Objective: The association between telomerase reverse transcriptase (TERT) promoter mutation and outcome of melanoma is unclear and controversial. We aim to conduct a meta-analysis and investigate whether the TERT promoter mutation is a prognostic factor of melanoma. Study Design: Appropriate studies were searched in 3 databases: PubMed, Web of Science, and Embase. Pooled hazard ratios (HRs) were counted through random effects model. Results: Heterogeneity was moderate in overall survival (OS) (I2=43.7%, p=0.059) and low in disease-free survival (DFS) (I2=0.0%, p=0.587). Sensitivity analysis indicated that the removal of any of the study did not affect the final results. Evidence for publication bias was not found (Begg’s test, p=0.281; Egger’s test, p=0.078). The pooled OS HRs from combined effects analysis was determined (HR 1.07; 95% CI 0.83–1.39, p=0.585), together with the pooled HRs of DFS (HR 1.65; 95% CI 1.02–2.66, p=0.042). TERT promoter mutation predicted a good outcome in meta-static melanoma patients (HR 0.66; 95% CI 0.46–0.96, p=0.042). The pooled HRs of combined mutation in TERT promoter and BRAF (HR 6.27; 95% CI 2.7–14.58, p=0.000) predicted a bad outcome in melanoma patients. Conclusion: TERT promoter mutation significantly predicted poor DFS outcome but, on the contrary, predicted a good outcome in metastatic melanoma patients. The combined TERT promoter and BRAF mutation was a significant independent factor of OS in melanoma patients. Keywords: melanoma; meta-analysis; mutation; prognosis; promoter regions, genetic; skin neoplasms; telomerase; TERT promoter mutation; TERT protein, human

1. 255
OBJECTIVE: The association between telomerase re-
verse transcriptase (TERT) promoter mutation and
outcome of melanoma is unclear and controversial. We
aim to conduct a meta-analysis and investigate whether
the TERT promoter mutation is a prognostic factor of
melanoma.
STUDY DESIGN: Appropriate studies were searched
in 3 databases: PubMed, Web of Science, and Embase.
Pooled hazard ratios (HRs) were counted through
random effects model.
RESULTS: Heterogeneity was moderate in overall
survival (OS) (I2=43.7%, p=0.059) and low in disease-
free survival (DFS) (I2=0.0%, p=0.587). Sensitivity
analysis indicated that the removal of any of the
study did not affect the final results. Evidence for pub­
lication bias was not found (Begg’s test, p=0.281;
Egger’s test, p=0.078). The pooled OS HRs from com-
bined effects analysis was determined (HR 1.07; 95%
CI 0.83–1.39, p=0.585), together with the pooled HRs
of DFS (HR 1.65; 95% CI 1.02–2.66, p=0.042). TERT
promoter mutation predicted a good outcome in meta-
static melanoma patients (HR 0.66; 95% CI 0.46–0.96,
p=0.042). The pooled HRs of combined mutation in
TERT promoter and BRAF (HR 6.27; 95% CI 2.7–14.58,
p=0.000) predicted a bad outcome in melanoma patients.
CONCLUSION: TERT promoter mutation significantly
predicted poor DFS outcome but, on the contrary, pre­
dicted a good outcome in metastatic melanoma patients.
The combined TERT promoter and BRAF mutation was
a significant independent factor of OS in melanoma pa-
tients. (Anal Quant Cytopathol Histpathol 2021;43:
255–268)
Keywords: melanoma; meta-analysis; mutation;
prognosis; promoter regions, genetic; skin neo­
plasms; telomerase; TERT promoter mutation;
TERT protein, human.
Malignant melanoma is an aggressive tumor with
inscrutable biological behavior. Despite the avail­
ability of more treatments for melanoma, survival
rates have not improved significantly in the last
Analytical and Quantitative Cytopathology and Histopathology®
0884-6812/21/4304-0255/$18.00/0 © Science Printers and Publishers, Inc.
Analytical and Quantitative Cytopathology and Histopathology®
Association Between Telomerase Reverse
Transcriptase Promoter Mutations and
Melanoma Prognosis
A Meta-Analysis
Qing Li, M.D., Jinzhan Zhang, M.S., Tingting Li, M.S., and Xiaojing Kang, Ph.D.
From the Department of Dermatology, Xinjiang Medical University, Urumqi; and the Department of Dermatology, People’s Hospital of
Xinjiang Uygur Autonomous Region, Xinjian Key Laboratory of Dermatology Research, Urumqi, Xinjiang, China.
Qing Li is Attending Physician, Department of Dermatology, Xinjiang Medical University.
Jinzhan Zhang is Attending Physician, Department of Dermatology, People’s Hospital of Xinjiang Uygur Autonomous Region, Xinjiang
Key Laboratory of Dermatology Research.
Tingting Li is Attending Physician, Department of Dermatology, People’s Hospital of Xinjiang Uygur Autonomous Region, Xinjiang
Key Laboratory of Dermatology Research.
Xiaojing Kang is Professor, Department of Dermatology, People’s Hospital of Xinjiang Uygur Autonomous Region, Xinjiang Key
Laboratory of Dermatology Research.
Special Project for the Construction of Innovative Environment (Talents, Bases) in the Autonomous Region (Talent special plan–Tianshan
innovation team) (202011254).
Address correspondence to: Xiaojing Kang, Ph.D., Department of Dermatology, People’s Hospital of Xinjiang Uygur Autonomous
Region, Xinjiang Key Laboratory of Dermatology Research, 91 Tianchi Road, Urumqi, Xinjiang 830001, China (drkangxj666@163.com).
Financial Disclosure: The authors have no connection to any companies or products mentioned in this article.

