Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer

被引：851

作者：

Kather, Jakob Nikolas ^{[1
,2
,3
,4
,5
]}

Pearson, Alexander T. ^{[4
]}

Halama, Niels ^{[2
,5
,6
]}

Jaeger, Dirk ^{[2
,3
,5
]}

Krause, Jeremias ^{[1
]}

Loosen, Sven H. ^{[1
]}

Marx, Alexander ^{[7
]}

Boor, Peter ^{[8
,9
]}

Tacke, Frank ^{[10
]}

Neumann, Ulf Peter ^{[11
]}

Grabsch, Heike I. ^{[12
,13
]}

Yoshikawa, Takaki ^{[14
,15
]}

Brenner, Hermann ^{[16
,17
,18
]}

Chang-Claude, Jenny ^{[19
,20
]}

Hoffmeister, Michael ^{[16
]}

Trautwein, Christian ^{[1
]}

Luedde, Tom ^{[1
]}

机构：

[1] Univ Hosp RWTH Aachen, Dept Med 2, Aachen, Germany

[2] German Canc Res Ctr, German Canc Consortium DKTK, Heidelberg, Germany

[3] German Canc Res Ctr, Appl Tumor Immun, Heidelberg, Germany

[4] Univ Chicago, Dept Med, Hematol Oncol, 5841 S Maryland Ave, Chicago, IL 60637 USA

[5] Natl Ctr Tumor Dis NCT, Med Oncol, Heidelberg, Germany

[6] German Canc Res Ctr, Translat Immunotherapy, Heidelberg, Germany

[7] Heidelberg Univ, Univ Med Ctr Mannheim, Inst Pathol, Mannheim, Germany

[8] Univ Hosp RWTH Aachen, Inst Pathol, Aachen, Germany

[9] Univ Hosp RWTH Aachen, Dept Nephrol, Aachen, Germany

[10] Charite, Hepatol & Gastroenterol, Berlin, Germany

[11] Univ Hosp RWTH Aachen, Visceral & Transplant Surg, Aachen, Germany

[12] Univ Leeds, Pathol & Data Analyt, Leeds Inst Med Res St Jamess, Leeds, W Yorkshire, England

[13] Maastricht Univ Med Ctr, Pathol & GROW Sch Oncol & Dev Biol, Maastricht, Netherlands

[14] Kanagawa Canc Ctr, Dept Gastrointestinal Surg, Yokohama, Kanagawa, Japan

[15] Natl Canc Ctr, Dept Gastr Surg, Tokyo, Japan

[16] German Canc Res Ctr, Div Clin Epidemiol & Aging Res, Heidelberg, Germany

[17] German Canc Res Ctr, Div Prevent Oncol, Heidelberg, Germany

[18] Natl Ctr Tumor Dis NCT, Heidelberg, Germany

[19] German Canc Res Ctr, Div Canc Epidemiol, Heidelberg, Germany

[20] Univ Med Ctr Hamburg Eppendorf, Univ Canc Ctr Hamburg, Canc Epidemiol Grp, Hamburg, Germany

来源：

NATURE MEDICINE | 2019年 / 25卷 / 07期

基金：

欧洲研究理事会; 欧盟地平线“2020”;

关键词：

COMPREHENSIVE MOLECULAR CHARACTERIZATION; GASTRIC-CANCER; TUMORS;

D O I：

10.1038/s41591-019-0462-y

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohistochemical tests. Here we show that deep residual learning can predict MSI directly from H&E histology, which is ubiquitously available. This approach has the potential to provide immunotherapy to a much broader subset of patients with gastrointestinal cancer.

引用

页码：1054 / +

页数：8

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