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. 2023 Sep 6;13(9):2050-2071.
doi: 10.1158/2159-8290.CD-22-0644.

Dynamic Glycoprotein Hyposialylation Promotes Chemotherapy Evasion and Metastatic Seeding of Quiescent Circulating Tumor Cell Clusters in Breast Cancer

Nurmaa K Dashzeveg  1 , Yuzhi Jia  1 , Youbin Zhang  2 , Lorenzo Gerratana  3 , Priyam Patel  4 , Asif Shajahan  5 , Tsogbadrakh Dandar  1 , Erika K Ramos  1 , Hannah F Almubarak  1 , Valery Adorno-Cruz  1 , Rokana Taftaf  1 , Emma J Schuster  1 , David Scholten  1 , Michael T Sokolowski  1 , Carolina Reduzzi  2   6 , Lamiaa El-Shennawy  1 , Andrew D Hoffmann  1 , Maroua Manai  2 , Qiang Zhang  2 , Paolo D'Amico  2 , Parastoo Azadi  5 , Karen J Colley  7 , Leonidas C Platanias  2   8 , Ami N Shah  2   8 , William J Gradishar  2   8 , Massimo Cristofanilli  2   6   8 , William A Muller  8   9 , Brian A Cobb  10 , Huiping Liu  1   2   8
Affiliations

Dynamic Glycoprotein Hyposialylation Promotes Chemotherapy Evasion and Metastatic Seeding of Quiescent Circulating Tumor Cell Clusters in Breast Cancer

Nurmaa K Dashzeveg et al. Cancer Discov. .

Abstract

Most circulating tumor cells (CTC) are detected as single cells, whereas a small proportion of CTCs in multicellular clusters with stemness properties possess 20- to 100-times higher metastatic propensity than the single cells. Here we report that CTC dynamics in both singles and clusters in response to therapies predict overall survival for breast cancer. Chemotherapy-evasive CTC clusters are relatively quiescent with a specific loss of ST6GAL1-catalyzed α2,6-sialylation in glycoproteins. Dynamic hyposialylation in CTCs or deficiency of ST6GAL1 promotes cluster formation for metastatic seeding and enables cellular quiescence to evade paclitaxel treatment in breast cancer. Glycoproteomic analysis reveals newly identified protein substrates of ST6GAL1, such as adhesion or stemness markers PODXL, ICAM1, ECE1, ALCAM1, CD97, and CD44, contributing to CTC clustering (aggregation) and metastatic seeding. As a proof of concept, neutralizing antibodies against one newly identified contributor, PODXL, inhibit CTC cluster formation and lung metastasis associated with paclitaxel treatment for triple-negative breast cancer.

Significance: This study discovers that dynamic loss of terminal sialylation in glycoproteins of CTC clusters contributes to the fate of cellular dormancy, advantageous evasion to chemotherapy, and enhanced metastatic seeding. It identifies PODXL as a glycoprotein substrate of ST6GAL1 and a candidate target to counter chemoevasion-associated metastasis of quiescent tumor cells. This article is featured in Selected Articles from This Issue, p. 1949.

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Figures

Figure 1. Chemotherapy correlates with CTC cluster formation and loss of α2,6-SA/ST6GAL1. A, The probability of OS by Kaplan–Meier estimates in the patients with advanced-stage breast cancer, stratified by three alteration patterns of single CTCs (left) or CTC clusters (middle) between baseline (prior to treatment) and the first radiologic evaluation (E1) after 3-month treatment, including (i) decreased CTCs; (ii) stably low or negative CTCs; and (iii) increased or stably high CTCs (singles or clusters). Wilcoxon signed-rank test P < 0.0001. CTCs were detected via CellSearch. Right, representative CellSearch images of a single CTC (CK+DAPI+CD45−) at baseline (top row) and a two-cell CTC cluster at E1 (bottom) from a chemo-treated patient (scale bars = 10 μm). Dec, decreased; Inc, increased; Neg, negative. B, Dynamic counts of CellSearch-detected CTCs (# events), singles and CTC clusters, at baseline and E1 for each breast cancer patient treated with chemotherapy (blue lines) and nonchemotherapy options (purple lines). Wilcoxon signed rank test for CTC cluster alterations P = 0.0158 with chemo (n = 47) and P = 0.6447 without chemo (n = 35); for single CTC alterations P = 0.5461 with chemo and P = 0.5028 without chemo. C, The probability of OS by Kaplan–Meier estimates in patients with advanced-stage breast cancer with or without chemotherapy (chemo ±, left and right), stratified by the CTC alteration patterns of decreased, negative or stable low, and increased CTC cluster events at E1 compared with baseline (log-rank test P = 0.0071 and P < 0.0001). CTCs were measured by CellSearch. D, Representative images (left) and quantification (right) of Sambucus Nigra (SNA)–bound α2,6-SA signals in individual CTCs, both singles (S; n = 120 cells) and from clusters [C; n = 44 tumor cells in the clusters (homotypic and heterotypic clusters of CTCs and CD45+ cells)] of patients with breast cancer (n = 6 patients), analyzed by CellSearch (scale bars = 10 μm). E, The bar graphs of SNA-high populations within singles (S) and clusters (C) in nonchemo-treated patients (left: −Chemo), chemo-treated patients (middle: +Chemo, n = 46, P = 0.002), and paclitaxel-treated patients (right: +PAX, n = 6, P = 0.038). F, Schematic of the PAX treatment for PDX-M1 tumors and subsequent analyses of CTCs and lung metastases (mets). One week after orthotopic implantation of PDX-M1 tumor cells into mouse mammary fat pads, mice were treated with PBS or PAX-NAB (PAX; 13.5 mg/kg) once every 3 days via tail vein 10 times. Three days after the last treatment, mice were sacrificed with collections of blood, breast tumors, and lungs for analyses of CTCs, tumors, and metastasis burdens, respectively. G–N, After PBS/PAX treatments shown in F, representative photos of PDX tumors (G; scale bars = 1 cm) and quantification of the tumor weight (H), bioluminescence images of dissected lungs ex vivo (I) and quantified lung metastases in total flux (J), counts of single CTCs (K) and CTC clusters (L) in PBS- and PAX-treated mice, and the percentage of SNA-high CTCs in singles vs. clusters in mice treated with PBS (M) and PAX (N). CTCs were analyzed via flow cytometry. P values were calculated by GraphPad (Student t test) unless otherwise indicated. Data, mean ± SD.
Figure 1.
Chemotherapy correlates with CTC cluster formation and loss of α2,6-SA/ST6GAL1. A, The probability of OS by Kaplan–Meier estimates in the patients with advanced-stage breast cancer, stratified by three alteration patterns of single CTCs (left) or CTC clusters (middle) between baseline (prior to treatment) and the first radiologic evaluation (E1) after 3-month treatment, including (i) decreased CTCs; (ii) stably low or negative CTCs; and (iii) increased or stably high CTCs (singles or clusters). Wilcoxon signed-rank test P < 0.0001. CTCs were detected via CellSearch. Right, representative CellSearch images of a single CTC (CK+DAPI+CD45−) at baseline (top row) and a two-cell CTC cluster at E1 (bottom) from a chemo-treated patient (scale bars = 10 μm). Dec, decreased; Inc, increased; Neg, negative. B, Dynamic counts of CellSearch-detected CTCs (# events), singles and CTC clusters, at baseline and E1 for each breast cancer patient treated with chemotherapy (blue lines) and nonchemotherapy options (purple lines). Wilcoxon signed rank test for CTC cluster alterations P = 0.0158 with chemo (n = 47) and P = 0.6447 without chemo (n = 35); for single CTC alterations P = 0.5461 with chemo and P = 0.5028 without chemo. C, The probability of OS by Kaplan–Meier estimates in patients with advanced-stage breast cancer with or without chemotherapy (chemo ±, left and right), stratified by the CTC alteration patterns of decreased, negative or stable low, and increased CTC cluster events at E1 compared with baseline (log-rank test P = 0.0071 and P < 0.0001). CTCs were measured by CellSearch. D, Representative images (left) and quantification (right) of Sambucus Nigra (SNA)–bound α2,6-SA signals in individual CTCs, both singles (S; n = 120 cells) and from clusters [C; n = 44 tumor cells in the clusters (homotypic and heterotypic clusters of CTCs and CD45+ cells)] of patients with breast cancer (n = 6 patients), analyzed by CellSearch (scale bars = 10 μm). E, The bar graphs of SNA-high populations within singles (S) and clusters (C) in nonchemo-treated patients (left: −Chemo), chemo-treated patients (middle: +Chemo, n = 46, P = 0.002), and paclitaxel-treated patients (right: +PAX, n = 6, P = 0.038). F, Schematic of the PAX treatment for PDX-M1 tumors and subsequent analyses of CTCs and lung metastases (mets). One week after orthotopic implantation of PDX-M1 tumor cells into mouse mammary fat pads, mice were treated with PBS or PAX-NAB (PAX; 13.5 mg/kg) once every 3 days via tail vein 10 times. Three days after the last treatment, mice were sacrificed with collections of blood, breast tumors, and lungs for analyses of CTCs, tumors, and metastasis burdens, respectively. G–N, After PBS/PAX treatments shown in F, representative photos of PDX tumors (G; scale bars = 1 cm) and quantification of the tumor weight (H), bioluminescence images of dissected lungs ex vivo (I) and quantified lung metastases in total flux (J), counts of single CTCs (K) and CTC clusters (L) in PBS- and PAX-treated mice, and the percentage of SNA-high CTCs in singles vs. clusters in mice treated with PBS (M) and PAX (N). CTCs were analyzed via flow cytometry. P values were calculated by GraphPad (Student t test) unless otherwise indicated. Data, mean ± SD.
