Crohn Disease, Ulcerative Colitis
Conditions
Keywords
Ulcerative Colitis, Crohn Disease, Stenosis, Post-operative recurrence, IBD, Biomarker prediction, Stricturing disease
Brief summary
A portion of patients with Inflammatory bowel disease often require surgical intervention since they do not respond to the current therapies. Besides this risk, patients may develop post-operative disease complications, and the factors beneath are far from being understood or predicted. The investigators hypothesize that some priming factors remain in the resection margin after surgery and act as a memory of the evolution of the disease, leading to the recurrence or complications. The following proposals are made: 1. defining and validating in humanized experimental models of intestinal inflammation the spatial and temporal dynamics of the postoperative complications-priming factors 2. integrating them into a machine-learning-driven model to determine risk indices of disease recurrence in IBD patients. This risk prediction model will not change the clinical decision-making process but will only be built for research. Consequently, patients enrolled in this study will be monitored and treated as per the standard of care. This project will reveal possible causes and build methods predictive of postoperative complications ultimately resulting in changes in clinical management in the near future.
Detailed description
A portion of patients with Inflammatory bowel disease often require surgical intervention since they do not respond to the current therapies. Besides this risk, patients may develop post-operative disease complications, and the factors beneath are far from being understood or predicted. The investigators hypothesize that some priming factors remain in the resection margin after surgery and act as a memory of the evolution of the disease, leading to the recurrence or complications. The following proposals are made: 1. defining and validating in humanized experimental models of intestinal inflammation the spatial and temporal dynamics of the postoperative complications-priming factors 2. integrating them into a machine-learning-driven model to determine risk indices of disease recurrence in IBD patients. This risk prediction model will not change the clinical decision-making process but will only be built for research. Consequently, patients enrolled in this study will be monitored and treated as per standard of care. This project will reveal possible causes and build methods that could help predict postoperative complications ultimately resulting in changes in clinical management.
Interventions
PROCEDURECD patients
The study will involve the collection of leftover surgical material after pathologist analysis, mucosal brushes, an additional volume of blood and feces of patients at the time of surgery
PROCEDUREUC patients
The study will involve the collection of leftover surgical material after pathologist analysis, mucosal brushes, an additional volume of blood and feces of patients at the time of surgery
Sponsors
IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo
Azienda Ospedaliera OO.RR. S. Giovanni di Dio e Ruggi D'Aragona
Ministero della Salute, Italy
IRCCS Ospedale San Raffaele
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 69 Years
Healthy volunteers
No
Inclusion criteria
* adult (age \>18 years) patients with histologically confirmed CD or UC undergoing intestinal resection due to stricturing disease, regardless of their current or past medical treatment; * given that it is an observational study, also pregnant and breastfeeding patients could be included; * able and willing to sign the informed consent.
Exclusion criteria
* patients \<18 years or \> 70 years; * patients with unconfirmed both UC and CD diagnoses; * patients with superimposed dysplasia or cancer diagnosis and resections for which post- operative endoscopic assessment of recurrence is not feasible; * patients unable or unwilling to sign the informed consent.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| To define spatial, cellular, and molecular characteristics of IBD-derived intestinal samples | 6 months from surgery | To define the spatial transcriptome of UC and CD-derived intestinal mucosa, IBD-derived tissues will be analized by spatial transcriptomics, either at molecular or at microbiota level on formalin-fixed paraffin-embedded (FFPE) tissues stored at our pathology unit. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| To determine the mechanism underlying post-operative complications by exploiting in-vivo (mouse) experimental models of intestinal inflammation. | 19-24 months from surgery | At the time of surgery, feces will be collected from patients. The microbial component from the IBD surgical specimens will be isolated and injected into humanized animal models. |
| To build the predictive model of postoperative complications based on spatially and temporally resolved IBD characteristics | 6-12 months from surgery | Other variables to be considered are CD4+ T-cells from the processing of blood |
Countries
Italy
Contacts
Primary ContactPierpaolo Sileri, MD. PhD.
Backup ContactFederica Ungaro, PhD.
Outcome results
None listed