2. few decades.1 Compared with other cancers, the
melanoma genotype is characterized by somatic
mutations with high burdens.2 Telomerase reverse
transcriptase (TERT), a catalytic subunit of the tel­
omerase holoenzyme complex, plays an important
role in cell senescence and tumorigenesis. The
molecular mechanisms of telomerase regulation
affect transcriptional, post-transcriptional, post-
translational, and subcellular localization.3 TERT
promoter mutation is one of important regulatory
mechanisms.4 Replication and immortality are the
hallmarks of cancer. Normally, telomeres are lim-
ited to replication in somatic cells. Repeated stim­
ulation of can­
cer cells leads to mutations in the
core promoter of the TERT, which increases telo-
merase activity and breaks the restriction of telo­
merase replication. Recently, TERT promoter mu-
tation was identified in primary and metastatic
melanoma. Additionally, these mutations have
independent prognostic value in many cancers,
including melanoma.5-7 However, some studies
showed that TERT promoter mutations did not
predict the prognosis of melanoma but that TERT
promoter mutation combined with BRAF muta­
tion was predictive.8,9 The aim of our study was
to resolve this controversial issue by conducting
meta-analysis and performing sub­
group analysis
and sensitivity analysis.
Materials and Methods
Search Strategy
We conducted a literature retrieval using the
following databases, with no data limitations:
PubMed, Embase, and Web of Science. The search
was updated to July 2019. Search terms were
as follows: (Telomerase [MeSH Terms] OR TERT
[All Fields] OR Telomerase Reverse Transcriptase
[All Fields] OR Telomerase Catalytic Subunit [All
Fields]) AND (Melanoma [MeSH Terms] OR
Malignant Melanoma [All Fields] OR Malignant
Melanomas [All Fields]). Potential references were
also checked for relevant articles.
Study Selection
We used the following inclusion criteria for the
studies included in our analysis: (1) studies that
discussed the relationship between Telomerase
Reverse Transcriptase promoter mutation and mel-
anoma survival, (2) hazard ratio (HR) and 95%
confidence interval (CI) values were reported di-
rectly, (3) survival analysis (time ending event)
with univariate or multivariate analysis was re-
ported, (4) HR and 95% CI values should be re-
trievable from the Kaplan-Meier (KM) curves, if
the study just offered KM curves, and (5) survival
outcome indicators must include overall survival
(OS), progression-free survival (PFS), and disease-
free survival (DFS). The exclusion criteria used
were: (1) reviews, (2) animals or cell line studies,
(3) unpublished and incomplete studies, (4) stud­
ies related to melanoma histology, differentiation,
and other malignant potential specifically without
survival outcomes of TERT promoter mutation in
melanoma, (5) sample size of research smaller than
ten, and (6) study on populations with specific dis­
eases or using specific medications.
The study by Diaz et al was excluded because
it found that TERT gene amplification, but not
TERT promoter mutation, predicted poor outcome
in acral lentiginous melanoma, which cannot di-
rectly reflect the prognostic role of TERT promoter
mutation.10 Melanoma populations from the stud­
ies of Nagore and Andrés-Lencina could overlap
with each other.9,11 The selected studies had high
statistical efficacy or a large sample size for primary
analyses; thus, we excluded the article of Andrés-
Lencina et al.
Data Abstraction and Quality Assessment
Two authors (Qing Li and Jinzhan Zhang) evalu­
ated all studies independently using a standard-
ized data extraction form. If the candidate stud­
ies could not be distinguished based on the title
and abstract, the full text was read. A third author
(Tingting Li) was consulted to resolve any dis­
agreements. For each study, we extracted the fol­
lowing including: first author, year of publication,
country, ethnicity, number of cases, follow-up
times, mean age, stage, histologic type, combined
mutation, adjustment for covariates, outcome, and
HR with 95% CI. If the studies just offered a
KM curve instead of HR and 95% CI values, we
extracted the data using the software Engauge
Digitizer 4.1. We extracted the HRs and 95%
CIs from the KM curves of Ekedahl et al12 and
Hugdahl et al.13 Because the sequencing of BRAF,
NRAS, and KIT are common in melanoma, these
mutations are mutually exclusive. If the study re-
ported the results of TERT promoter mutation sub­
types or TERT mutations combined with BRAF,
NRAS, or KIT mutations, we also extracted them.
The Newcastle-Ottawa Scale (NOS) was used to
assess the quality of a study by two independent
authors (Qing Li and Jinzhan Zhang). This process
256 Analytical and Quantitative Cytopathology and Histopathology®
Li et al

3. included three parts: selection (0–4 points), com­
parability (0–2 points), and outcome assessment (0–
3 points). A study with a score of ≥6 is considered a
superior quality choice (Supplemental Table I).
Statistical Analysis
We either obtained the effect sizes directly from
each study or estimated these data according to
the methods described by Tierney et al and Par­
mar et al. HR >1 suggests that melanoma patients
with TERT promoter mutations have a worse out­
come.14,15 Stata 12.0 (STATA, College Station, Texas,
USA) was used for this meta-analysis. We used
random effects models to calculate the effect sizes.
If the author provided different HR results in
the same study, the HR obtained by multivariate
analysis was considered superior to the HR ob-
tained by univariate analysis, and the HR obtained
by univariate analysis was considered superior to
the HR extracted from the survival curve data.
Heterogeneity was evaluated through Higgins I2
statistics and Cochran’s Q test. As we know, the
test efficiency of I2 statistics is better than that of
Cochran’s Q test; therefore, I2 statistics is superior
to the Q test.16,17 An I2 statistic <25% or PHeterogeneity
>0.05 suggest a low level of heterogeneity, and I2
>50% or PHeterogeneity value <0.05 indicate a high
level of heterogeneity. In order to achieve conser­
vative, robust results, all the conclusions were
extracted from the random-effects model.
We searched for the source of heterogeneity
through subgroup analysis and sensitivity analy­
sis. Publication bias was evaluated through Begg’s
funnel plot and Egger’s funnel plot. P<0.05 was
considered statistically significant for publication
bias. All p values were two-sided. P<0.05 was
statistically significant for publication bias. All the
p values are double-sided.
