McMahon Nathan P, Solanki Allison, Jones Jocelyn, Kwon Sunjong, Chang Young-Hwan, Chin Koei, Nederlof Michel A, Gray Joe W, Gibbs Summer L
Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR 97201.
Center for Spatial Systems Biomedicine, Oregon Health and Science University, Portland, OR 97201.
Proc SPIE Int Soc Opt Eng. 2020 Feb;11219. Epub 2020 Feb 19.
Successful cancer treatment continues to elude modern medicine and its arsenal of therapeutic strategies. Therapy resistance is driven by significant tumor heterogeneity, complex interactions between malignant, microenvironmental and immune cells and cross talk between signaling pathways. Advances in molecular characterization technologies such as next generation sequencing have helped unravel this network of interactions and identify druggable therapeutic targets. Tyrosine kinase inhibitors (TKI) are a class of drugs seeking to inhibit signaling pathways critical to sustaining proliferative signaling, resisting cell death, and the other hallmarks of cancer. While tumors may initially respond to TKI therapy, disease progression is near universal due to mechanisms of acquired resistance largely involving cellular signaling pathway reprogramming. With the ultimate goal of improved TKI therapeutic efficacy our group has developed intracellular paired agent imaging (iPAI) to quantify drug target interactions and oligonucleotide conjugated antibody (Ab-oligo) cyclic immunofluorescence (cycIF) imaging to characterize perturbed signaling pathways in response to therapy. iPAI uses spectrally distinct, fluorescently labeled targeted and untargeted drug derivatives, correcting for non-specific drug distribution and facilitating quantitative assessment of the drug binding before and after therapy. Ab-oligo cycIF exploits hybridization of complementary oligonucleotides for biomarker labeling while oligonucleotide modifications facilitate signal removal for sequential rounds of fluorescent tagging and imaging. Ab-oligo CycIF is capable of generating extreme multi-parametric images for quantifying total and phosphorylated protein expression to quantify protein activation, expression, and spatial distribution. Together iPAI and Ab-oligo cycIF can be applied to interrogate drug uptake and target binding as well as changes to heterogenous cell populations within tumors that drive variable therapeutic responses in patients.
成功的癌症治疗仍然是现代医学及其一系列治疗策略难以实现的目标。治疗耐药性是由显著的肿瘤异质性、恶性细胞、微环境细胞和免疫细胞之间复杂的相互作用以及信号通路之间的相互作用驱动的。下一代测序等分子表征技术的进步有助于揭示这种相互作用网络，并确定可成药的治疗靶点。酪氨酸激酶抑制剂（TKI）是一类旨在抑制对维持增殖信号、抵抗细胞死亡及癌症其他特征至关重要的信号通路的药物。虽然肿瘤最初可能对TKI治疗有反应，但由于获得性耐药机制（主要涉及细胞信号通路重编程），疾病进展几乎是普遍现象。为了提高TKI治疗效果这一最终目标，我们团队开发了细胞内配对试剂成像（iPAI）来量化药物靶点相互作用，以及寡核苷酸偶联抗体（Ab-oligo）循环免疫荧光（cycIF）成像来表征治疗后受干扰的信号通路。iPAI使用光谱不同、荧光标记的靶向和非靶向药物衍生物，校正非特异性药物分布，并便于定量评估治疗前后的药物结合情况。Ab-oligo cycIF利用互补寡核苷酸杂交进行生物标志物标记，而寡核苷酸修饰有助于在连续几轮荧光标记和成像中去除信号。Ab-oligo CycIF能够生成极端多参数图像，用于量化总蛋白和磷酸化蛋白表达，以量化蛋白激活、表达和空间分布。iPAI和Ab-oligo cycIF一起可用于研究药物摄取和靶点结合，以及肿瘤内异质细胞群的变化，这些变化会导致患者产生不同的治疗反应。
