The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types

The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types

Background: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not bee...

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Main Authors: Patrick Micke, Carina Strell, Johanna Mattsson, Alfonso Martín-Bernabé, Hans Brunnström, Jutta Huvila, Malin Sund, Fredrik Wärnberg, Fredrik Ponten, Bengt Glimelius, Ina Hrynchyk, Siarhei Mauchanski, Salome Khelashvili, Gemma Garcia-Vicién, David G. Molleví, Per-Henrik Edqvist, Aine O´Reilly, Sara Corvigno, Hanna Dahlstrand, Johan Botling, Ulrika Segersten, Agnieszka Krzyzanowska, Anders Bjartell, Jacob Elebro, Margareta Heby, Sebastian Lundgren, Charlotta Hedner, David Borg, Jenny Brändstedt, Hanna Sartor, Per-Uno Malmström, Martin Johansson, Björn Nodin, Max Backman, Cecilia Lindskog, Karin Jirström, Artur Mezheyeuski
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:EBioMedicine
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396421000621

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http://www.sciencedirect.com/science/article/pii/S2352396421000621

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