Results
Study Characteristics
After searching three electronic databases, our
meta-analysis ultimately included 10 published
studies between 2014 and 2018 with 2,147 patients
(Figure 1).6,8,9,12,13,18-22 In the research of Hugdahl
et al, patients were divided into primary melano­
ma and metastatic melanoma. We regarded this
research as the result of two parallel studies and
extracted the HRs and 95% CIs independently.
So, we ended up with 11 studies. All the studies
used a retrospective cohort design. Among them,
patients were Caucasian in 9 studies and Asian in
the other 2. Four of the studies were carried out
in Germany and Spain, 1 study in the USA, 1 in
Korea, 1 in China, and 2 in Norway. HRs and 95%
CIs were extracted from KM curves for 3 studies;
Volume 43, Number 4/August 2021 257
TERT Promoter Mutations and Melanoma
Figure 1
Flow chart of the included
studies.

4. the other 8 studies reported them directly. Seven
of these 11 studies calculated effect size via uni­
variable analysis, and 4 through multivariable
analysis. Seven of these studies’ intake was <200
patients, and 4 studies’ intake was >200 patients.
Other 7 studies did not clearly distinguish the
melanoma histology subtype. Three studies also
reported TERT promoter mutation combined with
BRAF V600E mutations influencing survival in
melanoma patients. We did not collect enough
information regarding the association of TERT
promoter mutation with other genes due to limited
data.
Of all the studies, 11 referred to OS, 3 studies re-
ferred to DFS, and 1 study referred to melanoma-
specific survival. The concept of OS was the peri-
od from randomization to death due to any reason.
Melanoma-specific survival was the time between
the definitive diagnosis of the disease and the pa-
tient’s death from melanoma. Based on this defi­
nition, we concluded that melanoma-specific sur­
vival was included in the OS endpoint range, so
we treated it as an OS indicator for classification
calculation. The baseline data of the studies we
analyzed are shown in Tables I and II.
TERT Promoter Mutation and OS, DFS
The meta-analysis indicated that, among mela­
noma patients, TERT promoter mutation did not
associ­
ate with OS (HR 0.97; 95% CI 0.74–1.29,
258 Analytical and Quantitative Cytopathology and Histopathology®
Li et al
Table I Main Characteristics of All Studies Included in This Meta-Analysis
Age, years Follow-up HR
Median time, mos Combined Out- Study estimation
Author Year Location Ethnicity (range) Median (range) mutation come design method
Griewank et al (A) 2014 Germany Caucasian ≥60, 172 34.6 (13.3–75.9) ND OS Retro- Reported
Spain <60, 181 spective in text
Hugdahl et al (A)* 2018 Norway Caucasian 70 (21–98) 115 (72–203) ND OS Retro- Extracted
spective from
survival
curve
Hugdahl et al (B)* 2018 Norway Caucasian 70 (21–98) 115 (72–203) ND OS Retro- Extracted
spective from
survival
curve
Pópulo et al 2014 Portugal Caucasian 60 (17.4) 57 (1–207) ND OS, Retro- Reported
DFS spective in text
Egberts et al 2016 Germany Caucasian ≥60, 148 47.6 (2–257) ND OS, Retro- Reported
<60, 81 DFS spective in text
Ekedahl et al 2016 Germany Caucasian ND 16 (4.8–228) ND OS Retro- Extracted
spective from
survival
curve
Nagore et al 2016 Spain Caucasian ND ND Braf MSS, Retro- Reported
DFS spective in text
Ofner et al 2017 Austria Caucasian ≥60, 22 ND ND OS Retro- Reported
<60, 15 spective in text
Missing 3
Roh et al 2017 Korea Asian 59 (28–87) ND Braf OS Retro- Reported
spective in text
Schwaederle et al 2018 California Caucasian 57.2 (55.1–58.5) 27.3 (23.2–31.4) ND OS Retro- Reported
spective in text
Bai et al 2017 China Asian ≥60, 162 50 (36.2–63.8) ND OS Retro- Reported
<60, 383 spective in text
ND = no description, OS = overall survival, MSS = melanoma-specific survival, DFS = disease-free survival.
Emilia Hugdahl (A)* and Emilia Hugdahl (B)* were independent study results.

5. p=0.856). A middle level of heterogeneity was
observed (I2=43.7%, p=0.059). Our results mani­
fested that TERT promoter mutation predicted
worse outcome for DFS (HR 1.65; 95% CI 1.02–2.66,
p=0.042) with no heterogeneity (I2=0.0%, p=0.587)
(Figure 2).
