A Feedback Loop Comprising EGF/TGF-Α Sustains TFCP2

Author Manuscript Published OnlineFirst on March 19, 2020; DOI: 10.1158/0008-5472.CAN-19-2908 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

1 A Feedback loop comprising EGF/TGF-α Sustains TFCP2-mediated 2 Breast Cancer Progression 3 4 Yi Zhao1,†, Neha Kaushik1,†, Jae-Hyeok Kang1, Nagendra Kumar Kaushik2, Seung Han Son1, 5 Nizam Uddin3, Min-Jung Kim4, Chul Geun Kim1,*and Su-Jae Lee1,* 6 7 1Department of Life Science, Research Institute for Natural Sciences, Hanyang University, Seoul 8 04763, Republic of Korea 9 2Plasma Bioscience Research Center, Applied Plasma Medicine Center, Department of Electrical and 10 Biological Physics, Kwangwoon University, Seoul 01897 11 3Center for Cell Analysis & Modeling, University of Connecticut Health Center, 400 Farmington Ave, 12 Farmington, CT. 06032, USA 13 4Laboratory of Radiation Exposure and Therapeutics, National Radiation Emergency Medical Center, 14 Korea Institute of Radiological and Medical Sciences, Seoul, South Korea 15 16 †These authors contributed equally to this work. 17 18 Running Title: TFCP2 promotes triple-negative breast cancer progression 19 20 Keywords: alpha-globin transcription factor, TFCP2; epithelial-mesenchymal transition, 21 EMT; cancer stem cell, CSC; epidermal growth factor, EGF; transforming growth factor 22 alpha, TGF-α. 23 24 *Correspondence should be addressed to: Su-Jae Lee, PhD. Professor, Laboratory of 25 Molecular Biochemistry, Department of Life Science, Hanyang University, 17 Haengdang-Dong, 26 Seongdong-Ku, Seoul 04763, Korea. Phone: 82-2-2220-2557, Fax: 82-2-2299-0762. E-mail: 27 [email protected] (S.J.L.) or Co-corresponding: Dr. Chun Geun Kim, Department of Life Science, 28 Research Institute for Natural Sciences, Hanyang University, Seoul 04763, Korea. Email: 29 [email protected] (C.G.K.) 30 31 Conflict of Interest 32 The authors declare no potential conflicts of interest. 33 34 Word Counting: 4999 35 Total number of figures: 6 36 Total number of tables: 0 37 38 39 40 41 42 43

Downloaded from cancerres.aacrjournals.org on September 28, 2021. © 2020 American Association for Cancer Research. Author Manuscript Published OnlineFirst on March 19, 2020; DOI: 10.1158/0008-5472.CAN-19-2908 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

44 Abstract

45 Stemness and epithelial-mesenchymal transition (EMT) are two fundamental characteristics of

46 metastasis that are controlled by diverse regulatory factors, including transcription factors. Compared

47 with other subtypes of breast cancer, basal-type or triple-negative breast cancer (TNBC) have high

48 frequencies of tumor relapse. However, the role of alpha-globin transcription factor CP2 (TFCP2) has

49 not been reported as an oncogenic driver in those breast cancers. Here we show that TFCP2 is a

50 potent factor essential for EMT, stemness, and metastasis in breast cancer. TFCP2 directly bound

51 promoters of epidermal growth factor (EGF) and transforming growth factor alpha (TGF-α) to regulate

52 their expression and stimulate autocrine signaling via epidermal growth factor receptor (EGFR).

53 These findings indicate that TFCP2 is a new anti-metastatic target and reveal a novel regulatory

54 mechanism in which a positive feedback loop comprising EGF/TGF-α and AKT can control malignant

55 breast cancer progression.

57 Significance

58 TFCP2 is a new anti-metastatic target that controls TNBC progression via a positive feedback loop

59 between EGF/TGF-α and the AKT signaling axis.

73 Introduction

74 Tumor metastasis is a multistep process that occurs through local invasion, intravasation, transport,

75 extravasation, and colonization, resulting in the dissemination of tumor cells from their primary site to

76 a distant site where secondary tumors are formed. In the tumor metastasis process, EMT and cancer

77 stem cell (CSC)-like characteristics make primary contributions to drive tumor initiation and

78 development (1). During the EMT process, epithelial cells shift toward a mesenchymal phenotype,

79 with the loss of cell-cell contacts and adhesions and an increased ability for migration and invasion

80 during morphogenesis (2). After the EMT program is activated, cancer cells can also exhibit high

81 plasticity by acquiring stem-like traits that endow them with the potential for tumor initiation and

82 metastasis, all of which promote cancer progression. Hence, tumor cells that undergo EMT and

83 possess CSC-like features have greater metastatic potential and result in poorer outcomes in cancer

84 patients.

85 TFCP2 is a member of the CP2/Grainyhead family of transcription factors that are conserved

86 throughout metazoans and fungi. In mammals, the CP2/Grainyhead family consists of two distinct

87 subfamilies: the first includes three Grainyhead-like factors currently termed GRHL1–3, and the other

88 subfamily consists of three factors known as TFCP2 (CP2c), TFCP2L1 (CRTR1), and UBP1 (CP2a

89 and CP2b) (3,4). Among these, TFCP2, also known as LSF, was first identified as a transcriptional

90 activator factor of the Simian virus 40 (SV40) late promoter in HeLa cells (5) and of the murine α-

91 globin promoter (6). As mentioned earlier, TFCP2 regulates a diverse range of cellular and viral

92 promoters (7,8), is expressed in all mammalian cell types and plays an important role in cell cycle

93 regulation (8). It facilitates entry into G1/S phase of the cell cycle, promotes DNA synthesis, and

94 functions as an antiapoptotic factor (9). Overexpression of TFCP2 may promote transformation and

95 cancer cell survival. Recent studies suggest that TFCP2 may also play a role in the pathogenesis of

96 colon, lung, and hepatocellular carcinoma (10-12). Moreover, TFCP2 has been shown to activate

97 osteopontin and matrix metalloproteinase-9 expression to regulate invasion, metastasis, and

98 angiogenesis in HCC (13,14). Although the expression and regulatory roles of TFCP2 have been

99 reported individually in some types of cancer, there is no evidence of TFCP2 involvement in

100 metastatic TNBC progression.

