一个反应性物种反应模块,用于整合到基因组规模的代谢模型中,以获得更好的洞察力:应用于癌症
Subasree Sridhar1, Prerna Bhalla2, Justin Kullu2
1Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences Building - 1 and 2, Indian Institute of Technology Madras, Chennai, 600 036, India; Centre for Integrative Biology and Systems medicinE, Indian Institute of Technology Madras, Chennai, 600 036, India.
Metabolic engineering
|September 9, 2023
概括
这项研究引入了一个新的模块,用于在癌症研究的基因组规模代谢模型中建模反应性物种 (RS). 整合RS反应改善了癌症代谢模型,揭示了途径失调并指导了化的向策略.
科学领域:
- 代谢建模 代谢建模
- 癌症生物学 癌症生物学
- 反应性物种的生物化学反应性物种的生物化学
背景情况:
- 反应性物种 (RS) 在疾病中至关重要,但在基因组规模代谢 (GSM) 模型中表现不佳.
- 准确的代谢建模对于理解癌症和开发向治疗至关重要.
研究的目的:
- 开发一个可扩展的反应性物种 (RS) 反应模块,用于整合到人类代谢模型中.
- 通过结合RS动态来增强癌症的GSM模型.
- 为了确定特定癌症中的代谢失调,并评估铁灭向潜力.
主要方法:
- 开发了一个可扩展的RS反应模块.
- 整合了该模块与Recon 3D衍生的人类代谢模型,用于三个癌症:三阴性乳腺癌 (TNBC),高度血清性卵巢癌 (HGSOC) 和结直肠癌 (CRC).
- 与标准模型相比,在RS集成的GSM模型中分析了流量变化 (失调).
主要成果:
- 集成RS的GSM模型精确地确定了TNBC,HGSOC和CRC中显著的路径流失调节.
- 这些失调在缺乏RS模块的标准癌症模型中不那么明显.
- 这项研究表明,在这些癌症中,对铁死向的易度有着下降的顺序:TNBC > HGSOC > CRC.
结论:
- 开发的RS模块显著提高了癌症GSM模型的准确性和生物相关性.
- RS建模提供了对癌症特异性代谢变化的更深入的洞察.
- 这些发现为基于ferroptosis的治疗策略优先考虑癌症类型提供了基础.
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