TERT Promoter Mutation and Metastatic Melanoma
Via this meta-analysis, we found that the relation­
ship between TERT promoter mutation and the
prognosis of melanoma patients with stage was
not available. However, we found that Hugdahl et
al and Ekedahl et al both informed that the TERT
Volume 43, Number 4/August 2021 259
TERT Promoter Mutations and Melanoma
Table II Data of Hazard Ratio Concerning the Prognostic Impacts of TERT Promoter Mutation in Melanoma
Out- HR
Source Comparison Model Cases (M/F) come (95% CI) Adjustment for Covariates
Griewank (A) TERT mut vs. TERT wt Multivariable 353 (187/166) OS 1.38 (0.69–2.76) Stage, histologic type,
Breslow thickness,
ulceration, Clark level
Griewank (B) TERT mut vs. TERT wt Multivariable 239 (136/103) OS 2.31 (1.18–4.5) Braf/NRAS, stage, histologic
(nonacral) type, Breslow thickness,
ulceration, Clark level
Hugdahl (A)* TERT mut vs. TERT wt Univariable 194 (ND) OS 0.98 (0.6–1.59) ND
Hugdahl (B)* TERT mut vs. TERT wt Univariable 72 (ND) OS 0.54 (0.29–1.01) ND
Hugdahl (C) TERT+BRAF mut vs. Univariable 178 (ND) OS 1.66 (0.95–2.9) ND
other combined mut
Pópulo TERT mut vs. TERT wt Univariable 116 (49/67) OS 2.34 (1.03–5.32) Epider malulceration,
mitotic rate, thickness,
thickness
Univariable 116 (ND) DFS 2.33 (1.01–5.39) Epider malulceration,
mitotic rate, thickness,
thickness
Egberts TERT mut vs. TERT wt Multivariable 229 (133/96) OS 1.41 (0.71–2.82) Age, Breslow thickness,
ulceration, mutation pattern
Multivariable 235 (ND) DFS 1.25 (0.49–3.15) Breslow thickness,
ulceration, NRAS
Ekedahl TERT mut vs. TERT wt Univariable 170 (ND) OS 0.74 (0.47–1.15) ND
Nagore (A) TERT mut vs. TERT wt Multivariable 280 (ND) MSS 3.57 (1.02–12.52) Age, stage, rs2853669
polymorphism
280 (ND) DFS 1.49 (0.7–3.18) Age, stage, rs2853669
polymorphism
Nagore (B) TERT+BRAF mut vs. Multivariable 280 (ND) MSS 5.81 (1.85–18.3) Age, stage, rs2853669
TERT+BRAF wt polymorphism
280 (ND) DFS 2.26 (1.16–4.4) Age, stage, rs2853669
polymorphism
Ofner TERT mut vs. TERT wt Univariable 40 (23/17) OS 0.69 (0.28–1.76) BRAF, stage, ulceration
Roh (A) TERT mut vs. TERT wt Univariable 88 (44/44) OS 0.96 (0.425–2.181) Age, stage, BRAF
Roh (B) TERT+BRAF mut vs. Univariable 82 (ND) OS 6.87 (1.98–23.88) ND
TERT+BRAF wt
Schwaederle TERT mut vs. TERT wt Multivariable 34 (ND) OS 0.635 (0.31–1.31) ND
Bai TERT mut (c228) vs. Univariable 545 (265/280) OS 0.744 (0.367–1.508) ND
TERT wt
DFS = disease-free survival, MSS = melanoma-specific survival, TERT mut = telomerase reverse transcriptase mutation, ND = no description, OS = overall
survival, TERT wt = telomerase reverse transcriptase wild type.

6. promoter mutation was a good prognostic marker
for melanoma patients after metastasis.12,13 Effect
sizes of two studies (HR 0.66; 95% CI 0.46–0.96,
p=0.042), with no heterogeneity (I2=0.0%, p=0.421)
(Table III).
TERT Promoter Mutation Combined with BRAF
Mutation
In this group, three studies were enrolled (Roh
et al, Nagore et al, and Hugdahl et al).8,9,13 A high
level of heterogeneity was detected (I2=70.1%,
p=0.035) (Table III). After the exclusion of Hugdahl
et al (2018) by sensitivity analysis (Supplemental
Figure 1), heterogeneity disappeared (I2=0, p=
0.846). We found that TERT promoter mutation
combined with BRAF mutation significantly pre­
dicted a worse outcome of OS (HR 6.27; 95% CI
2.7–14.58, p=0.000) (Figure 3). In this group the
combined effect size of Nagore et al and Roh et al
showed inconsistent directions with Hugdahl et al.
Discordance of effect size direction in the two
subgroups caused a high level of heterogeneity.
Secondly, the effect size of Hugdahl et al was
extracted from the survival curve by software,
which led to errors and heterogeneity.
Subgroup Analysis and Heterogeneity
Three subgroups were analyzed based on model,
ethnicity, and sample size.
Subgroup 1. High heterogeneity was found in the
four studies of multivariate analysis (I2=52.1%, p=
0.1) (Table III). After sensitivity analysis and exclu-
sion of the study by Schwaederle et al20 (Supple­
mental Figure 2), heterogeneity disappeared (I2=0,
p=0.392). In this group, TERT promoter mutation
predicted a worse outcome of OS (HR 1.58; 95%
CI 1.00–2.49, p=0.049) (Figure 4). We analyzed the
sources of heterogeneity in the four studies. The
biggest difference between Schwaederle et al and
the other three studies was that the sample size
of this study was 34 cases, while other three stud­
ies were more than 200 cases. The accuracy and
repeatability of the results needed to be verified
due to the minor sample size, so we excluded this
study in Subgroup 1.
Subgroup 2. In this subgroup, there was high het-
erogeneity in nine studies with Caucasian popu­
lations (I2=53.8%, p=0.027) (Table III). After sensi­
tivity analysis and exclusion of the study by Pópulo
260 Analytical and Quantitative Cytopathology and Histopathology®
Li et al
Figure 2
Forest plot of the association
between the TERT promoter
mutation and melanoma
survival.

7. et al6 (Supplemental Figure 3), the heterogeneity
was significantly reduced (I2=43.4%, p=0.089). Ef-
fect size predicted TERT promoter mutation was
not associated with the prognosis of Caucasian
Volume 43, Number 4/August 2021 261
TERT Promoter Mutations and Melanoma
Table III Meta-Analysis Results
No. of
HR (95% CI) Heterogeneity
Analysis trial References HR 95% CI p Value I2 (%) p Value
Total analysis 11 Griewank, Pópulo, Egberts, Ekedahl, Nagore,
Ofner, Roh, Schwaederle, Bai, Hugdahl (A),
Hugdahl (B)
Overall survival 11 Griewank, Pópulo, Egberts, Ekedahl, Nagore,
Ofner, Roh, Schwaederle, Bai, Hugdahl (A),
Hugdahl (B) 0.97
0.74–1.29
0.856 43.7 0.059
Disease-free survival 3 Nagore, Pópulo, Egberts 1.65 1.02–2.66 0.042 0.0 0.587
Metastatic melanoma 2 Hugdahl (B), Ekedahl 0.66 0.46–0.96 0.028 0.0 0.421
Combined mutation 3 Nagore, Roh, Hugdahl (C) 3.60 1.3–9.96 0.014 70.1 0.035
Subgroup 1 11 0.97
0.74–1.29
0.856 43.7 0.059
Univariate analysis 7 Pópulo, Roh, Ekedahl, Ofner, Bai, Hugdahl (A),
Hugdahl (B) 0.86
0.64–1.16
0.322 33.3 0.174
Multivariate analysis 4 Nagore, Griewank, Egberts, Schwaederle 1.29 0.72–2.29 0.389 52.1 0.100
Subgroup 2 11 0.97
0.74–1.29
0.856 43.7 0.059
Asian 2 Roh, Bai 0.83 0.49–1.42 0.494 0.0 0.644
Caucasian 9 Griewank, Pópulo, Egberts, Ekedahl, Nagore,
Ofner, Schwaederle, Hugdahl (A), Hugdahl (B) 1.02 0.73–1.42 0.919 53.8 0.027
Subgroup 3 11 0.97
0.74–1.29
0.856 43.7 0.059
Sample size >200 4 Nagore, Griewank, Bai, Egberts 1.32 0.79–2.19 0.286 39.4 0.175
Sample size <200 7 Pópulo, Ekedahl, Ofner, Roh, Schwaederle,
Hugdahl (A), Hugdahl (B) 0.84 0.62–1.15 0.283 36.5 0.150
I2 and p value results were from random-effects model.
