International Journal of Molecular Sciences

Article FOXE1-Dependent Regulation of Macrophage Chemotaxis by Cells In Vitro and In Vivo

Sara C. Credendino 1,2, Marta De Menna 1,3, Irene Cantone 1 , Carmen Moccia 1 , Matteo Esposito 1, Luigi Di Guida 1, Mario De Felice 1,2 and Gabriella De Vita 1,*

1 Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 80131 Naples, Italy; [email protected] (S.C.C.); [email protected] (M.D.M.); [email protected] (I.C.); [email protected] (C.M.); [email protected] (M.E.); [email protected] (L.D.G.); [email protected] (M.D.F.) 2 Institute of Experimental Endocrinology and Oncology “G. Salvatore”, National Research Council (CNR), 80131 Naples, Italy 3 DBMR-Department for BioMedical Research, University of Bern, 3012 Bern, Switzerland * Correspondence: [email protected]; Tel.: +39-081-746-3240

Abstract: Forkhead box E1 (FOXE1) is a lineage-restricted involved in thyroid cancer susceptibility. Cancer-associated polymorphisms map in regulatory regions, thus affecting the extent of expression. We have recently shown that genetic reduction of FOXE1 dosage modifies multiple thyroid cancer phenotypes. To identify relevant effectors playing roles in thyroid cancer development, here we analyse FOXE1-induced transcriptional alterations in thyroid cells that do   not express endogenous FOXE1. Expression of FOXE1 elicits cell migration, while transcriptome analysis reveals that several immune cells-related categories are highly enriched in differentially Citation: Credendino, S.C.; expressed , including several upregulated chemokines involved in macrophage recruitment. De Menna, M.; Cantone, I.; Moccia, C.; Accordingly, FOXE1-expressing cells induce chemotaxis of co-cultured monocytes. We then asked Esposito, M.; Di Guida, L.; De Felice, if FOXE1 was able to regulate macrophage infiltration in thyroid cancers in vivo by using a mouse M.; De Vita, G. FOXE1-Dependent model of cancer, either wild type or with only one functional FOXE1 allele. Expression of the same Regulation of Macrophage set of chemokines directly correlates with FOXE1 dosage, and pro-tumourigenic M2 macrophage Chemotaxis by Thyroid Cells In Vitro and In Vivo. Int. J. Mol. Sci. 2021, 22, infiltration is decreased in tumours with reduced FOXE1. These data establish a novel link between 7666. https://doi.org/10.3390/ FOXE1 and macrophages recruitment in the thyroid cancer microenvironment, highlighting an ijms22147666 unsuspected function of this gene in the crosstalk between neoplastic and immune cells that shape tumour development and progression. Academic Editor: Daniela Grimm Keywords: FOXE1; chemokines; TAMs; tumour microenvironment Received: 10 June 2021 Accepted: 12 July 2021 Published: 17 July 2021 1. Introduction Publisher’s Note: MDPI stays neutral The incidence of thyroid cancer is constantly increasing, with the most frequent histo- with regard to jurisdictional claims in type, papillary thyroid carcinoma (PTC), representing 2% of total diagnosed neoplasms [1] published maps and institutional affil- and being one of the most common cancers in women under the age of 50 [2,3]. Although iations. the differentiated forms, including PTC, have a good 5-year prognosis in 85% of cases [3], 15% remain with a poor prognosis and can either metastasise or progress to an aggressive anaplastic thyroid carcinoma (ATC). Despite mutations in several genes, as well as the expression levels of different markers having been associated with a poor prognosis, there Copyright: © 2021 by the authors. are not yet defined molecular markers that could predict cancer progression [4]. Cancer Licensee MDPI, Basel, Switzerland. cells are embedded in a complex microenvironment in which pivotal roles are played This article is an open access article by immune cells, the most abundant of which in thyroid cancer are tumour-associated distributed under the terms and macrophages (TAMs). High TAM density has been indeed associated with larger tumour conditions of the Creative Commons size and lymph node metastases in PTC [5,6] as well as with high histologic grade and Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ invasiveness in poorly differentiated thyroid cancer (PDTC) [7,8]. Moreover, in both PTC 4.0/). and PDTC, TAM density is correlated with reduced survival [5,7]. The correlation between

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increasing presence of TAMs and cancer progression and lethality has also been confirmed in ATC, where TAMs could represent more than 50% of the tumour mass [9], although the molecular bases of this correlation are still unclear. It has been shown that advanced thyroid cancer presents massive TAMs infiltration [8,9] and that defined macrophage subpopula- tions play different roles in determining the aggressive cancer course [10–12]. Infiltrating TAMs could, indeed, belong to the tumour-suppressive (M1) or the pro-tumourigenic (M2) subtype [13]. It has been demonstrated that the increase in M2 macrophages during thyroid cancer progression contributes to cancer aggressiveness by promoting angiogenesis and immune escape, particularly in BRAF-mutated cancer [8,10]. Recently, several polymorphisms in regulatory and/or coding regions of the transcrip- tion factor FOXE1 have been associated with increased susceptibility to PTC [14,15] and aggressive forms of thyroid cancer [16,17]. In particular, polymorphisms that increase FOXE1 expression levels have been associated with several bad clinical parameters such as severe histopathological characteristics, reduced degree of differentiation, invasion of lymph nodes and metastases [16,18]. By using a conditional mouse model of BRAFV600E-inducible thyroid cancer [19] crossed with FOXE1 heterozygous knockout mice, we recently demonstrated that FOXE1 gene dosage affects cancer histology, proliferation and differentiation [20], thus showing for the first time a cause–effect relationship between FOXE1 and the thyroid cancer phenotype. To investigate the programme induced by FOXE1, here we ectopi- cally express it in FRT rat thyroid cells lacking endogenous FOXE1 expression, showing that the differentially expressed genes are particularly enriched in categories related to immune cells functions. Moreover, FOXE1-expressing cells increase their migratory ability, being also able to induce monocytes chemotaxis. We then checked if FOXE1 was also involved in a similar phenotype in vivo in a thyroid cancer model with heterozygous FOXE1 knockout. Consistent with in vitro data, reduction of FOXE1 gene dosage downregulates the expression of immune-related genes by reducing Tam’s recruitment and impairing their polarisation towards anti-inflammatory and pro-tumourigenic M2 status. Our results highlight a FOXE1 function never described before, which goes beyond the regulation of thyroid-specific molecules and reveals a novel pathway of modulation of macrophage infiltration in the thyroid cancer microenvironment.

