Plattner Christina, Lamberti Giorgia, Blattmann Peter, Kirchmair Alexander, Rieder Dietmar, Loncova Zuzana, Sturm Gregor, Scheidl Stefan, Ijsselsteijn Marieke, Fotakis Georgios, Noureen Asma, Lisandrelli Rebecca, Böck Nina, Nemati Niloofar, Krogsdam Anne, Daum Sophia, Finotello Francesca, Somarakis Antonios, Schäfer Alexander, Wilflingseder Doris, Gonzalez Acera Miguel, Öfner Dietmar, Huber Lukas A, Clevers Hans, Becker Christoph, Farin Henner F, Greten Florian R, Aebersold Ruedi, de Miranda Noel F C C, Trajanoski Zlatko
Biocenter, Institute of Bioinformatics, Medical University of Innsbruck, 6020 Innsbruck, Austria.
Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, 8092 Zurich, Switzerland.
iScience. 2023 Nov 4;26(12):108399. doi: 10.1016/j.isci.2023.108399. eCollection 2023 Dec 15.
Precision oncology approaches for patients with colorectal cancer (CRC) continue to lag behind other solid cancers. Functional precision oncology-a strategy that is based on perturbing primary tumor cells from cancer patients-could provide a road forward to personalize treatment. We extend this paradigm to measuring proteome activity landscapes by acquiring quantitative phosphoproteomic data from patient-derived organoids (PDOs). We show that kinase inhibitors induce inhibitor- and patient-specific off-target effects and pathway crosstalk. Reconstruction of the kinase networks revealed that the signaling rewiring is modestly affected by mutations. We show non-genetic heterogeneity of the PDOs and upregulation of stemness and differentiation genes by kinase inhibitors. Using imaging mass-cytometry-based profiling of the primary tumors, we characterize the tumor microenvironment (TME) and determine spatial heterocellular crosstalk and tumor-immune cell interactions. Collectively, we provide a framework for inferring tumor cell intrinsic signaling and external signaling from the TME to inform precision (immuno-) oncology in CRC.
结直肠癌(CRC)患者的精准肿瘤学方法仍落后于其他实体癌。功能精准肿瘤学——一种基于干扰癌症患者原发性肿瘤细胞的策略——可为个性化治疗提供一条前进的道路。我们通过从患者来源的类器官(PDO)获取定量磷酸化蛋白质组数据,将这一范式扩展到测量蛋白质组活性图谱。我们表明,激酶抑制剂会诱导抑制剂特异性和患者特异性的脱靶效应以及信号通路串扰。激酶网络的重建显示,信号重布线受突变的影响较小。我们展示了PDO的非遗传异质性以及激酶抑制剂对干性和分化基因的上调作用。通过基于成像质谱流式细胞术的原发性肿瘤分析,我们对肿瘤微环境(TME)进行了表征,并确定了空间异细胞串扰和肿瘤-免疫细胞相互作用。总体而言,我们提供了一个框架,用于推断肿瘤细胞内在信号以及来自TME的外部信号,以为CRC的精准(免疫)肿瘤学提供信息。