Published OnlineFirst January 9, 2020; DOI: 10.1158/0008-5472.CAN-18-4099

CANCER RESEARCH | MOLECULAR CELL BIOLOGY

BACH1 Promotes Pancreatic Cancer Metastasis byRepressing Epithelial Genes and Enhancing Epithelial–
Mesenchymal Transition
Masaki Sato1,2, Mitsuyo Matsumoto1,3, Yuriko Saiki4, Mahabub Alam1,5, Hironari Nishizawa1,
Masahiro Rokugo1,6, Andrey Brydun1, Shinji Yamada7, Mika K. Kaneko7, Ryo Funayama3,8, Mamoru Ito9,
Yukinari Kato7,10, Keiko Nakayama3,8, Michiaki Unno2, and Kazuhiko Igarashi1,3

ABSTRACT◥

Pancreatic ductal adenocarcinoma (PDAC) is among thecancers with the poorest prognoses due to its highly malignant
features. BTB and CNC homology 1 (BACH1) has been implicated in RAS-driven tumor formation. We focused on the role of
BACH1 in PDAC, more than 90% of which have KRAS mutation. Knockdown of BACH1 in PDAC cell lines reduced cell
migration and invasion, in part, by increasing E-cadherin
expression, whereas its overexpression showed opposite effects.
BACH1 directly repressed the expression of FOXA1 that is
known to activate the expression of CDH1 encoding E-cadherin
and to inhibit epithelial-to-mesenchymal transition. BACH1
also directly repressed the expression of genes important forepithelial cell adhesion including CLDN3 and CLDN4. In a

Introduction
The 5-year survival rate of individuals diagnosed with pancreatic
ductal adenocarcinoma (PDAC) is 10% or less, placing PDAC among
the cancers with the poorest prognoses (1). While surgical resection iscurrently the only treatment with a chance of a successful outcome,
80% of cases at the time of diagnosis are inoperable due to extensive
metastasis. There are few effective diagnostic methods and treatments
for PDAC (2). Therefore, it is an urgent matter to elucidate the1
Department of Biochemistry, Tohoku University Graduate School of Medicine,
Sendai, Japan. 2Department of Surgery, Tohoku University Graduate School of
Medicine, Sendai, Japan. 3Center for Regulatory Epigenome and Diseases,
Tohoku University Graduate School of Medicine, Sendai, Japan. 4Departmentof Molecular Pathology, Tohoku University Graduate School of Medicine, Sendai,
Japan. 5Department of Animal Science and Nutrition, Chattogram Veterinary
and Animal Sciences University, Khulshi, Chattogram, Bangladesh. 6Department
of Otolaryngology-Head and Neck Surgery, Tohoku University Graduate Schoolof Medicine, Aoba-ku, Sendai, Japan. 7Department of Antibody Drug Development, Tohoku University Graduate School of Medicine, Sendai, Japan. 8Department of Cell Proliferation, Tohoku University Graduate School of Medicine,
Sendai, Japan. 9Central Institute for Experimental Animals, Tonomachi, Kawasaki, Japan. 10New Industry Creation Hatchery Center, Tohoku University,
Sendai, Miyagi, Japan.

Note: Supplementary data for this article are available at Cancer Research
Online (http://cancerres.aacrjournals.org/).
Corresponding Authors: Kazuhiko Igarashi and Mitsuyo Matsumoto, Tohoku
University Graduate School of Medicine, 2-1 Seiryo, Aoba-ku, Sendai 980-8575,
Japan. Phone: 812-2717-7596; Fax: 812-2717-7598; E-mail:igarashi@med.tohoku.ac.jp; and m-matsumoto@med.tohoku.ac.jp
Cancer Res 2020;80:1279–92
doi: 10.1158/0008-5472.CAN-18-4099
2020 American Association for Cancer Research.

mouse orthotopic implantation model, BACH1 was required
for the high metastatic ability of AsPC-1 cells. IHC analysis ofclinical specimens with a newly developed anti-BACH1 mAb
revealed that high expression of BACH1 is a poor prognostic
factor. These results suggest that the gene regulatory network of
BACH1 and downstream genes including CDH1 contribute to
the malignant features of PDAC by regulating epithelial-tomesenchymal transition.
Signiﬁcance: Greater understanding of the gene regulatory
network involved in epithelial-to-mesenchymal transition of
pancreatic cancer cells will provide novel therapeutic targets anddiagnostic markers.
molecular mechanisms underlying the development and malignant
features of PDAC. Recent genome analyses of PDAC have revealed
genetic mutation proﬁles of PDAC (3–5). More than 90% of PDAC
carry activating mutations of KRAS to promote their proliferation andmalignant features (6).
BACH1 is a basic leucine zipper transcription factor, which
represses expression of genes involved in the protection against
oxidative stress such as heme oxygenase-1 (HO-1) under normal
conditions. During oxidative stress, BACH1 is exported out of thenucleus, allowing for HO-1 induction and thus decrease of reactive
oxygen species (7). In addition, BACH1 inhibits cellular senescence byforming a complex with p53, thereby inhibiting the expression of asubset of p53 target genes (8, 9). Therefore, BACH1 contributes to themaintenance of cell homeostasis by increasing oxidative stress andrestricting tumor suppressor responses.
Recent studies have shown that BACH1 regulates the processes ofcancer. BACH1 promotes methylation of CpG islands of tumor
suppressor genes in cancers with BRAF mutation, repressing theirexpression (10). In breast cancer, BACH1 promotes metastasis byregulating multiple metastasis-related genes (11). It also promotes
tumor formation of triple-negative breast cancer cells by repressing
mitochondria-related genes (12). In a model of RAS-mediated transformation of mouse embryonic ﬁbroblast (MEF) cells, tumor formation and proliferation are markedly inhibited in BACH1 knockout(KO) MEF as compared with wild-type (WT) MEF cells (13). Theseobservations suggested that BACH1 might contribute to the development and malignant features of PDAC, which is often driven by
activating mutation of KRAS. However, the function of BACH1 in
PDAC is still unclear. This issue was analyzed here using siRNAmediated gene silencing and stable overexpression in human PDAC
cell lines. Direct target genes of BACH1 in PDAC cells were identiﬁed
by integrating RNA-sequencing and chromatin immunoprecipitation(ChIP) and sequencing. Orthotopic implantation of CRISPR-Cas9–

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Sato et al.

mediated gene knockout cells in NOG mice established that BACH1
promoted epithelial-to-mesenchymal transition (EMT) and metastasis as a key regulator of epithelial genes including CDH1 encoding
E-cadherin.

