# A Systematic Review and Meta-analysis on the Occurrence of Biomarker Mutation in Colorectal Cancer among the Asian Population

Authors: Hafeez Afolabi; Salzihan Md Salleh; Zaidi Zakaria; Ch’ng Ewe Seng; Siti Norasikin Binti Mohd Nafil; Ahmad Aizat Bin Abdul Aziz; Yusuf Wada; Ahmad Irekeola
Journal: BioMed Research International
 (2022)

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## Abstract

Globally, colorectal carcinoma (CRC) is the third most common cancer and the third major cause of cancer-related death in both sexes. KRAS and BRAF mutations are almost mutually exclusively involved in the pathogenesis of CRC. Both are major culprits in treatment failure and poor prognosis for CRC.Method. A systematic review and meta-analysis of various research was done following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. This trial is registered with PROSPERO CRD42021256452. The initial search included 646 articles; after the removal of noneligible studies, a total of 88 studies was finally selected. Data analysis was carried out using OpenMeta Analyst and Comprehensive Meta-Analysis 3.0 (CMA 3.0) software to investigate the prevalence of KRAS and BRAF mutations among patients with CRC in Asia. Results. The meta-analysis comprises of 25,525 sample sizes from Asia with most being male 15,743/25525 (61.7%). Overall prevalence of KRAS mutations was (59/88) 36.3% (95% CI: 34.5-38.2) with I2=85.54% (P value < 0.001). In 43/59 studies, frequency of KRAS mutations was majorly in codon 12 (76.6% (95% CI: 74.2–78.0)) and less in codon 13 (21.0% (95% CI: 19.1-23.0)). Overall prevalence of BRAF mutations was 5.6% (95% CI: 3.9-8.0) with I2=94.00% (P value < 0.001). When stratified according to location, a higher prevalence was observed in Indonesia (71.8%) while Pakistan has the lowest (13.5%). Conclusion. Total prevalence of KRAS and BRAF mutations in CRC was 36.6% and 5.6%, respectively, and the results conformed with several published studies on KRAS and BRAF mutations.


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## Body

## 1. Introduction

Globally, cancer is a serious medical burden, and it is one of the main causes of death and morbidity throughout the world [1, 2]. With more than 1.8 million new CRC diagnoses and 0.86 million deaths globally in 2018 [3], colorectal carcinoma (CRC) is the third most common cancer and the third major cause of cancer-related death in both sexes [4]. The occurrence of CRC differs globally; the overall highest incidence rates of CRC may be seen in the United States, Canada, Europe, and Australia, whereas the lowest rates can be found in South-Central Asia and Africa [2]. However, the prevalence is rising exponentially in Asia [5], especially as the number of new cases of CRC is rapidly growing in Asia-Pacific thus, accounting for more than half of all new cases diagnosed globally [5, 6]. CRC prevalence rates vary due to several factors such as ethnicity, genetics, regions, and lifestyles. It is reported to be 38 percent among Caucasians, 40 percent among Asians, and just 21 percent among Africans [6]. Pathogenesis of CRC involves gene mutation, mostly involving the MAPK-ERK cascade, for which the KRAS and BRAF are exclusively involved.Nation-wise, the prevalence of KRAS and BRAF mutation varies regionally, and this is majorly due to genetic changes from heterogeneously related races [6]. From the World Health Organization (WHO) regional grouping, the prevalence of KRAS mutation among constituting nations with CRC is 30.23%, 35.12%, 31.83%, 33.17%, and 32.64% for the EMRO, EURO, PAHO, SEARO, and WAPRO, respectively, [5]. Colorectal carcinogenesis is a multisignalling process involving four major pathways: the Wnt-β catenin pathway, MAPK/ERK pathway, PI3K/Akt pathway, and p53 pathway. Each pathway involves several sequential genetic modifications, such as chromosomal anomaly, gene mutations, and/or epigenetic changes, that turn normal colonic epithelium into colorectal cancer [7] [8]. Like the KRAS gene, BRAF is also part of the Ras family that targets the RAS/RAF/MEK/ERK pathway; together, they both account for 7-25% and 5-20% of all cancers as well as 30-45% and 8–10% of CRC for both KRAS and BRAF, respectively [8, 9]. Mutations in KRAS and BRAF are almost mutually exclusive. The detection or testing for KRAS and BRAF gene mutation presents a blueprint and change to standard diagnostic guidelines for inpatient care and creates a major development in early decision-making in personalizing cancer care. The identification of this mutation would be crucial for the prognosis of CRC patients. Early diagnosis and treatment will improve patients’ standard of health, increase their chances of survival, and lower morbidity and mortality. The poor prognosis of metastatic CRC has fuelled continued efforts to identify therapeutic options that will improve patient outcomes via detailed gene profiling such as in KRAS and BRAF mutations.Ras proteins are tiny guanosine triphosphatases (GTPases) to which the KRAS and BRAF genes belong. Through the GTPase cascade, they govern a variety of intracellular activities such as proliferation, differentiation, immune response, and survival rate [10]. The understanding of genetic alterations (such as in KRAS and BRAF mutations) in metastatic CRC (mCRC) via the use of gene profiling can be a catch point in explaining the gene’s resistance to antiepidermal growth factor receptor (EGFR) antibody management [11] and as a prognostic predictor in arresting the progress of CRC [12] [8, 13]. Both KRAS and BRAF are downstream EGFR oncogenes, for which their mutations can activate EGF receptor signalling in cancer cells and are linked with poor prognosis in the CRC. Hence, certain aberrations or mutations that have a well-established prognostic and predictive blueprint in CRC are now regularly examined as a component of clinical therapy [14]. Through this study, the authors intend to determine the prevalence of KRAS and BRAF gene mutations in CRC and whether the prevalence of mutated KRAS and mutated BRAF genes in colorectal carcinoma differs among patients in Asia via literature review and meta-analysis to provide a very accurate KRAS and BRAF mutation estimates.


