Prevalence of BRAF^V600E mutation in Asian series of papillary thyroid carcinoma—a contemporary systematic review

Abstract

Papillary thyroid carcinoma (PTC), the most common malignancy of the endocrine system, is frequently driven by BRAF^V600E mutation, which was reported in 35–60% cases in Western series. Numerous studies have recently emerged from Asian countries and regions; however sufficient summary is lacking to date. BRAF mutation serves as a diagnostic and prognostic tool in thyroid cancer, therefore establishing a rate of BRAF on the national scale could be of practical significance. We performed systematic reviews of available literature to investigate the prevalence of BRAF mutation in series of PTC from various Asian countries and regions. Out of the total 3,966 reports identified via initial screening, 138 studies encompassing over 40,000 PTCs were included for the final analysis. A vast majority (90.2%) of PTCs with known BRAF status were from East Asia, including China, South Korea, and Japan, with BRAF mutation rates of 71.2%, 75.5%, and 70.6%, respectively. Less abundant Indian and Saudi Arabian series found 45.6% and 46.3% prevalence of BRAF^V600E in PTC, respectively. Much limited evidence was available from Thailand, Iran, Kazakhstan, Taiwan, Singapore, Indonesia, Hong Kong, Philippines, Vietnam, Iraq, and Myanmar. No relevant publications were found from other highly populated countries, such as Pakistan, Bangladesh, and Malaysia. After grouping by geographic region, we found that the highest rate of BRAF^V600E was reported in the PTC series from East Asia (76.4%). Much lower rate (45–48%) was seen in PTC cohorts from South Asia, Central Asia, and the Middle East while the Southeast Asian series were in between (57%). Further subgroup analysis revealed that studies employing fresh frozen tissue and fine-needle aspirates showed higher rates of BRAF compared to those used formalin-fixed paraffin-embedded tissues. We found that the PTC series enrolled patients’ cohorts after 2010 demonstrated a higher rate of BRAF compared to the earlier series. Finally, pediatric PTCs had lower BRAF prevalence compared to the baseline rate for the country. In conclusion, despite considerable among and within countries heterogeneity, the Asian PTC series showed a higher prevalence of BRAF^V600E mutation than that in Western series. Causes of geographic heterogeneity, whether genuine (etiology, genetics) or methodology-related should be further investigated.

Introduction

Thyroid carcinoma is the most common endocrine malignancy that represents almost 2.1% of newly diagnosed cancer cases (1). Papillary thyroid carcinoma (PTC) is the most common histological type of differentiated thyroid carcinoma accounting for 75–85% cases, often characterized by low mortality rate and good response to radioiodine therapy (2). The 10-year overall survival rate for differentiated types of thyroid carcinoma is exceeding more than 90% (1).

Different types of thyroid cancer are characterized by different gene alterations. PTC development is closely linked to somatic point mutations in BRAF and rearrangements in RET/PTC1, RET/PTC3 and NTRK1/3 genes (2). Interestingly, driver gene aberrations in well-differentiated thyroid cancer are mutually exclusive. Rearranged during transfection (RET) gene encodes a single transmembrane tyrosine kinase receptor (3). RET/PTC fusions seem to be important in the early pathogenesis of PTC. These fusions are involved in development of 10–20% of PTC either it is sporadic or radiation-induced PTC (4,5). Other genetic alterations like RAS and PAX/PPARG are less involved in development of conventional PTC but more often associated with follicular thyroid carcinoma and follicular variant PTC (FVPTC) (2).

B-type Raf kinase (BRAF) proto-oncogene is the most common molecular target in PTC. BRAF^V600E mutation activates the protein kinase domain of BRAF that results in constitutive initiation of mitogen-activated protein kinase pathway, which in turn promotes cell growth and proliferation (5,6). Up to 10–15% of all human cancers are reported to have BRAF mutation, with a high prevalence in PTC and melanoma (7). BRAF^V600E is detected in about half of PTC cases, and may have higher rates in certain populations and histological types (2,5). In thyroid carcinoma, BRAF^V600E mutation has been shown to be associated with high risk clinicopathological characteristics, tumor recurrence, metastasis, and reduced sensitivity to radioiodine therapy (8,9). Recently, BRAF^V600E was introduced in the clinical guidelines to aid risk stratification of PTC (10).

Since BRAF mutation may serve as a diagnostic and prognostic tool, establishing a rate of BRAF on the national scale is of practical significance. Western countries have extensively reported on BRAF^V600E mutation rates in the past decade. In particular, the prevalence of BRAF^V600E mutation in the USA and Europe was ranging 35–60% (11-13). Numerous studies have recently emerged from Asian countries and regions; however, these were not sufficiently summarized to date except for showing overall high BRAF^V600E mutation prevalence in Asian PTC compared to that in Western series (14,15).

Therefore, we performed a systematic review of available literature to investigate the prevalence of BRAF mutation in series of PTC originated from various Asian countries and regions.

Methods

Search strategy

We conducted a search within three electronic databases available for all coauthors (PubMed, Google Scholar, and Scopus). Relevant articles were identified using the following combination of keywords: PTC (or cancer) and BRAF combined with the name of each Asian country. The latter was searched in the authors' affiliation. Transcontinental countries, such as Russia and Turkey were disregarded. An additional manual search was done by screening references within included publications. Furthermore, if the search in the above databases was not successful, relevant local publications were queried from the members of the Asian Working Group in Thyroid Pathology (16). We followed the recommendations of Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement (17).