Materials and Methods
Cell culture and reagent
Human PDAC lines AsPC-1, SW1990, and BxPC-3 cells werepurchased from ATCC. Human PDAC line Panc-1 was purchasedfrom RIKEN BioResource Center. Cells were expanded within 3
passages after purchase, and multiple lots were stocked at 80 C.
The Mycoplasma contamination check tests were performed using
e-Myco plus Mycoplasma PCR Detection Kit (iNtRON). Cells
were used at least less than 20 passages, but were not independently authenticated. SW1990, Panc-1, and BxPC-3 cells were
cultured in RPMI1640 medium (Sigma Aldrich) supplemented
with 10% FBS (Sigma Aldrich), 0.1 mg/mL penicillin/streptomycin(Gibco), and 10 mmol/L HEPES (Gibco) under humidiﬁed atmospheric conditions in 5% CO2. AsPC-1 was cultured similarly with
20% FBS.
siRNA, sgRNA, plasmids, and generation of stable cells
Target-speciﬁc siRNAs (Stealth RNAi siRNA Duplex Oligoribonucleotides, Invitrogen) were transfected using Lipofectamine RNAiMAX (Thermo Fisher Scientiﬁc). Stealth RNAi siRNA Negative
Control, Low GC (Thermo Fisher Scientiﬁc) was used as a control
siRNA. To knockout BACH1 in AsPC-1, lentiviruses were prepared byusing lentiCRISPR v2 (Addgene) with single guide RNAs (sgRNA)targeting BACH1 (see Fig. 6A). The infected AsPC-1 cells wereselected by using medium supplemented with 10 mg/mL puromycin(Sigma Aldrich). To overexpress BACH1 in Panc-1, a vector (pCMV2BACH1) was transfected into the cells using Fugene HD (Promega).
Cells were selected in a medium with 2,000 mg/mL G418 (Calbiochem)and cloned by isolation of surviving colonies.
Cell counting assay
Cells (300,000 cells per well) were seeded into 6-well plates, followed
by transfection with 30 pmol of siRNA using Lipofectamine RNAimax
on the next day. After the cell reseeding to dish or plate at 24 hours
posttransfection, the number of live cells was measured using TC20
Automated Cell Counter (Bio-Rad Laboratories) after staining with
Trypan blue.
qRT-PCR and ChIP-qPCR
Total RNA was isolated using RNeasy Plus Mini Kit (Qiagen).
One microgram of total RNA was used for cDNA synthesis using
Omniscript Reverse Transcription Kit (Qiagen). The ChIP-DNA
was prepared using anti-BACH1 antibody (A1-6) in AsPC-1 as
described (see Supplementary Methods for details). Quantitative
PCR analysis was performed in LightCycler Nano (Roche) using
LightCycler Fast Start DNA Master SYBR Green I (Roche). All gene
expression data were normalized with an internal control gene
(ACTB). All ChIP-qPCR data was normalized with target ampliﬁcation site in Input. The primer sequences are in Supplementary
Table S1.
Antibody
A new mouse mAb that speciﬁcally recognizes human BACH1 was
generated with full-length human BACH1 protein expressed in SF21
cells by expression vector pFastBac (Invitrogen). BALB/c mice were1280 Cancer Res; 80(6) March 15, 2020

immunized by injecting the antigen with Freund's complete adjuvant.
The splenocytes were fused with mouse melanoma Sp2/0 cells using
polyethylene glycol method. The hybridomas were cloned by limiting
dilution method and screened for antibodies against human BACH1.
Anti-BACH1 mAb (clone 9D11) was puriﬁed from the culture supernatant of selected hybridoma and its speciﬁcity was validated as shownin Figs. 3A and B and 6E. Anti-BACH1 antiserum (A1-6) and antiNRF2 antibody were reported previously (14, 15). Other antibodies
were GAPDH (ab8245, Abcam), ACTB (GTX109639, GeneTeX), Ecadherin (ab1416, Abcam), p44/42 MAPK (#9102, Cell Signaling
Technology), and phosphor-p44/42 MAPK (#9101, Cell Signaling
Technology).
Immunoﬂuorescent staining
The cells were ﬁxed in 4% formaldehyde/PBS. After incubation
with anti-E-cadherin (1:200) or an anti-BACH1 (1:200, 9D11)
antibodies for 1 hour at 37 C, the target proteins were detectedby an anti-mouse IgG FITC-conjugated secondary antibody(1:1,000, F3008, Sigma Aldrich). Nuclei were stained with 20 mg/mL
Hoechst 33342 in PBS.
Wound-healing assay
Cells in 6-well plates were grown to conﬂuence. Monolayer of cells
was scratched in a line by 1,000 mL pipette tips to remove a part of thecells. Areas of migrating cells were estimated at 24 hours later bycounting numbers of pixels using ImageJ software (NIH, Bethesda,
MD; https://imagej.nih.gov/ij/).
Transwell assay
For transwell migration and invasion assay, 24-well cell culture
insert (BD Falcon, 353097) and 24-well Matrigel Invasion chamber(Corning, 354480) were used. Cells suspended in serum-free medium(AsPC-1, 200,000 cells; SW1990, 100,000 cells) were seeded to the top
chamber after serum-containing medium (AsPC-1: 20% FBS;
SW1990: 10% FBS) was added to bottom chamber. The cells thattranslocated to the bottom surface of the membrane were ﬁxed with 4%
formaldehyde and stained with 0.05% crystal violet after 24 hours andcounted. The measurements were performed in technical duplicate
and biological triplicate.
RNA sequencing
Libraries were constructed using Ion Total RNA-Seq Kit for AB
Library Builder System (Thermo Fisher Scientiﬁc) and sequence run
was performed on Ion Proton (Thermo Fischer Scientiﬁc; see Supplementary Methods for details).
ChIP sequencing
The ChIP-DNA libraries were prepared from approximately 10 ng
of ChIP-DNA or Input-DNA using the Ovation Ultralow DR Multiplex System (NuGEN Technologies, 0330-32, 0331-32). The pooled
libraries were sequenced as 51-base paired-end reads on an Illumina
HiSeq 2500 (Illumina) across two lanes of rapid mode ﬂow cells. Image
analysis and base calling were done by Hiseq Control Software (HCS
v2.2.38, Illumina) and real-time analysis software (RTA v1.18.61,
Illumina). The low-quality reads marked by Illumina sequencers in
the fastq format data were ﬁltered using CASAVA v1.8. Other lowquality reads were removed by Fastx toolkit v.0.0.14. The obtained
reads were aligned to the hg19 human reference genome using bwa v
0.7.10. The peaks were called using MACS 2 v 2.1.0. The peaks existing
within 110 bases in the different samples were judged as overlapping
peaks.

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Addiction of Pancreatic Cancer to BACH1 in EMTHigh throughput data availability
The all high throughput data from this study have been deposited in
Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo) underSuperSeries accession number GSE124408.
In vivo tumor growth assay and metastasis analysis
All experimental protocols in mice were approved by the Institutional Animal Care and Use Committee of Tohoku University (Sendai,
Miyagi, Japan). NOD.Cg-PrkdcscidIl2rgtm1Sug/ShiJic (NOG) mice (6to 8-week-old) were transplanted with 10,000 cells in 100 mL PBS
under the capsule of the pancreatic tail by laparotomy. The mice wereeuthanized 5 weeks after transplantation. The necropsy was performed
to conﬁrm tumor formation, liver metastasis, and peritoneal metastasis. The size of the primary tumor was measured by the pancreas
weight. Liver metastasis was measured as the counted number ofmetastatic lesions that could be recognized visually. Peritoneal metastasis was counted as the total number of metastases of mesentery,
diaphragm, and abdominal wall.
In silico analysis
RNA-sequencing data and clinical data of 176 patients with PDAC
in the Cancer Genome Atlas (TCGA; https://cancergenome.nih.gov/)
were used for Kaplan–Meier analysis.
Patients and samples for IHC
Samples were obtained from 116 cases of PDAC who underwent
resection at Tohoku University Hospital (Sendai, Miyagi, Japan)
from 2007 to 2014. This study was approved by the Ethics Committee of Tohoku University School of Medicine (no. 2016-1-151).
All patients permitted the usage of a part of their tissue for scientiﬁc
purposes and written informed consent was obtained. Tissue specimens were immediately ﬁxated in 10% paraformaldehyde after
surgery.
IHC
Parafﬁn sections of 3 mm were incubated for 30 minutes at 95 C
with TE (10 mmol/L Tris-HCl pH 8.0, 1 mmol/L EDTA), followed byincubation for 24 hours with primary antibodies [anti-BACH1 antibody (1:100, 9D11) or E-cadherin (1:200)]. Secondary antibody used
was MAX-PO (Mouse) kit (Nichirei). Staining intensity of cancer cells
was judged to be BACH1-positive, if it was more intense than that oflymphocytes used as an internal control. Staining intensity wasclassiﬁed into three (weak: 0%–10%, moderate: 11%–49%, strong:
50%–100%).

