Deciphering tumor ecosystems at super resolution from spatial transcriptomics with TESLA.
Deciphering tumor ecosystems at super resolution from spatial transcriptomics with TESLA.
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用TESLA从空间转录组学中以超分辨率破译肿瘤生态系统。
DOI：
10.1016/j.cels.2023.03.008
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发表时间：
2023-05-17
期刊：
影响因子：
9.3
通讯作者：
中科院分区：
文献类型：
--
作者：
Cell populations in the tumor microenvironment (TME), including their abundance, composition, and spatial location, are critical determinants of patient response to therapy. Recent advances in spatial transcriptomics (ST) have enabled the comprehensive characterization of gene expression in the TME. However, popular ST platforms, such as Visium, only measure expression in low-resolution spots and have large tissue areas that are not covered by any spots, which limits their usefulness in studying the detailed structure of TME. Here, we present TESLA, a machine learning framework for tissue annotation with pixel-level resolution in ST. TESLA integrates histological information with gene expression to annotate heterogeneous immune and tumor cells directly on the histology image. TESLA further detects unique TME features such as tertiary lymphoid structures, which represents a promising avenue for understanding the spatial architecture of the TME. Although we mainly illustrated the applications in cancer, TESLA can also be applied to other diseases. We present TESLA, a machine learning framework for tissue annotation with pixel-level resolution, which uses spatial transcriptomics. TESLA is able to enhance gene expression to a higher resolution using histology images, and by integrating morphology and molecular profiles, TESLA provides a comprehensive characterization of the tumor microenvironment in various tumor types.
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影响因子：
64.8
作者：
Helmink BA;Reddy SM;Gao J;Zhang S;Basar R;Thakur R;Yizhak K;Sade-Feldman M;Blando J;Han G;Gopalakrishnan V;Xi Y;Zhao H;Amaria RN;Tawbi HA;Cogdill AP;Liu W;LeBleu VS;Kugeratski FG;Patel S;Davies MA;Hwu P;Lee JE;Gershenwald JE;Lucci A;Arora R;Woodman S;Keung EZ;Gaudreau PO;Reuben A;Spencer CN;Burton EM;Haydu LE;Lazar AJ;Zapassodi R;Hudgens CW;Ledesma DA;Ong S;Bailey M;Warren S;Rao D;Krijgsman O;Rozeman EA;Peeper D;Blank CU;Schumacher TN;Butterfield LH;Zelazowska MA;McBride KM;Kalluri R;Allison J;Petitprez F;Fridman WH;Sautès-Fridman C;Hacohen N;Rezvani K;Sharma P;Tetzlaff MT;Wang L;Wargo JA
通讯作者：
Wargo JA
影响因子：
5.9
作者：
Andersson A;Bergenstråhle J;Asp M;Bergenstråhle L;Jurek A;Fernández Navarro J;Lundeberg J
通讯作者：
Lundeberg J
影响因子：
46.9
作者：
He, Shanshan;Bhatt, Ruchir;Beechem, Joseph M.
通讯作者：
Beechem, Joseph M.
影响因子：
64.8
作者：
Cabrita, Rita;Lauss, Martin;Jonsson, Goran
通讯作者：
Jonsson, Goran
影响因子：
19
作者：
Klemm F;Joyce JA
通讯作者：
Joyce JA