Infiltration of CD8+ T cells into tumor cell clusters in triple-negative breast cancer

Abstract

Infiltration of [Formula: see text] T lymphocytes into solid tumors is associated with good prognosis in various types of cancer, including triple-negative breast cancer (TNBC). However, the mechanisms underlying different infiltration levels are largely unknown. Here, we have characterized the spatial profile of [Formula: see text] T cells around tumor cell clusters (tightly connected tumor cells) in the core and margin regions in TNBC patient samples. We found that in some patients, the [Formula: see text] T cell density first decreases when moving in from the boundary of the tumor cell clusters and then rises again when approaching the center. To explain various infiltration profiles, we modeled the dynamics of T cell density via partial differential equations. We spatially modulated the diffusion/chemotactic coefficients of T cells (to mimic physical barriers) or introduced the localized secretion of a diffusing T cell chemorepellent. Combining the spatial-profile analysis and the modeling led to support for the second idea; i.e., there exists a possible chemorepellent inside tumor cell clusters, which prevents [Formula: see text] T cells from infiltrating into tumor cell clusters. This conclusion was consistent with an investigation into the properties of collagen fibers which suggested that variations in desmoplastic elements does not limit infiltration of [Formula: see text] T lymphocytes, as we did not observe significant correlations between the level of T cell infiltration and fiber properties. Our work provides evidence that [Formula: see text] T cells can cross typical fibrotic barriers and thus their infiltration into tumor clusters is governed by other mechanisms possibly involving a local repellent.

Keywords: ECM; TIL; TNBC; chemokine; tumor-cell clusters.

Fig. 1.

(A) Illustration of different regions defined in the image analysis. (B) Illustration of the selected regions of tumor margin and tumor core. For the tumor margin, parts of the margins were excluded whenever the juxtatumoral tissue did not exist. For the tumor core, whenever possible three regions ($1.95\hspace{0.17em}\mathrm{m}\mathrm{m}\times 1.95$ mm) were selected for each tumor. (C) Illustration of the ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$–T cell profile calculation for two levels: margin-boundary level and tumor cell cluster level (Materials and Methods). (D) Based on the spatial profile of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cells at the tumor margin and the tumor core, 28 patients were grouped into two groups (margin-boundary level) and three groups (tumor cell cluster level), respectively.

Fig. 2.

(A) The density ratio of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ pixels for all 28 patients analyzed (margin-boundary–level analysis). Two patients, indicated by green arrows, are selected to illustrate the corresponding ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$-pixel profiles. (B and C) Examples of the density of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ pixels (blue lines) for one margin-restricted tumor and one infiltrated tumor, respectively. The average densities in region II (Fig. 1A, between $-750\hspace{0.17em}\mathrm{\mu }$m and $-250\hspace{0.17em}\mathrm{\mu }$m, red double-arrowed lines) are as indicated. The maximal densities (red circles) in the margin area (region I) (between $-250\hspace{0.17em}\mathrm{\mu }$m and $250\hspace{0.17em}\mathrm{\mu }$m) are as indicated.

Fig. 3.

(A) The density ratio of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ pixels ${\mathcal{R}}_{tc}$ for all 28 patients. Three patients, indicated by green arrows, are selected to illustrate the corresponding ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$-pixel profiles on the tumor cell cluster level. (B) Representative image with limited ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell infiltration inside of tumor cell clusters (Top) and the corresponding ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell distribution quantification (Bottom). (C) Representative image with intermediate ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell infiltration inside of tumor cell clusters (Top) and the corresponding ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell distribution quantification (Bottom). (D) Representative image with full ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell infiltration inside of tumor cell clusters (Top) and the corresponding ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell distribution quantification (Bottom). In the representative images, tumor epithelial cells are in blue (pan-cytokeratin) and ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cells in yellow (CD8). (Scale bar, 500 $\mathrm{\mu }$m.)

Fig. 4.

Time evolution of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell profiles predicted by various scenarios of models based on the physical-barrier hypothesis. For all graphs, the right y axis represents the diffusion ($D_T$) and/or chemotaxis coefficient (${\lambda }_A$) of T cells as indicated in the key. The left y axis represents the attractant concentration and the ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell distribution at different time points (in model units) as indicated in the key. The distribution of attractant is the same for all models. (A) Abrogated T cell motility scenario where dense fibers prevent T cell infiltration. (B) Reduced T cell motility scenario within regions of dense fibers and tumor cell clusters. Note that ${\lambda }_A\left(r\right)$ is scaled by a factor of 1/30 in A and B. (C) Reduced followed by regained T cell motility scenario where diffusion of T cells ($D_T$) gradually decreases in the region with dense fibers but goes back to a normal level once T cells reach the region with tumor cells (dashed green line). ${\lambda }_A\left(r\right)$ is scaled by a factor of 1/50 in the plot and is assumed to be zero once T cells move into tumor cell clusters (dashed-dotted green line). (D) Reduced followed by regained T cell motility and chemotaxis scenario. Scenario is similar to that in C with the exception that T cells retain their chemotaxis ability inside of tumor cell clusters. ${\lambda }_A\left(r\right)$ is scaled by a factor of 1/50 in the plot (dashed-dotted green line).

Fig. 5.

${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cell profiles predicted by various scenarios of models based on the repellent-barrier hypothesis. For both graphs, the y axis represents the long-term distribution of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cells and attractant and repellent (scaled) concentration as indicated in the key. (A) The chemotactic ability of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cells in following the gradient of the attractant is assumed to be zero once T cells are inside of the tumor cell cluster ($r\le 2$). The region of the source of the repellent is assumed to be between $r=0$ and $r=2$. Depending on how strongly the ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cells react to the repellent, the infiltration level can be limited (${\lambda }_R=20$, ${\lambda }_A=30$), intermediate (${\lambda }_R=2$, ${\lambda }_A=30$), or full (${\lambda }_R=0$, ${\lambda }_A=10$). (B) The chemotaxis ability of ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cells following the gradient of the attractant is assumed to be spatially uniform. The region of the source of the repellent is assumed to be between $r=1$ and $r=2$. Depending on how strongly the ${\mathrm{C}\mathrm{D}\mathrm{8}}^{+}$ T cells react to the gradient of the repellent, the infiltration level can be limited (${\lambda }_R=40$, ${\lambda }_A=60$), intermediate (${\lambda }_R=10$, ${\lambda }_A=30$), or full (${\lambda }_R=0$, ${\lambda }_A=10$). The diffusion coefficient of repellent ($D_R=60$) is assumed to six times larger than that in A ($D_R=10$). Note that in A and B, the spatial profile of chemorepellent is scaled by a factor of 0.1 and 0.2, respectively.

Fig. 6.

Desmoplastic elements are not limiting lymphocytic infiltration in TNBC. (A) Representative images of Picrosirius Red staining at the tumor margins. Bright-field images (Upper) and matched polarized-light images (Lower) are presented. (B) Quantification of Picrosirius Red polarized-light signal in tumor margin areas. (C) SHG images (Upper) and representation of fiber individualization (Lower) using the CT Fire software (tumor margins). (D) Quantification of tumor margin fiber parameters as described. (E) Representative images of Picrosirius Red staining at the tumor core. Bright-field images (Upper) and matched polarized-light images (Lower) are presented. (F) Quantification of Picrosirius Red polarized-light signal in tumor core areas. (G) SHG images (Upper) and representation of fiber individualization (Lower) using the CT Fire software (tumor margins). (H) Quantification of tumor margin fiber parameters as described. Spearman correlation is shown.