CellMinerCDB for Integrative Cross-Database Genomics and Pharmacogenomics Analyses of Cancer Cell Lines

被引：119

作者：

Rajapakse, Vinodh N. ^{[1
]}

Luna, Augustin ^{[2
,3
]}

Yamade, Mihoko ^{[7
]}

Loman, Lisa ^{[1
]}

Varma, Sudhir ^{[1
]}

Sunshine, Margot ^{[1
]}

Oria, Francesco ^{[4
]}

Sousa, Fabricio G. ^{[8
]}

Elloumi, Fathi ^{[9
]}

Aladjem, Mirit I. ^{[1
]}

Thomas, Anish ^{[1
]}

Sander, Chris ^{[2
,3
]}

Kohn, Kurt W. ^{[1
]}

Benes, Cyril H. ^{[5
,6
]}

Garnett, Mathew

Reinhold, William C. ^{[1
]}

Pommier, Yves ^{[1
]}

机构：

[1] Natl Canc Inst, Dev Therapeut Branch, Ctr Canc Res, NIH, Bethesda, MD 20892 USA

[2] Harvard Med Sch, CBio Ctr, Dana Farber Canc Inst, Boston, MA 02215 USA

[3] Harvard Med Sch, Dept Cell Biol, Boston, MA 02215 USA

[4] Wellcome Trust Sanger Inst, Wellcome Trust Genome Campus, Hinxton CB10 1SA, Cambs, England

[5] Harvard Med Sch, Massachusetts Gen Hosp, Canc Ctr, Charlestown, MA 02129 USA

[6] Harvard Med Sch, Dept Med, Charlestown, MA 02129 USA

[7] Hamamatsu Univ, Sch Med, Dept Med 1, Hamamatsu, Shizuoka 4313192, Japan

[8] Univ Fed Mato Grosso do Sul, Programa Posgrad Farm, Ctr Estudos Ceulas Tronco Terapia Celular E Genet, BR-79070900 Campo Grande, MS, Brazil

[9] Gen Dynam Informat Technol Inc, 3211 Jermantown Rd, Fairfax, VA 22030 USA

来源：

ISCIENCE | 2018年 / 10卷

基金：

英国惠康基金; 日本学术振兴会;

关键词：

TOPOISOMERASES; SENSITIVITY; PATTERNS; PROTEIN;

D O I：

10.1016/j.isci.2018.11.029

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

CellMinerCDB provides a web-based resource (https://discover.nci.nih.govicellminercdb/) for integrating multiple forms of pharmacological and genomic analyses, and unifying the richest cancer cell line datasets (the NCI-60, NCI-SCLC, Sanger/MGH GDSC, and Broad CCLE/CTRP). CellMinerCDB enables data queries for genomics and gene regulatory network analyses, and exploration of pharmacogenomic determinants and drug signatures. it leverages overlaps of cell lines and drugs across databases to examine reproducibility and expand pathway analyses. We illustrate the value of CellMinerCDB for elucidating gene expression determinants, such as DNA methylation and copy number variations, and highlight complexities in assessing mutational burden. We demonstrate the value of CellMinerCDB in selecting drugs with reproducible activity, expand on the dominant role of SLFN11 for drug response, and present novel response determinants and genomic signatures for topoisomerase inhibitors and schweinfurthins. We also introduce LIX1L as a gene associated with mesenchymal signature and regulation of cellular migration and invasiveness.

引用

页码：247 / +

页数：36

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