PFKFB2 Promoter Hypomethylation as Recurrence Predictive Marker in Well-Differentiated Thyroid Carcinomas

Abstract

Despite the low mortality rates, well-differentiated thyroid carcinomas (WDTC) frequently relapse. BRAF and TERT mutations have been extensively related to prognosis in thyroid cancer. In this study, the methylation levels of selected CpGs (5-cytosine-phosphate-guanine-3) comprising a classifier, previously reported by our group, were assessed in combination with BRAF and TERT mutations. We evaluated 121 WDTC, three poorly-differentiated/anaplastic thyroid carcinomas (PDTC/ATC), 22 benign thyroid lesions (BTL), and 13 non-neoplastic thyroid (NT) tissues. BRAF (V600E) and TERT promoter (C228T and C250T) mutations were tested by pyrosequencing and Sanger sequencing, respectively. Three CpGs mapped in PFKFB2, ATP6V0C, and CXXC5 were evaluated by bisulfite pyrosequencing. ATP6V0C hypermethylation and PFKFB2 hypomethylation were detected in poor-prognosis (PDTC/ATC and relapsed WDTC) compared with good-prognosis (no relapsed WDTC) and non-malignant cases (NT/BTL). CXXC5 was hypomethylated in both poor and good-prognosis cases. Shorter disease-free survival was observed in WDTC patients presenting lower PFKFB2 methylation levels (p = 0.004). No association was observed on comparing BRAF (60.7%) and TERT (3.4%) mutations and prognosis. Lower PFKFB2 methylation levels was an independent factor of high relapse risk (Hazard Ratio = 3.2; CI_95% = 1.1–9.5). PFKFB2 promoter methylation analysis has potential applicability to better stratify WDTC patients according to the recurrence risk, independently of BRAF and TERT mutations.

1. Introduction

Papillary (PTC) and follicular (FTC) thyroid carcinomas are the most prevalent thyroid tumors, designated as well-differentiated thyroid carcinomas (WDTC) [1]. Despite the high rates of recurrence, the majority of patients presents good prognosis, due to the low propensity for metastasis and excellent response to the conventional therapies [1]. Currently, clinical-pathological parameters used to predict the risk of relapse or mortality of WDTC patients are insufficient to accurately predict the disease progression [2,3,4]. The use of molecular approaches has the potential to reveal markers that can be used for risk stratification of these patients.

Papillary thyroid cancer harboring BRAF mutation is frequently described in patients with worse prognosis [5,6,7], mainly in older individuals [8]. However, the presence of this mutation is not enough to predict the risk of recurrence or death [9,10]. Recently, promoter mutations in the telomerase reverse transcriptase encoding gene (TERT) have been consistently associated with more aggressive thyroid carcinomas [11], especially in the presence of BRAF mutation [12,13]. TERT promoter mutation has been reported in approximately 9% of PTC and in higher frequency in poorly-differentiated thyroid carcinomas (PDTC) (40%) and anaplastic thyroid carcinomas (ATC) (>70%) [1]. Curiously, TERT promoter mutation is highly prevalent in advanced PTC (61% of the cases) and FTC (71%) [14]. This gene encodes the catalytic subunit of telomerase, a ribonucleoprotein complex that maintains the telomere length, playing an important role in the tumorigenesis and cellular immortality [15]. Two mutations in hot spots, C228T and C250T, mapped in the promoter region of this gene have been described in thyroid cancer [16].

In addition, the DNA methylation patterns have also been described with potential applicability in the prognosis of thyroid carcinomas [17,18,19,20,21]. At least two candidate markers of recurrence, RUNX3 hypermethylation [19] and TSHR hypomethylation [17], were reported in PTC patients. However, investigations of epigenetic prognostic markers in WDTC are poorly explored in the literature. Even though the recurrence may occur many years after the initial treatment [22,23], the thyroid cancer patients enrolled in these studies frequently have a follow-up period shorter than five years.

