Next Article in Journal
The Relationship between Cancer and Dementia: An Updated Review
Next Article in Special Issue
Outcomes of the Tall-Cell Variant of Papillary Thyroid Carcinoma in Patients with Different Ages: A 17-Year Mono-Institutional Experience
Previous Article in Journal
Mixed Hepatocellular Cholangiocarcinoma: A Comparison of Survival between Mixed Tumors, Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma from a Single Center
Previous Article in Special Issue
TROP-2, Nectin-4, GPNMB, and B7-H3 Are Potentially Therapeutic Targets for Anaplastic Thyroid Carcinoma
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma—A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study

by
Martyna Borowczyk
1,2,*,
Paula Dobosz
3,
Ewelina Szczepanek-Parulska
1,
Bartłomiej Budny
1,
Szymon Dębicki
1,
Dorota Filipowicz
1,
Elżbieta Wrotkowska
1,
Michalina Oszywa
1,
Frederik A. Verburg
4,
Małgorzata Janicka-Jedyńska
5,
Katarzyna Ziemnicka
1 and
Marek Ruchała
1
1
Department of Endocrinology, Metabolism and Internal Medicine, Poznan University of Medical Sciences, 60-355 Poznan, Poland
2
Department of Medical Simulation, Poznan University of Medical Sciences, 60-806 Poznan, Poland
3
Department of Genetics and Genomics, Central Clinical Hospital of the Ministry of Interior Affairs and Administration, 02-507 Warsaw, Poland
4
Department of Radiology and Nuclear Medicine, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands
5
Department of Clinical Pathology, Poznan University of Medical Sciences, 60-355 Poznan, Poland
*
Author to whom correspondence should be addressed.
Cancers 2023, 15(3), 638; https://doi.org/10.3390/cancers15030638
Submission received: 4 December 2022 / Revised: 16 January 2023 / Accepted: 18 January 2023 / Published: 19 January 2023

Abstract

:

Simple Summary

Approximately 50% of 60-year-old persons have thyroid nodules that in 7–15% may be thyroid cancer. Diagnosis of follicular thyroid adenoma (FTA) and follicular thyroid cancer (FTC) is particularly challenging. Furthermore, it is not clear whether they share a common or distinct background. The study aimed to compare FTA and FTC using the comprehensive microarray for the first time and to identify recurrent regions of loss of heterozygosity. We found that FTA and FTC may share a common genetic background—including the same LOH in 16p12.1, which encompasses many cancer-related genes. However, differentiating rearrangements may also be detected, such as LOH in 11p11.2-p11.12 only in FTA patients (56% vs. 0%) and LOH in 12q24.11-q24.13 detected more often in FTC (37.5% vs. 6.3% in FTA). Genomic screening may show the complexity of genetic background in follicular thyroid lesions and enable the identification of new genetic rearrangements participating in FTC pathogenesis.

Abstract

Pre- and postsurgical differentiation between follicular thyroid adenoma (FTA) and follicular thyroid cancer (FTC) represents a significant diagnostic challenge. Furthermore, it remains unclear whether they share a common or distinct background and what the mechanisms underlying follicular thyroid lesions malignancy are. The study aimed to compare FTA and FTC by the comprehensive microarray and to identify recurrent regions of loss of heterozygosity (LOH). We analyzed formalin-fixed paraffin-embedded (FFPE) samples acquired from 32 Caucasian patients diagnosed with FTA (16) and FTC (16). We used the OncoScan™ microarray assay (Affymetrix, USA), using highly multiplexed molecular inversion probes for single nucleotide polymorphism (SNP). The total number of LOH was higher in FTC compared with FTA (18 vs. 15). The most common LOH present in 21 cases, in both FTA (10 cases) and FTC (11 cases), was 16p12.1, which encompasses many cancer-related genes, such as TP53, and was followed by 3p21.31. The only LOH present exclusively in FTA patients (56% vs. 0%) was 11p11.2-p11.12. The alteration which tended to be detected more often in FTC (6 vs. 1 in FTA) was 12q24.11-q24.13 overlapping FOXN4, MYL2, PTPN11 genes. FTA and FTC may share a common genetic background, even though differentiating rearrangements may also be detected.

1. Introduction

Approximately 50 percent of 60-year-old persons have thyroid nodules [1]. Their clinical importance relates to the need to exclude thyroid cancer [2], which occurs in 7%–15% of cases [3]. The differentiation between benign and malignant thyroid lesions is usually based on ultrasound and thyroid fine-needle aspiration biopsy [4]. One particular type of thyroid nodule—follicular thyroid lesion including follicular thyroid adenoma (FTA) and follicular thyroid cancer (FTC)—remains a diagnostic challenge [5,6]. Their presurgical differentiation is not reliable when based on imaging or cytology [7]. Furthermore, their natural history is not clear—do they share a common or distinct background? Is FTC an extension of FTA? What is the phenomenon underlying malignancy and invasion of FTC?
In recent years, many studies have endeavored to identify additional factors to discriminate between those two related pathological entities [8] and to further clarify the relationship’s extent in their pathogenesis [9].
Typical markers of malignancy may appear as specific genetic alterations that may be present in FTC but not in FTA, especially since molecular markers are increasingly used as presurgical diagnostic tools in the management of indeterminate thyroid nodules [10]. However, the results of molecular testing performance of cytology specimens from thyroid nodules are still not fully satisfactory [11].
Although next-generation sequencing (NGS) has generated promising results in papillary thyroid cancer (PTC) [12], this technique has rarely been used in FTC [13] thus far. Moreover, although the genomic landscape of PTC is nearly complete, the molecular characterization of FTC and its progression from minimally invasive FTC to widely invasive FTC are still not totally clear [14]. Recently, our study group has proposed a few genetic markers of thyroid follicular lesions’ malignancy based on our NGS studies [15,16,17]. However, NGS is not exhaustive, as it only yields information about single point mutations.
To have a comprehensive insight into follicular thyroid lesions’ genetic landscape, analysis of larger rearrangements is needed. Recent array technology allows whole-genome screening, including copy number variants (CNVs) analysis at a high resolution. The microarray can determine chromosomal abnormalities and genomic instability; i.e., highly accurate pathogenic copy number variants and allelic imbalances in solid tumors from limited amounts of DNA [18]. Thus far, many studies have included only a targeted analysis of CNVs and loss of heterozygosity (LOH) of FTA or FTC [19,20,21]. The latter has been regarded as a characteristic feature of the follicular phenotype [19].
The OncoScan™ microarray assay (Affymetrix/Thermo Fisher Scientific, Waltham, MA, USA), which uses highly multiplexed molecular inversion probes for single nucleotide polymorphism (SNP) loci, has been developed and validated for genomic profiling of somatic copy number aberrations of various tumors [22,23]. To the best of our knowledge, researchers have not yet used this technique to simultaneously detect many genetic changes and analyze the complex interplay of distinct genetic alterations.
The aim of the study was to compare FTA and FTC using the high-resolution SNP array for the first time and to identify recurrent regions of LOH, which may support preoperative differentiation and a better understanding of those entities.

2. Materials and Methods

We analyzed 32 randomly selected patients at the Department of Endocrinology of our university hospital, who were diagnosed with follicular lesions (16 with FTA and 16 with FTC). The diagnosis was made according to the World Health Organization criteria [24]. We adjusted both groups for age and gender. The Bioethical Committee of Poznan University of Medical Sciences approved the study (approval no. 1061/15, January 2015), and it was conducted in accordance with the Declaration of Helsinki [25]. Due to the retrospective nature of the analysis and the use of stored materials, additional informed consent was not required.
We subjected formalin-fixed paraffin-embedded (FFPE) samples obtained from total or subtotal thyroidectomy, and we gained the detailed clinical annotates. The study group included 28 women and 4 men with a median age of diagnosis of 55 years (range: 29 to 82). All patients were Caucasian and did not suffer from any other endocrine disorders or cancers. They were not receiving any treatment at the time of diagnosis. The analysis covered data collected between 2008 and 2020. Patient characteristics are presented in Table 1.
The specimens were acquired by thyroidectomy and re-examined by a qualified pathologist, who confirmed the diagnosis of FTA and FTC. Patient and sample data included: the age at diagnosis, gender, tumor size, multifocality (when two or more foci were found), extra-thyroidal extension, the presence of histopathological signs of chronic lymphocytic thyroiditis, histopathological staging (pTNM) according to the 8th tumor-node-metastasis (TNM) classification [24], and radioiodine refractoriness (if a cumulative activity of 22.2 GBq/600 mCi of RAI did not result in achieving complete remission). All samples were anonymized.
A qualified pathologist indicated areas of interest from FFPE specimens, and slides were manually microdissected. Genomic DNA was extracted using a QIAamp DNA FFPE Tissue Kit (Qiagen, Valencia, CA, USA), following the manufacturer’s instructions. Genomic DNA was quantified using a fluorometer Qubit platform (Invitrogen, Carlsbad, CA, USA), and the DNA quality and integrity were tested.
Further studies included whole-genome microarrays based on molecular inversion probes performed with the use of OncoScan™ arrays (Affymetrix, Thermo Fisher Scientific, Waltham, MA, USA). All procedures related to genomic screening were conducted according to the array provider’s instructions to ensure proper efficiency and reliability of results. This method enabled analysis of copy number changes and allelic imbalances across the entire genome.
To minimize the number of false-positive findings, the following criteria for significant results were followed: genomic deletions of a minimum region of 150 kb and genomic amplifications of a minimum region of 200 kb.
To calculate the copy number of altered regions, the data were normalized to baseline reference intensities using NA 32.3v.2 reference model (provided by Affymetrix/Thermo Fisher Scientific, Waltham, MA, USA). The Hidden Markov Model (HMM) available within the software package was used to determine the copy number states and their breakpoints. Thresholds of log2ratio ≥ 0.58 and ≤1 allowed to categorize altered regions as CNV gains (amplifications) and copy number losses (deletions), respectively. To prevent the detection of false positive CNVs, at least 50 consecutive, adjacent probes were considered in the recognition of gains or losses in our study. Gains or losses were analyzed separately. To exclude aberrations representing common normal CNVs, all the identified CNVs were compared with those reported in the Database of Genomic Variants (DGV, http://projects.tcag.ca/variation/, accessed on 30 April 2022). To identify the genes within the CNVs, we used the UCSC database (http://genome.ucsc.edu, accessed on 30 April 2022) and Ensemble (http://www.ensembl.org, accessed on 30 April 2022). Gene annotation and gene overlap were assigned using the human genome build 19 (hg19) and NetAffx (http://www.affymetrix.com, accessed on 30 April 2022). In addition, the identified alterations were confronted with data deposited in COSMIC database (www.http://cancer.sanger.ac.uk, accessed on 30 April 2022) to look for overlap with up-to-date known genomic cancer regions and genes.
The algorithm for detection of copy number aberrations in tumor cell mixture (mosaicism and clonality) considered comprehensive analysis of adjacent single copy deletions and gains segments. The algorithm was designed to be most accurate when the normal/expected copy number state (CN) is diploid and targets detection of changes in regions of approximately 5Mb or more in size and variation within min. 500 markers (being typical for segments of 5000 markers or larger in size). This approach considers only a discrete number of mosaicism levels, which are set at 30%, 50%, and 70%. The range of log ratios is broken into a series of bands according to the detection level (30% or greater, 50% or greater, and 70–100% bands). This tool was most efficient in detecting mosaicism between approximately 30–70% of cells and for copy numbers between 1 and 3. The LOH were used for the final analysis.
The data obtained from genomic experiments were analyzed using a dedicated OncoScan™ Console 1.3 and ChAS v4 software and were compared with clinical data.
In order to fully explore identified alterations and contributing genes, we used a bioinformatics approach and tools such as DVID (The Database for Annotation, Visualization and Integrated Discovery) and Ingenuity® Pathway Analysis (IPA®, Qiagen Sciences, Germantown, MD, USA).
Parameters were recorded and entered into a dedicated database. Descriptive analysis was used to summarize the collected data. To determine the normality of continuous variables, data were tested by the D’Agostino and Pearson omnibus normality test. Variables that were found to be normally distributed were expressed as mean values. Data that were found to be distributed differently were expressed as median and minimum–maximum values.
To compare differences between the groups for categorical variables, the chi-square test was used if the Cochrane assumptions were met; otherwise, Fisher’s exact test was used. Interval data were compared using the Mann–Whitney U test as the data did not follow a normal distribution.
A p-value of less than 0.05 was regarded as significant. Statistical analyses were performed with StatSoft Statistica v13.0 and PQStat v1.6.8 software.

