Skip to main content

Main menu

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Advertisers
    • Editorial Board
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
  • About Us
    • General Policy
    • Contact
  • Other Publications
    • Cancer Genomics & Proteomics
    • Anticancer Research
    • In Vivo

User menu

  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Genomics & Proteomics
  • Other Publications
    • Cancer Genomics & Proteomics
    • Anticancer Research
    • In Vivo
  • Register
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Cancer Genomics & Proteomics

Advanced Search

  • Home
  • Current Issue
  • Archive
  • Info for
    • Authors
    • Advertisers
    • Editorial Board
  • Other Publications
    • Anticancer Research
    • In Vivo
    • Cancer Diagnosis & Prognosis
  • More
    • IIAR
    • Conferences
  • About Us
    • General Policy
    • Contact
  • Visit iiar on Facebook
  • Follow us on Linkedin
Research Article
Open Access

Transcriptomic Characterization, Chemosensitivity and Regulatory Effects of Exosomes in Spontaneous EMT/MET Transitions of Breast Cancer Cells

ELISABETTA BIGAGLI, LORENZO CINCI, MARIO D'AMBROSIO and CRISTINA LUCERI
Cancer Genomics & Proteomics May 2019, 16 (3) 163-173; DOI: https://doi.org/10.21873/cgp.20122
ELISABETTA BIGAGLI
Department of Neuroscience, Psychology, Drug Research and Child Health - NEUROFARBA – Section of Pharmacology and Toxicology, University of Florence, Florence, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: elisabetta.bigagli@unifi.it
LORENZO CINCI
Department of Neuroscience, Psychology, Drug Research and Child Health - NEUROFARBA – Section of Pharmacology and Toxicology, University of Florence, Florence, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
MARIO D'AMBROSIO
Department of Neuroscience, Psychology, Drug Research and Child Health - NEUROFARBA – Section of Pharmacology and Toxicology, University of Florence, Florence, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
CRISTINA LUCERI
Department of Neuroscience, Psychology, Drug Research and Child Health - NEUROFARBA – Section of Pharmacology and Toxicology, University of Florence, Florence, Italy
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Background/Aim: We examined the gene expression changes of breast cancer cells spontaneously undergoing epithelial–mesenchymal transition (EMT) and its reverse process mesenchymal–epithelial transition (MET) and the role of exosomes in these transitions. Materials and Methods: Highly invasive mesenchymal-like breast cancer cells, MDA-MB-231 (basal cells), EMT and MET variants, were characterized by microarray gene expression profiling, immunocytochemistry and chemo-sensitivity. Results: Spontaneously disseminated cells were anoikis resistant, exhibited a dissociative, EMT-like phenotype and underwent MET when reseeded in cell-free plates. MET was inhibited by exosomes secreted by basal cells. Chemo-sensitivity to doxorubicin, vincristine and paclitaxel decreased in the order EMT<MET<basal. Phenotypic plasticity arose with differential expression of metastasis and stemness associated genes (LGR5, FZD10, DTX1, ErbB3, FTH1 and DLL4) and pathways (DNA replication and repair, ABC transporter, Hedgehog, Notch and metabolic pathways). Conclusion: This is an appropriate model for studying EMT/MET transitions, drug targets and the role of exosomes in breast cancer dissemination.

  • Breast cancer
  • epithelial–mesenchymal transition (EMT)
  • mesenchymal–epithelial transition (MET)
  • metastasis
  • chemoresistance
  • exosomes

Epithelial to mesenchymal transition (EMT) occurs during tumor progression and contributes to cellular plasticity endowing cancer cells with increased motility and invasiveness (1, 2). A critical molecular feature of EMT is the down-regulation of the adhesion molecule E-cadherin and the acquisition of a mesenchymal phenotype associated with the up-regulation of vimentin (3). When cancer cells successfully establish metastasis at secondary sites, they also undergo the reverse process known as mesenchymal–to–epithelial transition (MET) and re-acquire epithelial markers (4).

There are a number of experimental approaches able to reproduce EMT in vitro such as the forced expression of EMT-inducing transcription factors (5), transforming growth factor-β (TGFβ) treatment (6) or transfection with C35 (7). Trypsin-sensitive breast and colon cancer cells subpopulations also showed characteristic of EMT (8). Similarly, EMT-like phenotype can be increased by culturing cells on soft substrates or on ultra-low attachment plates (9, 10). These experimental manipulations artificially induced gene expression alterations and cellular phenotypes, which may not recapitulate the in vivo status of cells (11).

We have previously demonstrated that a subpopulation of adherent colon cancer cells spontaneously undergoes EMT and that this transition is stabilized by exosomes, since EMT cells, in an exosomes depleted environment, undergo the reverse process, MET (12). These findings demonstrate the possibility to study the inter-conversion between epithelial and mesenchymal states in vitro without any artificial experimental manipulation and in the absence of exogenous cues from the surrounding microenvironment. However, since the degree of the ability to undergo EMT may differ among tumors (13), in this study, we investigated whether EMT and MET variants and their associated traits, such as anoikis and therapy resistance, spontaneously emerge in the highly invasive mesenchymal-like breast cancer cells MDA-MB-231 and whether exosomes may be drivers of these transitions. Moreover, although previous reports described gene expression variation in experimentally induced EMT in vitro (14-16), to our knowledge, none sought to identify the dynamic gene expression changes leading to spontaneous acquisition of EMT/MET phenotypes.