## 2. Materials and Methods

The present study is a systematic review and meta-analysis of various researched and published papers that were carried out following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) [15]. The study protocol was registered with PROSPERO (registration number: CRD42021256452).


### 2.1. Literature Search and Selection Criteria

In the study, articles were retrieved from three electronic databases (PubMed, Scopus, and ScienceDirect); the eligible studies were searched and assessed using a combination of relevant keywords: (“colorectal cancer” OR “colon cancer” OR “metastatic colon cancer” OR “metastatic colorectal cancer” OR “CRC” OR “Rectum”) and (“BRAF” OR “BRAF” OR “c-BRAF” OR “KRAS” OR “K-RAS” OR “c-KRAS”) and (“Asia”). The full details of the search strategies for this study are in the supplementary search strategic file. A comprehensive search for the most relevant studies was carried out by combing through titles, keywords, and abstracts of various papers. The initial search included 646 articles (Figure1) which were performed on 10 April 2021 via the EndNote X9 software; references of all assessed studies were exported to the software after which, duplications were then removed. The inclusion criteria for the studies selected for this meta-analysis include cross-sectional studies, cohort studies, or case series carried out to investigate the frequency of KRAS or BRAF gene mutations in colorectal cancer patients in Asia. Also included are studies on KRAS and BRAF gene mutations from fresh frozen, formalin-fixed paraffin-embedded (FFPE), or biopsied colorectal carcinoma specimens. Also, KRAS and BRAF studies involving more than one sample size and all related papers published at valid international summits were included. No limit is set on methods for determining gene mutations. The exclusion criteria include (1) studies not associated with frequency of KRAS and BRAF gene mutations, (2) studies that investigated just one of either codon 12 or codon 13 of KRAS gene mutation, (3) reviews and case reports, (4) KRAS and BRAF gene mutations that are related to cell lines and animal studies, and (5) studies that investigated BRAF gene mutation through KRAS-positive patients [16]. All authors were involved in the study screening, selection, and assessment criteria. Two authors (A.H.A. and A.A.I.) independently screened the articles based on title and abstract. This was proceeded by the assessment of the full texts. Any discords during the screening process were resolved by discussion with other authors in the study.Figure 1
Summary of article identification and selection process.


### 2.2. Data Extraction and Quality Assessment

The data extraction was carried out by using an Excel spreadsheet. Two reviewers (H.A.A. and A.A.I.) independently vetted the titles and abstracts and extracted crucial information required; study I.D, publication year, period and design, gender, data on the mutation of KRAS, and BRAF prevalence among patients diagnosed with colorectal cancer in Asia were diligently extracted. Any inconsistencies were handled through conversation with a third reviewer (S.M.S) to prevent any sort of prejudice, and any discrepancies were sorted out via dialogue involving other reviewers to avoid any kind of bias. The quality of the methodological approach for the studies included was appraised independently by two authors (A.H.A. and Y.W.) via the Joanna Briggs Institute (JBI) critical appraisal checklist for prevalence data [17] (Supplementary JBI file). A score of 1 for “yes” and 0 for other parameters was allotted to obtain a sum quality score that ranges between 0 and 9. Studies with a final score of 7–9 were chosen to be of desirable quality. The studies within the latter acceptable score range were included in the data extraction phase of the meta-analysis.