2. Results 2.1. FOXE1 Expression Induces a Migratory Phenotype in FRT Cells Cells in the Fischer rat thyroid epithelial cell line (FRT) are poorly differentiated follicular cells derived from Fischer rat thyroid glands that do not express FOXE1 or other thyroid differentiation markers, except for PAX8 [21]. FOXE1-expressing FRT cells were generated by transfection with a FOXE1-expressing vector. FOXE1 RNA and expression were measured in three independent FOXE1 clones (FC) by RT-PCR and Western blot, respectively, observing that FC26, FC19, and FC55 expressed different FOXE1 protein levels. FRT parental cells (from here on reported as ctr) are negative for FOXE1 expression, as expected (Figure1A). FOXE1 nuclear localisation was confirmed by immunofluorescence (Figure1B), revealing that the FC55 clone shows the most homogeneous staining. As FOXE1 induces thyroid cell motility both in development and in cancer [22,23], we analysed the migratory behaviour of FC. Cell motility was then measured by transwell assay: FOXE1- expressing clones and control cells were seeded in the upper transwell chamber in serum- free medium and allowed to migrate. Representative images of the transwell before (total cells) and after (migrating cells) membrane cleaning is reported in Figure1C, and the quantification of migrated cells per analysed area is reported in Figure1D, showing a significant increase of cell migration only for the clones FC19 and FC55. These results suggest that FOXE1, at high expression levels, stimulates FRT cell motility. Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 3 of 14

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FOXE1 Dapi A B

ctr FOXE1 FC26

ctr FC26 FC19 FC55

FOXE1 FC19

TUBULIN

FC55 Migrated C Total

* ctr D *** ns

FC26

FC19 % of migrated cells

FC55 ctr FC26 FC19 FC55

Figure 1. FOXE1 elicits thyroid cell migration of FOXE1-overexpressing clones. (A) FOXE1 expression in ctr cells and different FOXE1Figure clones 1. FOXE1 (FC) analysed elicits by thyroid qRT PCR cell (upper migration panel) and of WesternFOXE1-overexpressing blot (bottom panel). clones Tubulin. ( wasA) FOXE1 used to normalise. expres- (Bsion) Immunofluorescence in ctr cells and images different of the FOXE1 same clones clones as (FC) in A, analysed probed with by anti-FOXE1 qRT PCR antibody, (upper showingpanel) and nuclear Western FOXE1 localisation.blot (bottom Nuclei panel). are stained Tubulin with Dapi. was 40 ×usedmagnifications to normalise. are shown. (B) Immunofluorescence The scale bar represents 20 images um. (C) Transwellof the same assay performedclones as on in control A, probed cells (ctr) with and FOXE1-expressing anti-FOXE1 antibody, clones FC26, showing FC19, FC55. nuclear Representative FOXE1 localisation. images of the transwell Nuclei usedare beforestained (total) with and after Dapi. (migrated) 40× magnifications swab cleaning of theare inner shown. part ofThe the upperscale chamber.bar represents Cells were 20 stained um. with(C) DapiTranswell in order toassay visualise performed the nuclei. (Don) Thecontrol percentage cells of(ctr) migrated and FOXE1- on total cellsexpressing was calculated. clones One-way FC26, ANOVA FC19, FC55. test was Representa- performed on data,tive and imagesp-values of are the reported transwell for each used clone before relative (total) to ctr. *andp < 0.05,after *** (migrated)p < 0.001, ns: swab not significant. cleaning of the inner part of the upper chamber. Cells were stained with Dapi in order to visualise the nuclei. (D) The percent- 2.2. Transcriptomic Landscape of FOXE1-Expressing FRT Cells age of migrated on total cells was calculated. One-way ANOVA test was performed on data, and p- To investigate the transcriptional programme induced by FOXE1 in thyroid epithelial values are reported for each clone relative to ctr. * p < 0.05, *** p < 0.001, ns: not significant. cells, we selected the FC55 displaying the highest and most homogeneous expression of FOXE1. RNAseq analysis was performed on total RNA from FC55 and control cells. Differen- 2.2. Transcriptomic Landscapetially expressed of FOXE1-Expressing genes (DEG) were considered FRT Cells with a ±2-fold change and p ≤ 0.05 cut-off and To investigate analysedthe transcriptional by programme (GO). A total induced of 750 DEGby FOXE1 resulted in as thyroid being regulated epithelial± 2-folds , of which 469 (62.5%) were upregulated and 281 (37.5%) were downregulated (Figure2A). GO cells, we selected theterms FC55 enriched displaying in upregulated the highest genes were and clustered most inhomogeneous functional categories expression mainly related of to FOXE1. RNAseq analysissignal transduction, was performed macrophage on total recruitment RNA andfrom differentiation, FC55 and metalcontrol ion cells. homeostasis Dif- and ferentially expressedtransport genes and(DEG) extracellular were considered matrix components with a (Figure±2-fold2B). change GO terms and significantly p ≤ 0.05 cut- enriched off and analysed byin Gene downregulated Ontology genes (GO). were A insteadtotal of mainly 750 DEG related resulted to cell cycle, as being epigenetic regulated regulation of ± 2-folds, of which chromatin,469 (62.5%) immune were cell upre migrationgulated and cholesteroland 281 (37.5%) metabolism were (Figure downregulated2C). A panel of DEG, grouped for functional categories, was then validated performing quantitative RT-PCR on the (Figure 2A). GO termsthree enriched clones FC26, in FC19upregulate and FC55d (Figuregenes S1).were clustered in functional catego- ries mainly related to signal transduction, macrophage recruitment and differentiation, metal ion homeostasis and transport and extracellular matrix components (Figure 2B). GO terms significantly enriched in downregulated genes were instead mainly related to cell cycle, epigenetic regulation of chromatin, immune cell migration and cholesterol metabo- lism (Figure 2C). A panel of DEG, grouped for functional categories, was then validated performing quantitative RT-PCR on the three clones FC26, FC19 and FC55 (Figure S1).

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A dow$regulated, up$regulated,

37,5%

62,5%

B Up-regulated Genes

0,0 0,5 1,0 1,5 2,0 2,5 3,0 3,5 4,0 Sarc Homology 2 domain protein Member RAS oncogene family (Rab27a), Rab binding domain Signaling Response to hypoxia and Wnt signaling pathway Signal Src homology-3 domain protein transduction Protein-tyrosine phosphatase, /non-receptor type Negative regulation of protein kinase B signaling

Heparin binding SOCS (Suppressor of cytokine signalling) protein Macrophage Regulation of macrophage derived foam cell differentiation differentiation Positive regulation of macrophage chemotaxis and Cellular response to interleukyn 6 recruitment

Glucose transport Negative regulation of glucose import

Ion homeostasis Cellular metal ion homeostasis EGF-like calcium-binding Ion Copper transport homeostasis, Cellular copper ion omeostasis transport and Regulation of potassium ion transmembrane transport binding Cation channel activity Excitatory synapses,postsynaptic specialization, density

Fibronectin type-III domain Collagen functions Extracellular Collagen-activated tyrosine kinase receptor signaling pathway,… matrix Collagen trimer Extracellular fibril organization

Extracellular exosome Vescicle Lysosoma membrane trafficking Cytoplasmic vesicle membrane

Positive regulation of programmed cell death Negative regulation of necroptotic process Cell death Positive regulation of protein ubiquitination involved in ubiquitin-…

Protein modification process Others

Figure 2. Conts.

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C Down-regulated Genes

00 01 01 02 02 03 03 04 04 05 Centromere Kinetochore Microtubule-based movement, kinesin complex Regulation of mitotic sister chromatid separation Mitotic metaphase plate congression Cell Cluster 13: ATP binding cycle Regulation of metaphase/anaphase transition of cell cycle Mitotic cell cycle phase transition Nucleoside-triphosphatase activity Microtubule-based process(Gap junction/phagosome)

Nucleosome Core DNA replication-dependent nucleosome assembly Nucleotide-binding Epigenetic DNA methylation on cytosine regulation Chromatin silencing DNA replication-independent nucleosome assembly

Regulation of cell migration Regulation of T cell migration Immune Positive regulation of T cell migration cell Positive regulation of cell migration migration Regulation of chemokine production

Cholesterol metabolic process Cholesterol metabolism Cholesterol homeostasis Cholesterol LDL receptors metabolism Positive regulation of cholesterol biosynthetic process Positive regulation of steroid biosynthetic process Cholesterol biosynthetic process