Results
BACH1 is important for EMT-like morphology, but notproliferation
To examine whether BACH1 regulates cell proliferation, we performed siRNA-mediated knockdown of BACH1 in AsPC-1 cells.
These cells were chosen because BACH1 protein expression in
AsPC-1 cells was the highest among PDAC cells examined (Supplementary Fig. S1A and S1B). When cells were seeded at high concentrations, BACH1 silencing did not affect proliferation. However,knockdown of BACH1 led to reduced cell proliferation when theinitial seeding concentration was lower (Fig. 1A and B). Similar results
were obtained using additional cell lines of PDAC, SW1990, and
BxPC-3 cells (Fig. 1C and D; Supplementary Fig. S1C and S1D).
To investigate the inﬂuence of BACH1 on morphologic features of
PDAC cells, we compared BACH1 silencing and overexpression in

AACRJournals.org

PDAC cells. BACH1 silencing apparently resulted in increased cell–
cell attachment and an epithelial-like cell morphology in AsPC-1(Fig. 1E). Such alterations were not obvious in SW1990 cells that
tended to attach to each other in control conditions (Fig. 1E). To
carry out gain-of-function experiments, we used Panc-1 cells that
expressed relatively lower quantities of BACH1 protein among the
PDAC cells examined. BACH1 overexpression in Panc-1 cells
induced changes including mesenchymal-like cell morphology withdecreased cell–cell adhesion (Fig. 1F and G). These observations
suggested that adhesion between cells was increased, resulting inepithelial-like morphology following BACH1 silencing in AsPC-1
cells, whereas EMT-like alterations were induced by BACH1 overexpression in Panc-1 cells.
BACH1 inhibits epithelial gene expression to initiate EMT
To analyze the role of BACH1 in PDAC cells, RNA-sequencing
was performed using AsPC-1 cells with or without BACH1 knockdown. Expression of 402 Ensembl gene IDs was increased, whereas
969 Ensembl gene IDs were downregulated upon BACH1 knockdown (fold change > 2, false discovery rate < 0.05; Fig. 2A;
Supplementary Table S2). Because the previous experiments suggested that BACH1 might be involved in EMT (Fig. 1E and G), we
focused on EMT-related genes whose expression is either reduced
or induced upon EMT (16–18), and found that knockdown of
BACH1 resulted in elevated expression of epithelial genes including CDH1 encoding E-cadherin and those encoding tight junction
proteins (CLDN3, CLDN4, OCLN). Importantly, FOXA1, which is
critical for activating the expression of epithelial genes (18, 19), wasalso induced upon BACH1 knockdown. In contrast, we observed
decreased expression of mesenchymal genes including VIM encoding vimentin and SNAI2, a critical transcription factor necessary
for EMT (Fig. 2B). These results suggest that BACH1 is critical for
maintaining EMT in PDAC. To examine this possibility, weinvestigated transcriptional changes induced by BACH1 knockdown in AsPC-1 and SW1990 cells, and by BACH1 overexpressionin Panc-1 cells using qRT-PCR (Fig. 2C). The expression of CDH1
and OCLN, which are epithelial-speciﬁc, was increased whereas thatof VIM, which is mesenchymal-speciﬁc, was decreased upon knockdown of BACH1 in AsPC-1 and SW1990. Moreover, BACH1
overexpression in Panc-1 cells resulted in downregulation of CDH1
and OCLN, and upregulation of VIM. These results support the
hypothesis that BACH1 is important for the maintenance of
mesenchymal characteristics of PDAC cells. Importantly, FOXA1
expression was increased by BACH1 silencing, whereas it was
decreased after BACH1 overexpression (Fig. 2C). While FOXA1
is known to be an activator of CDH1 expression (18, 19), the double
knockdown of BACH1 and FOXA1 did not reduce CDH1 expression (Fig. 2D), suggesting the involvement of additional transcription factors in the regulation of CDH1 expression. SNAI2 expression
was decreased by BACH1 silencing and overexpression (Fig. 2C),
suggesting a biphasic regulation of SNAI2 by BACH1; its activation
and repression being dependent on BACH1 protein levels andactivity.
Gene ontology (GO) analysis was performed using the genes whose
expression was increased or decreased by the BACH1 silencing. GO
terms related to migration, wound healing, cell division, and proliferation were enriched in genes downregulated in response to BACH1
knockdown. On the other hand, in the genes whose expression wasincreased, we found terms related to the metabolism of anticancer
drugs and cell differentiation (Supplementary Fig. S2A). KEGG pathway analysis demonstrated that the genes related to MAPK (20, 21)

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**
**
1.0

0.5

6

siCont.
siBACH1-1
siBACH1-2

4
3

n.s.

n.s.

n.s.

2
1

C

SW1990D
Relative cell number

**
1.0

0.5

2
P= 0.0088 P= 0.0011

24
48Time (hours)

72

0

siCont.
siBACH1-1
siBACH1-2

3.0
2.5

n.s.

n.s.

2.0
1.5
1.0

0.0
2
siCont. 1
siBACH1

E

0

24
48
Time (hours)

siCont.

siBACH1-1

Empty vector (EV)exBACH1

72
Time (hours)

72

120

Panc-1

n.s.

0.5
0.0

24

F

SW19903.5**

P= 0.0049

3

0
0

1.5

P= 0.0184102
siCont. 1
siBACH1

siCont.
siBACH1-1
siBACH1-2

5

Relative BACH1 mRNA level

0.0

Relative BACH1 mRNA level

5

AsPC-1(9,000 cells/cm2)
Relative cell number

1.5

AsPC-1(20,000 cells/cm2)

B

AsPC-1

Relative cell number

Relative BACH1 mRNA level

A

6

**

5
4
3
2
1
0
EV exBACH1siBACH1-2

AsPC-1

SW1990G
Panc-1Figure 1.
BACH1 is important for mesenchymal morphologic maintenance independently of proliferation. A, BACH1 mRNA levels in BACH1-silenced AsPC-1 cells. Scrambled
siRNA was used as control. mRNA expression is normalized to the expression of control cells. B, Relative cell numbers of BACH1-silenced AsPC-1 cells; cells
were seeded at 20,000 cells/cm2 (left) or 9,000 cells/cm2 (right) and cells were counted after 24, 48, and 72 hours. C, BACH1 mRNA level in BACH1-silenced
SW1990 cells. Scrambled siRNA was used as control. mRNA expression is normalized to the expression of control cells. D, Relative cell number of BACH1-silenced
SW1990 cells. E, Morphology of BACH1-silenced AsPC-1 cells. Scrambled siRNA was used as control. Scale bar, 100 mm. F, BACH1 mRNA level in control
and BACH1-overexpressing Panc-1 cells. G, Morphology of BACH1-overexpressing Panc-1 cells. Empty vector was used as control. Scale bar, 100 mm. All data arepresented as mean  SD, with P values from the Student t test.  , P < 0.05;   , P < 0.01; n.s., not signiﬁcant.

