Abstract 2276: Whole exome sequencing of immune-mediated colitis in cancer patients treated with immune checkpoint inhibitors
Bibliographic record
Abstract
Abstract Background: Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, providing survival benefits across multiple cancer types. Despite this remarkable advancement, ∼15-30% of patients develop immune-related adverse events (irAEs). One of the common irAEs is immune-mediated colitis, and the incidence ranges from 1% to 25% by type of therapy. Previously, we have shown that polygenic risk scores of ulcerative colitis predict colitis irAE. However, the role of rare coding variants on the development of colitis irAE remains largely unknown. Methods: We conducted whole exome sequencing for colitis irAE in 1, 215 cancer patients treated with ICIs. Association analyses were carried out for each gene separately for protein-truncating missense variants, predicted splice (Sp) variants, and non-synonymous predicted deleterious (deN; CADD≥20 or VEST≥0.8) or any non-synonymous (N) variants. The main association analyses were burden tests in which genotypes were collapsed to a 0/1 variable based on whether samples carried a variant of the given class. All models were adjusted for age at diagnosis, sex, type of ICI therapy, recruitment site, and five ancestry-informative principal components. The exome-wide threshold for significance was set at 2.5 × 10-6, with genes beyond this considered significant. Results: Among 1, 215 patients treated with immune checkpoint inhibitors (ICIs), 60 (4.9%) developed colitis. We identified rare coding variants in two genes associated with an increased risk of colitis at the exome-wide significance level: PT+Sp+N variants in LRRC47 (OR = 5.5, P = 2.4 × 10-6) and PT+S+deN variants in PFKP (OR = 65.9, P = 1.2 × 10-6). Additionally, PT+S+deN variants in PTPRH showed a suggestive association with colitis irAEs (OR = 8.8, P = 7.1 × 10-5). Conclusions: To our knowledge, this is the first study to assess the role of rare coding variants in colitis immune-related adverse events (irAEs) among cancer patients treated with ICIs. Our findings highlight two exome-wide significant associations, implicating variants in LRRC47 and PFKP in the development of colitis irAEs. LRRC47 has previously been linked to inflammatory bowel disease through differential methylation patterns. Furthermore, genes involved in glycolysis, including PFKFB3, PKM, and PFKP, have been shown to be upregulated in patients with ulcerative colitis. Abnormal activity of PTPRH has also been reported to disrupt the regulatory mechanisms of the intestinal mucosa, potentially contributing to inflammation. These findings provide novel insights into the genetic underpinnings of colitis irAEs in cancer immunotherapy. Citation Format: Pooja Middha, 1 Zoe Quandt, 2 Karmugi Balaratnam, 3 Eduardo Cardenas, 1 Christina J. Falcon, 4 Princess Margaret Lung Group, Matthew A. Gubens, 1 Scott Huntsman, 1 Khaleeq Khan, 3 Min Li, 1 Christine M. Lovly, 5 Devalben Patel, 3 Luna Jia Zhan, 3 Melinda C. Aldrich, 6 Geoffrey Liu, 7 Adam J. Schoenfeld, 4 Elad Ziv1. Whole exome sequencing of immune-mediated colitis in cancer patients treated with immune checkpoint inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2276.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".