Thyroid Hormone Receptor Beta Induces a Tumor Suppressive

Author Manuscript Published OnlineFirst on June 17, 2020; DOI: 10.1158/1541-7786.MCR-20-0282 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

1 THYROID HORMONE RECEPTOR BETA INDUCES A TUMOR SUPPRESSIVE

2 PROGRAM IN ANAPLASTIC THYROID CANCER.

3 Eric L. Bolf1,2,*, Noelle E. Gillis1,2,*, Cole D. Davidson1,2, Princess D. Rodriguez3, Lauren

4 Cozzens1, Jennifer A. Tomczak1, Seth Frietze2,3, and Frances E. Carr1,2

6 1Department of Pharmacology, Larner College of Medicine

7 2University of Vermont Cancer Center,

8 3Department of Biomedical and Health Sciences, College of Nursing and Health

9 Sciences

10 University of Vermont

11 Burlington, VT 05405

13 Corresponding Author

14 Frances E. Carr, PhD, Department of Pharmacology, Larner College of Medicine,

15 University of Vermont, 89 Beaumont Avenue, Burlington VT 05405. E-mail:

16 [email protected].

17 *These authors contributed equally to this work

19 Running Title: TRβ induces a tumor suppressive program in ATC

21 Keywords: Thyroid Hormone Receptor, Thyroid Cancer, Tumor Suppression

23 COMPETING INTERESTS: The authors declare they have no conflict of interest. 1

Downloaded from mcr.aacrjournals.org on September 30, 2021. © 2020 American Association for Cancer Research. Author Manuscript Published OnlineFirst on June 17, 2020; DOI: 10.1158/1541-7786.MCR-20-0282 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.

24 ABSTRACT:

25 The thyroid hormone receptor beta (TRβ), a key regulator of cellular growth and

26 differentiation, is frequently dysregulated in cancers. Diminished expression of TR is

27 noted in thyroid, breast, and other solid tumors and is correlated with more aggressive

28 disease. Restoration of TR levels decreased tumor growth supporting the concept that

29 TR could function as a tumor suppressor. Yet, the TR tumor suppression

30 transcriptome is not well delineated and the impact of TR is unknown in aggressive

31 anaplastic thyroid cancer (ATC). Here, we establish that restoration of TR expression

32 in the human ATC cell line SW1736 (SW-TRβ) reduces the aggressive phenotype,

33 decreases cancer stem-cell populations and induces cell death in a T3-dependent

34 manner. Transcriptomic analysis of SW-TRβ cells via RNA-sequencing revealed

35 distinctive expression patterns induced by ligand-bound TRβ and revealed novel

36 molecular signaling pathways. Of note, liganded TRβ repressed multiple nodes in the

37 PI3K/AKT pathway, induced expression of thyroid differentiation markers, and promoted

38 pro-apoptotic pathways. Our results further revealed the JAK1-STAT1 pathway as a

39 novel, T3-mediated, anti-tumorigenic pathway that can be activated in additional ATC

40 lines. These findings elucidate a TR-driven tumor suppression transcriptomic

41 signature, highlight unexplored therapeutic options for ATC, and support TR activation

42 as a promising therapeutic option in cancers.

44 Implications: TRβ-T3 induced a less aggressive phenotype and tumor suppression

45 program in anaplastic thyroid cancer cells revealing new potential therapeutic targets.

47 48

49 INTRODUCTION:

50 The non-steroidal nuclear hormone receptor thyroid hormone receptor beta (TRβ) has

51 been characterized as a tumor suppressor in multiple tumor types, primarily thyroid,

52 breast, and hepatocellular carcinomas (1). Expression of TRβ is typically reduced in

53 aggressive tumors. Epigenetic silencing of THRB is frequent, while mutations in the

54 gene are relatively rare. As a nuclear hormone receptor, the canonical function of TRβ

55 is to regulate gene expression in response to its ligand triiodothyronine (T3). It is also

56 known that TRβ exerts ligand-independent genomic signaling and has non-genomic

57 functions that are ligand regulated (2).

58 Multiple lines of evidence demonstrate the tumor suppressive activity of TRβ in thyroid

59 cancer. Re-expression of silenced TRβ using demethylating agents delays thyroid tumor

60 progression in vivo (3), mice expressing a c-terminal frameshift of TRβ (ThrbPV)

61 spontaneously develop follicular thyroid cancer (4), and ThrbPV/PV KrasG12D mice

62 develop thyroid tumors with features of dedifferentiated thyroid cancer (5).

63 TRβ has previously been shown to modulate anti-tumorigenic signaling in thyroid cancer

64 in part through repression of driver pathways such as PI3K/AKT (6) and NF-κβ (7);

65 modulation of inflammatory processes (7); and repression of the oncogenes β-Catenin

66 (8,9) and RUNX2 (10,11). These signaling nodes are important contributors to the tumor

67 suppressive activity of TRβ, but they likely do not constitute the entire tumor

68 suppression program.

69 The current understanding of TRβ tumor suppressive activity has been described

70 primarily in differentiated thyroid cancers, but there is a need to determine TRβ-

71 mediated tumor suppressive actions in dedifferentiated anaplastic thyroid cancer (ATC).

72 Although this tumor subtype is rare, ATC is responsible for nearly 40% of thyroid cancer

73 deaths with most patients exhibiting a median survival time of less than six months (12).

74 This is mainly due to a lack of effective targeted therapeutic options. Characterization of

75 the activity of tumor suppressors can provide important insights into the development of

76 rationally designed treatment interventions.

77 These studies aimed to understand the systemic impact of TRβ and its ligand thyroid

78 hormone (T3) on ATC cancer cell characteristics. We performed transcriptomic analysis

79 of TRβ in ATC cells to provide a comprehensive network of cellular signaling events

80 altered by TRβ and T3. We have paired this transcriptomic data with functional studies

81 to characterize the TRβ-mediated changes to ATC cell characteristics. Lastly, this

82 analysis has revealed certain nodes of TRβ that represent key vulnerabilities in ATC

83 that can be exploited pharmacologically.

84 MATERIALS AND METHODS:

85 Culture of thyroid cell lines. Anaplastic thyroid cancer cell lines (SW1736, 8505C,

86 OCUT-2, and KTC-2) were cultured in RPMI 1640 growth media with L-glutamine (300

87 mg/L), sodium pyruvate and nonessential amino acids (1%) (Corning Inc, Corning, NY,

88 USA), supplemented with 10% fetal bovine serum (Thermo Fisher Scientific, Waltham,

89 MA, USA) and penicillin-streptomycin (200 IU/L) (Corning) at 37°C, 5% CO2, and 100%

90 humidity. Lentivirally modified SW1736 cells were generated as recently described (11)

91 with either an empty vector (SW-EV) or to overexpress TRβ (SW-TRβ). SW-EV and

92 SW-TRβ were grown in the above conditions with the addition of 1 µg/ml puromycin

93 (Gold Bio, St Louis, MO, USA). SW1736 and KTC-2 were authenticated by the Vermont

94 Integrative Genomics Resource at the University of Vermont using short tandem repeat

95 profiles and Promega GenePrint10 System (SW1736, May 2019; KTC-2, October

96 2019). 8505C and OCUT-2 were authenticated by University of Colorado by short

97 tandem repeat profiles (8505C, June 2013; OCUT-2, June 2018). TheSW1736 and

98 KTC-2 cells were tested for mycoplasma by PCR as described by Uphoff et al

99 (SW1736, April 2019; KTC-2, February 2020; 85050C, February 2020; OCUt-2, January

100 2020) (13).

