Anti–tumor necrosis factor (anti-TNF) therapy resistance is a major clinical challenge in inflammatory bowel disease (IBD), due, in part, to insufficient understanding of disease-site, protein-level mechanisms. Although proteomics data from IBD mouse models exist, data and phenotype discrepancies contribute to confounding translation from preclinical animal models of disease to clinical cohorts. We developed an approach called translatable components regression (TransComp-R) to overcome interspecies and trans-omic discrepancies between mouse models and human subjects. TransComp-R combines mouse proteomic data with patient pretreatment transcriptomic data to identify molecular features discernable in the mouse data that are predictive of patient response to therapy. Interrogating the TransComp-R models revealed activated integrin pathway signaling in patients with anti–TNF-resistant colonic Crohn’s disease (cCD) and ulcerative colitis (UC). As a step toward validation, we performed single-cell RNA sequencing (scRNA-seq) on biopsies from a patient with cCD and analyzed publicly available immune cell proteomics data to characterize the immune and intestinal cell types contributing to anti-TNF resistance. We found that ITGA1 was expressed in T cells and that interactions between these cells and intestinal cell types were associated with resistance to anti-TNF therapy. We experimentally showed that the α₁ integrin subunit mediated the effectiveness of anti-TNF therapy in human immune cells. Thus, TransComp-R identified an integrin signaling mechanism with potential therapeutic implications for overcoming anti-TNF therapy resistance. We suggest that TransComp-R is a generalizable framework for addressing species, molecular, and phenotypic discrepancies between model systems and patients to translationally deliver relevant biological insights.

抗肿瘤坏死因子 (anti-TNF) 治疗抵抗是炎症性肠病 (IBD) 的主要临床挑战，部分原因是对疾病部位、蛋白质水平机制的了解不足。尽管存在来自 IBD 小鼠模型的蛋白质组学数据，但数据和表型差异导致了从疾病的临床前动物模型到临床队列的混淆。我们开发了一种称为可翻译成分回归 (TransComp-R) 的方法来克服小鼠模型和人类受试者之间的种间和跨组差异。TransComp-R 将小鼠蛋白质组学数据与患者治疗前转录组学数据相结合，以识别小鼠数据中可识别的分子特征，这些特征可预测患者对治疗的反应。询问 TransComp-R 模型显示，在抗 TNF 耐药的结肠克罗恩病 (cCD) 和溃疡性结肠炎 (UC) 患者中，整合素通路信号传导激活。作为验证的一步，我们对一名 cCD 患者的活检进行了单细胞 RNA 测序 (scRNA-seq)，并分析了公开可用的免疫细胞蛋白质组学数据，以表征导致抗 TNF 耐药性的免疫和肠道细胞类型。我们发现ITGA1在 T 细胞中表达，这些细胞和肠道细胞类型之间的相互作用与抗 TNF 治疗的抗性有关。我们通过实验表明，α ₁整联蛋白亚基介导了人类免疫细胞中抗 TNF 治疗的有效性。因此，TransComp-R 确定了一种整合素信号传导机制，对克服抗 TNF 治疗耐药性具有潜在的治疗意义。我们建议 TransComp-R 是一个可推广的框架，用于解决模型系统和患者之间的物种、分子和表型差异，以转化地提供相关的生物学见解。