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Addiction of Pancreatic Cancer to BACH1 in EMT

B

siCont. siBACH1

1 2 3 1 2 3

Mesenchymal genes

Cluster 1
Cluster 1

AsPC-1

6**siCont.
siBACH1-1
siBACH1-2

**

4 **

**
**
*
*

2

*
**

0
CDH1 OCLN FOXA1 VIM SNAI2

Relative mRNA expression

**
*

8

Panc-1

SW19903 ******siCont.
siBACH1-1
siBACH1-2

**
**

2

**

**

*

**

1

0
CDH1 OCLN FOXA1VIM SNAI2

Relative mRNA expression

C
Relative mRNA expression

CDH1
KRT18
OCLN
CLDN3
CLDN4
PKP2
PKP3
TJP1
TJP3
FOXA1
GJB2
GJB3
SERPINE1
CDH2
ACTA2
VIM
CTGF
S100A2SPARC
z-Score
FN1
1.5
CYR61
1
COL8A1
0.5
SNAI1
0
SNAI2
−0.5
YAP1
−1
TWIST1
−1.5
ZEB1
ZEB2

Epithelial genes

A

2
EV
exBACH1

1.5
**

**

*

**

**

1
0.5
0
CDH1 OCLN FOXA1 VIM SNAI2

D
Relative mRNA expression

5

siCont.
siCont. + siBACH1-1
siCont. + siBACH1-2
siBACH1-1 + siFOXA1-1
siBACH1-1 + siFOXA1-2
siBACH1-2 + siFOXA1-1
siBACH1-2 + siFOXA1-2

4
3
2
1
0

BACH1

CDH1

OCLN

FOXA1

VIM

SNAI2

Figure 2.
BACH1 inhibits epithelial gene expression to initiate EMT. A, Heatmap of RNA sequencing results in control and BACH1 silencing samples (n ¼ 3). Scrambled siRNA wasused as control. Genes with fold change  2 and P < 0.05 are shown. B, Heatmap shows the RNA sequencing results (RPKM, reads per kilobase of exon per million
mapped sequence) of arbitrarily selected EMT-related genes, ignoring P value and fold change. RPKM was calculated on Cufﬂinks v2.2.1. C, qRT-PCR analyses of
the indicated transcripts (relative to ACTB). mRNA expression is normalized to the expression of control cells. All data are presented as mean  SD, with P values
from the Student t test.  , P < 0.05;   , P < 0.01. D, qRT-PCR analyses of the indicated transcripts (relative to ACTB) upon single or combined knockdown of BACH1and FOXA1 in AsPC-1 cells. All data are presented as mean  SD.

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proliferation of AsPC-1 cells in vitro shown above (Fig. 1B). GSEA
analysis showed also that the expression of EMT- and KRAS-related
genes were altered in comparison of BACH1 knockdown cells andthe control (Supplementary Fig. S2D and S2E). We surmised that
activities of these pathways are suppressed by BACH1 knockdown andthat BACH1 might be involved in the regulation of EMT.

and TGFb pathways (22, 23), which are important for proliferation,transformation, and EMT of PDAC, were decreased in their expression upon BACH1 knockdown (Supplementary Fig. S2B). Consistent
with the prediction of downregulation of MAKP, the quantity ofphospho-ERK protein was reduced in BACH1 knockdown cells(Supplementary Fig. S2C). These results may explain the reduced
AsPC-1A

SW1990siBACH1
1
2

siCont.

siCont.

(kDa)
150

Panc-1

siBACH1
1
2

(kDa)
150

EV exBACH1 (kDa)150

E-cadherin
100

100

100

100

BACH1

100

100
75
50

75
50

75
50

37

37

37

ACTB

B

E-cadherin

siCont.

siCont.

siBACH1-1

siBACH1-1

siBACH1-2

E-cadherin siBACH1-2
Nuclei
BACH1

CDH1

1.5
1.0
0.5

**
**

0.0

siCont. 1 2 siCont. 1 2
siBACH1
EV

E

Merge

BACH1
Nuclei*2.0

Relative mRNA expression

Relative mRNA expression

C

Hoechst
33342

BACH1

Figure 3.
BACH1 is important for maintenance of mesenchymal characteristics. A, Immunoblot analysis of
E-cadherin protein levels in BACH1silenced AsPC-1 and SW1990 cells and
BACH1-overexpressing Panc-1 cells. B,
Immunoﬂuorescence staining of Ecadherin (left) and BACH1 (right)
in BACH1-silenced AsPC-1 cells. Scalebar, 25 mm. C, qRT-PCR analyses
of indicated transcripts (relative
to ACTB as a control) in control (EV)or BACH1-overexpressing (exBACH1)
Panc1 cells with or without BACH1
knockdown. mRNA expression is normalized to the expression of the control samples. All data are presented asmean  SD, with P values from theStudent t test.  , P < 0.05;   , P < 0.01.
D, Immunoblot analysis of E-cadherin
protein levels in control cells (EV),cells overexpressing BACH1 with(siBACH1 1 and 2) or without BACH1
knockdown (siCont). E, Morphology
of BACH1-overexpressing cells withor without BACH1 silencing. Empty
vector and siCont were used as controls. Scale bar, 100 mm.

siBACH1
exBACH1

siCont.

0.6

Panc-1D**

exBACH1
0.4

siBACH1
EV siCont. 1
2

**

(kDa)

150

0.2

**

E-cadherin
100

0.0
50

siCont. 1 2 siCont. 1 2
siBACH1
EV

siBACH1ACTB
37exBACH1

siBACH1-1

siBACH1-2

EV

exBACH1

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Published OnlineFirst January 9, 2020; DOI: 10.1158/0008-5472.CAN-18-4099