101 RNA-seq Library Construction and Quality Control. 80% confluent monolayers of

102 SW-EV and SW-TRβ cells were hormone starved for 24 hours in phenol red free RPMI

-8 103 with charcoal-stripped fetal bovine serum. 10 M T3 was added and incubated for 24

104 hours prior to sample collection. Total RNA from three independent experiments was

105 extracted and purified using RNeasy Plus Kit (Qiagen, Venlo, Netherlands) according to

106 manufacturer’s protocol. Purity of the total RNA samples was assessed via BioAnalyzer

107 (Agilent Technologies, Santa Clara, CA, USA) and samples with a RIN score >7 were

108 used for library construction. rRNA was depleted using 1 μg of total RNA with the

109 RiboErase kit (Roche, Basel, Switzerland). Strand-specific Illumina cDNA libraries were

110 prepared using the KAPA Stranded RNA-Seq library preparation kit with 10 cycles of

111 PCR (Roche). Library quality was assessed by BioAnalyzer (Agilent Technologies) to

112 ensure an average library size of 300 bp and the absence of excess adaptors in each

113 sample. RNA-Seq libraries were pooled in triplicates per condition and sequenced on

114 the Illumina HiSeq 1500 with 50 bp single-end reads. Quality scores across sequenced

115 reads were assessed using FASTQC. All samples were high quality. For alignment and

116 transcript assembly, the sequencing reads were mapped to hg38 using STAR. Sorted

117 reads were counted using HTSeq and differential expression analysis was performed

118 using DESeq2. Genes with a p-value of <0.05 and a fold change of >2 were considered

119 differentially expressed and were used for further analysis through Ingenuity Pathway

120 Analysis (IPA) (Qiagen) and Gene Set Enrichment Analysis (GSEA). Raw and

121 processed RNA-seq datasets have been deposited in the Gene Expression Omnibus

122 (GEO) under accession code GSE150364.

123 Immunoblot Analysis. Proteins were isolated from whole cells in lysis buffer (20mM

124 Tris-HCl [pH 8], 137mM NaCl, 10% glycerol, 1% Triton X-100, and 2mM EDTA)

125 containing Protease Inhibitor Cocktail 78410 (Thermo Fisher Scientific). Proteins were

126 resolved by polyacrylamide gel electrophoresis on 10% sodium dodecyl sulfate gels

127 EC60752 (Thermo Fisher Scientific) and immobilized onto nitrocellulose membranes

128 (GE Healthcare, Chicago, IL, USA) by electroblot (Bio-Rad Laboratories, Hercules, CA,

129 USA). Specific proteins were detected by immunoblotting with the indicated antibodies

130 (STable 1); immunoreactive proteins were detected by enhanced chemiluminesence

131 (Thermo Scientific) on a ChemiDoc XRS+ (Bio-Rad Laboratories).

132 Continuous Cell Proliferation Assay. Live cell imaging was used to assess the growth

133 kinetics of SW-EV and SW-TRβ. To perform live cell imaging, 5000 cells were plated

134 per well in 24 well plates. After 24 hours in phenol red free, charcoal stripped media,

-8 135 media was supplemented with either 10 M T3 or equivolume vehicle (NaOH). Every

136 two hours cells were imaged with a Lionheart automated microscope (Agilent 6

137 Technologies) and quantified with Gen5 software (Agilent Technologies). The cells

138 entered the log phase of growth at approximately 48 hours, and we used the portion of

139 the curve following this point to calculate the doubling time of the cells.

140 Soft Agar Colony Formation Assay. Soft agar colony forming assays were used to

141 assess anchorage-independent growth. A layer 0.50% agar in thyroid media (as

142 described) was solidified in 6-well cell culture plates. SW-EV or SW-TRβ cells were

143 plated in a second layer of 0.25% agar in thyroid media. 200uL of thyroid media was

144 maintained at the top of each well to prevent the agar from drying. Where indicated, 10-8

145 M T3 or vehicle (NaOH) was added to the media in all layers to evaluate the effects of

146 liganded TRβ on anchorage-independent growth. Colonies were allowed to grow for 14

147 days. Live SW-EV and SW-TRβ colonies were detected via GFP expression using a

148 ChemiDoc XRS+ (Bio-Rad Laboratories). Colonies were then counted with ImageJ

149 using the Colony Counter plugin.

150 Tumorsphere Assay. Tumorsphere-forming assays were used to assess self-renewal

151 and sphere-forming efficiency. For generating thyrospheres, adherent SW-EV and SW-

152 TRβ monolayer cells were dissociated with Trypsin-EDTA, and single cells were moved

153 to round-bottom ultra-low attachment 96-well plates at a density of 1000 cells/well

154 (Corning). Thyrospheres were cultured in RPMI 1640 growth media supplemented with

155 20ng/mL each of epidermal growth factor (EGF) and fibroblastic growth factor (FGF)

-8 156 (Gold Bio). Where indicated, 10 M T3 or vehicle (NaOH) was added to the media to

157 evaluate the effects of liganded TRβ on thyrosphere growth. Thyrospheres grew for

158 seven days and were then counted with an inverted microscope.

159 Migration Assay. Cell migration was determined by wound healing assay. Cells were

160 plated and allowed to grow to 100% confluency. Two hours prior to scratching, cells

161 were treated with 10 mg/ml Mitomycin C. A scratch was performed with a P1000 pipette

162 tip and debris was washed away with PBS. Migration media was supplemented with 10-

8 163 M T3. Images were obtained at 0, 24, 48, and 72 hours. Wound closure was measured

164 using ImageJ macro “Wound Healing Tool” (http://dev.mri.cnrs.fr/projects/imagej-

165 macros/wiki/Wound_Healing_Tool). Values were normalized so that the initial scratch

166 was 0% closure.

167 Apoptosis Assay. Cells were plated at a density of 50,000 cells/well and treated with

-8 168 vehicle (1 N NaOH) or 10 M T3. After 5 days the cells were lysed for analysis, poly

169 (ADP-ribose) polymerase 1 (PARP1) and Caspase 3 cleavage were assessed by

170 immunoblot to measure apoptotic signaling.