Figure 3
Forest plot of the association
between the TERT promoter
mutation and melanoma
survival in the combined
mutation subgroup.

8. human melanoma (HR 0.92; 95% CI 0.67–1.26, p=
0.089) (Figure 5). After analysis of the Pópulo et al
study, we found that the samples collected in this
study were from multiple centers, and heterogeneity
in sample processing may lead to heterogeneity.
In addition, differences in melanoma subtypes
and inclusion of primary and metastatic melanoma
samples may also account for the heterogeneity.
Subgroup 3. In this subgroup, the combined effect
size showed that TERT promoter mutation is not
associated with OS in melanoma patients, and the
heterogeneity of subgroups 3 was not high (Table
III).
Sensitivity Analysis
Heterogeneity was not high in OS (I2=43.7%, p=
262 Analytical and Quantitative Cytopathology and Histopathology®
Li et al
Figure 4
Forest plot of the association
between the TERT promoter
mutation and melanoma
survival in the multivariate
analysis subgroup.
Figure 5
Forest plot of the association
between the TERT promoter
mutation and melanoma
survival in the Caucasian
populations subgroup.

9. TERT promoter mutations were found initially
in melanoma,26 then many other human cancers,27
including thyroid cancer.28,29 Telomerase main-
tains the length of the telomeres and is overex­
pressed in germ cells and tumor tissues.30 TERT
expression is physiologically limited to primary
germ cells and tumor cells, and it limits the activ­
ity of telomerase. The TERT promoter mutation
was commonly found at −124 bp (C228) and −146
bp (C250) sites of ATG site, which provide binding
motifs for ETS transcription factors that enhance
TERT expression.31 This explained the impact that
TERT promoter mutations have on melanoma
DFS. However, alternative mechanisms of telo­
merase activation may explain this discordancy
between nonmetastatic melanoma and metastatic
melanoma from other aspects, such as splicing of
TERT mRNA32 and DNA methylation.33 Seynnaeve
et al34 showed that methylation was obviously as-
sociated with recurrence-free survival in adoles-
cent melanoma patients as compared to TERT
promoter mutations. In our meta-analysis, the
subgroup analysis did not involve age stratifica-
tion, and we cannot verify this conclusion. How­
ever, it should be noted that our combined effects
in metastatic melanoma patients come from only
two studies, and a larger sample and multi-center
studies are needed to further verify this result.
Volume 43, Number 4/August 2021 263
TERT Promoter Mutations and Melanoma
0.059), but it was high in the combined mutation
group, Subgroup 1 and Subgroup 2. Therefore, we
conducted sensitivity analysis to guarantee the re-
sultant reliability and find the potential sources of
heterogeneity (Figure 6, Supplemental Figures 1–
3). We excluded each study separately and calcu­
lated the combined HR estimates for the remaining
studies.
Publication Bias
All combined effects were tested by Begg’s and
Egger’s regression test and showed that there
was no publication bias (Pr>|z|=0.281 (continuity
corrected); and p>|t|=0.078, respectively). More­
over, funnel plot did not observe a high degree
of publication bias in these articles (Supplemental
Figure 4) (Supplemental Table II).
Discussion
Our meta-analysis showed that TERT promoter
mutation predicted poor DFS outcome but did
not influence OS outcome. On the contrary, it was
a protective factor in metastatic melanoma pa-
tients. This may account for the fact that TERT
promoter mutation loses its effect at the late stage
of tumor progression, while other gene mutations
play a more important role after tumor metastasis,
such as CDKN2A,23 PTEN,24 and TP53.25
Figure 6
Total data sensitivity analysis.

10. 264 Analytical and Quantitative Cytopathology and Histopathology®
Li et al
TERT promoter mutation combined with BRAF
mutation was a significant independent factor of
OS in melanoma patients. Some studies revealed
that the combined mutation frequency of TERT
promoter and BRAF/NRAS was also higher than
that of random occurrence.5,6,31,35 These results
suggest that the oncogene duet formed by the
joint mutation of BRAF V600E and TERT promot-
ers has a congenerous role in driving the evolve­
ment and invasion of some cancers. Functionally,
the BRAF V600E/MAP kinase pathway phosphor­
ylates and activates the transcription factor FOS,
which binds and activates the GABPB promoter,
upregulates GABPB expression, and promotes the
formation of the GABPA-GABPB complex. The
latter binds and activates the TERT promoter to
upregulate the expression of TERT.36 This mech­
anism explained the results of our meta-analysis.
Regrettably, these three studies did not compare
combined mutations with either mutation alone.
Therefore, a larger sample of randomized clinical
trial studies are needed to prove that, compared
with either mutation alone, the combined muta-
tion has a strong incremental and synergistic im-
pact over melanoma survival. In addition, most
of the included studies did not detect BRAF mu-
tations. The TERT promoter mutation alone and
TERT promoter mutation coexistence with a BRAF
mutation were not discriminated. This prevents
us from further estimating the effect of BRAF mu-
tations on the final outcome.
