Circulating Breast Tumor Cells Exhibit Dynamic Changes in Epithelial and Mesenchymal Composition.
ABSTRACT Epithelial-mesenchymal transition (EMT) of adherent epithelial cells to a migratory mesenchymal state has been implicated in tumor metastasis in preclinical models. To investigate its role in human cancer, we characterized EMT in circulating tumor cells (CTCs) from breast cancer patients. Rare primary tumor cells simultaneously expressed mesenchymal and epithelial markers, but mesenchymal cells were highly enriched in CTCs. Serial CTC monitoring in 11 patients suggested an association of mesenchymal CTCs with disease progression. In an index patient, reversible shifts between these cell fates accompanied each cycle of response to therapy and disease progression. Mesenchymal CTCs occurred as both single cells and multicellular clusters, expressing known EMT regulators, including transforming growth factor (TGF)-β pathway components and the FOXC1 transcription factor. These data support a role for EMT in the blood-borne dissemination of human breast cancer.
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ABSTRACT: Background Many current therapies for metastatic castration-resistant prostate cancer (mCRPC) are aimed at AR signaling; however, resistance to these therapies is inevitable. To personalize CRPC therapy in an individual with clinical progression despite maximal AR signaling blockade, it is important to characterize the status of AR activity within their cancer. Biopsies of bone metastases are invasive and frequently fail to yield sufficient tissue for further study. Evaluation of circulating tumor cells (CTCs) offers an alternative, minimally invasive mechanism to characterize and study late-stage disease. The goal of this study was to evaluate the utility of CTC interrogation with respect to the AR as a potential novel therapeutic biomarker in patients with mCRPC.Methods Fifteen mL of whole blood was collected from patients with progressive, metastatic mCRPC, the mononuclear cell portion was isolated, and fluorescence-activated cell sorting (FACS) was used to isolate and evaluate CTCs. A novel protocol was optimized to use ImageStreamX to quantitatively analyze AR expression and subcellular localization within CTCs. Co-expression of AR and the proliferation marker Ki67 was also determined using ImageStreamX.ResultsWe found inter-patient and intra-patient heterogeneity in expression and localization of AR. Increased AR expression and nuclear localization are associated with elevated co-expression of Ki-67, consistent with the continued role for AR in castration-resistant disease. Despite intra-patient heterogeneity, CTCs from patients with prior exposure to abiraterone had increased AR expression compared to CTCs from patients who were abiraterone-naïve.Conclusions As our toolbox for targeting AR function expands, our ability to evaluate AR expression and function within tumor samples from patients with late-stage disease will likely be a critical component of the personalized management of advanced prostate cancer. AR expression and nuclear localization varies within patients and between patients; however it remains associated with markers of proliferation. This supports a molecularly diverse AR-centric pathobiology imparting castration-resistance.Journal of translational medicine. 11/2014; 12(1):313.
