NEW YORK — By generating a tissue atlas of ulcerative colitis, researchers have uncovered the presence of inflammatory cell types that may contribute to treatment resistance.
Ulcerative colitis, an inflammatory bowel disease, stems from a combination of genetic, immune, environmental, and microbiome factors. Its associated chronic inflammation can also increase affected individuals' risk of developing colorectal cancer. While new therapeutics like targeted modulatory drugs, including the tumor necrosis factor (TNF) inhibitors infliximab and adalimumab, have led to longer remissions and have fewer side effects, they are linked to an increased risk of infections and other cancers, and not all patients respond to treatment.
Researchers led by Stanford University School of Medicine's Stephan Rogalla generated a tissue atlas of ulcerative colitis as a starting point to uncover predictive biomarkers to identify the best treatment for individual patients. As they reported in Science Advances on Friday, they used a highly multiplexed immunofluorescence imaging approach called CODEX to create a spatial atlas. With this, they examined the relationship between cells as well as cellular niches and their responses to TNF inhibitors, finding some signals associated with treatment resistance.
"Our research suggests that examining cells within their spatial context may offer insights into developing biomarkers for therapy response in UC and that this framework has the potential to improve our understanding of inflammatory immune diseases," Rogalla and colleagues wrote in their paper.
CODEX, short for co-detection by indexing, allows researchers to simultaneously visualize up to 60 biomarkers on tissue samples with single-cell resolution. Based on the various biomarkers, investigators can identify different cell types and their states and then examine them spatially to tease out cell-cell interactions and to identify cellular neighborhoods.
In their study, Rogalla and colleagues analyzed 52 biomarkers in 42 colon tissue biopsies obtained from 29 patients with UC and five healthy controls. Of those with UC, 15 were being treated with a TNF inhibitor at the time of the biopsy, and about half of those did not respond to that treatment.
In all, the researchers examined 1.7 million single cells and identified 13 distinct cell-type clusters: eight different immune cell clusters, two epithelial cell clusters, a smooth muscle cluster, a mixed stroma cluster, and a vasculature cluster. Comparing the frequency of cells in these clusters to UC severity scores, they noted changes in T cells, epithelial cells, plasma cells, granulocytes, dendritic cells, and intraepithelial T cells associated with disease state.
The researchers have made this spatial atlas, which they said could be used for biomarker discovery and clinical correlation analyses, available through a cloud-based tool called Explorer.
They applied their tool to identify cell types, cell interactions, or cell neighborhoods that behaved differently based on TNFi treatment status. For instance, they found UC patients undergoing TNFi treatment had a subset of inflammatory cell types and cellular neighborhoods, which they said could reflect resistant niches.
They further found that female UC patients undergoing treatment had enriched levels of adaptive immune cells, contacts, and cellular neighborhoods compared to male patients. This, they noted, could reflect the higher TNF inhibitor response rate typically reported among women.
The researchers cautioned, though, that while they have identified architecture motifs associated with TNF inhibitor response, the mechanism of that response is unknown. "The presence of these motifs provides insights into the cellular basis of inflammation, although it is still uncertain as to whether these motifs are inherently pathological or whether they are required components of a normal inflammatory response and it is only their aberrant persistence that is pathological," Rogalla and colleagues wrote. They added that further studies in animal models are needed.