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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Summary: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 been systematically analysed. Methods: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns. Findings: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR(95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59(1.49-8.62)) associations of the tumour stroma fraction with survival. Interpretation: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance. Funding: The Swedish Cancer Society, The Lions Cancer Foundation Uppsala, The Swedish Government Grant for Clinical Research, The Mrs Berta Kamprad Foundation, Sweden, Sellanders foundation, P.O.Zetterling Foundation, and The Sjöberg Foundation, Sweden.
ISSN:2352-3964