小鼠手术模型中扩展 78% 肝切除术
May 24th, 2024
部分 2/3 （66%） 肝切除术的小鼠模型在文献中有很好的描述，但很少使用更扩展的肝切除术，模仿肝移植后的小尺寸综合征。我们描述了在小鼠模型中延长的 78% 肝切除术程序，该手术在健康小鼠中导致约 50% 的术后致死率。
我们的研究范围是评估增强肝脏再生和修复的治疗策略，这些策略可能有助于改善患者在使用边缘肝移植进行肝移植时的结果，以及延长肝切除术对原发性无功能和急性肝衰竭风险较高的癌症的治疗策略。我们的团队利用基因组学、蛋白质组学和代谢组学平台来研究肝脏再生，并确定新的治疗靶点以改善结果。我们实验室的重点是开发最先进的基因治疗平台，以提供保肝和肝脏再生基因A20。
我们揭示了 A20（也称为 TNFAIP3）在其肝细胞中结合的抗炎、抗凋亡和增殖功能的有效肝脏保护功能。肝脏靶向A20基因疗法在中毒性肝炎小鼠模型中免受致死，延长了78%，致命的根治性肝切除术延长了90%，并且还延长了肝缺血。最近在大型动物中有前途的前转化前研究为该疗法的临床转化奠定了基础。
该协议提供了一种独特的手术模型，旨在研究小尺寸综合征，以及评估治疗策略，以改善癌症广泛肝切除术的结果，并提高边际和扩展标准肝移植的成功率。当正确进行78%肝切除术时，该手术导致约50%的术后生存率，而与健康小鼠的经典2/3部分肝切除术相关的生存率接近100%。
概述
本研究调查了一个扩展78%肝切除的小鼠模型，该模型更好地模拟了肝移植后的小于大小综合征。研究结果表明，健康小鼠的术后存活率约为50%，这与传统的三分之二部分肝切除术相关的近100%存活率形成鲜明对比。
关键研究组成部分
研究领域
- 肝脏再生与修复
- 肝移植
- 提高预后的治疗策略
背景
- 扩展肝切除在文献中很少被探索。
- 边缘性肝移植物及其在移植环境中的风险是关键挑战。
- 以基因治疗为重点的肝细胞保护和再生是本研究的前沿。
使用的方法
- 扩展肝切除的小鼠模型
- 靶向肝脏的基因治疗
- 用于研究肝脏生物学的基因组和蛋白质组学平台
主要结果
- 成功实施了一种手术程序，导致50%的术后存活率。
- A20基因治疗表现出肝脏保护功能，改善了存活结果。
- 该模型可作为研究小于大小综合征和治疗干预的基础。
结论
- 调查扩展肝切除可以带来对肝脏疾病的更好理解和治疗。
- 该模型可以显著促进优化肝移植策略。
常见问题
Executive Industry Relevance
The extended 78% hepatectomy mouse model provides a rigorous platform for evaluating liver regenerative capacity and therapeutic interventions relevant to transplantation and oncology. This model enables mechanistic de-risking of candidate therapies and supports predictive confidence in preclinical assessment of small-for-size syndrome and marginal graft function. Its strategic value lies in bridging discovery biology with translational research for high-risk hepatic indications.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables interrogation of regenerative pathways and identification of therapeutic targets for liver repair.
- Supports biological de-risking by modeling clinically relevant hepatic insufficiency.
- Facilitates functional validation of gene therapies and hepatoprotective agents.
Screening & Assay Development
- Provides a validated in vivo system for quantitative assessment of liver regeneration and survival outcomes.
- Enables reproducible evaluation of candidate interventions under stringent regenerative stress.
- Supports standardization of efficacy benchmarks for hepatoprotective compounds.
Translational & Preclinical Research
- Aligns with disease-relevant endpoints for small-for-size syndrome and marginal graft transplantation.
- Enables continuity from mechanistic discovery to preclinical validation of gene therapies such as A20.
- Supports risk-adjusted advancement of therapeutic strategies targeting hepatic failure.
Pipeline & Workflow Integration
This model integrates into the discovery-to-preclinical continuum for liver-targeted therapies, supporting both target validation and translational biomarker development.
- Discovery Biology: Facilitates hypothesis testing for regenerative and hepatoprotective mechanisms.
- Screening: Provides quantitative survival and regeneration metrics for candidate evaluation.
- Analytics: Enables genomic, proteomic, and metabolomic profiling of regenerative responses.
- Translational Research: Bridges preclinical efficacy with clinical relevance in transplantation and oncology settings.
- Enterprise Reuse: Serves as a reusable platform for cross-program evaluation of liver-directed interventions.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in liver regeneration studies.
- Operational Value: Standardizes in vivo assessment of therapeutic efficacy under high-risk conditions.
- Strategic Value: Informs go/no-go decisions for liver-targeted therapies and gene therapy platforms.
- Portfolio Impact: Supports risk-adjusted prioritization of candidates for hepatic indications.
Implementation Considerations
- Requires advanced surgical expertise and rigorous perioperative management.
- Demands access to genomic, proteomic, and metabolomic analytical infrastructure.
- Necessitates cross-team standardization of surgical and analytical protocols.
- Adaptation to other preclinical models may require protocol optimization.
- Survival endpoints and regenerative thresholds must be clearly defined for reproducibility.