Addiction of Pancreatic Cancer to BACH1 in EMT

BACH1 is important for the maintenance of mesenchymal
characteristics
Immunoblotting analysis indicated that the amount of E-cadherin
protein was clearly increased by BACH1 silencing in AsPC-1 andSW1990 cells (Fig. 3A, left and middle). On the other hand, it was
decreased by BACH1 overexpression in Panc-1 cells (Fig. 3A, right).
Immunoﬂuorescence staining of AsPC-1 cells showed that cell–celladhesion involving E-cadherin was induced upon BACH1 knockdown(Fig. 3B, left). BACH1 protein was mainly present in the nuclei andreduced upon knockdown in AsPC-1 cells (Fig. 3B, right). Next, we
examined whether the decreased E-cadherin expression in BACH1overexpressing Panc-1 cells could be reversed by BACH1 knockdown.
However, the reduction of BACH1 mRNA was smaller in the
BACH1-overexpressing cells compared with the control cells.
Nonetheless, this small reduction was associated with small inductions of E-cadherin mRNA and protein (Fig. 3C and D). Unexpectedly, BACH1-overexpressing cells showed a severely altered cellmorphology with a ﬂattened, cellular senescence-like appearance
upon knockdown of BACH1 (Fig. 3E). BACH1-overexpressing
Panc-1 cells seem to require continuous expression of BACH1 tomaintain cellular homeostasis, the nature of which needs further
investigation. These results showed that BACH1 reduces the expression of E-cadherin and formation of cell–cell adhesion, and suggeststhat BACH1 is important for the maintenance of mesenchymal
characteristics of PDAC cells.
BACH1 promotes migration and invasion
To analyze the effect of BACH1 on cell migration, we performed
wound-healing assays with AsPC-1 cells after BACH1 knockdown andwith Panc-1 cells after BACH1 overexpression. Wound-healing assays
using these cells demonstrated that BACH1 silencing inhibited cell
migratory activity in AsPC-1 cells, whereas BACH1 overexpression in
Panc-1 cells increased the activity (Fig. 4A and B). However, BACH1
silencing did not inhibit the cell migration of BxPC-3 cells, which
possess WT KRAS (Supplementary Fig. S3A). BACH1 silencing did
not alter the expression of EMT-related genes in BxPC-3 cells (Supplementary Fig. S3B). These results and the result of GSEA (Supplementary Fig. S2E) suggested that dependency of PDAC cells on
BACH1 may be cell-type speciﬁc and dependent on the presence ofmutant KRAS. To further examine whether BACH1 silencing inhibits
cell migration and invasion, we carried out transwell assays using
AsPC-1 and SW1990 cells. BACH1 silencing decreased cell migratory
and invasive activities of these cells (Fig. 4C). Taken together, theseresults suggest that BACH1 is important for cell migration andinvasion of PDAC cells.
BACH1 directly controls a set of EMT-related genes
To identify direct target genes of BACH1 in the induction of EMT,
we performed BACH1 ChIP-sequencing analysis in AsPC-1 andSW1990 cells. The results of ChIP-sequencing were combined withthe above RNA-sequencing results of BACH1 knockdown (Fig. 5A).
Among the genes important for EMT (Fig. 2B), BACH1 directly
repressed the expression of FOXA1, PKP2, CLDN3, and CLDN4,
whereas it directly promoted the expression of SNAI2 (Fig. 5B). SNAI2
is known to repress CDH1 expression, whereas FOXA1 is known to
induce CDH1 expression (18, 24). CLDN3 and CLDN4 are moleculesthat constitute tight junctions and are also important for EMT
suppression as like E-cadherin (17, 25, 26). PKP2 is a constituent
protein of the desmosome that is involved in cell–cell adhesion (27).
ChIP-qPCR results conﬁrmed that BACH1 bound the genomic
regions of FOXA1 and SNAI2 in AsPC-1 and SW1990 cells

AACRJournals.org(Fig. 5C). We surmise that BACH1 regulates a set of EMT-related
genes by repressing critical epithelial genes and by activating SNAI2 toinitiate EMT.
BACH1 promotes metastasis but not tumor formation
We established AsPC-1 cells lacking BACH1 using a CRISPR/
Cas9 system. Knockout was performed using two different constructs of sgRNA (Fig. 6A), and the mutations were conﬁrmed bySanger sequencing. Expression of CDH1, OCLN and FOXA1 wasupregulated in BACH1 knockout cells. However, expression of VIM
and SNAI2 was not altered (Fig. 6B). We investigated E-cadherin
expression by immunoblotting and immunoﬂuorescence analyses(Fig. 6B and C; Supplementary Fig. S4A and S4B). E-cadherin
expression was upregulated in sgBACH1-2, but this effect was
smaller in sgBACH1-1. We observed consistent alterations in
BACH1 mRNA and protein amounts in the knockout, RNA silencing, and overexpressing cells except BACH1 mRNA in knockout
cells (Supplementary Fig. S4C and S4D, see below). Becauseamounts of NRF2 protein were similar between control and manipulated cells, alterations of oxidative stress appeared negligible upon
manipulation of BACH1. Also, the differences in BACH1 mRNAand protein in AsPC-1 and Panc-1 cells were not due to differencesin oxidative stress or NRF2.
To compare gene expression in these cells further, RNA-sequencing
was performed using control AsPC-1/sgCont cells and BACH1 knockout AsPC-1/sgBACH1-2 cells. While the amounts of BACH1 mRNA
were not greatly reduced by BACH1 knockout (Supplementary Figs.
S4C and S5A), the presence of the intended or unintended mutations
were conﬁrmed from RNA-sequencing reads (Supplementary
Fig. S5B). Comparison of gene expression patterns in these cells using
all genes (reads counts > 5 and CPM > 1 in more than one sample)
showed that the effects of siRNA and CRISPR/Cas9 were not the same
(Supplementary Fig. S5C and S5D; Supplementary Table S3), suggesting an adaptation of the cells to the BACH1 knockout. Consistent withthe above results of BACH1 silencing, BACH1 knockout resulted inelevated expression of epithelial genes including FOXA1 and CLDN3(Supplementary Fig. S5E–S5G; Supplementary Tables S2 and S3).
Repression of these genes might be especially important for thefunction of BACH1 in PDAC cells. In contrast, expression of mesenchymal genes and RAS-related genes was decreased by the BACH1
knockout (Supplementary Figs. S5E and S5F and S6A and S6B). These
results further support the hypothesis that BACH1 is important for the
maintenance of mesenchymal characteristics and KRAS signaling of
PDAC cells.
To examine whether BACH1 would be involved in tumor formation
and/or metastasis, we compared the effects of BACH1 knockout on
PDAC formation and metastasis in an orthotopic mouse model. Afterorthotopic transplantation to NOG mice, AsPC-1/sgCont cells andAsPC-1/sgBACH1-2 cells generated primary tumors in the pancreas
and metastases in the liver, mesentery, diaphragm, and peritoneumthat were examined ﬁve weeks later (Supplementary Fig. S6C). We
compared primary tumor formation between control and BACH1
knockout AsPC-1 by measuring the weight of pancreas. We counted
the number of liver metastases and peritoneal metastases (mesentery,
diaphragm, and abdominal wall). Primary tumor weight was notdifferent between the two experimental sets. In contrast, lower quantities of liver and peritoneal metastatic foci were observed in micecontaining BACH1 knockout AsPC-1 cells than those containing
control cells (Fig. 6D). BACH1 was strongly stained in nuclei of
AsPC-1/sgCont while barely present in AsPC-1/sgBACH1-2 cells of
the pancreas and liver at 5 weeks posttransplantation (Fig. 6E).

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BACH1 was clearly present in the nuclei of the control pancreaticcancer cells. E-cadherin was more homogeneously stained in cellclusters of AsPC-1/sgBACH1-2 than in those of control cells in thepancreas. A clearer accumulation of E-cadherin in the cell–cell contact
region was apparent in BACH1-deﬁcient cells compared with thesiBACH1-1

siBACH1-2

AsPC-1
Wound healing (%)

siCont.