Materials and Methods

Cell culture and suspension cells. MDA-MB-231 cells were maintained in DMEM (Invitrogen, Life technologies, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (Invitrogen), 100 U/ml penicillin-streptomycin, 1% l-glutamine (200 mmol/l), 4.5 g/l glucose and grown in 5% CO2. These cells are referred as basal cells. After 7 days post seeding, a number of MDA-MB-231 cells able to survive in suspension appeared in the culture medium; these cells that spontaneously found in suspension (referred as EMT cells) were harvested by 500xg centrifugation for 5 min and counted at different time points post seeding (48 h, 72 h, 96 h, 7 d, 10 d, 15 d).

Exosomes isolation. Exosomes were isolated from MDA-MB-231 culture media at day 7 post-seeding by using the Exosome Precipitation Solution (Macherey-Nagel, Düren, Germany).

Adherent colonies formation. To test the ability of EMT cells to form adherent colonies (referred as MET cells), 4×103 EMT cells collected at day 7 were seeded in 24-well plates and maintained for 72 h in DMEM or in DMEM containing 10% or 20% of exosomes isolated from basal cells culture media. MET cells were counted and cell viability was measured by trypan blue (Invitrogen).

Immunocytochemistry for E-cadherin and vimentin. Basal cells, as well as EMT and MET variants, were seeded on histological slides, fixed in 4% formaldehyde pH 7.4 for 10 min and pre-incubated in 0.5% triton and 1.5% bovine serum albumin (BSA) (Sigma Aldrich, Milan, Italy) for 15 min at RT. Immunostaining was performed by incubation for 24 h at 4°C with mouse monoclonal anti E-cadherin antibody at final dilution of 1:50 (Millipore, Burlington, MA, USA) or goat-polyclonal anti-Vimentin antibody at final dilution 1:40 (Sigma Aldrich) followed by Alexa Fluor 488 Goat anti-mouse (1:333) or Alexa Fluor 568 Donkey anti-Goat (1:333) antibodies (Invitrogen). Microscopic analysis was performed with a fluorescence microscope (Labophot-2, Nikon) connected to a CCD camera. Ten photomicrographs (~100 cells/microscopic field) were randomly taken for each sample and fluorescence was measured using ImageJ 1.33 image analysis software (http://rsb.info.nih.gov/ij). Results were expressed in arbitrary units.

Chemosensitivity assay. Differences in sensitivity among basal, EMT and MET cells exposed to doxorubicin (10−6 M), paclitaxel (10−6 M) or vincristine (10−6 M) for 72 h were assessed by MTS assay (Promega Corporation, Madison, WI, USA).

Reverse Transcription PCR. Total RNA was extracted by using the RNeasy Mini kit Plus (Macherey-Nagel) according to the manufacturer's protocol. For first-strand cDNA synthesis, 1 μg of total RNA from each sample was reverse-transcribed by using the RevertAid RT Kit (Thermo Fisher Scientific, Waltham, MA, USA). Primers were designed based on the human GenBank sequences. For each target gene, the relative amount of mRNA in the samples was calculated as the ratio of each gene to GAPDH mRNA (17).

Microarray experiments. To produce Cy3-labeled complementary RNA (cRNA), 550 ng of total RNA from the three cell clones, were labeled using the Agilent Quick Amp Labeling Kit (Agilent Technologies, Santa Clara, CA, USA) following the manufacturer's protocol. The Cy3-labeled samples were hybridized to Agilent Whole human genome 4X44K microarrays at 65°C for 18 h. Fluorescent signal intensities were detected using the Agilent Scan Control 7.0 Software on an Agilent DNA Microarray Scanner, at a resolution of 2 μm. Microarray analysis was performed on 3 independent biological replicates for each cell clone. Image analysis and initial quality control were performed using Agilent Feature Extraction Software v9.5. Values for control spots and spots that did not meet the quality criteria were flagged. Quality criteria included a minimal spot size, a median/mean ratio of at least 0.9 for each spot, non-saturated intensity for both channels, a signal well above background and a minimal signal intensity for at least one channel. Initial statistical analysis was performed using unpaired t-test considering Benjamini–Hochberg corrected p-value of 0.05. BRB-Array Tools 4.5.1 version was used to perform Statistical Analysis of Microarray (SAM), Gene set enrichment analysis (GSEA) and a two-way hierarchical clustering. Microarray data are stored into the Array Express database with accession number E-MTAB-6954.

Statistical analysis. Data were expressed as means±SEM of three independent experiments. Statistical analysis was performed by one-way analysis of variance, followed by the Student–Newman–Keuls multiple comparison post hoc test or by Mann–Whitney test. Calculations were done using a GraphPad Prism 4.0 (GraphPad software, San Diego, CA, USA).

Results

Behavioral characterization of suspension EMT cells and effect of exosomes secreted by basal cells on the reverse transition from EMT to MET. At 48 h post-seeding, a subpopulation of MDA-MB-231 basal cells detached the monolayer and spontaneously disseminated in the culture media. The number of cells growing in suspension significantly increased from the seventh to the fifteenth day post-seeding suggesting anoikis resistance and EMT like features (Figure 1A). When 4×103 suspension cells were collected and re-seeded in cell-free wells, they were able to adhere again and to form about 300 new adherent viable colonies suggesting the occurrence of MET.