Acetylcholine receptor activity Neuronal Cerebral cortex development processes

Serine-type endopeptidase activity Others Hemopoiesis

Figure 2. Functional annotation of differentially expressed genes in FOXE1-overxpressing cells. RNAseq analysis was Figure 2. Functional annotation of differentially expressed genes in FOXE1-overxpressing cells. RNAseq analysis was performed on total RNA from FC55 and control cells. (A) Pie chart of differentially expressed genes (DEG), considered performed on total RNA from FC55 and control cells. (A) Pie chart of differentially expressed genes (DEG), considered with a ±2-fold change (FC) and p ≤ 0.05 cut-off and analysed by Gene Ontology (GO). A total of 750 DEG resulted as with a ±2-fold change (FC) and p ≤ 0.05 cut-off and analysed by Gene Ontology (GO). A total of 750 DEG resulted as being regulated,being regulated, of which of which 469 (62.5%) 469 (62.5%) upregulated upregulated and and281 281(37.5%) (37.5%) downregulated. downregulated. Functional Functional categories categories were were significantly significantly enrichedenriched among among genes genes that that were were either either ( (BB)) upregulated upregulated or or ( (CC)) downregulated. downregulated. Functional Functional ca categoriestegories (highlighted (highlighted on on the the rightright in in vertical vertical groups) werewere obtainedobtained byby clusteringclustering the the functional functional annotation annotation contained contained in in the the web-based web-based DAVID DAVID database. data- base.To perform To perform clustering, clustering, we used we multipleused multiple annotations—namely, annotations—namely, gene ontology gene ontology for biological for biological processes, processes, molecular molecular function functionand cellular and componentscellular components (GO_DIRECT), (GO_DI pathways,RECT), pathways, protein interactions, protein interactions, protein domain protein and domain tissue expressions.and tissue expressions. Enrichment Enrichmentscores are plotted scores onlyare plotted for clusters only containingfor clusters multiplecontaining terms multiple with p terms< 0.05. with p < 0.05.

2.3.2.3. FOXE1 FOXE1 Enhances Enhances Chemoattractant Chemoattractant Ability Ability of of FRT FRT Cells Cells TheThe observed observed enrichment enrichment of of multiple multiple functional functional categories categories related related to to immune immune cells cells recruitment,recruitment, migration andand differentiation differentiation in inFOXE1 FOXE1-induced-induced DEG DEG was was largely largely unexpected. unex- pected.Particularly, Particularly, several several genes involved genes involved in macrophages in macrophages chemotaxis chemotaxis and differentiation and differentia- were tionclustered were clustered in the upregulated in the upregulated genes list. genes Among list. Among these, these, the most the stronglymost strongly upregulated upreg- ulatedwas CCL2 was, CCL2 a well-established, a well-established macrophage macrophage chemoattractant. chemoattractant. In addition, In addition, several several other genes encoding secreted involved in macrophage recruitment and activation, such

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Int. J. Mol. Sci. 2021, 22, 7666 6 of 13 other genes encoding secreted proteins involved in macrophage recruitment and activa- tion, such as CCL7, CSF1, LGALS3BP and INPP5D [24–26], resulted as being upregulated in FC55 by RNA-seq (Figure 3A). Upregulation of these macrophage ligands was vali- datedas CCL7, by quantitative CSF1, LGALS3BP RT-PCRand inINPP5D the FC,[24 revealing–26], resulted a correlation as being upregulatedbetween FOXE1 in FC55 dosage andby the RNA-seq extent (Figureof these3A). genes’ Upregulation upregulation of these (Figure macrophage 3B). To ligandsinvestigate was if validated the induction by of quantitative RT-PCR in the FC, revealing a correlation between FOXE1 dosage and the these genes could change macrophage recruitment by chemoattractants release in the ex- extent of these genes’ upregulation (Figure3B). To investigate if the induction of these genes tracellularcould change medium, macrophage we tested recruitment the ability by chemoattractantsof FC to induce releasemonocyte in the chemotaxis extracellular by co- culturemedium, assay. we FRT tested and the the ability three of FOXE1 FC to induce clones monocyte were cultured chemotaxis in the by transwell co-culture lower assay. cham- berFRT in order and the to threeobtainFOXE1 secretedclones proteins were cultured accumulation in the transwell in the medium. lower chamber U937 human in order mon- ocytesto obtain were secreted then added proteins in the accumulation upper chambe in ther in medium. serum-free U937 medium, human monocytes and their weremigration throughthen added the transwell in the upper porous chamber membrane in serum-free was me medium,asured (Figure and their 3C). migration A statistically through signif- icantthe increase transwell of porous U937 cells membrane migration was was measured observed (Figure only3C). when A statistically co-cultured significant with the high FOXE1increase expressing of U937 cells clones migration FC19 wasand observed FC55 (Figure only when 3D), co-cultured demonstrating with the a highFOXE1FOXE1 dose-de- expressing clones FC19 and FC55 (Figure3D), demonstrating a FOXE1 dose-dependent pendent gain in chemoattractant activity. gain in chemoattractant activity.

A B

60 FC26 FC19 FC55 40 25

20

15

10

ctr Relative expression 5

0 CCL2 LGALS3BP CSF1 CCL7 INPP5D

* C D *** ns % of U937 migrated

ctr FC26 FC19 FC55

Figure 3. FOXE1 modulates macrophage-related genes and their migration in vitro.(A) Macrophage-related genes from RNA-seq analysis of FOXE1-expressing FRT. (B) Quantitative RT-PCR analysis of genes in A in FOXE1 clones with low -∆∆Ct Figure(FC26), 3. FOXE1 moderate modulates (FC19) andmacrophage-related high (FC55) FOXE1 genes expression. and their The datamigration are shown in vitro. as ctr-relative (A) Macrophage-related expression (2 ). genes Actin from RNA-seqwas usedanalysis to normalise. of FOXE1-expressing The starting value FRT. of ( theB) Quantitative control, set to 1,RT-PCR is indicated analysis by the of dotted genes line.in A ( Cin) CtrFOXE1 cells andclones FOXE1 with low (FC26),clones moderate were seeded (FC19) in transwelland high low (FC55) chamber FOXE1 and U937expression. cells were The added data in are the uppershown chamber as ctr-relative after 48 h.expression (D) The percentage (2-∆∆Ct). Actin was usedof migrating to normalise. U937 cells The was starting evaluated value after of 4the h. One-waycontrol, set ANOVA to 1, is test indicated was performed by the ondotted data, line. and p (-valuesC) Ctr arecells reported and FOXE1 clonesfor were each seeded clone relative in transwell to ctr. * plo

