TERT promoter mutations and long-term survival in patients with thyroid cancer

in Endocrine-Related Cancer

TERT promoter mutations are emerging prognostic biomarkers in multiple cancers and are found in highly aggressive thyroid cancer. Our aim is to investigate the prognostic value of these mutations for the outcome of thyroid cancer-related mortality in a large cohort of thyroid cancer patients. This was a retrospective study of 409 patients (393 with differentiated thyroid cancer) with a median age of 44 years (range 16–81 years) and median follow-up of 13 years (interquartile range 11–16 years). Analyses of associations between mutational status and various clinicopathological variables were performed. TERT promoter mutations were identified in 32 (9.8%) papillary, 11 (16.7%) follicular and seven (43.8%) poorly differentiated/anaplastic thyroid cancer patients. The presence of TERT promoter mutations was associated with factors such as increased age (P < 0.001), extrathyroidal invasion (P = 0.01), increased stage at diagnosis (P < 0.001) and dedifferentiated histological type (P = 0.001). A TERT promoter mutation was independently associated with poorer overall survival in patients with differentiated thyroid cancer (10-year survival rate, 66.2% vs 98.3% for wild type; adjusted HR, 7.18; 95% CI: 2.77–18.59) and in patients with papillary cancer (74.2% vs 99.3%; 14.20; 3.03–66.68). Concomitant TERT and BRAF mutations worsened the survival rate of patients with papillary cancer (82.6% vs 99.4% for exclusively BRAF mutation alone; 5.62; 1.85–17.09). In conclusion, the presence of TERT promoter mutations is independently associated with increased mortality in patients with differentiated thyroid cancer. The results suggest that inclusion of TERT promoter mutation analysis with conventional clinicopathological evaluation can lead to better prognostication and management for individual patients.

Abstract

TERT promoter mutations are emerging prognostic biomarkers in multiple cancers and are found in highly aggressive thyroid cancer. Our aim is to investigate the prognostic value of these mutations for the outcome of thyroid cancer-related mortality in a large cohort of thyroid cancer patients. This was a retrospective study of 409 patients (393 with differentiated thyroid cancer) with a median age of 44 years (range 16–81 years) and median follow-up of 13 years (interquartile range 11–16 years). Analyses of associations between mutational status and various clinicopathological variables were performed. TERT promoter mutations were identified in 32 (9.8%) papillary, 11 (16.7%) follicular and seven (43.8%) poorly differentiated/anaplastic thyroid cancer patients. The presence of TERT promoter mutations was associated with factors such as increased age (P < 0.001), extrathyroidal invasion (P = 0.01), increased stage at diagnosis (P < 0.001) and dedifferentiated histological type (P = 0.001). A TERT promoter mutation was independently associated with poorer overall survival in patients with differentiated thyroid cancer (10-year survival rate, 66.2% vs 98.3% for wild type; adjusted HR, 7.18; 95% CI: 2.77–18.59) and in patients with papillary cancer (74.2% vs 99.3%; 14.20; 3.03–66.68). Concomitant TERT and BRAF mutations worsened the survival rate of patients with papillary cancer (82.6% vs 99.4% for exclusively BRAF mutation alone; 5.62; 1.85–17.09). In conclusion, the presence of TERT promoter mutations is independently associated with increased mortality in patients with differentiated thyroid cancer. The results suggest that inclusion of TERT promoter mutation analysis with conventional clinicopathological evaluation can lead to better prognostication and management for individual patients.

Introduction

Thyroid cancer is the most common endocrine malignancy, and its prevalence is increasing worldwide (Chen et al. 2009). In the USA, the 10-year overall survival rates for papillary thyroid cancer (PTC), follicular thyroid cancer (FTC) and poorly differentiated/anaplastic thyroid cancer (PDTC/ATC) are approximately 93, 85 and 14%, respectively (Hundahl et al. 1998). Given the increased likelihood of long-term survival in patients with differentiated thyroid cancer, it is important to distinguish patients who need aggressive treatment to reduce mortality from those who do not. Several clinicopathological prognostic variables have been used to stratify cancer patients, including increased age, histological type, tumor size, direct local tumor invasion, lymph node metastasis and distant metastasis (DeGroot et al. 1990, Mazzaferri & Kloos 2001). These conventional risk factors, alone or in combination as a component of staging system (Hay et al. 1993, Edge et al. 2010), imperfectly predict the final outcome of each individual patient.