Data extraction

Results of the search from all sources were imported into EndNote reference manager (Thompson Reuters, New York, NY) and two reviewers (F. R. and J. M.) independently screened the abstracts. Upon mutual agreement on eligibility of the study, both reviewers independently extracted data as per the predefined data collection sheet. The only target of our review was BRAF^V600E, therefore, other BRAF mutations were excluded from the analysis. The following information was extracted: first author, year of publication, name of institution, city, country/region, tissue type used for nucleic acid extraction, technique to detect BRAF mutation, total number of PTCs, and number of cases positive for BRAF. Therefore, clear indication of all these parameters either in the abstract or full text was qualified as inclusion criteria for our systematic review. Additional information, such as histological type of PTC, age of the cohort (e.g., pediatric), and years where study cohort belongs to, was optional but not mandatory. Baseline and clinicopathological characteristics of the patients except specified above were not required. In addition, two reviewers were asked to score and record the quality and risk of bias of the included studies. Any discrepancies during data extraction were resolved after consultation with a supervisor (A. B.) of the study. Studies not qualified as per inclusion criteria were disregarded. More exclusion criteria were as follows: (I) less than 10 cases enrolled; (II) non-primary PTC (regional and distant metastases) only and thyroid tumors other than PTC; (III) experimental and animal studies, (IV) duplicated cohorts. The latter were decided based on the overlapping of the institution name and study cohort in several publications. If potential overlap was found, a study with the largest sample size was selected.

Statistics

Descriptive statistics were calculated with Microsoft Office Excel 2010 (Microsoft, CA, USA). Further statistical analysis was performed with SPSS 23.0 statistical software package (SPSS, Chicago, IL, USA). A χ² test with Yates’s correction was applied for subgroup analysis. P value of less than 0.05 was considered to be statistically significant.

Results

Out of the total 3,966 studies identified via search in electronic libraries, only 244 met our inclusion criteria and were selected for further evaluation. Finally, after reading abstracts and full texts, 138 studies were qualified as eligible for data extraction. A flow chart of the data selection process is shown in Figure 1.

Figure 1.

The PRISMA flowchart of study selection.

Asian studies classified by country and geographical region

We further separated 3 studies from Japan, China, and Saudi Arabia (18-20) in a subgroup, composed exclusively of pediatric PTCs, and focused on 135 adult or unselected series from Asian countries and regions including 40,371 PTCs. The largest datasets were provided by Japan (Table 1), South Korea (Table 2), China (Table 3), India (Table 4), and Saudi Arabia (Table 5). Summary of all 135 publications stratified by country and region of origin is shown in Table 6.

Table 1. Characteristics of included studies from Japan.

##	Author	Year	Institution	City	Study cohort	Tissue type	Technique	Total PTC	BRAF+	BRAF rate (%)
1	Kondo T (21)	2007	University of Yamanashi	Yamanashi	n/s	FFPE	Seq	31	13	42
2	Kumagai A (22)	2007	Nagasaki University Hospital	Nagasaki	2003–2006	FNA	PCR-RFLP	14	12	86
3	Takahashi K (23)	2007	Radiation Effects Research Foundation	Hiroshima	2003–2005	FFPE	RFLP	64	38	59
4	Matsuse M (24)	2011	Kuma Hospital	Kobe	n/s	FFPE	Seq	492	388	79
5	Mitsutake N (18)	2015	Fukushima Medical University	Fukushima	2013–2014	Fresh frozen	Seq	67	43	64
6	Xing M (25)	2015	Kanagawa Cancer Center	Yokohama	n/s	Fresh frozen	Seq	49	33	67
7	Nasirden A (26)	2016	Juntendo University Hospital	Tokyo	2009, 2017	FFPE	Seq	144	53	37
8	Vuong HG (27)	2016	Yamanashi Hospital	Yamanashi	2011–2014	FFPE	AS-PCR	67	55	82
9	Oishi N (28)	2017	University of Yamanashi + Kuma Hospital	Yamanashi, Kobe	1991–2013	FFPE	AS-PCR + Seq	172	121	70
10	Bandoh N (29)	2018	Hokuto Hospital	Obihiro	2014–2016	FFPE	Seq	34	27	79

AS-PCR, allele specific-polymerase chain reaction; FFPE, formalin fixed paraffin embedded tissues; FNA, fine needle aspiration; n/s, not specified; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; Seq, sequencing.

Table 2. Characteristics of included studies from South Korea.

