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Published on: May 11, 2016
Left behind but not left alone: Excluded cell populations in the non-small cell lung cancer stroma predict superior
Sebastian Marwitz1, Hans Brunnström2, Miklos Gulyas3
1Histology, Research Center Borstel - Leibniz Lung Center, Borstel, Germany; Airway Research Center North (ARCN), Member of the German Center for Lung Research (DZL), Germany.
Background:
Non-small cell lung cancer (NSCLC) is a heterogenous disease with challenging prognosis despite clinical improvements in the last years. The tumor-microenvironment (TME) is a major factor with many cell types involved as well as distinct spatial organization. We assessed the global immune landscape and spatial architecture of excluded immune cell types within the stroma of NSCLC tissues.
Methods:
Multiplex Immunofluorescence (mIF) staining was used to detect major immune cell lineages in tissues of 674 NSCLC patients. AI-based digital image analyses were conducted to stratify NSCLC tissues into stroma and tumor compartments as well as identify and classify single cells based on mIF marker combinations into major immune cell phenotypes. Quantitative single-cell resolved immune cell phenotypes within the stroma area were used to cluster patients based on their excluded immune signature and spatial architecture and explored for impact on overall-survival.
Results:
NSCLC stroma harbored distinct immune cell as well as spatial organizational patterns with varying combinations. Among these, a mixed immune landscape together with a stromal organization dominated by long distances to B cells and short distances to Helper T cells was associated with long-term overall-survival. This was successfully reduced to a two-variable signature comprising three different cell types, where short distances of Helper T cells to Regulatory T cells in conjunction with high B cell densities provided superior prognostic value.
Conclusions:
The excluded immune cells within the stromal compartment are associated with strong prognostic effects based on their spatial architecture and represent a previously underappreciated cell population.
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