3. Results

The total number of LOH was higher in FTC compared with FTA (18 vs. 15). The most common LOH present in 21 cases, including both follicular thyroid adenoma (10 cases) and follicular thyroid carcinoma (11 cases), was 16p12.1 comprising over 7.5 Mbp in size, encompassing 149 known genes, including many important cancer-related genes such as TP53 and its variants, UBE2MP1, ATP2A1, IL27, TGFB, MAPK3, BCL7C, and many transcription factor subunit genes. Another LOH present in both types of thyroid cancer was 3p21.31, about 6.4 Mbp in size, comprising 172 genes, including KIF9, SLC26A6, UBA7, CACNA2D2, TLR9, and BAP1. This region was affected in nine cases of FTC and seven cases of FTA. Moreover, LOH 15q15.1 was frequently found in both follicular lesions; it comprises over 3.6 Mbp and includes genes such as TYRO3, CAPN3, TP53BP1, and EIF3J.
The only LOH present exclusively in FTA patients (56% vs. 0%) was 11p11.2-p11.12 (5.4 Mb in size), including KAI1, a metastasis suppressor gene, OR4 subfamily genes and CREB family transcription factor members. Another LOH on chromosome 20 (q11.21-q11.23, 6.89 Mb) also predominated in FTA and consisted of genes such as SRC, BCL2L, DNMT3B, and MMP24, among others. Only one patient with thyroid cancer different to FTA presented this LOH region.
The alteration which tended to be detected more often in FTC was 12q24.11-q24.13 (region size: 3.99 Mb) overlapping FOXN4, MYL2, PTPN11, UBE3B, RAD9B, and RASAL1 genes, as well as OAS gene family. This region was affected in six cases of FTC, but only once among the FTA cohort.
Table 2 presents all LOHs present in both types of lesions, and predominantly in one type of thyroid cancer, including genes detected in the LOH region, together with non-coding RNA genes.
Other significant LOHs detected only in FTC patients, albeit less frequently, included the following regions: 1q21.1 (about 3.03 Mbp, most important genes: PDE4DIP, BCL9), 2q11.2 (over 4.2 Mbp, including ARID5A and COX5B genes), 3p12.2 (about 3.7 Mbp, including GBE1 gene), 8q11.1 (over 2.8 Mbp in size, including MCM4 and UBE2 genes), 14q23.3 (3.5 Mbp, including MAX, ATP6, EIF2, ARG2, RAD51B, and GPHN genes), 14q32.31 (over 2.8 Mbp, including HSP90, TRAF3, TNFA, APOPT1, and KIF26A), and 22q11.23 (0.82 Mbp, including GSTT1, GSTT2, and CABIN1 genes). Even though most of the changes mentioned above have been of “loss” type, several “gain” changes have been also discovered, especially in the following regions: 19q13.41 (nearly 2 Mbp in size, including ZNF331, PPP2R1A, HAS1, and BIRC8), 1p13.3 (44,148 in size, including GSTM gene family members), 3p14.1 (0.43 Mbp, including SUCLG2 and FAM19A1 genes), and 13q12.3 (about 2.7 Mbp in size, including BRCA2 gene).
Regarding the differences in a group of FTC patients, we found an increased frequency of LOH in the 3p21.31 for the T2–T3 group (p = 0.001). Nodal involvement has been accompanied by 14q32.31 LOH. In a case of capsular invasion, the most common were LOHs in the 12q24.11 and 16p12.1. Multifocality was linked to 2q11.2 and 8q11.1.
Among FTA patients, other detected LOHs included: 1q21.1 (over 2.5 Mbp, including PDE4DIP and CD160 genes), 3p12.2 (over 3.7 Mbp, including GBE1 gene), 3q28 (nearly 6.7 Mbp, including TFRC, IL1RAP, and FGF12 genes), 7q11.21 (nearly 3.8 Mbp, including SBDS and VKORC1 genes), 8q11.1 (2.8 Mbp, including PRKDC gene), 9q34.3 (1.8 Mbp, including NOTCH1 gene), 10q11.21 (3.1 Mbp, including NPY4R and AGAP9), 17q21.31 (nearly 3kbp, including MAP3K, MAPT, NSF, and WNT3), 20q13.33 (0.15 Mbp, including HRH3 and SS18L1), and 14q32.31 (4.2 Mbp in size, including AKT1 and JAG2). Even though most of the changes mentioned above have been of “loss” type, several “gain” changes have been also discovered, especially in the regions 1p13.3 and 3p14.4, although no significant genes related to the cancer process have been reported in those areas. Figure 1 shows the results of the comparison analysis. We identified which markers are significantly different between FTA and FTC and which are similar, and we compared them with known ones from the previous research.

4. Discussion

The results indicate that FTA and FTC may share a common genetic background, even though differentiating rearrangements may also be detected. The most common LOH region, 16p12.1, is present in both FTA and FTC, with similar numbers of cases. Also, 3p21.31, as well as 15q15.1 deletion. These big regions contain several pseudogenes and genes with non-coding RNA products, but also many important genes, including those with known involvement in cancer pathogenesis, as indicated in Table S1. The same LOH present in both FTA and FTC localized on 3p has been described already in 2008. In the study of Hu et al., LOHs on chromosome 3p, including 3p21, were detected in 71% of follicular thyroid carcinoma (17/24), 30% of papillary thyroid carcinoma (9/30), and 10% of follicular adenoma (2/20) cases [32]. The concept of FTA and FTC similarities is not new as RAS somatic mutations and PAX8/PPARγ rearrangements, the key FTC alterations, were detected in both FTCs and FTAs [33].
LOH 12q24.11, present primarily in follicular thyroid carcinoma, may constitute a possible marker of follicular thyroid lesions’ malignancy as it seems to include genes strictly associated with thyroid cancer pathogenesis, as shown in Table S2. LOH in 12q24 has been regarded as potentially pathogenic for gastric cancer [34] and for neuroblastoma progression [35]. Locus 12q24.11 encompasses the human glycolipid transfer protein (GLTP) gene responsible for glycosphingolipid metabolism, including lipid binding and glycolipid transfer activity [36]. Another LOH present only in FTC was allelic deletions in 22q, previously described in highly invasive FTCs with poor prognosis [37].
On the other hand, follicular thyroid adenoma’s most specific regions, 11p11.2 and 20q11.21 LOH, comprises several gene encoding transcription factors and many miRNA genes, which are also known for their impact on carcinogenesis, as well as direct and indirect regulation of the transcription factor function. Further, LOH within the short arm of chromosome 11 (11 p) in the development of FTA has been previously described [38]. Selected genes have been depicted in Table S3.
Overall frequency of allelic loss (OFAL), including LOH, has been regarded as a characteristic feature of the follicular phenotype [19,39]. It is why we decided to precisely analyze LOH in FTA and FTC in our study. They represent molecular disorders acquired by the cell during neoplasm transformation [20]. In this disorder, one of the gene alleles is lost in a neoplastic cell [40]. The mechanism of LOH is chromosome-specific. Knudson et al. [41] postulated that loss of function of both tumor suppressor gene (TSG) copies is required for an uncontrolled proliferation of modified cells and, eventually, for neoplastic transformation [20]. One allele may be inactivated by promoter hypermethylation or point mutation (e.g., substitution) or intragenic microdeletion, while the second allele may be lost via LOH [41]. It was confirmed by a finding of LOH high percentage in anaplastic thyroid carcinoma, suggesting that LOH may be regarded as a late event in thyroid tumorigenesis associated with the loss of tumor differentiation and increased degree of aggressiveness [20].
The similarities between the FTA and FTC genetic backgrounds found in our study supports the hypothesis that they may constitute a partial continuum in their natural history. This was also previously suggested by Nikitski et al. [42] and many others, who analyzed TP53-mutant FTA as a precursor not only to FTC, but also to anaplastic thyroid carcinoma. In our study, deletion of a region including TP53BP1 gene was present in both FTA and FTC.
The new LOHs may occur not only as a sign of transformation from FTA and FTC, but also of its growth. In their study, Migdalska-Sęk et al. [19] found regions with significantly increased frequency of LOH/MSI for specific histotypes: the 3p24.2 region for FA and 1p31.2 for FTC. LOH/MSI in 3p21.3 was significantly elevated in PTC and FTC. LOH/MSI in 3p21.3 was increased for small-size tumors (T1a + T1b), tumors with no regional lymph node involvement (N0 + Nx), American Joint Committee on Cancer (AJCC) stage I tumors, and tumor diameter (Td) < 10 mm. We confirmed the occurrence of LOH3p21.31 in both FTA and FTC, indicating early-stage tumorigenesis.
Similarly to the results of our study, the number of allelic losses (LOH) calculated in different studies increases from the lowest in FTA to higher numbers in FTC, with the highest number for anaplastic thyroid cancer [27,38,43]. It was also higher for atypical FTA than for typical FTA [44]. This increased number of LOH events may contribute to the clinical aggressiveness of cancer [45]. The follicular adenoma–carcinoma sequence in thyroid carcinogenesis may include atypical follicular thyroid adenoma as an important intermediate in this pathway [46]. The results of our study also prove that the incidence of LOH may overtly increase with tumor progression. The incidence of LOH and the numbers of loci, in which the loss of heterozygosity increases with the degree of neoplastic progression, indicates a successive accumulation of molecular disorders in cells and a coincidence of LOH and mutations in thyroid tumorigenesis.
Our study demonstrates that the role of LOH in the process of thyroid neoplastic transformation lays in an inactivation of various genes by deletions in their loci, which is already present in preneoplastic lesions. It may prove the role of LOH in the process of carcinogenesis initiation and neoplastic transformation of the thyroid gland. It is compatible with the classical multistep carcinogenesis model applied to FTC, which is based on a theory of cancer clonal origin. Genome instability within somatic cells is the first step. Then, more aggressive clones appear, and they survive the selection pressure of the microenvironment. The appearance of a functionally significant mutation leads to divergence of a new subclone, which can dominate and outcompete other cells to result in a homogenous tumor until a new, significant, and more versatile mutation appears [47]. According to this theory, FTC is considered to be derived from FTA [48].
One of the hot LOH sites included in the first step may be 15q region, while in our study its LOH were present both in FTA and FTC. It may lead to a neoplastic transformation of normal thyroid cells towards adenoma. In turn, the imprinted genes take part in differentiation of typical adenomas into an atypical form, thus confirming their role in an early stage of neoplastic transformation towards malignant lesion (FTC) [49,50].
Loss of heterozygosity in the 3p21.31, 15q15.1, or 16p12.1, present in both FTA and FTC, may be regarded as an early and probably initiating event in the development of follicular adenoma. The progressive character of the process is particularly evident for LOH in the 12q24.11 locus, which may have a role in FTA transformation towards FTC. The high incidence of the loss of heterozygosity in FTC (37.5%) and lower incidence in FTA (6.25%) suggest that the 12q24.11 locus could be the minimally deleted regions (MDR), specifically for FTC.
Moreover, the higher percentage of malignant tumors with LOH observed in those loci vs. benign lesions may confirm the hypothesis that the development of FTA and FTC is associated with a clonal event, occurring in a single precursor cell.
We hypothesize that the 16p12.1, 3p21.31, or 15q15.1 deletion sensitizes the genome for disease, while “second-hits” in the genetic background, such as 12q24.11 deletion, modulate the phenotypic trajectory and cause tumorigenesis. The same role of 16p12.1 deletion as “the first hit” was suggested for maldevelopment of nervous system.
The results of our study are passed on molecular inversion probe (MIP) technology. The analysis of LOH is comprehensive as MIP is a proven technology for identifying rearrangements and simultaneous detection of selected somatic mutations (so-called “driving mutations”). This assay has been shown to perform well with low inputs of DNA starting material, making the assay a natural choice in cancer clinical research. It enabled having FFPE as a source of DNA, despite a DNA degradation and getting rid of method bias, as the OncoScanTM algorithms have been especially developed to address two major challenges associated with solid tumor copy number analysis: first, establishing the expected normal copy number state for a given locus, and second, accounting for “normal cell contamination” present in most samples, which affects copy number estimates.
The study has two main limitations. The first limitation is the small number of participants. However, to the best of our knowledge, the method used in our study (highly multiplexed molecular inversion probes for SNP loci) has been used for the first time in FTA and FTC analysis. Contrary to previous research (also including a small number of patients), we were able to simultaneously detect many genetic changes. The second one is a lack of any experiments about the expression of mapping genes to understand if the allelic copy still present in FTC samples is inactivated or functional. It requires a further analysis by in situ hybridization or immunohistochemistry on the same FFPE specimens to understand if the LOH is simply an FTC marker or if they represent potential tumor suppressors in FTC. We consider our study as a starting point for future research increasing the number of FFPE specimens from additional patients and including functional analysis.
Genomic screening may show the complexity of follicular thyroid lesions’ genetic background and enable the identification of new genetic rearrangements participating in FTC pathogenesis. Given the general similarities of FTA and FTC and the same tissue origin, some LOH differences may reflect malignant progression potential, including useful candidate biomarkers for FTC and identifying factors important for FTC pathogenesis.

