Oregon Health and Science University, Biomedical Engineering Department, Portland, Oregon, United States.
Oregon Health and Science University, OHSU Center for Spatial Systems Biomedicine, Portland, Oregon, United States.
J Biomed Opt. 2020 May;25(5):1-18. doi: 10.1117/1.JBO.25.5.056004.
Advanced genetic characterization has informed cancer heterogeneity and the challenge it poses to effective therapy; however, current methods lack spatial context, which is vital to successful cancer therapy. Conventional immunolabeling, commonplace in the clinic, can provide spatial context to protein expression. However, these techniques are spectrally limited, resulting in inadequate capacity to resolve the heterogenous cell subpopulations within a tumor.
We developed and optimized oligonucleotide conjugated antibodies (Ab-oligo) to facilitate cyclic immunofluorescence (cyCIF), resulting in high-dimensional immunostaining.
We employed a site-specific conjugation strategy to label antibodies with unique oligonucleotide sequences, which were hybridized in situ with their complementary oligonucleotide sequence tagged with a conventional fluorophore. Antibody concentration, imaging strand concentration, and configuration as well as signal removal strategies were optimized to generate maximal staining intensity using our Ab-oligo cyCIF strategy.
We successfully generated 14 Ab-oligo conjugates and validated their antigen specificity, which was maintained in single color staining studies. With the validated antibodies, we generated up to 14-color imaging data sets of human breast cancer tissues.
Herein, we demonstrated the utility of Ab-oligo cyCIF as a platform for highly multiplexed imaging, its utility to measure tumor heterogeneity, and its potential for future use in clinical histopathology.
先进的遗传特征分析揭示了癌症异质性及其对有效治疗的挑战;然而,当前的方法缺乏空间背景,这对癌症治疗的成功至关重要。临床上常用的常规免疫标记可以提供蛋白质表达的空间背景。然而,这些技术在光谱上受到限制,导致无法充分解析肿瘤内异质细胞亚群。
我们开发并优化了寡核苷酸偶联抗体(Ab-oligo)以促进循环免疫荧光(cyCIF),从而实现高维免疫染色。
我们采用了一种位点特异性偶联策略,用独特的寡核苷酸序列标记抗体,这些寡核苷酸序列在原位与标记有常规荧光团的互补寡核苷酸序列杂交。优化了抗体浓度、成像链浓度、构型以及信号去除策略,以利用我们的 Ab-oligo cyCIF 策略生成最大的染色强度。
我们成功生成了 14 种 Ab-oligo 偶联物,并验证了它们的抗原特异性,在单重染色研究中保持不变。使用经过验证的抗体,我们生成了多达 14 种颜色的人乳腺癌组织成像数据集。
本文展示了 Ab-oligo cyCIF 作为高度多重成像平台的实用性,其用于测量肿瘤异质性的效用,以及在未来临床组织病理学中的潜在用途。