Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data

被引：134

作者：

Abdelmoula, Walid M. ^{[1
]}

Balluff, Benjamin ^{[2
,3
]}

Englert, Sonja ^{[4
]}

Dijkstra, Jouke ^{[1
]}

Reinders, Marcel J. T. ^{[5
]}

Walch, Axel ^{[4
]}

McDonnell, Liam A. ^{[2
,6
]}

Lelieveldt, Boudewijn P. F. ^{[1
,5
]}

机构：

[1] Leiden Univ, Med Ctr, Div Image Proc, Dept Radiol, NL-2300 RC Leiden, Netherlands

[2] Leiden Univ, Med Ctr, Ctr Prote & Metabol, NL-2300 RC Leiden, Netherlands

[3] Maastricht Univ, Maastricht MultiModal Mol Imaging Inst M4I, NL-6200 MD Maastricht, Netherlands

[4] German Res Ctr Environm Hlth, Res Unit Analyt Pathol, D-85764 Neuherberg, Germany

[5] Delft Univ Technol, Fac Elect Engn Math & Comp Sci, Pattern Recognit & Bioinformat Grp, NL-2600 AA Delft, Netherlands

[6] Fdn Pisana Sci ONLUS, I-56121 Pisa, Italy

来源：

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA | 2016年 / 113卷 / 43期

基金：

欧盟地平线“2020”;

关键词：

intratumor heterogeneity; mass spectrometry imaging; t-SNE; biomarker; cancer; INTRATUMOR HETEROGENEITY; VISUALIZATION; CHALLENGES; EXPRESSION; EVOLUTION; CANCER; BRAIN;

D O I：

10.1073/pnas.1510227113

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

The identification of tumor subpopulations that adversely affect patient outcomes is essential for a more targeted investigation into how tumors develop detrimental phenotypes, as well as for personalized therapy. Mass spectrometry imaging has demonstrated the ability to uncover molecular intratumor heterogeneity. The challenge has been to conduct an objective analysis of the resulting data to identify those tumor subpopulations that affect patient outcome. Here we introduce spatially mapped t-distributed stochastic neighbor embedding (t-SNE), a nonlinear visualization of the data that is able to better resolve the biomolecular intratumor heterogeneity. In an unbiased manner, t-SNE can uncover tumor subpopulations that are statistically linked to patient survival in gastric cancer and metastasis status in primary tumors of breast cancer.

引用

页码：12244 / 12249

页数：6

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