##	Author	Year	Institution	City	Study cohort	Tissue type	Technique	Total PTC	BRAF+	BRAF rate (%)
1	Kim KH (30)	2005	Eulji University Hospital, Chungnam National University Hospital	Daejeon	2000–2003	FFPE	PCR	79	64	81
2	Kim TY (31)	2005	Asan Medical Center	Seoul	1997–2001	FFPE	PCR	60	31	52
3	Jo YS (32)	2006	Chungnam National University Hospital	Daejeon	2004–2005	FFPE	IHC + Seq	161	102	63
4	Kim TY (33)	2006	Asan Medical Center	Seoul	n/s	FFPE	PCR + Seq	203	149	73
5	Lee JH (34)	2006	Korea University Guro Hospital	Seoul	2000–2003	FFPE	PCR	100	58	58
6	Park SY (35)	2006	Seoul National University Bundang Hospital	Seongnam	2003–2005	FFPE	PCR + Seq	61	53	87
7	Kim SK (36)	2009	Konkuk University Hospital	Seoul	2005–2006	FNA	Pyroseq	101	88	87
8	Kwak JY (37)	2009	Severance Hospital	Seoul	2008	FNA	PCR + Seq	339	213	63
9	Kim JH (38)	2010	Kosin University College of Medicine	Busan	2007–2009	Fresh frozen	Seq	109	35	32
10	Kim SW (39)	2010	Samsung Medical Center	Seoul	n/s	FNA	PCR + Seq	263	221	84
11	Lee HJ (40)	2010	Asan Medical Center	Seoul	2008	FNA	PCR, Seq, Pyroseq	52	47	90
12	Park YJ (41)	2010	Seoul National University Hospital	Seoul	1983–2004	FFPE	PCR	230	153	67
13	Ahn D (42)	2012	Kyungpook National University Hospital	Daegu	2010	FFPE	multiplex PCR	107	85	79
14	Chang H (43)	2012	Korea University Guro Hospital	Seoul	2008–2009	FNA	Seq + MCA	126	96	76
15	Joo JY (44)	2012	Chungnam National University	Daejeon	2009–2011	FNA	Seq	148	79	53
16	Kim SJ (45)	2012	Seoul National University Hospital	Seoul	2009–2010	FFPE	PCR + Seq	547	381	70
17	Moon WJ (46)	2012	Konkuk University Medical Center	Seoul	2006–2008	FNA	PCR+Seq	164	140	85
18	Choi SY (47)	2013	Dong-A Medical Center	Busan	2011–2012	FFPE	qPCR	101	72	71
19	Jeong D (48)	2013	Soonchunhyang University College of Medicine	Cheonan	n/s	FFPE	qPCR	211	189	90
20	Kang KH (49)	2013	Seoul National University Hospital	Seoul	n/s	Fresh frozen	PCR	46	37	80
21	Lim JY (50)	2013	Severance Hospital	Seoul	2009–2012	FFPE	RFLP + Seq	3130	2313	74
22	Min HS (51)	2013	Seoul National University Hospital	Seoul	2009	FFPE	Seq + IHC	255	179	70
23	Chai YJ (52)	2014	Seoul National University Hospital	Seoul	2009–2013	FFPE	Seq	137	35	26
24	Han SA (53)	2014	Kyung Hee University Hospital	Seoul	2010–2012	FFPE	qPCR	499	353	71
25	Hong AR (54)	2014	Seoul National University Hospital	Seoul	1995–2003, 2009–2012	FFPE	RFLP + Seq	2624	1912	73
26	Jung YY (55)	2015	Chung-Ang University Hospital	Seoul	2011–2012	FFPE	IHC + qPCR, RNA FISH	467	402	86
27	Lee SR (56)	2015	Ajou University	Suwon	2012	FFPE	IHC+ PCR, Seq	163	143	88
28	Na JI (57)	2015	Chonnam National University Hospital	Gwang-ju	2005–2013	FFPE	IHC + qPCR, Seq	104	71	68
29	Xing M (25)	2015	Ulsan University Hospital	Ulsan	n/s	FFPE	Seq	197	144	73
30	Kim SK (58)	2016	Samsung Medical Center	Seoul	2008–2012	FNA + FFPE	PCR + Seq	3107	2530	81
31	Kim S (59)	2017	Ajou University	Suwon	2009–2013	FFPE	PCR	1503	1171	78
32	Lee SE (60)	2017	Konkuk University Medical Center	Seoul	2010–2014	FNA	Pyroseq	769	625	81
33	Yeo MK (61)	2017	Chungnam National University School of Medicine	Daejeon	2010	FFPE	qPCR	99	88	89
34	Kim H (62)	2018	Pusan National University Hospital	Busan	2011–2012	FFPE	PCR	1411	861	61
35	Kim HJ (63)	2018	Samsung Medical Center	Seoul	2010–2015	FNA	PCR + Seq	215	173	80
36	Kim JK (64)	2018	Seoul National University Hospital	Seoul	2013–2016	FFPE	IHC + Seq	697	627	90
37	Oh HS (65)	2018	Asan Medical Center	Seoul	2011–2013	FFPE	Seq	62	57	92
38	Lee SM (66)	2019	Severance Hospital	Seoul	2011–2012	FNA	qPCR	911	717	79
39	Choden S (67)	2020	St. Mary’s Hospital	Seoul	2008–2010	FFPE	IHC + Seq	514	436	85
40	Yoon JH (68)	2020	Severance Hospital	Seoul	2015–2017	FFPE	PCR	527	428	81

AS-PCR, allele specific-polymerase chain reaction; FFPE, formalin fixed paraffin embedded tissues; FISH, fluorescence in situ hybridization; FNA, fine needle aspiration; IHC, immunohistochemistry; MCA, melting curve analysis; n/s, not specified; PCR, polymerase chain reaction; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; Pyroseq, pyrosequencing; qPCR, quantitative polymerase chain reaction; Seq, sequencing.

Table 3. Characteristics of included studies from China.