5. Conclusions

The results indicate that FTA and FTC may share a common genetic background, even though differentiating rearrangements might also be detected. 12q24.11 LOH may constitute a possible marker of malignancy as it includes genes strictly associated with thyroid cancer pathogenesis. Genomic screening may show the complexity of follicular thyroid lesions’ genetic background and enable the identification of new genetic rearrangements participating in FTC pathogenesis.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cancers15030638/s1, Table S1: Significant genes located in the LOHs typical for both follicular thyroid carcinoma and follicular thyroid adenoma; Table S2: Significant genes located in the LOHs discovered more frequently among follicular thyroid carcinoma patients. Table S3: Significant genes located in the LOHs discovered more frequently among follicular thyroid adenoma compared to follicular thyroid cancers patients. [51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154].

Author Contributions

Conceptualization, M.B., P.D. and E.S.-P..; methodology, M.B., B.B., P.D., S.D., E.W. and M.J.-J.; software, M.B., P.D., B.B. and S.D.; validation, F.A.V.; formal analysis, M.R.; investigation, M.B., P.D., B.B. and S.D; resources, M.B. and P.D.; data curation, D.F. and M.O.; writing—original draft preparation, M.B. and P.D.; writing—review and editing, E.S.-P., F.A.V., D.F., B.B., M.O., M.J.-J. and K.Z.; visualization, M.B.; supervision, E.S.-P.; F.A.V., K.Z. and M.R.; project administration, M.B.; funding acquisition, M.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by a PRELUDIUM Grant of the Polish National Center for Science number 2015/19/N/NZ5/02257.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethical Committee of Poznan University of Medical Sciences approved the study (an approval no. 1061/15 from January 2015).