In a previous study of our group, a genome-wide DNA methylation profiling (Illumina 450k platform) was performed in 141 thyroid samples, including WDTC, PDTC/ATC, benign thyroid lesions (BTL), and non-neoplastic thyroid (NT) tissues [20]. A prognostic signature was designed based on 21 CpGs (5-cytosine-phosphate-guanine-3), achieving 63% of sensitivity and 92% of specificity to discriminate recurrent from non-recurrent WDTC patients. A “high-risk” prediction was considered as an independent marker of worse prognosis in the multivariate analysis, which was reproducible using the PTC cohort from The Cancer Genome Atlas (TCGA) database [20].

Herein, TERT promoter and BRAF mutations were genotyped, and three differentially methylated CpGs, included in the previous reported prognostic signature, were assessed by bisulfite pyrosequencing. The molecular data were compared with the WDTC patient’s outcome, which was followed-up during 10.6 years in the median.

2. Results

The study design and main results are summarized in Figure 1.

2.1. High Agreement between Global DNA Methylation and Bisulfite Pyrosequencing Results

High-quality the sequencing was obtained in 152, 146, and 159 samples for the CpGs mapped in the promoters of PFKFB2, ATPV6V0C, and CXXC5 genes, respectively. Methylation microarray and pyrosequencing were both performed in 42 samples, showing high positive correlation (PFKFB2 r = 0.768; ATPV6V0C r = 0.762; CXXC5 r = 0.881) (Figure S1).

2.2. PFKFB2 Hypomethylation in Thyroid Carcinomas in Poor Prognosis Patients

The methylation levels of the CpGs were compared in thyroid samples from patients with poor prognosis (PDTC/ATC and relapsed WDTC), good prognosis (WDTC without relapse), and non-neoplastic tissues (NT and BTL). PFKFB2 and CXXC5 were hypomethylated in both tumor groups compared to NT and BTL. Moreover, PFKFB2 methylation loss was more pronounced in poor prognosis cases. ATPV6V0C hypermethylation was observed in poor prognosis patients compared with good prognosis and non-neoplastic tissues (Figure 2A). PFKFB2 hypomethylation and ATPV6V0C hypermethylation were also detected in poor-prognosis WDTC (WDTC-PP) compared with good-prognosis WDTC (WDTC-GP) cases (p = 0.003 and p = 0.027, respectively) (Figure 2B). However, considering exclusively the microarray-independent WDTCs samples (N = 79), only PFKFB2 remained statistically significant (p = 0.031) (Figure S2).

2.3. Methylation Levels of PFKFB2 as Recurrence Predictor in WDTC

The predictive value of the CpGs methylation to discriminate WDTC-PP from WDTC-GP was tested verifying the area under the receiver operating characteristic curve (AUC) from our previous methylation microarray results [20], the TCGA methylation microarray database, and in samples from the current study assessed by bisulfite pyrosequencing (Figure S3). The PFKFB2 methylation level was a promising recurrence predictor marker (methylation microarray analysis: AUC = 0.797; TCGA database: AUC = 0.667; current study: AUC = 0.698).

2.4. Lower Methylation Level of PFKFB2 is an Independent Marker of High Risk of Recurrence in WDTC

Shorter disease-free survival was observed in WDTC patients showing decreased methylation levels of PFKFB2 (classified as below of the median) (Figure 3A). The BRAFV600E mutation was detected in 68 of 112 (60.7%) PTC samples and no increased risk of recurrence was verified (Figure 3B). High-quality results for TERT genotyping were obtained for 121 of 124 tumor samples. TERT promoter mutation was detected in two of three PDTC/ATC, and in four of 118 WDTC cases (3.4%) (three PTC and one FTC), showing no association with disease-free survival (Figure 3B).