101 The EGFR is a major oncogene identified in a variety of human cancers, including breast cancer

102 (15-17). These receptors are activated by ligand binding and consequent receptor homo- and

103 heterodimerization, which leads to activation of the kinase domain, auto- and transphosphorylation of

104 their intracellular domains, and the initiation of signaling (18). Many different ligands, including EGF-

105 like molecules, TGF-α and neuregulins, activate the receptor by binding to the extracellular domain

106 and inducing the formation of receptor homodimers or heterodimers (19). Genes in the EGF signaling

107 pathway are among the most frequently activated oncogenes in breast cancer (20). Clinical studies

108 have shown that TNBC is more aggressive than other breast cancers and TNBC patients have a

109 worse prognosis than those with other breast cancer subtypes (21). More than 60% of TNBCs

110 express EGFR, which may serve as a prognostic marker for TNBC outcomes (22). Although EGFR

111 has been widely studied in breast cancer tumorigenesis, the mechanism underlying TFCP2-induced

112 malignancy remains unknown. The goal of this study was to determine the role of TFCP2 in breast

113 cancer progression, with a focus on EMT, stemness, and metastasis. Using basal-like breast cancer

114 cell lines and NOD/SCID gamma (NSG, 5–6 weeks old) mouse models, we investigated the

115 mechanisms by which TFCP2 affects the EGFR signaling axis positively or negatively in TNBCs.

116

117 Materials and Methods

118 Materials and reagents

119 All breast cell lines (MCF10A, MCF7, SKBR3, T47D, BT474, MDA-MB453, MDA-MB231, BT549,

120 Hs578T, and MDA-MB361) were purchased from the American Type Culture Collection (ATCC;

121 Manassas, VA, USA), cultured in the indicated media and incubated at 37°C with 5% CO2 according

122 to standard protocols. They were routinely tested for mycoplasma contamination using PCR

123 methods and cultured cell lines were often treated with Plasmocin™ treatment (InvivoGen, San

124 Diego, CA) to remain contamination-free. Cells were used at least less than 20 passages number

125 for 3 months, but were not independently authenticated. After each thawing, cells were confirmed

126 as mycoplasma-negative prior to experiments. The p-EF1α (control vector), p-EF1α-CP2 (TFCP2

127 WT vector), TFCP2 D153A, and LSFdn vectors were received by Hanyang University, Department of

128 Life Science, Seoul, Korea, SNAI1 (pBabe puro Snail) and pGL3-basic vectors were purchased from

129 Addgene (Seoul, Korea). EGF (epidermal growth factor, #AFL236) and TGF-α (transforming growth

130 factor alpha, #239-A) were purchased from R&D Systems, Inc. Antibodies and Inhibitors information

131 are listed in Supplementary Table S1.

132 Transfection

133 p-EF1α, p-EF1α-CP2, TFCP2 D153A, LSFdn and SNAI1 vectors or siRNAs were transfected into the

134 appropriate cells using Lipofectamine reagents (Invitrogen, Carlsbad, CA, USA) according to the

135 manufacturer’s instructions. Cells were harvested 48 h after transfection for subsequent experiments.

136 All siRNAs were purchased from Genolution Pharmaceuticals, Inc. (Seoul, Korea).

137

138 Scratch, soft agar, morphology (collagen coating), and Transwell assays

139 For the wound-healing (scratch) assay, cells were seeded in 35 mm cell culture dishes and cultured

140 until 80-90% confluent. Afterwards, a 200 μl pipet tip was used to make a scratch wound across the

141 middle of the cell monolayer. Images were taken with Olympus IX71 fluorescence microscope

142 (Olympus, Seoul, Korea) immediately after and 24 h after the scratch was made. The rate of cell

143 migration from at least three independent experiments was calculated with ImageJ. To examine

144 anchorage-independent growth, cells were suspended in 0.4% agar in growth medium and analyzed

145 as previously described (23). For morphological analysis, cells were seeded at medium confluency

146 directly into Corning® BioCoat™ Collagen I-coated plates (Corning Inc., Corning, NY, USA) and

147 photographed 24 h later. Migration assays were performed using Boyden chambers (Corning Inc.,

148 Corning, NY, USA). Cells (2 × 104) in 200 μL of serum-free medium were seeded into the upper

149 chamber, and 800 μL of medium with 10% FBS was added to the bottom chamber as a

150 chemoattractant. Migratory cells were stained using a Diff-Quick kit (Fisher, Pittsburgh, PA, USA) then

151 imaged and counted. The invasion assays were carried out in accordance with the migration assays

152 except that each Transwell chamber was coated with growth factor-reduced Matrigel (BD Biosciences,

153 San Jose, CA, USA). All experiments were performed in triplicate.

154

155 Spheroid assays

156 For the sphere formation assays, sphere size was determined using Motic Images Plus 2.0 software

157 (Motic, Hong Kong) in three randomly chosen visual fields each day until day 4 after the cells were

158 seeded. For colony formation assays, single-cell suspensions containing breast cells were plated in

159 96-well cell culture plates, and colony formation was observed at different time points for 2 weeks.

160 Colonies were photographed and their diameter was measured (24).

161

162 IHC analysis

163 For IHC experiments, paraffin-embedded tissue sections were deparaffinized in xylene and then

164 rehydrated in a graded series of ethanol (95%, 90%, 80% and 70%) followed by PBS treatment.

165 Epitopes were retrieved with 20 mg/mL proteinase K in PBS containing 0.1% Triton X-100. Sections

166 were incubated overnight with appropriate primary antibodies at 4°C and then processed as

167 previously described (25).

168

169 RNA preparation and q-PCR

170 Total RNA was prepared using TRIzol reagent (Invitrogen, Carlsbad, CA, USA), and RNA quality was

171 measured using a NanoDrop spectrophotometer (ND1000, NanoDrop Technologies, Wilmington, DE,

172 USA). qRT-PCR was performed using a KAPA SYBR FAST qPCR kit (KAPA Biosystems, Wilmington,

173 DE, USA) according to the manufacturer’s procedures. Reactions were performed in a Rotor Gene Q

174 instrument (Qiagen, Hilden, Germany), and the results were expressed as the fold change relative to

175 the control sample calculated using the ΔΔCt method. β-actin served as an internal normalization

176 control. All primers were purchased from DNA Macrogen (Seoul, Korea). All primers used in this study

177 are listed in Supplementary Table S2 and S3.