Recently, molecular marker-based risk stratification of thyroid cancer has been proposed to better estimate the risk (Xing et al. 2013b). The v-Raf murine sarcoma viral oncogene homolog B (BRAF) T1799A mutation has drawn much attention based on its high prevalence, occurring in about 45% of PTC and 25% of ATC cases and its association with PTC recurrence (Kim et al. 2012, Xing et al. 2015). However, many clinicians note that the mutation is common, whereas thyroid cancer-related mortality in patients with PTC is low. In a large multicenter study of 1849 patients with PTC, the BRAF T1799A mutation was associated with an increased cancer-related mortality, but it was no longer significant after the adjustment of risk factors, such as lymph node metastasis, extrathyroidal invasion and distant metastasis (Xing et al. 2013a).

In 2013, recurrent point mutations were found in the telomerase reverse transcriptase (TERT) promoter in 71% of melanoma genomes, and these somatic mutations enhanced promoter activity by two- to four-fold (Horn et al. 2013, Huang et al. 2013), which might immortalize proliferative cancer cells by maintaining telomere length (Vinagre et al. 2014). Starting with the seminal work of Liu and coworkers (2013), the importance of these findings has been reinforced in thyroid cancer by the association of mutations with tumor aggressiveness, early recurrence and even patient mortality (Melo et al. 2014, Xing et al. 2014a,b, Song et al. 2015). This potential prognostic marker is very promising, but its relationship to the long-term survival of patients with thyroid cancer requires further study. Currently, none of the mortality risk systems takes molecular testing results into consideration. It is still unclear if patients with TERT promoter-mutated thyroid cancer should be managed differently than those with wild-type tumor. The goal of our study is to investigate the association of TERT promoter mutations with thyroid cancer-specific survival to lead to more informed decisions and better management of thyroid cancer.

Subjects and methods

Patients and clinicopathological data

The Institutional Review Board at Samsung Medical Center, Seoul, Korea, approved the study protocol and the use of human thyroid tissue. This study included 409 patients with thyroid cancer. All patients were treated with initial thyroidectomy (398 total or near-total thyroidectomy and 11 less than total thyroidectomy) and therapeutic neck dissection from October 1994 to December 2004. All patients received standard thyrotropin suppression, and 376 of them received radioiodine ablation as guided by standard criteria (Cooper et al. 2006, 2009). Sample characteristics obtained from medical records are presented in Table 1. Thyroid cancer samples were obtained from the tissue archives of the Department of Pathology of the Samsung Medical Center. Only one sample per individual was included. All mutational analyses were performed after surgical and radioiodine treatment of patients, and the test results did not affect the decision-making process of the acting physician. Thyroid cancer-related mortality, based on the date of registration of death where the primary cause of death was thyroid cancer, was obtained from the Korea National Statistical Office and hospital medical records.

Table 1

Summary of clinical and genetic characteristics of 409 thyroid cancer patients.

CharacteristicN (%)
Sex
 Female 339 (82.9)
 Male 70 (17.1)
Age (years)
 Median 44
 Range 16–81
 <45 226 (55.3)
 ≥45 183 (44.7)
TERT promoter mutations
 WT 359 (87.8)
 228 C>T 46 (11.2)
 250 C>T 4 (1.0)
BRAF mutation
 WT 121 (29.6)
 1799 T>A 202 (49.4)
 Missing data 86 (21.0)
Histological type
 PTC 327 (80.0)
 FTC 66 (16.1)
 PDTC/ATC 16 (3.9)
Multifocality
 Absent 299 (73.1)
 Present 110 (26.9)
Lymph node metastasis
 Absent 206 (50.4)
 Present 201 (49.1)
 Missing data 2 (0.5)
Extrathyroidal invasion
 Absent 111 (27.1)
 Present 248 (60.6)
 Missing data 50 (12.2)
Distant metastasis
 Absent 384 (93.9)
 Present 25 (6.1)
Stage at diagnosisa
 I 222 (54.3)
 II 26 (6.4)
 III 103 (25.2)
 IV 58 (14.2)
Tumor size
 Median 2.8
 Range 0.4–13.0
 <2.0 cm 45 (11.0)
 2.0–4.0 cm 302 (73.8)
 >4.0 cm 62 (15.2)

BRAF, v-Raf murine sarcoma viral oncogene homolog B; FTC, follicular thyroid cancer; PDTC/ATC, poorly differentiated/anaplastic thyroid cancer; PTC, papillary thyroid cancer; TERT, telomerase reverse transcriptase.

Staging according to the American Joint Committee on Cancer (AJCC) Thyroid Cancer Staging System 2009 (Edge et al. 2010).

DNA isolation from thyroid cancer samples

Tumor cells with a percentage greater than 75% were dissected under microscopy from 4 μm unstained sections by comparison with hematoxylin- and eosin-stained slides according to a standard protocol (Kim et al. 2014). Genomic DNA was extracted using a Qiagen DNA FFPE Tissue Kit (Qiagen) according to the manufacturer’s instructions.