171 Cell Cytotoxicity Assay. Sulforhodamine B Cell Cytotoxicity Assay (Abcam,

172 Cambridge, UK) was used to stain total cell protein to measure changes in cell viability

173 in response to pharmacological agents. ATC cells were plated in 96-well clear flat-

174 bottom plates at a density of 5,000 cells/well. Cells were treated with serial dilutions of

175 the STAT1 activator 2-(1,8-Naphthyridin-2-ly)phenol (2-NP) (Abcam), the CDK4/6

176 inhibitor palbociclib, the PI3K inhibitor buparlisib, or vehicle (DMSO). Plates were then

177 incubated for 72 hours. Cells were fixed, stained, and imaged using a plate reader

178 according to manufacturer’s instructions. Relative changes in cell growth in response to

179 each agent were calculated relative to the corresponding vehicle control group.

180 RNA Extraction and Quantitative Real-Time PCR (qRT-PCR). Total RNA was

181 extracted using RNeasy Plus Kit (Qiagen) according to manufacturer’s protocol. cDNA

182 was then generated using the 5X RT Mastermix (ABM, Vancouver, Canada). Gene

183 expression to validate RNASeq analysis was quantified by qRT-PCR using 2X

184 SuperGreen Mastermix (Thermo Fisher Scientific) on a QuantStudio 3 real-time PCR

185 system (Thermo Fisher Scientific). Fold change in gene expression compared to

186 endogenous controls was calculated using the ddCT method. Primer sequences are

187 indicated in Supplemental Table 1.

188 Statistics. All statistical analyses were performed using GraphPad Prism software.

189 Paired comparisons were by T-test and group comparisons were made by a 2-way

190 ANOVA followed by a Tukey multiple comparisons test (p<0.05). Data are represented

191 as mean  standard deviation, or when stated otherwise mean  standard error of the

192 mean. Area under the curve (AUC) at the 95th confidence interval was used to evaluate

193 statistical differences in growth and migration assays.

194 RESULTS

195 Expression of TRβ inhibits pro-tumorigenic characteristics of human anaplastic

196 thyroid cells.

197 Anti-tumorigenic signaling from the tumor suppressor TRβ has not been

198 comprehensively defined in ATC. We utilized the human ATC cell line SW1736,

199 modified to overexpress TRβ (previously used in (11)), to examine the effect of both T3

200 and TRβ on the cellular growth. T3 modestly decreased the growth rate of SW-EV

201 (Figure 1A). Vehicle treated SW-EV also grew faster than vehicle treated SW-TRβ.

202 Importantly, the combination of TRβ overexpression and T3 treatment profoundly

203 reduced cellular growth. T3 treated SW-TRβ also exhibited the greatest doubling time

204 (Figure 1B). We further explored the anti-proliferative potential of TRβ activity by

205 treating unmodified SW1736 and KTC-2 cells with T3 and measuring cell growth over

206 time (SFigure 1). KTC-2 cells express significantly greater TRβ than SW1736, and were

207 responsive to T3 treatment, which reduced their proliferative capacity. TRβ expression

208 and treatment with cognate ligand profoundly reduced the growth of ATC cells.

209 In addition to inducing anti-proliferative activity, TRβ is known to block metastasis in vivo

210 (14). As metastasis and invasiveness require heightened cellular motility, we also

211 assessed the impact of T3 and TRβ on ATC cell migration by wound healing assay.

212 Ligand treated SW-TRβ showed reduced migratory potential compared to ligand treated

213 SW-EV (Figure 1C-D). These data indicate that TRβ in the presence of T3 ligand exerts

214 tumor suppressor activity in ATC cells.

215 TRβ reprograms the anaplastic thyroid cancer cell transcriptome.

216 Given that T3 significantly reduced ATC cell growth and migration, we then interrogated

217 the gene expression patterns elicited by TRβ with T3 treatment by RNA-seq. The

218 expression patterns of differentially expressed genes (DEGs) across each condition was

219 visualized using a clustered heatmap (Figure 2A). This analysis resulted in 5 distinctive

220 clusters of DEGs. Clusters 1 and 5 are DEGs regulated by T3 in the absence of TRβ

221 overexpression. Clusters 2 and 3 are DEGs that are T3-regulated only when TRβ is

222 overexpressed. Cluster 4 includes the DEGs that are repressed by T3 in the absence of

223 TRβ and induced by T3 in cells that overexpress TRβ.

224 Enriched pathways within these five clusters of DEGs were determined using IPA

225 software (Figure 2B). Highly enriched processes include Integrin-linked kinase (ILK)

226 signaling (cluster 1), interferon signaling (cluster 2), endoplasmic reticulum (ER) stress

227 (cluster 2), nucleotide excision repair (NER) (cluster 3), DNA methylation and

228 transcriptional repression (cluster 3), and protein ubiquitination (cluster 4). Of these

229 pathways highlighted in the cluster analysis, TRβ has previously been shown to regulate

230 ILK (hereafter PI3K/ILK) and interferon signaling (hereafter interferon/JAK1/STAT1)

231 (6,15).

232 Following PI3K phosphorylation of PIP2, ILK catalyzes phosphorylation AKT and

233 activates proliferative and invasive cellular processes (16). A pairwise comparison

234 between T3-treated SW-EV and SW-TRβ cells demonstrates that expression of TRβ

235 further represses genes within the PI3K/ILK pathway (SFigure 2A-I). Therefore,

236 changes to the PI3K/ILK pathway are likely a reflection of the known repressive effect

237 TRβ has on PI3K in cancer cells (6). TRβ repression of PI3K signaling was confirmed by

238 assessing pAKT/AKT by immunoblot (SFigure 2J).

239 TRβ has recently been shown to alter a set of genes in the interferon/JAK1/STAT1

240 pathway in breast cancer cells (15). This pathway was also significantly upregulated by

241 TRβ in our ATC cell line model as predicted by IPA (Figure 2B) and GSEA (STable 3).

242 Since the transcriptomic profiling of SW1736 was performed in vitro, the observed

243 interferon response is likely intrinsic signaling (17). In the intrinsic interferon pathway,

244 stimulation of the interferon receptor in cells drives phosphorylation of JAK proteins,

245 which in turn phosphorylate STAT1 to initiate a transcriptional response. STAT1

246 signaling has been reported to promote apoptosis and differentiation of tumor cells, as

247 well as inhibit growth (17). 11

248 The upstream regulators of each cluster were determined using IPA (Figure 2C). This

249 analysis further confirmed alteration of the PI3K/ILK and interferon/JAK1/STAT1

250 pathways. Suppression of PI3K/ILK signaling was consistent with repression of the PI3K

251 family and the receptor tyrosine kinases FGF2 and EGFR (cluster 1). There was

252 predicted activation of multiple effectors within the interferon/JAK1/STAT1 signaling

253 network, including IFNG, IRF1, IFNA2, and STAT1 in cluster 2 as well as IRF7 in

254 clusters 2 and 5.

255 Analysis of the upstream regulators highlighted other genes known to be important in

256 tumorigenesis. Notable upstream regulators were NF-κβ (cluster 1), MAPK1 (cluster 2),

257 CCND1 (cluster 4), ATF4 (clusters 1 and 3), and SMARCB1 (cluster 5). NF-κβ and

258 MAPK1 are well recognized to be oncogenic (18,19) and were predicted to be

259 repressed by TRβ and T3. CCND1 encodes the protein cyclin D1, a cell cycle regulator

260 which is regulated by T3 and TRβ in other cell types (20), and was predicted to be

261 repressed in this analysis. The ER stress regulator ATF4 was repressed, itself a gene

262 that is typically upregulated in malignancy and a potential drug target for ATC (21).