Informed Consent Statement

Patient consent was waived due to use of archived material.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy and ethical restrictions.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Hegedüs, L.; Bonnema, S.J.; Bennedbaek, F.N. Management of Simple Nodular Goiter: Current Status and Future Perspectives. Endocr. Rev. 2003, 24, 102–132. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Haugen, B.R.; Alexander, E.K.; Bible, K.C.; Doherty, G.M.; Mandel, S.J.; Nikiforov, Y.E.; Pacini, F.; Randolph, G.W.; Sawka, A.M.; Schlumberger, M.; et al. 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer. Thyroid 2016, 26, 1–133. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Hegedüs, L. Clinical Practice. The Thyroid Nodule. N. Engl. J. Med. 2004, 351, 1764–1771. [Google Scholar] [CrossRef] [PubMed]
  4. Holt, E.H. Current Evaluation of Thyroid Nodules. Med. Clin. N. Am. 2021, 105, 1017–1031. [Google Scholar] [CrossRef]
  5. Ohori, N.P.; Nishino, M. Follicular Neoplasm of Thyroid Revisited: Current Differential Diagnosis and the Impact of Molecular Testing. Adv. Anat. Pathol. 2022, 30, 11–23. [Google Scholar] [CrossRef]
  6. Borowczyk, M.; Woliński, K.; Więckowska, B.; Jodłowska-Siewert, E.; Szczepanek-Parulska, E.; Verburg, F.A.; Ruchała, M. Sonographic Features Differentiating Follicular Thyroid Cancer from Follicular Adenoma-A Meta-Analysis. Cancers 2021, 13, 938. [Google Scholar] [CrossRef]
  7. Filetti, S.; Durante, C.; Hartl, D.; Leboulleux, S.; Locati, L.D.; Newbold, K.; Papotti, M.G.; Berruti, A.; ESMO Guidelines Committee. Thyroid Cancer: ESMO Clinical Practice Guidelines for Diagnosis, Treatment and Follow-Up. Ann. Oncol. 2019, 30, 1856–1883. [Google Scholar] [CrossRef] [Green Version]
  8. McHenry, C.R.; Phitayakorn, R. Follicular Adenoma and Carcinoma of the Thyroid Gland. Oncologist 2011, 16, 585–593. [Google Scholar] [CrossRef] [Green Version]
  9. Jung, S.-H.; Kim, M.S.; Jung, C.K.; Park, H.-C.; Kim, S.Y.; Liu, J.; Bae, J.-S.; Lee, S.H.; Kim, T.-M.; Lee, S.H.; et al. Mutational Burdens and Evolutionary Ages of Thyroid Follicular Adenoma Are Comparable to Those of Follicular Carcinoma. Oncotarget 2016, 7, 69638–69648. [Google Scholar] [CrossRef] [Green Version]
  10. Nikiforov, Y.E.; Nikiforova, M.N. Molecular Genetics and Diagnosis of Thyroid Cancer. Nat. Rev. Endocrinol. 2011, 7, 569–580. [Google Scholar] [CrossRef]
  11. Borowczyk, M.; Szczepanek-Parulska, E.; Olejarz, M.; Więckowska, B.; Verburg, F.A.; Dębicki, S.; Budny, B.; Janicka-Jedyńska, M.; Ziemnicka, K.; Ruchała, M. Evaluation of 167 Gene Expression Classifier (GEC) and ThyroSeq v2 Diagnostic Accuracy in the Preoperative Assessment of Indeterminate Thyroid Nodules: Bivariate/HROC Meta-Analysis. Endocr. Pathol. 2019, 30, 8–15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Agrawal, N.; Akbani, R.; Aksoy, B.A.; Ally, A.; Arachchi, H.; Asa, S.L.; Auman, J.T.; Balasundaram, M.; Balu, S.; Baylin, S.B.; et al. Cancer Genome Atlas Research Network Integrated Genomic Characterization of Papillary Thyroid Carcinoma. Cell 2014, 159, 676–690. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Chen, H.; Luthra, R.; Routbort, M.J.; Patel, K.P.; Cabanillas, M.E.; Broaddus, R.R.; Williams, M.D. Molecular Profile of Advanced Thyroid Carcinomas by Next-Generation Sequencing: Characterizing Tumors Beyond Diagnosis for Targeted Therapy. Mol. Cancer Ther. 2018, 17, 1575–1584. [Google Scholar] [CrossRef] [Green Version]
  14. Prete, A.; Borges de Souza, P.; Censi, S.; Muzza, M.; Nucci, N.; Sponziello, M. Update on Fundamental Mechanisms of Thyroid Cancer. Front. Endocrinol. 2020, 11, 102. [Google Scholar] [CrossRef] [Green Version]
  15. Borowczyk, M.; Szczepanek-Parulska, E.; Dębicki, S.; Budny, B.; Verburg, F.A.; Filipowicz, D.; Więckowska, B.; Janicka-Jedyńska, M.; Gil, L.; Ziemnicka, K.; et al. Differences in Mutational Profile between Follicular Thyroid Carcinoma and Follicular Thyroid Adenoma Identified Using Next Generation Sequencing. Int. J. Mol. Sci. 2019, 20, 3126. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Borowczyk, M.; Szczepanek-Parulska, E.; Dębicki, S.; Budny, B.; Verburg, F.A.; Filipowicz, D.; Wrotkowska, E.; Janicka-Jedyńska, M.; Więckowska, B.; Gil, L.; et al. Genetic Heterogeneity of Indeterminate Thyroid Nodules Assessed Preoperatively with Next-Generation Sequencing Reflects the Diversity of the Final Histopathologic Diagnosis. Pol. Arch. Intern. Med. 2019, 129, 761–769. [Google Scholar] [CrossRef] [Green Version]
  17. Borowczyk, M.; Szczepanek-Parulska, E.; Dębicki, S.; Budny, B.; Janicka-Jedyńska, M.; Gil, L.; Verburg, F.A.; Filipowicz, D.; Wrotkowska, E.; Majchrzycka, B.; et al. High Incidence of FLT3 Mutations in Follicular Thyroid Cancer: Potential Therapeutic Target in Patients with Advanced Disease Stage. Ther. Adv. Med. Oncol. 2020, 12, 1758835920907534. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Hu, J.; Gao, J.-B.; Cao, Y.; Bottinger, E.; Zhang, W. Exploiting Noise in Array CGH Data to Improve Detection of DNA Copy Number Change. Nucleic. Acids. Res. 2007, 35, e35. [Google Scholar] [CrossRef] [Green Version]
  19. Migdalska-Sęk, M.; Czarnecka, K.H.; Kusiński, M.; Pastuszak-Lewandoska, D.; Nawrot, E.; Kuzdak, K.; Brzeziańska-Lasota, E. Clinicopathological Significance of Overall Frequency of Allelic Loss (OFAL) in Lesions Derived from Thyroid Follicular Cell. Mol. Diagn. Ther. 2019, 23, 369–382. [Google Scholar] [CrossRef] [Green Version]
  20. Migdalska-Sęk, M.; Pastuszak-Lewandoska, D.; Brzeziańska, E. MSI and LOH in the Development and Prognosis of Follicular Cell-Derived Thyroid Tumours. Endokrynol. Pol. 2012, 63, 126–136. [Google Scholar]
  21. Kim, J.H.; Choi, K.Y.; Lee, D.J.; Rho, Y.-S.; Jo, S.-J. Loss of Heterozygosities in Five Tumor Suppressor Genes (FHIT Gene, P16, PRb, E-Cadherin and P53) in Thyroid Tumors. Clin. Exp. Otorhinolaryngol. 2014, 7, 53–58. [Google Scholar] [CrossRef] [PubMed]
  22. Foster, J.M.; Oumie, A.; Togneri, F.S.; Vasques, F.R.; Hau, D.; Taylor, M.; Tinkler-Hundal, E.; Southward, K.; Medlow, P.; McGreeghan-Crosby, K.; et al. Cross-Laboratory Validation of the OncoScan® FFPE Assay, a Multiplex Tool for Whole Genome Tumour Profiling. BMC Med. Genom. 2015, 8, 5. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Singh, R.R.; Mehrotra, M.; Chen, H.; Almohammedsalim, A.A.; Sahin, A.; Bosamra, A.; Patel, K.P.; Routbort, M.J.; Lu, X.; Ronald, A.; et al. Comprehensive Screening of Gene Copy Number Aberrations in Formalin-Fixed, Paraffin-Embedded Solid Tumors Using Molecular Inversion Probe–Based Single-Nucleotide Polymorphism Array. J. Mol. Diagn. 2016, 18, 676–687. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Jarząb, B.; Dedecjus, M.; Lewiński, A.; Adamczewski, Z.; Bakuła-Zalewska, E.; Bałdys-Waligórska, A.; Barczyński, M.; Biskup-Frużyńska, M.; Bobek-Billewicz, B.; Bossowski, A.; et al. Diagnosis and Treatment of Thyroid Cancer in Adult Patients—Recommendations of Polish Scientific Societies and the National Oncological Strategy. 2022 Update [Diagnostyka i Leczenie Raka Tarczycy u Chorych Dorosłych—Rekomendacje Polskich Towarzystw Naukowych Oraz Narodowej Strategii Onkologicznej. Aktualizacja Na Rok 2022]. Endokrynol. Pol. 2022, 73, 173–300. [Google Scholar] [CrossRef] [PubMed]
  25. Sawicka-Gutaj, N.; Gruszczyński, D.; Guzik, P.; Mostowska, A.; Walkowiak, J. Publication Ethics of Human Studies in the Light of the Declaration of Helsinki—A Mini-Review. J.Med. Sci. 2022, 91, e700. [Google Scholar] [CrossRef]
  26. Weber, F.; Aldred, M.A.; Morrison, C.D.; Plass, C.; Frilling, A.; Broelsch, C.E.; Waite, K.A.; Eng, C. Silencing of the Maternally Imprinted Tumor Suppressor ARHI Contributes to Follicular Thyroid Carcinogenesis. J. Clin. Endocrinol. Metab. 2005, 90, 1149–1155. [Google Scholar] [CrossRef] [Green Version]
  27. Rodrigues-Serpa, A.; Catarino, A.; Soares, J. Loss of Heterozygosity in Follicular and Papillary Thyroid Carcinomas. Cancer Genet. Cytogenet. 2003, 141, 26–31. [Google Scholar] [CrossRef]
  28. Trovato, M.; Fraggetta, F.; Villari, D.; Batolo, D.; Mackey, K.; Trimarchi, F.; Benvenga, S. Loss of Heterozygosity of the Long Arm of Chromosome 7 in Follicular and Anaplastic Thyroid Cancer, but Not in Papillary Thyroid Cancer 1. J. Clin. Endocrinol. Metab. 1999, 84, 3235–3240. [Google Scholar] [CrossRef] [Green Version]
  29. Zhang, J.-S.; Nelson, M.; McIver, B.; Hay, I.D.; Goellner, J.R.; Grant, C.S.; Eberhardt, N.L.; Smith, D.I. Differential Loss of Heterozygosity at 7q31.2 in Follicular and Papillary Thyroid Tumors. Oncogene 1998, 17, 789–793. [Google Scholar] [CrossRef] [Green Version]
  30. Farrand, K.; Delahunt, B.; Wang, X.-L.; McIver, B.; Hay, I.D.; Goellner, J.R.; Eberhardt, N.L.; Grebe, S.K.G. High Resolution Loss of Heterozygosity Mapping of 17p13 in Thyroid Cancer: Hurthle Cell Carcinomas Exhibit a Small 411-Kilobase Common Region of Allelic Imbalance, Probably Containing a Novel Tumor Suppressor Gene. J. Clin. Endocrinol. Metab. 2002, 87, 4715–4721. [Google Scholar] [CrossRef] [Green Version]
  31. Grebe, S.K.; McIver, B.; Hay, I.D.; Wu, P.S.; Maciel, L.M.; Drabkin, H.A.; Goellner, J.R.; Grant, C.S.; Jenkins, R.B.; Eberhardt, N.L. Frequent Loss of Heterozygosity on Chromosomes 3p and 17p without VHL or P53 Mutations Suggests Involvement of Unidentified Tumor Suppressor Genes in Follicular Thyroid Carcinoma. J. Clin. Endocrinol. Metab. 1997, 82, 3684–3691. [Google Scholar] [CrossRef] [PubMed]