Detection of TERT promoter mutations

Semi-nested polymerase chain reaction (PCR) was carried out to identify TERT promoter mutations (Sohn et al. 2016). First-round PCR was performed using primers TERT-F and TERT-236-R as described previously (Liu et al. 2013). The 235 bp-sized PCR amplicon was subjected to second-round PCR using primers TERT-F and TERT-163-R (Horn et al. 2013). The primer sequences for TERT mutations are presented in Supplementary Table 1, see section on supplementary data given at the end of this article. PCRs were performed using a GeneAmp PCR system 9700 thermal cycler (Applied Biosystems). Cycle sequencing was performed using Big Dye Terminator Cycle Sequencing Ready Reaction kits (Applied Biosystems) on an ABI 3730xl Genetic Analyzer (Applied Biosystems).

Detection of BRAF T1799A mutation

Mutant enrichment with 3′-modified oligonucleotides-PCR (MEMO-PCR) and direct sequencing were performed as described previously (Lee et al. 2012). The obtained sequences were analyzed using the Sequencher program (Gene Codes Corp, Ann Arbor, MI, USA) and compared with a reference sequence (GenBank accession number NM_004333.4).

Target exome sequencing (including TERT promoter and BRAF)

Genomic DNA (250 ng) was sheared by Covaris S220 (Covaris, Woburn, MA, USA) and was used for the construction of a library using targeted exome sequencing (CancerSCAN) probes and SureSelect XT reagent kit, HSQ (Agilent Technologies) according to the manufacturers’ protocols. CancerSCAN probes cover the TERT promoter region and whole exons of 381 genes, including BRAF. After enriched exome libraries were multiplexed, the libraries were sequenced on HiSeq 2500 sequencing platform (Illumina, San Diego, CA, USA). Briefly, a paired-end DNA sequencing library was prepared through genomic DNA shearing, end-repair, A-tailing, paired-end adaptor ligation and amplification. After hybridization of the library with bait sequences for 16 h, the captured library was purified and amplified with an index barcode tag, and the library quality and quantity were measured. Sequencing of the exome library was carried out using the 100 bp paired-end mode of the TruSeq Rapid PE Cluster kit and TruSeq Rapid SBS kit (Illumina).

Statistical analysis

We used univariate logistic regression analyses to evaluate the association of TERT promoter mutation status with conventional clinical and pathological variables (Table 2). We investigated the association between clinicopathological variables, TERT and BRAF mutation status with thyroid cancer-specific survival, defined as the time from the initial surgical treatment to thyroid cancer-related mortality. Cases in which the end point was not reached at the time of the last follow-up were censored.

Table 2

Association of TERT mutation status with clinicopathological variables in 409 thyroid cancer patients.

VariablesTERT WT (N (%))TERT mut (N (%))TotalORa (95% CI)P value
Sex
 Female297 (87.6)42 (12.4)3391.00 (referent)0.82
 Male62 (88.6)8 (11.4)700.91 (0.41–2.04)
Age
 Per 5 year4091.96 (1.64–2.36)<0.001
 <45222 (98.2)4 (1.8)2261.00 (referent)<0.001
 ≥45137 (74.9)46 (25.1)18318.64 (6.56–52.92)
BRAF mutation
 WT109 (90.1)12 (9.9)1211.00 (referent)0.43
 Mutant176 (87.1)26 (12.9)2021.34 (0.65–2.77)
 Missing data74 (86.0)12 (14.0)86
Histological type
 PTC295 (90.2)32 (9.8)3271.00 (referent)0.001
 FTC55 (83.3)11 (16.7)661.84 (0.88–3.88)
 PDTC/ATC9 (56.3)7 (43.8)167.17 (2.50–20.55)
Multifocality
 Absent263 (88.0)36 (12.0)2991.00 (referent)0.85
 Present96 (87.3)14 (12.7)1101.07 (0.55–2.06)
Lymph node metastasis
 Absent184 (89.3)22 (10.7)2061.00 (referent)0.39
 Present174 (86.6)27 (13.4)2011.30 (0.71–2.36)
 Missing data1 (50.0)1 (50.0)2
Extrathyroidal invasion
 Absent105 (94.6)6 (5.4)1111.00 (referent)0.01
 Present211 (85.1)37 (14.9)2483.07 (1.26–7.50)
 Missing data43 (86.0)7 (14.0)50
Distant metastasis
 Absent342 (89.1)42 (10.9)3841.00 (referent)0.003
 Present17 (68.0)8 (32.0)253.83 (1.56–9.42)
Stage at diagnosisb
 I216 (97.3)6 (2.7)2221.00 (referent)<0.001
 II25 (96.2)1 (3.8)261.44 (0.17–12.45)
 III91 (88.3)12 (11.7)1034.75 (1.73–13.04)
 IV27 (46.6)31 (53.4)5841.33 (15.80–108.10)
Tumor size
 <2.0 cm41 (91.1)4 (8.9)451.00 (referent)0.08
 2.0–4.0 cm269 (89.1)33 (10.9)3021.26 (0.42–3.73)
 >4.0 cm49 (79.0)13 (21.0)622.72 (0.82–8.98)