178

179 Western blotting

180 Total cellular protein was extracted in cold lysis buffer (Tris–HCl [40 mM, pH 8.0], NaCl [120 mM], and

181 Nonidet-P40 [0.1%]) enriched with protease inhibitors and was quantified using a BSA assay. Protein

182 lysates were separated by SDS-PAGE and transferred onto nitrocellulose membranes (Amersham,

183 Arlington Heights, IL, USA). The membranes were then blocked in PBST containing 5% milk and

184 probed with the indicated primary antibody followed by the corresponding HRP-conjugated secondary

185 antibody. Finally, the protein bands were detected using chemiluminescence (Amersham) according

186 to the manufacturer’s instructions.

187

188 Flow cytometry analysis

189 To assess cell death, cells were incubated in the listed conditions for the desired time, after which

190 they were labeled with propidium iodide (PI; Sigma, 50 ng/mL), incubated for 20 min at 4°C, and

191 analyzed immediately. To detect the cancer stemness marker CD44 and CD24, 1 × 106 of TFCP2-

192 knockdown cells were harvested by trypsin digestion, washed and resuspended in PBS. An R-

193 phycoerythrin (PE)-conjugated anti-CD44 monoclonal antibody and FITC conjugated anti-CD24

194 antibody (Miltenyi Biotec Inc., Bergisch Gladbach, Germany) were used for detection. All data were

195 analyzed using CellQuest software (BD Biosciences) and repeated three times.

196

197 ELISA

198 Cellular protein was prepared as western blotting. The concentrations of total and phosphorylated

199 EGFR were measured using human EGFR (pY1068) and total EGFR ELISA kits (Abcam, Cambridge,

200 UK), respectively, according to the manufacturer’s instructions.

201

202 ChIP assays

203 Prior to performing ChIP experiments, cells were cross-linked with 4% paraformaldehyde. ChIP

204 assays were performed using an EZ-ChIP™ kit (EMD Millipore, Burlington, MA, USA) according to the

205 manufacturer's instructions. Immunoprecipitation was performed using an anti-TFCP2 antibody or a

206 rabbit isotype control IgG (Upstate Biotechnology, Lake Placid, NY, USA). PCR was performed using

207 primers specific to the EGF and TGF-α gene promoter regions shown in Supplementary Table S3.

208

209 Construction of luciferase reporter plasmids

210 The human EGF and TGF-α promoter regions were obtained by PCR, using genomic DNA from

211 MDA-MB231 cells as a template. The promoters of EGF and TGF-α were generated by PCR using

212 primers shown in Supplementary Table S3. They were subcloned into XhoI and HindIII sites of pGL3-

213 basic vector (Addgene, Seoul, Korea). All constructs were verified by sequencing.

214

215 Luciferase Reporter Assay

216 HEK293T cells were seeded in a 24-well plate, at 60-70% confluence, cells were co-transfected using

217 Lipofectamine 2000 according to manufacturer’s manual. In brief, each well was transfected with

218 300ng of reporter constructs and 300ng of pRL-CMV-Renilla plasmid (Promega, Wisconsin, USA) for

219 48 h. Luciferase activity was measured using a dual-luciferase reporter assay system (Promega,

220 Wisconsin, USA) according to manufacturer’s instructions and normalized to Renilla luciferase activity.

221 All experiments were performed in triplicate.

222

223 In vivo xenografts and metastasis assays

224 All animal procedures were performed according to the guidelines of the Institutional Animal Care and

225 Use Committee of Academia Sinica. NSG mice (5–6 weeks old) were obtained from Orient Bio (Seoul,

226 Korea). For these experiments, 40 µL of metastatic MDA-MB231-LM1 breast cancer cells (1×106),

227 which were derived from lung lesions after colonization (shCtrl-LM1, shTFCP2-LM1), were injected

228 into the fourth mammary fat pad of NSG mice. Twice per week, the mice were weighed and tumor

229 size was determined using a digital caliper. Tumor volumes were assessed by measuring the length (l)

230 and width (w) and calculated using the following formula: (shortest diameter2) × (longest diameter/2).

231 Mice were sacrificed 8–12 weeks after injection, and the lungs were removed and fixed in 9%

232 paraformaldehyde. Detectable tumor nodules on the surface of the entire lung were counted to

233 calculate the metastatic index. Tumor tissues were homogenized, and the expression of target genes

234 was analyzed by western blotting and qRT-PCR.

235

236 Immunofluorescence

237 For immunofluorescence staining, cells were plated onto glass coverslips, fixed with 4%

238 paraformaldehyde, and permeabilized with 0.1% Triton in PBS. Cells then incubated overnight at 4°C

239 with the appropriate primary antibody. The following day, Alexa Fluor 488-conjugated anti-rabbit or

240 anti-mouse and Alexa Fluor 546-conjugated anti-rabbit or anti-mouse (Molecular Probes, Eugene, OR,

241 USA) secondary antibodies were used to visualize the proteins. Cell nuclei were counterstained with

242 4′,6-diamidino-2-phenylindole (DAPI; Sigma, St Lois, MO, USA). Immunostained cells were observed

243 using an IX71 fluorescence microscope (Olympus, Tokyo, Japan).

244

245 Human tissue microarrays

246 Breast tissue microarray samples were obtained from US Biomax (BR1101, BR20814, BR1509;

247 Rockville, MD, USA). Healthy specimens were also included in each of the array blocks. Samples

248 were reviewed by a pathologist to confirm the diagnosis of breast carcinoma, histological grade, and

249 tumor purity. TFCP2, EGF and TGF-α levels were graded as 0, 1, 2, or 3 according to the intensity

250 scores.

251

252 GSEA, dataset evaluation and Kaplan-Meier analysis

253 GSEA was performed on diverse gene signatures by comparing gene sets from either the Molecular

254 Signature Database (MSigDB) database or published gene signatures. To analyze the expression of

255 TFCP2, TFCP2L1, and UBP1 in breast invasive carcinomas, previously published microarray data

256 under accession codes GSE41313, GSE1456, GSE20713, GSE7513, GSE2603 and GSE25055 were

257 reanalyzed. To examine the prognostic value of TFCP2, EGF and TGF-α, patient samples were

258 divided into two groups (low and high expression) for each gene, which were analyzed using the KM

259 plot program (http://kmplot.com/analysis/) as previously described (26).

