A tissue atlas of ulcerative colitis revealing evidence of sex-dependent differences in disease-driving inflammatory cell types and resistance to TNF inhibitor therapy

Author:

Mayer Aaron T.123ORCID,Holman Derek R.24ORCID,Sood Anav5ORCID,Tandon Utkarsh3,Bhate Salil S.6ORCID,Bodapati Sunil3,Barlow Graham L.6ORCID,Chang Jeff3ORCID,Black Sarah6ORCID,Crenshaw Erica C.4ORCID,Koron Alexander N.4,Streett Sarah E.4ORCID,Gambhir Sanjiv S.12ORCID,Sandborn William J.7ORCID,Boland Brigid S.7,Hastie Trevor5ORCID,Tibshirani Robert5ORCID,Chang John T.7,Nolan Garry P.68ORCID,Schürch Christian M.689ORCID,Rogalla Stephan24ORCID

Affiliation:

1. Department of Bioengineering, Stanford University School of Medicine, Stanford, CA, USA.

2. Molecular Imaging Program at Stanford, Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.

3. Enable Medicine LLC, Menlo Park, CA, USA.

4. Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.

5. Department of Biomedical Data Science and of Statistics, Stanford University School of Medicine, Stanford, CA, USA.

6. Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA.

7. Division of Gastroenterology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.

8. Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.

9. Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany.

Abstract

Although literature suggests that resistance to TNF inhibitor (TNFi) therapy in patients with ulcerative colitis (UC) is partially linked to immune cell populations in the inflamed region, there is still substantial uncertainty underlying the relevant spatial context. Here, we used the highly multiplexed immunofluorescence imaging technology CODEX to create a publicly browsable tissue atlas of inflammation in 42 tissue regions from 29 patients with UC and 5 healthy individuals. We analyzed 52 biomarkers on 1,710,973 spatially resolved single cells to determine cell types, cell-cell contacts, and cellular neighborhoods. We observed that cellular functional states are associated with cellular neighborhoods. We further observed that a subset of inflammatory cell types and cellular neighborhoods are present in patients with UC with TNFi treatment, potentially indicating resistant niches. Last, we explored applying convolutional neural networks (CNNs) to our dataset with respect to patient clinical variables. We note concerns and offer guidelines for reporting CNN-based predictions in similar datasets.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference51 articles.

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