  32. Hu, M.-J.; Xu, H.-D.; Zhou, R.; Li, X.-F.; Zhang, H.-Y. Loss of heterozygosity on chromosome 3p in thyroid tumors. Zhonghua Bing Li Xue Za Zhi Chin. J. Pathol. 2008, 37, 305–308. [Google Scholar]
  33. Nikiforova, M.N.; Lynch, R.A.; Biddinger, P.W.; Alexander, E.K.; Dorn, G.W.; Tallini, G.; Kroll, T.G.; Nikiforov, Y.E. RAS Point Mutations and PAX8-PPAR Gamma Rearrangement in Thyroid Tumors: Evidence for Distinct Molecular Pathways in Thyroid Follicular Carcinoma. J. Clin. Endocrinol. Metab. 2003, 88, 2318–2326. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Tanikawa, C.; Kamatani, Y.; Toyoshima, O.; Sakamoto, H.; Ito, H.; Takahashi, A.; Momozawa, Y.; Hirata, M.; Fuse, N.; Takai-Igarashi, T.; et al. Genome-Wide Association Study Identifies Gastric Cancer Susceptibility Loci at 12q24.11-12 and 20q11.21. Cancer Sci. 2018, 109, 4015–4024. [Google Scholar] [CrossRef] [Green Version]
  35. Wolf, M.; Korja, M.; Karhu, R.; Edgren, H.; Kilpinen, S.; Ojala, K.; Mousses, S.; Kallioniemi, A.; Haapasalo, H. Array-Based Gene Expression, CGH and Tissue Data Defines a 12q24 Gain in Neuroblastic Tumors with Prognostic Implication. BMC Cancer 2010, 10, 181. [Google Scholar] [CrossRef] [Green Version]
  36. Zou, X.; Gao, Y.; Ruvolo, V.R.; Gardner, T.L.; Ruvolo, P.P.; Brown, R.E. Human Glycolipid Transfer Protein Gene (GLTP) Expression Is Regulated by Sp1 and Sp3: Involvement of the Bioactive Sphingolipid Ceramide. J. Biol. Chem. 2011, 286, 1301–1311. [Google Scholar] [CrossRef] [Green Version]
  37. Hemmer, S.; Wasenius, V.M.; Knuutila, S.; Franssila, K.; Joensuu, H. DNA Copy Number Changes in Thyroid Carcinoma. Am. J. Pathol. 1999, 154, 1539–1547. [Google Scholar] [CrossRef] [Green Version]
  38. Kitamura, Y.; Shimizu, K.; Ito, K.; Tanaka, S.; Emi, M. Allelotyping of Follicular Thyroid Carcinoma: Frequent Allelic Losses in Chromosome Arms 7q, 11p, and 22q. J. Clin. Endocrinol. Metab. 2001, 86, 4268–4272. [Google Scholar] [CrossRef]
  39. Ward, L.S.; Brenta, G.; Medvedovic, M.; Fagin, J.A. Studies of Allelic Loss in Thyroid Tumors Reveal Major Differences in Chromosomal Instability between Papillary and Follicular Carcinomas. J. Clin. Endocrinol. Metab. 1998, 83, 525–530. [Google Scholar] [CrossRef]
  40. Boland, C.R.; Thibodeau, S.N.; Hamilton, S.R.; Sidransky, D.; Eshleman, J.R.; Burt, R.W.; Meltzer, S.J.; Rodriguez-Bigas, M.A.; Fodde, R.; Ranzani, G.N.; et al. A National Cancer Institute Workshop on Microsatellite Instability for Cancer Detection and Familial Predisposition: Development of International Criteria for the Determination of Microsatellite Instability in Colorectal Cancer. Cancer Res. 1998, 58, 5248–5257. [Google Scholar]
  41. Knudson, A.G. Two Genetic Hits (More or Less) to Cancer. Nat. Rev. Cancer 2001, 1, 157–162. [Google Scholar] [CrossRef] [PubMed]
  42. Nikitski, A.V.; Nikiforova, M.N.; Yip, L.; Karslioglu-French, E.; Carty, S.E.; Nikiforov, Y.E. Can TP53-Mutant Follicular Adenoma Be a Precursor of Anaplastic Thyroid Carcinoma? Endocr. Relat. Cancer 2021, 28, 621–630. [Google Scholar] [CrossRef] [PubMed]
  43. Hunt, J.L.; Livolsi, V.A.; Baloch, Z.W.; Swalsky, P.A.; Bakker, A.; Sasatomi, E.; Finkelstein, S.; Barnes, E.L. A Novel Microdissection and Genotyping of Follicular-Derived Thyroid Tumors to Predict Aggressiveness. Hum. Pathol. 2003, 34, 375–380. [Google Scholar] [CrossRef] [PubMed]
  44. Marsh, D.J.; Zheng, Z.; Zedenius, J.; Kremer, H.; Padberg, G.W.; Larsson, C.; Longy, M.; Eng, C. Differential Loss of Heterozygosity in the Region of the Cowden Locus within 10q22-23 in Follicular Thyroid Adenomas and Carcinomas. Cancer Res. 1997, 57, 500–503. [Google Scholar] [PubMed]
  45. Wozniak, A.; Wiench, M.; Olejniczak, A.; Wloch, J.; Lachinski, A.; Lange, D.; Olczyk, T.; Jarzab, B.; Limon, J. Loss of Heterozygosity in 73 Human Thyroid Tumors. Neuroendocrinol. Lett. 2005, 26, 521–525. [Google Scholar]
  46. Sarquis, M.S.; Weber, F.; Shen, L.; Broelsch, C.E.; Jhiang, S.M.; Zedenius, J.; Frilling, A.; Eng, C. High Frequency of Loss of Heterozygosity in Imprinted, Compared with Nonimprinted, Genomic Regions in Follicular Thyroid Carcinomas and Atypical Adenomas. J. Clin. Endocrinol. Metab. 2006, 91, 262–269. [Google Scholar] [CrossRef] [Green Version]
  47. Gerashchenko, T.S.; Denisov, E.V.; Litviakov, N.V.; Zavyalova, M.V.; Vtorushin, S.V.; Tsyganov, M.M.; Perelmuter, V.M.; Cherdyntseva, N.V. Intratumor Heterogeneity: Nature and Biological Significance. Biochemistry 2013, 78, 1201–1215. [Google Scholar] [CrossRef]
  48. Chmielik, E.; Rusinek, D.; Oczko-Wojciechowska, M.; Jarzab, M.; Krajewska, J.; Czarniecka, A.; Jarzab, B. Heterogeneity of Thyroid Cancer. Pathobiology 2018, 85, 117–129. [Google Scholar] [CrossRef]
  49. Pizzo, L.; Lasser, M.; Yusuff, T.; Jensen, M.; Ingraham, P.; Huber, E.; Singh, M.D.; Monahan, C.; Iyer, J.; Desai, I.; et al. Functional Assessment of the “Two-Hit” Model for Neurodevelopmental Defects in Drosophila and X. Laevis. PLoS Genet. 2021, 17, e1009112. [Google Scholar] [CrossRef]
  50. Vasko, V.V.; Gaudart, J.; Allasia, C.; Savchenko, V.; Di Cristofaro, J.; Saji, M.; Ringel, M.D.; De Micco, C. Thyroid follicular adenomas may display features of follicular carcinoma and follicular variant of papillary carcinoma. Eur. J. Endocrinol. 2004, 151, 779–786. [Google Scholar] [CrossRef] [Green Version]
  51. Odermatt, A.; Barton, K.; Khanna, V.K.; Mathieu, J.; Escolar, D.; Kuntzer, T.; Karpati, G.; MacLennan, D.H. The Mutation of Pro789 to Leu Reduces the Activity of the Fast-Twitch Skeletal Muscle Sarco(Endo)Plasmic Reticulum Ca2+ ATPase (SERCA1) and Is Associated with Brody Disease. Hum. Genet. 2000, 106, 482–491. [Google Scholar] [CrossRef] [PubMed]
  52. Expression of ATP2A1 in Cancer-Summary-The Human Protein Atlas. Available online: https://www.proteinatlas.org/ENSG00000196296-ATP2A1/pathology (accessed on 31 July 2022).
  53. Bloise, F.F.; Cordeiro, A.; Ortiga-Carvalho, T.M. Role of Thyroid Hormone in Skeletal Muscle Physiology. J. Endocrinol. 2018, 236, R57–R68. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. GeneCards Database.
  55. Hartong, R.; Wang, N.; Kurokawa, R.; Lazar, M.A.; Glass, C.K.; Apriletti, J.W.; Dillmann, W.H. Delineation of Three Different Thyroid Hormone-Response Elements in Promoter of Rat Sarcoplasmic Reticulum Ca2+ ATPase Gene. Demonstration That Retinoid X Receptor Binds 5’ to Thyroid Hormone Receptor in Response Element 1. J. Biol. Chem. 1994, 269, 13021–13029. [Google Scholar] [CrossRef] [PubMed]
  56. Muller, A.; Vanderlinden, G.C.; Zuidwijk, M.J.; Simonides, W.S.; Vanderlaarse, W.J.; Vanhardeveld, C. Differential Effects of Thyroid Hormone on the Expression of Sarcoplasmic Reticulum Ca2+-ATPase Isoforms in Rat Skeletal Muscle Fibers. Biochem. Biophys. Res. Commun. 1994, 203, 1035–1042. [Google Scholar] [CrossRef]
  57. Simonides, W.S.; Brent, G.A.; Thelen, M.M.; van der Linden, C.G.; Larsen, P.R.; van Hardeveld, C. Characterization of the Promoter of the Rat Sarcoplasmic Endoplasmic Reticulum Ca2+-ATPase 1 Gene and Analysis of Thyroid Hormone Responsiveness. J. Biol. Chem. 1996, 271, 32048–32056. [Google Scholar] [CrossRef] [Green Version]
  58. Dang, D.; Rao, R. Calcium-ATPases: Gene Disorders and Dysregulation in Cancer. Biochim. Biophys. Acta(BBA)-Mol. Cell Res. 2016, 1863, 1344–1350. [Google Scholar] [CrossRef]
  59. He, W.; Wang, B.; Mu, K.; Zhang, J.; Yang, Y.; Yao, W.; Li, S.; Zhang, J. Association of Single-Nucleotide Polymorphisms in the IL27 Gene with Autoimmune Thyroid Diseases. Endocr. Connect. 2019, 8, 173–181. [Google Scholar] [CrossRef] [Green Version]
  60. Saeed, M.-H.; Kurosh, K.; Zahra, A.; Hossein, D.M.; Davood, R.; Ataollahi, M.R. Decreased Serum Levels of IL-27and IL-35 in Patients with Graves Disease. Arch. Endocrinol. Metab. 2020, 64, 521–527. [Google Scholar] [CrossRef] [Green Version]
  61. Nie, X.; Yuan, F.; Chen, P.; Pu, Y.; Zhu, J.; Wang, Y.; Xiao, X.; Che, G.; Gao, L.; Zhang, L. Association between IL-27 Gene Polymorphisms and Risk of Papillary Thyroid Carcinoma. Biomark. Med. 2017, 11, 141–149. [Google Scholar] [CrossRef]
  62. Xi, C.; Zhang, G.-Q.; Sun, Z.-K.; Song, H.-J.; Shen, C.-T.; Chen, X.-Y.; Sun, J.-W.; Qiu, Z.-L.; Luo, Q.-Y. Interleukins in Thyroid Cancer: From Basic Researches to Applications in Clinical Practice. Front. Immunol. 2020, 11, 1124. [Google Scholar] [CrossRef]
  63. Jia, H.; Dilger, P.; Bird, C.; Wadhwa, M. IL-27 Promotes Proliferation of Human Leukemic Cell Lines Through the MAPK/ERK Signaling Pathway and Suppresses Sensitivity to Chemotherapeutic Drugs. J. Interferon Cytokine Res. 2016, 36, 302–316. [Google Scholar] [CrossRef] [Green Version]
  64. Larousserie, F.; Bardel, E.; Coulomb L’Herminé, A.; Canioni, D.; Brousse, N.; Kastelein, R.; Devergne, O. Variable Expression of Epstein–Barr Virus-Induced Gene 3 during Normal B-Cell Differentiation and among B-Cell Lymphomas. J. Pathol. 2006, 209, 360–368. [Google Scholar] [CrossRef] [PubMed]
  65. Gonin, J.; Carlotti, A.; Dietrich, C.; Audebourg, A.; Radenen-Bussière, B.; Caignard, A.; Avril, M.-F.; Vacher-Lavenu, M.-C.; Larousserie, F.; Devergne, O. Expression of IL-27 by Tumor Cells in InvasCutaneous and Metastatic Melanomas. PLoS ONE 2013, 8, e75694. [Google Scholar] [CrossRef]