BRAF, v-Raf murine sarcoma viral oncogene homolog B; FTC, follicular thyroid cancer; PDTC/ATC, poorly differentiated/anaplastic thyroid cancer; PTC, papillary thyroid cancer; TERT, telomerase reverse transcriptase.

The odds ratio (OR) represents the odds for being a TERT promoter mutation carrier as compared with a TERT promoter wild-type carrier; bStaging according to the American Joint Committee on Cancer (AJCC) Thyroid Cancer Staging System 2009 (Edge et al. 2010).

Survival analyses were focused on patients with differentiated thyroid cancer (PTC and FTC) because PDTC/ATC is uncommon and highly lethal. Univariate results were displayed using the Kaplan–Meier method, and hazard estimates and P values were calculated from Cox proportional hazard models. For univariate analyses of BRAF mutation, we used only cases with BRAF mutation status available. Because the effect of BRAF mutation was not significant in the univariate analyses, BRAF mutation was not included in multivariate analyses.

As ‘Stage at diagnosis’ is a composite variable, we decided to separate the variable into its components (‘Age’, ‘Extrathyroidal invasion’, ‘Distant metastasis’ and ‘Tumor size’) in some of the multivariate analyses. In the extended model, all main effects with univariate P values less than 0.20, except ‘Stage at diagnosis’, were evaluated simultaneously (Tables 3 and 4, model 1). In the restricted model, the ‘Stage at diagnosis’ variable replaced its components to avoid overfitting (Tables 3 and 4, model 2). The model diagnostic included both graphical and formal Schoenfeld residual checks of the proportional hazards assumptions (Harrell et al. 1996). We conducted a sensitivity analysis by applying a backward elimination approach to a multivariate Cox regression including all the univariate explanatory variables.

In addition, we performed subgroup analysis for patients with PTC, the most common histological type. All P values were two sided, and a P value < 0.05 was treated as statistically significant. All statistical analyses were performed using SPSS statistical software (version 21.0; SPSS).

Results

Clinical evaluation

In total, 421 thyroid cancer samples were screened for the study. The further analyzed cohort consisted of samples from 409 patients whose TERT promoter sequencing of tumor DNA was successful. There were 339 women and 70 men with a median age of 44 years (range 16–81 years) and a median follow-up duration of 13 years (interquartile range 11–16 years). There were cumulative deaths in 5.5% (18/327) of PTC, 18.2% (12/66) of FTC and 75.0% (12/16) of PDTC/ATC patients. Most of these deaths were related to thyroid cancer. Specifically, 4.9% (16/327) of PTC, 15.2% (10/66) of FTC and 75.0% (12/16) of PDTC/ATC cases resulted in a thyroid cancer-related death. The baseline clinical data and mutation status of the tumors are presented in Table 1.

Mutational analysis

The TERT promoter was successfully PCR amplified and sequenced in 409 patients (327 PTC, 66 FTC and 16 PDTC/ATC). Recurrent mutations were located at previously described hotspots: chr.5:1,295,228C>T and chr.5:1,295,250C>T. The TERT promoter region showed mutant reads in 9.8% (32/327) of PTC, 16.7% (11/66) of FTC and 43.8% (7/16) of PDTC/ATC patients: the majority of the mutations were 228 C>T, and 250 C>T was found in three PTC and one FTC patients. Sequencing for BRAF was successful in 323 (79.0%) patients. The BRAF T1799A mutation was observed in 75.4% (199/264) of PTC, 0% (0/52) of FTC and 42.9% (3/7) of PDTC/ATC patients. For validation of the TERT promoter and BRAF genotyping results, we also performed high-coverage cancer panel sequencing in a randomly selected subset of TERT promoter mutation-positive (n = 2) and -negative cases (n = 8). The results obtained by two different methods were identical in all selected cases (Supplementary Fig. 1A, B and Supplementary Table 2).