##	Author	Year	Institution	City	Study cohort	Tissue type	Technique	Total PTC	BRAF+	BRAF rate (%)
1	Gu LQ (69)	2009	Shanghai Jiaotong University School of Medicine + Yueqing People’s Hospital	Shanghai, Zhejiang	n/s	FFPE	PCR	123	42	34
2	Guan H (70)	2009	multisite	Shenyang, Shanghai, Binzhou, Heze, Qingdao	1990–2007	FFPE	Seq	1032	639	62
3	Feng L (71)	2011	Dalian Medical University	Dalian	2006–2007	FFPE	IHC	70	42	60
4	Wang W (72)	2012	The First Affiliated Hospital, Zhejiang University School of Medicine	Hangzhou	2006–2008	FFPE	PCR + Seq	208	115	55
5	Xia T (73)	2012	Affiliated Tumor Hospital of Tianjin Medical University	Tianjin	2011	Fresh frozen	PCR + Seq	110	69	63
6	Zheng X (74)	2012	Tianjin Medical University Cancer Institute and Hospital	Tianjin	1995–2000	FFPE	PCR	512	263	51
7	Zhou YL (75)	2012	First Affiliated Hospital of Wenzhou Medical College	Wenzhou	2010–2011	FNA	PCR	100	31	31
8	Gong RX (76)	2013	West China Hospital, Sichuan University	Chengdu	2009–2011	FFPE	PCR	187	119	64
9	Huang Y (77)	2013	The First Affiliated Hospital, Sun Yat-Sen University	Guangzhou	2008–2010	Fresh frozen	PCR	69	33	48
10	Guo HQ (78)	2014	Chinese Academy of Medical Science	Beijing	2010–2011	FNA	PCR	63	41	65
11	He G (79)	2014	West China Hospital, Sichuan University	Sichuan	2009–2011	FFPE	PCR	187	119	64
12	Huang FJ (80)	2014	Shanghai Jiaotong University	Shanghai	2009–2011	Fresh frozen	Seq	214	147	69
13	Liu S (81)	2014	Xian Jiaotong University Health Science Center	Xian	2011–2014	FNA	Pyroseq	132	80	61
14	Liu X (82)	2014	multisite	Shanghai, Shenyang, Qingdao, Heza, Binzhou	n/s	FFPE	PCR	408	250	61
15	Lu H (83)	2014	Chinese Academy of Medical Science	Beijing	2010–2012	FFPE	PCR + Seq	292	190	65
16	Shao H (84)	2014	Heze Municipal Hospital	Shandong	2002–2006	FFPE	Seq	200	133	67
17	Wei X (85)	2014	Tianjin Cancer Hospital	Tianjin	2011–2013	FFPE	IHC	369	297	80
18	Lu J (86)	2015	Peking Union Medical College Hospital (PUMCH)	Beijing	2013–2014	FFPE	ARMS PCR + qPCR	150	121	81
19	Qiu T (87)	2015	Chinese Academy of Medical Sciences	Beijing	2010–2014	FFPE	IHC + Seq	127	102	80
20	Shi C (88)	2015	Second Affiliated Hospital of Harbin Medical University	Harbin	n/s	FFPE	qPCR	126	87	69
21	Sun J (89)	2015	Peking Union Medical College Hospital (PUMCH)	Beijing	2010–2012	FFPE	IHC + Seq	556	419	75
22	Yang LB (90)	2015	West China Hospital	Sichuan	2013–2014	FFPE	Seq	543	170	31
23	Yu L (91)	2015	Hangzhou First Peoples Hospital	Hangzhou	2012–2013	Fresh frozen	PCR+ Seq	65	40	62
24	Zhao H (92)	2015	Chinese Academy of Medical Sciences	Beijing	2010–2012	FNA	PCR	170	114	67
25	Jin L (93)	2016	Wenzhou Medical University	Wenzhou	2009–2014	FFPE	Seq	653	416	64
26	Sun J (94)	2016	Peking Union Medical College Hospital (PUMCH)	Beijing	2010–2013	FFPE	Seq	455	343	75
27	Wen H (95)	2016	XinJiang Medical University	Urumqi	2007–2011	FFPE	Seq	26	19	73
28	Zhang B (96)	2016	Affiliated Hospital of the Academy of Military Medical Sciences	Beijing	2011–2014	FFPE	ARMS qPCR	120	106	88
29	Zheng L (97)	2016	First Affiliated Hospital of Anhui Medical University	Hefei	2009–2012	FFPE	PCR + Seq	60	40	67
30	Geng J (19)	2017	Beijing Children’s Hospital	Beijing	1994–2014	FFPE	qPCR	48	17	35
31	Li Q (98)	2017	Affiliated Cancer Hospital of Zhengzhou University	Zhengzhou	n/s	Fresh frozen	PCR + Seq	34	18	53
32	Zhang Q (99)	2017	Shanghai Tenth People’s Hospital of Tongji University School	Shanghai	2015–2016	FFPE	PCR	438	379	87
33	Guan Q (100)	2018	Fudan University Shanghai Cancer Center	Shanghai	2012–2013	FFPE	qPCR + Seq	99	63	64
34	Huang L (101)	2018	Wuhan Puai Hospital	Wuhan	2010–2016	FFPE	qPCR	184	140	76
35	Liang J (102)	2018	Beijing Cancer Hospital	Beijing	n/s	FFPE	DNA, RNA Seq	355	257	72
36	Liu Z (103)	2018	Shanghai Jiaotong University School of Medicine	Shanghai	2016	Fresh frozen	PCR + Seq	145	81	56
37	Ren H (104)	2018	Chongqing Medical University	Chongqing	2016–2017	Fresh frozen	Seq	342	270	79
38	Zheng B (105)	2018	Guangzhou Kingmed Diagnostics	Guangzhou	2014–2016	FNA	PCR	55	37	67
39	Zhou D (106)	2018	Inner Mongolia Peoples’ Hospital	Hohhot	2016–2017	FFPE	PCR	50	37	74
40	Chen B (107)	2019	Hospital of Jiangsu University	Jiangsu	2014–2017	FFPE	Seq	116	70	60
41	Gao J (108)	2020	The First Affiliated Hospital of USTC	Hefei	2017–2018	FFPE	ARMS qPCR	60	39	65
42	Huang M (109)	2019	Xijing Hospital	Xian	2018–2019	FFPE	Seq	483	419	87
43	Ji W (110)	2019	Beijing Shijitan Hospital	Beijing	2012–2015	FFPE	ARMS qPCR	89	67	75
44	Li X (111)	2019	Renji Hospital, Shanghai Jiaotong University	Shanghai	2016–2018	FNA	ARMS PCR	777	674	87
45	Li XJ (112)	2019	Jiangsu Province Hospital	Nanjing	2016–2018	FNA	qPCR	333	304	91
46	Lin ZM (113)	2019	Second Affiliated Hospital, Zhejiang University School of Medicine	Zhejiang	2016–2018	FNA	PCR	1199	791	66
47	Liu Y (114)	2019	Chongqing Medical University	Chongqing	2016–2018	FNA	PCR	207	155	75
48	Shen G (115)	2019	West China Hospital of Sichuan University	Chengdu	2012–2015	FFPE	PCR	236	147	62
49	Wang J (116)	2019	Beijing Hospital	Beijing	2015–2018	FFPE	qPCR	444	384	86
50	Yan C (117)	2019	Xijing Hospital	Shaanxi	2015–2018	FFPE	PCR	2048	1715	84
51	Yang T (118)	2019	West China Hospital, Sichuan University	Chengdu	n/s	FFPE	Seq	326	269	83
52	Zhou C (119)	2019	Liaocheng People's Hospital	Liaocheng	2015–2016	FFPE	qPCR	162	135	83

