PO.CH02.02 · 化学
用于精准肿瘤学的原代类肿瘤模型的整合蛋白质基因组学
Integrated proteogenomics of primary tumoroid models for precision oncology
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
可扩展的原代肿瘤模型的可及性仍然是新治疗策略临床前评估的障碍。近来,原代类肿瘤(tumoroid)模型被开发出来,以辅助药物化合物的早期评估。这些模型由解离的原代肿瘤生成,可通过多次传代进行扩增,从传统的包埋圆顶(dome)阶段到悬浮状态,这使得能够生成大量类肿瘤以进行全面研究。类肿瘤细胞系从最初的早期传代包埋阶段到后期传代悬浮培养,均保持了亲本肿瘤潜在的基因组和转录组特征。这些模型非常适合于细胞内在性治疗干预的体外评估,也适合于细胞外在性治疗手段,因为来自亲本组织的肿瘤驻留免疫细胞和基质细胞在冻存的解离组织中得以保留。蛋白质基因组学(Proteogenomics)是将基因组、转录组和蛋白质组数据集整合起来,以揭示单一数据集无法发现的新生物学见解。类肿瘤代表了理解DNA变异、RNA表达和蛋白质表达之间关系的、生理相关性最高的肿瘤学模型。我们从类肿瘤模型生成了基于质谱的蛋白质组学数据,并与由全外显子组测序及全转录组数据生成的样本特异性数据库进行比对检索,以全面概览类肿瘤的生物学特征。这一稳健的分析进一步得到了类肿瘤药物响应数据的支持,这些类肿瘤暴露于一组标准的经典化疗化合物和小分子抑制剂。我们鉴定出一个携带致病性KRAS-G12C突变的结直肠癌肿瘤模型,并进一步评估了用临床KRAS-G12C抑制剂sotorasib治疗如何改变全局蛋白质表达。此外,我们分析了由DNA错配修复缺陷的子宫内膜肿瘤生成的高突变负荷类肿瘤,以更好地理解DNA超突变如何影响全局蛋白质表达。总体而言,这些研究建立了一条生成肿瘤细胞生物学整体视图的流程,从而能够发现新的生物标志物和药物靶点。
查看英文原文 English abstract
The availability of scalable primary oncology models remains an impediment to preclinical evaluation of new therapeutic strategies. Recently, primary tumoroid models have been developed to aid in early-phase evaluation of drug compounds. These models are generated from dissociated primary tumors and can be expanded through numerous passages, from a conventional, embedded dome stage through a suspension state, which allows for the generation of a large number of tumoroids for comprehensive studies. The tumoroid lines maintain the underlying genomic and transcriptomic signatures of the parent tumor from the initial, early-passage embedded stage to later-passage suspension cultures. These models are highly amendable to in vitro evaluation of cell-intrinsic therapeutic interventions, as well as cell-extrinsic modalities, since tumor-resident immune and stromal cells from the parent tissue are preserved in the cryopreserved dissociated tissue. Proteogenomics is the integration of genomic, transcriptomic, and proteomic datasets to uncover novel biological insights that cannot be uncovered with a single data set alone. Tumoroids represent the most physiologically relevant oncology models to understand the relationship between DNA variants, RNA expression, and protein expression. Mass spectrometry-based proteomic data were generated from the tumoroid models and searched against sample-specific databases generated from whole exome sequencing as well as whole transcriptome data for a comprehensive overview of the biology of the tumoroids. This robust analysis was further supported by drug response data of the tumoroids exposed to a standard set of classical chemotherapeutic compounds and small-molecule inhibitors. We identified a colorectal cancer tumor model with a pathogenic KRAS-G12C mutation, and how treatment with the clinical KRAS-G12C inhibitor sotorasib altered global protein expression was further evaluated. Additionally, high mutational burden tumoroids generated from deficient DNA mismatch repair endometrial tumors were analyzed to better understand how DNA hypermutation affects global protein expression. Collectively, these studies establish a pipeline to generate a holistic view of tumor cell biology, enabling for the discovery of new biomarkers and drug targets.
利益披露 Disclosure
S. P. Fahl, None..
A. Kleeman, None..
J. Maxwell, None..
Y. Bhurke, None..
J. Moore, None..
J. Arivalagan, None..
K. Colwell, None..
C. Ott, None..
K. Williams, None..
D. Gutierrez, None.