Association of TERT promoter mutation status with clinicopathological variables

TERT promoter mutations were significantly more common in older patients (P < 0.001), in tumors with extrathyroidal invasion (P = 0.01), in cases with distant metastasis (P = 0.003) and with increased stage at diagnosis (P < 0.001) (Table 2). The TERT mutation frequencies differed among histological type (9.8% in PTC, 16.7% in FTC and 43.8% in PDTC/ATC; P = 0.001 for the frequency difference). Separate data for patients with differentiated thyroid cancer are presented in Supplementary Table 3. In patients with PTC, the largest subgroup, TERT promoter mutations were more common in the mutant BRAF than the wild type (12.1% (24/199) vs 3.1% (2/65); P = 0.03).

Association of TERT promoter mutation status and clinicopathological variables with thyroid cancer-related mortality

Survival analyses were performed for patients with differentiated thyroid cancer (Fig. 1A and Table 3) and for patients with PTC (Fig. 1B and Table 4). In differentiated thyroid cancer patients (Table 3), univariate predictors of survival were TERT promoter mutation status (P < 0.001), patient age (P < 0.001), histological type (poorer in FTC compared with PTC; P = 0.002), distant metastasis (P < 0.001), stage at diagnosis (P < 0.001) and tumor size (P = 0.03). Patients with mutant TERT promoter tumors showed worse prognosis (10-year survival rate of 66.2%, compared with 98.3% for wild-type tumors). In multivariate analysis, however, the adjusted HRs (95% CI) were differently estimated according to variable selection strategy (5.19 (1.87–14.44), P = 0.002 for the extended model; 7.18 (2.77–18.59), P < 0.001 for the restricted model). In addition, patient age, histological type, extrathyroidal invasion, stage at diagnosis and tumor size were independent factors.

Figure 1
Figure 1

Kaplan–Meier curves of thyroid cancer-specific survival by TERT mutational status. Results from the analysis of patients with (A) differentiated thyroid cancer and (B) papillary thyroid cancer. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0219.

Citation: Endocrine-Related Cancer 23, 10; 10.1530/ERC-16-0219

Table 3

Association of TERT mutation status and clinicopathological variables with thyroid cancer-specific survival in 393 differentiated thyroid cancer patients.

Univariate Cox modelsMultivariate Cox model 1b (extended model)Multivariate Cox model 2c (restricted model)
VariablesNa10-year survival rate (%)HR (95% CI)P valueHR (95% CI)P valueHR (95% CI)P value
Sex
 Female32995.41.00 (referent)0.31
 Male6492.01.60 (0.64–3.99)
Aged
 Per 5 year3931.76 (1.60–1.92)<0.0011.51 (1.30–1.72)<0.001
 <4522399.11.00 (referent)<0.001
 ≥4517089.317.23 (4.07–72.95)
TERT mutations
 WT35098.31.00 (referent)<0.0011.00 (referent)0.0021.00 (referent)<0.001
 Mutant4366.223.26 (10.10–53.56)5.19 (1.87–14.44)7.18 (2.77–18.59)
BRAF mutation
 WT11792.31.00 (referent)0.28
 Mutant19997.50.60 (0.24–1.51)
Histological type
 PTC32796.91.00 (referent)0.0021.00 (referent)0.0041.00 (referent)<0.001
 FTC6684.83.24 (1.47–7.15)9.27 (2.06–41.72)4.94 (2.09–11.68)
Multifocality
 Absent28694.71.00 (referent)0.98
 Present10795.30.99 (0.42–2.36)
Lymph node metastasis
 Absent19994.41.00 (referent)0.91
 Present19395.30.96 (0.44–2.10)
Extrathyroidal invasion
 Absent10898.11.00 (referent)0.111.00 (referent)0.04
 Present23994.92.70 (0.79–9.22)5.16 (1.06–24.99)
Distant metastasis
 Absent37396.51.00 (referent)<0.0011.00 (referent)0.23
 Present2065.08.66 (3.63–20.64)1.89 (0.67–5.31)
Stage at diagnosise
 I21899.11.00 (referent)<0.0011.00 (referent)0.003
 II2692.38.18 (1.15–58.11)4.58 (0.63–33.33)
 III10397.16.92 (1.40–34.32)6.53 (1.26–33.84)
 IV4671.047.09 (10.81–205.09)18.28 (3.58–93.25)
Tumor size
 <2.0 cm4595.41.00 (referent)0.031.00 (referent)0.04
 2.0–4.0 cm29396.21.20 (0.28–5.23)0.72 (0.16–3.37)
 >4.0 cm5587.03.58 (0.76–16.84)2.52 (0.49–13.14)

BRAF, v-Raf murine sarcoma viral oncogene homolog B; FTC, follicular thyroid cancer; PTC, papillary thyroid cancer; TERT, telomerase reverse transcriptase.