Interactions with other genes, splicing of TERT
mRNA, and DNA methylation resulted in the
inconsistency of TERT promoter mutations over
the prognosis of OS and DFS in melanoma. How­
ever, our meta-analysis also pointed us to further
stratify melanoma patients with TERT promoter
mutations to distinguish whether there is a com­
bined mutation with a BRAF mutation. On the
other hand, it is possible that patients without
BRAF mutation are affected by TERT promoter
mutations, which may lead to a relatively longer
survival period in patients with TERT mutations in
metastatic melanoma.
We conducted an overall meta-analysis of the
results of 11 studies and found that heterogeneity
was not high, but obvious, in the subgroup ana-
lysis. The sources of heterogeneity are analyzed
from two aspects. First, some research studies re-
quired us to use software to extract HRs, which
is bound to produce errors with the original re-
sults. Second, differences in clinical research meth­
ods among various studies, such as ethnicity, sam­
ple size, area, follow-up time, melanoma subtype,
and stage are the sources of heterogeneity.
In order to show the rigor of the results, other
deficiencies of the meta-analysis should be dis­
cussed. First, the occurrence of selection bias may
be due to the fact that all our studies were retro­
spective studies. Secondly, studies published in
languages other than English were not enrolled.
Thus, publication bias needs to be taken into
account. Last, we had no individual patient data.
At the same time, some basic information was not
adequate, such as cancer stage. Our meta-analysis
is the first study to report the association of TERT
promoter mutation and outcome of melanoma.
These results can be further strengthened by in-
creasing the sample size to obtain more reliable
data, increasing the number of samples to make
the data results of the meta-analysis more reliable.
In short, our meta-analysis found that TERT pro­
moter mutation significantly predicted poor DFS
in melanoma patients. However, this relationship
was not found between TERT promoter mutation
and OS in melanoma. In the combined mutation
subgroup, TERT promoter mutation combined
with BRAF mutation was a significant independent
prognostic factor of OS in melanoma patients. Fur­
ther studies higher sample numbers need to be
launched to prove the prognostic value of TERT
promoter mutation in nonacral and metastatic
melanoma patients, and to assess whether the
combined mutation has a strong incremental and
synergistic impact over melanoma survival.
References
1. Hodi FS, Chiarion-Sileni V, Gonzalez R, Grob JJ, Rutkowski
P, Cowey CL, Lao CD, Schadendorf D, Wagstaff J, Dummer
R, Ferrucci PF, Smylie M, Hill A, Hogg D, Marquez-Rodas
I, Jiang J, Rizzo J, Larkin J, Wolchok JD: Nivolumab plus
ipilimumab or nivolumab alone versus ipilimumab alone
in advanced melanoma (CheckMate 067): 4-year outcomes
of a multicentre, randomised, phase 3 trial. Lancet Oncol
2018;19:1480-1492
2. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SAJR,
Behjati S, Biankin AV, Bignell GR, Bolli N, Borg A, Børresen-
Dale AL, Boyault S, Burkhardt B, Butler AP, Caldas C,
Davies HR, Desmedt C, Eils R, Eyfjörd JE, Foekens JA,
Greaves M, Hosoda F, Hutter B, Ilicic T, Imbeaud S,
Imielinski M, Jäger N, Jones DTW, Jones D, Knappskog S,
Kool M, Lakhani SR, López-Otín C, Martin S, Munshi NC,
Nakamura H, Northcott PA, Pajic M, Papaemmanuil E,
Paradiso A, Pearson JV, Puente XS, Raine K, Ramakrishna
M, Richardson AL, Richter J, Rosenstiel P, Schlesner M,
Schumacher TN, Span PN, Teague JW, Totoki Y, Tutt ANJ,
Valdés-Mas R, van Buuren MM, van‘t Veer L, Vincent-

11. Volume 43, Number 4/August 2021 265
TERT Promoter Mutations and Melanoma
Salomon A, Waddell N, Yates LR, Australian Pancreatic
Cancer Genome Initiative; ICGC Breast Cancer Consortium;
ICGC MMML-Seq Consortium; ICGC PedBrain; Zucman-
Rossi J, Futreal PA, McDermott U, Lichter P, Meyerson
M, Grimmond SM, Siebert R, Campo E, Shibata T, Pfister
SM, Campbell PJ, Stratton MR: Signatures of mutational
processes in human cancer. Nature 2013;500:415-421
3. Kim W, Ludlow AT, Min J, Robin JD, Stadler G, Mender I,
Lai TP, Zhang N, Wright WE, Shay JW: Regulation of the
human telomerase gene TERT by Telomere Position Effect-
Over Long Distances (TPE-OLD): Implications for aging and
cancer. PLoS Biol 2016;14:e2000016
4. Bell RJ, Rube HT, Xavier-Magalhães A, Costa BM, Mancini A,
Song JS, Costello JF: Understanding TERT promoter muta-
tions: A common path to immortality. Mol Cancer Res 2016;
14:315-323
5. Macerola E, Loggini B, Giannini R, Garavello G, Giordano
M, Garavello G, Giordano M, Proietti A, Niccoli C, Basolo
F, Fontanini G: Coexistence of TERT promoter and BRAF
muta­
tions in cutaneous melanoma is associated with more
clin­
icopathological features of aggressiveness. Virchows
Arch 2015;467:177-184
6. Pópulo H, Boaventura P, Vinagre J, Batista R, Mendes A,
Caldas R, Pardal J, Azevedo F, Honavar M, Guimarães I,
Manuel Lopes J, Sobrinho-Simões M, Soares P: TERT pro­
moter mutations in skin cancer: The effects of sun exposure
and X-irradiation. J Invest Dermatol 2014;134:2251-2257
7. Vinagre J, Pinto V, Celestino R, Reis M, Pópulo H, Boaventura
P, Melo M, Catarino T, Lima J, Lopes JM, Máximo V,
Sobrinho-Simões M, Soares P: Telomerase promoter muta­
tions in cancer: An emerging molecular biomarker? Virchows
Arch 2014;465:119-133
8. Roh MR, Park KH, Chung KY, Shin SJ, Rha SY, Tsao H:
Telomerase reverse transcriptase (TERT) promoter muta­
tions in Korean melanoma patients. Am J Cancer Res 2017;
7:134-138
9. Nagore E, Heidenreich B, Rachakonda S, Garcia-Casado
Z, Requena C, Soriano V, Frank C, Traves V, Quecedo E,
Sanjuan-Gimenez J, Hemminki K, Landi MT, Kumar R:
TERT promoter mutations in melanoma survival. Int J Can­
cer 2016;139:75-84
10. Diaz A, Puig-Butille JA, Muñoz C, Costa D, Díez A, Garcia-
Herrera A, Carrera C, Badenas C, Solé F, Malvehy J, Puig
S, Alos L: TERT gene amplification is associated with poor
outcome in acral lentiginous melanoma. J Am Acad Derma­
tol 2014; 71:839-841
11. Andrés-Lencina JJ, Rachakonda S, Garcia-Casado Z, Srinivas
N, Skorokhod A, Requena C, Soriano V, Kumar R, Nagore
E: TERT promoter mutation subtypes and survival in stage
I and II melanoma patients. Int J Cancer 2019;144:1027-1036
12. Ekedahl H, Lauss M, Olsson H, Griewank KG, Schadendorf
D, Ingvar C, Jönsson G: High TERT promoter mutation
frequency in non-acral cutaneous metastatic melanoma.