A

control cells. The metastatic cells in the liver showed similar expression
patterns of E-cadherin between AsPC-1/sgCont and AsPC-1/
sgBACH1-2. These results indicate that BACH1 is not required fortumor proliferation in the pancreas, but is required for efﬁcientmetastases in vivo.

0 hour

24 hours

100

**
**

75
50
25
0

siCont.

B
Panc-1

exBACH1

0 hour

24 hours

*

100
75
50
25
0

EV

exBACH1

C
siCont.

siBACH1-1

siBACH1-2

Invasion

SW1990siCont.

Migration

Invasion

1286 Cancer Res; 80(6) March 15, 2020

siBACH1-1

siBACH1-2

Relative migratory cell number

Relative invasive cell number

Migration

Relative invasive cell number

AsPC-1

Relative migratory cell number

Wound healing (%)

EV

1
2
siBACH1

Figure 4.
BACH1 promotes cell migration andinvasion. A, Wound-healing assay of
BACH1-silenced AsPC-1 cells. Scrambled siRNA was used as control. Representative photos (left) and area ofwound closure (right) are shown. Scalebar, 100 mm. B, Wound-healing assay
of BACH1-overexpressing Panc-1 cells.
Empty vector (EV) was used ascontrol. Representative photos andarea of wound closure are shown. Scalebar, 1,000 mm. C, Transwell assay of
BACH1-silencing AsPC-1 and SW1990
cells. Scrambled siRNA was used ascontrol. Representative photos andnumbers of migration or invasion
cells are shown. Scale bar, 100 mm.
All data are presented as mean  SD,
with P values from the Student t test.
, P < 0.05;   , P < 0.01.

1.5

**
**

1.0
0.5
0.0
2
siCont. 1
siBACH1
1.5

**
**

1.0
0.5
0.0

1.5

2
siCont. 1
siBACH1

*
*

1.0
0.5
0.0

1.5

2
siCont. 1
siBACH1

**
**

1.0
0.5
0.0

2
siCont. 1
siBACH1CANCER RESEARCH

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Published OnlineFirst January 9, 2020; DOI: 10.1158/0008-5472.CAN-18-4099

Addiction of Pancreatic Cancer to BACH1 in EMT

ARNA-seq DOWN

ChIP-seq AsPC-1(≥ 1.5 times, FDR ≤ 0.05)

total 5,543 genes

total 1,466 genes

RNA-seq UP

ChIP-seq SW1990(≥ 1.5 times, FDR ≤ 0.05)

1,829

997

total 722 genes

146

0
461

FOXA1
PKP2
CLDN3
CLDN4

0

total 4,638 genes

3,065
1,054

269
0

65

54

SNAI2

0

169
27

B
Negative region

E1 (Positive region)

HMOX1

TOM1

[0 - 2.38][0 - 145][0 - 2.38][0 - 145][0 - 2.38][0 - 145][0 - 2.38]

BACH1
Input

SW1990

BACH1Input
Region 1

FOXA1
BACH1
Input

SW1990

TTC6

CLDN4

[0 - 2.78][0 - 13][0 - 4.46][0 - 4.41][0 - 2.78][0 - 13][0 - 4.46][0 - 4.41][0 - 2.78][0 - 13][0 - 4.46][0 - 4.41][0 - 2.78][0 - 13][0 - 4.46]

10 kb

C

200
100 P = 0.090
0
NRS BACH1 NRS BACH1
Negative
E1
region

1,000
750
500
250
0
NRS BACH1 NRS BACH1
Negative
E1
regionRelative fold enrichment

P = 0.079

FOXA1
P = 0.0059

3 P = 0.061

2

1

0

NRS BACH1 NRS BACH1
Region 1

Relative fold enrichment

Relative fold enrichment

300

1 kb

20 kb

HMOX1

Relative fold enrichment

SW1990

CLDN3

PKP2

[0 - 4.41]

BACH1
Input

AsPC-1

1 kb

SNAI2

9
6
3

NRS BACH1 NRS BACH1
Region 1

3

P = 0.012

2
1
0
NRS

BACH1

NRS

BACH1

Region 2

12

0

1 kb

Relative fold enrichment

AsPC-1

10 kb

Region 2

Relative fold enrichment

AsPC-1SNAI2[0 - 145]

15

10

5

0

Region 2

Figure 5.
BACH1 directly controls a set of EMT-related genes. A, Venn diagram of genes showing  1.5-fold up (RNA-seq UP) and down (RNA-seq DOWN) regulation in BACH1
knockdown samples compared with control samples from RNA-seq (Fig. 2) and putative target genes of BACH1, which were detected in ChIP-seq analysis on AsPC-1
and SW1990. B, ChIP-seq binding proﬁles for the BACH1 in AsPC-1 and SW1990. C, ChIP-qPCR analysis of HMOX1, FOXA1, and SNAI2 in AsPC-1 and SW1990 cells.
Relative fold change is normalized to Normal Rabbit Serum (NRS). All data are presented as mean  SD, with P values from the Student t test.

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A

sgBACH1-1 Target sequence

sgBACH1-2 Target sequence

Reference
sgBACH1-1
sgBACH1-2

Relative mRNA expression

2

**
*

sgCont.
sgBACH1-1
sgBACH1-2
n.s.
n.s.

(kDa)
150

E-cadherin
100

n.s.
n.s.

100

BACH1

37
25

CDH1 OCLN FOXA1 VIM SNAI2
Primary tumor

Liver metastasis

0.8
0.6
0.4
0.2

P = 0.47

0.0

sgCont.

121086

P = 0.0025

420sgCont.

sgBACH1-2

Peritoneal metastasis

sgBACH1-2

4030

P = 0.0032

20
10
0

sgCont.

α-BACH1

E

Liver(Metastasis
lesion)

2

GAPDH

1.0

Pancreas(Primary
tumor)

175

Number of metastasis

Pancreas weight (g)****sgBACH1
sgCont.

1

0

D

C

**
**

3

Number of metastasis

B

sgBACH1-2

α-E-cadherin

sgCont.

sgCont.

sgCont.

sgCont.

200 x

400 x

200 x

400 x

sgBACH1-2

sgBACH1-2

sgBACH1-2

sgBACH1-2

200 x

400 x

200 x

400 x

sgCont.

sgCont.

sgCont.

sgCont.