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were treated with doxycycline for one week to develop thyroid cancer [19], and the ex- pression levels of CCL2, CSF-1, LGALS3BP, INPP5D and CCL7, together with that of the Int. J. Mol. Sci. 2021, 22, 7666 7 of 13 chemokine receptors CCR2 and CSF1R, were measured in cancer specimens by quantita- tive RT-PCR. Tumours developed in BRAF FOXE1+/- background showed significantly re- duced expression of all the genes investigated compared with those developed in BRAF FOXE1CCL2,+/+ mice CSF-1, (Figure LGALS3BP, 4A,B). INPP5D In this and cancer CCL7, model, together it with is known that ofthe that chemokine BRAFV600E receptors activation inducesCCR2 a androbust CSF1R, recruitment were measured of M2-polarised in cancer specimens TAMs [12]. by quantitative Tumour infiltration RT-PCR. Tumours by TAMs developed in BRAF FOXE1+/- background showed significantly reduced expression of all the was then evaluated on thyroid cancer sections by immunohistochemistry (IHC) for the genes investigated compared with those developed in BRAF FOXE1+/+ mice (Figure4A,B). macrophageIn this cancer markers model, IBA1 it is knownand for that GALECTIN-3, BRAFV600E activation this latter induces being a described robust recruitment to regulate alternativeof M2-polarised macrophage TAMs [activation12]. Tumour towards infiltration an byM2 TAMs pro-tumourigenic was then evaluated state on [27–29]. thyroid As showncancer in Figure sections 4C,D, by immunohistochemistry both markers show (IHC)reduced for staining the macrophage in the BRAF markers FOXE1 IBA1+/- and cancer samplesfor GALECTIN-3, with respect this to latterthe BRAF being describedFOXE1+/+ toones. regulate The alternative expression macrophage of two additional activation M2- relatedtowards markers, an M2 ARGINASE1 pro-tumourigenic (ARG) state and [27 –INTERLEUKINE1029]. As shown in Figure (IL10)4C,D, [30,31], both markers was meas- +/- uredshow to further reduced evaluate staining if in the the reduction BRAF FOXE1 of FOXE1cancer levels samples could with affect respect the to abundance the BRAF of +/+ this FOXE1macrophageones. subpopulation The expression ofwithin two additional the tumour. M2-related BRAF markers, FOXE1 ARGINASE1+/- cancers (ARG)showed a and INTERLEUKINE10 (IL10) [30,31], was measured to further evaluate if the reduction weaker expression of both M2 markers with respect to the BRAF FOXE1+/+ ones (Figure of FOXE1 levels could affect the abundance of this macrophage subpopulation within the 4E). tumour.Since cancer-associated BRAF FOXE1+/- cancersfibroblasts showed (CAF a weakers), together expression with TAMs, of both are M2 the markers main with compo- nentsrespect of the to tumour the BRAF stroma, FOXE1 +/+weones looked (Figure at α4E).-SMA Since expression cancer-associated as a CAFs-specific fibroblasts (CAFs), marker. IHCtogether for α-SMA with reveals TAMs, are that the reducing main components FOXE1 levels of the tumourin BRAF stroma,V600E-induced we looked thyroid at α-SMA cancer decreasesexpression the CAFs as a CAFs-specific stromal expansion marker. IHCobserved for α-SMA in FOXE1 reveals wild that reducingtype background FOXE1 levels (Figure 4F). inAs BRAF control,V600E -inducedwe analysed thyroid WT cancer and FOXE1 decreases+/- mice, the CAFs that stromal do not expansion develop observedcancer because in +/- theyFOXE1 are not wild transgenic type background for BRAF (FigureV600E [20],4F). Asobserving control, we no analysed statistically WT andsignificant FOXE1 differencesmice, V600E in thethat expression do not develop of chemokines cancer because and they their are receptors not transgenic (Figure for BRAFS2A) or in[ 20IHC], observing staining for no statistically significant differences in the expression of chemokines and their receptors IBA1 (Figure S2B,C). (Figure S2A) or in IHC staining for IBA1 (Figure S2B,C).

A 4 BRAF FOXE1+/+ +/+ BRAF FOXE1+/- B 20 BRAF FOXE1 BRAF FOXE1+/- 3 15 ** 2 *** 10 ** 1 *** * * 5 NT-Relative expression NT-Relative expression 0 0 CCL2 LGALS3BP CSF1 CCL7 INPP5D CCR2 CSF1R

C BRAF FOXE1+/+ BRAF FOXE1+/− D BRAF FOXE1+/+ BRAF FOXE1+/− 20X 20X GALECTIN-3 GALECTIN-3 IBA1 40X 40X

Figure 4. Conts.

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F BRAF FOXE1+/+ BRAF FOXE1+/− E

8 BRAF FOXE1+/+ +/-

BRAF FOXE1 20X

6

* α-SMA * 4

2 NT-Relative expression 0

ARG IL10 40X

Figure 4. FOXE1 modulates macrophage recruitment in vivo.(A) BRAF FOXE1+/+ and BRAF FOXE1+/- mice were treated with doxycycline for one week to induce BRAFV600E-dependent thyroid cancer. RNA was isolated from pools of Figurewith 4. the FOXE1 same genotypemodulates and macrophage treatment. Macrophage-related recruitment in vivo. genes (A and) BRAF (B) CCR2 FOXE1and+/+CSF1R and BRAFexpression FOXE1 was+/- analysedmice were by treated withquantitative doxycycline RT-PCR, for one and week the resultsto induce are reportedBRAFV600E as-dependent the fold change thyroid of BRAF cancer. FOXE1 RNA+/+ was- and isolatedBRAF FOXE1 from +/-pools-treated of thyroids withgroups the same on the genotype respective and untreated treatmen group.t. Macrophage-related * p < 0.05, ** p < 0.01; genes *** andp < 0.001.(B) CCR2 (C) Thyroidand CSF1R sections expression were analysed was analysed by by quantitativeimmunohistochemical RT-PCR, and staining the results for macrophage are reported markers as the IBA1 fold and change (D) GALECTIN3. of BRAF FOXE1 Nuclei+/+- areand stained BRAF withFOXE1 haematoxylin.+/--treated groups on the20× respective(upper panels) untreated and 40 ×group.(lower * panels)p < 0.05, of ** the p < 20 0.01;× boxed *** p < area, 0.001 magnifications. (C) Thyroid aresections shown. were (E) Expression analysed by analysis immunohisto- of chemicalM2 macrophage staining for subpopulation macrophage markers markersARGINASE1 IBA1 and (ARG)(D) GALECTIN3. and INTERLEUKINE10 Nuclei are(IL10) stained on with the same haematoxylin. samples as in 20× A. (upper panels)* p < and 0.05. 40× (F) (lower Immunohistochemical panels) of the 20× analysis boxed of area,α-SMA magnifications in thyroid sections are shown. from BRAF (E) Expression FOXE1+/+ analysisand BRAF of FOXE1M2 macrophage+/- subpopulationdoxycycline-treated markers mice. ARGINASE1 Nuclei are (ARG) stained and with INTERLEUKINE10 haematoxylin. 20X (upper (IL10) panel) on the and same 40X samples (lower panels) as in ofA. the * p area < 0.05. (F) Immunohistochemicalboxed in 20× magnifications analysis are ofshown. α-SMA The in thyroid images aresections representative from BRAF of six FOXE1 different+/+ and images. BRAF FOXE1+/- doxycycline-treated mice. Nuclei are stained with haematoxylin. 20X (upper panel) and 40X (lower panels) of the area boxed in 20× magnifi- cations are shown. The images3. Discussionare representative of six different images. The transcription factor FOXE1, essential for thyroid organogenesis and function, has 3.been Discussion identified as susceptibility gene for differentiated thyroid cancer. Most of cancer- associated FOXE1 polymorphisms are likely to regulate the gene’s expression, as the poly- The transcription factor FOXE1, essential for thyroid organogenesis and function, has morphisms fall in locus regulatory regions. Despite the identification of numerous FOXE1 beenvariants identified associated as with susceptibility PTC risk, it isgene poorly for understood differentiated how they thyroid modulate cancer. thyroid Most cancer of cancer- associatedsusceptibility FOXE1 at the molecularpolymorphisms level. Recently, are likely we demonstrated to regulate the that gene’sFOXE1 expression,dosage alteration as the pol- ymorphismsaffects thyroid fall cancer in histology,locus regulatory proliferation regions. and differentiation Despite thein vivoidentification[20], thus showing of numerous FOXE1for the firstvariants time aassociated cause–effect with relationship PTC risk, between it is poorlyFOXE1 understoodand thyroid how cancer they phenotype. modulate thy- roidTo further cancer investigate susceptibility the phenotypic at the molecular effects of FOXE1 level. levelRecently, variation we ondemonstrated thyroid cancer, that here FOXE1 dosagewe combined alteration two complementaryaffects thyroid approaches: cancer histology, gain-of-function proliferationin vitro andand differentiation loss-of-function in vivo [20],in vivo thus. The showing transcriptional for the first landscape time induceda cause–effect by FOXE1 relationshipin FRT thyroid between cells FOXE1in vitro isand thy- enriched in differentially expressed genes involved in immune response and macrophage roid cancer phenotype. To further investigate the phenotypic effects of FOXE1 level vari- recruitment/activation, such as the chemokines CCL2, CSF1, LGALS3BP, INPP5D and CCL7. ationFOXE1 on-expressing thyroid cancer, cells increase here we their combined ability to two induce complement monocytesary chemotaxis approaches:in vitro gain-of-func-, thus tionindicating in vitro that and the loss-of-function upregulated chemokines in vivo. areThe secreted transcriptional and functional. landscape Interestingly, induced these by FOXE1 ingenes FRT result thyroid frequently cells in in vitro being upregulatedis enriched duringin differentially the progression expressed of several genes cancers involved [32–34]. in im- muneThe BRAF responseV600E-dependent and macrophage mouse model recruitmen of thyroidt/activation, cancer with such a single as functionalthe chemokinesFOXE1 CCL2, CSF1,allele (LGALS3BP,FOXE1+/-) was INPP5D then used and to CCL7 test if. FOXE1 the identified-expressing genes werecells underincreaseFOXE1 theircontrol, ability to in- ducealso inmonocytes vivo. When chemotaxis cancer was in induced, vitro, thus reduced indicating expression that of the the upregulated identified chemokines chemokines are +/- secretedwas observed and functional. in FOXE1 Interestingly,, thus showing these that these genes genes result are underfrequently FOXE1 in control, being upregulated being both upregulated in vitro by FOXE1 ectopic expression and downregulated in vivo by FOXE1 during the progression of several cancers [32–34]. The BRAFV600E-dependent mouse model hemizygosity. It is worth noting that such correlation does not occur in a normal thyroid, +/- ofbeing thyroid evident cancer only with in poorly a single differentiated functional and/or FOXE1 neoplastic allele contexts,(FOXE1 such) was as FRTthen cells used and to test if theBRAFV600E-induced identified genes were cancer, under respectively, FOXE1 similar control, to whatalso hasin vivo. already When been cancer demonstrated was induced, reducedfor FOXE1 expressioncontrol of of thyroid the identified differentiation chemokines [20]. Because was observedFOXE1-regulated in FOXE1 chemokines+/-, thus showing thatCCL2 these and CSF1,genes through are under the bindingFOXE1 of control, the myeloid being cells both receptors upregulated CCR2 and inCSF1R, vitro by respec- FOXE1 ec- topic expression and downregulated in vivo by FOXE1 hemizygosity. It is worth noting that such correlation does not occur in a normal thyroid, being evident only in poorly differentiated and/or neoplastic contexts, such as FRT cells and BRAFV600E-induced can- cer, respectively, similar to what has already been demonstrated for FOXE1 control of