When exosomes isolated from the culture medium of basal cells were added at a concentration of 10% or 20% to EMT cells, their ability to undergo MET in cell-free wells was significantly and dose dependently reduced compared to DMEM alone (Figure 1B).

Expression of the EMT hallmarks vimentin and E-cadherin. Adherent MDA-MB-231 cells (Basal), had high expression levels of E-cadherin and low expression of vimentin (Figure 2A and B). On the contrary, disseminated MDA-MB-231 (EMT) were E-cadherin low and vimentin high (Figure 2C and D). When the latter where re-seeded in cell-free wells, they reverted back to the epithelial state forming new adherent viable colonies (MET), that were E-cadherin high and vimentin low (Figure 2E and F); Figure 2G and H show the results of the densitometric analysis of E-cadherin and vimentin, respectively, in basal, EMT and MET cells. The gene expression of vimentin and E-cadherin recapitulated the results of immunocytochemistry with EMT cells displaying up-regulation of vimentin and down-regulation of E-cadherin compared to both adherent and MET cells (Table I).

Figure 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1.

Behavioral characterization of suspension EMT cells and effect of exosomes secreted by basal cells on the reverse transition from EMT to MET. A: Time-dependent increase in the number of viable MDA-MB-231 cells spontaneously growing in suspension. Data are expressed as means±SEM of 3 independent experiments. ***p<0.001 vs. 48 h. B: Number of adherent new colonies (MET cells) formed by EMT cells in DMEM alone or in the presence of 10% and 20% exosomes isolated from the culture medium of basal cells. ***p<0.001 vs. DMEM alone.

Chemosensitivity assay. In basal cells, the percentage of cell death was of 28 %, 38 % and 42% upon doxorubicin, paclitaxel and vincristine treatment, respectively. These percentages were dramatically reduced in EMT cells which were almost insensitive to all the three chemotherapeutic agents with percentages of cell death below 10 % (p<0.001). The chemosensitivity to doxorubicin was completely restored in MET cells whereas that to paclitaxel and vincristine was only partially reacquired compared to basal cells (Figure 3).

Whole-gene expression analysis and Gene Set Enrichment Analysis (GSEA). Transcriptomic analysis identified 223 differentially expressed genes between EMT cells and basal cells; among the genes that were up-regulated in EMT compared to basal cells are DTX1, ADH1A, BCAS1, FZD10 and ERBB3; beta 1 catenin (CTNNB1) was instead down-regulated. 219 genes were found differentially expressed by comparing EMT and MET cells: FTH1, was up-regulated in EMT compared to MET cells whereas DLL4 was down-regulated. PBOV, BMP7, RHOJ, ELA2B and ELA3B were all up-regulated in MET, and were among the 319 differentially expressed genes between MET and basal cells.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table I.

Expression of vimentin and E-cadherin, in basal, EMT and MET.

Unsupervised hierarchical clustering analysis was performed in order to evaluate the degree of changes in gene expression observed in EMT and MET cells compared to basal cells. The results are shown in the form of a tree whose branch lengths reflect the degree of similarities among the experimental groups; thus, similar expression profiles are closer to each other. This analysis distinguished the expression profiles of the three cell clones and in particular those of EMT cells compared to basal cells (Figure 4A).

Venn diagrams showed the degree of overlapping results in gene expression among different comparisons (Figure 4B). In particular, the expression of a single gene, the heath shock protein HSP90AA, emerged from all the three comparisons and was up-regulated in basal and EMT cells compared to MET. Interestingly, 7 genes whose expression regulation emerged from the comparison between basal and EMT and between EMT and MET were found. LGR5, SLC30A2 and COBL were overexpressed in EMT cells compared to basal and MET. Instead, CYTB, ADH5, ARL13B and ATP5B were highly expressed in basal and MET compared to EMT. When comparing MET cells to EMT and basal cells, 26 genes were differentially expressed: PBOV1 was up-regulated in EMT and MET cells compared to basal cells, FTH1 and SIRT3 were up-regulated in basal and EMT compared to MET cells, and ELA3B was up-regulated in MET compared to basal and EMT cells.

Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 2.

Expression of the EMT hallmarks vimentin and E-cadherin. Immunocytochemical evaluation of the expression of E-cadherin (A) and vimentin (B) in adherently growing MDA-MB-231 cells (Basal). Expression of E-cadherin (C) and vimentin (D) in MDA-MB-231 growing in suspension (EMT). Expression of E-cadherin (E) and vimentin (F) in adherent new colonies (MET) obtained by seeding disseminated MDA-MB-231 cells in cell-free wells (20x magnification; Barr 100 mm objective). Densitometric analysis of E-cadherin in Basal, EMT and MET cells (G). Densitometric analysis of vimentin in Basal, EMT and MET cells. **p<0.01 vs. Basal and MET cells (H).

In order to evaluate the biological processes characterizing the three cell clones, a Gene Set Enrichment Analysis (GSEA) was performed. This analysis measures the cumulative effect of small but consistent changes in gene expression within a biological pathway. Forty-six out of 136 KEGG pathways passed the 0.001 significance threshold. Table II shows the first 22 gene sets of the list. Among them, genes associated to the DNA replication (hsa03030), base excision repair (hsa03410) and TCA cycle (hsa00020) were mainly up-regulated in MET compared to basal and EMT cells (Figure 5). Other gene sets significantly enriched in EMT and MET cells were mTOR, NOD-like receptor signaling and several metabolic pathways.