200 x

400 x

200 x

400 x

sgBACH1-2

sgBACH1-2

200 x

400 x

sgBACH1-2

200 x

High expression of BACH1 is correlated with poor prognosis
IHC analysis of clinical specimens was performed to investigate if
BACH1 expression is correlated with clinicopathologic factors andprognosis. For this purpose, we generated mAb against human
BACH1. On the basis of the intensity of staining, patients wereclassiﬁed into three groups (weak, moderate, and strong; Fig. 7A).
For the following analysis, these three groups were collapsed into twogroups: strong staining intensity was used as the BACH1-high expres-1288 Cancer Res; 80(6) March 15, 2020

Figure 6.
BACH1 promotes metastasis but nottumor formation. A, The sequences of
two sgRNAs for BACH1 and its corresponding insertion and deletion sites
in the human genome.  and - indicate
the presence of the same base in all
sequences and the gap, respectively.
B, Relative expression levels of theindicated transcripts of genes by
qRT-PCR (relative to ACTB as a control). All data are presented as mean SD, with P values from the Student t
test.  , P < 0.05;   , P < 0.01; n.s., notsigniﬁcant. C, Immunoblot analysis of
BACH1 and E-cadherin in BACH1WT and KO AsPC-1 cells. D, Pancreas
weight and number of liver and peritoneal metastasis (WT, n ¼ 17; KO,
n ¼ 18). The lower end of the box
shows 25% of the data, the upper
end shows 75%, the middle line
shows the median value, and thebeard shows the maximum value or
minimum value. P values are fromthe Student t test. E, Immunocytochemistry analysis of BACH1 andE-cadherin in the primary tumor
and liver metastasis lesion. Magniﬁcation, 200 or 400.

sgBACH1-2

400 x

sion group, whereas the groups of weak and moderate staining
intensities were combined to form the BACH1-low expression group.
There was no signiﬁcant difference in clinicopathologic factors
between these two groups (Supplementary Table S4). However, overall
survival (OS) rate was signiﬁcantly lower in the BACH1-high expression group (Fig. 7B left). Similar results were obtained using threegroups (weak, moderate, and strong; Fig. 7B right). In univariate
analysis, lymph node metastasis, distant metastasis, and BACH1-high

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Published OnlineFirst January 9, 2020; DOI: 10.1158/0008-5472.CAN-18-4099

Addiction of Pancreatic Cancer to BACH1 in EMTA

Weak
BACH1 Expression

Overall survival

1.00

High(28): strong
Low(88): weak + intermediate

0.75
0.50
0.25
0.00

Log-rank
P = 0.021
0

0.50
0.25

0

D

2,000
1,500
1,000
500

0.75

BACH1 Expression
High(42)
Low(134)

0.50

Log-rank

0.25

0

Low
High
BACH1 Expression
1.00

FOXA1 Expression
High (57)
Low (119)

0.75
0.50
Log-rank
P = 0.0033
025 50 75
Time (months)

G100

F 1.00Overall survival

E
Overall survival

P < 0.0001

0.00

0

0.00

25 50 75 100
Time (months)

1.00

2,500

0.25

BACH1 Expression
Weak(32)
Intermediate(56)Strong(28)

0.75

0.00

25 50 75 100
Time (months)

Overall survival

Normalized BACH1 mRNA
expression value

C

Strong1.00
Overall survival

B

Moderate

25 50 75
Time (months)

100

FOXA1 and BACH1 Expression

0.75

BACH1 High/FOXA1 High (14, A)
BACH1 High/FOXA1 Low (28, B)
BACH1 Low/FOXA1 High (43, C)
BACH1 Low/FOXA1 Low (91, D)

0.50Interaction

P

A-B
A-C
A-D
B-C
B-D
C-D

0.2416
0.0316
0.4265<0.0001
0.00030.00114

0.25
0.00
0

75
50
25
Time (months)

100

BACH1
FOXA1

Epithelial genes
Figure 7.
BACH1-high expression is correlated with poor prognosis. A, BACH1 IHC of PDAC specimens was performed and classiﬁed into three groups according to staining
ratio (weak, moderate, and strong). Weak and moderate were classiﬁed as BACH1-low group, and strong was classiﬁed as BACH1-high group. Magniﬁcation, 200.
B, Overall survival curve by Kaplan–Meier method between the two groups (high and low) based on BACH1 expression levels (left) or the three groups (strong,
moderate, and weak; right). P value was obtained by log-rank test. C, RNA-sequencing data obtained from the TCGA (n ¼ 176) were classiﬁed into two groups(BACH1 Low and High), with cut-off values obtained from the ROC curve. D, Overall survival curve by the Kaplan–Meier method between the two groups in C isshown. P value was obtained by log-rank test. E, RNA-sequencing data obtained from the TCGA (n ¼ 176) were classiﬁed into two groups (FOXA1 Low and High),with cut-off values obtained from the ROC curve. Overall survival curve by the Kaplan-Meier method between the two groups is shown. P value was obtainedby log-rank test. F, Overall survival curve by the Kaplan–Meier method between the four groups (combination of BACH1 and FOXA1) is shown. P value was obtainedby log-rank test. G, A model of GRN for epithelial gene regulation. This structure suggests that steady state of the network is sensitive to signals that regulate BACH1.

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expression were detected as prognostic factors for OS. Multivariate
analysis with the Cox proportional hazard model (28) revealed thatlymph node metastasis and BACH1 high expression were the independent prognostic factors for OS (Supplementary Table S5). These
results indicate that high expression of BACH1 is correlated with poor
prognosis in PDAC.
When it is necessary to rely on mRNA expression, activity oftranscription factors such as BACH1 may be more accurately assessedby combining expression levels of both the transcription factor andthose of downstream target genes as an indication of the activity of thetotal transcriptional network. To test this idea, RNA-sequencing andclinical data were obtained from the TCGA database. The data wereseparated into two groups based on BACH1 mRNA expression levels;
BACH1 low and high (Fig. 7C). OS rate of the BACH1-high expression
group was signiﬁcantly lower than that of the BACH1-low expression
group (Fig. 7D), but there was no signiﬁcant difference in clinicopathologic factors (Supplementary Table S6). In contrast, the expression of FOXA1 was positively correlated with OS rate (Fig. 7E). When
FOXA1 and BACH1 were combined (Fig. 7F), the OS rate was thelowest in the group with BACH1-high expression and FOXA1-low
expression, whereas it was the highest in the group with low BACH1
and high FOXA1 expression. Thus, this type of combinational analysis
has improved patient stratiﬁcation when compared with the usage ofmRNA levels of BACH1 or FOXA1 mRNA levels alone. Other combinations of genes showed similar improvements (Supplementary
Fig. S7). For example, the BACH1 high and CDH1 low group showed
poorer survival than the BACH1-low and CDH1-high group. However,
low expression of both BACH1 and CDH1 showed the highest OS.
Furthermore, when used on its own, high CDH1 expression showed
poorer survival than the CDH1 low group. Therefore, BACH1 expression may provide a useful marker for stratiﬁcation of patients with
PDAC.