  66. Kourko, O.; Seaver, K.; Odoardi, N.; Basta, S.; Gee, K. IL-27, IL-30, and IL-35: A Cytokine Triumvirate in Cancer. Front. Oncol. 2019, 9, 969. [Google Scholar] [CrossRef] [PubMed]
  67. Pisarev, M.A.; Thomasz, L.; Juvenal, G.J. Role of Transforming Growth Factor Beta in the Regulation of Thyroid Function and Growth. Thyroid 2009, 19, 881–892. [Google Scholar] [CrossRef] [PubMed]
  68. Kardalas, E.; Sakkas, E.; Ruchala, M.; Macut, D.; Mastorakos, G. The Role of Transforming Growth Factor Beta in Thyroid Autoimmunity: Current Knowledge and Future Perspectives. Rev. Endocr. Metab. Disord. 2022, 23, 431–447. [Google Scholar] [CrossRef]
  69. Mincione, G.; Di Marcantonio, M.C.; Tarantelli, C.; D’Inzeo, S.; Nicolussi, A.; Nardi, F.; Donini, C.F.; Coppa, A. EGF and TGF- <b/> 1 Effects on Thyroid Function. J. Thyroid. Res. 2011, 2011, 1–13. [Google Scholar] [CrossRef] [Green Version]
  70. Grubeck-Loebenstein, B.; Buchan, G.; Sadeghi, R.; Kissonerghis, M.; Londei, M.; Turner, M.; Pirich, K.; Roka, R.; Niederle, B.; Kassal, H. Transforming Growth Factor Beta Regulates Thyroid Growth. Role in the Pathogenesis of Nontoxic Goiter. J. Clin. Invest. 1989, 83, 764–770. [Google Scholar] [CrossRef]
  71. Wikipathways MAPK Pathway in Congenital Thyroid Cancer (Homo Sapiens).
  72. Protein Atlas.
  73. Knauf, J.A.; Fagin, J.A. Role of MAPK Pathway Oncoproteins in Thyroid Cancer Pathogenesis and as Drug Targets. Curr. Opin. Cell Biol. 2009, 21, 296–303. [Google Scholar] [CrossRef]
  74. Lin, H.-Y.; Davis, F.B.; Gordinier, J.K.; Martino, L.J.; Davis, P.J. Thyroid Hormone Induces Activation of Mitogen-Activated Protein Kinase in Cultured Cells. Am. J. Physiol.-Cell Physiol. 1999, 276, C1014–C1024. [Google Scholar] [CrossRef]
  75. Cho, S.Y.; Kim, S.; Kim, G.; Singh, P.; Kim, D.W. Integrative Analysis of KIF4A, 9, 18A, and 23 and Their Clinical Significance in Low-Grade Glioma and Glioblastoma. Sci. Rep. 2019, 9, 4599. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  76. Cao, J.; Wang, P.; Chen, J.; He, X. Systemic Characterization of the SLC Family Genes Reveals SLC26A6 as a Novel Oncogene in Hepatocellular Carcinoma. Transl. Cancer Res. 2021, 10, 2882–2894. [Google Scholar] [CrossRef] [PubMed]
  77. Alper, S.L.; Sharma, A.K. The SLC26 Gene Family of Anion Transporters and Channels. Mol. Asp. Med. 2013, 34, 494–515. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  78. Zhu, Y.; Huang, Y.; Chen, L.; Guo, L.; Wang, L.; Li, M.; Liang, Y. Up-Regulation of SLC26A6 in Hepatocellular Carcinoma and Its Diagnostic and Prognostic Significance. Crit. Rev. Eukaryot.Gene Expr. 2021, 31, 79–94. [Google Scholar] [CrossRef] [PubMed]
  79. Fontaine, J.-F.; Mirebeau-Prunier, D.; Franc, B.; Triau, S.; Rodien, P.; Houlgatte, R.; Malthièry, Y.; Savagner, F. Microarray Analysis Refines Classification of Non-Medullary Thyroid Tumours of Uncertain Malignancy. Oncogene 2008, 27, 2228–2236. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  80. Lin, M.; Li, Y.; Qin, S.; Jiao, Y.; Hua, F. Ubiquitin-like Modifier-activating Enzyme 7 as a Marker for the Diagnosis and Prognosis of Breast Cancer. Oncol. Lett. 2020, 19, 2773–2784. [Google Scholar] [CrossRef]
  81. Fan, J.-B.; Miyauchi, S.; Xu, H.-Z.; Liu, D.; Kim, L.J.Y.; Burkart, C.; Cheng, H.; Arimoto, K.; Yan, M.; Zhou, Y.; et al. Type I Interferon Regulates a Coordinated Gene Network to Enhance Cytotoxic T Cell–Mediated Tumor Killing. Cancer Discov. 2020, 10, 382–393. [Google Scholar] [CrossRef]
  82. Warnier, M.; Roudbaraki, M.; Derouiche, S.; Delcourt, P.; Bokhobza, A.; Prevarskaya, N.; Mariot, P. CACNA2D2 Promotes Tumorigenesis by Stimulating Cell Proliferation and Angiogenesis. Oncogene 2015, 34, 5383–5394. [Google Scholar] [CrossRef]
  83. Carboni, G.L.; Gao, B.; Nishizaki, M.; Xu, K.; Minna, J.D.; Roth, J.A.; Ji, L. CACNA2D2-Mediated Apoptosis in NSCLC Cells Is Associated with Alterations of the Intracellular Calcium Signaling and Disruption of Mitochondria Membrane Integrity. Oncogene 2003, 22, 615–626. [Google Scholar] [CrossRef] [Green Version]
  84. Peng, S.; Li, C.; Wang, X.; Liu, X.; Han, C.; Jin, T.; Liu, S.; Zhang, X.; Zhang, H.; He, X.; et al. Increased Toll-Like Receptors Activity and TLR Ligands in Patients with Autoimmune Thyroid Diseases. Front. Immunol. 2016, 7, 578. [Google Scholar] [CrossRef] [Green Version]
  85. Nihon-Yanagi, Y.; Wakayama, M.; Tochigi, N.; Saito, F.; Ogata, H.; Shibuya, K. Immunohistochemical Analysis of Toll-Like Receptors, MyD88, and TRIF in Human Papillary Thyroid Carcinoma and Anaplastic Thyroid Carcinoma. J. Thyroid. Res. 2021, 2021, 1–12. [Google Scholar] [CrossRef] [PubMed]
  86. Inoue, N.; Katsumata, Y.; Watanabe, M.; Ishido, N.; Manabe, Y.; Watanabe, A.; Masutani, R.; Hidaka, Y.; Iwatani, Y. Polymorphisms and Expression of Toll-like Receptors in Autoimmune Thyroid Diseases. Autoimmunity 2017, 50, 182–191. [Google Scholar] [CrossRef] [PubMed]
  87. McDonnell, K.J.; Gallanis, G.T.; Heller, K.A.; Melas, M.; Idos, G.E.; Culver, J.O.; Martin, S.-E.; Peng, D.H.; Gruber, S.B. A Novel BAP1 Mutation Is Associated with Melanocytic Neoplasms and Thyroid Cancer. Cancer Genet. 2016, 209, 75–81. [Google Scholar] [CrossRef]
  88. Farid, R.M.; Abd El Atti, R.M.; Abd Raboh, N.M. Immunohistochemical Expression of the Cancer Predisposition Gene BRCA1-Associated Protein 1 in Thyroid and Lung Carcinoma. Egypt J. Pathol. 2019, 39, 98. [Google Scholar]
  89. Haugh, A.M.; Njauw, C.-N.; Bubley, J.A.; Verzì, A.E.; Zhang, B.; Kudalkar, E.; VandenBoom, T.; Walton, K.; Swick, B.L.; Kumar, R.; et al. Genotypic and Phenotypic Features of BAP1 Cancer Syndrome: A Report of 8 New Families and Review of Cases in the Literature. JAMA Dermatol. 2017, 153, 999. [Google Scholar] [CrossRef] [PubMed]
  90. Gallanis, G.T.; Heller, K.A.; Melas, E.-M.; Gruber, S.B. Abstract 3522: A Novel BAP1 Mutation Is Associated with Melanocytic Neoplasms and Thyroid and Pancreatic Cancers. Cancer Res. 2014, 74, 3522. [Google Scholar] [CrossRef]
  91. Avilla, E.; Guarino, V.; Visciano, C.; Liotti, F.; Svelto, M.; Krishnamoorthy, G.; Franco, R.; Melillo, R.M. Activation of TYRO3/AXL Tyrosine Kinase Receptors in Thyroid Cancer. Cancer Res. 2011, 71, 1792–1804. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  92. Hsu, P.-L.; Jou, J.; Tsai, S.-J. TYRO3: A Potential Therapeutic Target in Cancer. Exp. Biol. Med. 2019, 244, 83–99. [Google Scholar] [CrossRef] [Green Version]
  93. Ao, Z.; Chen, Y.; Lu, J.; Shen, J.; Peng, L.; Lin, X.; Peng, C.; Zeng, C.; Wang, X.; Zhou, R.; et al. Identification of Potential Functional Genes in Papillary Thyroid Cancer by Co-expression Network Analysis. Oncol. Lett. 2018, 16, 4871–4878. [Google Scholar] [CrossRef]
  94. Sato, A.; Matsuda, K.; Motoyama, T.; Mussazhanova, Z.; Otsubo, R.; Kondo, H.; Akazawa, Y.; Higuchi, M.; Suzuki, A.; Hirokawa, M.; et al. 53BP1 Expression as a Biomarker to Differentiate Thyroid Follicular Tumors. Endocr. Connect. 2021, 10, 309–315. [Google Scholar] [CrossRef]
  95. Xia, Z.; Morales, J.C.; Dunphy, W.G.; Carpenter, P.B. Negative Cell Cycle Regulation and DNA Damage-Inducible Phosphorylation of the BRCT Protein 53BP1. J. Biol. Chem. 2001, 276, 2708–2718. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. Mussazhanova, Z.; Matsuda, K.; Naruke, Y.; Mitsutake, N.; Stanojevic, B.; Rougounovitch, T.; Saenko, V.; Suzuki, K.; Nishihara, E.; Hirokawa, M.; et al. Significance of P53-Binding Protein 1 (53BP1) Expression in Thyroid Papillary Microcarcinoma: Association with BRAF V 600E Mutation Status. Histopathology 2013, 63, 726–734. [Google Scholar] [CrossRef] [PubMed]
  97. Otsubo, R.; Matsuda, K.; Mussazhanova, Z.; Sato, A.; Matsumoto, M.; Yano, H.; Oikawa, M.; Kondo, H.; Ito, M.; Miyauchi, A.; et al. A Novel Diagnostic Method for Thyroid Follicular Tumors Based on Immunofluorescence Analysis of P53-Binding Protein 1 Expression: Detection of Genomic Instability. Thyroid 2019, 29, 657–665. [Google Scholar] [CrossRef]
  98. Zambrano, A.; García-Carpizo, V.; Gallardo, M.E.; Villamuera, R.; Gómez-Ferrería, M.A.; Pascual, A.; Buisine, N.; Sachs, L.M.; Garesse, R.; Aranda, A. The Thyroid Hormone Receptor β Induces DNA Damage and Premature Senescence. J. Cell Biol. 2014, 204, 129–146. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  99. Luong, T.M.H.; Matsuda, K.; Niino, D.; Kurohama, H.; Ito, M.; Nakashima, M. Significance of Abnormal 53BP1 Expression as a Novel Molecular Pathologic Parameter of Follicular-Shaped B-Cell Lymphoid Lesions in Human Digestive Tract. Sci. Rep. 2021, 11, 3074. [Google Scholar] [CrossRef]
  100. Lee, A.S.Y.; Kranzusch, P.J.; Cate, J.H.D. EIF3 Targets Cell-Proliferation Messenger RNAs for Translational Activation or Repression. Nature 2015, 522, 111–114. [Google Scholar] [CrossRef] [Green Version]
  101. Lee, A.S.Y.; Kranzusch, P.J.; Doudna, J.A.; Cate, J.H.D. EIF3d Is an MRNA Cap-Binding Protein That Is Required for Specialized Translation Initiation. Nature 2016, 536, 96–99. [Google Scholar] [CrossRef] [Green Version]
  102. Chi, N.C.; Shaw, R.M.; De Val, S.; Kang, G.; Jan, L.Y.; Black, B.L.; Stainier, D.Y.R. Foxn4 Directly Regulates Tbx2b Expression and Atrioventricular Canal Formation. Genes Dev. 2008, 22, 734–739. [Google Scholar] [CrossRef] [Green Version]