Moreover, comparing each cell variant to the other ones, the Hedgehog signaling pathway found to be down-regulated in basal cells, became up-regulated in EMT and returned to a down-regulated state in MET. ABC transporters were mostly up-regulated in MET cells, drug metabolism-associated genes were overall down-regulated in basal cells, whereas both EMT and MET showed an up-regulation of this gene set. Notch was up-regulated in EMT cells compared to both basal and MET cells (Figure 6).

GSEA identified also 48 gene sets, computationally predicted to be targets of the same miRNA, that were differentially expressed in EMT, MET and basal cells (Table III). As an example, Figure 7, shows the heat maps with the list of genes predicted to be targets of miR-30b, miR-181a, and miR134.

Figure 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 3.

Chemosensitivity assay in basal, EMT and MET cells. Data are expressed as means±SEM of 3 independent experiments. ***p<0.001 vs. adherent MDA-MB-231.

Discussion

Metastasis is the major cause of treatment failure and death in breast cancer patients (18). For many years, EMT has been seen as an extreme phenotype, recapitulated in vitro with artificial manipulations which keep cells in a fixed state. However, there is evidence that, in vivo, cancer cells undergo a spectrum of intermediate states called metastable phenotypes in which cells retain some epithelial features but also acquire mesenchymal characteristics (19). These hybrid phenotypes that seem to be facilitated in collective cell migration, are associated with the acquisition of stem-like properties, chemoresistance and aggressiveness (20-21). These observations illustrate the importance of studying EMT in a non-experimentally manipulated setting (11). Moreover, most of the in vitro studies conducted so far, focused on EMT transition rather to its reverse process MET. Park et al. recently demonstrated that a long-term suspension of MDA-MB-468 cells resembled some features of human circulating tumor cells (10), but did not investigate their ability to overcome the EMT program, which is essential for metastatic colonization.

Figure 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 4.

Gene Expression Analysis. A: Hierarchical clustering of gene expression profiles of EMT, MET and basal cells. B: Venn diagram showing the number of differentially expressed genes in the three cell clones, the degree of overlap between the differentially expressed genes in the three comparisons; non-overlapping numbers specify the genes unique to each comparison.

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table II.

Top 22 KEGG gene sets found to be differentially modulated by comparing basal, EMT and MET cells.

In line with our previous results on HCT8 colon cancer cells, we demonstrated that EMT transition spontaneously occurs also in MDA-MB-231 cells, and that exosomes stabilize the EMT phenotype allowing anoikis resistance; when exosomes are removed, EMT cells revert back to the epithelial state, undergoing MET. In vivo, it is likely that a complex mix of signals, both from cancer cells and from the tumor microenvironment, contribute to these transitions: in the elegant paper from Chao and coworkers, MDA-MB-231 exhibited a reversion to an epithelial phenotype when cultured with hepatocytes, suggesting that micro environmental factors may modulate this switch (22). However, our results suggest that at least part of the plasticity of the EMT and MET phenotypes can be driven by exosomes, reinforcing the idea that by secreting exosomes, primary cancer cells try to preserve their own niche meanwhile endowing cells with migratory and invasive traits necessary to colonize other free niches (12).

View this table:
  • View inline
  • View popup
  • Download powerpoint
Table III.

Top 22 gene sets computationally predicted to be targets of the same miRNA, found to be differentially modulated by comparing basal, EMT and MET cells.

In addition, EMT cells are selectively advantaged through the acquisition of chemoresistance to doxorubicin, vincristine and paclitaxel, the most commonly used drugs for the therapy of breast cancer. Interestingly, upon the acquisition of the MET phenotype, the sensitivity to doxorubicin is completely re-acquired and that of vincristine and paclitaxel is significantly regained, but still reduced compared to parental cells.

Whole gene expression analysis showed that EMT and MET cells are molecularly distinct variants compared to adherent cells. Given the large number of genes differentially expressed, attention was paid on those expressed in an opposite manner almost in two out of the three cell clones, as it was hypothesized that metastasis-related genes are more likely to be oppositely expressed. A number of genes associated with metastatic activity and cancer stem cell traits were identified. Among those are the leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5), a stem cell marker in intestinal crypts and mammary glands (23) that promotes cell mobility, tumor formation and EMT in breast cancer cells by activating Wnt/β-catenin signaling (24), FZD10, a receptor for Wnt signalling, that is up-regulated in breast cancer and is a potential drug target (25), DTX1, a Notch interacting protein that is also associated with the proliferative, migratory and clonogenic potential of cancer cells (26) and elevated expression of ErbB3 resulting in paclitaxel resistance in breast cancer cells (27).

Among the most up-regulated genes in EMT cells compared to MET cells, was the FTH1 gene, a subunit of the ferritin complex, which is associated with the progression of breast cancer and with increased resistance to doxorubicin (28). DLL4 (Delta-like 4), a component of the Notch signaling pathway, has also been implicated in EMT and chemoresistance (29).

Figure 5.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 5.

Heat maps representing the three KEGG pathways pointed out by Gene Set Enrichment Analysis (GSEA) of MDA-MB-231 cells transcriptomic data: DNA replication (hsa03030), base excision repair (hsa03410) and TCA cycle (hsa00020). Up-regulated genes are shown in dark blue, down-regulated genes in light blue color.

