Heumos Simon, Dehn Sandra, Bräutigam Konstantin, Codrea Marius C, Schürch Christian M, Lauer Ulrich M, Nahnsen Sven, Schindler Michael
Quantitative Biology Center (QBiC), University of Tübingen, 72076, Tübingen, Germany.
Biomedical Data Science, Dept. of Computer Science, University of Tübingen, 72076, Tübingen, Germany.
Cancer Cell Int. 2022 Oct 11;22(1):311. doi: 10.1186/s12935-022-02710-y.
Immunotherapy with immune checkpoint inhibitors (ICI) has revolutionized cancer therapy. However, therapeutic targeting of inhibitory T cell receptors such as PD-1 not only initiates a broad immune response against tumors, but also causes severe adverse effects. An ideal future stratified immunotherapy would interfere with cancer-specific cell surface receptors only.
To identify such candidates, we profiled the surface receptors of the NCI-60 tumor cell panel via flow cytometry. The resulting surface receptor expression data were integrated into proteomic and transcriptomic NCI-60 datasets applying a sophisticated multiomics multiple co-inertia analysis (MCIA). This allowed us to identify surface profiles for skin, brain, colon, kidney, and bone marrow derived cell lines and cancer entity-specific cell surface receptor biomarkers for colon and renal cancer.
For colon cancer, identified biomarkers are CD15, CD104, CD324, CD326, CD49f, and for renal cancer, CD24, CD26, CD106 (VCAM1), EGFR, SSEA-3 (B3GALT5), SSEA-4 (TMCC1), TIM1 (HAVCR1), and TRA-1-60R (PODXL). Further data mining revealed that CD106 (VCAM1) in particular is a promising novel immunotherapeutic target for the treatment of renal cancer.
Altogether, our innovative multiomics analysis of the NCI-60 panel represents a highly valuable resource for uncovering surface receptors that could be further exploited for diagnostic and therapeutic purposes in the context of cancer immunotherapy.
免疫检查点抑制剂（ICI）免疫疗法彻底改变了癌症治疗方式。然而，靶向抑制性T细胞受体（如PD-1）进行治疗不仅会引发针对肿瘤的广泛免疫反应，还会导致严重的不良反应。理想的未来分层免疫疗法应仅干扰癌症特异性细胞表面受体。
为了确定此类候选受体，我们通过流式细胞术分析了NCI-60肿瘤细胞系的表面受体。将所得的表面受体表达数据应用复杂的多组学多重共惯性分析（MCIA）整合到蛋白质组学和转录组学NCI-60数据集中。这使我们能够识别皮肤、脑、结肠、肾和骨髓来源的细胞系的表面特征，以及结肠癌和肾癌的癌症实体特异性细胞表面受体生物标志物。
对于结肠癌，确定的生物标志物为CD15、CD104、CD324、CD326、CD49f；对于肾癌，生物标志物为CD24、CD26、CD106（VCAM1）、表皮生长因子受体（EGFR）、阶段特异性胚胎抗原-3（SSEA-3，由β-1,3-半乳糖基转移酶5编码）、阶段特异性胚胎抗原-4（SSEA-4，由跨膜和卷曲螺旋结构域1编码）、甲型肝炎病毒细胞受体1（TIM1，HAVCR1）和TRA-1-60R（podocalyxin样蛋白）。进一步的数据挖掘显示，特别是CD106（VCAM1）是治疗肾癌的一个有前景的新型免疫治疗靶点。
总之，我们对NCI-60细胞系进行的创新性多组学分析是一个非常有价值的资源，可用于发现那些在癌症免疫治疗背景下可进一步用于诊断和治疗目的的表面受体。