### 2.3. Data Synthesis and Analysis

Data analysis was carried out via the use of OpenMeta Analyst and Comprehensive Meta-Analysis 3.0 (CMA 3.0) software [18]. The prevalence of KRAS and BRAF gene mutations among patients with colorectal carcinoma in Asia was calculated, and subgroup analysis was also carried out on location, tumour stage, tumour grade, and period of study. A random-effect model through the DerSimonian-Laird method of the meta-analysis was employed to obtain the pooled estimates of the reported KRAS and BRAF gene mutation cases. Further, to ascertain the study quality, possible publication bias was scrutinized by creating a funnel plot. The asymmetry of the plot was further investigated via Egger’s regression test [19]. The heterogeneities of study-level estimates were determined by Cochran’s Q test and quantified using I2 statistics. I2 values of 25%, 50%, and 75% were considered low, moderate, and high heterogeneities, respectively [20]. For all tests, a P value < 0.001 was labelled statistically significant.


## 2.1. Literature Search and Selection Criteria

In the study, articles were retrieved from three electronic databases (PubMed, Scopus, and ScienceDirect); the eligible studies were searched and assessed using a combination of relevant keywords: (“colorectal cancer” OR “colon cancer” OR “metastatic colon cancer” OR “metastatic colorectal cancer” OR “CRC” OR “Rectum”) and (“BRAF” OR “BRAF” OR “c-BRAF” OR “KRAS” OR “K-RAS” OR “c-KRAS”) and (“Asia”). The full details of the search strategies for this study are in the supplementary search strategic file. A comprehensive search for the most relevant studies was carried out by combing through titles, keywords, and abstracts of various papers. The initial search included 646 articles (Figure1) which were performed on 10 April 2021 via the EndNote X9 software; references of all assessed studies were exported to the software after which, duplications were then removed. The inclusion criteria for the studies selected for this meta-analysis include cross-sectional studies, cohort studies, or case series carried out to investigate the frequency of KRAS or BRAF gene mutations in colorectal cancer patients in Asia. Also included are studies on KRAS and BRAF gene mutations from fresh frozen, formalin-fixed paraffin-embedded (FFPE), or biopsied colorectal carcinoma specimens. Also, KRAS and BRAF studies involving more than one sample size and all related papers published at valid international summits were included. No limit is set on methods for determining gene mutations. The exclusion criteria include (1) studies not associated with frequency of KRAS and BRAF gene mutations, (2) studies that investigated just one of either codon 12 or codon 13 of KRAS gene mutation, (3) reviews and case reports, (4) KRAS and BRAF gene mutations that are related to cell lines and animal studies, and (5) studies that investigated BRAF gene mutation through KRAS-positive patients [16]. All authors were involved in the study screening, selection, and assessment criteria. Two authors (A.H.A. and A.A.I.) independently screened the articles based on title and abstract. This was proceeded by the assessment of the full texts. Any discords during the screening process were resolved by discussion with other authors in the study.Figure 1
Summary of article identification and selection process.


## 2.2. Data Extraction and Quality Assessment

The data extraction was carried out by using an Excel spreadsheet. Two reviewers (H.A.A. and A.A.I.) independently vetted the titles and abstracts and extracted crucial information required; study I.D, publication year, period and design, gender, data on the mutation of KRAS, and BRAF prevalence among patients diagnosed with colorectal cancer in Asia were diligently extracted. Any inconsistencies were handled through conversation with a third reviewer (S.M.S) to prevent any sort of prejudice, and any discrepancies were sorted out via dialogue involving other reviewers to avoid any kind of bias. The quality of the methodological approach for the studies included was appraised independently by two authors (A.H.A. and Y.W.) via the Joanna Briggs Institute (JBI) critical appraisal checklist for prevalence data [17] (Supplementary JBI file). A score of 1 for “yes” and 0 for other parameters was allotted to obtain a sum quality score that ranges between 0 and 9. Studies with a final score of 7–9 were chosen to be of desirable quality. The studies within the latter acceptable score range were included in the data extraction phase of the meta-analysis.


## 2.3. Data Synthesis and Analysis

Data analysis was carried out via the use of OpenMeta Analyst and Comprehensive Meta-Analysis 3.0 (CMA 3.0) software [18]. The prevalence of KRAS and BRAF gene mutations among patients with colorectal carcinoma in Asia was calculated, and subgroup analysis was also carried out on location, tumour stage, tumour grade, and period of study. A random-effect model through the DerSimonian-Laird method of the meta-analysis was employed to obtain the pooled estimates of the reported KRAS and BRAF gene mutation cases. Further, to ascertain the study quality, possible publication bias was scrutinized by creating a funnel plot. The asymmetry of the plot was further investigated via Egger’s regression test [19]. The heterogeneities of study-level estimates were determined by Cochran’s Q test and quantified using I2 statistics. I2 values of 25%, 50%, and 75% were considered low, moderate, and high heterogeneities, respectively [20]. For all tests, a P value < 0.001 was labelled statistically significant.