The unique gene significantly modulated in the three cell variants was HSP90AA1, a member of the HSP90 family whose expression is an independent risk factor of death from metastatic breast cancer in TNBC (30) and it is associated to chemoresistance (31). Pharmacological inhibitors of HSP90 in breast cancer treatment are under investigation in clinical trials (32).

An alternative approach to the analysis of single gene expression variations, is GSEA analysis, where a group of related genes from the same pathway is examined instead of groups of potentially unrelated genes. This approach has the advantage of taking into account the cooperative nature of genes and of considering that genes involved in the same process are often regulated together. Among the gene sets found to be differentially expressed among the three cell variants the DNA replication end Base Excision Repair was found; most of the genes listed in these pathways were in fact up-regulated in MET cells, suggesting that both mechanisms might be involved in cell survival and chemoresistance after re-adhesion. TCA cycle, mTOR, NOD-like receptor signaling and several metabolic gene sets were also enriched in EMT and MET cells. Hedgehog signaling pathways were clearly down-regulated in basal cells, became up-regulated in EMT cells and returned to a down-regulated state in MET cells. A similar trend was observed for Notch pathway; interestingly, both contribute to the maintenance of stem-like properties and favor chemoresistance and metastasis (33). ABC transporters and drug metabolism pathways were activated in MET cells and in both EMT and MET cells respectively, suggesting their potential role in the acquisition of chemoresistance. GSEA also identified several gene sets predicted to be targets of the same miRNA; the most differentially expressed gene set was that associate with the miR-30d recently recognized as a mediator of invasion, migration and EMT in breast cancer (34).

Figure 6.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 6.

Heat maps representing KEGG pathways pointed out by Gene Set Enrichment Analysis (GSEA) of MDA-MB-231 cells transcriptomic data. Up-regulated genes are shown in dark blue, down-regulated genes in light blue color.

In conclusion, evidence was provided indicating that a dynamic gene expression reprogramming during EMT-MET takes place in vitro without any experimental manipulation and that it is associated to the acquisition of chemoresistance and metastatic traits. This model is useful for studying EMT and MET transitions, drug targets and the role of tumor-derived exosomes in breast cancer.

Figure 7.
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 7.

Heat maps representing the gene sets predicted to be targets of miR-30d, miR-181a and miR-134. Up-regulated genes are shown in dark blue, down-regulated genes in light blue color.

Acknowledgements

This work was supported by the Ministry of Education, University and Research (MIUR) under the Grant FIRB 2012 code RBFR12SOQ1: “Optimization of oncology therapy: novel drugs affecting multidrug resistance” and by AIRC (Associazione Italiana per la Ricerca sul Cancro) under REGIONAL GRANT 2005.

Footnotes

  • ↵* These Authors contributed equally to this study.

  • Authors' Contributions

    EB and LC conceived and designed the project. CL designed and performed microarray experiments and supervised the project; LC and MD performed cell cultures and carried out immunocytochemistry; EB and CL performed microarray analysis and interpretation; EB and CL wrote the manuscript. All authors read and approved the final version of the manuscript.

  • This article is freely accessible online.

  • Conflicts of Interest

    The Authors report no conflict of interest regarding this study.

  • Received February 26, 2019.
  • Revision received March 18, 2019.
  • Accepted March 19, 2019.
  • Copyright© 2019, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved

References

  1. ↵
    1. Tomaskovic-Crook E,
    2. Thompson EW,
    3. Thiery JP
    : Epithelial to mesenchymal transition and breast cancer. Breast Cancer Res 11(6): 213, 2009. PMID: 19909494. DOI: 10.1186/bcr2416
    OpenUrlCrossRefPubMed
  2. ↵
    1. Nieto MA
    : Epithelial plasticity: a common theme in embryonic and cancer cells. Science 342(6159): 1234850, 2013. PMID: 24202173. DOI: 10.1126/science.1234850
    OpenUrlAbstract/FREE Full Text
  3. ↵
    1. Yeung KT,
    2. Yang J
    : Epithelial-mesenchymal transition in tumor metastasis. Mol Oncol 11(1): 28-39, 2017. PMID: 28085222. DOI: 10.1002/1878-0261.12017
    OpenUrlCrossRefPubMed
  4. ↵
    1. Yao D,
    2. Dai C,
    3. Peng S
    : Mechanism of the mesenchymal-epithelial transition and its relationship with metastatic tumor formation. Mol Cancer Res 9(12): 1608-1620, 2011. PMID: 21840933. DOI: 10.1158/1541-7786.MCR-10-0568
    OpenUrlAbstract/FREE Full Text
  5. ↵
    1. Morel AP,
    2. Hinkal GW,
    3. Thomas C,
    4. Fauvet F,
    5. Courtois-Cox S,
    6. Wierinckx A,
    7. Devouassoux-Shisheboran M,
    8. Treilleux I,
    9. Tissier A,
    10. Gras B,
    11. Pourchet J,
    12. Puisieux I,
    13. Browne GJ,
    14. Spicer DB,
    15. Lachuer J,
    16. Ansieau S,
    17. Puisieux A
    : EMT inducers catalyze malignant transformation of mammary epithelial cells and drive tumorigenesis towards claudin-low tumors in transgenic mice. PLoS Genet 8(5): e1002723, 2012. PMID: 22654675. DOI: 10.1371/journal.pgen.1002723
    OpenUrlCrossRefPubMed
  6. ↵
    1. Pinho SS,
    2. Oliveira P,
    3. Cabral J,
    4. Carvalho S,
    5. Huntsman D,
    6. Gärtner F,
    7. Seruca R,
    8. Reis CA,
    9. Oliveira C
    : Loss and recovery of Mgat3 and GnT-III Mediated E-cadherin N-glycosylation is a mechanism involved in epithelial-mesenchymal-epithelial transitions. PLoS One 7(3): e33191, 2012. PMID: 22427986. DOI: 10.1371/journal.pone.0033191
    OpenUrlCrossRefPubMed
  7. ↵
    1. Katz E,
    2. Dubois-Marshall S,
    3. Sims AH,
    4. Gautier P,
    5. Caldwell H,
    6. Meehan RR,
    7. Harrison DJ
    : An in vitro model that recapitulates the epithelial to mesenchymal transition (EMT) in human breast cancer. PLoS One 6(2): e17083, 2011. PMID: 21347235. DOI: 10.1371/journal.pone.0017083
    OpenUrlCrossRefPubMed
  8. ↵
    1. Morata-Tarifa C,
    2. Jiménez G,
    3. García MA,
    4. Entrena JM,
    5. Griñán-Lisón C,
    6. Aguilera M,
    7. Picon-Ruiz M,
    8. Marchal JA
    : Low adherent cancer cell subpopulations are enriched in tumorigenic and metastatic epithelial-to-mesenchymal transition-induced cancer stem-like cells. Sci Rep 6: 18772, 2016. PMID: 26752044. DOI: 10.1038/srep18772
    OpenUrlCrossRef
  9. ↵
    1. Tang X,
    2. Kuhlenschmidt TB,
    3. Li Q,
    4. Ali S,
    5. Lezmi S,
    6. Chen H,
    7. Pires-Alves M,
    8. Laegreid WW,
    9. Saif TA,
    10. Kuhlenschmidt MS
    : A mechanically-induced colon cancer cell population shows increased metastatic potential. Mol Cancer 13: 131, 2014. PMID: 24884630. DOI: 10.1186/1476-4598-13-131
    OpenUrlCrossRef
  10. ↵
    1. Park JY,
    2. Jeong AL,
    3. Joo HJ,
    4. Han S,
    5. Kim SH,
    6. Kim HY,
    7. Lim JS,
    8. Lee MS,
    9. Choi HK,
    10. Yang Y
    : Development of suspension cell culture model to mimic circulating tumor cells. Oncotarget 9(1): 622-640, 2017. PMID: 29416640. DOI: 10.18632/oncotarget. 23079
    OpenUrl
  11. ↵
    1. Beerling E,
    2. Seinstra D,
    3. de Wit E,
    4. Kester L,
    5. van der Velden D,
    6. Maynard C,
    7. Schäfer R,
    8. van Diest P,
    9. Voest E,
    10. van Oudenaarden A,
    11. Vrisekoop N,
    12. van Rheenen J
    : Plasticity between epithelial and mesenchymal states unlinks EMT from metastasis-enhancing stem cell capacity. Cell Rep 14(10): 2281-2288, 2016. PMID: 26947068. DOI: 10.1016/j.celrep.2016.02.034
    OpenUrlCrossRef
  12. ↵
    1. Bigagli E,
    2. Luceri C,
    3. Guasti D,
    4. Cinci L
    : Exosomes secreted from human colon cancer cells influence the adhesion of neighboring metastatic cells: Role of microRNA-210. Cancer Biol Ther 11: 1-8, 2016. PMID: 27611932.
    OpenUrl
  13. ↵
    1. Nieto MA,
    2. Huang RY,
    3. Jackson RA,
    4. Thiery JP
    : EMT: 2016. Cell 166(1): 21-45, 2016. PubMed PMID: 27368099. DOI: 10.1016/j.cell.2016.06.028
    OpenUrlCrossRefPubMed
  14. ↵
    1. Mani SA,
    2. Guo W,
    3. Liao MJ,
    4. Eaton EN,
    5. Ayyanan A,
    6. Zhou AY,
    7. Brooks M,
    8. Reinhard F,
    9. Zhang CC,
    10. Shipitsin M,
    11. Campbell LL,
    12. Polyak K,
    13. Brisken C,
    14. Yang J,
    15. Weinberg RA
    : The epithelial–mesenchymal transition generates cells with properties of stem cells. Cell 133(4): 704-715, 2008. PMID:18485877. DOI: 10.1016/j.cell.2008.03.027
    OpenUrlCrossRefPubMed
    1. Minafra L,
    2. Bravatà V,
    3. Forte GI,
    4. Cammarata FP,
    5. Gilardi MC,
    6. Messa C
    : Gene expression profiling of epithelial-mesenchymal transition in primary breast cancer cell culture. Anticancer Res 34(5): 2173-2183, 2014. PMID: 24778019.
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Chu IM,
    2. Michalowski AM,
    3. Hoenerhoff M,
    4. Szauter KM,
    5. Luger D,
    6. Sato M,
    7. Flanders K,
    8. Oshima A,
    9. Csiszar K,
    10. Green JE
    : GATA3 inhibits lysyl oxidase-mediated metastases of human basal triple-negative breast cancer cells. Oncogene 31(16): 2017-2027, 2012. PMID: 21892208. DOI: 10.1038/onc.2011.382
    OpenUrlCrossRefPubMed
  16. ↵
    1. Bigagli E,
    2. Cinci L,
    3. Paccosi S,
    4. Parenti A,
    5. D'Ambrosio M,
    6. Luceri C
    : Nutritionally relevant concentrations of resveratrol and hydroxytyrosol mitigate oxidative burst of human granulocytes and monocytes and the production of pro-inflammatory mediators in LPS-stimulated RAW 264.7 macrophages. Int Immunopharmacol 43: 147-155, 2017. PMID: 27998828. DOI: 10.1016/j.intimp.2016.12.012