Discussion
EMT is one of the mechanisms by which cancer cells acquire
metastatic potential through loss of adherence to surrounding cells
and by enhancing mobility and invasiveness (29–32). EMT is characterized by decreased quantities of epithelial adhesion molecules suchas E-cadherin and increased amounts of mesenchymal molecules
typiﬁed by vimentin (33). We showed here that BACH1 represses
the expression of a set of epithelial genes to maintain EMT and topromote metastasis in PDAC.
We found that genes important for the regulation or structure ofepithelia such as FOXA1, PKP2, CLDN3, and CLDN4 were directly
repressed by BACH1, whereas EMT-promoting transcription factor
SNAI2 was directly activated by BACH1 in PDAC. The results ofcomparison of siRNA and knockout experiments in AsPC-1 cells andoverall survival analysis suggest that FOXA1 may be one of theimportant targets of BACH1 in PDAC. In addition to these genes,
CDH1 appears indirectly but tightly regulated by BACH1. We suggestthat the observed suppression of the epithelial phenotype and repression of CDH1 by BACH1 can be explained by the structure of the gene
regulatory network (GRN) discovered in this study. BACH1 inhibits
the expression of CDH1 by repressing FOXA1 and activating SNAI2,
the activator and repressor genes of CDH1, respectively (18, 24). This
study also suggests the presence of additional transcription factor(s)for activating CDH1 upon reduction of BACH1 function. Whenepithelial genes are aggregated, BACH1 is suggested to form a GRN
involving a coherent type 2 feed-forward loop (34) in PDAC cells(Fig. 7G). Such a circuit structure is expected to confer not only

1290 Cancer Res; 80(6) March 15, 2020

efﬁcient suppression of the epithelial phenotype, but also rapid
reexpression of this epithelial phenotype by transcription factors
including FOXA1 once BACH1 is inactivated. However, the responseof BACH1-overexpressing Panc-1 cells to BACH1 knockdown suggests that this GRN may fail to regulate epithelial genes in a dynamic
manner under some circumstances. Our ﬁndings are consistent with
epigenetic regulation by BACH1 (10) and warrant further studies onreversibility and irreversibility of BACH1-mediated regulation.
The reduction of SNAI2 expression in response to both knockdown
and overexpression of BACH1 points to the importance of a proper
regulation of the expression and function of SNAI2. SNAI2 expressionis also regulated by XBP-1, a regulator of endoplasmic stress response,and KLF10, an effector of TGFb signaling pathway, in cancer
cells (35, 36). The promotion of motility and scattering of pancreaticcancer cells by SNAI2 overexpression are observed only when Rhoassociated protein kinase ROCK1/2 is inhibited (37). Therefore, theﬁnal output of BACH1 on SNAI2 and EMT may be modulated by its
protein amount and other factors converging upon SNAI2.
Recently, Pastushenko and colleagues showed the presence ofsubspecies of PDAC cells, each representing a transition stage of EMT,
based on cell surface markers (38). Among them, the cells exhibiting
high metastatic potential are not the most advanced stage of EMT but
an earlier stage (38). This highly metastatic stage may be conﬁgured by
BACH1, which represses the expression of epithelial genes andactivates only SNAI2 among mesenchymal genes. Another importantpossibility emerging from this study is that BACH1 is relevant to the
dynamic nature of EMT and MET upon metastasis. There are two
important steps in forming metastatic lesions of cancer cells. One is the
migration of cancer cells caused by EMT and the other is the initiationof colonization and growth by MET at the metastatic lesions (39). We
surmise that heme may be one of triggers of MET because BACH1 isexported out of the nucleus and inactivated by heme (40). The liver is
one of the organs with very active heme biosynthesis in the body. When
incipient metastatic cancer cells with BACH1-high expression reachthe liver, heme may inactivate the BACH1 protein, causing MET.
Consistent with this idea, there was no apparent difference in theexpression of E-cadherin between the metastatic control and BACH1deﬁcient AsPC-1 cells in the liver.
Metastasis and recurrence aggravate cancer prognosis (41). Our
results suggest that a higher expression of BACH1 causes poor
prognosis of PDAC. While BACH1 can be inactivated by nuclear
exclusion (42) or phosphorylation (43), we showed that this issue canbe circumvented by analyzing both expression of BACH1 and its target
genes like FOXA1. Prediction of prognosis and other phenotypes ofcancer can be improved by knowledge of key GRNs. Recently, Roe andcolleagues showed that, while FOXA1 acts as an antagonist of EMT, it
can induce enhancer remodeling to promote metastasis of a certain
subtype of PDAC (44). Therefore, a combination of BACH1 anddownstream target genes can be an excellent prognostic biomarker of
PDAC (Fig. 7F).
During the course of revision of this article, it has been reported thatlung cancer metastasis is promoted by BACH1 in a RAS-driven mousemodel (45, 46). Our results suggest that diverse epithelial cancers may
utilize BACH1 to alter transiently their EMT phenotype. This is consistent with a recent ﬁnding that, while loss of E-cadherin increases
invasion, it is required for systemic dissemination and seeding phases ofmetastasis (47). One article also reports that SNP in the 30 untranslated
region of human BACH1 mRNA is associated with pancreatic cancer,
suggesting BACH1 as a tumor suppressor (48). Because BACH1 isrequired for a proper mitosis (41), it may also play a tumor suppressor
function in some stages of cancer formation, possibly in earlier stages. It

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Published OnlineFirst January 9, 2020; DOI: 10.1158/0008-5472.CAN-18-4099

Addiction of Pancreatic Cancer to BACH1 in EMT

will be important to unveil how the function of BACH1 is regulated
dynamically from incipient to metastatic processes of cancer.

Disclosure of Potential Conﬂicts of Interest
No potential conﬂicts of interest were disclosed.

Authors’ Contributions
Conception and design: M. Sato, M. Matsumoto, K. Igarashi
Development of methodology: M. Sato, M. Matsumoto, H. Nishizawa
Acquisition of data (provided animals, acquired and managed patients, provided
facilities, etc.): M. Sato, M. Matsumoto, Y. Saiki, M. Alam, H. Nishizawa, M. Rokugo,
A. Brydun, M.K. Kaneko, R. Funayama, M. Ito, K. Nakayama, M. Unno
Analysis and interpretation of data (e.g., statistical analysis, biostatistics,
computational analysis): M. Sato, M. Matsumoto, Y. Saiki, K. Igarashi
Writing, review, and/or revision of the manuscript: M. Sato, M. Matsumoto,
M. Unno, K. Igarashi
Administrative, technical, or material support (i.e., reporting or organizing data,
constructing databases): M. Matsumoto, Y. Saiki, S. Yamada, Y. Kato, M. Unno
Study supervision: M. Matsumoto, M. Unno, K. Igarashi

Acknowledgments
M. Matsumoto received Grants-in-Aid 19K07680, 16K07108, and 22700869
from the Japan Society for the Promotion of Science. Y. Kato received a grantJP18am0101078 from Agency for Medical Research and Development, Japan. K.
Igarashi received Grants-in-Aid 15H02506, 24390066, 23659168, and 18H04021
from the Japan Society for the Promotion of Science. We are grateful for stimulating
discussions with members of Department of Biochemistry and Department ofSurgery, and Jelle Bonthuis for comments on the manuscript. We also acknowledge
the technical support of the Biomedical Research Core of Tohoku University
Graduate School of Medicine.

The costs of publication of this article were defrayed in part by thepayment of page charges. This article must therefore be hereby marked
advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate
this fact.

Received December 31, 2018; revised July 12, 2019; accepted January 6, 2020;
published ﬁrst January 9, 2020.

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CANCER RESEARCH

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Published OnlineFirst January 9, 2020; DOI: 10.1158/0008-5472.CAN-18-4099

BACH1 Promotes Pancreatic Cancer Metastasis by Repressing
Epithelial Genes and Enhancing Epithelial−Mesenchymal Transition
Masaki Sato, Mitsuyo Matsumoto, Yuriko Saiki, et al.
Cancer Res 2020;80:1279-1292. Published OnlineFirst January 9, 2020.

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