263 Genes positively regulated by SMARCB1, a component of the SWI/SNF chromatin

264 remodeling complex, were induced by T3. SWI/SNF components are more commonly

265 mutated in ATC than in other thyroid cancer subtypes (22).

266 These gene clusters were also used for chromatin immunoprecipitation enrichment

267 analysis (ChEA) (23) in order to determine which transcription factors have

268 overrepresented binding sites (SFigure 3). Of these transcription factors, GATA2, IRF1,

269 NELFE, VDR, and ZMIZ1 exhibited altered expression and are therefore possible

270 drivers of TRβ-mediated signaling. 12

271 The majority of the DEGs in this analysis belong to clusters that were only significantly

272 altered in the TRβ-T3 condition. Therefore, a pairwise comparison between SW-EV-T3

273 and SW-TRβ-T3 was performed (SFigure 4). The long noncoding RNAs (lncRNA) were

274 pulled from the set of genes due to their emerging role in tumor biology (24). lncRNAs

275 upregulated included C1QTNF1-AS1, MIR210HG, TBILA, GAS6-AS1, LUCAT1,

276 DRAIC, KIAA0125, MIR22HG, and UCA1. Conversely, LINC01133 was repressed.

277 These lncRNAs have all been found to have a role in tumorigenesis (25-33).

278 In addition to the pathways and key regulators uncovered by the use of bioinformatics

279 software, we decided to directly examine cell cycle regulators that may aid in explaining

280 the anti-proliferative phenotype we observed in the SW-TRβ-T3 group. CDKN1A is a

281 known TRβ-T3 regulated gene in hepatocellular carcinoma, where CDKN1A mediates

282 the anti-proliferative activity of TRβ (34). Expression of the oncogene MYC is induced

283 by TRβ-PV in the development of thyroid tumors (5). In SW1736 cells, TRβ increased

284 expression of CDKN1A and repressed MYC expression (SFigure 5).

285 Analysis of the transcriptomic profile induced by overexpression of TRβ and T3 shows

286 that many pathways and key regulators in cancer biology are altered. These signaling

287 nodes relate to survival signaling, invasiveness, cellular maintenance, differentiation,

288 and chromatin organization. Thus, T3 treatment of SW-TRβ induces transcriptomic

289 changes associated with reduced cell growth, migration, cell cycle, and cell survival.

290 Liganded TRβ reduces ATC stem-cell characteristics.

291 Recently, it was demonstrated that TRβ to reduces cancer stem cell renewal in luminal

292 breast cancer cell lines (15). We therefore examined whether TRβ expression and T3

293 treatment could attenuate the stem-like properties of SW1736 cells. Soft agar colony

294 formation assays were used to measure changes in anchorage independent growth in

295 the presence and absence of TRβ and T3. Treatment with T3 reduced anchorage-

296 independent colony growth in SW-EV cells, and nearly ablated colony growth in SW-

297 TRβ cells (Figure 3A-B). Tumorsphere assays were used to assess self-renewal and

298 estimate the size of the cancer stem cell population within our heterogenous cultures. T3

299 had no effect on the number of tumorspheres formed from SW-EV cells. Expression of

300 TRβ alone reduced tumorsphere formation, however the addition of T3 blocked almost

301 all tumorsphere growth (Figure 3C).

302 Expression of key stem cell markers was also altered. Although the markers for thyroid

303 cancer stem cells have not been studied with the same rigor as other aggressive cancer

304 types, a recent review compiled a list of proposed cancer stem cell markers that have

305 been characterized in the thyroid (35). The combination of TRβ overexpression and T3

306 significantly reduced expression of the thyroid-specific cancer stem cell genes ALDH,

307 POU5F1 (encodes OCT3/4), CD44, FUT4 (encodes SSEA-1), and PROM1 (encodes

308 CD133) (Figure 3D). We also examined the EMT markers CHD1 (E-cadherin), VIM

309 (Vimentin) (SFigure 6). The epithelial marker CDH1 exhibited increased expression in

310 SW1736-TRβ T3 treated cells, whereas expression of the mesenchymal marker VIM

311 was decreased. Together with the phenotypic assays, these results demonstrate that

312 TRβ in association with ligand decreases the stem cell population of ATC cells.

313 To further explore the impact of T3 treatment in this ATC model, the thyroid

314 differentiation score (TDS) was calculated for the SW1736 cells under each condition to

315 evaluate whether the transcriptomic data indicates a change in thyroid-specific 14

316 differentiation. The TDS has been demonstrated to have utility in predicting the

317 aggressiveness of a thyroid tumor (36,37). Ten out of the thirteen genes which

318 constitute the TDS are expressed in at least one condition in this dataset. DIO2,

319 DUOX1, TPO, and TG, were highly responsive to TRβ expression and the addition of T3

320 (SFigure 7). SW-TRβ cells treated with T3 have a significantly higher TDS, indicating

321 that they have the most thyroid-like gene expression (Figure 3E). These results suggest

322 that the tumor suppressive activity of TRβ observed in SW1736 cells may involve

323 cellular differentiation and a consequential reduction in the cancer stem cell properties.

324 TRβ stimulates apoptotic signaling.

325 As a tumor suppressor, TRβ promotes apoptosis in other cancer cell types, however

326 this has never been described in ATC (5,38). A targeted pathway enrichment analysis

327 between SW-TRβ treated with vehicle or T3 revealed alterations in pathways that

328 suggested that pro-apoptotic programming was occurring (Figure 4A). Additionally,

329 GSEA analysis using Hallmark gene sets highlighted enrichment of apoptotic signaling

330 (Figure 4B). We further investigated the ability of T3 to stimulate apoptosis in our model.

331 SW-EV and SW-TRβ cells were cultured in media supplemented with T3 continuously

332 for five days. Caspase 3 and PARP1 cleavage were detected by immunoblot to assess

333 apoptotic activity. T3 induced cleavage of these apoptotic effectors only in SW-TRβ

334 (Figure 4C). Neither T3 nor TRβ alone was sufficient to elicit this response. These data

335 demonstrate heightened activity of TRβ promotes an apoptotic response in aggressive

336 cancer cells, further confirming tumor suppressive activity.

337 TRβ stimulates anti-proliferative interferon/JAK1/STAT1 signaling.

338 Of the pathways altered by TRβ, the interferon/JAK1/STAT1 pathway was among the

339 most prominent within our transcriptomic analysis (Figure 2, Stable3). Activation of

340 interferon/JAK1/STAT1 signaling has been demonstrated to have anti-tumor and anti-

341 proliferative activity in other cancer models (17,39). Interestingly, expression of the

342 kinase effectors JAK1 and STAT1 were significantly increased in SW-TRβ cells

343 following treatment with T3 (Figure 5A and SFigure 8A-C). Additionally, T3 also

344 increased the expression of the STAT1 target genes IRF1 and TAP1, and the IRF1

345 target genes APOL6 and TNFSF10 (Figure 5B). TRβ-T3 mediated induction of these

346 genes was confirmed by qRT-PCR (SFigure 8D).