Pigment Cell Melano­
ma Res 2016;29:598-600
13. Hugdahl E, Kalvenes MB, Mannelqvist M, Ladstein RG,
Akslen LA: Prognostic impact and concordance of TERT
promoter mutation and protein expression in matched
primary and metastatic cutaneous melanoma. Br J Cancer
2018;118:98-105
14. Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR:
Practical methods for incorporating summary time-to-event
data into meta-analysis. Trials 2007;8:16
15. Parmar MK, Torri V, Stewart L: Extracting summary statis­
tics to perform meta-analyses of the published literature for
survival endpoints. Stat Med 1998;17:2815-2834
16. Huedo-Medina TB, Sanchez-Meca J, Marin-Martinez F,
Botella J: Assessing heterogeneity in meta-analysis: Q sta­
tistic or I2 index? Psychol Methods 2006;11:193-206
17. Thorlund K, Imberger G, Johnston BC, Walsh M, Awad T,
Thabane L, Gluud C, Devereaux PJ, Wetterslev J: Evolution
of heterogeneity (I2) estimates and their 95% confidence
intervals in large meta-analyses. PLoS One 2012;7:e39471
18. Griewank KG, Murali R, Puig-Butille JA, Schilling B,
Livingstone E, Potrony M, Carrera C, Schimming T, Möller
I, Schwamborn M, Sucker A, Hillen U, Badenas C, Malvehy
J, Zimmer L, Scherag A, Puig S, Schadendorf D: TERT pro-
moter mutation status as an independent prognostic factor in
cutaneous melanoma. J Natl Cancer Inst 2014 Sep 13;106(9):
dju246
19. Ofner R, Ritter C, Heidenreich B, Kumar R, Ugurel S,
Schrama D, Becker JC: Distribution of TERT promoter mu-
tations in primary and metastatic melanomas in Austrian
patients. J Cancer Res Clin Oncol 2017;143:613-617
20. Schwaederle M, Krishnamurthy N, Daniels GA, Piccioni
DE, Kesari S, Fanta PT, Schwab RB, Patel SP, Parker BA,
Kurzrock R: Telomerase reverse transcriptase promoter al-
terations across cancer types as detected by next-generation
sequencing: A clinical and molecular analysis of 423 patients.
Cancer 2018;124:1288-1296
21. Egberts F, Bohne AS, Kruger S, Hedderich J, Rompel R, Haag
J, Röcken C, Hauschild A: Varying mutational alterations
in multiple primary melanomas. J Mol Diagn 2016;18:75-83
22. Bai X, Kong Y, Chi Z, Sheng X, Cui C, Wang X, Mao L, Tang
B, Li S, Lian B, Yan X, Zhou L, Dai J, Guo J, Si L: MAPK
Pathway and TERT promoter gene mutation pattern and
its prognostic value in melanoma patients: A retrospective
study of 2,793 cases. Clin Cancer Res 2017;23:6120-6127
23. Hodis E, Watson IR, Kryukov GV, Arold ST, Imielinski M,
Theurillat JP, Nickerson E, Auclair D, Li L, Place C, Dicara
D, Ramos AH, Lawrence MS, Cibulskis K, Sivachenko S,
Voet D, Saksena G, Stransky N, Onofrio RC, Winckler W,
Ardlie K, Wagle N, Wargo J, Chong K, Morton DL, Stemke-
Hale K, Chen G, Noble M, Meyerson M, Ladbury JE, Davies
MA, Gershenwald JE, Wagner SN, Hoon DSB, Schadendorf
D, Lander ES, Gabriel SB, Getz G, Garraway LA, Chin L: A
landscape of driver mutations in melanoma. Cell 2012;150:
251-263
24. Shain AH, Garrido M, Botton T, Talevich E, Yeh I, Sanborn
JZ, Chung J, Wang NJ, Kakavand H, Mann GJ, Thompson
JF, Wiesner T, Roy R, Olshen AB, Gagnon A, Gray JW,
Huh N, Hur JS, Busam KJ, Scolyer RA, Cho RJ, Murali R,
Bastian BC: Exome sequencing of desmoplastic melanoma
identifies recurrent NFKBIE promoter mutations and diverse
activating mutations in the MAPK pathway. Nat Genet 2015;
47:1194-1199
25. Hayward NK, Wilmott JS, Waddell N, Johansson PA,
Field MA, Nones K, Patch AM, Kakavand H, Alexandrov
LB, Burke H, Jakrot V, Kazakoff S, Holmes O, Leonard C,

12. 266 Analytical and Quantitative Cytopathology and Histopathology®
Li et al
Sabarinathan R, Mularoni L, Wood S, Xu Q, Waddell N,
Tembe V, Pupo GM, De Paoli-Iseppi R, Vilain RE, Shang
P, Lau LMS, Dagg RA, Schramm SJ, Pritchard A, Dutton-
Regester K, Newell F, Fitzgerald A, Shang CA, Grimmond
SM, Pickett HA, Yang JY, Stretch JR, Behren A, Kefford RF,
Hersey P, Long GV, Cebon J, Shackleton M, Spillane AJ, Saw
