Copy number signatures predict chromothripsis and clinical outcomes in newly diagnosed multiple myeloma.
Copy number signatures predict chromothripsis and clinical outcomes in newly diagnosed multiple myeloma.
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DOI：
10.1038/s41467-021-25469-8
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发表时间：
2021-08-27
影响因子：
16.6
通讯作者：
Maura F
中科院分区：
文献类型：
--
作者：
Maclachlan KH;Rustad EH;Derkach A;Zheng-Lin B;Yellapantula V;Diamond B;Hultcrantz M;Ziccheddu B;Boyle EM;Blaney P;Bolli N;Zhang Y;Dogan A;Lesokhin AM;Morgan GJ;Landgren O;Maura F
Chromothripsis is detectable in 20–30% of newly diagnosed multiple myeloma (NDMM) patients and is emerging as a new independent adverse prognostic factor. In this study we interrogate 752 NDMM patients using whole genome sequencing (WGS) to investigate the relationship of copy number (CN) signatures to chromothripsis and show they are highly associated. CN signatures are highly predictive of the presence of chromothripsis (AUC = 0.90) and can be used identify its adverse prognostic impact. The ability of CN signatures to predict the presence of chromothripsis is confirmed in a validation series of WGS comprised of 235 hematological cancers (AUC = 0.97) and an independent series of 34 NDMM (AUC = 0.87). We show that CN signatures can also be derived from whole exome data (WES) and using 677 cases from the same series of NDMM, we are able to predict both the presence of chromothripsis (AUC = 0.82) and its adverse prognostic impact. CN signatures constitute a flexible tool to identify the presence of chromothripsis and is applicable to WES and WGS data. Chromothripsis is associated with unfavourable outcomes in multiple myeloma (MM), but its detection usually requires whole genome sequencing. Here the authors develop an approach to detect chromothripsis in MM based on copy-number signatures that also works with whole exome sequencing data.
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影响因子：
64.8
作者：
Nik-Zainal S;Davies H;Staaf J;Ramakrishna M;Glodzik D;Zou X;Martincorena I;Alexandrov LB;Martin S;Wedge DC;Van Loo P;Ju YS;Smid M;Brinkman AB;Morganella S;Aure MR;Lingjærde OC;Langerød A;Ringnér M;Ahn SM;Boyault S;Brock JE;Broeks A;Butler A;Desmedt C;Dirix L;Dronov S;Fatima A;Foekens JA;Gerstung M;Hooijer GK;Jang SJ;Jones DR;Kim HY;King TA;Krishnamurthy S;Lee HJ;Lee JY;Li Y;McLaren S;Menzies A;Mustonen V;O'Meara S;Pauporté I;Pivot X;Purdie CA;Raine K;Ramakrishnan K;Rodríguez-González FG;Romieu G;Sieuwerts AM;Simpson PT;Shepherd R;Stebbings L;Stefansson OA;Teague J;Tommasi S;Treilleux I;Van den Eynden GG;Vermeulen P;Vincent-Salomon A;Yates L;Caldas C;van't Veer L;Tutt A;Knappskog S;Tan BK;Jonkers J;Borg Å;Ueno NT;Sotiriou C;Viari A;Futreal PA;Campbell PJ;Span PN;Van Laere S;Lakhani SR;Eyfjord JE;Thompson AM;Birney E;Stunnenberg HG;van de Vijver MJ;Martens JW;Børresen-Dale AL;Richardson AL;Kong G;Thomas G;Stratton MR
通讯作者：
Stratton MR
DOI：
10.1093/bioinformatics/btr670
发表时间：
2012-02-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Boeva V;Popova T;Bleakley K;Chiche P;Cappo J;Schleiermacher G;Janoueix-Lerosey I;Delattre O;Barillot E
通讯作者：
Barillot E
影响因子：
16.6
作者：
Oben B;Froyen G;Maclachlan KH;Leongamornlert D;Abascal F;Zheng-Lin B;Yellapantula V;Derkach A;Geerdens E;Diamond BT;Arijs I;Maes B;Vanhees K;Hultcrantz M;Manasanch EE;Kazandjian D;Lesokhin A;Dogan A;Zhang Y;Mikulasova A;Walker B;Morgan G;Campbell PJ;Landgren O;Rummens JL;Bolli N;Maura F
通讯作者：
Maura F
影响因子：
12.8
作者：
Hoang, Phuc H.;Cornish, Alex J.;Houlston, Richard S.
通讯作者：
Houlston, Richard S.
影响因子：
64.8
作者：
Puente, Xose S.;Bea, Silvia;Campo, Elias
通讯作者：
Campo, Elias