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ABSTRACT: INTRODUCTION: Incisional biopsies, including the diagnostic core needle biopsy (CNB), routinely performed before surgical excision of breast cancer tumors are hypothesized to increase the risk of metastatic disease. In this study, we experimentally determined whether CNB of breast cancer tumors results in increased distant metastases and examine important resultant changes in the primary tumor and tumor microenvironment associated with this outcome. METHOD: To evaluate the effect of CNB on metastasis development, we implanted murine mammary 4T1 tumor cells in BALB/c mice and performed CNB on palpable tumors in half the mice. Subsequently, emulating the human scenario, all mice underwent complete tumor excision and were allowed to recover, with attendant metastasis development. Tumor growth, lung metastasis, circulating tumor cell (CTC) levels, variation in gene expression, composition of the tumor microenvironment, and changes in immunologic markers were compared in biopsied and non-biopsied mice. RESULTS: Mice with biopsied tumors developed significantly more lung metastases compared to non-biopsied mice. Tumors from biopsied mice contained a higher frequency of myeloid-derived suppressor cells (MDSCs) accompanied by reduced CD4 + T cells, CD8 + T cells, and macrophages, suggesting biopsy-mediated development of an increasingly immunosuppressive tumor microenvironment. We also observed a CNB-dependent up-regulation in the expression of SOX4, Ezh2, and other key epithelial-mesenchymal transition (EMT) genes, as well as increased CTC levels among the biopsy group. CONCLUSION: CNB creates an immunosuppressive tumor microenvironment, increases EMT, and facilitates release of CTCs, all of which likely contribute to the observed increase in development of distant metastases.Neoplasia (New York, N.Y.) 11/2014; · 5.48 Impact Factor
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ABSTRACT: Circulating tumor cells (CTCs) are prognostic in all stages of breast cancer. However, since they are extremely rare, little is known about the molecular nature of these cells. We report a novel strategy for the isolation and expression profiling of pure populations of CTCs derived from peripheral blood. We developed a method to isolate CTCs based on immunomagnetic capture followed by fluorescence-activated cell sorting (IE/FACS). After assay validation using the BT474 cell line spiked into blood samples in vitro, RNA from CTCs isolated from the blood of five metastatic breast cancer (MBC) patients was linearly amplified and subjected to gene expression profiling via cDNA microarrays. We isolated a range of 9-993 captured CTCs from five MBC patients' blood and profiled their RNA in comparison to a diverse panel of primary breast tumors (n = 55). Unsupervised hierarchical clustering revealed that CTC profiles clustered with more aggressive subtypes of primary breast tumors and were readily distinguishable from peripheral blood (PB) and normal epithelium. Differential expression analysis revealed CTCs to have downregulated apoptosis, and they were distinguishable from PB by the relative absence of immune-related signals. As expected, CTCs from MBC had significantly higher risk of recurrence scores than primary tumors (p = 0.0073). This study demonstrates that it is feasible to isolate CTCs from PB with high purity through IE/FACS and profile them via gene expression analysis. Our approach may inform the discovery of therapeutic predictors and be useful for real-time identification of emerging resistance mechanisms in MBC patients.Breast Cancer Research and Treatment 11/2014; · 4.47 Impact Factor
, 580 (2013);
et al.Min Yu
and Mesenchymal Composition
Circulating Breast Tumor Cells Exhibit Dynamic Changes in Epithelial
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Circulating Breast Tumor Cells
Exhibit Dynamic Changes in Epithelial
and Mesenchymal Composition
Min Yu,1,6* Aditya Bardia,1,3* Ben S. Wittner,1Shannon L. Stott,1,2Malgorzata E. Smas,1
David T. Ting,1Steven J. Isakoff,1,3Jordan C. Ciciliano,1Marissa N. Wells,1Ajay M. Shah,2
Kyle F. Concannon,1Maria C. Donaldson,1Lecia V. Sequist,1,3Elena Brachtel,1,4
Dennis Sgroi,1,4Jose Baselga,1,3Sridhar Ramaswamy,1,3Mehmet Toner,2,5
Daniel A. Haber,1,3,6† Shyamala Maheswaran1,5†
Epithelial-mesenchymal transition (EMT) of adherent epithelial cells to a migratory mesenchymal
state has been implicated in tumor metastasis in preclinical models. To investigate its role in
human cancer, we characterized EMT in circulating tumor cells (CTCs) from breast cancer patients.
Rare primary tumor cells simultaneously expressed mesenchymal and epithelial markers, but
mesenchymal cells were highly enriched in CTCs. Serial CTC monitoring in 11 patients suggested an
association of mesenchymal CTCs with disease progression. In an index patient, reversible shifts
between these cell fates accompanied each cycle of response to therapy and disease progression.