Int. J. Mol. Sci. 2021, 22, 7666 9 of 13

tively, are responsible for TAMs recruitment in several solid cancers [12,35,36], we evaluated TAMs infiltration in the experimental thyroid cancers by measuring the expression of the two receptors and the TAM markers IBA1 and GALECTIN-3, involved in macrophages motility/migration [28,29]. Our results show that reduction in vivo of FOXE1 impairs the upregulation of both IBA1 and GALECTIN-3, induced by BRAFV600E activation, indicating a FOXE1-dependent reduction of TAMs recruitment. In particular, the decrease of GALECTIN-3 staining, ARGINASE and IL10 levels indicates that this reduction mainly concerns the M2 population. It has already been shown, in the same cancer model, that targeting CLC2 and CSF1 impairs TAMs recruitment and M2 polarisation [12], as we here obtained by targeting FOXE1 as well. This suggests that in thyroid, the processes driven by these chemokines could be downstream of FOXE1, indicating that acting on FOXE1 could affect at the same time CCL2/CCR2 or CSF1/CSF1R signalling that are currently faced individually [37–39]. TAMs are important players in cancer progression because of their specific function and their contribution in modelling and determining cancer stroma properties [40] together with CAFs. Consistently, we also observed a reduction of CAFs in BRAF FOXE1+/- tumour stroma. CAFs can promote tumourigenesis and metastasis dissemination by sustain- ing inflammation, angiogenesis, immunosuppression, epithelial–mesenchymal transition and extracellular matrix remodelling [41,42]. Thus, the crosstalk between CAFs and M2 macrophages and their synergistic effect on cancer progression [43] could be impaired in FOXE1+/- cancers. The demonstration that variations in FOXE1 dosage change the tumour microenvironment suggests a previously unsuspected function for this transcription factor in addition to the well-established regulation of thyrocyte differentiation, indicating that FOXE1 could play a role more in thyroid cancer progression than in its onset. In conclusion, this study highlights a novel function of FOXE1 in modulating TAMs infiltration and stromal organisation in differentiated thyroid cancer. This is the first time, to the best of our knowledge, that FOXE1 has been connected to the expression of immune-related genes, thus paving the way to novel perspectives to understand the contribution of such a transcription factor to thyroid cancer susceptibility.

4. Materials and Methods 4.1. Plasmid Preparation Rat FOXE1 CDS sequence (NM_138909.1) was amplified by PCR from the pCMV FOXE1 plasmid [44] and subcloned in the NheI site of CET 1019 AS-puro-SceI plasmid (Merck Millipore Corporation, Burlington, MA, USA).

4.2. Cell Culture and Transfection FRT (Fisher rat thyroid cells) cells were cultured in Coon’s Modified Ham’s F12 Medium (Euroclone, Milan, Italy) supplemented with 5% foetal bovine serum (Euroclone), 1% penicillin (Euroclone) and 1% streptomycin (Euroclone). U937 cells were cultured in RPMI supplemented with 10% foetal bovine serum. FRT cells were stably transfected with CET 1019 AS-Puro-SceI- FOXE1 plasmid using FuGene 6 Transfection Reagent (Roche, Basel, Switzerland) according to manufacturer’s instruction. Briefly, 3 µg of CET 1019 AS-Puro-SceI-FOXE1 plasmid or 3 µg of empty vector was transfected in FRT cells seeded in 100 mm culture dishes (Corning, NY, USA) at 20% confluence. Forty-eight hours after transfection, cells were selected in complete medium supplemented with 1 µg/mL of puromycin. After two weeks of continuous selection, single colonies were picked from plates transfected with either CET 1019 AS-Puro-SceI-FOXE1 vector or empty vector. The clones overexpressing the greatest amount of FOXE1 (FOXE1-FRT) were used for the showed experiments. Int. J. Mol. Sci. 2021, 22, 7666 10 of 13