347 Pharmacological modulation of TRβ-regulated pathways slows growth of ATC.

348 Our transcriptomic analysis revealed pathways that are central to TRβ tumor suppressor

349 activity. We therefore assessed whether perturbing these signaling nodes could

350 recapitulate the striking anti-proliferative effects of TRβ restoration. A panel of four

351 unmodified ATC cell lines (SW1736, 8505C, OCUT-2, and KTC-2) were treated with

352 serial dilutions of pharmacological agents targeting the interferon/JAK1/STAT1 pathway,

353 the PI3K/ILK pathway, and the cell cycle. Cytotoxicity was assessed after 72 hours of

354 treatment. 2-NP, a small molecule activator of STAT1 (40) (Figure 6A), was used to

355 stimulate interferon/JAK1/STAT1 pathway activity. SW1736 and 8505C were most

356 sensitive to 2-NP, and growth of both KTC-2 and OCUT-2 were repressed by the

357 compound at 50 µM. The CDK4/6 inhibitor palbociclib was effective in inhibiting the

358 growth of SW1736, 8505C, and OCUT-2 at 5 nM (Figure 6B). Finally, modulation of the

359 PI3K/ILK pathway with the PI3K inhibitor buparlisib inhibited growth of all four ATC cell

360 lines, including at low doses ranging from 0.5 to 5 µM (Figure 6C). These results 16

361 demonstrate that the key pathways TRβ modulates have potent anti-tumor potential.

362 DISCUSSION:

363 While TRβ is a recognized tumor suppressor in thyroid cancer and is known to be

364 silenced in ATC (10), TRβ-mediated signaling and phenotypic effects are not well

365 characterized in ATC. Our data in ATC cells demonstrates that TRβ, in conjunction with

366 T3, acts to regulate pathways important for the process of tumorigenesis and reduces

367 the aggressive phenotypic characteristics. This change was demonstrated via multiple

368 measures including reduced growth, migration, and stemness. In addition, the

369 combination of TRβ and T3 induced the expression of thyroid differentiation markers in

370 ATC cells, and after 5 days resulted in apoptosis. T3 was essential for the profound anti-

371 tumorigenic molecular signaling and phenotypic remodeling observed in this study. A

372 summary of the major findings of our analysis are represented in Figure 7.

373 Our transcriptomic results reveal new details about TRβ-mediated regulation of critical

374 cancer-related pathways in ATC. We show TRβ mediates repression of PI3K in ATC, a

375 pathway that has been demonstrated in breast cancer and differentiated thyroid tumors

376 (6,38), suggestive that this signaling is active in a variety of tumor types. Additionally,

377 we highlight the interferon/JAK1/STAT1 pathway, previously unknown to be modulated

378 by T3 in thyroid cells. Along with alterations to PI3K and interferon activity, there were

379 changes to cellular repair processes driven by TRβ overexpression. TRβ and T3 altered

380 expression of genes involved ER stress. This is consistent with alteration of protein

381 ubiquitination, which may indicate a greater turnover rate of misfolded proteins, an

382 important component of ER stress. Additionally, alteration of transcriptional repression

383 and NER are consistent with observed reduction of cell growth. These pathways can

384 initiate an apoptotic response, such as through an accumulation of misfolded proteins in

385 the ER (41), or a failure of DNA repair pathways to repair damaged DNA (42). Thus,

386 these results indicate that these cells are primed for apoptosis to occur after multiple

387 days of hormone treatment.

388 The pathways in this analysis overlap substantially with known drivers of ATC. ATC

389 commonly exhibits mutations to the MAPK and PI3K pathways, the SWI/SNF complex,

390 and DNA repair processes (22,43). The TRβ driven transcriptomic reprogramming is

391 indicative of a reversal of the process of malignancy. Indeed, these changes in gene

392 expression suggest that TRβ is promoting a differentiating effect in the cells, which was

393 demonstrated by the TDS and multiple stemness assays, indicating that TRβ

394 expression may be predictive in determining the aggressiveness of a tumor. Our results

395 indicate that TRβ reduces the aggressive malignant phenotype of ATC cells.

396 An increased understanding of the pathways TRβ regulates has revealed drug targets

397 for intervention. The PI3K inhibitor buparlisib was able to significantly repress the

398 growth of ATC cell lines. Clinical trials have been conducted for buparlisib in non-ATC

399 thyroid cancer, with some degree of success and concerning degrees of toxicity (44).

400 Additionally, buparlisib has seen some success in a pre-clinical ATC study (45). The

401 cyclin-dependent kinase inhibitor palbociclib was effective in blocking the growth of our

402 ATC cell lines and there is evidence that it is able to synergize with PI3K inhibition to

403 further block cancer cell growth (46). While this study validated PI3K and the cell cycle

404 as attractive targets which other groups have investigated, we have also identified an

405 unexplored pathway in ATC, STAT1. STAT1 is stimulated by interferons, which have 18

406 been reported to be tumor suppressive in multiple cancer types (17). STAT1 itself may

407 be a clinically important drug target as stimulation of STAT1 activity was sufficient to

408 reduce growth in multiple ATC cell lines. Prior research has demonstrated that

409 upstream stimulation by interferon α can suppress growth in thyroid cancer cells and

410 patients, however toxicity is high (47,48). Modulation of STAT1 directly to suppress

411 tumor growth may be better tolerated, however it is not yet known what side effects 2-

412 NP may cause in humans. These results show that modulation of TRβ regulated

413 pathways can repress tumor growth and are suggestive of future combinational

414 applications of pharmacological compounds in the management of ATC.

415 We have used our investigation into TRβ signaling to elucidate ATC vulnerabilities. Only

416 recently have targeted therapies in ATC shown success in managing disease burden

417 and progression (49). These treatment modalities focus primarily upon the mutational

418 landscape of ATC, however epigenetic alterations, including silencing of the tumor

419 suppressor TRβ, have an unrealized potential to inform drug development. Additionally,

420 reversing the epigenetic silencing of TRβ may itself be beneficial. Finally, our data

421 demonstrates that there is value to maintaining euthyroid status in ATC patients.

422 Hypothyroidism is a known consequence of certain treatment regimens (50) and

423 treating chemotherapy-induced hypothyroidism may improve clinical outcomes due to

424 stimulation of the tumor suppressive activity of TRβ, illustrating the potential for TRβ as

425 a diagnostic marker.