Mesenchymal CTCs occurred as both single cells and multicellular clusters, expressing known EMT
regulators, including transforming growth factor (TGF)–b pathway components and the FOXC1
transcription factor. These data support a role for EMT in the blood-borne dissemination of
human breast cancer.
the blood to new organ sites (1). Aberrant acti-
vation of epithelial-mesenchymal transition (EMT)
has been implicated in this process, based on
ost cancer-related deaths are caused by
metastasis, the dissemination of cancer
cells from the primary tumor through
studies with human cancer cell lines and mouse
models (2, 3). Immunohistochemical approaches
to identify EMT in tumors is complicated by the
presence of reactive mesenchymal stromal cells
(4,5),and analysis of circulating tumor cells (CTCs)
has been hampered by reliance on epithelial markers
to separate cancer cells from surrounding hema-
topoietic cells of mesenchymal origin (6, 7). To
address these technical challenges, we optimized
microfluidic capture of CTCs with epithelial- and
tumor-specific antibodies, and we then used this
technology to analyze EMT in CTCs from breast
We established a quantifiable, dual-colorimetric
RNA–in situ hybridization (ISH) assay to exam-
ine tumor cells for expression of seven pooled
epithelial (E) transcripts [keratins (KRT) 5, 7, 8,
18, and 19; EpCAM (epithelial cell adhesion
molecule); and CDH1 (cadherin 1)] and three
mesenchymal (M) transcripts [FN1 (fibronectin
1), CDH2 (cadherin 2), and SERPINE1/PAI1
(serpin peptidase inhibitor, clade E)]. These probes
were validated in cell lines to confirm differen-
tial expression in epithelial versus mesenchymal
cancer cells and the absence of expression in
blood cells that contaminate CTC preparations
(table S1 and fig. S1A). After validating the
1Massachusetts General Hospital Cancer Center, Harvard Med-
ical School, Charlestown, MA 02129, USA.2Center for Bioengi-
neering in Medicine, Harvard Medical School, Charlestown,
MA 02129, USA.3Department of Medicine, Harvard Medical
School, Charlestown, MA 02129, USA.4Department of Pathol-
ogy, Harvard Medical School, Charlestown, MA 02129, USA.
5Department of Surgery, Harvard Medical School, Charlestown,
MA 02129, USA.6Howard Hughes Medical Institute, Chevy
Chase, MD 20815, USA.
*These authors contributed equally to this work.
†To whom correspondence should be addressed. E-mail:
firstname.lastname@example.org (D.A.H.); maheswaran@helix.
E/M dual positive (%)
Fig. 1. RNA-ISH analysis of EMT markers in human breast tumors. Representa-
tive RNA-ISH analysis of pooled epithelial (E) (red dots, arrowheads) and
mesenchymal (M) (dark blue dots, arrows) markers in (A) primary tumor and
(B) tumor-infiltrated lymph node of a patient with ductal ER+/PR+type breast
cancer. (C) RNA-ISH analysis of HER2 (red dots, arrowheads) and M (dark blue dots, arrows) expression in a HER2+primary breast tumor. (D) Quantitation of
E and M dual-positive tumor cells (percentage of total tumor cells) in a TMA consisting of premalignant DCIS (N = 7 cases) and ER+/PR+(N = 20 cases), HER2+
(N = 9 cases), and TN (N = 16 cases) breast cancers. A representative image from a TN case is shown on the right. E, red dots; M, dark blue dots; nuclei are
stained with hematoxylin, light blue. Scale bars: (A) to (D), 20 mm; inserts, 10 mm.
1 FEBRUARY 2013VOL 339
on March 22, 2013
E/M RNA-ISH analysis in mouse xenografts of
epithelial or mesenchymal breast cancer cells
(fig. S1B), we applied the assays to primary hu-
man breast cancer specimens.
Among the majority of E+cancer cells, and
distinct from the M+stromal cells, we detected a
small number of biphenotypic E+/M+cells with
clear epithelial histology, both in primary tumors
and in draining lymph nodes (Fig. 1, A and B).