4.3. RNA Sequencing and Bioinformatic Analysis Total RNA from FRT and FOXE1-FRT was assessed with Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, CA, USA). Indexed libraries were obtained from 500 ng of each sample using TrueSeq polyA+ mRNA Sample Prep Kit (Illumina, Sam Diego, CA, USA) according to manufacturer’s instructions. Three replicates for each sample were analysed. HiSeq1500 platform (Illumina) was used to perform libraries sequencing at 8 pmol/ul per lane (paired-end, 2 × 100 cycles) with coverage of about 20 × 106 reads per sample. FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (accessed on 10 June 2021)) was used to control sequencing raw data (.fastq files), and the selected reads were aligned to rat genome (rn4/Baylor 3.4 assembly) using Tophat 2.0.10 [45] with standard parameters. Gene annotation was obtained for all known genes in the rat genome as provided by UCSC (rn4) (https://support.illumina.com/sequencing/sequencing_software/igenome.ilmn (accessed on 10 June 2021)). To identify differentially expressed genes between FRT and FOXE1-FRT, the software HTSeq-count [46] was used to find known genes with more than 10 reads that served as input of DESeq software 1.14.0 [47] to normalise each transcript expression value. Transcripts with a fold change <−3 or >3 and a p-value < 0.05 were selected. Differentially expressed genes functional annotation analysis was performed by using DAVID. The web- based clustering tool was used for clustering different functional annotation categories: gene ontology, pathways, protein interaction, protein domains, tissue expression, sequences features and keywords. Only clusters containing more than one term with p < 0.05 were considered. The raw data are available as supplementary files.

4.4. Immunoblotting Whole cell lysates of FRT cells or stable FOXE1 clones were prepared using 50 mM Tris HCl pH 8, 5 mM MgCl2, 150 mM NaCl, 0.5% Deoxycholic Acid, 0.1% SDS, 1% Triton, 1× protease inhibitor cocktail, 0.5 mM PMSF, 5 mM sodium orthovanadate (Na3VO4), 10 mM sodium fluoride (NaF), 0.5 mM sodium pyrophosphate (Na4P2O7) and 1 mM dithiothreitol (DTT) (all provided by Sigma-Aldrich, St. Luis, MO, USA). Cell lysates were incubated 15 min on ice and centrifuged at full speed at 4 ◦C for 25 min. Protein concentration was estimated using the BCA Protein Assay Kit (Thermo Fisher Scientific Inc., Rockford, IL, USA). Protein lysates were loaded on precasted NuPAGE 4–12% Bis-Tris gels (Life Technolo- gies Ltd., Carlsbad, CA, USA). Gels were electroblotted on Immobilion-P PVDF membranes (Millipore, Billerica, MA, USA) and screened for FOXE1 (De Vita et al. 2005) and TUBULIN (Sigma-Aldrich). Secondary antibodies mouse IgG horseradish peroxidase-linked whole antibody (GE Healthcare, Little Chalfont, Buckinghamshire, UK) and rabbit IgG horseradish peroxidase- linked whole antibody (GE Healthcare) were used as indicated by manufacturers. Chemi- luminescence was detected using Pierce ECL Western blotting substrate (Thermo Fisher Scientific Inc., Rockford, IL, USA).

4.5. Immunofluorescence Assay Cells were cultured on 12 mm diameter glass coverslips. At 24 h after seeding, cells were fixed in 4% PFA for 15 min, permeabilised for 3 min in 0.2% Triton X-100 and blocked for 30 min in 5% BSA. Cells were incubated for 1 h at RT with primary antibody anti- FOXE1, washed thrice with PBS 1X and incubated after with secondary FITC-tagged goat anti-rabbit antibody (Jackson Immunoresearch Laboratories Inc, West Grove, PA, USA). Immunofluorescence was captured by confocal laser scanner microscope Zeiss LSM 510 (Carl Zeiss AG, Oberkochen, Germany).

4.6. Transwell Assay Transwell Permeable Support with 8.0 µm (for FRT) or 5.0 µm (for U937) polycarbonate filter membrane 6.5 mm insert provided by Corning, were used for motility assay. To evaluate FOXE1 clones’ migration, cells were then fixed for 15 min in PFA 4% permeabilised with 0.2% Triton X-100 for 5 min, blocked with 5% BSA for 30 min and stained with Dapi Int. J. Mol. Sci. 2021, 22, 7666 11 of 13

for 5 min. The results of two independent experiments performed in duplicate are reported; for each replicate, a minimum of 4 areas were analysed. To evaluate U937 migration, FRT and FOXE1-FRT were seeded in transwell lower chamber to allow cell growth and accumulation of secreted proteins in culture medium for 48 h, then U937 were added in the upper chamber, and their migration was evaluated 4 h after. Representative areas of the transwell were acquired with a 10× objective. Cells migrated in the lower chamber were recovered from the suspension and counted; the results of two independent experiments performed in triplicate are reported. For each replicate, migrating cells were counted twice using a Neubauer chamber. Representative areas of the transwell were acquired with a 10× objective.

4.7. Quantitative Real-Time PCR Total RNA isolation and retro-transcription were performed as described in Cre- dendino et al. 2020 [20]. Quantitative Real-Time PCR on total cDNA was performed with iTaq Universal SYBR Green Supermix (Bio-Rad. Hercules, California, USA) using gene-specific oligonucleotides. Mouse CSF1, CSF1R, CCL2, CCL2R, ARGINASE, IL10 and ß- ACTIN oligonucleotides were from Ryder et al. [12]. RAT CCL2, RAT CSF1, CCL7. LGALS3B, INPP5D and TUBULIN oligonucleotides sequences are: RAT CCL2 FW: TGTAGCATCCACGTGCTGTC RAT CCL2 REV: CCGACTCATTGGGATCATCT RAT CSF1 FW: CTGCCCTTCTTCGACATGGAT RAT CSF1 REV: CTACAGTGCTCCGACACCT CCL7 FW: TGAAGCCAGCTCTCTCTCTC CCL7 REV: TGGATGAATTGGTCCCATCT LGALS3B FW: CTCTGTGTTCTTGCTGGTTCC LGALS3B REV: CTGAGGCCCCATTAACCA INPP5D FW: ACCTGCAGTTCCCCGTGC INPP5D REV: GGTGGGCATGACACTTTCTG TUBULIN FW CAACACCTTCTTCAGTGAGACAGG TUBULIN REV: TCAATGATCTCCTTGCCAATGGT

4.8. Mice Treatment and Genotyping Animals were kept, fed and genotyped as already described [20].

4.9. Immunohistochemistry Thyroid sections were obtained and stained as described in Credendino et al. 2020 using the following primary antibodies: GALECTIN-3 (#CL8942B, Cedarlane, Burlington, Canada), alpha smooth muscle actin (α-SMA) (#M0851, Agilent-Dako, Santa Clara, Califor- nia, USA) and IBA-1 (#019-19741, Wako, Neuss, Deutschland). Images were obtained as described in Credendino et al. 2020 [20].