  103. Luo, H.; Jin, K.; Xie, Z.; Qiu, F.; Li, S.; Zou, M.; Cai, L.; Hozumi, K.; Shima, D.T.; Xiang, M. Forkhead Box N4 (Foxn4) Activates Dll4-Notch Signaling to Suppress Photoreceptor Cell Fates of Early Retinal Progenitors. Proc. Natl. Acad. Sci. USA 2012, 109. [Google Scholar] [CrossRef] [Green Version]
  104. MalaCards.
  105. Weterman, M.A.J.; Barth, P.G.; van Spaendonck-Zwarts, K.Y.; Aronica, E.; Poll-The, B.-T.; Brouwer, O.F.; van Tintelen, J.P.; Qahar, Z.; Bradley, E.J.; de Wissel, M.; et al. Recessive MYL2 Mutations Cause Infantile Type I Muscle Fibre Disease and Cardiomyopathy. Brain 2013, 136, 282–293. [Google Scholar] [CrossRef] [Green Version]
  106. Manivannan, S.N.; Darouich, S.; Masmoudi, A.; Gordon, D.; Zender, G.; Han, Z.; Fitzgerald-Butt, S.; White, P.; McBride, K.L.; Kharrat, M.; et al. Novel Frameshift Variant in MYL2 Reveals Molecular Differences between Dominant and Recessive Forms of Hypertrophic Cardiomyopathy. PLoS Genet. 2020, 16, e1008639. [Google Scholar] [CrossRef]
  107. Claes, G.R.F.; van Tienen, F.H.J.; Lindsey, P.; Krapels, I.P.C.; Helderman-van den Enden, A.T.J.M.; Hoos, M.B.; Barrois, Y.E.G.; Janssen, J.W.H.; Paulussen, A.D.C.; Sels, J.-W.E.M.; et al. Hypertrophic Remodelling in Cardiac Regulatory Myosin Light Chain (MYL2) Founder Mutation Carriers. Eur. Heart J. 2016, 37, 1815–1822. [Google Scholar] [CrossRef] [Green Version]
  108. Lee, E.J.; Shaikh, S.; Choi, D.; Ahmad, K.; Baig, M.H.; Lim, J.H.; Lee, Y.-H.; Park, S.J.; Kim, Y.-W.; Park, S.-Y.; et al. Transthyretin Maintains Muscle Homeostasis through the Novel Shuttle Pathway of Thyroid Hormones during Myoblast Differentiation. Cells 2019, 8, 1565. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  109. Miao, H.; Burnett, E.; Kinch, M.; Simon, E.; Wang, B. Activation of EphA2 Kinase Suppresses Integrin Function and Causes Focal-Adhesion-Kinase Dephosphorylation. Nat. Cell Biol. 2000, 2, 62–69. [Google Scholar] [CrossRef]
  110. Lee, H.-H.; Chang, Z.-F. Regulation of RhoA-Dependent ROCKII Activation by Shp2. J. Cell Biol. 2008, 181, 999–1012. [Google Scholar] [CrossRef]
  111. Pannone, L.; Bocchinfuso, G.; Flex, E.; Rossi, C.; Baldassarre, G.; Lissewski, C.; Pantaleoni, F.; Consoli, F.; Lepri, F.; Magliozzi, M.; et al. Structural, Functional, and Clinical Characterization of a Novel PTPN11 Mutation Cluster Underlying Noonan Syndrome: HUMAN MUTATION. Hum. Mutat. 2017, 38, 451–459. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  112. Hu, Z.-Q.; Ma, R.; Zhang, C.-M.; Li, J.; Li, L.; Hu, Z.-T.; Gao, Q.; Li, W.-M. Expression and Clinical Significance of Tyrosine Phosphatase SHP2 in Thyroid Carcinoma. Oncol. Lett. 2015, 10, 1507–1512. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Basel-Vanagaite, L.; Dallapiccola, B.; Ramirez-Solis, R.; Segref, A.; Thiele, H.; Edwards, A.; Arends, M.J.; Miró, X.; White, J.K.; Désir, J.; et al. Deficiency for the Ubiquitin Ligase UBE3B in a Blepharophimosis-Ptosis-Intellectual-Disability Syndrome. Am. J. Hum. Genet. 2012, 91, 998–1010. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  114. Basel-Vanagaite, L.; Yilmaz, R.; Tang, S.; Reuter, M.S.; Rahner, N.; Grange, D.K.; Mortenson, M.; Koty, P.; Feenstra, H.; Farwell Gonzalez, K.D.; et al. Expanding the Clinical and Mutational Spectrum of Kaufman Oculocerebrofacial Syndrome with Biallelic UBE3B Mutations. Hum. Genet. 2014, 133, 939–949. [Google Scholar] [CrossRef]
  115. Wickenhagen, A.; Sugrue, E.; Lytras, S.; Kuchi, S.; Noerenberg, M.; Turnbull, M.L.; Loney, C.; Herder, V.; Allan, J.; Jarmson, I.; et al. A Prenylated DsRNA Sensor Protects against Severe COVID-19. Science 2021, 374, eabj3624. [Google Scholar] [CrossRef]
  116. Yamazaki, K.; Suzuki, K.; Yamada, E.; Yamada, T.; Takeshita, F.; Matsumoto, M.; Mitsuhashi, T.; Obara, T.; Takano, K.; Sato, K. Suppression of Iodide Uptake and Thyroid Hormone Synthesis with Stimulation of the Type I Interferon System by Double-Stranded Ribonucleic Acid in Cultured Human Thyroid Follicles. Endocrinology 2007, 148, 3226–3235. [Google Scholar] [CrossRef] [Green Version]
  117. Stefan, M.; Wei, C.; Lombardi, A.; Li, C.W.; Concepcion, E.S.; Inabnet, W.B.; Owen, R.; Zhang, W.; Tomer, Y. Genetic–Epigenetic Dysregulation of Thymic TSH Receptor Gene Expression Triggers Thyroid Autoimmunity. Proc. Natl. Acad. Sci. USA 2014, 111, 12562–12567. [Google Scholar] [CrossRef] [Green Version]
  118. Poma, A.M.; Basolo, A.; Bonuccelli, D.; Proietti, A.; Macerola, E.; Ugolini, C.; Torregrossa, L.; Alì, G.; Giannini, R.; Vignali, P.; et al. Activation of Type I and Type II Interferon Signaling in SARS-CoV-2-Positive Thyroid Tissue of Patients Dying from COVID-19. Thyroid 2021, 31, 1766–1775. [Google Scholar] [CrossRef] [PubMed]
  119. Hébrant, A.; Dom, G.; Dewaele, M.; Andry, G.; Trésallet, C.; Leteurtre, E.; Dumont, J.E.; Maenhaut, C. MRNA Expression in Papillary and Anaplastic Thyroid Carcinoma: Molecular Anatomy of a Killing Switch. PLoS ONE 2012, 7, e37807. [Google Scholar] [CrossRef] [PubMed]
  120. Zhen, J.; Song, Z.; Su, W.; Zeng, Q.-C.; Li, J.; Sun, Q. Integrated Analysis of RNA-Binding Proteins in Thyroid Cancer. PLoS ONE 2021, 16, e0247836. [Google Scholar] [CrossRef] [PubMed]
  121. Jiang, Y.; Zhang, P.; Li, L.-P.; He, Y.-C.; Gao, R.; Gao, Y.-F. Identification of Novel Thyroid Cancer-Related Genes and Chemicals Using Shortest Path Algorithm. BioMed Res. Int. 2015, 2015, 1–8. [Google Scholar] [CrossRef] [Green Version]
  122. Auslander, N.; Wolf, Y.I.; Koonin, E.V. Interplay between DNA Damage Repair and Apoptosis Shapes Cancer Evolution through Aneuploidy and Microsatellite Instability. Nat. Commun. 2020, 11, 1234. [Google Scholar] [CrossRef] [Green Version]
  123. Xing, M. RASAL1 in Thyroid Cancer: Promise From a New Friend. J. Clin. Endocrinol. Metab. 2014, 99, 3619–3621. [Google Scholar] [CrossRef] [Green Version]
  124. Chang, R.-X.; Cui, A.-L.; Dong, L.; Guan, S.-P.; Jiang, L.-Y.; Miao, C.-X. Overexpression of RASAL1 Indicates Poor Prognosis and Promotes Invasion of Ovarian Cancer. Open Life Sci. 2019, 14, 133–140. [Google Scholar] [CrossRef]
  125. Liu, D.; Yang, C.; Bojdani, E.; Murugan, A.K.; Xing, M. Identification of RASAL1 as a Major Tumor Suppressor Gene in Thyroid Cancer. JNCI J. Natl. Cancer Inst. 2013, 105, 1617–1627. [Google Scholar] [CrossRef] [Green Version]
  126. Wang, G.; Li, Z.; Li, X.; Zhang, C.; Peng, L. RASAL1 Induces to Downregulate the SCD1, Leading to Suppression of Cell Proliferation in Colon Cancer via LXRα/SREBP1c Pathway. Biol. Res. 2019, 52, 60. [Google Scholar] [CrossRef]
  127. Hińcza, K.; Kowalik, A.; Kowalska, A. Current Knowledge of Germline Genetic Risk Factors for the Development of Non-Medullary Thyroid Cancer. Genes 2019, 10, 482. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  128. Lyssikatos, C.; Quezado, M.M.; Faucz, F.R.; Angelousi, A.; Nasiri-Ansari, N.; Stratakis, C.A.; Kassi, E. A Rare Case of Medullary Thyroid Cancer, Mesothelioma and Meningioma, Due to APC and RASAL1 Mutations. In Proceedings of the 19th European Congress of Endocrinology, Lisbon, Portugal, 20–23 May 2017. [Google Scholar] [CrossRef]
  129. Henderson, Y.C.; Toro-Serra, R.; Chen, Y.; Ryu, J.; Frederick, M.J.; Zhou, G.; Gallick, G.E.; Lai, S.Y.; Clayman, G.L. Src Inhibitors in Suppression of Papillary Thyroid Carcinoma Growth: Effects of SRC Inhibitors in PTC. Head Neck 2014, 36, 375–384. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  130. Beadnell, T.C.; Nassar, K.W.; Rose, M.M.; Clark, E.G.; Danysh, B.P.; Hofmann, M.-C.; Pozdeyev, N.; Schweppe, R.E. Src-Mediated Regulation of the PI3K Pathway in Advanced Papillary and Anaplastic Thyroid Cancer. Oncogenesis 2018, 7, 23. [Google Scholar] [CrossRef]
  131. Chan, C.M.; Jing, X.; Pike, L.A.; Zhou, Q.; Lim, D.-J.; Sams, S.B.; Lund, G.S.; Sharma, V.; Haugen, B.R.; Schweppe, R.E. Targeted Inhibition of Src Kinase with Dasatinib Blocks Thyroid Cancer Growth and Metastasis. Clin. Cancer Res. 2012, 18, 3580–3591. [Google Scholar] [CrossRef] [Green Version]
  132. Lee, W.K.; Kim, W.G.; Fozzatti, L.; Park, S.; Zhao, L.; Willingham, M.C.; Lonard, D.; O’Malley, B.W.; Cheng, S. Steroid Receptor Coactivator-3 as a Target for Anaplastic Thyroid Cancer. Endocr.-Relat. Cancer 2020, 27, 209–220. [Google Scholar] [CrossRef] [PubMed]
  133. Liu, Z.; Falola, J.; Zhu, X.; Gu, Y.; Kim, L.T.; Sarosi, G.A.; Anthony, T.; Nwariaku, F.E. Antiproliferative Effects of Src Inhibition on Medullary Thyroid Cancer. J. Clin. Endocrinol. Metab. 2004, 89, 3503–3509. [Google Scholar] [CrossRef] [Green Version]
  134. Chen, Z. CD82, but Not CD63, Is Linked to Cellular Invasiveness in Human Thyroid Carcinoma. Ph.D. Thesis, Martin-Luther-Universität Halle-Wittenberg, Halle (Saale), Germany, 2007. [Google Scholar] [CrossRef]
  135. Kim, T.; Kim, Y.; Kwon, H.J. Expression of CD9 and CD82 in Papillary Thyroid Microcarcinoma and Its Prognostic Significance. Endokrynologia Polska 2019, 70, 224–231. [Google Scholar] [CrossRef] [Green Version]
  136. Qiu, K.; Li, K.; Zeng, T.; Liao, Y.; Min, J.; Zhang, N.; Peng, M.; Kong, W.; Chen, L. Integrative Analyses of Genes Associated with Hashimoto’s Thyroiditis. J. Immunol. Res. 2021, 2021, 1–9. [Google Scholar] [CrossRef]
  137. Bang, H.S.; Choi, M.H.; Kim, C.S.; Choi, S.J. Gene Expression Profiling in Undifferentiated Thyroid Carcinoma Induced by High-Dose Radiation. J. Radiat. Res. 2016, 57, 238–249. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  138. Weidinger, D.; Jovancevic, N.; Zwanziger, D.; Theurer, S.; Hönes, J.; Führer, D.; Hatt, H. Functional Characterization of Olfactory Receptors in the Thyroid Gland. Front. Physiol. 2021, 12, 676907. [Google Scholar] [CrossRef] [PubMed]