The number of available data for a particular variable in the univariate analysis

Extended model in which all predictors with univariate P values ≤ 0.20, except ‘Stage at diagnosis’, are included; no interactions were considered

Restricted model that includes ‘TERT mutations’, ‘Histological type’ and ‘Stage at diagnosis’; no interactions were considered

Multivariate Cox regression analysis results for ‘Age’ are analyzed and presented for the continuous linear variable

Staging according to the American Joint Committee on Cancer (AJCC) Thyroid Cancer Staging System 2009 (Edge et al. 2010).

Table 4

Association of TERT mutation status and clinicopathological variables with thyroid cancer-specific survival in 327 papillary thyroid cancer patients.

Univariate Cox modelsMultivariate Cox model 1b (extended model)Multivariate Cox model 2c (restricted model)
VariablesNa10-year survival rate (%)HR (95% CI)P valueHR (95% CI)P valueHR (95% CI)P value
Sex
 Female27697.81.00 (referent)0.071.00 (referent)0.561.00 (referent)0.21
 Male5192.02.62 (0.91–7.56)1.50 (0.38–5.99)2.00 (0.68–5.84)
Aged
 Per 5 year3271.74 (1.54–1.94)<0.0011.33 (1.06–1.59)0.04
 <4518798.91.00 (referent)0.002
 ≥4514094.210.21 (2.32–44.99)
TERT mutations
 WT29599.31.00 (referent)<0.0011.00 (referent)0.0011.00 (referent)0.001
 Mutant3274.233.38 (10.76–103.61)10.78 (2.67–43.51)14.20 (3.03–66.68)
BRAF mutation
 WT6598.51.00 (referent)0.28
 Mutant19997.53.12 (0.39–24.60)
Multifocality
 Absent22897.31.00 (referent)0.50
 Present9995.91.41 (0.51–3.89)
Lymph node metastasis
 Absent13697.81.00 (referent)0.48
 Present19096.31.47 (0.50–4.30)
Extrathyroidal invasion
 Absent73100.01.00 (referent)0.131.00 (referent)0.27
 Present23395.74.85 (0.64–36.72)3.45 (0.39–30.66)
Distant metastasis
 Absent31497.41.00 (referent)0.091.00 (referent)0.78
 Present1384.63.66 (0.83–16.13)1.32 (0.19–8.93)
Stage at diagnosise
 I17898.91.00 (referent)<0.0011.00 (referent)0.64
 II17100.0NANA
 III9598.94.14 (0.76–22.62)2.04 (0.31–13.35)
 IV3780.427.94 (6.12–127.64)3.61 (0.47–27.47)
Tumor size
 <2.0 cm3597.11.00 (referent)0.201.00 (referent)0.14
 2.0–4.0 cm25397.61.46 (0.19–11.32)0.84 (0.10–6.82)
 >4.0 cm3992.13.91 (0.44–35.03)3.37 (0.34–33.73)

BRAF, v-Raf murine sarcoma viral oncogene homolog B; TERT, telomerase reverse transcriptase.

The number of available data for a particular variable in the univariate analysis

Extended model in which all predictors with univariate P values ≤ 0.20, except ‘Stage at diagnosis’, are included; no interactions were considered

Restricted model that includes ‘Sex’, ‘TERT mutations’ and ‘Stage at diagnosis’; no interactions were considered

Multivariate Cox regression analysis results for ‘Age’ are analyzed and presented for the continuous linear variable

Staging according to the American Joint Committee on Cancer (AJCC) Thyroid Cancer Staging System 2009 (Edge et al. 2010).

In patients with PTC (Table 4), factors that were significantly associated with poorer survival in univariate analyses included TERT promoter mutations (P < 0.001), increased age (P < 0.001) and increased stage at diagnosis (in particular stage IV, compared with lower stage; P < 0.001). Multivariate analysis showed that TERT promoter mutations (P = 0.001) and increased age (P = 0.04) were independently associated with poorer survival. In the restricted model, the estimated adjusted HR (95% CI) was 14.20 (3.03–66.68) for the mutant TERT promoter compared with the wild type, and stage at diagnosis was no longer a significant predictor of survival.

In a sensitivity analysis with backward elimination approach, the models included TERT mutations that are presented in Table 3 (TERT mutations with histological type and extrathyroidal invasion) and also in Table 4 (TERT mutations only). HRs for TERT mutations were 14.33 (4.81–42.71) and 39.47 (8.38–185.99) (Tables 3 and 4). Although these HRs differed from those in other models, they were contained within 95% CIs of HR in all other models; and their 95% CIs contained HRs in all other models.