426

427 ACKNOWLEDGEMENTS:

428 We would like to thank Dr. Jane Lian for her help in editing this manuscript. The 429 research reported here was supported by grants from National Institutes of Health U54 430 GM115516 for the Northern New England Clinical and Translational Research Network 431 (G. Stein); National Cancer Institute 1F99CA245796-01 (N.Gillis); UVM Cancer Center- 432 Lake Champlain Cancer Research Organization (C3) 12577-21 (F.Carr); and UVM 433 Larner College of Medicine (F.Carr). SW1736 and KTC-2 cell lines were generously 434 provided by Dr. John Copland III (Mayo Clinic) and 8505C and OCUT-2 cells were 435 generously provided by Dr. Rebecca Schweppe (University of Colorado). Human cell 436 line authentication, NextGen sequencing, automated DNA sequencing and molecular 437 imaging was performed in the Vermont Integrative Genomics Resource supported by 438 the University of Vermont Cancer Center, Lake Champlain Cancer Research 439 Organization, and the UVM Larner College of Medicine. Additional human cell line 440 authentication was performed by the CU Cancer Center Tissue Culture Shared 441 Resource supported by National Cancer Institute P30CA046934. 442

443 REFERENCES:

444 1. Kim WG, Cheng SY. Thyroid hormone receptors and cancer. Biochimica et biophysica 445 acta 2013;1830:3928-36 446 2. Flamant F, Cheng SY, Hollenberg AN, Moeller LC, Samarut J, Wondisford FE, et al. 447 Thyroid Hormone Signaling Pathways: Time for a More Precise Nomenclature. 448 Endocrinology 2017;158:2052-7 449 3. Kim WG, Zhu X, Kim DW, Zhang L, Kebebew E, Cheng SY. Reactivation of the silenced 450 thyroid hormone receptor beta gene expression delays thyroid tumor progression. 451 Endocrinology 2013;154:25-35 452 4. Suzuki H, Willingham MC, Cheng SY. Mice with a mutation in the thyroid hormone 453 receptor beta gene spontaneously develop thyroid carcinoma: a mouse model of 454 thyroid carcinogenesis. Thyroid : official journal of the American Thyroid Association 455 2002;12:963-9 456 5. Zhu X, Zhao L, Park JW, Willingham MC, Cheng SY. Synergistic signaling of KRAS and 457 thyroid hormone receptor beta mutants promotes undifferentiated thyroid cancer 458 through MYC up-regulation. Neoplasia 2014;16:757-69 459 6. Kim WG, Zhao L, Kim DW, Willingham MC, Cheng SY. Inhibition of tumorigenesis by the 460 thyroid hormone receptor beta in xenograft models. Thyroid : official journal of the 461 American Thyroid Association 2014;24:260-9 462 7. Park S, Zhu J, Altan-Bonnet G, Cheng SY. Monocyte recruitment and activated 463 inflammation are associated with thyroid carcinogenesis in a mouse model. Am J Cancer 464 Res 2019;9:1439-53 465 8. Guigon CJ, Zhao L, Lu C, Willingham MC, Cheng SY. Regulation of beta-catenin by a novel 466 nongenomic action of thyroid hormone beta receptor. Molecular and cellular biology 467 2008;28:4598-608 468 9. Guigon CJ, Kim DW, Zhu X, Zhao L, Cheng SY. Tumor suppressor action of liganded 469 thyroid hormone receptor beta by direct repression of beta-catenin gene expression. 470 Endocrinology 2010;151:5528-36

471 10. Carr FE, Tai PW, Barnum MS, Gillis NE, Evans KG, Taber TH, et al. Thyroid Hormone 472 Receptor-beta (TRbeta) Mediates Runt-Related Transcription Factor 2 (Runx2) 473 Expression in Thyroid Cancer Cells: A Novel Signaling Pathway in Thyroid Cancer. 474 Endocrinology 2016;157:3278-92 475 11. Gillis NE, Taber TH, Bolf EL, Beaudet CM, Tomczak JA, White JH, et al. Thyroid Hormone 476 Receptor β Suppression of RUNX2 is Mediated by Brahma Related Gene 1 Dependent 477 Chromatin Remodeling. Endocrinology 2018:en.2018-00128-en.2018- 478 12. Molinaro E, Romei C, Biagini A, Sabini E, Agate L, Mazzeo S, et al. Anaplastic thyroid 479 carcinoma: from clinicopathology to genetics and advanced therapies. Nature Reviews 480 Endocrinology 2017;13:644 481 13. Uphoff CC, Denkmann SA, Drexler HG. Treatment of mycoplasma contamination in cell 482 cultures with Plasmocin. J Biomed Biotechnol 2012;2012:267678 483 14. Martinez-Iglesias O, Garcia-Silva S, Regadera J, Aranda A. Hypothyroidism enhances 484 tumor invasiveness and metastasis development. PLoS One 2009;4:e6428 485 15. Lopez-Mateo I, Alonso-Merino E, Suarez-Cabrera C, Park JW, Cheng SY, Alemany S, et al. 486 The thyroid hormone receptor beta inhibits self-renewal capacity of breast cancer stem 487 cells. Thyroid : official journal of the American Thyroid Association 2019 488 16. Yen C-F, Wang H-S, Lee C-L, Liao S-K. Roles of integrin-linked kinase in cell signaling and 489 its perspectives as a therapeutic target. Gynecology and Minimally Invasive Therapy 490 2014;3:67-72 491 17. Parker BS, Rautela J, Hertzog PJ. Antitumour actions of interferons: implications for 492 cancer therapy. Nat Rev Cancer 2016;16:131-44 493 18. Xing M. Molecular pathogenesis and mechanisms of thyroid cancer. Nat Rev Cancer 494 2013;13:184-99 495 19. Giuliani C, Bucci I, Napolitano G. The Role of the Transcription Factor Nuclear Factor- 496 kappa B in Thyroid Autoimmunity and Cancer. Frontiers in endocrinology 2018;9:471 497 20. Porlan E, Vidaurre OG, Rodriguez-Pena A. Thyroid hormone receptor-beta (TR beta 1) 498 impairs cell proliferation by the transcriptional inhibition of cyclins D1, E and A2. 499 Oncogene 2008;27:2795-800 500 21. Wortel IMN, van der Meer LT, Kilberg MS, van Leeuwen FN. Surviving Stress: Modulation 501 of ATF4-Mediated Stress Responses in Normal and Malignant Cells. Trends in 502 endocrinology and metabolism: TEM 2017;28:794-806 503 22. Landa I, Ibrahimpasic T, Boucai L, Sinha R, Knauf JA, Shah RH, et al. Genomic and 504 transcriptomic hallmarks of poorly differentiated and anaplastic thyroid cancers. The 505 Journal of Clinical Investigation 2016;126:1052-66 506 23. Lachmann A, Xu H, Krishnan J, Berger SI, Mazloom AR, Ma'ayan A. ChEA: transcription 507 factor regulation inferred from integrating genome-wide ChIP-X experiments. 508 Bioinformatics (Oxford, England) 2010;26:2438-44 509 24. Sanchez Calle A, Kawamura Y, Yamamoto Y, Takeshita F, Ochiya T. Emerging roles of 510 long non-coding RNA in cancer. Cancer science 2018;109:2093-100 511 25. Li H, Zhang B, Ding M, Lu S, Zhou H, Sun D, et al. C1QTNF1-AS1 regulates the occurrence 512 and development of hepatocellular carcinoma by regulating miR-221-3p/SOCS3. Hepatol 513 Int 2019;13:277-92

514 26. Li J, Wu QM, Wang XQ, Zhang CQ. Long Noncoding RNA miR210HG Sponges miR-503 to 515 Facilitate Osteosarcoma Cell Invasion and Metastasis. DNA Cell Biol 2017;36:1117-25 516 27. Lu Z, Li Y, Che Y, Huang J, Sun S, Mao S, et al. The TGFbeta-induced lncRNA TBILA 517 promotes non-small cell lung cancer progression in vitro and in vivo via cis-regulating 518 HGAL and activating S100A7/JAB1 signaling. Cancer letters 2018;432:156-68 519 28. Sun Y, Jin SD, Zhu Q, Han L, Feng J, Lu XY, et al. Long non-coding RNA LUCAT1 is 520 associated with poor prognosis in human non-small lung cancer and regulates cell 521 proliferation via epigenetically repressing p21 and p57 expression. Oncotarget 522 2017;8:28297-311 523 29. Zhao D, Dong JT. Upregulation of Long Non-Coding RNA DRAIC Correlates with Adverse 524 Features of Breast Cancer. Noncoding RNA 2018;4 525 30. Yang Y, Zhao Y, Hu N, Zhao J, Bai Y. lncRNA KIAA0125 functions as a tumor suppressor 526 modulating growth and metastasis of colorectal cancer via Wnt/beta-catenin pathway. 527 Cell Biol Int 2019 528 31. Zhang DY, Zou XJ, Cao CH, Zhang T, Lei L, Qi XL, et al. Identification and Functional 529 Characterization of Long Non-coding RNA MIR22HG as a Tumor Suppressor for 530 Hepatocellular Carcinoma. Theranostics 2018;8:3751-65 531 32. Wang H, Guan Z, He K, Qian J, Cao J, Teng L. LncRNA UCA1 in anti-cancer drug 532 resistance. Oncotarget 2017;8:64638-50 533 33. Yang XZ, Cheng TT, He QJ, Lei ZY, Chi J, Tang Z, et al. LINC01133 as ceRNA inhibits gastric 534 cancer progression by sponging miR-106a-3p to regulate APC expression and the 535 Wnt/beta-catenin pathway. Mol Cancer 2018;17:126 536 34. Lin YH, Huang YH, Wu MH, Wu SM, Chi HC, Liao CJ, et al. Thyroid hormone suppresses 537 cell proliferation through endoglin-mediated promotion of p21 stability. Oncogene 538 2013;32:3904-14 539 35. Nagayama Y, Shimamura M, Mitsutake N. Cancer Stem Cells in the Thyroid. Front 540 Endocrinol (Lausanne) 2016;7:20 541 36. Cancer Genome Atlas Research N. Integrated genomic characterization of papillary 542 thyroid carcinoma. Cell 2014;159:676-90 543 37. Landa I, Pozdeyev N, Korch C, Marlow LA, Smallridge RC, Copland JA, et al. 544 Comprehensive Genetic Characterization of Human Thyroid Cancer Cell Lines: A 545 Validated Panel for Preclinical Studies. Clinical cancer research : an official journal of the 546 American Association for Cancer Research 2019;25:3141-51 547 38. Park JW, Zhao L, Willingham M, Cheng S-y. Oncogenic mutations of thyroid hormone 548 receptor β. Oncotarget 2015;6:8115-31 549 39. Meissl K, Macho-Maschler S, Muller M, Strobl B. The good and the bad faces of STAT1 in 550 solid tumours. Cytokine 2017;89:12-20 551 40. Lynch RA, Etchin J, Battle TE, Frank DA. A small-molecule enhancer of signal transducer 552 and activator of transcription 1 transcriptional activity accentuates the antiproliferative 553 effects of IFN-gamma in human cancer cells. Cancer research 2007;67:1254-61 554 41. Yadav RK, Chae SW, Kim HR, Chae HJ. Endoplasmic reticulum stress and cancer. J Cancer 555 Prev 2014;19:75-88 556 42. Nowsheen S, Yang ES. The intersection between DNA damage response and cell death 557 pathways. Experimental oncology 2012;34:243-54

558 43. Pozdeyev N, Gay LM, Sokol ES, Hartmaier R, Deaver KE, Davis S, et al. Genetic Analysis of 559 779 Advanced Differentiated and Anaplastic Thyroid Cancers. Clinical cancer research : 560 an official journal of the American Association for Cancer Research 2018;24:3059-68 561 44. Borson-Chazot F, Dantony E, Illouz F, Lopez J, Niccoli P, Wassermann J, et al. Effect of 562 Buparlisib, a Pan-Class I PI3K Inhibitor, in Refractory Follicular and Poorly Differentiated 563 Thyroid Cancer. Thyroid : official journal of the American Thyroid Association 564 2018;28:1174-9 565 45. De Martino D, Yilmaz E, Orlacchio A, Ranieri M, Zhao K, Di Cristofano A. PI3K blockage 566 synergizes with PLK1 inhibition preventing endoreduplication and enhancing apoptosis 567 in anaplastic thyroid cancer. Cancer letters 2018;439:56-65 568 46. Wong K, Di Cristofano F, Ranieri M, De Martino D, Di Cristofano A. PI3K/mTOR inhibition 569 potentiates and extends palbociclib activity in anaplastic thyroid cancer. Endocr Relat 570 Cancer 2019;26:425-36 571 47. Selzer E, Wilfing A, Sexl V, Freissmuth M. Effects of type I-interferons on human thyroid 572 epithelial cells derived from normal and tumour tissue. Naunyn Schmiedebergs Arch 573 Pharmacol 1994;350:322-8 574 48. Argiris A, Agarwala SS, Karamouzis MV, Burmeister LA, Carty SE. A phase II trial of 575 doxorubicin and interferon alpha 2b in advanced, non-medullary thyroid cancer. Invest 576 New Drugs 2008;26:183-8 577 49. Ljubas J, Ovesen T, Rusan M. A Systematic Review of Phase II Targeted Therapy Clinical 578 Trials in Anaplastic Thyroid Cancer. Cancers (Basel) 2019;11 579 50. Hartmann K. Thyroid Disorders in the Oncology Patient. J Adv Pract Oncol 2015;6:99-106 580

581

582

583

584

585

586

587 Figure 1: Liganded TRβ Repressed Proliferation and Migration of ATC Cells. A)

588 The combination of TRβ expression and T3 treatment repressed the growth of the ATC

589 cells (n=8). Variability is represented by the standard error of the mean; significance

590 was determined by calculating the 95th confident interval of AUC measurements. B) TRβ

591 and T3 acted to increase doubling time of the cells (n=8, * p<0.01). C) SW-TRβ treated

th 592 with T3 exhibited significantly reduced scratch closure at the 95 confidence interval by

593 AUC (n=9) and D) representative images.

594

595 Figure 2: TRβ-T3 Altered the Transcriptome of ATC Cells. A) Thresholds for

596 differentially regulated genes (DEGs) were set at p<0.05 and an absolute

597 log2foldchange of at least 1, upregulated transcripts in red and repressed transcripts in

598 blue. Genes were clustered according to patterns of expression. Clusters 1 and 5 are

599 genes that are T3 regulated independent of TRβ overexpression. Clusters 2-4 require

600 TRβ for T3 to exert a regulatory effect. B) Ingenuity Pathway Analysis (IPA) software

601 was utilized to determine pathways altered within each cluster. Notable cancer-related

602 pathways are highlighted. C) IPA software was used to ascertain upstream regulators

603 within each cluster. Exogenous chemicals were excluded, however endogenous

604 chemicals were retained.