Among the WDTC harboring TERT mutation, two PTC also presented BRAF mutation. In addition, hypomethylation of PFKFB2 (p < 0.001) and CXXC5 (p < 0.001) were associated with BRAF mutation (Figure S4). The multivariate analysis revealed PFKFB2 hypomethylation as an independent factor of high risk of relapse (Hazard Ratio = 3.2; CI_95% = 1.1–9.5) (

Table 1. Univariate and multivariate analyses of the comparison of clinical, pathological, and molecular characteristics of WDTC samples in relation to the risk of relapse.

Variable	Univariate Analysis		Multivariate Analysis
	HR (CI95%)	p	HR (CI95%)	p
Age
<55 years	1.0
≥55 years	0.48 (0.11–2.05)	0.325
Gender
Female	1.0		1.0
Male	3.63 (1.65–7.98)	0.001	1.89 (0.65–5.47)	0.242
Tumor Size (cm)
≤1 cm	1.0
>1 cm	1.69 (0.71–4.05)	0.239
Multicentricity
No	1.0		1.0
Yes	2.10 (0.95–4.63)	0.066	1.53 (0.58–4.05)	0.396
Histology
PTC	1.0
FTC	1.08 (0.25–4.57)	0.919
PTC Variant
Classic	1.0
Others	0.43 (0.13–1.43)	0.169
Extrathyroidal Extension
No	1.0		1.0
Yes	1.96 (0.89–4.31)	0.093	1.53 (0.41–5.61)	0.525
Lymph node Metastasis
No (cN0, pN0)	1.0		1.0
Yes (pN1)	4.19 (1.85–9.51)	<0.001	5.77 (0.64–52)	0.118
Risk stratification *
Low	1.0		1.0
Intermediate	2.49 (0.98–6.33)	0.055	0.35 (0.03–4.54)	0.419
High	6.08 (1.22–30.35)	0.028	0.35 (0.01–12.36)	0.563
BRAFV600E #
No	1.0		1.0
Yes	0.98 (0.42–2.26)	0.955	0.74 (0.27–2.02)	0.560
TERT C228T/C250T
No	1.0
Yes	1.21 (0.16–8.95)	0.854
CXXC5 Methylation
Below Median	1.22 (0.51–2.94)	0.658
Above Median	1.0
ATP6V0C Methylation
Below Median	1.0
Above Median	1.93 (0.85–4.36)	0.116
PFKFB2 Methylation
Below Median	3.85 (1.42–10.44)	0.008	3.17 (1.06–9.46)	0.038
Above Median	1.0		1.0

HR: hazard ratio; p: obtained from Cox regression model. CI_95%: 95% confidence interval; PTC: papillary thyroid carcinoma; FTC: follicular thyroid carcinoma; cN0: no clinical evidence of lymph nodes involvement; pN0: no pathologically evidence of lymph nodes involvement; pN1: pathological confirmation of lymph nodes involvement; * American Thyroid Association recurrence risk stratification [4]; # variable entered in the multivariate model, since an association with PFKFB2 methylation was detected; bold: significant p-value.

).

3. Discussion

We previously reported a DNA methylation signature composed of 21 CpGs which was capable of discriminating WDTC samples according to the clinical outcome (86% of accuracy). The reproducibility of this algorithm was corroborated using the TCGA-thyroid samples as an independent cohort of cases (82% accuracy) [20]. Here, three CpGs mapped in the gene promoters (PFKFB2, ATP6V0C, and CXXC5), included in this classifier, were selected to be evaluated by bisulfite pyrosequencing and to validate their potential to be used in the clinical practice.