Dual–RNA-ISH staining for M markers and a
tumor-specific marker (HER2) confirmed the
identity of such mesenchymal cells as tumor-
derived (Fig. 1C). We scored tissue microarrays
(TMAs) containing multiple primary breast can-
cers of various histological subtypes for the num-
ber of dual E+/M+cells. Using this assay, we found
that benign breast tissue (N = 6 cases) and tu-
mor cells in pre-invasive ductal carcinoma in situ
(DCIS) lesions (N = 7 cases) were exclusively
epithelial, whereas reactive stromal cells were
exclusively mesenchymal. In contrast, we found
that all three major histological subtypes of in-
vasive breast cancer contained rare tumor cells
with epithelial morphology that stained with both
E and M markers: ER/PR+subtype (mean = 3.3%,
range 0 to 10%, N = 20 cases); HER2+subtype
(mean = 2.7%, range 0 to 10%, N = 9 cases); and
the triple negative (TN) (ER–/PR–/HER2–) sub-
type (mean = 12.1%, range 0 to 45%, N = 16 cases)
(Fig. 1D). The higher number of M+tumor cells
in primary TN breast cancer is consistent with
this type of breast cancer being enriched for mes-
enchymal markers, including vimentin (8, 9).
Some TN cases contained clusters of cells in the
middle of the tumor mass that were strongly pos-
itive for both E and M markers, yet were histo-
logically indistinguishable from the neighboring
E+tumor cells (Fig. 1D). Thus, human primary
breast tumors contain rare cancer cells that co-
express mesenchymal and epithelial markers.
To extend our EMT analysis to CTCs, we
used the microfluidic HB (herringbone)–chip (10)
to capture CTCs from blood with an antibody
cocktail directed against EpCAM, EGFR (epi-
thelial growth factor receptor), and HER2 (human
epithelial growth factor receptor 2) (fig. S2). Hu-
man breast cancer cell lines exhibiting epithelial
(MCF7 and SKBR3) and mesenchymal (MDA-
MB-231) characteristics were spiked into blood
and captured on the triple-antibody cocktail-coated
CTC-chip to ensure capture efficiencies of 80 to
90%. MCF10A cells expressing the EMT-inducing
transcription factor LBX1 (11) were used to op-
timize the quantitative immunofluorescence–based
Fig. 2. RNA-ISH analysis of EMT markers in CTCs
from patients with metastatic breast cancer. (A)
Representative images of five types of CTCs iso-
lated from patients with metastatic breast cancer,
based on RNA-ISH staining of E (green dots) and M
(red dots) markers. Scale bar, 5 mm (B) Quantita-
tion of EMT features in CTCs based on E and M
RNA-ISH staining of histological subtypes of breast
cancer [lobular, ductal, and U (unknown)], along
with molecular classification (ER/PR, HER2, TN).
CTC numbers per 3 ml of blood based on RNA (E+M)
or protein (CK) staining are listed below. (C) Frac-
tionation of CTCs according to E/M ratios in five
patients who were clinically responding to treat-
ment (top) and five patients who had progressive
disease on treatment (bottom). The subtype of breast
cancer, each patient’s treatment regimen, and the
number of days on treatment are shown. The drugs
used to inhibit the signaling pathways shown on the
figure are as follows: MET + VEGF (vascular endothe-
lial growth factor), cabozantinib; AI (aromatase inhib-
itor), letrozole; PI3K (phosphatidylinositol 3-kinase),
BKM120, INK1117, and BYL719; PI3K/mTOR (mam-
malian target of rapamycin), SAR245409; MEK (MAP
kinase kinase), MSC193639B; EGFR/HER3 (human
epidermal growth factor receptor 3), MEHD7945A.
The chemotherapeutic drugs used were cisplatin,
taxol, and adriamycin. Tumor genotypes are given
in table S2.