    OpenUrl
  17. ↵
    1. Scully OJ,
    2. Bay BH,
    3. Yip G,
    4. Yu Y
    : Breast cancer metastasis. Cancer Genomics Proteomics 9(5): 311-320, 2012. PMID: 22990110.
    OpenUrlAbstract/FREE Full Text
  18. ↵
    1. Jolly MK,
    2. Somarelli JA,
    3. Sheth M,
    4. Biddle A,
    5. Tripathi SC,
    6. Armstrong AJ,
    7. Hanash SM,
    8. Bapat SA,
    9. Rangarajan A,
    10. Levine H
    : Hybrid epithelial/mesenchymal phenotypes promote metastasis and therapy resistance across carcinomas. Pharmacol Ther 194: 161-184, 2019. PMID: 30268772. DOI: 10.1016/ j.pharmthera.2018.09.007
    OpenUrl
  19. ↵
    1. Lee JM,
    2. Dedhar S,
    3. Kalluri R,
    4. Thompson EW
    : The epithelial-mesenchymal transition: new insights in signaling, development, and disease. J Cell Biol 172(7): 973-981, 2006. PMID: 16567498. DOI: 10.1083/jcb.200601018
    OpenUrlAbstract/FREE Full Text
  20. ↵
    1. Ribeiro AS,
    2. Paredes J
    : P-cadherin linking breast cancer stem cells and invasion: A promising marker to identify an “Intermediate/Metastable” EMT state. Front Oncol 4: 371, 2015. PMID: 25601904. DOI: 10.3389/fonc.2014.00371
    OpenUrlCrossRefPubMed
  21. ↵
    1. Chao YL,
    2. Shepard CR,
    3. Wells A
    : Breast carcinoma cells re-express E-cadherin during mesenchymal to epithelial reverting transition. Mol Cancer 9: 179, 2010. PMID:20609236. DOI: 10.1186/1476-4598-9-179
    OpenUrlCrossRefPubMed
  22. ↵
    1. Trejo CL,
    2. Luna G,
    3. Dravis C,
    4. Spike BT,
    5. Wahl GM
    : Lgr5 is a marker for fetal mammary stem cells, but is not essential for stem cell activity or tumorigenesis. NPJ Breast Cancer 3: 16, 2017. PMID: 28649656. DOI: 10.1038/s41523-017-0018-6
    OpenUrl
  23. ↵
    1. Yang L,
    2. Tang H,
    3. Kong Y,
    4. Xie X,
    5. Chen J,
    6. Song C,
    7. Liu X,
    8. Ye F,
    9. Li N,
    10. Wang N,
    11. Xie X
    : LGR5 promotes breast cancer progression and maintains stem-like cells through activation of Wnt/β-catenin signaling. Stem Cells 33(10): 2913-2924, 2015. PMID: 26086949. DOI: 10.1002/stem.2083
    OpenUrlCrossRefPubMed
  24. ↵
    1. Katoh M,
    2. Katoh M
    : Molecular genetics and targeted therapy of WNT-related human diseases. Int J Mol Med 40(3): 587-606, 2017. PMID: 28731148. DOI: 10.3892/ijmm.2017.3071
    OpenUrlCrossRef
  25. ↵
    1. Huber RM,
    2. Rajski M,
    3. Sivasankaran B,
    4. Moncayo G,
    5. Hemmings BA,
    6. Merlo A
    : Deltex-1 activates mitotic signaling and proliferation and increases the clonogenic and invasive potential of U373 and LN18 glioblastoma cells and correlates with patient survival. PLoS One 8(2): e57793, 2013. PMID:23451269. DOI: 10.1371/journal.pone.0057793
    OpenUrlCrossRefPubMed
  26. ↵
    1. Chen J,
    2. Ren Q,
    3. Cai Y,
    4. Lin T,
    5. Zuo W,
    6. Wang J,
    7. Lin R,
    8. Zhu L,
    9. Wang P,
    10. Dong H,
    11. Zhao H,
    12. Huang L,
    13. Fu Y,
    14. Yang S,
    15. Tan J,
    16. Lan X,
    17. Wang S
    : Mesenchymal stem cells drive paclitaxel resistance in ErbB2/ErbB3-coexpressing breast cancer cells via paracrine of neuregulin 1. Biochem Biophys Res Commun 501(1): 212-219, 2018. PMID: 29715459. DOI: 10.1016/j.bbrc.2018.04.218.
    OpenUrl
  27. ↵
    1. Shpyleva SI,
    2. Tryndyak VP,
    3. Kovalchuk O,
    4. Starlard-Davenport A,
    5. Chekhun VF,
    6. Beland FA,
    7. Pogribny IP
    : Role of ferritin alterations in human breast cancer cells. Breast Cancer Res Treat 126(1): 63-71, 2011. PMID: 20390345. DOI: 10.1007/s10549-010-0849-4
    OpenUrlCrossRefPubMed
  28. ↵
    1. Kang M,
    2. Jiang B,
    3. Xu B,
    4. Lu W,
    5. Guo Q,
    6. Xie Q,
    7. Zhang B,
    8. Dong X,
    9. Chen D,
    10. Wu Y
    : Delta like ligand 4 induces impaired chemo-drug delivery and enhanced chemoresistance in pancreatic cancer. Cancer Lett 330(1): 11-21, 2013. PMID: 23200678. DOI: 10.1016/j.canlet.2012.11.015
    OpenUrlCrossRefPubMed
  29. ↵
    1. Cheng Q,
    2. Chang JT,
    3. Geradts J,
    4. Neckers LM,
    5. Haystead T,
    6. Spector NL,
    7. Lyerly HK
    : Amplification and high-level expression of heat shock protein 90 marks aggressive phenotypes of human epidermal growth factor receptor 2 negative breast cancer. Breast Cancer Res 14(2): R62, 2012. PMID: 22510516. DOI: 10.1186/bcr3168
    OpenUrlCrossRefPubMed
  30. ↵
    1. Jarzab M,
    2. Kowal M,
    3. Bal W,
    4. Oczko-Wojciechowska M,
    5. Rembak-Szynkiewicz J,
    6. Kowalska M,
    7. Stobiecka E,
    8. Chmielik E,
    9. Tyszkiewicz T,
    10. Kaszuba M,
    11. Nowicka E,
    12. Lange B,
    13. Czarniecka A,
    14. Krajewska J,
    15. Dyla A,
    16. Dobrut M,
    17. Lange D,
    18. Jarzab B,
    19. Bobek-Billewicz B,
    20. Tarnawski R
    : Ratio of proliferation markers and HSP90 gene expression as a predictor of pathological complete response in breast cancer neoadjuvant chemotherapy. Folia Histochem Cytobiol 54(4): 202-209, 2016. PMID: 28051275. DOI: 10.5603/FHC.a2016.0026
    OpenUrl
  31. ↵
    1. Zagouri F,
    2. Sergentanis TN,
    3. Chrysikos D,
    4. Papadimitriou CA,
    5. Dimopoulos MA,
    6. Psaltopoulou T
    : Hsp90 inhibitors in breast cancer: a systematic review. Breast 22(5): 569-578, 2013. PMID: 23870456. DOI: 10.1016/j.breast.2013.06.003
    OpenUrlCrossRefPubMed
  32. ↵
    1. Jamdade VS,
    2. Sethi N,
    3. Mundhe NA,
    4. Kumar P,
    5. Lahkar M,
    6. Sinha N
    . Therapeutic targets of triple-negative breast cancer: a review. Br J Pharmacol 172(17): 4228-4237, 2015. PMID: 26040571. DOI: 10.1111/bph.13211
    OpenUrlPubMed
  33. ↵
    1. Han M,
    2. Wang Y,
    3. Guo G,
    4. Li L,
    5. Dou D,
    6. Ge X,
    7. Lv P,
    8. Wang F,
    9. Gu Y
    : microRNA-30d mediated breast cancer invasion, migration, and EMT by targeting KLF11 and activating STAT3 pathway. J Cell Biochem 119(10): 8138-8145, 2018. PMID: 29923255. DOI: 10.1002/jcb.26767
    OpenUrl
PreviousNext
Back to top