ARMS-PCR, amplification refractory mutation system-polymerase chain reaction; FFPE, formalin fixed paraffin embedded tissues; FNA, fine needle aspiration; IHC, immunohistochemistry; n/s, not specified; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; Pyroseq, pyrosequencing; qPCR, quantitative polymerase chain reaction; Seq, sequencing.

Table 4. Characteristics of included studies from India.

##	Author	Year	Institution	City	Study cohort	Tissue type	Technique	Total PTC	BRAF+	BRAF rate (%)
1	Chakraborty A (120)	2012	Tata Memorial Hospital	Mumbai	2002–2006	Fresh frozen	PCR + Seq	86	46	53
2	Khan MS (121)	2014	Sher-I-Kashmir Institute of Medical Sciences	Srinagar	2010–2012	FFPE	PCR	42	15	36
3	Agarwal S (122)	2016	All India Institute of Medical Sciences	New Delhi	2015–2016	FFPE	Seq	40	19	48
4	Nair CG (123)	2017	Amrita Institute of Medical Sciences	Kochi	2012	FFPE	PCR	59	30	51
5	Ahmad F (124)	2018	Research and Development Division of SRL	Mumbai	n/s	FFPE	PCR + Seq	70	35	50
6	Fonseca D (125)	2018	Basavatarakam Indo American Cancer Hospital	Telangana	2015–2018	FFPE	IHC	23	11	48
7	George N (126)	2018	Sanjay Gandhi Postgraduate Institute	Lucknow	2000–2014	FFPE	PCR	109	56	51
8	Hemalatha R (127)	2018	Christian Medical College	Vellore	n/s	FNA	Seq	53	19	36
9	Krishnamurthy A (128)	2018	Cancer Institute (WIA)	Chennai	2005–2006	FFPE	IHC + qPCR	79	25	32

IHC, immunohistochemistry; FFPE, formalin fixed paraffin embedded tissues; FNA, fine needle aspiration; n/s, not specified; qPCR, quantitative polymerase chain reaction; Seq, sequencing

Table 5. Characteristics of included studies from other Asian countries and regions.

