A Cdh3-β-catenin-laminin signaling axis in a subset of breast tumor leader cells control leader cell polarization and directional collective migration

Abstract

Carcinoma dissemination can occur when heterogeneous tumor and tumor-stromal cell clusters migrate together via collective migration. Cells at the front lead and direct collective migration, yet how these leader cells form and direct migration are not fully appreciated. From live videos of primary mouse and human breast tumor organoids in a 3D microfluidic system mimicking native breast tumor microenvironment, we developed 3D computational models, which hypothesize that leader cells need to generate high protrusive forces and overcome extracellular matrix (ECM) resistance at the leading edge. From single-cell sequencing analyses, we find that leader cells are heterogeneous and identify and isolate a keratin 14- and cadherin-3-positive subpopulation sufficient to lead collective migration. Cdh3 controls leader cell protrusion dynamics through local production of laminin, which is required for integrin/focal adhesion function. Our findings highlight how a subset of leader cells interact with the microenvironment to direct collective migration.

Keywords: cadherin-integrin crosstalk; cancer metastasis; cellular protrusion dynamics; collective migration; leader cells.

Figure 1.. Computational modeling of tumor organoid collective invasion in 3D

(A) Schemes describing 3D tumor organoid response to a chemokine gradient (SDF1). (B) Key modeling variables: leader/follower adhesions and protrusions (left). Leader cells (green) and follower cells (blue) in 3D (right). (C) Heatmaps for leader cell polarization (left), organoid circularity (middle), and organoid displacement relative to initial radius (right) for varying $J_{LF}$ and $J_{FF}$, leader-leader adhesions moderate $(J_{LL}=5)$, and leader cell protrusive forces high $(P_L=20,P_F=1)$. (D) Cross-section views of 3D organoid at t = 4 h for high leader cell protrusive forces and varying adhesions: (Di) weak follower-follower $(J_{FF}=10)$ and strong leader-follower $(J_{LF}=1)$; (Dii) strong follower-follower $(J_{FF}=1)$ and weak leader-follower $(J_{LF}=1)$; (Diii) weak follower-follower $(J_{FF}=10)$ and weak leader-follower $(J_{LF}=10)$; and (Div) strong follower-follower $(J_{FF}=10)$ and strong leader-follower $(J_{LF}=10)$. (E) Schemes describing 4 cases in (D). (F) Cross-section views of 3D organoid at t = 16 h for increasing $P_L$. X marks the initial position of organoid center. (G) With ECM adhesion feedback present cross-section views of 3D organoid at t = 16 h for increasing $P_L$. Red outline and ${}^{‘‘{}^{\ast }’’}$ symbol mark the case which captures video observation. (H) Without ECM adhesion feedback (dotted line) and with ECM adhesion feedback (solid line) leader cell polarization, organoid circularity, and organoid displacement relative to organoid radius are plotted for varying leader protrusions $P_L$. (I) Average leader population speed (green line) and average follower population speed (blue line) over time.

Figure 2.. scRNA-seq analysis of collectively migrated mouse breast tumor organoids

(A–C) UMAP plots of mouse MMTV-PyMT breast tumor organoids before migration (no signal) (A); after migration in a SDF1 gradient (B), or an interstitial (IS) flow gradient (C). (D–I) (D–F) UMAP plots and violin plots (G–I) of K14 expression. Red outlines in each setting identify predominant K14 expressing tumor cell cluster. (J–L) UMAP plots showing cell clusters expressing migration gene set. Red outlines identify tumor cell cluster co-enriched for K14 and migration genes. For scRNA-seq experiments, n = 3 biological replicates.

Figure 3.. Cdh3 enrichment identifies a unique leader cell subpopulation

(A–C) Volcano plots of the major K14+ tumor cell subpopulations (#7, no signal; #4, SDF1 gradient; #2, IS flow gradient) relative to all other K14+ tumor cell clusters within each respective sample. Black arrows identify Cdh3 and fold enrichment. Blue arrows identify Cdh1 and fold change. (D) Venn diagram of overlapping genes in unique K14 tumor cell subpopulations from each experimental setting. (E–J) Violin plots of Cdh3 expression (E–G) and Cdh1 expression (H–J) in cell clusters for each experimental setting. (K) IF images of mouse MMTV-PyMT tumor organoid after migration in SDF1 gradient. White arrow direction of migration. Arrowheads identify cells at leading edge that express both K14 and Cdh3. (L) Pearson’s correlation coefficient analysis measuring co-localization of K14 and Cdh3 or K14 and Cdh1 in migrated organoids. For scRNA-seq experiments, n = 3 biological replicates.

Figure 4.. The K14+/Cdh3+ leader cell subpopulation promotes directed collective migration of normal breast organoids

(A) Organoid reconstitution assay: K14+/Cdh3+ cells sorted from MMTV-PyMT tumors, depleted of CD45⁺ immune cells and CAFs (Thy1+/PDGFRβ+), and mixed with normal mammary gland organoids (MG). (B) Polarization of K14-Actin.GFP tumor cells in reconstituted organoid. (C) Migration tracking maps for MGs, K14+/Cdh3+ reconstituted organoids, and K14+/Cdh3+ (Ddr2^−/−) reconstituted organoids in response to a SDF1. (D and E) Migration efficiency and velocity for indicated reconstituted organoids. For experiments in microfluidic devices n = 12–15 technical replicates with n = 3 biological replicates were analyzed, *p < 0.05 ANOVA with Tukey’s post hoc analysis.