260

261 Statistics

262 All experimental data are presented as the mean ± standard deviation (S.D.) of at least three

263 independent experiments. Statistical analyses were performed using an unpaired two-tailed

264 parametric Student’s t-test. Multiple group comparisons were made by ANOVA using PRISM 8.0

265 software (GraphPad, San Diego, CA, USA). Variances were confirmed to be similar between groups

266 that were being statistically compared, and p-values < 0.05 were considered significant. No samples

267 were excluded from the analysis. The investigators were not blinded to allocation during experiments

268 and outcome assessments.

269

270 Results

271 TFCP2 is upregulated and associated with poor survival in breast cancer

272 patients

273 To explore the association of CP2 family transcription factors in breast cancer, we utilized an online

274 database screening system to investigate their expression in normal and breast cancer tissues using

275 gene expression profiling interactive analysis (GEPIA) (27). Assessment of the dataset showed that

276 TFCP2 and UBP1 expression is comparatively higher in breast tumours than in normal tissues, but

277 not TFCP2L1 (Fig. 1A). To verify further, additionally, gene set enrichment analysis (GSEA) was

278 performed with data from the Molecular Signatures Database (MSigDB), which showed that TFCP2

279 expression is well-correlated with aggressive basal subtypes of breast cancer compared to the

280 luminal type (Fig. 1B; Supplementary Fig. S1) while UBP1 does not seem so, suggesting the possible

281 involvement of TFCP2 in basal type breast tumours. Consistent data were also observed in basal and

282 luminal breast cancer subtypes using a gene expression omnibus (GEO) dataset (28) and Gene

283 Expression-Based Outcome for Breast Cancer Online (GOBO, (29) datasets (Fig. 1C and D). In

284 agreement with the online database findings, quantification of TFCP2, TFCP2L1 and UBP1 mRNA

285 expression shows that the basal-type cell lines expressed high levels of TFCP2 compared to the

286 luminal cell lines (Fig. 1E). After validating the specificity of TFCP2 levels in malignant breast cancer,

287 we confirmed its expression in human tissue samples using tissue microarray analysis. Notably,

288 increased TFCP2 expression was observed in basal and high-grade breast carcinomas (Fig. 1F and

289 1G). Furthermore, Kaplan-Meier survival analysis (30) determined that high expression of TFCP2

290 correlates with poor survival in breast cancer patients independently among basal, luminal and HER2

291 subtypes (Fig. 1H). These observations strongly suggest that TFCP2 is primarily associated with

292 malignant breast cancer.

293 TFCP2 enhances EMT, metastasis, and stemness in breast cancer

294 To discover the pathological mechanism of TFCP2 upregulation in breast cancer, we screened

295 hallmarks of cancer with the GSEA database in breast cancer. Gene ontology enrichment analysis

296 showed that TFCP2 is positively correlated with signature gene sets relating to EMT and cancer

297 stemness (Fig. 2A). When we ectopically introduced TFCP2 in luminal MCF7 and SKBR3 breast

298 cancer cells to examine EMT, MCF7 and SKBR3 cells showed a reduction in epithelial features and

299 an increase in mesenchymal features as evidenced by the elongation of cells on the collagen-coated

300 surface, enhanced cell invasion and migration abilities and the induction of fibronectin (FN), N-

301 cadherin (CDH2) and vimentin (VIM) expression (Fig. 2B-2E; Supplementary Fig. S2A-S2D). Similar

302 results were also observed in MCF10A normal breast epithelial cells with TFCP2 overexpression

303 (Supplementary Fig. S2E-S2H). Prior to the TFCP2 overexpression experiments in MCF7, additional

304 experiments with TFCP2 family members TFCP2L1 and UBP1 were performed, which confirmed that

305 silencing of these genes did not affect the migration and invasion capabilities of Hs578T and MDA-

306 MB453 cells which expresses high level of TFCP2L1 and UBP1 respectively (Supplementary Fig.

307 S3A and S3B). In addition, TFCP2 knockdown (with siRNA#1, siRNA#2) mitigated these effects in

308 both MDA-MB231 and BT549 basal-type breast cancer cells (Supplementary Fig. S3C-S3H). Recent

309 studies have documented that the acquisition of CSC traits occurs with the EMT program (31,32) and

310 the induction of EMT can induce many of the defining characteristics of stem cells, including self-

311 renewal (33). In accordance with these studies and our GSEA analysis data (Fig. 2A), we tried to

312 determine the involvement of TFCP2 in the acquisition of stemness in breast cancer cells. The

313 sphere-forming or clonal efficiency of breast cancer cells was dramatically reduced after TFCP2

314 knockdown in both EGF-treated (a well-known EMT inducer) MCF7 and SKBR3 cells in a sphere-

315 permissive medium (Fig. 2F-2I). The inhibitory effect of TFCP2 on stem-like breast cells was observed

316 until several passages, as evidenced by limiting dilution sphere-forming assays with MCF7 cells

317 (Supplementary Fig. S3I). We also screened several CSC-related transcription factors, such as SOX2,

318 NANOG, and OCT4. qRT-PCR and immunofluorescence data showed that OCT4 was prominently

319 affected along with CD44 after TFCP2 knockdown in spheres formed from MCF7 or SKBR3 cells

320 (Supplementary Fig. S3J and S3K). EMT-related transcription factors have been reported to boost the

321 CD44+/CD24- subpopulation, as observed in breast CSCs (34). In agreement, flow cytometry analysis

322 revealed that the percentage of CD44-positive and CD24-negative cells were decreased in both

323 MCF7 and SKBR3 cells after TFCP2 knockdown (Fig. 2J). Additionally, we also performed sphere

324 formation assay and checked percentage of CD44+/CD24- by FACS analysis in TFCP2

325 overexpression system using MCF7 cells. We found that overexpressed TFCP2 can induce cancer

326 stemness in those MCF7 cells (Supplementary Fig. S3L and S3M). On the other hand, interestingly,

327 silencing of TFCP2 did not affect breast cancer cell proliferation, as confirmed by soft agar-

328 independent cell growth and cell death assays (Supplementary Fig. S3N-S3P). These results showed

329 that TFCP2 has the potential to regulate EMT and the CSC phenotype rather than cell proliferation

330 and death in breast cancer cells.

