利用转录组数据推断癌细胞的代谢目标
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- 英文论文题名：Inferring Metabolic Tasks of Cancer Cells from Transcriptomics
- 论文作者：高帅师 ; 戴紫薇 ; 来鲁华
- 英文论文作者：Shuaishi Gao ; Ziwei Dai ; Luhua Lai ; Center for Quantitative Biology ; Academy for Advanced Interdisciplinary Studies ; Peking University ; BNLMS ; State Key for Structural Chemistry of Unstable and Stable Species ; College of Chemistry and Molecular Engineering ; Peking University
- 年：2016
- 作者机构：北京大学前沿交叉学科研究院定量生物学中心;北京大学化学与分子工程学院分子动态与稳态结构国家重点实验室分子科学国家实验室;
- 论文关键词：代谢目标 ; 流平衡分析 ; 帕累托优化 ; 全基因组范围的代谢网络
- 会议召开时间：2016-07-01
- 会议录名称：中国化学会第30届学术年会摘要集-第二十五分会：化学信息学与化学计量学
- 语种：中文
- 分类号：R730.2
- 学会代码：ZGHY
- 会议名称：中国化学会第30届学术年会-第二十五分会 ; 化学信息学与化学计量学
- 会议地点：中国辽宁大连
- 主办单位：中国化学会
- 学会名称：中国化学会
- 页数：1
- 文件大小：250k
- 原文格式：D
- 会议级别：全国
摘要
在癌细胞区别于正常细胞的诸多特征中,代谢异常是人们关注的重点。全基因组范围的代谢网络在很大程度上帮助我们理解这一系统水平上的复杂疾病。流平衡分析是最常见的代谢网络研究手段,其主要目的是求出在满足某一优化目标的情况下,系统可能的流分布~([1])。癌细胞优化目标,也就是流平衡分析的目标函数,目前还没有公认的结论。通常说来,生物体要同时完成多个任务才能达到最适的进化状态,而一个给定的表型又无法在所有任务上达到最优,所有可能的表型处于帕累托前沿上,顶点代表其中一个任务完成最优的情况~([2])。帕累托任务推断算法可以通过高维生物学数据,找到描述这些数据的帕累托前沿~([3]),再通过进一步分析,推断顶点的具体含义。本文利用这一算法分析了乳腺癌细胞的代谢相关的转录组数据,发现癌细胞有四个代谢目标,分别是生长增殖、能量产生、迁移以及维持氧化还原电位平衡。后续,还将进一步对这些代谢目标进行定量验证。
Alternative cancer metabolism is a major focus of cancer research.Genome-scale metabolic network is a powerful tool for understanding cancer in system level,and flux balance analysis(FBA) is a mathematical approach for analyzing the flow of metabolites through it.The best objective function in FBA describes the task of cell is not agreeable.Organisms need to perform multiple tasks that all contribute to fitness,while a given phenotype cannot be optimal at all tasks,all the possible phenotypes are in the Pareto front.Pareto task inference method(ParTI) can find the Pareto front as a polytope for high-dimensional biological data,and allow identification of the tasks the vertices represent.Here,we use this algorithm inferred four tasks,which is growth,energy production,metastasis and redox balance,of cancer cells through metabolic-related transcriptomics.There still a lot quantitative verification work in future.
Alternative cancer metabolism is a major focus of cancer research.Genome-scale metabolic network is a powerful tool for understanding cancer in system level,and flux balance analysis(FBA) is a mathematical approach for analyzing the flow of metabolites through it.The best objective function in FBA describes the task of cell is not agreeable.Organisms need to perform multiple tasks that all contribute to fitness,while a given phenotype cannot be optimal at all tasks,all the possible phenotypes are in the Pareto front.Pareto task inference method(ParTI) can find the Pareto front as a polytope for high-dimensional biological data,and allow identification of the tasks the vertices represent.Here,we use this algorithm inferred four tasks,which is growth,energy production,metastasis and redox balance,of cancer cells through metabolic-related transcriptomics.There still a lot quantitative verification work in future.
引文
[1]Orth,J.D.;Thiele,L;Palsson,B.0.Nat.Biotechnol.2010,28:245-248.
[2]Shoval,O.et al.Science.2012,336:1157-1160.
[3]Hart,Y.et al.Nat.Methods.2015,12:233-235.
[2]Shoval,O.et al.Science.2012,336:1157-1160.
[3]Hart,Y.et al.Nat.Methods.2015,12:233-235.