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. 2016 Sep 23:6:33322.
doi: 10.1038/srep33322.

In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium

J C L Alfonso  1   2 , N S Schaadt  3 , R Schönmeyer  4 , N Brieu  4 , G Forestier  5   6 , C Wemmert  5 , F Feuerhake  3   7 , H Hatzikirou  1   2
Affiliations

In-silico insights on the prognostic potential of immune cell infiltration patterns in the breast lobular epithelium

J C L Alfonso et al. Sci Rep. .

Abstract

Scattered inflammatory cells are commonly observed in mammary gland tissue, most likely in response to normal cell turnover by proliferation and apoptosis, or as part of immunosurveillance. In contrast, lymphocytic lobulitis (LLO) is a recurrent inflammation pattern, characterized by lymphoid cells infiltrating lobular structures, that has been associated with increased familial breast cancer risk and immune responses to clinically manifest cancer. The mechanisms and pathogenic implications related to the inflammatory microenvironment in breast tissue are still poorly understood. Currently, the definition of inflammation is mainly descriptive, not allowing a clear distinction of LLO from physiological immunological responses and its role in oncogenesis remains unclear. To gain insights into the prognostic potential of inflammation, we developed an agent-based model of immune and epithelial cell interactions in breast lobular epithelium. Physiological parameters were calibrated from breast tissue samples of women who underwent reduction mammoplasty due to orthopedic or cosmetic reasons. The model allowed to investigate the impact of menstrual cycle length and hormone status on inflammatory responses to cell turnover in the breast tissue. Our findings suggested that the immunological context, defined by the immune cell density, functional orientation and spatial distribution, contains prognostic information previously not captured by conventional diagnostic approaches.

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Conflict of interest statement