For patients with PTC, we performed stratified analysis of four genotypes according to the TERT and BRAF mutational status. The Kaplan–Meier analysis (Fig. 2) shows significant difference in survival in relation to the genotypes (log-rank P < 0.001). There were no deceased cases in either wild type. The 10-year survival rates among the BRAF mutation only and concomitant TERT and BRAF mutations were 99.4% and 82.6%, respectively. TERT promoter mutations in addition to BRAF mutation significantly worsened PTC patient survival: when the genotypes replaced the “TERT mutations” variable in the extended and the restricted models (Table 4), the adjusted HRs (95% CI) were 2.77 (1.15–6.65), P = 0.02 for the former model and 5.62 (1.85–17.09), P = 0.002 for the latter model.

Figure 2
Figure 2

Kaplan–Meier curves of thyroid cancer-specific survival by four genotypes according to the TERT and BRAF mutational status. Results from the analysis of patients with papillary thyroid cancer. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0219.

Citation: Endocrine-Related Cancer 23, 10; 10.1530/ERC-16-0219

Discussion

In this study, we found recurrent TERT promoter mutations in 9.8% of PTC, 16.7% of FTC and 43.8% of PDTC/ATC patients. In analyses of both differentiated thyroid cancer and PTC patients, the presence of TERT promoter mutations was found to be a marker of poor survival and remained significant on multivariate adjustment for conventional clinicopathological risk factors and for stage. The absence of the mutations conferred negligible mortality risk during long-term follow-up in PTC patients.

This study is notable because of the inclusion of a large cohort of thyroid cancer patients with robust clinicopathological data and adequate follow-up period (median 13 years), which is essential to evaluate the final outcome of a slowly progressing cancer with distinctively low mortality such as thyroid cancer (Kim et al. 2012). The results obtained here demonstrated that TERT promoter mutation status could be an independent prognostic marker in differentiated thyroid cancer for the outcome of long-term mortality, as suggested by preexisting studies (Landa et al. 2013, Liu et al. 2013, 2014ac,b, Vinagre et al. 2013, Melo et al. 2014, Xing et al. 2014b). We observed that the point estimates for the HR for TERT varied across the models (i.e., extended, restricted and backward elimination based) as the HR was conditional on the variables selected in each model. Also, because mutant TERT is not very common, the HR was not estimated very precisely. Nevertheless, the independent effect of TERT mutations was demonstrated in all models, including the backward elimination-based model.

Cell immortalization is the step that is thought to be a prerequisite for the development of all human cancers; however, the exact mechanism of telomere stabilization had remained elusive. The discovery of TERT promoter mutations (-124C>T (C228T) and -146C>T (C250T)) (Horn et al. 2013, Huang et al. 2013) out of the non-coding region (so-called dark matter) of the human genome provided new mechanistic insight for telomere activation, particularly in tumors originating from tissues with a relatively low rate of self-renewal, such as glioma (Killela et al. 2013), bladder cancer (Hurst et al. 2014) and thyroid cancer (Liu et al. 2013). The mutations generate de novo consensus binding motifs for mitogen-activated protein kinase (MAPK)-dependent E26 transformation-specific (ETS) transcription factor (Strahl et al. 1996, Horn et al. 2013, Huang et al. 2013). This mechanism is relevant in thyroid cancer as the majority of cases are driven by activation of the RAS-MAPK pathway via point mutations (BRAF and RAS) (The Cancer Genome Atlas Research Network 2014) or chromosomal rearrangements (RET/PTC (Nikiforov 2002), AKAP9/BRAF (Ciampi et al. 2005) and TRK (Russell et al. 2000)); therefore, it is expected that ETS transcription factors are highly activated. Mutant TERT promoters in thyroid cancer were responsible for the increased expression of the enzymatic subunit of the telomere holoenzyme (Muzza et al. 2015), resulting in the maintenance of chromosomal stability in proliferative cancer cells without control by apoptosis or senescence (Gunes & Rudolph 2013).

