title: Data-driven identification of prognostic tumor subpopulations using spatially mapped t-SNE of mass spectrometry imaging data.
abstract: 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.
authors: Division of Image Processing, Department of Radiology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.
authors: Walid M
authors: WM
authors: Abdelmoula
authors: Center for Proteomics and Metabolomics, Leiden University Medical Center, 2300 RC Leiden, The Netherlands; The Maastricht MultiModal Molecular Imaging Institute (M4I), Maastricht University, 6200 MD Maastricht, The Netherlands.
authors: Benjamin
authors: B
authors: Balluff
authors: Research Unit Analytical Pathology, German Research Center for Environmental Health, D-85764 Neuherberg, Germany.
authors: Sonja
authors: S
authors: Englert
authors: Division of Image Processing, Department of Radiology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands.
authors: Jouke
authors: J
authors: Dijkstra
authors: Pattern Recognition and Bioinformatics Group, Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, 2600 AA Delft, The Netherlands.
authors: Marcel J T
authors: 0000-0002-1148-1562
authors: MJ
authors: Reinders
authors: Research Unit Analytical Pathology, German Research Center for Environmental Health, D-85764 Neuherberg, Germany.
authors: Axel
authors: A
authors: Walch
authors: Center for Proteomics and Metabolomics, Leiden University Medical Center, 2300 RC Leiden, The Netherlands; Fondazione Pisana per la Scienza ONLUS, 56121 Pisa, Italy l.a.mcdonnell@outlook.com.
authors: Liam A
authors: LA
authors: McDonnell
authors: Division of Image Processing, Department of Radiology, Leiden University Medical Center, 2300 RC Leiden, The Netherlands; Pattern Recognition and Bioinformatics Group, Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, 2600 AA Delft, The Netherlands.
authors: Boudewijn P F
authors: BP
authors: Lelieveldt
mesh_terms: D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics; D001943:Breast Neoplasms / Q000235:genetics / Q000473:pathology*; D019070:Cell Lineage / Q000235:genetics; D005260:Female; D015972:Gene Expression Regulation, Neoplastic; D014644:Genetic Variation; D006801:Humans; D008297:Male; D013058:Mass Spectrometry; D008875:Middle Aged; D057285:Precision Medicine; D011379:Prognosis; D013274:Stomach Neoplasms / Q000235:genetics / Q000473:pathology*; D016019:Survival Analysis
chemical_list: D014408:Biomarkers, Tumor
keywords: biomarker; cancer; intratumor heterogeneity; mass spectrometry imaging; t-SNE