331

332 Silencing TFCP2 expression blocks EMT and stemness in vivo

333 We further investigated the effect of TFCP2 knockdown on metastasis in a breast cancer mouse

334 models by injecting LM1-MDA-MB231 cells into the fat pad (Fig. 3A). As shown in the knockdown

335 experiments, diminished TFCP2 expression reduced the formation of lung metastatic foci with

336 inhibition of EMT- and CSC-related transcription factors and markers such as FN, CDH2, VIM, OCT4,

337 and CD44 (Fig. 3B-J). However, tumor growth remained unaffected in these xenografts after TFCP2

338 knockdown (Supplementary Fig. S4A-S4C). Measurement of Ki67 and cleaved caspase 3 in

339 shTFCP2-injected mouse tissues confirmed that TFCP2 did not induce any cell death in breast

340 tumors (Supplementary Fig. S4D and S4E). These data further revealed a critical role of TFCP2 in

341 maintaining mesenchymal features to sustain EMT and metastasis with stemness in basal-type breast

342 cancer without affecting growth or cell death.

343 Since TFCP2 knockdown affects SNAI1 expression more effectively than the other EMT

344 transcription factors tested, we hypothesized that TFCP2-mediated metastatic activity through the

345 SNAI1 pathway. We knocked down TFCP2 with siRNA in SNAI1-overexpressing MDA-MB231 basal-

346 type breast cancer cells. Consistent with previous experiments, exogenous SNAI1 expression

347 recovered TFCP2-mediated inhibition of migration, invasion, and expression of the mesenchymal

348 markers FN, CDH2, and VIM in those cells (Supplementary Fig. S4F-S4H). Similar effects were

349 observed when MCF7 cells in spheroids were treated with similar conditions. When overexpressing

350 SNAI1, MCF7 cells with TFCP2 knockdown regained the ability to form spheres and exhibited a

351 stemness phenotype along with CD44-positive cells (Supplementary Fig. S4I-S4L). Thus, we suggest

352 that SNAI1 drives TFCP2-induced EMT and stemness, thereby sustaining metastatic programming in

353 basal-type breast cancer cells.

354

355 TFCP2 regulates EGFR signaling activation in breast cancer

356 To achieve mechanism selectivity, GSEA analysis was performed to investigate which signaling

357 pathways are involved in the TFCP2-induced pro-metastatic effects in basal-type breast cancer. We

358 found that there is a highly positive correlation between TFCP2 expression and EGFR signaling along

359 with its downstream signaling pathway (Fig. 4A). Next, we performed ELISA and western blot assays

360 to determine whether TFCP2 regulates EGFR activity. Both assays showed that TFCP2 enhanced

361 EGFR protein level activity based on the TFCP2 silencing and overexpression experiments; however,

362 the EGFR mRNA expression levels did not change (Fig. 4B-D; Supplementary Fig. S5A and S5B).

363 EGFR is widely involved in a variety of cellular processes, including proliferation, motility, and survival,

364 and can be activated by a variety of polypeptide ligands, such as EGF and HBEGF. Since TFCP2

365 regulates EGFR activity, we assessed the expression level of several EGFR ligands, including

366 epidermal growth factor (EGF), transforming growth factor alpha (TGF-α), epiregulin (EREG),

367 amphiregulin (AREG), epithelial mitogen (EPGN), heparin-binding EGF (HBEGF) and betacellulin

368 (BTC), all of which can activate EGFR. Silencing and overexpressing TFCP2 revealed that TFCP2

369 more profoundly affects EGF and TGF-α than all the other ligands tested in MDA-MB231 and MCF7

370 cells, respectively (Fig. 4E; Supplementary Fig. S5C). Subsequent, we hypothesized that if there is

371 any correlation between TFCP2 and both the EGF and TGF-α ligands. We screened breast cancer

372 cohorts through GEO databases and found a positive correlation of TFCP2 with both EGF and TGF-α

373 (Fig. 4F). Luciferase assays confirmed the binding of TFCP2 on EGF and TGF-α promoters,

374 suggesting their role in TFCP2 induced EGFR signaling (Fig. 4G). To further confirm this correlation,

375 we predicted TFCP2 binding sites to EGF and TGF-α promoters using the JASPAR online tool

376 (http://jaspar.genereg.net) and performed chromatin immunoprecipitation (ChIP) assays using MDA-

377 MB231 and Hs578T cell lines. We found that TFCP2 can directly bind to the F2 fragment site of the

378 EGF promoter and F1-4 fragment sites of the TGF-α promoter in both cells (Fig. 4H-I). In addition,

379 when TFCP2 D153A (which mutated aspartate (D) to alanine (A) at the TFCP2 DNA binding site),

380 LSF dominant negative (LSFdn, double amino acid substitution mutant of LSF that is unable to bind

381 DNA, initially named 234QL/236KE) (35), and TFCP2 WT constructs were overexpressed in MCF7

382 cells, we observed that only TFCP2 WT significantly upregulated EGF and TGF-α mRNA expression

383 along with EGFR protein activity; however, there was no change observed in cells overexpressing

384 TFCP2 D153A or LSFdn, which was similar to the levels in the control cells (Supplementary Fig. S5D

385 and S5E). ChIP assay was also confirmed that neither TFCP2 D153A or LSFdn cannot bind to EGF

386 or TGF-α promoters (Supplementary Fig. S5F). It is worth mentioning that inhibiting EGFR signaling in

387 TFCP2-overexpressing MCF7 cells suppressed signature genes related to EMT and CSC, which

388 further suggests that TFCP2-induced EGFR activation regulates both phenotypes in breast cancer

389 (Supplementary Fig. S5G).

390 Rescue experiments were performed in both MDA-MB231 and Hs578T cell lines with silenced

391 TFCP2 in the presence or absence of recombinant EGF/TGF-α. Interestingly, EMT-related SNAI1,

392 CDH2, and VIM protein expression; migration; and invasion were decreased upon silencing TFCP2;

393 these decreases were rescued again with the treatment of EGF or TGF-α in MDA-MB231 and

394 Hs578T cells (Fig. 4J, Supplementary Fig. S5H). Similar effects were observed in TFCP2-

395 overexpressing MCF7 cells with or without EGF/TGF-α silencing (Supplementary Fig. S5I). Taken

396 together, these results indicated that TFCP2 can directly upregulate EGF and TGF-α expression to

397 activate the EGFR signaling pathway in metastatic breast cancer cells.