Supplementary Materials: The following are available online at https://www.mdpi.com/article/10 .3390/ijms22147666/s1. Author Contributions: Conceptualisation, G.D.V. and M.D.F.; methodology, M.D.M. and I.C.; investiga- tion, S.C.C., M.D.M., C.M. and M.E.; resources, L.D.G.; data curation, S.C.C. and I.C.; writing—original draft preparation, S.C.C.; writing—review and editing, G.D.V.; supervision, G.D.V. and M.D.F.; funding acquisition, G.D.V. All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the Italian Ministry of University and Research (MIUR) grant PON03PE_00060_7 and by POR Campania FESR 2014-2020 “SATIN” grant, both to GDV. Institutional Review Board Statement: The present study has been approved by the Institutional Animal Care and Use Committee (IACUC) of University of Naples Federico II and by the Italian Ministry of Health with protocol no. 2013/0078506. Conflicts of Interest: The authors declare no conflict of interest. Int. J. Mol. Sci. 2021, 22, 7666 12 of 13

References 1. Kitahara, C.M.; Sosa, J.A. The changing incidence of thyroid cancer. Nat. Rev. Endocrinol. 2016, 12, 646–653. [CrossRef][PubMed] 2. Douglas, E.H.; Rhoads, A.; Thomas, A.; Aloi, J.; Suhl, J.; Lycan, T., Jr.; Oleson, J.; Conway, M.K.; Klubo-Gwiezdzinska, J.; Lynch, C.F.; et al. Incidence and Survival in Reproductive-Aged Women with Differentiated Thyroid Cancer: United States SEER 18 2000–2016. Thyroid 2020, 30, 1781–1791. [CrossRef] 3. Rahbari, R.; Zhang, L.; Kebebew, E. Thyroid cancer gender disparity. Future Oncol. 2010, 6.[CrossRef][PubMed] 4. Handkiewicz-Junak, D.; Czarniecka, A.; Jarzab, B. Molecular prognostic markers in papillary and follicular thyroid cancer. Current status and future directions. Mol. Cell. Endocrinol. 2010, 322, 8–28. [CrossRef] 5. Kim, S.; Cho, S.W.; Min, H.S.; Kim, K.M.; Yeom, G.Y.; Kim, E.Y.; Lee, K.E.; Yun, Y.G.; Park, D.J.; Park, Y.J. The Expression of Tumor-Associated Macrophages in Papillary Thyroid Carcinoma. Endocrinol. Metab. 2013, 28, 192–198. [CrossRef] 6. Qing, W.; Fang, W.Y.; Ye, L.; Shen, L.Y.; Zhang, X.F.; Fei, X.C.; Chen, X.; Wang, W.Q.; Li, X.Y.; Xiao, J.C.; et al. Density of tumor- associated macrophages correlates with lymph node metastasis in papillary thyroid carcinoma. Thyroid 2012, 9, 905–910. [CrossRef] 7. Jung, K.Y.; Cho, S.W.; Kim, Y.A.; Kim, D.; Oh, B.C.; Park, D.J.; Park, Y.J. Cancers with Higher Density of Tumor-Associated Macrophages Were Associated with Poor Survival Rates. J. Pathol. Transl. Med. 2015, 49, 318–324. [CrossRef] 8. Ryder, M.; Ghossein, R.A.; Ricarte-Filho, J.C.; Knauf, J.A.; Fagin, J.A. Increased density of tumor-associated macrophages is associated with decreased survival in advanced thyroid cancer. Endocr. Relat. Cancer 2008, 15, 1069–1074. [CrossRef] 9. Caillou, B.; Talbot, M.; Weyemi, U.; Pioche-Durieu, C.; Al Ghuzlan, A.; Bidart, J.M.; Chouaib, S.; Schlumberger, M.; Dupuy, C. Tumor-associated macrophages (TAMs) form an interconnected cellular supportive network in anaplastic thyroid carcinoma. PLoS ONE 2011, 6, e22567. [CrossRef][PubMed] 10. Komohara, Y.; Jinushi, M.; Takeya, M. Clinical significance of macrophage heterogeneity in human malignant tumors. Cancer Sci. 2014, 105, 1–8. [CrossRef] 11. Mantovani, A.; Sozzani, S.; Locati, M.; Allavena, P.; Sica, A. Macrophage polarization: Tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends Immunol. 2002, 23, 549–555. [CrossRef] 12. Ryder, M.; Gild, M.; Hohl, T.M.; Pamer, E.; Knauf, J.; Ghossein, R.; Joyce, J.A.; Fagin, J.A. Genetic and pharmacological targeting of CSF-1/CSF-1R inhibits tumor-associated macrophages and impairs BRAF-induced thyroid cancer progression. PLoS ONE 2013, 8, e54302. [CrossRef] 13. Ohno, S.; Suzuki, N.; Ohno, Y.; Inagawa, H.; Soma, G.I.; Inoue, M. Tumor-associated macrophages: Foe or accomplice of tumors? Anticancer Res. 2003, 23, 4395–4409. [PubMed] 14. He, H.; Li, W.; Liyanarachchi, S.; Jendrzejewski, J.; Srinivas, M.; Davuluri, R.V.; Nagy, R.; de la Chapelle, A. Genetic predisposition to papillary thyroid carcinoma: Involvement of FOXE1, TSHR, and a novel lincRNA gene, PTCSC2. J. Clin. Endocrinol. Metab. 2015, 100, E164–E172. [CrossRef][PubMed] 15. Tomaz, R.A.; Sousa, I.; Silva, J.G.; Santos, C.; Teixeira, M.R.; Leite, V.; Cavaco, B.M. FOXE1 polymorphisms are associated with familial and sporadic nonmedullary thyroid cancer susceptibility. Clin. Endocrinol. 2012, 77, 926–933. [CrossRef] 16. Somuncu, E.; Karatas, A.; Ferahman, S.; Saygili, N.; Yilmaz, E.; Ozturk, O.; Kapan, M. The investigation of foxe1 variations in papillary thyroid carcinoma. Int. J. Clin. Exp. Pathol. 2015, 8, 13458–13464. [PubMed] 17. Takahashi, M.; Saenko, V.A.; Rogounovitch, T.I.; Kawaguchi, T.; Drozd, V.M.; Takigawa-Imamura, H.; Akulevich, N.M.; Ratana- jaraya, C.; Mitsutake, N.; Takamura, N.; et al. The FOXE1 locus is a major genetic determinant for radiation-related thyroid carcinoma in Chernobyl. Hum. Mol. Genet. 2010, 19, 2516–2523. [CrossRef] 18. Landa, I.; Ruiz-Llorente, S.; Montero-Conde, C.; Inglada-Perez, L.; Schiavi, F.; Leskela, S.; Pita, G.; Milne, R.; Maravall, J.; Ramos, I.; et al. The variant rs1867277 in FOXE1 gene confers thyroid cancer susceptibility through the recruitment of USF1/USF2 transcription factors. PLoS Genet. 2009, 5, e1000637. [CrossRef] 19. Chakravarty, D.; Santos, E.; Ryder, M.; Knauf, J.A.; Liao, X.H.; West, B.L.; Bollag, G.; Kolesnick, R.; Thin, T.H.; Rosen, N.; et al. Small-molecule MAPK inhibitors restore radioiodine incorporation in mouse thyroid cancers with conditional BRAF activation. J. Clin. Investig. 2011, 121, 4700–4711. [CrossRef] 20. Credendino, S.C.; Moccia, C.; Amendola, E.; D’Avino, G.; Di Guida, L.; Clery, E.; Greco, A.; Bellevicine, C.; Brunetti, A.; De Felice, M.; et al. Foxe1 Gene Dosage Affects thyroid Cancer Histology and Differentiation in Vivo. Int. J. Mol. Sci. 2020, 22, 25. [CrossRef] 21. Ambesi-Impiombato, F.S.; Coon, H.G. Thyroid cells in culture. Int. Rev. Cytol. 1979, 10, 163–172. [CrossRef] 22. De Felice, M.; Ovitt, C.; Biffali, E.; Rodriguez-Mallon, A.; Arra, C.; Anastassiadis, K.; Macchia, P.E.; Mattei, M.G.; Mariano, A.; Scholer, H.; et al. A mouse model for hereditary thyroid dysgenesis and cleft palate. Nat. Genet. 1998, 19, 395–398. [CrossRef] [PubMed] 23. Morillo-Bernal, J.; Fernández, L.P.; Santisteban, P. FOXE1 regulates migration and invasion in thyroid cancer cells and targets ZEB1. Endocr. Relat. Cancer 2020, 27, 137–151. [CrossRef] 24. Dobranowski, P.; Sly, L.M. SHIP negatively regulates type II immune responses in mast cells and macrophages. J. Leukoc. Biol. 2018, 103, 1053–1064. [CrossRef] 25. Loimaranta, V.; Hepojoki, J.; Laaksoaho, O.; Pulliainen, A.T. Galectin-3-binding protein: A multitask glycoprotein with innate immunity functions in viral and bacterial infections. J. Leukoc. Biol. 2018, 104, 777–786. [CrossRef][PubMed] 26. Pauls, S.D.; Marshall, A.J. Regulation of immune cell signaling by SHIP1: A phosphatase, scaffold protein, and potential therapeutic target. Eur. J. Immunol. 2017, 47, 932–945. [CrossRef] 27. MacKinnon, A.C.; Farnworth, S.L.; Hodkinson, P.S.; Henderson, N.C.; Atkinson, K.M.; Leffler, H.; Nilsson, U.J.; Haslett, C.; Forbes, S.J.; Sethi, T. Regulation of alternative macrophage activation by galectin-3. J. Immunol. 2008, 180, 2650–2658. [CrossRef] Int. J. Mol. Sci. 2021, 22, 7666 13 of 13