## 3. Result

This section is divided into subheadings to provide a concise and precise description of the experimental results and their interpretation, as well as the experimental conclusions that can be drawn from the outcomes.


### 3.1. Search Results and Study Selection

A total of 646 records were obtained by searching three electronic databases. After eliminating duplications and studies that do not favour the inclusion criteria, the remaining 498 were screened via titles and abstracts and by further excluding 261 records that satisfied the exclusion criteria and another 115 records that were done outside Asia; then, 122 records were left. Upon further scrutiny, another 34 records that did not merit the inclusion criteria as depicted in Figure1 above were excluded. Finally, a total of 88 unique records were confirmed eligible to be included in the meta-analysis. Among these later 88 eligible studies, 59 reported on KRAS gene mutation, and 29 reported on BRAF gene mutation. Thus, a total of 88 studies were selected for this meta-analysis.


### 3.2. Characteristics of the Eligible Studies

The characteristics of studies on KRAS and BRAF mutations are illustrated in Tables1 and 2, respectively. The meta-analysis study comprises of 25,525 sample sizes; all studies were from the Asian region with the male patient being most of the total participants, 15,743 out of 25525 (61.7%). The comprehensive characteristics of the included studies are illustrated in Table 1.Table 1
Major characteristics of the prevalence of KRAS screening studies that were included in the meta-analysis.
S/N
Author
Year
Location
Male,n (%)
Age
Sample size
Tumour stage (early stage)∗
Tumour stage (late stage)∗
Tumour location (colon)∗
Tumour location (rectum)∗
Tumour grade (poorly differentiated)∗
Tumour grade (moderately differentiated)∗
Tumour grade (well-differentiated)∗
Method
Total KRAS mutation (%)
KRAS (codon 12) %
KRAS (codon 13) %
1
Al-Allawi et al., 2012 [21]
2012
Iraq
54
55.4
±
15.25
50
50
50
44
56
18
62
20
Sequencing
48
91.7
8.3
2
Amirifard et al., 2016 [22]
2016
Iran
79
51.5
±
12.6
33
0
100
55
45
9
21.2
69.8
Sequencing
36.4
91.7
8.3
3
Awidi et al., 2019 [23]
2019
Jordan
60
58 (19-83)
190
NR
NR
97.4
2.63
NR
NR
NR
Sequencing
48.4
81.5
17.4
4
Bader and Ismail, 2014 [24]
2014
Saudi Arabia
58
55 (26-90)
83
13.3
86.7
76
24
9.6
82
8.4
Sequencing
42.2
88.6
11.4
5
Bakarman and AlGarni, 2019a [2]
2019
Saudi Arabia
56
57
±
13
279
34
56.6
59.5
40.5
6.5
73.8
5.7
Sequencing
12.5
NR
NR
6
Bando et al., 2012 [25]
2012
Japan
60
NR
109
NR
NR
69.7
30.2
NR
NR
NR
Sequencing
30.3
78.8
21.2
7
Bishehsari et al., 2006 [26]
2006
Iran
57
NR
182
NR
NR
71
29
NR
NR
NR
Sequencing
37.4
66.2
32.4
8
Bagadi et al., 2012 [27]
2012
India
74
56 (23-93)
100
22.5
77.5
78
22
NR
NR
NR
Sequencing
23
87
13
9
Chen et al., 2009 [28]
2009
Taiwan
54
25-90
90
NR
NR
68.9
31.1
NR
NR
NR
Sequencing
35.6
75
25
10
Dallol et al., 2016 [29]
2016
Saudi Arabia
59
NR
99
NR
NR
72.7
27.3
10.1
61.6
16.2
HTT-sequencing
35.4
NR
NR
11
Deng et al., 2015 [30]
2015