RPM, López-Bigas N, Pearson JV, Thompson JF, Scolyer RA,
Mann GJ: Whole-genome landscapes of major melanoma
subtypes. Nature 2017;545:175-180
26. Huang FW, Hodis E, Xu MJ, Kryukov GV, Chin L, Garraway
LA: Highly recurrent TERT promoter mutations in human
mel­
anoma. Science 2013;339:957-959
27. Killela PJ, Reitman ZJ, Jiao Y, Bettegowda C, Agrawal N,
Diaz LA Jr, Friedman AH, Friedman H, Gallia GL, Gio­
vanella BC, Grollman AP, He TC, He Y, Hruban RH, Jallo
GI, Mandahl N, Meeker AK, Mertens F, Netto GJ, Rasheed
BA, Riggins GJ, Rosenquist TA, Schiffman M, Shih IM,
Theodorescu D, Torbenson MS, Velculescu VE, Wang TL,
Wentzensen N, Wood LD, Zhang M, McLendon RE, Bigner
DD, Kinzler KW, Vogelstein B, Papadopoulos N, Yan H:
TERT promoter mutations occur frequently in gliomas and
a subset of tumors derived from cells with low rates of self-
renewal. Proc Natl Acad Sci U S A 2013;110: 6021-6026
28. Liu R, Xing M: TERT promoter mutations in thyroid cancer.
Endocr Relat Cancer 2016;23:R143-155
29. Liu X, Bishop J, Shan Y, Pai S, Liu D, Murugan AK, Sun H,
El-Naggar AK, Xing M: Highly prevalent TERT promoter
mutations in aggressive thyroid cancers. Endocr Relat Can­
cer 2013;20:603-610
30. Pellatt AJ, Wolff RK, Torres-Mejia G, John EM, Herrick JS,
Lundgreen A, Baumgartner KB, Giuliano AR, Hines LM,
Fejerman L, Cawthon R, Slattery ML: Telomere length,
telomere-related genes, and breast cancer risk: The breast
cancer health disparities study. Genes Chromosomes Can-
cer 2013;52:595-609
31. Horn S, Figl A, Rachakonda PS, Fischer C, Sucker A, Gast
A, Kadel S, Moll I, Nagore E, Hemminki K, Schadendorf
D, Kumar R: TERT promoter mutations in familial and spo­
radic melano­
ma. Science 2013;339:959-961
32. Dwight T, Flynn A, Amarasinghe K, Benn DE, Lupat R, Li
J, Cameron DL, Hogg A, Balachander S, Candiloro ILM,
Wong SQ, Robinson BG, Papenfuss AT, Gill AJ, Dobrovic
A, Hicks RJ, Clifton-Bligh RJ, Tothill RW: TERT structural
rearrangements in metastatic pheo­
chromocytomas. Endocr
Relat Cancer 2018;25:1-9
33. Lai SR, Phipps SM, Liu L, Andrews LG, Tollefsbol TO:
Epigenetic control of telomerase and modes of telomere
maintenance in aging and abnormal systems. Front Biosci
2005;10:1779-1796
34. Seynnaeve B, Lee S, Borah S, Park Y, Pappo A, Kirkwood JM,
Bahrami A: Genetic and epigenetic alterations of TERT are
associated with inferior outcome in adolescent and young
adult patients with melanoma. Sci Rep 2017;7:45704
35. Heidenreich B, Nagore E, Rachakonda PS, Garcia-Casado
Z, Requena C, Traves V, Becker J, Soufir N, Hemminki K,
Kumar R: Telomerase reverse transcriptase promoter muta-
tions in primary cutaneous melanoma. Nat Commun 2014;5:
3401
36. Liu R, Zhang T, Zhu G, Xing M: Regulation of mutant TERT
by BRAF V600E/MAP kinase pathway through FOS/GABP
in human cancer. Nat Commun 2018;9:579
Supplemental Figure 1
Combined mutation subgroup
sensitivity analysis.
Supplemental Figures and Tables

13. Volume 43, Number 4/August 2021 267
TERT Promoter Mutations and Melanoma
Supplemental Figure 2
Multivariate analysis subgroup
sensitivity analysis.
Supplemental Figure 3
Caucasian populations
subgroup sensitivity analysis.

14. 268 Analytical and Quantitative Cytopathology and Histopathology®
Li et al
Supplemental Table I Quality Assessment Using the Newcastle-
Ottawa Quality Assessment Scale in the
Studies
Selec- Compa- Out-
Study Year tion rability come Score
Griewank 2014 3 1 3 7
Pópulo 2014 3 0 3 6
Egberts 2016 3 1 3 7
Ekedahl 2016 3 0 3 6
Nagore 2016 4 1 3 8
Ofner 2017 3 0 3 6
Roh 2017 3 0 3 6
Schwaederle 2017 3 1 3 7
Bai 2017 3 0 3 6
Hugdahl (A) 2018 3 1 3 7
Hugdahl (B) 2018 3 1 3 7
Supplemental Figure 4
Funnel plot of the publication
bias tests.
Supplemental Table II Begg’s and Egger’s Results
Begg’s Egger’s
Outcome (p value) (p value)
DFS 0.602 0.842
OS 0.243 0.098
Overall 0.281 0.078
DFS = disease-free survival, OS = overall survival.