In this issue

Cancer Genomics - Proteomics: 16 (3)
Cancer Genomics & Proteomics
Vol. 16, Issue 3
May-June 2019
  • Table of Contents
  • Table of Contents (PDF)
  • Index by author
  • Back Matter (PDF)
  • Ed Board (PDF)
  • Front Matter (PDF)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Cancer Genomics & Proteomics.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Transcriptomic Characterization, Chemosensitivity and Regulatory Effects of Exosomes in Spontaneous EMT/MET Transitions of Breast Cancer Cells
(Your Name) has sent you a message from Cancer Genomics & Proteomics
(Your Name) thought you would like to see the Cancer Genomics & Proteomics web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
1 + 13 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Transcriptomic Characterization, Chemosensitivity and Regulatory Effects of Exosomes in Spontaneous EMT/MET Transitions of Breast Cancer Cells
ELISABETTA BIGAGLI, LORENZO CINCI, MARIO D'AMBROSIO, CRISTINA LUCERI
Cancer Genomics & Proteomics May 2019, 16 (3) 163-173; DOI: 10.21873/cgp.20122

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Reprints and Permissions
Share
Transcriptomic Characterization, Chemosensitivity and Regulatory Effects of Exosomes in Spontaneous EMT/MET Transitions of Breast Cancer Cells
ELISABETTA BIGAGLI, LORENZO CINCI, MARIO D'AMBROSIO, CRISTINA LUCERI
Cancer Genomics & Proteomics May 2019, 16 (3) 163-173; DOI: 10.21873/cgp.20122
del.icio.us logo Digg logo Reddit logo Twitter logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Materials and Methods
    • Results
    • Discussion
    • Acknowledgements
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • No citing articles found.
  • Google Scholar

Similar Articles

Keywords

  • breast cancer
  • epithelial–mesenchymal transition (EMT)
  • mesenchymal–epithelial transition (MET)
  • metastasis
  • chemoresistance
  • exosomes
Cancer & Genome Proteomics

© 2022 Cancer Genomics & Proteomics

Powered by HighWire