China
59
NR
433
50.3
49.7
73.9
26.1
21.2
49.2
21.9
Sequencing
38.3
74.1
25.9
12
Dolatkhah et al., 2015 [31]
2015
Iran
77
77.6 (27–90)
30
36.7
46.7
NR
NR
6.7
26.7
50
Sequencing
20
NR
NR
13
Dolatkhah et al., 2016 [32]
2016
Iran
65
61.9
±
15.34
100
37
29
72
28
3
22
49
Sequencing
26
61.5
34.6
14
Elbjeirami and Sughayer, 2012 [33]
2012
Jordan
55
55 (22-74)
100
5
95
78
22
NR
NR
NR
Sequencing
44
88.6
11.4
15
Elsamany et al., 2014 [34]
2014
Saudi Arabia
54
NR
116
23.3
76.7
67.8
32.2
29.3
58.7
12
Sequencing
37.1
NR
NR
16
Fu et al., 2019 [35]
2019
China
60
60 (14-96)
5495
NR
NR
50.1
49.9
6.5
71.3
24.4
HRMS
37.7
75.1
22.2
17
He et al., 2020 [36]
2020
China
62
59 (26-83)
194
4.1
83
72.6
27.3
45.9
NR
NR
Sequencing
42.3
63.4
17.1
18
Hsieh et al., 2012 [37]
2012
Taiwan
NR
NR
182
NR
NR
NR
NR
NR
NR
NR
Sequencing
33.5
NR
NR
19
Hamzehzadeh et al., 2018 [38]
2018
Iran
59
57 (27-86)
87
NR
NR
87.3
12.6
4.6
77
18.3
Sequencing
28.7
72
28
20
Jauhri et al., 2017a [39]
2017
India
61
NR
112
23.2
76.8
82.1
17.9
NR
NR
NR
Sequencing
35.7
67.5
17.5
21
Jazi et al., 2017 [40]
2017
Iran
56
61.2
±
9.13
52
55.8
28.8
28.8
71.2
15.4
42.3
23.1
Sequencing
15.4
75
25
22
Kaji et al., 2011 [41]
2011
Japan
35
68.9
±
9.8
98
NR
NR
NR
NR
NR
NR
NR
NR
60.2
71.2
23.7
23
Karbalaie Niya et al., 2016 [42]
2016
Iran
57
NR
1000
NR
NR
NR
NR
16.4
38.4
43.9
HRMS
33.6
85.1
14.9
24
Korphaisarn et al., 2019 [14]
2019
Thailand
57
64 (30-89)
108
24.1
75.9
82.4
17.6
6.5
86.1
4.6
PNAM-PCR
47.2
NR
NR
25
Kwon et al., 2011 [43]
2011
South Korea
60
54
±
12.33
92
0
100
56.5
43.5
15.2
67.4
12
PNAM/PCR/S
20.7
NR
NR
26
Kaidarova et al., 2020 [44]
2020
Kazakhstan
45
56.4
+
10.5
332
NR
NR
NR
NR
NR
NR
NR
PCR
44.9
80.5
19.5
27
Koochak et al., 2016 [16]
2016
Iran
57
NR
1000
0
100
NR
NR
16.4
38.4
43.9
HRMA/P
33.6
85.1
14.9
28
Kumar et al., 2015 [45]
2015
Oman
59
56 (18–80)
162
22.8
75.3
29.6
70.4
16.7
77.2
5.6
IHC
23.5
NR
NR
29
Kuo et al., 2014 [46]
2014
Taiwan
54
63.2 (30-88)
52
9.6
90.4
67.3
30.8
5.8
84.6
3.8
PNA-M/PCR
28.8
66.7
33.3
30
Lee et al., 2020 [47]
2020
South Korea
43
62 (27-88)
310
23.6
74.9
NR
NR
NR
NR
NR
Sequencing
37.1
76.5
23.5
31
Mohamed Suhaimi et al., 2015 [48]
2015
Singapore
54
58.5 (26-74)
44
50
40.9
54.5
45.5
NR
NR
NR
HRM-S
31.8
NR
NR
32
Mohsen et al., 2016 [49]
2016
Iran
70
62.17
±
14.18
50
NR
NR
74
26
NR
36
30
Sequencing
28
71.4
28.6
33
Mulla et al., 2020 [50]
2020
Saudi Arabia
51
60 (28-91)
51
35.3
64.7
NR
NR
3.9
84.3
11.8
Histopathology
39.2
75
20
34
Murtaza et al., 2014 [51]
2014
Pakistan
64
NR
150
12
88
48
52
38.7
26.7
34.7
Sequencing
13.3
60
35
35
Nagakubo et al., 2019 [52]
2019
Japan
NR
NR
50
NR
NR
NR
NR
NR
NR
NR
Sanger sequencing
50
68
20
36
Nguyen et al., 2021 [53]
2021
Vietnam
56
59.94
±
12.36
151
76.2
19.2
68.9
31.1
10.2
36.2
53.2
Sanger sequencing
37.1
55.4
44.6
37
Omidifar et al., 2015 [54]
2015
Iran
55
59.08
±
15.55
100
NR
NR
NR
NR
NR
NR
NR
Sequencing
32
71.9
25
38
Park et al., 2021 [55]
2021
South Korea
61
23–93
298
55.4
44.6
72.8
25.2
6
72.5
21.5
Sequencing
44
NR
NR
39
Payandeh et al., 2016 [56]
2016
Iran
61
57.7
±
13.0
