Antigen receptor repertoire profiling from RNA-seq data.
Antigen receptor repertoire profiling from RNA-seq data.
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DOI：
10.1038/nbt.3979
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发表时间：
2017-10-11
影响因子：
46.9
通讯作者：
Chudakov DM
中科院分区：
文献类型：
--
作者：
Bolotin DA;Poslavsky S;Davydov AN;Frenkel FE;Fanchi L;Zolotareva OI;Hemmers S;Putintseva EV;Obraztsova AS;Shugay M;Ataullakhanov RI;Rudensky AY;Schumacher TN;Chudakov DM
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To the Editor: Somatic recombination and accumulation of mutations in VDJ segments result in vast heterogeneity of T-cell receptor (TCR) and immunoglobulin repertoires1, 2. High-throughput profiling of immune receptors has become an important tool for studies of adaptive immunity and for the development of diagnostics, vaccines, and immunotherapies3–7. There are efficient molecular and software tools for the targeted sequencing of TCR and immunoglobulin repertoires6, 8, including MiXCR, developed by our team9. However, sufficient amount and quality of tissue or extracted RNA or DNA are not always available for analysis. An alternative way of immune profiling is to use TCR and immunoglobulin transcripts that are present in bulk RNA-seq data. Because transcriptome sequencing has become routine in both basic and clinical studies, it could serve as a source of functionally relevant information on immune receptor hypervariable region (CDR3) repertoires. The massive repositories of RNA-seq data available from The Cancer Genome Atlas (TCGA, with> 10,000 tumor samples; https://gdcportal. nci. nih. gov/) and other databases could be employed for immune repertoire profiling. Such analysis is of particular interest in cancer immunotherapy studies. Available tumor tissue is often limited, which precludes splitting the samples for separate transcriptome, TCR, and immunoglobulin profiling. Separate immune repertoire profiling also adds complexity and increases the costs for massive clinical studies. Furthermore, transcriptomic analysis is often employed in comparative studies of functional T-and B-cell subsets10–12, and it could additionally yield the immune receptor repertoires at no cost.
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影响因子：
30.5
作者：
Hsieh, CS;Zheng, Y;Rudensky, AY
通讯作者：
Rudensky, AY
影响因子：
64.8
作者：
Shalapour S;Font-Burgada J;Di Caro G;Zhong Z;Sanchez-Lopez E;Dhar D;Willimsky G;Ammirante M;Strasner A;Hansel DE;Jamieson C;Kane CJ;Klatte T;Birner P;Kenner L;Karin M
通讯作者：
Karin M
影响因子：
4.3
作者：
Shugay M;Bagaev DV;Turchaninova MA;Bolotin DA;Britanova OV;Putintseva EV;Pogorelyy MV;Nazarov VI;Zvyagin IV;Kirgizova VI;Kirgizov KI;Skorobogatova EV;Chudakov DM
通讯作者：
Chudakov DM
影响因子：
30.8
作者：
Li, Bo;Li, Taiwen;Liu, X. Shirley
通讯作者：
Liu, X. Shirley
影响因子：
46.9
作者：
Reddy, Sai T.;Ge, Xin;Georgiou, George
通讯作者：
Georgiou, George