Country/region	##	Author	Year	Institution	City	Study cohort	Tissue type	Technique	Total PTC	BRAF+	BRAF rate (%)
Saudi Arabia	1	Abubaker J (129)	2008	King Faisal Specialist Hospital	Riyadh	1988–2004	FFPE	Seq	296	153	52
	2	Schulten HJ (130)	2012	King Abdulaziz University + King Faisal Specialist Hospital	Jeddah	1995–2011	FFPE	PCR, Seq	213	87	41
	3	Zou M (131)	2014	King Faisal Specialist Hospital	Riyadh	1987–2006	Fresh frozen	Seq	88	42	48
	4	Qasem E (132)	2015	King Faisal Specialist Hospital	Riyadh	2008–2011	FFPE	Seq	243	105	43
	5	Murugan AK (133)	2016	King Faisal Specialist Hospital	Riyadh	n/s	FFPE	Seq	201	95	47
	6	Alzahrani AS (20)	2017	King Faisal Specialist Hospital	Riyadh	1998–2015	FFPE	Seq	79	19	24
Iran	1	Mohammadi-Asl J (134)	2009	Tehran University of Medical Science	Tehran	2007–2008	FFPE	PCR-RFLP	28	20	71
	2	Ranjbari N (135)	2013	Imam Khomeini Hospital	Ahvaz	2000–2010	FFPE	PCR-RFLP	63	49	78
	3	Daliri M (136)	2014	Ghaem Hospital	Mashhad	1999–2014	FFPE	PCR-RFLP	69	28	41
	4	Zarkesh M (137)	2018	Erfan Hopital + Atiyeh Hospital	Tehran	2015–2016	Fresh frozen	Seq	60	24	40
	5	Ghasemi M (138)	2019	Khalili Hospital	Shiraz	2012–2017	FFPE	PCR-RFLP	79	65	82
Iraq	1	Salih A (139)	2017	Duhok Private Medical Laboratory + Vin Private Medical laboratory	Duhok	2011–2015	FFPE	qPCR	47	12	26
Kazakhstan	1	Kumagai A (22)	2007	Medical Institute of Semipalatinsk	Semipalatinsk	2004–2006	FNA	PCR-RFLP	76	19	25
	2	Tlegenov AS (140)	2018	Kazakh Scientific Research Institute of Oncology and Radiology	Almaty	2016–2017	Fresh frozen	IHC	92	62	67
Myanmar	1	Than MM (141)	2017	Yangon University of Medicine	Yangon	2014–2016	FFPE	PCR	44	10	23
Thailand	1	Choden S (142)	2020	Chulalongkorn University	Bangkok	2007–2017	FFPE	IHC	476	290	61
Vietnam	1	Vuong HG (27)	2016	Cho Ray Hospital	Ho Chi Minh	2011–2014	FFPE	AS-PCR	53	44	83
Indonesia	1	Brahma B (143)	2013	Mangunkusumo Hospital Medical Faculty University	Jakarta	2010–2011	FNA	PCR RFLP	44	17	39
	2	Kristiani E (144)	2016	Siloam Hospitals Lippo Village	Tangerang	n/s	FFPE	IHC	50	17	34
Singapore	1	Yang P (145)	2015	Singapore National University Hospital	Singapore	n/s	FFPE	IHC	49	39	80
	2	Goh X (146)	2019	Singapore National University Hospital	Singapore	2010–2012	FFPE	Seq	75	42	56
Taiwan	1	Liu RT (147)	2005	Chang Gung Memorial Hospital	Kaohsiung	1997–2002	FFPE	Seq	105	49	47
	2	Chang YS (148)	2013	China Medical University Hospital	Taichung	n/s	Fresh frozen	Seq	52	32	62
Hong Kong	1	Lo CC (149)	2004	University of Hong Kong	Hong Kong	2001–2003	FFPE	Seq	34	17	50
	2	Law Y (150)	2009	The Hong Kong Polytechnic University	Hong Kong	n/s	FFPE	PCR RFLP	50	24	48
Philippines	1	Navarro-Locsin CG (151)	2016	St. Luke’s Medical Center	Quezon City	2010–2012	FFPE	Seq + qPCR	65	25	38
	2	Espiritu GAM (152)	2019	Makati Medical Center	Makati	2016	FFPE	Seq	17	12	71

AS-PCR, allele specific-polymerase chain reaction; FFPE, formalin fixed paraffin embedded tissues; FNA, fine needle aspiration; IHC, immunohistochemistry; n/s, not specified; PCR-RFLP, polymerase chain reaction-restriction fragment length polymorphism; qPCR, quantitative polymerase chain reaction; Seq, sequencing

Table 6. Summary on BRAF rate in PTC from Asian countries and regions.

Region	Country/region	No. of studies	Year of publication	Total PTC*	BRAF-positive	BRAF rate (%)
East Asia	Japan	9	2007–2018	986	696	71
	South Korea	40	2005–2020	20599	15558	76
	China	51	2009–2019	15509	11038	71
	Taiwan	2	2005, 2013	157	81	52
	Hong Kong	2	2004, 2009	84	41	49
South Asia	India	9	2012–2018	561	256	46
Central Asia	Kazakhstan	2	2007, 2018	168	81	48
Middle East	Saudi Arabia	5	2008–2017	1041	482	46
	Iran	5	2008–2017	346	198	57
	Iraq	1	2017	47	12	26
Southeast Asia	Myanmar	1	2017	44	10	23
	Thailand	1	2020	476	290	61
	Vietnam	1	2016	53	44	83
	Indonesia	2	2013, 2016	94	34	36
	Singapore	2	2015, 2019	124	81	65
	The Philippines	2	2016, 2019	82	37	45

*, pediatric cases were excluded if indicated in the original studies (one series from Japan, China, and Saudi Arabia). PTC, papillary thyroid carcinoma.

Nine Japanese studies included 986 PTCs with an average BRAF rate 70.6% (Table 1). Korean series were more extensive, encompassing 20,599 PTCs in 40 studies with resultant BRAF prevalence 75.5% (Table 2). The largest number of reports were from China (n=51; 15,509 PTCs), which showed 71.2% BRAF rate (Table 3). In contrast to the countries above, Indian institutions started to report their findings quite recently, so far providing results on 561 PTCs from 9 centers across the country, averaging 45.6% prevalence of BRAF^V600E mutation (Table 4). Five studies from Saudi Arabia (mean BRAF rate 46.3%) along with less abundant reports from other Asian countries and regions, including Iran, Iraq, Kazakhstan, Myanmar, Thailand, Vietnam, Indonesia, Singapore, Taiwan, Hong Kong, and Philippines are shown in Table 5. Figure 2 summarizes BRAF prevalence on the color map. We could not find any relevant publications from such large and highly populated Asian countries as Pakistan, Bangladesh, and Malaysia.

Figure 2.

Prevalence of BRAF^V600E mutation in PTC from Asian countries and regions. PTC, papillary thyroid carcinoma.