83
0
100
61.4
38.6
7.3
32.5
60.2
HRM/AS/PCR/P
44.6
81.1
18.9
40
Rahadiani et al., 2018 [57]
2018
Indonesia
55
NR
39
NR
NR
NR
NR
2.6
NR
69.2
RT-PCR
71.8
75
17.9
41
Siraj et al., 2014 [58]
2014
Saudi Arabia
51
NR
770
44.5
49.2
NR
NR
12.1
76.6
9.6
PCR/sequencing
28.1
70.4
29.6
42
Song et al., 2020 [59]
2020
China
61
NR
2356
44.8
45.2
NR
NR
18.7
NR
81.3
Sequencing
32.3
NR
NR
43
Saito et al., 2014 [60]
2014
Japan
58
63.5 (20-82)
109
NR
NR
NR
NR
NR
NR
NR
ARMS/S-assay/DS
37.6
68.3
31.7
44
Sirisena et al., 2017 [61]
2017
Sri Lanka
63
61 (29-85)
108
NR
NR
NR
NR
NR
NR
NR
PCR/sequencing
23.1
60
40
45
Segal et al., 2011 [62]
2011
Israel
46
NR
419
NR
NR
NR
NR
NR
NR
NR
Sequencing
44.9
82.4
17.6
46
Taniguchi, H., et al. 2018 [63]
2018
Japan
59
64 (26-89)
302
26.8
73.2
53
47
9.6
NR
NR
Sequencing
42.7
69.8
15.5
47
Veldore et al., 2014 [64]
2014
India
65
55.9
±
12.8
299
NR
NR
70.2
29.8
7.02
13
79.9
RT/PCR/S
42.8
92.2
7.8
48
Watanabe et al., 2011 [65]
2011
Japan
67
66 (26-87)
113
21.2
78.8
73.5
26.5
12.4
34.5
53.1
PNA/RT-PCR
31
NR
NR
49
Watanabe et al., 2013 [66]
2013
Japan
61
NR
5732
17.1
79.7
68.3
31.7
NR
NR
NR
Sequencing
37.6
79.5
20.5
50
Yari et al., 2020 [67]
2020
Iran
NR
NR
100
NR
NR
NR
NR
NR
NR
NR
Sequencing
29
72.4
20.7
51
Yip et al., 2013 [68]
2013
Malaysia
65
NR
44
51.2
48.8
68.3
31.7
7.3
82.9
9.8
Sequencing
25
72.7
18.2
52
Yoshino et al., 2015 [69]
2015
Japan
NR
NR
307
NR
NR
NR
NR
NR
NR
NR
Sequencing
37.8
80.2
18.1
53
Zahrani et al., 2014 [70]
2014
Saudi Arabia
63
56.7 (21-88)
150
16
84
78.7
21.3
NR
NR
NR
Sequencing
56
86.9
13
54
Zekri et al., 2019 [71]
2019
Saudi Arabia
NR
NR
45
NR
NR
NR
NR
NR
NR
NR
Sanger sequencing
51.1
NR
NR
55
Zekri et al., 2012 [72]
2012
Saudi Arabia
65
61 (21-80)
46
30
70
83
17
15
83
2
Sanger sequencing
32.6
86.7
13
56
Zhang et al., 2015 [73]
2015
China
59
62.1 (18-96)
1110
19.1
80.9
50.7
49.3
7.5
73.5
19
PCR-SS
45.4
79
21
57
Zhu et al., 2020 [74]
2020
China
70
NR
53
37.7
62.3
NR
NR
NR
NR
NR
Sequencing
47.2
NR
NR
58
Zhang et al., 2018 [75]
2018
China
62
64
813
52.4
47.5
45.5
54.5
4.1
73.7
17
Sequencing
42.6
NR
NR
59
Zihui Yong et al., 2020 [76]
2020
Singapore
53
62 (12-91)
363
0
100
77
23
NR
NR
NR
Sequencing
34.7
NR
NR
N: number; NR: not reported.∗Percentage of all samples, age is presented in years (mean+SD/median (range/IQR)/range). HRMS: high resolution melting- (HRM-) sequencing; HRMA/P: high resolution melting assay/pyrosequencing; PNAM/PCR and PNAM/PCR/S: peptide nucleic acid-mediated polymerase chain reaction/sequencing; IHC: immunohistochemistry; SS: Sanger sequencing.Table 2
Major characteristics of the prevalence of BRAF screening studies that were included in the meta-analysis.
S/N
Author
Year
Location
Male,n (%)
Age
Sample size
Tumour stage (early stage)∗
Tumour stage (late-stage)∗
Tumour location (colon)∗
Tumour location (rectum)∗
Tumour grade (poorly differentiated)∗
Tumour grade (moderately differentiated)∗
Tumour grade (well-differentiated)∗
Method
Total BRAF mutation (%)
1
Bagadi et al., 2012 [27]
2012
India
74
56 (23-93)
100
22.5
77.5
78
22
NR
NR