The comparison between the DNA methylation values obtained by microarray and pyrosequencing analyses revealed high concordance (r > 0.75 for the three candidate markers tested). As expected, the same methylation pattern of PFKFB2, CXXC5 (tumor hypomethylation in relation to NT and BTL), and ATPV6V0C (tumor hypermethylation in comparison with NT and BTL) described in the microarray analysis and in the TCGA cross-study validation [20] was confirmed. Furthermore, WDTC-PP patients presented significantly ATP6V0C increased and PFKFB2 decreased CpGs methylation levels mapped in gene promoter. ATP6V0C encodes a component of vacuolar ATPase in a complex that regulates the acidification of eukaryotic intracellular organelles, playing a role in critical processes, zymogen activation, intracellular protein sorting, and endocytosis [24]. We integrated the methylation microarray and RNA sequencing data of 563 thyroid samples from TCGA (collected from UCSC Xena https://xenabrowser.net/datapages/—accessed in March 2019), and no significant association was found for ATP6V0C (Spearman correlation test r = 0.031; p = 0.459) (Figure S5). Nonetheless, an accurate prognostic marker could be a passenger alteration with no relevant biological function in a specific tumor type [25].

The CpG mapped in the PFKFB2 promoter was demonstrated to be a promising prognostic marker based on the association with shorter disease-free survival and decreased DNA methylation levels. PFKFB2 encodes a regulatory protein of the glycolytic pathway, which plays a role in the synthesis and degradation of fructose-2,6-bisphosphate [26]. PFKFB2 increased expression levels were associated with shorter overall survival in ovarian cancer, showing a direct association with the long non-coding LINC00092 [27]. These authors described that PFKFB2 is an independent prognostic marker (p = 0.036, HR = 1.36). Functional in vitro and in vivo assays demonstrated induction of anoikis and loss of invasiveness by PFKFB2 silencing [27]. PFKFB2 was also reported as a potential thyroid cancer diagnostic marker, being down-expressed in malignant compared to benign thyroid tissues [28]. The integrative analysis between PFKFB2 promoter methylation and gene expression from TCGA database (same parameter used to test ATP6V0C) revealed a significant positive correlation (r = 0.310; p < 0.001) (Figure S5). In addition, no association between PFKFB2 expression levels with disease-free survival was detected using the TCGA database (log rank test p = 0.288). Gene expression control is a multifaced process, involving not only DNA methylation but a combination of several other epigenetic mechanisms, including histone modifications and non-coding RNA targeting [29]. In line with this, we previously suggested that PFKFB2 is regulated by two miRNAs (hsa-miR-21 and hsa-miR-146b overexpression) that are putatively regulated by DNA hypomethylation [30]. These findings exemplify the complexity of the intercommunication among epigenetic mechanisms in gene expression regulation.

The BRAF V600E and TERT promoter mutations (C228T and C250T) have been extensively related to prognosis in thyroid cancer [6,7,8,11,12,13,31]. In our PTC cohort, 69 of the 113 cases (61% of frequency) presented BRAF mutation, a similar prevalence reported by other studies (50–70%) [32,33]. Overall, no difference in the relapse rate for patients harboring BRAF mutation was observed in our study.

TERT promoter mutations were detected in two of the three highly aggressive PDTC/ATC, in agreement with previous literature data [1,14]. However, this alteration was rare in our WDTC sample set, being detected in only 3.4% of the cases (four of the 118). A similar frequency was detected in WDTC-PP (one of 24 samples, 4.2%) and WDTC-GP (three of 94 WDTC-PP, 3.2%) cases. Therefore, the majority of patients showing recurrence were negative for TERT promoter mutations, and this marker failed to correctly predict the risk of recurrence in our cohort. The co-occurrence of TERT and BRAF mutations was observed in two PTC, and none of them relapsed.

Although our sample size was relatively small, the patients were carefully selected in a large period of follow-up (minimum of 5-years and median of 10.6 years). Of note, 65% (63 of 97) of the WDTC-GP patients were followed up for more than 10-years. Recurrence of WDTC has been described up to 43 years after the initial treatment [23]. However, the risk decreases in each subsequent year in the logarithmic trend, commonly occurring within the first five years [22].