28. Ohsawa, K.; Imai, Y.; Kanazawa, H.; Sasaki, Y.; Kohsaka, S. Involvement of Iba1 in membrane ruffling and phagocytosis of macrophages/microglia. J. Cell Sci. 2000, 113 Pt 17, 3073–3084. [CrossRef] 29. Sano, H.; Hsu, D.K.; Apgar, J.R.; Yu, L.; Sharma, B.B.; Kuwabara, I.; Izui, S.; Liu, F.T. Critical role of galectin-3 in phagocytosis by macrophages. J. Clin. Investig. 2003, 112, 389–397. [CrossRef] 30. Chung, H.S.; Lee, B.S.; Ma, J.Y. Ethanol Extract of Mylabris phalerata Inhibits M2 Polarization Induced by Recombinant IL-4 and IL-13 in Murine Macrophages. Evid. Based Complementary Altern. Med. Ecam 2017, 2017, 4218468. [CrossRef][PubMed] 31. Zhang, Y.; Choksi, S.; Chen, K.; Pobezinskaya, Y.; Linnoila, I.; Liu, Z.G. ROS play a critical role in the differentiation of alternatively activated macrophages and the occurrence of tumor-associated macrophages. Cell Res. 2013, 23, 898–914. [CrossRef] 32. Fernandes, S.; Iyer, S.; Kerr, W.G. Role of SHIP1 in cancer and mucosal inflammation. Ann. N. Y. Acad. Sci. 2013, 1280, 6–10. [CrossRef][PubMed] 33. Woodman, N.; Pinder, S.E.; Tajadura, V.; Le Bourhis, X.; Gillett, C.; Delannoy, P.; Burchell, J.M.; Julien, S. Two E-selectin ligands, BST-2 and LGALS3BP, predict metastasis and poor survival of ER-negative breast cancer. Int. J. Oncol. 2016, 49, 265–275. [CrossRef] [PubMed] 34. Zhang, X.; Ding, H.; Lu, Z.; Ding, L.; Song, Y.; Jing, Y.; Hu, Q.; Dong, Y.; Ni, Y. Increased LGALS3BP promotes proliferation and migration of oral squamous cell carcinoma via PI3K/AKT pathway. Cell. Signal. 2019, 63, 109359. [CrossRef][PubMed] 35. Chen, C.; He, W.; Huang, J.; Wang, B.; Li, H.; Cai, Q.; Su, F.; Bi, J.; Liu, H.; Zhang, B.; et al. LNMAT1 promotes lymphatic metastasis of bladder cancer via CCL2 dependent macrophage recruitment. Nat. Commun. 2018, 9, 3826. [CrossRef][PubMed] 36. Richardsen, E.; Uglehus, R.D.; Johnsen, S.H.; Busund, L.T. Macrophage-colony stimulating factor (CSF1) predicts breast cancer progression and mortality. Anticancer Res. 2015, 35, 865–874. 37. Evrard, D.; Szturz, P.; Tijeras-Raballand, A.; Astorgues-Xerri, L.; Abitbol, C.; Paradis, V.; Raymond, E.; Albert, S.; Barry, B.; Faivre, S. Macrophages in the microenvironment of head and neck cancer: Potential targets for cancer therapy. Oral Oncol. 2019, 88, 29–38. [CrossRef] 38. Li, X.; Yao, W.; Yuan, Y.; Chen, P.; Li, B.; Li, J.; Chu, R.; Song, H.; Xie, D.; Jiang, X.; et al. Targeting of tumour-infiltrating macrophages via CCL2/CCR2 signalling as a therapeutic strategy against hepatocellular carcinoma. Gut 2017, 66, 157–167. [CrossRef] 39. Pyonteck, S.M.; Akkari, L.; Schuhmacher, A.J.; Bowman, R.L.; Sevenich, L.; Quail, D.F.; Olson, O.C.; Quick, M.L.; Huse, J.T.; Teijeiro, V.; et al. CSF-1R inhibition alters macrophage polarization and blocks glioma progression. Nat. Med. 2013, 19, 1264–1272. [CrossRef] 40. Varricchi, G.; Loffredo, S.; Marone, G.; Modestino, L.; Fallahi, P.; Ferrari, S.M.; de Paulis, A.; Antonelli, A.; Galdiero, M.R. The Immune Landscape of Thyroid Cancer in the Context of Immune Checkpoint Inhibitin. Int. J. Mol. Sci. 2019, 20, 3934. [CrossRef] 41. Gascard, P.; Tlsty, T.D. Carcinoma-associated fibroblasts: Orchestrating the composition of malignancy. Genes Dev. 2016, 30, 1002–1019. [CrossRef] 42. Shiga, K.; Hara, M.; Nagasaki, T.; Sato, T.; Takahashi, H.; Takeyama, H. Cancer-Associated Fibroblasts: Their Characteristics and Their Roles in Tumor Growth. Cancers 2015, 7, 2443–2458. [CrossRef] 43. Comito, G.; Giannoni, E.; Segura, C.P.; Barcellos-de-Souza, P.; Raspollini, M.R.; Baroni, G.; Lanciotti, M.; Serni, S.; Chiarugi, P. Cancer-associated fibroblasts and M2-polarized macrophages synergize during prostate carcinoma progression. Oncogene 2014, 33, 2423–2431. [CrossRef][PubMed] 44. Perrone, L.; Pasca di Magliano, M.; Zannini, M.; Di Lauro, R. The thyroid transcription factor 2 (TTF-2) is a promoter-specific DNA-binding independent transcriptional repressor. Biochem. Biophys. Res. Commun. 2000, 275, 203–208. [CrossRef][PubMed] 45. Trapnell, C.; Roberts, A.; Goff, L.; Pertea, G.; Kim, D.; Kelley, D.R.; Pimentel, H.; Salzberg, S.L.; Rinn, J.L.; Pachter, L. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 2012, 7, 562–578. [CrossRef] [PubMed] 46. Anders, S.; Pyl, P.T.; Huber, W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinformatics 2015, 31, 166–169. [CrossRef] 47. Anders, S.; Huber, W. Differential expression analysis for sequence count data. Genome Biol. 2010, 11, R106. [CrossRef]