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Hookworm Therapy for young people at high risk for colorectal cancer

ABSTRACT: Interventions: Open label Phase 1b proof of concept study to test for dysbiosis in small cohort of people identified as at risk for developing colorectal cancer (CRC) based on the background of conventional adenomatous polyps, and the potential of a light infection with hookworm to improve microbial richness and diversity. All participants will receive in total 20 hookworm larvae (L3) to be applied by the study nurse as two doses of 10x L3 to the skin approximately 4 weeks apart. The L3 will be applied to a non-adherent dressing which will be placed on the forearm of the participant. The dressing will need to remain in place for the remainder of the day, and disposed of at night. Analyses of blood and rectal mucosal immune responses, mucosal and faecal microbiomes will be undertaken pre and 12 months post hookworm infection. The fidelity of the hookworm intervention will be monitored by participant reported incidence of a rash at the inoculation site (the first week after inoculation) and laboratory tests for the typical immune response (eosinophilia) and the presence of parasite eggs in faecal samples taken at the post-inoculation clinic visits. Primary outcome(s): A composite primary outcome including measurements of bacterial species richness (number of observed operational taxonomic units, OTUs) and bacterial species diversity (Shannon Index) in faecal and colon biopsy specimens, determined by shotgun metagenomic sequencing[Week 52 post hookworm inoculation] Study Design: Purpose: Prevention; Allocation: Non-randomised trial; Masking: Open (masking not used);Assignment: Single group;Type of endpoint: Efficacy

DISEASE(S): Colorectal Cancer,Cancer-bowel-back Passage (rectum) Or Large Bowel (colon)

PROVIDER: 2469531 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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Project description:Leber2015 - Mucosal immunity and gut microbiome interaction during C. difficile infection This model is described in the article: Systems Modeling of Interactions between Mucosal Immunity and the Gut Microbiome during Clostridium difficile Infection. Leber A, Viladomiu M, Hontecillas R, Abedi V, Philipson C, Hoops S, Howard B, Bassaganya-Riera J. PLoS ONE 2015; 10(7): e0134849 Abstract: Clostridium difficile infections are associated with the use of broad-spectrum antibiotics and result in an exuberant inflammatory response, leading to nosocomial diarrhea, colitis and even death. To better understand the dynamics of mucosal immunity during C. difficile infection from initiation through expansion to resolution, we built a computational model of the mucosal immune response to the bacterium. The model was calibrated using data from a mouse model of C. difficile infection. The model demonstrates a crucial role of T helper 17 (Th17) effector responses in the colonic lamina propria and luminal commensal bacteria populations in the clearance of C. difficile and colonic pathology, whereas regulatory T (Treg) cells responses are associated with the recovery phase. In addition, the production of anti-microbial peptides by inflamed epithelial cells and activated neutrophils in response to C. difficile infection inhibit the re-growth of beneficial commensal bacterial species. Computational simulations suggest that the removal of neutrophil and epithelial cell derived anti-microbial inhibitions, separately and together, on commensal bacterial regrowth promote recovery and minimize colonic inflammatory pathology. Simulation results predict a decrease in colonic inflammatory markers, such as neutrophilic influx and Th17 cells in the colonic lamina propria, and length of infection with accelerated commensal bacteria re-growth through altered anti-microbial inhibition. Computational modeling provides novel insights on the therapeutic value of repopulating the colonic microbiome and inducing regulatory mucosal immune responses during C. difficile infection. Thus, modeling mucosal immunity-gut microbiota interactions has the potential to guide the development of targeted fecal transplantation therapies in the context of precision medicine interventions. This model is hosted on BioModels Database and identified by: BIOMD0000000583. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Analysis of gingival crevicular fluid (GCF) samples may give information of the identity of unattached (planktonic) subgingival bacteria, the 35 forefront candidates for systemic dispersal via ulcerated periodontal pocket epithelium. Our study represents the first one targeting the identity of bacteria in gingival crevicular fluid. Methodology/Principal findings: We determined bacterial species diversity in GCF samples of a group of periodontitis patients and delineated contributing bacterial and host-associated factors. Subgingival paper point (PP) samples from the same sites were taken for comparison. After DNA extraction, 16S rRNA genes were PCR amplified and DNA-DNA hybridization was performed using a microarray for over 300 bacterial species or groups. Altogether 133 species from 41 genera and 8 phyla 45 were detected with 9 to 62 and 18 to 64 species in GCF and PP samples, respectively, 46 per patient. Projection to latent structures by means of partial least squares (PLS) was applied to the multivariate data analysis. PLS regression analysis showed that species of genera including Campylobacter, Selenomonas, Porphyromonas, Catonella, Tannerella, Dialister, Peptostreptococcus, Streptococcus and Eubacterium had significant positive correlations and the number of teeth with low-grade attachment loss a significant negative correlation to species diversity in GCF samples. OPLS/O2PLS discriminant analysis revealed significant positive correlations to GCF sample group membership for species of genera Campylobacter, Leptotrichia, Prevotella, Dialister, Tannerella, Haemophilus, Fusobacterium, Eubacterium, and Actinomyces. Conclusions/Significance: Among a variety of detected species those traditionally classified as Gram-negative anaerobes growing in mature subgingival biofilms were the main predictors for species diversity in GCF samples as well as responsible for distinguishing GCF samples from PP samples. GCF bacteria may provide new prospects for studying dynamic properties of subgingival biofilms. The microbial profiles of GCF and subgingival plaque were analyzed from 17 subjects with periodontal disease.

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Hookworm Therapy for young people at high risk for colorectal cancer

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