41 59 19 350 17 20 28 5 19 8 20 8 8 15 9 12 14
73 219 42 5604 0 38 1 40 2 3 0 1 0 0 0 8 11
Percentage of CTCs
9 10 11 12 13 14 15 16 17
Days on 0 48
VOL 3391 FEBRUARY 2013
on March 22, 2013
E and M RNA-ISH detection of cells captured
on the CTC-chip (fig. S3). Using this assay, we
defined five categories of cells ranging from ex-
clusively epithelial (E) to intermediate (E > M,
E = M, M > E) and exclusively mesenchymal
(M) (fig. S3 and Fig. 2A).
To determine the cutoff for a positive CTC
score, we first analyzed samples from five healthy
blood donors. Two mesenchymal cells were iden-
tified in one of the five specimens (median 0,
range 0 to 2 cells per 3 ml). To set a conserva-
tive threshold, we established 5 cells per 3 ml as
cutoff for a positive CTC score. We next ana-
lyzed blood samples from 41 patients at various
stages of treatment for metastatic breast cancer.
Seventeen patients (41%) scored positive for
CTCs, with EMT features varying according to
histological subtype (Fig. 2, A and B). CTCs
from patients with lobular type cancers (typ-
ically ER+/PR+) were predominantly epithelial,
whereas those from the TN subtype were predom-
inantly mesenchymal. Interestingly, CTCs from
patients with HER2+breast cancer, whose pri-
mary tumors typically contain few E+/M+cells,
were also predominantly mesenchymal (Fig.
2B). Of note, standard cytokeratin-based pro-
tein staining of CTCs was comparable to RNA-
ISH for scoring epithelial CTCs but dramati-
cally undercounted cases with mesenchymal
We next compared CTC features in pre- and
posttreatment blood samples from 10 of these
cases. Five patients who responded to therapy
showed a decrease in CTC numbers and/or a
proportional decrease in M+compared with E+
CTCs in the posttreatment sample (Fig. 2C). In
contrast, five patients who had progressive dis-
ease while on therapy showed an increased num-
ber of M+CTCs in the posttreatment sample.
We obtained serial specimens from one index
patient with ER/PR+lobular carcinoma. This pa-
tient had initially responded to an experimental
regimen, developed resistance, and then responded
transiently to standard chemotherapy (Fig. 3). A
high number of M+CTCs was evident at the
first time point. The first clinical response to the
experimental regimen was accompanied by de-
clining CTC numbers and a switch to predomi-
nantly E+cells. After 7 months of this therapy,
the patient showed disease progression, which was
associated with an increase in M+CTCs. These
cells declined in number again and switched to
an E+phenotype during a second response to
the chemotherapy regimen. After 3 months, the
patient again showed disease progression, along
with a switch to M+CTCs (Fig. 3).
The increase in M+CTCs in the index pa-
tient was accompanied by the appearance of
multicellular CTC clusters, ranging from 4 to
50 cells, with one cluster having ~100 tumor cells
(Fig. 3, fig. S4, and movie S1). These clusters
were absent from specimens with predominantly
E+CTCs. CTC clusters are seen in patients with
advanced cancer (10) and can be detected with
different CTC isolation platforms (13, 14). The
CTC clusters were strongly positive for M markers
and weakly positive for E markers by ISH and
were stained weakly with epithelial cytokeratin
antibodies (Fig. 3). This observation is at odds
with the prevailing hypothesis that EMT results
in highly migratory single cells rather than clus-
ters of cells bearing mesenchymal markers (2, 3).
However, consistent with the recent observation
that platelets bound to tumor cells release trans-
forming growth factor b (TGF-b), potentially
inducing EMT within the circulation (15), stain-
ing of CTC clusters showed an abundance of
attached (CD61-positive) platelets (Fig. 3). We
detected M+CTC clusters of 2 to 20 cells not
only in the index patient but in two additional pa-
tients, both with ER/PR+breast cancer (fig. S5).