R. Schönmeyer and N. Brieu are employees of Definiens AG. The rest of authors declare no competing financial interests.

Figures

Figure 1
Figure 1. The range of infiltration patterns within breast tissue from one healthy woman.
From top to bottom, immunohistochemical stainings for CD8, CD163 and CD4. From left to right, a representative spectrum of immune cell infiltration in different lobular structures for almost consecutive tissue sections by columns. The breast tissue samples were obtained from reduction mammoplasty in a 25-year-old premenopausal woman without clinical abnormality nor familial history of breast cancer, who underwent the surgical procedure during the luteal phase of her regular menstrual cycle, reported to be 30 days long.
Figure 2
Figure 2. The range of infiltration patterns across breast tissue samples from several healthy women.
From top to bottom, immunohistochemical stainings for CD8, CD163 and CD4. From left to right, a representative spectrum of immune cell infiltration in different lobular structures for almost consecutive tissue sections by columns. The breast tissue samples show representative variations as observed in premenopausal women without clinical abnormality nor familial history of breast cancer, with ages ranging from 20 to 33 years (median age 24.5 years), who underwent the surgical procedures during the luteal phase of their regular menstrual cycles, reported to be from 25 to 37 days long (median 28 days).
Figure 3
Figure 3. Experimental data, agent-based model simulation domain and epithelial cell turnover during the menstrual cycle.
(a–c) Quantification of epithelial and immune cells in breast lobular tissue. From left to right, amount of epithelial cells and relative number of (a) CD8+, (b) CD163+ and (c) CD4+ cells with respect to the menstrual cycle phase in healthy women. Each box is drawn around the region between the first and third quartiles of the data points, with a horizontal line at the median value and whiskers extend for a range equal to 1.5 times the interquartile range. (d,e) Cross-sections of terminal ductal lobular units (TDLUs). (d) Annotated TDLUs composed by several terminal ductules/acini and (e) the corresponding simplified simulation domain, where luminal (light blue) and myoepithelial (dark blue) cells are represented, respectively. (f) Normalized curves of the epithelial cell proliferation (PI) and apoptosis (AI) indices with respect to the menstrual cycle. The follicular phase ranges from day 0 to 14, while the luteal phase between days 14 and 28.
Figure 4
Figure 4. Agent-based model formulation details.
(a) Schematic representation of the cell processes mimicked in the agent-based model. (b) Flowchart describing the checkpoints and possible actions that cells can perform in each simulation time-step.
Figure 5
Figure 5. Time evolution of epithelial and immune cells in healthy breast tissue.
The results are averaged over 20 simulations each consisting in 12 menstrual cycles of 28 days and normal hormone levels. (a) Amount of epithelial cells. (b) Relative number of regulatory and effector cells. (c,d) Number of proliferating and apoptotic epithelial cells per 1000 epithelial cells, respectively. Simulation results for a single menstrual cycle are represented in the right panels.
Figure 6
Figure 6. Inflammatory responses induced by increasing damage rates of epithelial cells.
The results are averaged over 10 simulations, for every parameter constellation, each consisting in 12 menstrual cycles of 28 days and normal hormone levels. The mean (marked solid line) and min/max (shadow) values are represented. (a,b) Relative number of damaged epithelial cells for kkill = 0.05 and kkill = 0.10, respectively. (c,d) Relative number of immune cells for kkill = 0.05 and kkill = 0.10, respectively. (e) Difference between the relative number of regulatory and effector cells for different kkill values. (f) Relative number of immune cells during a single menstrual cycle for kkill = 0.05 and different kdge values.
Figure 7
Figure 7. Influence of hormone levels on epithelial damage and inflammatory responses.
The results are averaged over 10 simulations, for every parameter constellation, each consisting in 12 menstrual cycles of 28 days. The mean (marked solid line) and min/max (shadow) values are represented. (a) Normalized curves of epithelial cell proliferation and apoptosis during the menstrual cycle for normal (θ = 1.0), increased (θ = 2.0) and decreased (θ = 0.5) hormone levels. (b) Relative number of immune cells for increasing hormone levels and different kdge values with kkill = 0.10. (c) Difference between the maximum and minimum relative number of regulatory and effector cells, as well as the total amount of immune cells, for kdge = 0.15 and kkill = 0.10. (d,e) Relative number of damaged epithelial and immune cells for increasing kdge values and different hormone levels with kkill = 0.10, respectively.
Figure 8
Figure 8. Influence of hormone levels and epithelial damage on the spatial distribution of immune cells.
The results are averaged over 10 simulations for every parameter constellation. The mean (marked solid line) and min/max (shadow) fitted values are represented. (a–d) Estimates of parameters m and b of the power law b · r−m that better fit the radial distribution functions g(r) at the follicular (day 5) and luteal (day 25) phase of the menstrual cycle, as well as in the middle (day 14). (e,f) Radial distribution functions g(r) at day 25 of the menstrual cycle for different parameter sets and the resulting power law fittings.
Figure 9
Figure 9. Immunological context in cross-sections of a terminal ductal lobular unit (TDLU).
Relative number and spatial distribution of immune cells for (a) increasing hormone levels θ without epithelial damage kdge = 0.0 and (b) increasing kdge values and normal hormone levels θ = 1.0, with kkill = 0.05.
Figure 10
Figure 10. Spatial distribution of immune cells for increasing epithelial damage rates and time evolution of immune cells in cross-sections of terminal ductal lobular units (TDLUs).
(a,b) The results are averaged over 10 simulations, for every parameter constellation, each consisting in 12 menstrual cycles of 28 days and normal hormone levels. The mean (marked solid line) and min/max (shadow) values are represented. Mean relative number of immune cells with respect to their position in the lobular epithelium for (a) kkill = 0.05 and (b) kkill = 0.02. (c,d) Simulations of 6 menstrual cycles each of 28 days and normal hormone levels. Relative number of immune cells in different TDLUs for (c) kdge = 0.0 and (d) kdge = 0.2, with kkill = 0.02.
Figure 11
Figure 11. Influence of menstrual cycle length on epithelial damage and inflammatory responses.
The results are averaged over 10 simulations, for every parameter constellation, each consisting in 12 menstrual cycles and normal hormone levels. (a) Normalized curves of epithelial cell proliferation and apoptosis for menstrual cycles with the follicular phase of 7, 14 and 21 days, with the luteal phase 14 days long. (b,c) Mean relative number of damaged epithelial and immune cells in the short and long menstrual cycle for increasing kdge values. (d,e) Difference between the maximum and minimum relative number of regulatory and effector cells, as well as the total amount of immune cells, in the short and long menstrual cycle for increasing kdge values.
Figure 12
Figure 12. Model-driven diagnostic criteria.
(a) Immunological evaluation in breast lobular tissue with respect to immune cell density, functional orientation and spatial distribution. (b) Quantification of immune cells in breast lobular tissue from women who underwent reduction mammoplasty (RM) due to orthopedic or cosmetic reasons, and prophylactic mastectomy (PM) due to BRCA1/2 mutations. Amount of immune cells in normal lobular tissue adjacent (more than 1 mm) to breast cancer/neoplastic tissue (NT) is also quantified. From top to bottom, the relative number of CD8+, CD163+ and CD4+ cells with respect to epithelial cells. Each box is drawn around the region between the first and third quartiles of the data points, with a horizontal line at the median value and whiskers extend for a range equal to 1.5 times the interquartile range.
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