605

606 Figure 3: TRβ Reduced Stem Cell Characteristics in ATC Cells. A) Treatment of

607 SW1736 cells with T3 was sufficient to decrease anchorage-independent growth; the

608 most pronounced effect was observed in the SW-TRβ cells (n=4, * p<0.05). B-C) T3

609 significantly repressed tumorsphere formation in SW-TRβ, but not SW-EV (n=4, *

610 p<0.05). D) Thyroid cancer-specific stem cell marker mRNA transcript levels were

611 significantly repressed by TRβ and T3 by RNA-seq (n=3, * p<0.05). E) Reintroduction of

612 TRβ and treatment with T3 resulted in a significantly increased thyroid differentiation

613 score (TDS) (n=3, * p<0.05).

614

615

616 Figure 4: Re-expression of TRβ Increased Apoptotic Signaling. A) In a comparison

617 of DEGs between SW-EV and SW-TRβ, both T3 treated, IPA predicted changes in

618 pathways important to apoptotic signaling, and B) GSEA predicted activation of

619 apoptosis. C) Representative immunoblot demonstrates that 5 days of T3 treatment

620 induces apoptosis in SW-TR cells assessed by cleavage of PARP1 and caspase 3

621 (n=6).

622

623 Figure 5: The Interferon-JAK1-STAT1 Pathway is Activated by TRβ. A) Interferon

624 pathway effector proteins JAK1 and STAT1 are expressed at higher levels in SW-TRβ

625 cells following T3 treatment (*p<0.05, n=3). B) STAT1 and IRF1 upregulated genes were

626 induced upon overexpression of TRβ and T3 treatment. (n=3, * p<0.05, ** p<0.01, ***

627 p<0.001, **** p<0.0001).

628

629 Figure 6: Pharmacological Manipulation of TRβ Regulated Pathways Inhibits Cell

630 Growth. A) Stimulation of STAT1 transcriptional activity with the agonist 2-NP

631 repressed growth of ATC cell lines. B) The cell cycle inhibitor palbociclib inhibited the

632 growth of ATC cell lines. C) ATC cell lines treated with the PI3K inhibitor buparlisib

633 exhibit reduced growth potential. (n=8, * p<0.05, ** p<0.01, *** p<0.001).

634

635 Figure 7: TRβ Regulates Multiple Pathways to Repress Tumorigenic Activity. TRβ

636 induces expression of epithelial markers, stimulates STAT1 and apoptotic activity, and

637 represses cell cycle progression and the PI3K pathway. Modulation of these pathways

638 ultimately repress the proliferative capacity of anaplastic cancer cells.

639

640

641

Downloaded from mcr.aacrjournals.org on September 30, 2021. © 2020 American Association for Cancer Research. Figure 2 A B SW-EV SW-TRβ SW-EV SW-TRβ Tryptophan Degradation X T3: - + - + T3: - + - + ILK Signaling Melatonin Degradation II 1

r Noradrenaline and Adrenaline Degradation e t

s Notch Signaling u l Interferon Signaling C 450 DEGs Endoplasmic Reticulum Stress Pathway n o

2 Prostanoid Biosynthesis i

r s

e Antigen Presentation t s s e

u Eicosanoid Signaling r l C p 982 DEGs Nucleotide Excision Repair x

e DNA Methylation and Transcriptional Repression Signaling

d Granzyme A Signaling 3

e r Urate Biosynthesis/Inosine 5'-phosphate Degradation z e i t l s Sirtuin Signaling Pathway a u l 369 DEGs

C Protein Ubiquitination Pathway m r Aldosterone Signaling in Epithelial Cells o 4 n

Actin Nucleation by ARP-WASP Complex r e Author Manuscript Published OnlineFirst on June 17, 2020; DOI: 10.1158/1541-7786.MCR-20-02821 t Fatty Acid Activation s Author manuscripts have been peer reviewed and accepted for publication+ but have not yet been edited. u l 2 Oncostatin M Signaling 201 DEGs C g Gαq Signaling o l

5 Factors Promoting Cardiogenesis in Vertebrates

e α-Adrenergic Signaling t s

u Nitric Oxide Signaling in the Cardiovascular System l 19 DEGs C 1 -log(p-value) 1 2 3 4 5 min max Cluster 0 2 4 C 10 -log(p-value) 20 z-score -

5 l 10 o g e ( p r - o v

c 0 0 a s l - u z e

-10 ) -5 Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 -20 -10 ) ) l l l 4 2 x 5 A 3 y R o 1 G 1 F a 1 1 2 1 -3 7 1 1 N 4 e o 1 1 R 1 2 1 G 2 1 1 o R 1 9 7 1 8 e in F F e X 1 6 il F i B K N h L F A T 2 F R F C F s i S P D L P H L D R i B A F B A n l T l B F P d F N P p N R A R P B T o d S O 7 7 2 d G N 0 R C 0 o u G p I T m G a IF T l I N X I Y t a A T E F B E N S a P 0 I 0 r b A F C H a E tr G A a IF IF T K U E M A c tr P C M X 1 F C E tr N 1 R 1 te o m f s T M n S N R u s E I C IR C s T A s l o ( e o N S fr e R T N e C S S e g (c K - r - - M - M o 3 a e D a a S g n B I t f t t o u k P e r e e r F b te b b p m N In Im

THYROID HORMONE RECEPTOR BETA INDUCES A TUMOR SUPPRESSIVE PROGRAM IN ANAPLASTIC THYROID CANCER.

Eric L Bolf, Noelle E Gillis, Cole D Davidson, et al.

Mol Cancer Res Published OnlineFirst June 17, 2020.

Updated version Access the most recent version of this article at: doi:10.1158/1541-7786.MCR-20-0282

Supplementary Access the most recent supplemental material at: Material http://mcr.aacrjournals.org/content/suppl/2020/06/26/1541-7786.MCR-20-0282.DC1

Author Author manuscripts have been peer reviewed and accepted for publication but have not yet been Manuscript edited.

E-mail alerts Sign up to receive free email-alerts related to this article or journal.

Reprints and To order reprints of this article or to subscribe to the journal, contact the AACR Publications Subscriptions Department at [email protected].

Permissions To request permission to re-use all or part of this article, use this link http://mcr.aacrjournals.org/content/early/2020/06/17/1541-7786.MCR-20-0282. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC) Rightslink site.