Sparse canonical correlation to identify breast cancer related genes regulated by copy number aberrations.
Sparse canonical correlation to identify breast cancer related genes regulated by copy number aberrations.
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DOI：
10.1371/journal.pone.0276886
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发表时间：
2022
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
癌症中的拷贝数畸变（CNA）通过调节分子表型（如基因表达）影响疾病结局，这些表型驱动重要的生物学过程。为了全面了解癌症的分子生物标志物，识别CNA的关键组、相关基因模块、调节模块及其对结果的下游影响至关重要。在本文中，我们展示了一种创新的使用稀疏典型相关分析（sCCA），有效地识别合奏的CNA，和基因模块的背景下，二进制和删失的疾病终点。我们的方法检测与CNA集高度相关的潜在正交基因表达模块，然后识别与结果相关的这些模块内的基因。通过分析METABRIC研究中1,904名乳腺癌患者的临床和基因组数据，我们发现14个基因模块受到邻近CNA位点组的调控。我们使用来自癌症基因组图谱（TCGA）的1，077个乳腺浸润性癌样本的独立集验证了这一发现。我们对7个临床终点的分析确定了几个新的和可解释的监管协会，突出了CNA在乳腺癌关键生物学途径和过程中的作用。与结果显著相关的基因富集了早期雌激素反应途径，DNA修复途径以及转录因子的靶点，如E2 F4，MYC和ETS 1，这些转录因子在肿瘤特征和生存中具有公认的作用。随后的终点荟萃分析通过聚集较弱的关联进一步确定了几个基因。我们的研究结果表明，sCCA分析可以聚集较弱的关联，以确定可解释的和重要的基因，模块和临床后果的途径。
Copy number aberrations (CNAs) in cancer affect disease outcomes by regulating molecular phenotypes, such as gene expressions, that drive important biological processes. To gain comprehensive insights into molecular biomarkers for cancer, it is critical to identify key groups of CNAs, the associated gene modules, regulatory modules, and their downstream effect on outcomes. In this paper, we demonstrate an innovative use of sparse canonical correlation analysis (sCCA) to effectively identify the ensemble of CNAs, and gene modules in the context of binary and censored disease endpoints. Our approach detects potentially orthogonal gene expression modules which are highly correlated with sets of CNA and then identifies the genes within these modules that are associated with the outcome. Analyzing clinical and genomic data on 1,904 breast cancer patients from the METABRIC study, we found 14 gene modules to be regulated by groups of proximally located CNA sites. We validated this finding using an independent set of 1,077 breast invasive carcinoma samples from The Cancer Genome Atlas (TCGA). Our analysis of 7 clinical endpoints identified several novel and interpretable regulatory associations, highlighting the role of CNAs in key biological pathways and processes for breast cancer. Genes significantly associated with the outcomes were enriched for early estrogen response pathway, DNA repair pathways as well as targets of transcription factors such as E2F4, MYC, and ETS1 that have recognized roles in tumor characteristics and survival. Subsequent meta-analysis across the endpoints further identified several genes through the aggregation of weaker associations. Our findings suggest that sCCA analysis can aggregate weaker associations to identify interpretable and important genes, modules, and clinically consequential pathways.
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影响因子：
64.5
作者：
Boyle EA;Li YI;Pritchard JK
通讯作者：
Pritchard JK
影响因子：
12.3
作者：
Bashashati A;Haffari G;Ding J;Ha G;Lui K;Rosner J;Huntsman DG;Caldas C;Aparicio SA;Shah SP
通讯作者：
Shah SP
影响因子：
4
作者：
Chen, Lin-Feng
通讯作者：
Chen, Lin-Feng
影响因子：
11.1
作者：
Holland, Daniel G.;Burleigh, Angela;Git, Anna;Goldgraben, Mae A.;Perez-Mancera, Pedro A.;Chin, Suet-Feung;Hurtado, Antonio;Bruna, Alejandro;Ali, H. Raza;Greenwood, Wendy;Dunning, Mark J.;Samarajiwa, Shamith;Menon, Suraj;Rueda, Oscar M.;Lynch, Andy G.;McKinney, Steven;Ellis, Ian O.;Eaves, Connie J.;Carroll, Jason S.;Curtis, Christina;Aparicio, Samuel;Caldas, Carlos
通讯作者：
Caldas, Carlos
影响因子：
64.8
作者：
Curtis, Christina;Shah, Sohrab P.;Chin, Suet-Feung;Turashvili, Gulisa;Rueda, Oscar M.;Dunning, Mark J.;Speed, Doug;Lynch, Andy G.;Samarajiwa, Shamith;Yuan, Yinyin;Graef, Stefan;Ha, Gavin;Haffari, Gholamreza;Bashashati, Ali;Russell, Roslin;McKinney, Steven;Langerod, Anita;Green, Andrew;Provenzano, Elena;Wishart, Gordon;Pinder, Sarah;Watson, Peter;Markowetz, Florian;Murphy, Leigh;Ellis, Ian;Purushotham, Arnie;Borresen-Dale, Anne-Lise;Brenton, James D.;Tavare, Simon;Caldas, Carlos;Aparicio, Samuel
通讯作者：
Aparicio, Samuel