Fig. 3. Longitudinal monitoring of EMT features in CTCs
from an index patient. Plot of CTC counts per 3 ml of
blood based on RNA (E and M markers) detection meth-
ods in a patient with KRAS- and PIK3CA-mutant ER/PR+
lobular breast cancer, who was serially sampled during
treatment with inhibitors targeting the PI3K (GDC0941)
and MEK (GDC0973) pathways, followed by adriamycin
chemotherapy. Color-coded quantitation of EMT features
based on RNA-ISH staining is shown above each time
point. Treatment history and clinical responses are noted
on the chart. P, disease progression; R, treatment re-
sponse). M+clusters were detected at time points 1, 8,
and 12. Images of CTCs staining for E (green) and M
(red) markers and protein staining for CK (red), CD45
(green), or platelet marker CD61 (green) from different
time points are shown below the chart. The number of
single CTCs (S-CTC) detected on the entire CTC-chip
upon processing 3 ml of blood and the number of CTCs
within the CTC clusters (C-CTC) are indicated. Nuclei are
stained with 4´,6-diamidino-2-phenylindole (DAPI)
(blue). Scale bar, 10 mm. Criteria for disease progres-
sion (P) or treatment response (R) are described in the
CTC count (E+M) / 3mls
Month 1 Month 3Month 6Month 8
1 FEBRUARY 2013 VOL 339
on March 22, 2013
To identify signaling pathways within CTCs
that contribute to EMT in breast cancer patients,
we subjected these to RNA sequencing, using a
single-molecule platform to avoid amplification
bias associated with rare templates (16, 17). Be-
cause captured CTCs are contaminated with abun-
dant leukocytes, we processed each specimen
through paired anti-EpCAM–capture and mock-
capture CTC-chips, allowing us to subtract digi-
tal gene expression (DGE) profiles of adherent
blood cells from the CTC-enriched cells. DGE
profiles for CTC-enriched cell populations from
the index patient at five serial time points iden-
tified 45 enriched genes, compared with sim-
ilarly processed blood samples from 10 healthy
donors used to measure anti-EpCAM–capture
background [permutation-based statistical model
applied to each of five time points with a false
discovery rate (FDR) threshold of 0.15] (Fig. 4
and table S3). Enriched transcripts included epi-
thelial keratins KRT 8 and 19, and breast tu-
mor markers, mammaglobins (SCGB2A2 and
SCGB2A1), and trefoil factors 1 and 3 (TFF1
and TFF3), the most abundant of which (TFF1)
was highly expressed in both primary tumor and
metastatic lymph node from this patient (fig.
S6). CTC-associated transcripts identified 12 sig-
natures in the Gene Set Enrichment Analysis
(GSEA) database, with an FDR < 0.25 (Fig. 4
and table S4). The strongest association was
with a gene signature up-regulated in bone re-
lapse of breast cancer (P = 1.32 × 10–7; FDR =
0.000767), which is noteworthy because the
patient had metastatic bone lesions at the time
of CTC analysis.
An additional set of 170 transcripts was en-
riched in CTCs captured at a mesenchymal pre-
dominant time point, characterized by multiple
(>18) M+CTC clusters (Fig. 4 and table S5).
SERPINE1/PAI1 and FN1, two mesenchymal
probes used in the RNA-ISH panel, were the most
and third most abundant CTC cluster-associated
transcripts. The GSEA database identified 717
gene signatures (FDR of 0.25) (Fig. 4 and table
S6) with dramatic enrichment for EMT-related
expression changes, including significant over-
lap with a core EMT signature (18) (table S7)
(11 out of 90; P = 8.1 × 10–8; odds ratio = 9.8).
In addition, enrichment for extracellular matrix
(ECM) and ECM-related membrane receptors
(including integrin and interleukin receptors)
were potentially associated with the clustering
phenomenon. Signatures reported in invasive
ductal and lobular carcinomas, therapy resist-
ance, and TGF-b, interleukin-6, and WNT (LEF1)
signaling pathways were also noted. Among
these, the most significant was TGF-b (P= 2.96 ×
10–11), a potent initiator of mesenchymal trans-
formation (2), directly implicated in platelet-
induced EMT (15). Expression of Snail, Slug,
or other well-established transcriptional regu-
lators of EMT was not detected in the M+CTC
clusters, but Forkhead box protein C1 (FOXC1)
(Fig. 4), a transcription factor that induces EMT
in cell culture models (19, 20), was detected.