Figure 2. a2,6-SA and ST6GAL1 inhibit cluster formation and confer sensitivity to PAX. A, Left, flow profile of MDA-MB-231 cells with α2,6-SA–low and α2,6-SA–high populations. Right, representative images of sorted α-2,6-SA–low and α2,6-SA–high cells at 4 hours of clustering (top) and cluster formation curves (cluster size by area) of sorted cells (bottom). Scale bars = 60 μm. See Supplementary Videos S1 and S2 for cluster videos. B, Flow histograms of SNA-binding signals (left), representative cluster images (middle), and cluster formation curves (right) of MDA-MB-231 cells: ST6WT and ST6KO cells transfected with control vectors (-Con), and ST6KO cells transfected with ST6GAL1 overexpression vector (-OE). Scale bars = 100 μm. Cluster videos are available as Supplementary Videos S3–S5. C, Left: cell death (%) of CTC-092 PDX tumor cells ex vivo 24 hours after paclitaxel (PAX) treatments at 0, 25, 50, and 250 μg/mL, measured as DAPI positivity of live cells via flow cytometry (ns, not significant). Right, representative flow profile of DAPI and SNA signals in PAX-treated cells at the high dose of 250 μg/mL. D, Representative flow histograms (left) and SNA-high population (%) within alive CTC-092 cells (right) after 24 hours of PAX treatment at indicated doses (0–250 μg/mL). E, Representative images of CTC clusters formed at 24 hours (left) and the time-course cluster formation curves (right, cluster size) of CTC-092 PDX cells ex vivo upon treatment with PBS and PAX-NAB at 25 μg/mL. Scale bar = 50 μm. See Supplementary Videos S6 and S7 for cluster videos. F, Representative flow plots (left) and quantified viability (DAPI exclusion %; right graph) of flow sorting–enriched SNA-high and SNA-low MDA-MB-231 cells (as shown in A) after overnight treatment with PAX at 0 and 25 μg/mL. G, Immunoblots of ST6GAL1, ST3GAL1, FUT3, CD44, and β-actin (loading control) of ST6WT and ST6KO cells at indicated time points (0, 24, and 48 hours) after PAX (25 μg/mL) treatment. Data are representative images of 2 biological replicates. H, Bright-field images of ST6WT and ST6KO cells (left) and their cell viability (%) after treatment with PAX at indicated doses (0–200 μg/mL; right). I, Cell viability of ST6WT and ST6KO cells after indicated time of paclitaxel (PAX) treatment at 25 μg/mL. P values were calculated with the Student t test in GraphPad unless otherwise indicated. Data, mean ± SD of 3–5 experimental replicates.
Figure 2.
a2,6-SA and ST6GAL1 inhibit cluster formation and confer sensitivity to PAX. A, Left, flow profile of MDA-MB-231 cells with α2,6-SA–low and α2,6-SA–high populations. Right, representative images of sorted α-2,6-SA–low and α2,6-SA–high cells at 4 hours of clustering (top) and cluster formation curves (cluster size by area) of sorted cells (bottom). Scale bars = 60 μm. See Supplementary Videos S1 and S2 for cluster videos. B, Flow histograms of SNA-binding signals (left), representative cluster images (middle), and cluster formation curves (right) of MDA-MB-231 cells: ST6WT and ST6KO cells transfected with control vectors (-Con), and ST6KO cells transfected with ST6GAL1 overexpression vector (-OE). Scale bars = 100 μm. Cluster videos are available as Supplementary Videos S3–S5. C, Left: cell death (%) of CTC-092 PDX tumor cells ex vivo 24 hours after paclitaxel (PAX) treatments at 0, 25, 50, and 250 μg/mL, measured as DAPI positivity of live cells via flow cytometry (ns, not significant). Right, representative flow profile of DAPI and SNA signals in PAX-treated cells at the high dose of 250 μg/mL. D, Representative flow histograms (left) and SNA-high population (%) within alive CTC-092 cells (right) after 24 hours of PAX treatment at indicated doses (0–250 μg/mL). E, Representative images of CTC clusters formed at 24 hours (left) and the time-course cluster formation curves (right, cluster size) of CTC-092 PDX cells ex vivo upon treatment with PBS and PAX-NAB at 25 μg/mL. Scale bar = 50 μm. See Supplementary Videos S6 and S7 for cluster videos. F, Representative flow plots (left) and quantified viability (DAPI exclusion %; right graph) of flow sorting–enriched SNA-high and SNA-low MDA-MB-231 cells (as shown in A) after overnight treatment with PAX at 0 and 25 μg/mL. G, Immunoblots of ST6GAL1, ST3GAL1, FUT3, CD44, and β-actin (loading control) of ST6WT and ST6KO cells at indicated time points (0, 24, and 48 hours) after PAX (25 μg/mL) treatment. Data are representative images of 2 biological replicates. H, Bright-field images of ST6WT and ST6KO cells (left) and their cell viability (%) after treatment with PAX at indicated doses (0–200 μg/mL; right). I, Cell viability of ST6WT and ST6KO cells after indicated time of paclitaxel (PAX) treatment at 25 μg/mL. P values were calculated with the Student t test in GraphPad unless otherwise indicated. Data, mean ± SD of 3–5 experimental replicates.
