A Novel Bayesian Framework Infers Driver Activation States and Reveals Pathway-Oriented Molecular Subtypes in Head and Neck Cancer.
A Novel Bayesian Framework Infers Driver Activation States and Reveals Pathway-Oriented Molecular Subtypes in Head and Neck Cancer.
复制标题
DOI：
10.3390/cancers14194825
复制
发表时间：
2022-10-03
期刊：
影响因子：
5.2
通讯作者：
Lu, Xinghua
中科院分区：
文献类型：
--
作者：
Liu, Zhengping;Cai, Chunhui;Ma, Xiaojun;Liu, Jinling;Chen, Lujia;Lui, Vivian Wai Yan;Cooper, Gregory F.;Lu, Xinghua
许多因素，例如基因组突变、染色体变化、转录控制、磷酸化和蛋白质-蛋白质相互作用等，可以影响蛋白质的活化状态。虽然每种数据类型只能部分揭示特定基因中断的状态，但下游表达变化最终表明癌症驱动蛋白改变的功能影响。通过结合转录组和基因组改变的数据，我们开发了一个贝叶斯框架来推断驱动程序激活状态，并通过将我们的模型应用于TCGA HNSCC患者数据来进一步测试我们的方法以突出统计学和生物学意义。头颈部鳞状细胞癌（HNSCC）是一种由异质性原因引起的侵袭性癌症。为了揭示不同HNSCC肿瘤的潜在驱动因子和信号机制，我们开发了一种新的贝叶斯框架来识别个体肿瘤的驱动因子并推断HNSCC肿瘤细胞信号系统中驱动蛋白的状态。首先，我们使用肿瘤特异性因果推断（TCI）模型系统地确定每个TCGA HNSCC肿瘤的体细胞基因组改变（SGA）和差异表达基因（DEG）之间的因果关系。然后，我们概括了TCGA HNSCC队列中最具统计学意义的驱动SGAs及其调节的DEG。最后，我们开发了机器学习模型，该模型结合联合收割机基因组和转录组数据来推断肿瘤中驱动SGAs的蛋白质功能激活状态，这使我们能够在细胞信号传导系统的空间中代表肿瘤。我们发现了HNSCC的四种机制导向亚型，它们显示了HNSCC驱动蛋白激活状态的独特模式，重要的是，这种亚型与先前报道的基于转录组学的HNSCC分子亚型正交。此外，我们的分析揭示了可能参与HPV感染诱导的致癌过程的驱动蛋白，即使它们不受HPV+肿瘤中基因组改变的干扰。
Numerous factors, such as genomic mutations, chromosomal changes, transcriptional controls, phosphorylation, and protein–protein interactions, among others, can affect the activation status of proteins. Although each data type only partially reveals the status of a particular gene’s disruption, downstream expression changes ultimately indicate the functional effects of cancer driver protein alterations. By combining data on transcriptome and genomic alterations, we have developed a Bayesian framework to infer driver activation state, and further tested our method to highlight both statistical and biological significance by applying our model to TCGA HNSCC patient data. Head and neck squamous cell cancer (HNSCC) is an aggressive cancer resulting from heterogeneous causes. To reveal the underlying drivers and signaling mechanisms of different HNSCC tumors, we developed a novel Bayesian framework to identify drivers of individual tumors and infer the states of driver proteins in cellular signaling system in HNSCC tumors. First, we systematically identify causal relationships between somatic genome alterations (SGAs) and differentially expressed genes (DEGs) for each TCGA HNSCC tumor using the tumor-specific causal inference (TCI) model. Then, we generalize the most statistically significant driver SGAs and their regulated DEGs in TCGA HNSCC cohort. Finally, we develop machine learning models that combine genomic and transcriptomic data to infer the protein functional activation states of driver SGAs in tumors, which enable us to represent a tumor in the space of cellular signaling systems. We discovered four mechanism-oriented subtypes of HNSCC, which show distinguished patterns of activation state of HNSCC driver proteins, and importantly, this subtyping is orthogonal to previously reported transcriptomic-based molecular subtyping of HNSCC. Further, our analysis revealed driver proteins that are likely involved in oncogenic processes induced by HPV infection, even though they are not perturbed by genomic alterations in HPV+ tumors.
登录
查看更多内容
影响因子：
3.7
作者：
Walter V;Yin X;Wilkerson MD;Cabanski CR;Zhao N;Du Y;Ang MK;Hayward MC;Salazar AH;Hoadley KA;Fritchie K;Sailey CJ;Weissler MC;Shockley WW;Zanation AM;Hackman T;Thorne LB;Funkhouser WD;Muldrew KL;Olshan AF;Randell SH;Wright FA;Shores CG;Hayes DN
通讯作者：
Hayes DN
影响因子：
9
作者：
Deville SS;Luft S;Kaufmann M;Cordes N
通讯作者：
Cordes N
影响因子：
6.7
作者：
Basukala, Om;Mittal, Suruchi;Banks, Lawrence
通讯作者：
Banks, Lawrence
影响因子：
3
作者：
Liu, Jinling;Ma, Xiaojun;Lu, Xinghua
通讯作者：
Lu, Xinghua
影响因子：
7.7
作者：
Grossmann P;Stringfield O;El-Hachem N;Bui MM;Rios Velazquez E;Parmar C;Leijenaar RT;Haibe-Kains B;Lambin P;Gillies RJ;Aerts HJ
通讯作者：
Aerts HJ