RNA-ISH revealed FOXC1 expression in CTCs
and within localized regions of primary breast
cancer and a tumor-infiltrated lymph node from
the index patient and other cases (fig. S7). Thus,
along with TGF-b activation, aberrant expres-
sion of FOXC1 may contribute to EMT in hu-
man breast cancer.
In summary, we have provided evidence of
EMT in human breast cancer specimens, both
in rare cells within primary tumors and more
abundantly in CTCs. These findings are consist-
ent with results derived from mouse tumor mod-
els, including recent studies using lineage tracing
in Kras/Tp53 pancreatic and Her2-transgenic
breast cancers (21, 22) and with the detection of
vimentin-stained and/or CK–CTCs in patients
with cancer (23–25). Notably, we found a strik-
ing association between expression of mesen-
chymal markers and clusters of CTCs, rather
than single migratory cells. The expression of
mesenchymal markers by these adherent cells
could result from proliferation of a single cell
170 genes 45 genes
Fig. 4. RNA-sequence analysis of transcripts enriched in CTCs. Heat map
representing transcripts enriched in CTCs captured from the index patient,
who was sampled at multiple time points during treatment. A CTC signature
of 45 genes was derived by comparing 5 time points from the patient (rows
1 to 5) with identically processed blood specimens from 10 healthy donors
(HDs) (rows 6 to 15). An EMT-specific signature of 170 genes was derived
from comparing M+cluster-enriched CTCs (row 4) with E+CTCs. Red and
blue colors indicate relative high and low gene expression, respectively.
Categories of gene signatures in the GSEA database are shown for both the
45 gene CTC signature and the 170 gene EMT-cluster CTC signature, with
genes contributing to the enrichment highlighted in green. The number of
enriched signatures within each category is given in parentheses.
VOL 3391 FEBRUARY 2013
on March 22, 2013
that has undergone EMT into a cluster of such
cells or, alternatively, from the mesenchymal
transformation of preexisting CTC clusters with-
in the bloodstream. The proposal that mesenchy-
mal transformation of epithelial cells is mediated
by TGF-b released from platelets (15) is sup-
ported by our observation of strong TGF-b sig-
natures in mesenchymal CTC clusters, many
of which carry attached platelets. Collective
migration of grouped cells that maintain their
cell-cell and cell-matrix connections has been
implicated in cancer metastasis (26, 27), and
may involve increased survival signals as CTC
clusters circulate in the blood (17, 28, 29). The
clinical importance of EMT as a potential bio-
marker of therapeutic resistance and as a poten-
tial drug target in breast cancer warrants further
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Acknowledgments: We are grateful to all the patients who
participated in this study; we thank D. Juric, C. Koris, and
the Massachusetts General Hospital (MGH) clinical research
coordinators for help with clinical studies; A. Gilman, B. Brannigan,
and M. Zeinali for technical support; F. Ozsolak and P. Milos
(Helicos) for RNA sequencing; A. Forrest-Hay and Q. Nguyen
(Affymetrix) for RNA-ISH reagents; L. Libby for mouse studies; and
J. Walsh for expertise with microscopy. This work was supported
by grants from the Breast Cancer Research Foundation (D.A.H.),
Stand Up To Cancer (D.A.H., M.T., and S.M.), Susan G. Komen for
the Cure KG090412 (S.M.), NIBIB EB008047 (M.T., D.A.H.),
NCI CA129933 (D.A.H.), the National Cancer Institute–MGH
Federal Share Program (S.M.), and the Howard Hughes Medical
Institute (M.Y. and D.A.H.). The MGH and M.T. have filed a patent
for the HB (Herringbone) microchip (U.S. patent 09816815.4).