Most of the known associations among conventional clinicopathological variables and TERT promoter mutations were reproduced in this study, supporting our findings (Table 2 and Supplementary Table 3) (Liu et al. 2013, 2014a, Melo et al. 2014). In particular, the mutation frequency detected in differentiated thyroid cancers was about 11%, whereas the frequency increased to 44% in PDTC/ATC patients. As progressive dedifferentiation of PTC and FTC gives rise to PDTC and ATC, the close relationship between TERT promoter mutations and thyroid differentiation status may be one of the key biological mechanisms for the causal association between TERT promoter mutations and poor survival of patients even in cases morphologically classified as differentiated thyroid cancer. This relationship is consistent with in vitro evidence showing that the suppression of telomerase activity in melanoma cell lines induced cellular differentiation and reduced metastasis (Bagheri et al. 2006) or, vice-versa, the induction of differentiation leads to the downregulation of telomerase activity in immortalized cell lineages and embryonic stem cells (Sharma et al. 1995). In histological subgroup analysis of our data, survival differences based on TERT promoter mutational status were evident in PTC (Fig. 1B) and FTC (Supplementary Fig. 2A), but fell short of significance in already dedifferentiated cancers (Supplementary Fig. 2B). It is worth noting that the number of cases analyzed for dedifferentiated cancers was small compared with the number for PTC and FTC and that may be the reason for the lack of significance. A recent study of 106 patients with anaplastic thyroid cancer found an association of TERT C228T with BRAF T1799A mutations, older patient age and distant metastasis (Shi et al. 2015).

We observed that TERT promoter mutations were more common in PTC patients with the BRAF T1799A mutation, as suggested by some previous reports (Liu et al. 2013, Melo et al. 2014), but not all (Landa et al. 2013, Muzza et al. 2015). An American study including 507 patients who were treated for PTC from 1990 to 2012 at Johns Hopkins Hospital reported that a combination of the TERT C228T and BRAF T1799A mutations was associated with a high risk of early recurrence (Xing et al. 2014b). On the contrary, a recent Italian study reported that neither BRAF nor RAS mutations had additional effects on disease persistence in patients with PTC and FTC (Muzza et al. 2015). However, the number of cases with coexisting mutations in the latter study was too small to reach statistically meaningful conclusion. In stratified analysis of our data of PTC, the vast majority of TERT promoter mutations occurred on a background of BRAF mutation. This coexistence significantly worsens PTC patient survival compared with having BRAF mutation alone, supporting the notion that the aggressiveness of TERT mutations is in fact largely from the synergy of coexisting genetic abnormalities that activate the RAS-MAPK pathway, particularly BRAF and RAS mutations (Ngeow & Eng 2014, Xing et al. 2014b, Song et al. 2016, Xing 2016). A previous large study on the role of TERT mutations on the mortality of PTC also supports this interaction (Xing et al. 2014a).

There are several limitations to this study. This was a retrospective study and was thus prone to selection bias. An independent prospectively collected cohort with long-term follow-up will be needed to validate the study results. As the samples were collected before the era of widespread ultrasonographic screening for indolent thyroid cancer (Brito et al. 2013, Vaccarella et al. 2015), this cohort contained a low number of small tumors (11% of cases were smaller than 2 cm) and most of the cases presented with palpable neck mass. The inclusion of larger tumors might exaggerate the frequency of TERT promoter mutations in a given sample population, as the reported frequency in micro-PTC was only 4.7% (de Biase et al. 2015). Therefore, caution is necessary when applying the mutations as a prognostic biomarker to a different population, particularly for individuals with ultrasound-detected small micro-PTC. TERT mutations can coexist with RAS mutations as demonstrated previously (Muzza et al. 2015, Song et al. 2016) and as shown by two cases in Supplementary Table 2 (KRAS Q61R and NRAS Q61R). We could not develop more sophisticated models for FTC and PTC with wild-type BRAF using RAS mutations because of the small sample size of these subgroups with sufficient long-term follow-up.

In conclusion, the presence of TERT promoter mutations was found to be an independent marker of poor survival in differentiated thyroid cancer in our patient cohort. The absence of the mutations conferred negligible mortality risk during long-term follow-up in PTC patients. We predicted that the inclusion of TERT promoter mutation analysis with conventional clinicopathological evaluation could markedly improve the prognostication and management of individual patients with differentiated thyroid cancer.

Supplementary data

This is linked to the online version of the paper at http://dx.doi.org/10.1530/ERC-16-0219.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This research was supported by Korean Foundation for Cancer Research grant (grant number CB-2011-03-02).

Acknowledgements

The authors would like to thank Dr Alice Hyun-Kyung Tan (Samsung Medical Center, Seoul, Korea) for improving the use of English in the manuscript and Drs Chan Kwon Jung (Catholic University, Seoul, Korea) and Young Suk Jo (Yonsei University, Seoul, Korea) for materials and for the development of the TERT promoter mutation analysis platform.

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    Kaplan–Meier curves of thyroid cancer-specific survival by TERT mutational status. Results from the analysis of patients with (A) differentiated thyroid cancer and (B) papillary thyroid cancer. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0219.

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    Kaplan–Meier curves of thyroid cancer-specific survival by four genotypes according to the TERT and BRAF mutational status. Results from the analysis of patients with papillary thyroid cancer. A full colour version of this figure is available at http://dx.doi.org/10.1530/ERC-16-0219.

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