After grouping countries by geographic region, we found that the highest rate of BRAF^V600E was reported in PTC series from East Asia (76.4%). Much lower rate (45–48%) was seen in PTC cohorts originated from South Asia, Central Asia, and the Middle East while the Southeast Asian series were in between (57%). At the same time, it should be noted that the level of evidence per country demonstrated by the number of studies, number of institutions, and the total sample size was highly heterogeneous (Figure 3A,B,C). For instance, 90.2% out of all PTCs with known BRAF status were reported from China, South Korea, and Japan—countries belonging to East Asia. After adjusting the sample size to such variables as the country’s population and incidence of thyroid carcinoma, we concluded that the South Korean series provided the best evidence on BRAF mutation prevalence at the national level (Figure 3D).

Figure 3.

Summary statistics of publications on BRAF mutation by country and region. (A) Total number of studies, (B) total sample size, (C) number of institutions, and (D) ratios of total sample size per annual incidence of thyroid carcinoma and total sample size per population.

Within country heterogeneity

As it could be seen from Tables 1-5 containing original data, there was a considerable heterogeneity of BRAF rate within most of the countries, the best illustrated in Japan (42–86%), South Korea (32–92%), and China (31–87%). Furthermore, such heterogeneity was found even within the same institution. For example, a group from Yamanashi, Japan reported two series of PTC with BRAF rate 42% and 82% (21,27). Similar discordances were found in studies from Sichuan, China (31% vs. 64%), Daejeon, Korea (53% vs. 89%), and others (31,44,61,65,79,90).

It is known that the detection rate of BRAF may depend on a large variety of factors. As per the data collection form, we were able to assess several of them. First, pediatric PTCs, where indicated, had lower BRAF prevalence compared to the baseline rate for the country; however this assumption was based only on a very limited number of studies with pediatric PTCs (18-20,28). Further analysis of factors potentially contributing to the within country heterogeneity was limited to China and South Korea, which had enough studies to be dichotomized by a variable of interest. We found that studies employed fresh frozen tissue and fine-needle aspirates showed a significantly higher rate of BRAF compared to those used formalin-fixed paraffin-embedded tissues (78% vs. 66% in Chinese series and 79% vs. 74% in Korean series; P<0.01). To evaluate a possibility of time trend, we divided studies into those enrolled samples before and after 2010 (only when this was indicated). It was found that the recent PTC series demonstrated a higher rate of BRAF—80% vs. 58% in Chinese series and 76% vs. 72% in Korean series (P<0.01).

Discussion

PTC is the most common malignancy of the endocrine system (153). The prevalence and annual incidence of PTC has approximately triplicated in the last three decades (154). Thyroid carcinoma ranks at the ninth place for incidence rates among all cancers (155). PTC constitutes up to 90% of thyroid carcinoma in contemporary series (156). The estimated age-standardized rate of thyroid cancer incidence in women is 3 times higher than that in men. Thyroid cancer was estimated to be the third most common malignant tumor in women in the USA and the fifth most common in Asia (157). Furthermore, the incidence rate in countries having a high human development index is 4–5 times greater than in those with the low index, while mortality rate does not differ between them (158). This is explained by the early diagnostics, advanced treatment options, and the development of the health care system in general. According to the GLOBOCAN 2018, Asia is the main continent contributing to the epidemiologic profile of thyroid cancer on a worldwide scale (157). For instance, Asia accounted for about 60% of thyroid carcinoma cases in terms of incidence, five-year prevalence, and mortality (157).

While Western opinion is dominating in the contemporary international guidelines on reporting and management of thyroid tumors, a wealth of evidence suggests that there are considerable differences between Western and Asian series of PTC, widely spanning from epidemiology and biology to specific practice patterns and treatment strategies (159-161). BRAF^V600E mutation placed on the molecular end of the spectrum is a good example of such disparity. While European and American studies reported 30–60% rate of BRAF mutation in PTC, Asian series found it to be much more prevalent (11-15).

It is important that detection of BRAF^V600E in PTC may have diagnostic significance in preoperative cytologic aspirates and also in surgical specimens (10,12,43,78,96,101,112). More recently BRAF was suggested as an important adjunct in predicting adverse prognosis in PTC, therefore getting wide recognition as a biomarker tailoring postoperative management of PTC patients (10,25). Furthermore, targeting of BRAF is considered as a promising strategy for patients with BRAF-mutant advanced thyroid cancer. In addition, recent studies found that concomitant BRAF and TERT promoter mutations in PTC patients were associated with a poor clinical outcome such as tumor aggressiveness and recurrence (162,163). Therefore, establishing a rate of BRAF on the regional and even institutional level is of practical significance. For instance, BRAF testing for rendering malignancy in preoperative thyroid fine-needle aspirates is much effective in regions with a high prevalence of BRAF mutation (39,164).

In this systematic review, we investigated a rate of BRAF mutation in a series of more than 40,000 PTCs originated from 16 Asian countries and regions, published in 2004–2020. The highest prevalence of BRAF^V600E was reported in East Asian countries (>70%), followed by Southeast Asia (57%), and a region encompassing South Asia, Central Asia, and the Middle East (<50%) (Figure 2).

With this largest series to date, we could confirm that PTCs from Asian continent, particularly from East and Southeast Asia are much more saturated with BRAF mutation than those from Europe. Studies from Eastern (Poland, Czech Republic), Central (Germany), and Southern Europe (Italy, Spain, Portugal) consistently reported BRAF prevalence in PTC below 45% (14,165-172). Series from North (USA) and South America (Brazil) also showed BRAF rate lower than in Asia (168,173,174). Although we did not perform extensive search on Western series, existing evidence based on the above studies from leading thyroid cancer centers is sufficient to illustrate a substantial difference between Asian and Western PTC.