Figure 3. Lack of a2,6-SA and ST6GAL1 is associated with quiescence in CTC clusters. A, Representative CellSearch CTC (CK+DAPI+CD45−) images of two singles and one 5-cell cluster with channels of CK/DAPI merged, DAPI, CD45, and Ki-67 signals, collected from the blood of patients with breast cancer. One single CTC and one CTC within the cluster stained Ki-67 positive. Scale bars = 10 μm. B, Ki-67 signal intensity per cell in single CTCs (n = 83 cells) and clustered CTCs (n = 102 cells, P = 0.0005), as well as binary assessment of Ki-67–positive cells (positive threshold at the intensity mean >75) between single CTCs and CTC clusters (P = 0.008), as measured on ImageJ. C, Plots of individual CTCs showing a positive association between quantified Ki-67 (proliferative index) and DAPI (DNA content) signal intensities per CTC (n = 141, R = 0.8618, P < 0.00001, calculated using www.socscistatistics.com), as measured on ImageJ. D, Proportion of single and clustered CTC distributions within the cell-cycle phases (G0–G1, S, G2–M) at baseline and E1 after treatment, based on the DAPI (DNA) intensity of each CTC on ImageJ using CellSearch images. The ranges of DAPI mean intensity/cell: G1/G0 < 100, S = 100–140, G2–M > 140 (n = 1,684 CTCs from 15 patients with breast cancer), P = 0.052 (baseline singles vs. baseline clusters), P = 8.8E-26 (E1 singles vs. E1 clusters), P = 0.935 (baseline singles vs. E1 singles), and P = 5.2E-07 (baseline clusters vs. E1 clusters). E, Dot plots of individual CTCs with a positive correlation between SNA signals (α2,6-SA) and DAPI intensity (DNA content) per CTC (n = 164 cells, R = 0.4052, P < 0.00001). F and G, Pearson correlation of the percentage (%) of SNA-high cells and % of Ki-67+ CTCs in M1-PDX tumor-bearing mice (n = 20 mice, R = 0.6278, P < 0.00304 calculated using www.socscistatistics.com; F) and the % of Ki-67+ CTCs in singles vs. clusters (G) in the PBS/PAX-treated PDX-M1 model shown in Fig. 1F–N. H–J, Gene set enrichment analysis of RNA-seq of ST6WT vs. ST6KO MDA-MB-231 cells. H, The most downregulated pathways are purple, and the most upregulated pathways are blue. I, The enrichment plots for downregulated pathways include E2F targets, G2–M checkpoint, and MYC targets (V1 and V2). J, The upregulated pathways include interferon response sets, epithelial-to-mesenchymal transition, and inflammatory response genes. K, Cell confluency curves of two clones of ST6WT (1 and 2, purple) vs. two clones of ST6KO (1 and 2, blue) cells over 120 hours Data, mean ± SD of 12 experimental replicates. L, The relative proportion (%) of α2,6-SA–low and α2,6-SA–high populations in each of the cell-cycle phases of ST6WT cells. M and N, Representative flow profiles (M) and quantification of cell-cycle phases (N) of ST6WT vs. ST6KO cells. Cellular DNA content is measured with Hoechst 33342, and RNA content is measured with Pyronin Y. Quiescent cells (G0) are distinguished from the G1 phase by a low level of RNA content with the same amount of DNA content. P values were calculated with the Student t test in Excel or GraphPad unless otherwise indicated. Data, mean ± SD of 3–5 experimental replicates.
Figure 3.
