A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types
Tekijät: Micke Patrick, Strell Carina, Mattsson Johanna, Martin-Bernabé Alfonso, Brunnström Hans, Huvila Jutta, Sund Malin, Wärnberg Fredrik, Ponten Fredrik, Glimelius Bengt, Hrynchyk Ina, Mauchanski Siarhei, Khelashvili Salome, Garcia-Vicién Gemma, Mollevi David G, Edqvist Per-Henrik, Reilly Aine O, Corvigno Sara, Dahlstrand Hanna, Botling Johan, Segersten Ulrika, Krzyzanowska Agnieszka, Bjartell Anders, Elebro Jacob, Heby Margareta, Lundgren Sebastian, Hedner Charlotta, Borg David, Brändstedt Jenny, Sartor Hanna, Malmström Per-Uno, Johansson Martin, Nodin Björn, Backman Max, Lindskog Cecilia, Jirström Karin, Mezheyeuski Artur
Kustantaja: ELSEVIER
Julkaisuvuosi: 2021
Journal: EBioMedicine
Tietokannassa oleva lehden nimi: EBIOMEDICINE
Lehden akronyymi: EBIOMEDICINE
Artikkelin numero: ARTN 103269
Vuosikerta: 65
Sivujen määrä: 6
ISSN: 2352-3964
eISSN: 2352-3964
DOI: https://doi.org/10.1016/j.ebiom.2021.103269
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/53658201
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.
Ladattava julkaisu This is an electronic reprint of the original article. |