NR
Sequencing
17
2
Eachkoti et al., 2018 [77]
2018
India
49
51.2
±
14.3
57
36.8
63.2
52.6
47.4
8.8
54.4
36.8
Sequencing
21.1
3
Fu et al., 2019 [78]
2019
China
60
60 (14-96)
5495
NR
NR
50.1
0.499
6.5
0.713
24.4
HRMS
2.8
4
Mohammadi Asl et al., 2014 [79]
2014
Iran
55
44.ynn (40-50)
80
NR
NR
NR
NR
NR
NR
NR
PCR-FFLP/S
46.3
5
He et al., 2020 [36]
2020
China
62
59 (26-83)
194
4.1
83
72.6
27.3
45.9
NR
NR
Sequencing
11.9
6
Hsieh et al., 2012 [37]
2012
Taiwan
NR
NR
182
NR
NR
NR
NR
NR
NR
NR
Sequencing
1.1
7
Jauhri et al., 2017a [39]
2017
India
61
NR
112
23.2
76.8
82.1
17.9
NR
NR
NR
Sequencing
7.1
8
Kaji et al., 2011 [41]
2011
Japan
35
68.9
+
9.8
98
NR
NR
NR
NR
NR
NR
NR
NR
0
9
Karbalaie Niya et al., 2016 [42]
2016
Iran
57
NR
1000
NR
NR
NR
NR
16.4
38.4
43.9
HRMS
0
10
Korphaisarn et al., 2019 [14]
2019
Thailand
57
64 (30-89)
108
24.1
75.9
82.4
17.6
6.5
86.1
4.6
PNAMPCR
1.9
11
Kwon et al., 2011 [43]
2011
South Korea
60
54
±
12.33
92
0
100
56.5
43.5
15.2
67.4
12
PNAMPCR/S
3.3
12
Mohamed Suhaimi et al., 2015 [48]
2015
Singapore
55
58.5 (26-74)
44
50
40.9
54.5
45.5
NR
NR
NR
HRM-S
11.4
13
Nagakubo et al., 2019 [52]
2019
Japan
NR
NR
50
NR
NR
NR
NR
NR
NR
NR
SS
6
14
Nguyen et al., 2021 [53]
2021
Vietnam
56
59.94
±
12.36
151
76.2
19.2
68.9
31.1
10.2
36.2
53.2
SS
2.6
15
Rozek et al., 2010 [80]
2010
Israel
5
NR
1297
NR
NR
NR
NR
NR
NR
NR
Sequencing
5
16
Saxena et al., 2018 [81]
2018
India
68
64 (26-90)
65
60
40
NR
NR
23.1
50.8
26.2
Immunohistochemistry
4.6
17
Shimada et al., 2018 [82]
2018
Japan
59
NR
111
NR
NR
NR
NR
NR
NR
NR
NGS
6.3
18
Siraj et al., 2014 [58]
2014
Saudi Arabia
51
NR
770
44.5
49.2
NR
NR
12.1
76.6
9.6
PCR/sequencing
2.2
19
Song et al., 2020 [59]
2020
China
61
NR
2356
44.8
45.2
NR
NR
18.7
NR
81.3
Sequencing
1
20
Taniguchi et al., 2020 [83]
2020
Japan
NR
66
325
NR
NR
NR
NR
NR
NR
NR
Sequencing
10.5
21
Taniguchi et al., 2018 [63]
2018
Japan
59
64 (26-89)
302
26.8
73.2
53
47
9.6
NR
NR
Sequencing
6
22
Vilkin et al., 2009 [84]
2009
Israel
47
67.6
±
12.3
128
54.9
45.1
NR
NR
25.1
54.6
20.3
Sequencing
18.8
23
Wang et al., 2017 [85]
2017
China
NR
NR
1694
NR
NR
NR
NR
NR
NR
NR
Sequencing
4.2
24
Warsinggih et al., 2020 [86]
2020
Indonesia
46
56
±
11.2
43
NR
NR
67.4
32.6
44.2
34.9
20.9
Sequencing
14
25
Yari et al., 2020 [67]
2020
Iran
NR
NR
100
NR
NR
NR
NR
NR
NR
NR
Sequencing
7
26
Yip et al., 2013 [68]
2013
Malaysia
65
NR
44
51.2
48.8
68.3
31.7
7.3
82.9
9.8
Sequencing
2.3
27
Zhang et al., 2020 [87]
2020
China
60
NR
480
18.8
81.3
44
56
21.5
NR
NR
Sequencing
4
28
Zhang et al., 2015 [73]
2015
China
59
62.1 (18-96)
1110
19.1
80.9
50.7
49.3
7.5
73.5
19
PCR-SS
3.1
29
Zhu et al., 2020 [74]
2020
China
70
NR
53
37.7
62.3
NR
NR
NR
NR
NR
Sequencing
11.3
N: number; NR: not reported.∗Percentage of all samples, age is presented in years ((mean+SD/median (range/IQR)/range). HRMS: high resolution melting- (HRM-) sequencing; HRMA/P: high resolution melting assay/pyrosequencing; PNAM/PCR and PNAM/PCR/S: peptide nucleic acid-mediated polymerase chain reaction/sequencing; IHC: immunohistochemistry; SS: Sanger sequencing.


