Al Bakir Ibrahim, Curtius Kit, Cresswell George D, Grant Heather E, Nasreddin Nadia, Smith Kane, Nowinski Salpie, Guo Qingli, Belnoue-Davis Hayley L, Fisher Jennifer, Clarke Theo, Kimberley Christopher, Mossner Maximilian, Dunne Philip D, Loughrey Maurice B, Speight Ally, East James E, Wright Nicholas A, Rodriguez-Justo Manuel, Jansen Marnix, Moorghen Morgan, Baker Ann-Marie, Leedham Simon J, Hart Ailsa L, Graham Trevor A
Barts Cancer Institute, Queen Mary University of London, London, UK.
Inflammatory Bowel Disease Unit, St Mark's Hospital, Harrow, UK.
Gut. 2025 Apr 7;74(5):740-751. doi: 10.1136/gutjnl-2024-333353.
The risk of developing advanced neoplasia (AN; colorectal cancer and/or high-grade dysplasia) in ulcerative colitis (UC) patients with a low-grade dysplasia (LGD) lesion is variable and difficult to predict. This is a major challenge for effective clinical management.
We aimed to provide accurate AN risk stratification in UC patients with LGD. We hypothesised that the pattern and burden of somatic genomic copy number alterations (CNAs) in LGD lesions could predict future AN risk.
We performed a retrospective multicentre validated case-control study using n=270 LGD samples from n=122 patients with UC. Patients were designated progressors (n=40) if they had a diagnosis of AN in the ~5 years following LGD diagnosis or non-progressors (n=82) if they remained AN-free during follow-up. DNA was extracted from the baseline LGD lesion, low-coverage whole genome sequencing performed and data processed to detect CNAs. Survival analysis was used to evaluate CNAs as predictors of future AN risk.
CNA burden was significantly higher in progressors than non-progressors (p=2×10 in discovery cohort) and was a very significant predictor of AN risk in univariate analysis (OR=36; p=9×10), outperforming existing clinical risk factors such as lesion size, shape and focality. Optimal risk prediction was achieved with a multivariate model combining CNA burden with the known clinical risk factor of incomplete LGD resection. Within-LGD lesion genetic heterogeneity did not confound risk prediction.
Measurement of CNAs in LGD is an accurate predictor of AN risk in inflammatory bowel disease and is likely to support clinical management.
患有低级别异型增生（LGD）病变的溃疡性结肠炎（UC）患者发生高级别肿瘤（AN；结直肠癌和/或高级别异型增生）的风险是可变的，且难以预测。这是有效临床管理面临的一项重大挑战。
我们旨在为患有LGD的UC患者提供准确的AN风险分层。我们假设LGD病变中体细胞基因组拷贝数改变（CNA）的模式和负担可以预测未来的AN风险。
我们进行了一项回顾性多中心验证病例对照研究，使用了来自122例UC患者的270份LGD样本。如果患者在LGD诊断后的约5年内被诊断为AN，则被指定为进展者（n = 40）；如果在随访期间未发生AN，则为非进展者（n = 82）。从基线LGD病变中提取DNA，进行低覆盖度全基因组测序并处理数据以检测CNA。生存分析用于评估CNA作为未来AN风险的预测指标。
进展者的CNA负担显著高于非进展者（发现队列中p = 2×10），并且在单变量分析中是AN风险的非常显著的预测指标（OR = 36；p = 9×10），优于现有的临床风险因素，如病变大小、形状和局灶性。通过将CNA负担与LGD切除不完全这一已知临床风险因素相结合的多变量模型，实现了最佳风险预测。LGD病变内的基因异质性并未混淆风险预测。
LGD中CNA的测量是炎症性肠病中AN风险的准确预测指标，可能有助于临床管理。