Considering that BRAF mutation was detected in more than half of our PTC and most of the patients present indolent disease, other molecular mechanisms might be responsible for a more aggressive tumor phenotype. On the other hand, TERT promoter mutation is very uncommon in indolent WDTC and frequent in highly aggressive thyroid neoplasia. However, this alteration was not able to predict relapse in our WDTC cohort.

In conclusion, the DNA methylation analysis of PFKFB2 promoter is a potential tool to estimate the risk of recurrence in WDTC patients, which can be easily performed by a low-cost technique compatible to the clinical practice as bisulfite pyrosequencing.

4. Materials and Methods

4.1. Patients

A cohort of 121 snap-frozen post-surgical WDTC samples was retrospectively included in this study, being 42 previously evaluated by global DNA methylation analysis (array-dependent) and 79 independent samples [20] (

Table 2. Clinical and pathological features of well-differentiated thyroid carcinomas (WDTC) patients enrolled in the study.

Characteristics	Microarray Dependent		Microarray Independent
	N = 42	%	N = 79	%
Age
Median (interquartile range)	40.4 (31.4–49.9)		44.2 (34.5–51.0)
<55 years	35	83.3%	67	84.8%
≥55 years	7	16.7%	12	15.2%
Gender
Female	36	85.7%	54	68.4%
Male	6	14.3%	25	31.6%
Histology
PTC classic variant	28	66.7%	56	70.9%
PTC follicular variant	4	9.5%	15	19.0%
PTC rare variant	4	9.5%	5	6.3%
FTC	6	14.3%	3	3.8%
Tumor dimension (cm)
Median (interquartile range)	1.3 (0.9–1.9)		1.4 (1.0–2.2)
≤1 cm	15	35.7%	31	39.2%
>1 cm	27	64.3%	48	60.8%
Multicentricity
No	32	76.2%	42	53.2%
Yes	10	23.8%	37	46.8%
Extrathyroidal extension
No	27	64.3%	48	60.8%
Yes	15	35.7%	31	39.2%
Lymph node metastasis
No (cN0, pN0)	26	61.9%	53	67.1%
Yes (pN1)	16	38.1%	26	32.9%
Risk stratification *
Low	16	38.1%	36	45.6%
Intermediate	23	54.8%	42	53.2%
High	3	7.1%	1	1.3%
Clinical evolution
Free of disease	35	83.3%	61	77.2%
Relapsed	7	16.7%	18	22.8%

PTC: papillary thyroid carcinoma; FTC: follicular thyroid carcinoma; cN0: no clinical evidence of lymph node involvement; pN0: no pathological evidence of lymph node involvement; pN1: pathological confirmation of lymph node involvement; * American Thyroid Association recurrence risk stratification [4].

and Table S1).

Additionally, three highly aggressive carcinomas (one PDTC and two ATC), 22 benign lesions, and 13 non-neoplastic thyroid tissues were included in this study. The patients were submitted to surgical procedures from 2001 to 2013 at A.C. Camargo Cancer Center, São Paulo, Brazil. The Institutional Human Research Ethics Committee of the Antonio Prudente Foundation at the A.C. Camargo Cancer Center approved the study (Protocol #2327-17, 21 February 2017). The study was conducted in accordance with the Helsinki Declaration.

Well-differentiated thyroid carcinoma patients classified as having “good-prognosis” (WDTC-GP) included those with no active disease (normal serum thyroglobulin measurement and imaging tests) during at least five years of follow-up (N = 96). “Poor-prognosis” patients (WDTC-PP) included cases with local recurrence (confirmed by imaging tests or histopathological analysis) or distant metastasis during the follow-up (N = 25).

Patients with incomplete clinical and pathological data, presenting the previous history of malignant tumors and relapsed after partial thyroidectomy or inadequate Thyroid-Stimulating Hormone (TSH) suppression, were excluded from the study.