Lack of a2,6-SA and ST6GAL1 is associated with quiescence in CTC clusters. A, Representative CellSearch CTC (CK+DAPI+CD45−) images of two singles and one 5-cell cluster with channels of CK/DAPI merged, DAPI, CD45, and Ki-67 signals, collected from the blood of patients with breast cancer. One single CTC and one CTC within the cluster stained Ki-67 positive. Scale bars = 10 μm. B, Ki-67 signal intensity per cell in single CTCs (n = 83 cells) and clustered CTCs (n = 102 cells, P = 0.0005), as well as binary assessment of Ki-67–positive cells (positive threshold at the intensity mean >75) between single CTCs and CTC clusters (P = 0.008), as measured on ImageJ. C, Plots of individual CTCs showing a positive association between quantified Ki-67 (proliferative index) and DAPI (DNA content) signal intensities per CTC (n = 141, R = 0.8618, P < 0.00001, calculated using www.socscistatistics.com), as measured on ImageJ. D, Proportion of single and clustered CTC distributions within the cell-cycle phases (G0–G1, S, G2–M) at baseline and E1 after treatment, based on the DAPI (DNA) intensity of each CTC on ImageJ using CellSearch images. The ranges of DAPI mean intensity/cell: G1/G0 < 100, S = 100–140, G2–M > 140 (n = 1,684 CTCs from 15 patients with breast cancer), P = 0.052 (baseline singles vs. baseline clusters), P = 8.8E-26 (E1 singles vs. E1 clusters), P = 0.935 (baseline singles vs. E1 singles), and P = 5.2E-07 (baseline clusters vs. E1 clusters). E, Dot plots of individual CTCs with a positive correlation between SNA signals (α2,6-SA) and DAPI intensity (DNA content) per CTC (n = 164 cells, R = 0.4052, P < 0.00001). F and G, Pearson correlation of the percentage (%) of SNA-high cells and % of Ki-67+ CTCs in M1-PDX tumor-bearing mice (n = 20 mice, R = 0.6278, P < 0.00304 calculated using www.socscistatistics.com; F) and the % of Ki-67+ CTCs in singles vs. clusters (G) in the PBS/PAX-treated PDX-M1 model shown in Fig. 1F–N. H–J, Gene set enrichment analysis of RNA-seq of ST6WT vs. ST6KO MDA-MB-231 cells. H, The most downregulated pathways are purple, and the most upregulated pathways are blue. I, The enrichment plots for downregulated pathways include E2F targets, G2–M checkpoint, and MYC targets (V1 and V2). J, The upregulated pathways include interferon response sets, epithelial-to-mesenchymal transition, and inflammatory response genes. K, Cell confluency curves of two clones of ST6WT (1 and 2, purple) vs. two clones of ST6KO (1 and 2, blue) cells over 120 hours Data, mean ± SD of 12 experimental replicates. L, The relative proportion (%) of α2,6-SA–low and α2,6-SA–high populations in each of the cell-cycle phases of ST6WT cells. M and N, Representative flow profiles (M) and quantification of cell-cycle phases (N) of ST6WT vs. ST6KO cells. Cellular DNA content is measured with Hoechst 33342, and RNA content is measured with Pyronin Y. Quiescent cells (G0) are distinguished from the G1 phase by a low level of RNA content with the same amount of DNA content. P values were calculated with the Student t test in Excel or GraphPad unless otherwise indicated. Data, mean ± SD of 3–5 experimental replicates.
Figure 4. ST6GAL1 inhibits cluster formation and blocks metastatic seeding in PDX models. A, Flow cytometry profiles of α2,6-SA (SNA) of indicated PDX models (M1, M2, and M3). B, Representative images (left) and quantification (right) of cluster size (area) of PDX-M1 (M1) vs. PDX-M2 (M2) tumor cells at 24 hours (scale bars = 300 μm). Data are represented as mean ± SD of 6 experimental replicates. C, Schematic design to analyze spontaneous metastases of M1 (−5 weeks) and M2 (−8 weeks) PDX tumor models: 5 × 104 cells were orthotopically injected into the fourth mouse mammary fat pads. Five to 8 weeks after implantation, breast tumor weight and lung metastases (mets) were measured. D, Top: images of dissected tumors (scale bar = 1 cm) and lung metastases (bioluminescence) of M1 and M2 PDX models. Bottom: quantified tumor weight (g) and lung metastasis (bioluminescence imaging total flux). E, Flow cytometry profiles of α2,6-SA levels in ST6WT and ST6KO PDX-M1/M2 models. F, Flow cytometry profile of α2,6-SA levels (left) and cluster formation curves (right) in ST6WT and ST6OE cells derived from M2 PDXs. Curve data are represented as mean ± SD of 12 experimental replicates. G, Experimental illustration of tail-vein injection of ST6KO (KO) with appropriate ST6WT (WT) controls of PDX-M1 and PDX-M2 models; 1 × 105 cells/mouse were injected via tail vein, and lung localization signals were measured 24 hours and/or 5 weeks after injection. H, Representative images (left) and quantification (right) of lung metastatic seedings of ST6WT vs. ST6KO M1 and M2 models 24 hours after injection. Lung total flux of cellular bioluminescence signals was imaged prior to and after injections. I, Lung bioluminescence images (left) and quantified lung metastases (photons/s; right) 5 weeks after tail-vein injection of ST6WT and ST6KO cells. J, Schematic illustration of orthotopic implantations of ST6WT and ST6KO PDX-M1 into the fourth mouse mammary fat pads. Two batches of ST6WT (1.2 × 103 cells/injection) and ST6KO (5 × 103 cells/injection) cells were injected, and tumors were harvested when reaching ∼0.5 g or 1.0 g. K, Quantified tumor weight for both ST6WT and ST6KO M1 tumors collected at various time points. L, Representative bioluminescence images (left) and quantified lung metastasis (right) of ST6WT and ST6KO PDX-M1 models at 0.5 g and 1.0 g, respectively. Data, mean ± SD of 8 experimental replicates. M, Schematic of orthotopic implantations of ST6WT (6 × 104 cells) and ST6OE (2 × 104 cells) PDX-M2 cells per mammary fat pad, photo of primary breast tumors, and tumor weight comparison between two groups to assess the lung metastases. N, Representative bioluminescence images of dissected lungs (left) and the relative lung metastases, presented as total flux of the lung bioluminescence, at 2 months of implantation. P values were calculated with Student t test using GraphPad, and data are represented as mean ± SD of 3–5 experimental replicates unless otherwise indicated.
