Analyzing the Immunological Landscape of a Tumor—Heterogeneity of Immune Infiltrates in Breast Cancer as a New Prognostic Indicator
JNCI J Natl Cancer Inst (
Analyzing the Immunological Landscape of a Tumor-Heterogeneity of Immune Infiltrates in Breast Cancer as a New Prognostic Indicator
Carsten Denkert 0 1 2
Stephan Wienert 0 1 2
Frederick Klauschen 0 1 2
0 The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions , please
1 Berlin , Germany (
2 Affiliations of authors: Institute of Pathology, Charite ́-Universita€tsmedizin Berlin, corporate member of Freie Universita€t Berlin, Humboldt-Universita€t zu Berlin, and Berlin Institute of Health , (CD, SW, FK) Berlin, Germany; German Cancer Consortium (DKTK), Partner Site Charite ́, Berlin, Germany, CD, FK
If we want to understand the characteristics of a country or a
city, we pay attention to the composition of the landscape and
the environment. In geography, it is quite obvious that the
spatial organization of houses, forests, streets, and meadows is
central for the characterization of the environmental conditions
and the development of a city or a country.
It is becoming increasingly evident that we need to use a
similar spatial approach to evaluate tumor heterogeneity. To
understand tissue function, the spatial relationship of different
cell types is important. Spatial relationships offer options for
interactions of neighboring cells and also provide constraints
that limit the interaction of cell types that are separated within
a tumor. In tumor biology, we therefore need to do more than
just measure the expression of a marker, the rate of a mutation,
or the numbers of immune cells.
The paper by Heindl et al. (
) published in this issue of the
Journal gives an elegant example of how the quantitative
analysis of spatial relationships between tumor and immune cells
can provide insights into new parameters of tumor progression.
In a large cohort of 1178 hormone receptor–positive breast
cancers from the ATAC study, different cell types were
automatically identified in scanned hematoxylin and eosin (H&E)
images. With a spatial data clustering method originally
developed for the analysis of geographic data by Getis and Ord (
the authors defined so-called cancer or immune hotspots, in
which the density of cancer cells or lymphocytes is statistically
significantly higher than the average density in the tumor. Both
parameters can be combined, resulting in so-called immune
cancer hotspots, indicating close interactions between immune
cells and cancer cells. As a main result, the authors found that
the total abundance of immune cells—without their spatial
relationship—was not relevant for prognosis. In contrast, when
they included spatial organization patterns, the presence of
immune cell hotspots was associated with reduced survival in the
ATAC cohort of hormone receptor–positive tumors.
This finding is particularly interesting because the role of
immune infiltrates in hormone receptor–positive breast cancer
is not completely clear as most studies have so far focused on
the triple-negative and human epidermal growth factor
receptor 2 (HER2)–positive tumor subtype. In triple-negative and
HER2-positive tumors, an increased number of
tumorinfiltrating lymphocytes is related to increased chemotherapy
response and improved survival (
). Interestingly, Yuan
and colleagues have already tested their spatial clustering
approach in a cohort of triple-negative tumors in a previous
). They were able to show that increased immune cell
clusters (and increased overall TIL rates) are a positive
prognostic factor in triple-negative breast cancer, validating the results
of previous studies on the positive role of immune markers in
these tumor types. This suggests that the negative prognostic
effect in luminal breast cancer is not due to the different
method used, but that this might be a biological difference
between luminal and triple-negative tumors.
In luminal tumors, disease recurrence and survival are
driven by the existence of disseminated tumor cells and
micrometastases that remain clinically undetected for a long time. It
is intriguing to speculate that immune evasion strategies are
relevant for the survival of these dormant tumor cells. The
interaction of immune cells with different subclones within a
tumor might determine the memory function of the immune
system that controls elimination of disseminated tumor cell
clones. The heterogeneity of tumor-immune interactions could
then be an indicator of the emergence of tumor subclones with
successful immune escape mechanisms. This model would
partly explain the findings reported by Heindl et al. (
additional studies are required to support and validate this
hypothesis. The spatial heterogeneity of the tumor–immune cell
landscape might be more relevant in slow-growing tumors—
such as luminal breast cancer—where the low growth rate could
increase the molecular differences between different areas of
the tumor. In contrast, in a rapidly growing tumor, the
molecular diversity could be increased even in cells that are spatially
close to each other. In both scenarios, the tumor would be
heterogeneous on a molecular level, but only in the slow-growing
tumor would the heterogeneity be linked to spatial organization
There are still relevant challenges and open questions for
further translation of this finding into new diagnostic and
therapeutic concepts. The use of H&E-stained slides does not permit
the identification of different immune cell subtypes. On the
other hand, recent molecular studies have used gene expression
algorithms that separate different types of immune cells in
transcriptomic data sets without a spatial resolution (
For the future, it would be interesting to combine both
approaches and use molecular quantitative in situ methods
that allow marker quantification and assessment of spatial
differences in parallel.
The current diagnostic guidelines of the International TIL
working group (
) are made for visual evaluation by
pathologists, and their robustness has been shown in international ring
). The agreement between the standardized TIL
evaluation and the image analysis–based segmentation in the ATAC
cohort is currently very limited. For further improvement of
diagnostic concepts, it would therefore be interesting to generate
standardized diagnostic guidelines for spatial evaluation of
immune cells in tumors. Relevant challenges include the
variability of different H&E stainings, the robustness of the tissue
segmentation algorithms, and the development and validation
of cut-points for heterogeneity parameters across different
cohorts. Furthermore, improved software packages would have
to be designed to serve as clinically useful standardized digital
diagnostics systems that could be used decentrally by
pathologists in a routine diagnostic setting.
The relevance of immunological parameters for
chemotherapy response (
), in particular in triple-negative breast cancer,
has been the basis for the first phase I and phase II trials
investigating immune checkpoint inhibitors (
). At the annual
American Society of Clinical Oncology meeting in 2017, a first
neoadjuvant trial (17) of a combination of immune checkpoint
inhibitors and chemotherapy reported increased pathological
complete response rates in triple-negative tumors, but also in
luminal breast cancer. For a better description of the
immunobiology of these tumors, a combination of quantitative
molecular markers with spatial morphological parameters would be of
German Cancer Aid, TransLuminal-B project.
The funder had no role in the writing of the editorial or the
decision to submit the editorial for publication. The authors have no
conflicts of interest to disclose.
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