Center for Immunotherapy Research, Houston Methodist Research Institute, Houston, Texas 77030, United States.
Department of Medicine, Weill Cornell Medical College, New York, New York 10065, United States.
J Proteome Res. 2021 Jan 1;20(1):858-866. doi: 10.1021/acs.jproteome.0c00666. Epub 2020 Dec 8.
Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers. Dissecting the tumor cell proteome from that of the non-tumor cells in the PDAC tumor bulk is critical for tumorigenesis studies, biomarker discovery, and development of therapeutics. However, investigating the tumor cell proteome has proven evasive due to the tumor's extremely complex cellular composition. To circumvent this technical barrier, we have combined bioorthogonal noncanonical amino acid tagging (BONCAT) and data-independent acquisition mass spectrometry (DIA-MS) in an orthotopic PDAC model to specifically identify the tumor cell proteome . Utilizing the tumor cell-specific expression of a mutant tRNA synthetase transgene, this approach provides tumor cells with the exclusive ability to incorporate an azide-bearing methionine analogue into newly synthesized proteins. The azide-tagged tumor cell proteome is subsequently enriched and purified via a bioorthogonal reaction and then identified and quantified using DIA-MS. Applying this workflow to the orthotopic PDAC model, we have identified thousands of proteins expressed by the tumor cells. Furthermore, by comparing the tumor cell and tumor bulk proteomes, we showed that the approach can distinctly differentiate proteins produced by tumor cells from those of non-tumor cells within the tumor microenvironment. Our study, for the first time, reveals the tumor cell proteome of PDAC under physiological conditions, providing broad applications for tumorigenesis, therapeutics, and biomarker studies in various human cancers.
胰腺导管腺癌（PDAC）是最致命的癌症之一。从 PDAC 肿瘤块中的非肿瘤细胞中解析肿瘤细胞蛋白质组对于肿瘤发生研究、生物标志物发现和治疗药物的开发至关重要。然而，由于肿瘤极其复杂的细胞组成，研究肿瘤细胞蛋白质组一直具有挑战性。为了规避这一技术障碍，我们在原位 PDAC 模型中结合了生物正交非规范氨基酸标记（BONCAT）和无依赖数据获取质谱（DIA-MS），以特异性鉴定肿瘤细胞蛋白质组。利用突变 tRNA 合成酶转基因在肿瘤细胞中的特异性表达，这种方法为肿瘤细胞提供了将带有叠氮基的蛋氨酸类似物掺入新合成蛋白质中的独特能力。通过生物正交反应对叠氮标记的肿瘤细胞蛋白质组进行富集和纯化，然后使用 DIA-MS 进行鉴定和定量。将此工作流程应用于原位 PDAC 模型，我们已经鉴定出数千种由肿瘤细胞表达的蛋白质。此外，通过比较肿瘤细胞和肿瘤块蛋白质组，我们表明该方法可以明显区分肿瘤微环境中肿瘤细胞和非肿瘤细胞产生的蛋白质。我们的研究首次揭示了生理条件下 PDAC 的肿瘤细胞蛋白质组，为肿瘤发生、治疗和各种人类癌症的生物标志物研究提供了广泛的应用。