Figure 4.
ST6GAL1 inhibits cluster formation and blocks metastatic seeding in PDX models. A, Flow cytometry profiles of α2,6-SA (SNA) of indicated PDX models (M1, M2, and M3). B, Representative images (left) and quantification (right) of cluster size (area) of PDX-M1 (M1) vs. PDX-M2 (M2) tumor cells at 24 hours (scale bars = 300 μm). Data are represented as mean ± SD of 6 experimental replicates. C, Schematic design to analyze spontaneous metastases of M1 (−5 weeks) and M2 (−8 weeks) PDX tumor models: 5 × 104 cells were orthotopically injected into the fourth mouse mammary fat pads. Five to 8 weeks after implantation, breast tumor weight and lung metastases (mets) were measured. D, Top: images of dissected tumors (scale bar = 1 cm) and lung metastases (bioluminescence) of M1 and M2 PDX models. Bottom: quantified tumor weight (g) and lung metastasis (bioluminescence imaging total flux). E, Flow cytometry profiles of α2,6-SA levels in ST6WT and ST6KO PDX-M1/M2 models. F, Flow cytometry profile of α2,6-SA levels (left) and cluster formation curves (right) in ST6WT and ST6OE cells derived from M2 PDXs. Curve data are represented as mean ± SD of 12 experimental replicates. G, Experimental illustration of tail-vein injection of ST6KO (KO) with appropriate ST6WT (WT) controls of PDX-M1 and PDX-M2 models; 1 × 105 cells/mouse were injected via tail vein, and lung localization signals were measured 24 hours and/or 5 weeks after injection. H, Representative images (left) and quantification (right) of lung metastatic seedings of ST6WT vs. ST6KO M1 and M2 models 24 hours after injection. Lung total flux of cellular bioluminescence signals was imaged prior to and after injections. I, Lung bioluminescence images (left) and quantified lung metastases (photons/s; right) 5 weeks after tail-vein injection of ST6WT and ST6KO cells. J, Schematic illustration of orthotopic implantations of ST6WT and ST6KO PDX-M1 into the fourth mouse mammary fat pads. Two batches of ST6WT (1.2 × 103 cells/injection) and ST6KO (5 × 103 cells/injection) cells were injected, and tumors were harvested when reaching ∼0.5 g or 1.0 g. K, Quantified tumor weight for both ST6WT and ST6KO M1 tumors collected at various time points. L, Representative bioluminescence images (left) and quantified lung metastasis (right) of ST6WT and ST6KO PDX-M1 models at 0.5 g and 1.0 g, respectively. Data, mean ± SD of 8 experimental replicates. M, Schematic of orthotopic implantations of ST6WT (6 × 104 cells) and ST6OE (2 × 104 cells) PDX-M2 cells per mammary fat pad, photo of primary breast tumors, and tumor weight comparison between two groups to assess the lung metastases. N, Representative bioluminescence images of dissected lungs (left) and the relative lung metastases, presented as total flux of the lung bioluminescence, at 2 months of implantation. P values were calculated with Student t test using GraphPad, and data are represented as mean ± SD of 3–5 experimental replicates unless otherwise indicated.
