PO.BCS01.04 · 生物信息与计算
结直肠癌免疫治疗反应预测因子：一种多组学方法
Immunotherapy response predictors in colorectal cancer: A multi-omics approach
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
由于获批的生物标志物疗效有限，预测免疫治疗（IT）结局仍是一项临床挑战。尽管异常糖基化已与肿瘤进展相关联，但其在预测IT结局中的作用尚未得到充分探索。为辅助患者分层，我们整合了基因组、转录组和糖组数据，以探索糖免疫基因的预测能力。使用无监督机器学习方法并通过两个独立队列进行交叉验证，我们开发了糖免疫特征（GlycoImmune Signature，GIS），这是一个由18个基因表达组成的特征，与改善的IT反应和生存结局相关。我们将GIS应用于来自TCGA-COAD的结直肠癌（CRC）样本，并表征其免疫浸润和蛋白组特征。MSI-H患者和预测的反应者（TIDE算法）表现出更高的GIS评分（p<0.0001）。与低GIS评分（GISL）病例相比，高GIS评分（GISH）患者表现出"热"肿瘤微环境（TME）和免疫相关特征的上调。有趣的是，约40%的MSI-L/MSS患者为GISH，提示GIS可能识别出那些可能对IT有反应但目前未被临床指南考虑的患者。将未经治疗样本的CD45+和肿瘤细胞的单细胞转录组数据（GSE200997）按患者聚合以生成假散装（pseudobulk）图谱，并将其分类为GISH和GISL。GISH肿瘤表现出效应CD8+ T细胞的富集以及Treg和Th17细胞浸润的减少，证实了先前的发现。将这些GISH和GISL相关的细胞状态映射到接受IT治疗患者（GSE205506）的细胞上，揭示GISH相关的效应CD8+ T细胞在反应者中细胞毒性更强且更为普遍，而来自GISL患者的效应CD8+ T细胞表达耗竭标志物（LAG3、PDCD1、CTLA4、EOMES、TOX）。反过来，GISH相关的Treg表现出调节性标志物（FOXP3、CTLA4、TIGIT）的缺失。为将我们的转录组标志物转化为蛋白组标志物，我们分析了TCGA-COAD中GISH患者的蛋白组数据，发现29个与免疫反应和细胞杀伤相关的上调蛋白，以及9个与代谢重编程相关的下调蛋白。在前者中，六个蛋白具有相关生物学作用且在CRC肿瘤中高表达，可作为经济高效的临床读数。总体而言，这些发现将GIS定位为CRC中IT反应的多组学替代指标，并凸显其扩大免疫治疗患者适用范围的潜力。
查看英文原文 English abstract
Predicting immunotherapy (IT) outcomes remains a clinical challenge as approved biomarkers show limited efficacy. Although aberrant glycosylation has been linked to tumor progression, its role in predicting IT outcomes is underexplored. With the goal of aiding in patient stratification, we integrated genomic, transcriptomic and glycomic data to explore the predictive capacity of glycoimmune genes. Using unsupervised machine-learning methods and cross-validation with two independent cohorts, we developed the GlycoImmune Signature (GIS), an 18-gene expression signature associated with improved response to IT and survival outcomes. We applied the GIS to colorectal cancer (CRC) samples from TCGA-COAD and characterized their immune infiltration and proteomic profiles. MSI-H patients and predicted responders (TIDE algorithm) showed higher GIS scores (p<0.0001). High GIS-scoring (GISH) patients exhibited a “hot” tumor microenvironment (TME) and upregulation of immune-related signatures compared to low GIS-scoring (GISL) cases. Interestingly, approximately 40% of MSI-L/MSS patients were GISH, suggesting that the GIS may identify patients who might respond to IT but are not currently considered by clinical guidelines. Single-cell transcriptomics data of CD45+ and tumor cells (GSE200997) of treatment-naïve samples were aggregated per patient to generate pseudobulk profiles and classify them into GISH and GISL. GISH tumors showed an enrichment of effector CD8+ T cells and reduced infiltration of Tregs and Th17 cells, confirming previous findings. Mapping these GISH and GISL-associated cell states onto cells from patients treated with IT (GSE205506) revealed that GISH-associated effector CD8+ T cells were more cytotoxic and prevalent in responders, while those from GISL patients expressed exhaustion markers ( LAG3, PDCD1, CTLA4, EOMES, TOX). In turn, GISH-associated Tregs showed the loss of regulatory markers ( FOXP3 , CTLA4 , TIGIT ). To translate our transcriptomic marker into a proteomic one, we analyzed proteomic data from GISH patients in TCGA-COAD, finding 29 upregulated proteins associated with immune response and cell killing, and 9 downregulated proteins associated with metabolic reprogramming. Among the former, six proteins present relevant biological roles and are highly expressed in CRC tumors, which could serve as cost-effective clinical readouts. Overall, these findings position the GIS as a multi-omics surrogate of IT response in CRC and highlight its potential to expand patient eligibility for immunotherapy.
利益披露 Disclosure
J. P. Merlo, None..
M. A. Scheidegger, None..
A. G. Blidner, None..
A. Cagnoni, None..
G. A. Rabinovich, None..
K. Mariño, None.