Sequencing data have been deposited in the Gene Expression
Omnibus database (accession no. GSE41245).
Materials and Methods
Figs. S1 to S7
Tables S1 to S7
7 August 2012; accepted 6 December 2012
of Signal-Activated Stochastic
Gregor Neuert,1,2* Brian Munsky,3* Rui Zhen Tan,1,5,6Leonid Teytelman,1
Mustafa Khammash,4,7† Alexander van Oudenaarden1,8†‡
Although much has been done to elucidate the biochemistry of signal transduction and gene
regulatory pathways, it remains difficult to understand or predict quantitative responses. We
integrate single-cell experiments with stochastic analyses, to identify predictive models of
transcriptional dynamics for the osmotic stress response pathway in Saccharomyces cerevisiae.
We generate models with varying complexity and use parameter estimation and cross-validation
analyses to select the most predictive model. This model yields insight into several dynamical
features, including multistep regulation and switchlike activation for several osmosensitive genes.
Furthermore, the model correctly predicts the transcriptional dynamics of cells in response to different
environmental and genetic perturbations. Because our approach is general, it should facilitate
a predictive understanding for signal-activated transcription of other genes in other pathways
regulatory proteins in these processes, this typi-
cally does not enable construction of quantitative-
ly predictive models of transcriptional dynamics.
One challenge lies in the fact that gene regula-
tion is a dynamic multistate process with largely
unknown reactionrates.Forexample,a two-state
system may represent closed and openchromatin
factor (7–9). Including more states or regulatory
central goal of systems biology is to un-
tic dynamics of gene regulation (1–3).
We propose a data-driven comprehensive ap-
proach to identify and validate predictive, quan-
titative models of transcriptional dynamics through
the integration of single-cell experiments and dis-
crete stochastic analyses within a system identifi-
cation framework. We apply this approach to the
in Saccharomyces cerevisiae and focus on the
regulation of STL1, CTT1, and HSP12 (11, 12)
genes. Upon osmotic shock, the Hog1p kinase
quickly enters the nucleus (Fig. 1A, and figs. S2
to S4, and S6) (13–16) and activates STL1, CTT1,
and HSP12 gene expression (figs. S6 and S9)
ics is homogeneous (14, 15, 17), yet downstream
gene activation is heterogeneous among cells
(17). To quantify STL1 expression directly, we de-
veloped a single-molecule fluorescent in situ hy-
bridization (smFISH) (18, 19, 20) assay, which
captures the stochastic nature of mRNA transcrip-
tion with high temporal and single-molecule res-
olution (Fig. 1B) (21, 22, 23).
In addition to the kinase Hog1p, we consider
the effects of the transcription factor Hot1p and
the chromatin modifiers Arp8p and Gcn5p that
modulate STL1 transcription (17, 24). For this
system, we seek to find and validate a model that
1Departments of Physics and Biology and Koch Institute for
Integrative Cancer Research, Massachusetts Institute of Tech-
nology, Cambridge, MA 02139, USA.2Department of Molec-
University, Nashville, TN 37232, USA.3Center for Nonlinear
Studies and the Information Sciences Group, Los Alamos
National Laboratory, Los Alamos, NM 87545, USA.4Depart-
ment of Biosystems Science and Engineering, ETH-Zuerich,
4058 Basel, Switzerland.5Bioinformatics Institute, A*STAR,
Singapore 138671, Singapore.6Harvard University Graduate
USA.7Center for Control, Dynamical Systems and Computation
and Department of Mechanical Engineering, University of
Royal Netherlands Academy of Arts and Sciences and Uni-
versity Medical Center Utrecht, Uppsalalaan 8, 3584 CT,
*These authors contributed equally to this work.
‡To whom correspondence should be addressed. E-mail:
1 FEBRUARY 2013VOL 339
on March 22, 2013