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  • Poster presentation
  • Open Access

Immune-cancer interactions in tumors and tumor-draining lymph nodes: Novel prognostic indicators for breast cancer

  • 1 and
  • 2
Journal for ImmunoTherapy of Cancer20142 (Suppl 3) :P255

  • Published:

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  • Breast Cancer
  • Immune Cell
  • Tumor Microenvironment
  • Tumor Metastasis
  • Visual Assessment

It is becoming clear that immune cells play many important but sometimes conflicting roles in cancer. Immune profile changes at sites of immune-cancer interactions, such as the tumor microenvironment and tumor-draining lymph nodes (TDLNs), may represent a sensitive predictor of local and distant tumor metastasis. However, standard pathologic analysis of tumor sections has remained at the visual assessment of one marker per serial section level; it would be extremely useful to be able to visualize the distributions of multiple phenotyped immune and other cells in-situ in solid tumors to dissect the complex interplay between immune/stromal cells and cancer cells within tumors, tumor-draining lymph nodes (TDLNs), and blood. We generate immune profiles that include complete immunophenotyping and identification of cellular spatial relationships within and between the tumor microenvironment and TDLNs from formalin-fixed paraffin-embedded lymph node and tumor specimens from cancer patients using a combination of multiplexed IHC/IF, multispectral imaging, and automated image analysis which delivers quantitative per-cell measures of each marker. These per-cell intensities are then translated into a phenotype for each cell. We have found that immune cell populations as well as their spatial distributions and clustering patterns have strong correlation with clinical outcome.

Authors’ Affiliations

PerkinElmer, Hopkinton, MA, USA
City of Hope Comprehensive Cancer Center, CA, USA


© Mansfield et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.