  139. Abaffy, T. Human olfactory receptors expression and their role in non-olfactory tissues-a mini-review. J. Pharm. Pharm. 2015, 6, 1. [Google Scholar] [CrossRef]
  140. Mitsiades, C.S.; Hayden, P.; Kotoula, V.; McMillin, D.W.; McMullan, C.; Negri, J.; Delmore, J.E.; Poulaki, V.; Mitsiades, N. Bcl-2 Overexpression in Thyroid Carcinoma Cells Increases Sensitivity to Bcl-2 Homology 3 Domain Inhibition. J. Clin. Endocrinol. Metab. 2007, 92, 4845–4852. [Google Scholar] [CrossRef]
  141. Wang, Q.; Shen, Y.; Ye, B.; Hu, H.; Fan, C.; Wang, T.; Zheng, Y.; Lv, J.; Ma, Y.; Xiang, M. Gene Expression Differences between Thyroid Carcinoma, Thyroid Adenoma and Normal Thyroid Tissue. Oncol. Rep. 2018, 40, 3359–3369. [Google Scholar] [CrossRef] [PubMed]
  142. He, W.; Qi, B.; Zhou, Q.; Lu, C.; Huang, Q.; Xian, L.; Chen, M. Key Genes and Pathways in Thyroid Cancer Based on Gene Set Enrichment Analysis. Oncol. Rep. 2013, 30, 1391–1397. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  143. Rakhsh-Khorshid, H.; Samimi, H.; Torabi, S.; Sajjadi-Jazi, S.M.; Samadi, H.; Ghafouri, F.; Asgari, Y.; Haghpanah, V. Network Analysis Reveals Essential Proteins That Regulate Sodium-Iodide Symporter Expression in Anaplastic Thyroid Carcinoma. Sci. Rep. 2020, 10, 21440. [Google Scholar] [CrossRef] [PubMed]
  144. Cai, T.; Zhang, J.; Wang, X.; Song, R.; Qin, Q.; Muhali, F.; Zhou, J.; Xu, J.; Zhang, J. Gene-Gene and Gene-Sex Epistatic Interactions of DNMT1, DNMT3A and DNMT3B in Autoimmune Thyroid Disease. Endocr. J. 2016, 63, 643–653. [Google Scholar] [CrossRef] [Green Version]
  145. Kyono, Y.; Sachs, L.M.; Bilesimo, P.; Wen, L.; Denver, R.J. Developmental and Thyroid Hormone Regulation of the DNA Methyltransferase 3a Gene in Xenopus Tadpoles. Endocrinology 2016, 157, 4961–4972. [Google Scholar] [CrossRef]
  146. Coppedè, F. Epigenetics and Autoimmune Thyroid Diseases. Front. Endocrinol. 2017, 8, 149. [Google Scholar] [CrossRef] [Green Version]
  147. Zafon, C.; Gil, J.; Pérez-González, B.; Jordà, M. DNA Methylation in Thyroid Cancer. Endocr.-Relat. Cancer 2019, 26, R415–R439. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  148. Arakawa, Y.; Watanabe, M.; Inoue, N.; Sarumaru, M.; Hidaka, Y.; Iwatani, Y. Association of Polymorphisms in DNMT1, DNMT3A, DNMT3B, MTHFR and MTRR Genes with Global DNA Methylation Levels and Prognosis of Autoimmune Thyroid Disease. Clin. Exp. Immunol. 2012, 170, 194–201. [Google Scholar] [CrossRef] [PubMed]
  149. Cai, T.; Muhali, F.; Song, R.; Qin, Q.; Wang, X.; Shi, L.; Jiang, W.; Xiao, L.; Li, D.; Zhang, J. Genome-Wide DNA Methylation Analysis in Graves’ Disease. Genomics 2015, 105, 204–210. [Google Scholar] [CrossRef]
  150. Wojcicka, A.; Piekielko–Witkowska, A.; Kedzierska, H.; Rybicka, B.; Poplawski, P.; Boguslawska, J.; Master, A.; Nauman, A. Epigenetic Regulation of Thyroid Hormone Receptor Beta in Renal Cancer. PLoS ONE 2014, 9, e97624. [Google Scholar] [CrossRef] [PubMed]
  151. Lee, J.; Hwang, J.-A.; Lee, E.K. Recent Progress of Genome Study for Anaplastic Thyroid Cancer. Genomics Inform. 2013, 11, 68. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  152. Gobin, E.; Bagwell, K.; Wagner, J.; Mysona, D.; Sandirasegarane, S.; Smith, N.; Bai, S.; Sharma, A.; Schleifer, R.; She, J.-X. A Pan-Cancer Perspective of Matrix Metalloproteases (MMP) Gene Expression Profile and Their Diagnostic/Prognostic Potential. BMC Cancer 2019, 19, 581. [Google Scholar] [CrossRef] [Green Version]
  153. Rodrigues, R.F.; Roque, L.; Rosa-Santos, J.; Cid, O.; Soares, J. Chromosomal Imbalances Associated with Anaplastic Transformation of Follicular Thyroid Carcinomas. Br. J. Cancer 2004, 90, 492–496. [Google Scholar] [CrossRef] [Green Version]
  154. Bialek, J.; Kunanuvat, U.; Hombach-Klonisch, S.; Spens, A.; Stetefeld, J.; Sunley, K.; Lippert, D.; Wilkins, J.A.; Hoang-Vu, C.; Klonisch, T. Relaxin Enhances the Collagenolytic Activity and In Vitro Invasiveness by Upregulating Matrix Metalloproteinases in Human Thyroid Carcinoma Cells. Mol. Cancer Res. 2011, 9, 673–687. [Google Scholar] [CrossRef]
Figure 1. (a) The overlapping chromosomal regions with loss of heterozygosity in follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA). The first set shows LOH present only in follicular thyroid cancer, the second both in FTC and FTA, and the third shows LOH present only in FTA. Findings from the present study are in bold. Other regions (not in bold) were found in the literature [19,21,26,27,28,29,30,31,32]. (b) The most important genes included in overlapping chromosomal regions with loss of heterozygosity in follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA). * represents statistical significance at p < 0.05; # represents regions present only in FTC or in both FTC and FTA (the latter in our study).
Figure 1. (a) The overlapping chromosomal regions with loss of heterozygosity in follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA). The first set shows LOH present only in follicular thyroid cancer, the second both in FTC and FTA, and the third shows LOH present only in FTA. Findings from the present study are in bold. Other regions (not in bold) were found in the literature [19,21,26,27,28,29,30,31,32]. (b) The most important genes included in overlapping chromosomal regions with loss of heterozygosity in follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA). * represents statistical significance at p < 0.05; # represents regions present only in FTC or in both FTC and FTA (the latter in our study).
Cancers 15 00638 g001
Table 1. Patient characteristics according to histopathological diagnosis.
Table 1. Patient characteristics according to histopathological diagnosis.
CharacteristicsFollicular Thyroid Adenomas
n = 16
Follicular Thyroid Carcinomas
n = 16
p-Value 1
Male/female, n (%)2/14 (12.5%/87.5%)2/14 (12.5%/87.5%)1.000
Median age at diagnosis, years (range)53 (29–81)56 (31-82)0.649
Age group ≤60 years/>60 years), n (%)11/5 (68.8%/31.2%)10/6 (62.5%/37.5%)1.000
Median length of follow-up, months (range)119 (58–162)152 (47–174)0.587
Multifocality, n (%)02 (12.5%)0.4839
Capsule invasion, n (%)NA
7 (43.8%)NA
Extracapsular extension, n (%)NA
10 (62.5%)NA
Nodal (N) involvement, n (%)NA
1 (6.3%)NA
Mean tumor size, mm (range)23 (6–50)26 (8-50)0.112
Tumor diameter ≤10 mm, n (%)3 (18.8%)1 (6.3%)0.5996
Localization in the right/left/both lobes, n (%)9/7/0 (56.3%/43.7%)8/7/1 (50%/43.8%/6.2%)0.7222
Chronic lymphocytic thyroiditis, n (%) 2 (12.5%)3 (18.8%)1.000
Radioactive iodine refractoriness n (%) NA1 (6.3%)NA
1 The p-values were based on a chi-square test (or Fisher’s exact test where appropriate) for categorical variables and a Mann–Whitney U test for quantitative variables. NA—not applicable.
Table 2. LOHs present in both types of lesions or predominantly in FTA or FTC. Census genes detected in the LOH region are listed.
Table 2. LOHs present in both types of lesions or predominantly in FTA or FTC. Census genes detected in the LOH region are listed.
Chrom.Cytoband StartSize (kbp)Gene CountCensus GenesMicroarray
Nomenclature
FTCFTASump-ValueOR (95% CI)
LOHs present in both follicular thyroid carcinoma and follicular thyroid adenoma
16p12.17500.913149FUSarr[hg19] 16p12.1-p11.1(27,770,812–35,271,725) hmz1110210.7101.32 (0.31–5.70)
3p21.316391.659172SETD2, NCKIPSD,
RHOA, BAP1, PBRM1
arr[hg19] 3p21.31-p21.1(46,778,841–53,170,500) hmz97160.4811.65 (0.41–6.68)
15q15.13616.64170B2Marr[hg19] 15q15.1-q21.1(41,796,900–45,413,541) hmz95140.1592.82 (0.67–12.02)
LOHs present predominantly in follicular thyroid carcinoma:
12q24.113990.6559SH2B3, ALDH2, PTPN11arr[hg19] 12q24.11-q24.13(109,669,669–113,660,319) hmz6170.0579.00 (0.94–86.53)
LOHs present predominantly in follicular thyroid adenoma:
11p11.25404.54858CREB3L1, DDB2arr[hg19] 11p11.2-p11.12(46,171,403–51,575,951) hmz 0990.01441.80 (2.14–816.37)
20q11.216885.552125ASXL1, SRCarr[hg19] 20q11.21-q11.23(29,519,155–36,404,707) hmz1560.0996.82 (0.69–66.91)
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Borowczyk, M.; Dobosz, P.; Szczepanek-Parulska, E.; Budny, B.; Dębicki, S.; Filipowicz, D.; Wrotkowska, E.; Oszywa, M.; Verburg, F.A.; Janicka-Jedyńska, M.; et al. Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma—A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study. Cancers 2023, 15, 638. https://doi.org/10.3390/cancers15030638

AMA Style

Borowczyk M, Dobosz P, Szczepanek-Parulska E, Budny B, Dębicki S, Filipowicz D, Wrotkowska E, Oszywa M, Verburg FA, Janicka-Jedyńska M, et al. Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma—A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study. Cancers. 2023; 15(3):638. https://doi.org/10.3390/cancers15030638

Chicago/Turabian Style

Borowczyk, Martyna, Paula Dobosz, Ewelina Szczepanek-Parulska, Bartłomiej Budny, Szymon Dębicki, Dorota Filipowicz, Elżbieta Wrotkowska, Michalina Oszywa, Frederik A. Verburg, Małgorzata Janicka-Jedyńska, and et al. 2023. "Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma—A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study" Cancers 15, no. 3: 638. https://doi.org/10.3390/cancers15030638

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop