissue microarray analysis of the of tumor samples from the colorectal cancer organoid-stroma biobank cohort. Supplementary Figure S7 shows the association of growth characteristics with molecular features of colorectal cancer organoid-stroma biobank. Supplementary Figure S8 shows the shows CMS and CRIS classifications of tumors and of matched organoids in different contexts. Supplementary Figure S9 describes the establishment of a drug screening workflow in 3D organoid-stroma co-cultures. Supplementary Figure S10 describes the development of a dual luciferase assay to study cell viability simultaneously in organoids and CAFs. Supplementary Figure S11 demonstrates that the MET inhibitor BAY-474 sensitizes Gefitinib resistant co-cultures. Supplementary Figure S12 shows the association of identified sensitivity and resistance signatures with gene expression and prognosis in different CMS.</p

Supplementary Tables 1-12 from Colorectal Cancer Organoid–Stroma Biobank Allows Subtype-Specific Assessment of Individualized Therapy Responses

Supplementary Table S1 shows the clinical data of the CRC organoid-stroma cohort. Supplementary Table S2 shows the inventory of available materials and molecular analyses. Supplementary Table S3 shows the selected variant types for whole exome analysis. Supplementary Table S4 summarizes the genetic characterization of CRC models. Supplementary Table S5 shows the classification according to the consensus molecular subtypes (CMS). Supplementary Table S6 shows classification according to the CRC intrinsic subtypes (CRIS). Supplementary Table S7 summarizes the functional data in mono- and co-cultures. Supplementary Table S8 shows drug sensitivity of CRC organoids in co-culture with autologous and heterologous fibroblasts. Supplementary Table S9 show the drug sensitivity in all biobank models in mono- and co-culture. Supplementary Table S10 shows the cell viability data of the chemogenomic library screens in resistant co-culture models. Supplementary Table S11 shows the identified drug sensitivity and resistance signatures. Supplementary Table S12 lists all antibodies and primer sequences used in this study.</p