Figure 5. Glycoproteomic analyses reveal novel α2,6-sialylation targets of ST6GAL1. A, Experimental design of glycoproteome profiles of SNA-bound α2,6-SA+ membrane proteins isolated from ST6WT and KO cells. The membrane fractions were isolated, and α2,6-SA–linked proteins were coimmuno­precipitated with SNA-conjugated agarose beads. Purified proteins were loaded to the glycoproteomics analysis. B, The list of top ST6GAL1 target glycoproteins including their α2,6-sialylation sites on the peptide. C, Immunoblots of the ST6GAL1 substrates PODXL, ECE1, CD97, ALCAM1, and ICAM1 with immunoprecipitation (IP) by SNA (α-2,6-SA+ proteins) or agarose controls, and input controls of the membrane fraction (Mem) or whole-cell lysate (WCL) from ST6WT (+) and ST6KO (−) MDA-MB-231 cells. D, Immunoblots of ST6GAL1 target proteins and the loading control β-actin from the lysates of ST6KO MDA-MB-231 cells transfected with the scramble control (scr) and siRNAs for PODXL, ECE1, CD97, ALCAM1, and ICAM1. E and F, Representative images of clusters at 2 hours (E) and cluster formation curves over the time (0–16 hours; F) of ST6KO MDA-MB-231 cells after downregulation of indicated genes. P scrST6KO vs. WT < 0.0001, P scrST6KO vs. siPODXL = 0.0001, P scrST6KO vs. siECE1 = 0.0175, P scrST6KO vs. siALCAM1 = 0.0260, P scrST6KO vs. siCD97 = 0.0043, and P scrST6KO vs. siICAM1 = 0.0003; scale bars = 100 μm. P values were calculated with the t test using GraphPad. Data are represented as mean ± SD of 12 experimental replicates. Cluster videos are available as Supplementary Videos S8–S14. G, Representative images of PODXL staining on patient CTCs (CD45−CK+DAPI+) via CellSearch (left) and flow cytometry–based quantification (right) of PODXL expression. H, Schematic (left) and quantification (right) of cell-binding analyses (ST6WT/ST6KO) with PODXL and α2,6-desialylated PODXL isolated from ST6WT and ST6KO cells, respectively. P values were calculated with the Student t test using GraphPad, and data are represented as mean ± SD of 3–5 experimental replicates unless otherwise indicated.
Figure 5.
Glycoproteomic analyses reveal novel α2,6-sialylation targets of ST6GAL1. A, Experimental design of glycoproteome profiles of SNA-bound α2,6-SA+ membrane proteins isolated from ST6WT and KO cells. The membrane fractions were isolated, and α2,6-SA–linked proteins were coimmuno­precipitated with SNA-conjugated agarose beads. Purified proteins were loaded to the glycoproteomics analysis. B, The list of top ST6GAL1 target glycoproteins including their α2,6-sialylation sites on the peptide. C, Immunoblots of the ST6GAL1 substrates PODXL, ECE1, CD97, ALCAM1, and ICAM1 with immunoprecipitation (IP) by SNA (α-2,6-SA+ proteins) or agarose controls, and input controls of the membrane fraction (Mem) or whole-cell lysate (WCL) from ST6WT (+) and ST6KO (−) MDA-MB-231 cells. D, Immunoblots of ST6GAL1 target proteins and the loading control β-actin from the lysates of ST6KO MDA-MB-231 cells transfected with the scramble control (scr) and siRNAs for PODXL, ECE1, CD97, ALCAM1, and ICAM1. E and F, Representative images of clusters at 2 hours (E) and cluster formation curves over the time (0–16 hours; F) of ST6KO MDA-MB-231 cells after downregulation of indicated genes. P scrST6KO vs. WT < 0.0001, P scrST6KO vs. siPODXL = 0.0001, P scrST6KO vs. siECE1 = 0.0175, P scrST6KO vs. siALCAM1 = 0.0260, P scrST6KO vs. siCD97 = 0.0043, and P scrST6KO vs. siICAM1 = 0.0003; scale bars = 100 μm. P values were calculated with the t test using GraphPad. Data are represented as mean ± SD of 12 experimental replicates. Cluster videos are available as Supplementary Videos S8–S14. G, Representative images of PODXL staining on patient CTCs (CD45−CK+DAPI+) via CellSearch (left) and flow cytometry–based quantification (right) of PODXL expression. H, Schematic (left) and quantification (right) of cell-binding analyses (ST6WT/ST6KO) with PODXL and α2,6-desialylated PODXL isolated from ST6WT and ST6KO cells, respectively. P values were calculated with the Student t test using GraphPad, and data are represented as mean ± SD of 3–5 experimental replicates unless otherwise indicated.
Figure 6. Targeting PODXL blocks ST6KO- and chemo-associated metastasis. A–C, Bioluminescence images (BLI) and lung metastasis quantifications of mouse imaging (A) and dissected lungs ex vivo (B), and fluorescence images and relative metastatic seeding (disseminated colonies) to the lungs (C) 24 hours after tail-vein injections of ST6WT (in purple) and ST6KO (in blue) cells transfected twice with scrambled control (scr) and siPODXL (siP) for gene knockdown. Scale bars = 100 μm. D–F, Experimental design (D), as well as representative images and quantification of mouse BLI (E) and lung ex vivo BLI (F) to determine the lung metastases (met) after administration of IgG and anti-PODXL (αP) neutralizing antibody to ST6WT MDA-MB-231 cells [6.5 × 104 cells/mice were preincubated with αP antibody (7 μg/mice) or isotope control IgG (7 μg/mice) for 1 hour]. Cells were then injected via the tail vein, and bioluminescence imaging was measured after 24 hours of injection (E). Then mice were sacrificed and ex vivo images of the lungs were measured (F). G, Schematic view of experiment for cotreatment of PAX and αP antibody, PDX-M1 tumor cells were pretreated with PAX-NAB (50 μg/mL) or PBS with αP (20 μg/mL) or IgG control (20 μg/mL) and incubated for 12 hours at 37°C. Meanwhile, mice were treated with the same combination of drugs (PAX-NAB, 27 mg/kg or PBS, αP or IgG control, 30 μg/mouse) via tail vein 3 hours prior to cell inoculation. Twenty hours and 3 weeks (3 w) after i.v. injection of the cells, lungs were dissected for ex vivo bioluminescence imaging (H, left, 20 hours) and disseminated lung metastasis quantified as total flux in H (right, 20 hours) and I (3 w). J–N, Experimental design of cotreatment of mice bearing orthotropic (OI) PDX-M1 tumors. First, ST6KO M1-PDX cells were injected into a mammary fat pad. Mice were cotreated with PAX-NAB (13.5 mg/kg) or PBS and αP or IgG control (20 μg/mouse) once every 3 days. After 11 times treatments, mice were sacrificed for further analysis. Tumor weight (K), representative images of lung bioluminescence imaging (L) with normalized quantification of lung total flux with tumor weight (M), and the count of CTC clusters (N; left) and single CTCs (right) are shown. P values were calculated with the Student t test using GraphPad. Data, mean ± SD of 3–4 biological replicates.
