A first-generation pediatric cancer dependency map.
A first-generation pediatric cancer dependency map.
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DOI：
10.1038/s41588-021-00819-w
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发表时间：
2021-04
期刊：
影响因子：
30.8
通讯作者：
Stegmaier K
中科院分区：
文献类型：
--
作者：
Dharia NV;Kugener G;Guenther LM;Malone CF;Durbin AD;Hong AL;Howard TP;Bandopadhayay P;Wechsler CS;Fung I;Warren AC;Dempster JM;Krill-Burger JM;Paolella BR;Moh P;Jha N;Tang A;Montgomery P;Boehm JS;Hahn WC;Roberts CWM;McFarland JM;Tsherniak A;Golub TR;Vazquez F;Stegmaier K
令人兴奋的治疗靶点正在从基于CRISPR的高突变负荷成人癌症筛选中出现。然而，一个关键问题是功能基因组方法是否会在儿科癌症中产生新的靶点，这些癌症以很少的突变而闻名，这些突变通常编码被认为具有挑战性的药物靶点的蛋白质。为了解决这个问题，我们创建了第一代儿科癌症依赖性地图，代表了13种儿科实体瘤和脑瘤类型。对82个儿科癌细胞系进行了基因组规模的CRISPR-Cas9功能丧失筛选，以鉴定细胞存活所需的基因。与儿科癌症具有较少的体细胞突变的发现相反，我们发现与成人模型相比，儿科癌症细胞系中遗传依赖性的复杂性相似。儿科癌症依赖地图的发现为正在进行的精准医学临床试验提供了临床前支持。在儿童癌症中观察到的脆弱性通常与成人不同，这表明重新利用成人肿瘤药物不足以解决儿童癌症。
Exciting therapeutic targets are emerging from CRISPR-based screens of high mutational burden adult cancers. A key question, however, is whether functional genomic approaches will yield new targets in pediatric cancers, known for remarkably few mutations which often encode proteins considered challenging drug targets. To address this, we created a first-generation Pediatric Cancer Dependency Map representing 13 pediatric solid and brain tumor types. Eighty-two pediatric cancer cell lines were subjected to genome-scale CRISPR-Cas9 loss-of-function screening to identify genes required for cell survival. In contrast to the finding that pediatric cancers harbor fewer somatic mutations, we found a similar complexity of genetic dependencies in pediatric cancer cell lines compared to adult models. Findings from the Pediatric Cancer Dependency Map provide pre-clinical support for ongoing precision medicine clinical trials. The vulnerabilities seen in pediatric cancers were often distinct from adult, indicating that repurposing adult oncology drugs will be insufficient to address childhood cancers.
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遗传对人体组织基因表达的影响。
影响因子：
64.8
作者：
GTEx Consortium;Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group;Statistical Methods groups—Analysis Working Group;Enhancing GTEx (eGTEx) groups;NIH Common Fund;NIH/NCI;NIH/NHGRI;NIH/NIMH;NIH/NIDA;Biospecimen Collection Source Site—NDRI;Biospecimen Collection Source Site—RPCI;Biospecimen Core Resource—VARI;Brain Bank Repository—University of Miami Brain Endowment Bank;Leidos Biomedical—Project Management;ELSI Study;Genome Browser Data Integration &Visualization—EBI;Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz;Lead analysts:;Laboratory, Data Analysis &Coordinating Center (LDACC):;NIH program management:;Biospecimen collection:;Pathology:;eQTL manuscript working group:;Battle A;Brown CD;Engelhardt BE;Montgomery SB
通讯作者：
Montgomery SB
影响因子：
46.9
作者：
Doench JG;Fusi N;Sullender M;Hegde M;Vaimberg EW;Donovan KF;Smith I;Tothova Z;Wilen C;Orchard R;Virgin HW;Listgarten J;Root DE
通讯作者：
Root DE
影响因子：
64.8
作者：
Ghandi, Mahmoud;Huang, Franklin W.;Sellers, William R.
通讯作者：
Sellers, William R.
影响因子：
3.2
作者：
Dome, Jeffrey S.;Fernandez, Conrad V.;Mullen, Elizabeth A.;Kalapurakal, John A.;Geller, James I.;Huff, Vicki;Gratias, Eric J.;Dix, David B.;Ehrlich, Peter F.;Khanna, Geetika;Malogolowkin, Marcio H.;Anderson, James R.;Naranjo, Arlene;Perlman, Elizabeth J.
通讯作者：
Perlman, Elizabeth J.
影响因子：
14.9
作者：
Costello M;Pugh TJ;Fennell TJ;Stewart C;Lichtenstein L;Meldrim JC;Fostel JL;Friedrich DC;Perrin D;Dionne D;Kim S;Gabriel SB;Lander ES;Fisher S;Getz G
通讯作者：
Getz G