In addition to differences among geographic regions, we found a considerable within-country heterogeneity of BRAF rate. Causes of geographic heterogeneity are multifactorial, which could be due to different etiology or study methodology, including selection bias, detection techniques, and many more. There are several etiological factors associated with the development of thyroid carcinoma, of which ionizing radiation has been the well-documented environmental cause of PTC (175). Other factors include genetic predisposition via single nucleotide polymorphisms, hormonal influence, and dietary components, such as iodine and nitrates (24,176,177). The discrepancy identified in the BRAF^V600E frequency among different regions of Asia might be due to the variation in the iodine intake. Dietary iodine intake varies in population from as low as 20 µg/d in iodine-deficient areas to as high as 1,000 µg/d in iodine-sufficient areas, where seaweed is rich in iodine, such as Japan and South Korea. Iodine intake is considered as a major risk factor for thyroid tumorigenesis especially in iodine-deficient regions (178). Thyroid follicular cells divide slowly in normal conditions but in the case of iodine deficiency, the proliferation rate of follicular cells increases due to growth of serum TSH level. Excessive proliferation of thyroid follicular cells makes their genome more susceptible to molecular alterations such as BRAF^V600E mutation. The overall incidence of histological subtypes of thyroid cancer depends upon level of iodine intake, for instance, follicular thyroid carcinoma is more prevalent in iodine-deficient areas while PTC incidence is greater in high iodine intake areas (179). In China, BRAF^V600E mutation is higher in regions where drinking water is rich in iodine compared to mildly deficient iodine intake (70). Interestingly, the most recent studies showed that both low iodine intake and excessive iodine intake served as a significant risk factor for the occurrence of BRAF mutations in the thyroid, therefore, may be risk factors for the development of PTC (63,180).

Nevertheless, we do not expect that our BRAF prevalence map (Figure 2) would match with the iodine status map due to a high complexity and interplay of all the factors that contributed to the variation of BRAF rate in different series of PTC. Our data collection protocol did not require extracting additional information about baseline characteristics of the PTC cohorts, such as age, gender, distribution of tumors by histological types, clinical stage, and other important clinicopathological variables. Further systematic review and meta-analysis studies should consider matching PTC series with the major characteristics of enrolled patients, which may help to elucidate certain tumor-specific parameters as a source of heterogeneity.

Apart from the above issues, technical aspects could greatly contribute to heterogeneity of results. We revealed that studies employed fresh frozen tissue and fine-needle aspirates showed significantly higher rates of BRAF compared to those used formalin-fixed paraffin-embedded tissues, which could be explained by the poorer DNA quality in the latter specimens. There was a wide variety of molecular methods used across the Asian studies, from a simple gel-based polymerase chain reaction (PCR) and routine Sanger sequencing to highly-sensitive real-time PCR, pyrosequencing, and next-generation sequencing. In addition, mutation-specific immunohistochemistry with VE1 antibody employed as an alternative for genotyping to detect BRAF^V600E mutation got increasing adoption in the recent studies.

All the multitude of factors described above could contribute to the geographic heterogeneity of BRAF mutation whether within Asia or between Asian and Western series. From the pathologist’s standpoint, one of the potential reasons behind the difference is the inter-observer variability in encapsulated follicular lesions between Asian and Western practices (181). Most of Western FVPTCs are classified as benign follicular adenomas or follicular carcinomas in Asia. Follicular variant of PTC is associated with RAS driver mutation (2) and sharp increase of this mutation in PTC was documented in US (173) while RAS-mutated FVPTCs are rare in Asian series (14), making the BRAF mutation rate high in Asian PTC.

This study has several limitations, which are inherently coupled with drawbacks of the original studies, including lack of data about clinicopathological characteristics of patients and histological type of PTC. Despite of the huge amount of data accumulated on BRAF mutation prevalence in Asia, more than 90% of PTCs were reported from Japan, South Korea, and China. The evidence from other countries and regions of Asia is very limited (Figure 3). Many of the studies were performed on less than 100 samples, which could not be considered sufficient to draw relevant conclusions about the nationwide rate of BRAF mutation. Our estimates suggest that 300–400 PTC cases should be enrolled to qualify a well-powered study. However, dealing with a relatively large amount of samples may be challenging in the limited resources settings, which is a case of most Asian countries. Recently we developed and validated a low-cost testing algorithm to estimate the prevalence of BRAF^V600E in large cohort studies based on mutation-specific immunostaining applied to small-sized specimens (67,142,182).

Conclusions

Our study found that the highest rate of BRAF^V600E was reported in the PTC series from East Asia (76.4%), contributed by South Korea (75.5%), China (71.2%), and Japan (70.6%). Much lower rate (45–48%) based on the limited number of studies was seen in PTC cohorts originated from South Asia, Central Asia, and the Middle East while the Southeast Asian series were in between (57%). Asian series demonstrated considerable among and within countries heterogeneity regarding the prevalence of BRAF^V600E mutation in PTC. Pooled Asian series of PTC showed a higher prevalence of BRAF^V600E than in Western series. Causes of geographic heterogeneity, whether genuine (etiology, genetics) or methodology-related (selection bias, detection techniques, and more) should be further investigated.

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