398 A positive feedback loop exists between TFCP2 and the EGFR/PI3K/AKT axis

399 Since TFCP2 could regulate EGF/TGF-α expression to activate EGFR activation, we investigated the

400 upstream regulator of TFCP2. To this end, we examined TFCP2 expression in the presence of

401 various signaling pathway inhibitors, such as U0126 (a MEK1/2 inhibitor), a JNK inhibitor, SB203580

402 (a p38 MAP kinase), a JAK inhibitor, WP1066 (a STAT3 inhibitor), LY294002 (a PI3 kinase/AKT

403 inhibitory), and PP2 (a SRC inhibitor). Prior to this experiment, the efficacy of the inhibitors was

404 confirmed by western blot (Supplementary Fig. S6A). These analyses revealed that inhibiting the AKT

405 pathway downregulates TFCP2 mRNA levels to a greater extent than inhibition of other pathways in

406 MDA-MB231 cells (Fig. 5A). To further confirm that the AKT pathway was blocked in the same cells

407 with AKT-targeted siRNA or LY294002, the TFCP2 protein level was measured and shown to be

408 dramatically reduced as observed by western blot analysis (Fig. 5B; Supplementary Fig. S6B). As we

409 found above, EGFR can be activated through TFCP2, and we next asked whether AKT could regulate

410 EGFR through TFCP2. Knockdown or pharmacological blockade of AKT attenuated EGFR and

411 TFCP2 activity in MDA-MB231 cells, while this attenuation was rescued in the presence of TFCP2

412 overexpression. The expression of SNAI1, FN, CDH2, CD44, and OCT4 in MDA-MB231 cells was

413 also affected by LY294002 treatment, which was rescued with TFCP2 overexpression (Fig. 5C and D;

414 Supplementary Fig. S6C). This result supported the view that AKT serves an essential upstream

415 regulator of TFCP2, thereby inducing EGFR activation to promote metastatic activity. Earlier, we

416 observed that concomitant treatment with recombinant EGF/TGF-α increases TFCP2 expression in

417 TFCP2 silencing MDA-MB231 cells compared with that in cells with TFCP2 knockdown alone (Fig. 4J).

418 Hence, we hypothesized that if there is any positive feedback loop such as EGFR activation can also

419 regulate TFCP2 expression in breast cancer. To verify this, we analyzed TFCP2 expression in the

420 presence of either si-EGFR or an EGFR inhibitor (AG1478). Both approaches decreased the protein

421 activity and mRNA expression of TFCP2 in MDA-MB231 cells (Fig. 5E; Supplementary Fig. S6D and

422 S6E), suggesting potential involvement of EGFR in TFCP2 induction. Similar observations were also

423 made in BT549 cells by inhibiting EGFR on TFCP2 levels (Supplementary Fig. S6F). To evaluate

424 whether the EGFR/PI3K/AKT axis is a true upstream candidate of TFCP2 feedback regulation, we

425 treated MCF7 cells with recombinant EGF/TGF-α in the presence or absence of LY294002. TFCP2

426 expression was greatly enhanced in the presence of EGF/TGF-α alone, but this effect was reduced

427 when LY294002 was added to the cells (Fig. 5F). These data indicated that TFCP2 expression is

428 upregulated by the EGFR/PI3K/AKT axis in metastatic breast cancer cells through a positive feedback

429 loop.

430

431 Correlation between TFCP2 and EGF/TGF-α expression in patient samples

432 To evaluate whether our in vitro findings are correlated with human breast cancer and metastasis

433 formation, we assessed the prognostic value of TFCP2 expression with EGF and TGF-α in breast

434 cancer patient samples. To this end, we performed immunohistochemistry (IHC) analysis to examine

435 the co-expression of TFCP2, EGF and TGF-α in tumors derived from breast carcinoma patients

436 (n=150). Tissue array data showed that expression of TFCP2, EGF and TGF-α was significantly

437 higher in tumor tissues than in matched normal tissues (Fig. 6A). The increased TFCP2 expression

438 correlated well with the augmented expression of EGF and TGF-α (Fig. 6B). Furthermore, Kaplan-

439 Meier survival analysis revealed that the survival time of patients with high TFCP2 and either EGF or

440 TGF-α expression was shorter than those with low expression of these genes (Fig. 6C and D).

441 Additionally, high expression of TFCP2, EGF, and TGF-α was found to be significantly associated

442 with poor outcomes in breast cancer patients, as shown in Fig. 6E. Overall, clinical dataset analysis

443 indicates that TFCP2 levels are positively correlated with EGFR signaling in breast tumors, and higher

444 TFCP2 levels are associated with reduced metastasis-free survival in breast tumors and an increased

445 probability of poor overall survival in EGF/TGFα-high tumors.

446

447 Discussion

448 Here, we demonstrated that TFCP2 functions as an activator of prometastatic transcription factors by

449 directly regulating the expression of the EGFR ligands EGF and TGF-α, resulting in EGFR activation;

450 this signaling cascade is a critical determinant of oncogenic EGFR signaling, leading to poor long-

451 term survival in breast cancer patients. Although various studies have shown that EMT affects the

452 migratory potential of metastatic breast cancer cells and subsequent metastasis, many critical factors

453 regarding how these tumor cells access this fundamental cellular event remain unknown. In this study,

454 we found that the transcription factor, TFCP2, promotes breast cancer cells to acquire increased

455 migration/invasion abilities and CSC traits via the EGFR signaling pathway but has no effect on tumor

456 growth and apoptosis. As we known, EGFR overexpression is frequently observed in TNBC (16,36-

457 38), the aggressive behavior of TNBC and the lack of established clinical treatment targets create a

458 major challenge in treating these patients. In this paper, we showed that high levels of TFCP2

459 expression in TNBC cells increased the activation of the EGFR signaling pathway. In this pathway,

460 ligands play several significant roles at different levels to promote invasion and metastasis (39).

461 Furthermore, our ChIP assay data suggested that TFCP2 directly binds to the promoters of the EGFR

462 ligands EGF and TGF-α (Fig. 4H-4I). Dysregulation of the EGFR pathway via overexpression or

463 constitutive activation can promote processes related to tumor progression, such EMT and stemness,

464 and is associated with poor prognosis in breast malignancies (40-42). Hence, inhibiting TFCP2

465 expression, which can suppress EGF and TGF-α expression, may be effective at preventing EGFR

466 activation in TNBC.