Figure 5.. Cdh3 expression in leader cells is required for collective migration, K14 cell polarization, protrusion efficiency, and collagen fiber deformation

(A and B) Migration efficiency and velocity of mouse PyMT breast tumor organoids, ±Cdh3, in a SDF1 gradient. (C and D) Migration efficiency and velocity of human-in-mouse PDX breast tumor organoids, ±Cdh3, in a SDF1 gradient. (E and F) Polarization of mouse PyMT K14+ tumor cells, ±Cdh3. (E) Organoids immunostained K14 (green) and lentiviral transduction (red) exposed to a SDF1 gradient. White arrow direction of migration. Broken line start position. (F) Quantification of results in (E) over 6 h. (G and H) Orthotopic, syngeneic breast transplant experiment. Control 4T1 cells (n = 8) or 4T1 cells depleted of Cdh3 (n = 7). Primary tumor weight (G) and number of lung metastases (H) at termination. (I) WT and Cdh3-depleted mouse PyMT tumor organoids in 2.3 mg/mL collagen for 12 h, imaging was performed for 1.5 h at 5-min interval. Protrusion outlines of organoids are plotted, visualized by color-coded timestamps. Unidirectional (single arrowheads) and regressive (double arrowheads) protrusions. (J) Percentage change in tumor organoid area, relative to the reference time point, over time calculated from protrusion outlines. (K) Protrusion efficiency: area under the curve of percent spreading over time using Y = 0 as baseline. (L) Spatial heatmap of collagen deformation around tumor organoids. (M) Rate of collagen deformation by tumor organoids over time. n = 3 for WT and n = 5 for Cdh3− depleted. Solid lines mean and shaded background standard error (SE). For experiments in microfluidic devices n = 12–15 technical replicates with n = 3 biological replicates were analyzed. For all experiments, *p < 0.05 ANOVA with Tukey’s post hoc analysis.

Figure 6.. Cdh3 controls Lam332 expression in leader cells

(A) IF images of WT PyMT tumor organoids migrating in a SDF1 gradient (white arrow), stained for indicated proteins. (B) IF images of PyMT tumor organoids, ±Cdh3, migrated in a SDF1 chemical gradient (white arrow) stained for indicated proteins. (C) H&E and IF images of the invasive edge of 4T1 breast primary tumor sections, ±Cdh3, stained for indicated proteins. (D) qPCR analysis of Lam332 genes mRNA levels in 4T1 breast tumors, ±Cdh3. (E) Migration tracking maps for PyMT tumor organoids, ±Lamα3, in a SDF1 gradient. (F and G) Migration efficiency and velocity of organoids in (E). (H) Polarization of K14+ tumor leader cells in mouse tumor organoids, ±Lamα3. For experiments in microfluidic devices n = 12–15 technical replicates with n = 3 biological replicates were analyzed. For all experiments, *p < 0.05, ***p < 0.01 ANOVA with Tukey’s post hoc analysis.

Figure 7.. Cdh3 controls β-catenin activity to stimulate local laminin 332 production that is required for collective migration

(A) Subcellular fractionation and quantitative western blots of confluent mouse 4T1 cells, ±Cdh3. Nuclear/cytoplasmic ratio of β-catenin levels was determined by comparing subcellular extract levels normalized to equivalent number of cells. (B) Quantitative western blot analyses of confluent mouse 4T1 and human BT549 cells, ±Cdh3, with indicated antibodies. β-cat-pS552 in 4T1 cells not determined (nd) as total β-cat in Cdh3-depleted cells was too low. Cartoon on left highlights signaling pathways interrogated. (C) Chromatin IP of confluent WT mouse 4T1 cells with indicated antibodies and PCR of promoter regions of Lam332 genes. (D) IF images of PyMT breast tumor organoids, ±Lamα3, exposed to a SDF1 gradient (arrow) and stained for K14-Actin.GFP (green) and active β-integrin (9EG7) (red). Arrowheads identify co-stained cells at leading edge. 9EG7 fluorescence in K14+ cells quantified (right). (E) Western blot of confluent mouse 4T1 cells, ±Cdh3, with indicated antibodies. (F) Migration tracking maps and migration efficiency of PyMT tumor organoids, ±Cdh3, in microfluidic devices containing collagen I: laminin 332 (1:1) and exposed to a SDF1 gradient. (G–J) Multiplex immunohistochemical analysis of human breast tumor TMAs from untreated patients with metastatic disease. (G) Low resolution merged image stained with indicated antibodies. Samples with tumor-stromal interfaces were scored and compared with equal number without tumor-stromal interface (I and J). n = 6 for each. (H) Higher magnification images delineated by the white box in (G). Arrowheads in each panel identify the same cells. For experiments in microfluidic devices n = 12–15 technical replicates with n = 3 biological replicates were analyzed. For all experiments, *p < 0.05 ANOVA with Tukey’s post hoc analysis.