Figure 6.
Targeting PODXL blocks ST6KO- and chemo-associated metastasis. A–C, Bioluminescence images (BLI) and lung metastasis quantifications of mouse imaging (A) and dissected lungs ex vivo (B), and fluorescence images and relative metastatic seeding (disseminated colonies) to the lungs (C) 24 hours after tail-vein injections of ST6WT (in purple) and ST6KO (in blue) cells transfected twice with scrambled control (scr) and siPODXL (siP) for gene knockdown. Scale bars = 100 μm. D–F, Experimental design (D), as well as representative images and quantification of mouse BLI (E) and lung ex vivo BLI (F) to determine the lung metastases (met) after administration of IgG and anti-PODXL (αP) neutralizing antibody to ST6WT MDA-MB-231 cells [6.5 × 104 cells/mice were preincubated with αP antibody (7 μg/mice) or isotope control IgG (7 μg/mice) for 1 hour]. Cells were then injected via the tail vein, and bioluminescence imaging was measured after 24 hours of injection (E). Then mice were sacrificed and ex vivo images of the lungs were measured (F). G, Schematic view of experiment for cotreatment of PAX and αP antibody, PDX-M1 tumor cells were pretreated with PAX-NAB (50 μg/mL) or PBS with αP (20 μg/mL) or IgG control (20 μg/mL) and incubated for 12 hours at 37°C. Meanwhile, mice were treated with the same combination of drugs (PAX-NAB, 27 mg/kg or PBS, αP or IgG control, 30 μg/mouse) via tail vein 3 hours prior to cell inoculation. Twenty hours and 3 weeks (3 w) after i.v. injection of the cells, lungs were dissected for ex vivo bioluminescence imaging (H, left, 20 hours) and disseminated lung metastasis quantified as total flux in H (right, 20 hours) and I (3 w). J–N, Experimental design of cotreatment of mice bearing orthotropic (OI) PDX-M1 tumors. First, ST6KO M1-PDX cells were injected into a mammary fat pad. Mice were cotreated with PAX-NAB (13.5 mg/kg) or PBS and αP or IgG control (20 μg/mouse) once every 3 days. After 11 times treatments, mice were sacrificed for further analysis. Tumor weight (K), representative images of lung bioluminescence imaging (L) with normalized quantification of lung total flux with tumor weight (M), and the count of CTC clusters (N; left) and single CTCs (right) are shown. P values were calculated with the Student t test using GraphPad. Data, mean ± SD of 3–4 biological replicates.
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References

    1. Cheung KJ, Padmanaban V, Silvestri V, Schipper K, Cohen JD, Fairchild AN, et al. . Polyclonal breast cancer metastases arise from collective dissemination of keratin 14-expressing tumor cell clusters. Proc Natl Acad Sci U S A 2016;113:E854–63. - PMC - PubMed
    1. Mu Z, Wang C, Ye Z, Austin L, Civan J, Hyslop T, et al. . Prospective assessment of the prognostic value of circulating tumor cells and their clusters in patients with advanced-stage breast cancer. Breast Cancer Res Treat 2015;154:563–71. - PubMed
    1. Aceto N, Bardia A, Miyamoto DT, Donaldson MC, Wittner BS, Spencer JA, et al. . Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell 2014;158:1110–22. - PMC - PubMed
    1. Liu X, Taftaf R, Kawaguchi M, Chang YF, Chen W, Entenberg D, et al. . Homophilic CD44 interactions mediate tumor cell aggregation and polyclonal metastasis in patient-derived breast cancer models. Cancer Discov 2019;9:96–113. - PMC - PubMed
    1. Zoller M. CD44: can a cancer-initiating cell profit from an abundantly expressed molecule? Nat Rev Cancer 2011;11:254–67. - PubMed

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