4.2. Sample Processing, DNA Extraction, and Detection of BRAF and TERT Mutation

Samples were macrodissected, and DNA was isolated using conventional phenol-chloroform protocol and quantified by Qubit^® dsDNA BR Assay no Qubit^® 2.0 Fluorometer (Life Technologies, Carlsbad, CA, USA), as previously described [20].

BRAF V600E mutation was investigated exclusively in PTC samples by pyrosequencing using a threshold of 10% of altered alleles, as previously described [34]. The TERT promoter mutations, C228T and C250T (positions 124 and 146 base pairs upstream of the ATG site, respectively) were evaluated by direct Sanger sequencing after the amplification of the target regions (Forward primer: 5′CACCCGTCCTGCCCCTTCACCTT′3; Reverse primer: 5′GGCTTCCCACGTGCGCAGCAGGA′3), as previously described [35]. The amplification reaction was performed with HotStart Taq DNA polymerase (Qiagen, Valencia, CA, USA) and purified with ExoSAP-IT (USB Corporation, Cleveland, Ohio, USA). The sequencing reaction (reverse strand) was performed using ABI Prism BigDye Terminator Kit (Applied Biosystems, Foster City, CA, USA) in an ABI 3130xl DNA sequencer (Applied Biosystems, Foster City, CA, USA). The sequences were aligned using CLCBio Genomics Workbench Software (CLCbio’s, Aarhus, Denmark). Mutations were further confirmed by repeating the sequencing in both directions (forward and reverse).

4.3. Bisulfite Pyrosequencing for DNA Methylation Analysis

Three (cg02710090, cg05884711, and cg19628988) of 21 promoter CpGs differentially methylated probes, detected in WDTC-PP compared to WDTC-GP, were selected based on our previous study [20]. These three probes presented the highest AUC and were validated in the TCGA database analysis (Δβ between WDTC-PP and WDTC-GP >0.1 or <−0.1) (Table S2).

The DNA was denatured and treated with sodium bisulfite using the EZ DNA Methylation-Gold™ Kit (Zymo Research, Irvine, CA, USA), according to the manufacturer’s recommendations. The PCR followed by pyrosequencing was carried out as previously reported [34]. The primer sequences used were: PFKFB2 (forward: 5′AGGTGGTGGTAGTGTAAGGA3′; reverse: 5′GAGAGGGTAATTTAGAGTATTTTGGGAG3′; sequencing 5′TTGAATTTTAAAGTA3′), CXXC5 (forward 5′GGTAGGATTAGTTTAGGAGA3′; reverse 5′CTTCTAAAACACCACATAAAAAC3′; sequencing 5′TAGAGTGTATATTT3′), and ATP6V0C (forward 5′GGTTTTGAAGGTGTAGGTTTTG3′; reverse 5′CCACACCTATAAAATCCCAACC3′; sequencing 5′AGGTAGAGATAGGTG3′). Pyrosequencing reactions were assembled using the PSQ Vacuum Prep Tool (Qiagen) and sequenced at PSQ HS 96A Pyrosequencer (Qiagen) using Pyromark Gold Q96 (Qiagen).

4.4. Data Analysis

Statistical analysis was performed using SPSS (SPSS v. 21.0, Chicago, IL, USA) and GraphPad Prism 5.0 (GraphPad Software Inc., La Jolla, CA, USA). Microarray and bisulfite pyrosequencing methylation values were compared using Spearman’s correlation test. The sample groups were compared using Kruskal-Wallis (Dunn’s post-hoc) and Mann Whitney test. The performance of the methylation markers in discriminate WDTC-PP from WDTC-GP was verified by the AUC. Disease-free survival analysis was performed using the Kaplan-Meier estimator and log-rank test. Cox Proportional-Hazards Model was applied to perform the univariate and multivariate analyses (p < 0.10 in univariate analysis was fitted in the multivariate model). The null hypothesis was rejected with two-tailed p < 0.05.