467 In a previous study, TFCP2 was shown to be overexpressed in HCC and to target FN1 and TJP1

468 to regulate HCC metastasis (43). Moreover, TFCP2 can affect pancreatic cancer cell growth, invasion,

469 and migration (44). However, in these studies, the mechanism by which TFCP2 expression is

470 regulated was not fully addressed. In the present study, we found that TFCP2 expression was

471 mediated by the EGFR/PI3K/AKT axis in TNBC, which caused a positive feedback loop (Fig. 5).

472 However, there are some limitations to the current study. First, we identified a signaling pathway that

473 can regulate TFCP2 expression, but the specific regulators of TFCP2 expression remain unclear.

474 Second, although TFCP2 induced both EGF and TGF-α expression to activate EGFR, we could not

475 distinguish which ligand was more important for EGFR signaling. Third, TFCP2 regulated the

476 EGF/TGF-α/EGFR axis in breast cancer; however, we do not know whether this also occurs in other

477 human malignancies. Further studies are required to determine the role of TFCP2 in other cancer

478 types.

479 In summary, we describe the functions of TFCP2 as an oncogenic driver in TNBC. Additionally,

480 we identified the underlying mechanisms whereby TFCP2 regulates EMT and CSC activity in breast

481 cancer through the EGFR/AKT axis. In turn, TFCP2 expression is also regulated by the EGFR/AKT

482 axis (Fig. 6F). Enhanced expression of TFCP2 was associated with poor patient survival and

483 therefore lends itself as a potential target for metastatic breast cancer treatment.

484

485

486

487 Acknowledgments

488 We are thankful to all the research participants who participated in this study. This study was

489 supported by the Bio & Medical Technology Development Program of the National Research

490 Foundation (NRF) funded by the Korean government (MSIT) (2019M3E5D1A01069361 to S.J.Lee).

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636 Figure Legends

637 Fig. 1 High TFCP2 expression was associated with invasive metastatic breast carcinoma. (A)

638 TFCP2, TFCP2L1, and UBP1 expression data in normal breast tissue (n = 291) and breast cancer

639 tissue (n=1,085) from breast cancer patients were obtained from the GEPIA database

640 (http://gepia.cancer-pku.cn/index.html). (B) Heatmap analyses showed that TFCP2 is upregulated

641 (red) in basal-type (n=61) versus luminal-type (n=50) breast cancers in the GSEA datasets

642 (GSE41313). Blue indicates downregulation. (C, D). TFCP2, TFCP2L1, and UBP1 expression data in

643 basal (n = 61) and luminal (n = 80) human breast cancer types were obtained from the GEO database

644 (human patients; GSE41313; https://www.ncbi.nlm.nih.gov/geo) and the GOBO database (human cell

645 lines; http://co.bmc.\\\\lu.se/gobo). (E) qRT-PCR was performed to detect the expression of TFCP2

646 subfamily members in various basal- and luminal-type breast cancer cell lines (n=3). (F) Tissue

647 microarray analysis of TFCP2 expression in basal (n=87) and luminal (n=95) type of breast carcinoma

648 tissues. (G) Analysis of TFCP2 expression in breast cancer through gradewise. High TFCP2 protein

649 expression was correlated with higher tumor grade breast carcinoma. Scale bar = 100 µm. (H)

650 Kaplan-Meier survival analysis for TFCP2 in breast cancer cohorts (basal, HER2 and luminal) based

651 on low and high expression (GSE1456, n=159). Values in the graph represent the means ± SD (n = 3).

652 * p < 0.05; ** p < 0.01; *** p < 0.001; ns, not significant; determined by two-tailed Student’s t-test (95%

653 confidence interval).

654

655

656 Fig. 2 TFCP2 potentiated EMT, metastasis, and the CSC phenotype in breast cancer cell lines.

657 (A) GSEA (GSE41313) analysis was performed in TFCP2-positive breast cancers for hallmarks of

658 cancer progression, including signature genes of the EMT and CSC phenotypes. GSEA analyses

659 indicated that TFCP2 significantly upregulated genes involved in the EMT and CSC processes. ES:

660 enrichment score; NES, normalized enrichment score. (B) Representative images of the morphology

661 of MCF7 breast cancer cells overexpressing TFCP2. TFCP2 overexpression was performed 48 h prior

662 to experiments. Scale bar, 10 µm. (C) Migration and invasion assays were performed using MCF7

663 cells overexpressing TFCP2. (D, E) qRT-PCR and western blot analysis of EMT regulators (ZEB1,

664 SNAI1, SNAI2) and EMT markers (FN, CDH2, VIM) in TFCP2-overexpressing MCF7 cells after 48 hr

665 of overexpression. (F) Sphere formation assays in EGF (100 ng/μL)-treated MCF7 and SKBR3 cells

666 with TFCP2 silencing (Right panel). Cell lines were treated with EGF for 6 h after starvation overnight

667 prior to TFCP2 silencing and TFCP2 knockdown efficiency were analysed by western blot (Left panel)

668 after 48 h of silencing. Scale bar = 10 µm. (G) The total number of spheres in three independent fields

669 was counted and plotted in a graph. (H) Sphere formation of single-cell suspensions at different time

670 points under similar treatment conditions. (I) The average sphere size was measured after 14 days in

671 indicated panels using Motic Images Plus 2.0 software. Scale bar = 100 µm. (J) Flow cytometry

672 analysis of the CSC markers of CD44+/CD24- in EGF-treated MCF7 and SKBR3 cells with TFCP2

673 knockdown. EGF treatment and TFCP2 knockdown was performed similarly in these cells as

674 mentioned above. β-actin was used as a control for normalization. All these experiments were

675 performed in triplicates and values are presented as SD. * p < 0.05; ** p < 0.01; *** p < 0.001; ns, not

676 significant; determined by two-tailed Student’s t-test (95% confidence interval).

677

678

679 Fig. 3 Depletion of TFCP2 inhibited EMT and CSC progression in vivo. (A) LM1 cells stably

680 transfected with shCtrl or shTFCP2 (1 × 106/40 μL per mouse, 5 weeks) were injected into the fourth

681 mammary fat pad of NSG mice (n = 5 per group). The silencing efficiency of shTFCP2 in MDA-MB231

682 LM1 cells was confirmed by western blotting. (B) Images of lung sections in the shCtrl and shTFCP2

683 NSG mice groups. The graph shows the numbers of lung metastatic foci in the respective groups. (C,

684 D) qRT-PCR and western blot analysis of the expression levels of EMT regulators and markers in

685 tumor tissues from control and TFCP2-knockdown mice groups. (E) IHC staining of SNAI1, FN, VIM,

686 CDH2, and CDH1 expression in tumor tissues from shCtrl- and shTFCP2-injected mice. (F)

687 Representative graph showing the IHC staining scores in both groups. (G, H) qRT-PCR and western

688 blot analysis of CSC marker and regulators (CD44, SOX2, NANOG, OCT4) in shCtrl- and shTFCP2-

689 treated mouse tissues. (I, J) IHC staining assays and intensity score analysis of CSC markers and

690 regulators in control and TFCP2 knockdown mouse tissues. Scale bar, 100 μm. β-actin was used as a

691 control for normalization. Data is presented as mean of three independent experiments (SD). * p <

692 0.05; ** p < 0.01; *** p < 0.001; ns, not significant; determined by two-tailed Student’s t-test (95%

693 confidence interval).

694

695

696 Fig. 4 TFCP2 induced EGF and TGF-α expression to activate EGFR signaling in breast cancer.

697 (A) Major functional pathways modulated by TFCP2 in breast cancer cells based on transcriptome

698 analysis using GSEA (GSE7513) analysis. NES, normalized enrichment score. Among the identified

699 pathways, EGFR signaling showed a positive correlation with high expression levels of TFCP2 based

700 on a dataset from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). Enrichment plots are shown

701 in various panels and stratified by high vs low expression of TFCP2. Quantification of expression data

702 is shown in the graph. (B, C) EGFR and AKT activation were determined by western blot; TFCP2 and

703 EGFR mRNA analysis by qPCR both in TFCP2-silenced MDA-MB231 and Hs578T cell lines after 48

704 h. (D) ELISA was used to measure total and phosphorylated EGFR levels in TFCP2-knockdown

705 MDA-MB231 cells after 48 h. (E) qRT-PCR analysis for screening the expression of EGFR ligands in

706 MDA-MB231 cells with silenced TFCP2 after 48 h. (F) A positive correlation between TFCP2

707 expression and EGF/TGF-α was obtained from the GEO database (GSE2603 [n=121]; GSE25055 [n

708 = 310]). (G) Luciferase reporter assays for TFCP2 directly binding to the EGF and TGF-α promoters.

709 (H) Schematic figure shows predicted TFCP2 binding sites of the EGF and TGF-α promoter regions.

710 (I) The ChIP assay showed that TFCP2 directly binds to the EGF and TGF-α promoters at specific

711 sites in basal type cell lines MDA-MB231 and Hs578T. (J) Rescued experiments were performed

712 using western blot analysis in TFCP2-silenced MDA-MB231 and Hs578T cells with recombinant EGF

713 or TGF-α after 48 h. β-actin was used as a control for normalization. Data is presented as mean of

714 three independent experiments (SD). * p < 0.05; ** p < 0.01; *** p < 0.001; ns, not significant;

715 determined by two-tailed Student’s t-test (95% confidence interval).

716

717

718 Fig. 5 EGFR increased TFCP2 expression in breast cancer via a positive feedback loop. (A)

719 Detection of TFCP2 mRNA expression in MDA-MB231 cells after treatment with U0126 (10 μM, ERK

720 inhibitor), a JNK Inhibitor (10 μM), SB203580 (25 μM, P38 inhibitor), a JAK Inhibitor (10 μM), a STAT3

721 inhibitor (10 μM), LY294002 (10 μM, PI3K inhibitor), and PP2 (10 μM, SRC inhibitor). TFCP2 mRNA

722 expression was analyzed after 24 h of inhibitors treatment. (B) Western blotting analysis of TFCP2

723 levels in MDA-MB231 cells after 24 h of treatment with LY294002. (C, D) Western blot and

724 immunofluorescence analysis for p-EGFR, TFCP2, SNAI1, FN, CDH2, OCT4 and CD44 protein levels

725 in MDA-MB231 cells overexpressing TFCP2 and treated with si-AKT. si-AKT was treated together

726 with TFCP2 overexpression before 48 h of experiment. Scale bar = 10 μm. (E) Analysis of TFCP2

727 protein and mRNA expression in MDA-MB231 cells at 24 h after treatment with the EGFR inhibitor

728 AG1478 (10 μM) using western blotting and qRT-PCR, respectively. (F) Rescue experiments for the

729 detection of TFCP2 mRNA expression in MCF7 cells after 6h treated with EGF and TGF-α (100 ng/μL)

730 in the absence or presence of LY294002. Scale bar = 100 μm. β-actin was used as a control for

731 normalization. Data is presented as mean of three independent experiments (SD). * p < 0.05; ** p <

732 0.01; *** p < 0.001; ns, not significant; determined by two-tailed Student’s t-test (95% confidence

733 interval).

734

735

736 Fig. 6 Correlation between TFCP2 expression and EGF/TGF-α in breast cancer patients. (A)

737 Representative IHC images of TFCP2, EGF, and TGF-α in breast cancer and corresponding normal

738 tissues. Scale bar = 100 μm. Distribution of the TFCP2, EGF, and TGF-α staining intensity in breast

739 cancer tissues. (B) The association between TFCP2 and both EGF and TGF-α expression in breast

740 cancer tissues. The number of cases and the percentage of positive staining in the corresponding

741 groups as well as the statistical significance based on Student’s t-tests and Pearson’s correlations of

742 expression are shown in the table. (C, D, and E). Kaplan-Meier survival analysis showed that high

743 levels of TFCP2 expression along with high levels of either EGF or TGF-α expression or high levels of

744 all three were associated with lower survival rates of breast cancer patients. (F) Schematic

745 representation of the TFCP2/EGFR/PI3K/AKT axis mechanism in metastatic breast cancer.

A Feedback loop comprising EGF/TGF-α Sustains TFCP2-mediated Breast Cancer Progression

Yi Zhao, Neha Kaushik, Jae-Hyeok Kang, et al.

Cancer Res Published OnlineFirst March 19, 2020.

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