### 3.3. Prevalence of KRAS Mutations in CRC Patients

The prevalence of KRAS gene mutation illustrated in the 59 studies included in the meta-analysis involves a total of 25525 patients. Among the studies, the highest frequency of KRAS mutations reported by Rahadiani et al. [57] was 71.8% (95% CI: 55.9-83.6) (38), and the lowest frequency of KRAS mutations was reported by Bakarman and AlGarni [2] was at a rate of 12.5% (95% CI: 9.1-17.0) (37). Using the random-effect model, the overall prevalence of KRAS mutations among Asians was 36.3% (95% CI: 34.5-38.2) with I2=85.54% and (P value < 0.001) (Figure 2). Furthermore, in 43 out of 59 studies, the frequency of KRAS gene mutations was reported in codon 12 and codon 13. The prevalence of mutated codons across all KRAS mutations could be seen in supplementary figures SF1 and SF2. Codon 12 and codon 13 mutations were discovered in the populations to be 76.6% (95% CI: 74.2-78.8) and 21.0% (95% CI: 19.1-23.0), respectively (Supplementary figures SF1 and SF2).Figure 2
A forest plot for the prevalence of KRAS mutation in Asian CRC patients.


### 3.4. Prevalence of KRAS Gene Mutation in Colorectal Cancer Stratified by Study Location and Period of Study

To determine the prevalence of KRAS mutation in CRC patients from various regions in Asia, a subgroup meta-analysis was undertaken. Data were available for nineteen locations from the listed studies, with the largest number of studies coming from Iran (n: 12) (Table 3; Supplementary Figure SF3).Table 3
Subgroup analysis. Prevalence of KRAS of patients with colorectal cancer stratified by study location of study.
No. of Studies
Prevalence (%)
95% CI
I
2 (%)
Q
Heterogeneity test
DF
P
Location
Iraq
1
48.0
0.346-0.617
NA
NA
NA
NA
Iran
12
32.2
0.293-0.353
45.35
20.129
11
0.044
Jordan
2
46.9
0.412-0.527
0
0.514
1
0.474
Saudi Arabia
9
35.7
0.265-0.460
91.95
99.408
8
0.001
Japan
8
40.1
0.355-0.448
77.04
30.494
7
0.001
India
3
34.0
0.237-0.461
83.77
12.320
2
0.002
Taiwan
3
33.4
0.284-0.387
0
0.672
2
0.715
China
7
39.9
0.361-0.439
91.21
68.226
6
0.001
Thailand
1
47.2
0.380-0.566
NA
NA
NA
NA
South Korea
3
34.3
0.246–0.456
87.18
15.600
2
0.001
Kazakhstan
1
44.9
0.396-0.503
NA
NA
NA
NA
Oman
1
23.5
0.176-0.306
NA
NA
NA
NA
Singapore
2
34.4
0.299-0.392
0
0.145
1
0.703
Pakistan
1
13.3
0.088-0.198
NA
NA
NA
NA
Vietnam
1
37.1
0.298-0.451
NA
NA
NA
NA
Indonesia
1
71.8
0.559-0.836
NA
NA
NA
NA
Sri Lanka
1
23.1
0.161-0.320
NA
NA
NA
NA
Israel
1
44.9
0.402-0.497
NA
NA
NA
NA
Malaysia
1
25.0
0.144-0.397
NA
NA
NA
NA
Overall
59
36.3
0.345-0.382
85.54
401.015
58
0.001
KRAS subgroup by period of study conduct
2010 and below
19
32.3
0.288-0.360
90.78
187.902
18
0.001
After 2010
28
39.9
0.373-0.425
82.25
152.081
27
0.001
Early tumour stage1
27
30.3
0.224-0.395
96.11
768.164
26
0.001
Late tumour stage2
27
67.9
0.593-0.755
82.25
668.459
26
0.001
KRAS subgroup by tumour location
Colon
26
61.2
0.551-0.670
92.78
346.249
25
0.001
Rectum
26
39.3
0.336-0.453
92.34
326.498
25
0.001
KRAS subgroup by tumour grading
Poor
23
9.6
0.063-0.145
90.420
229.651
22
0.001
Moderate
23
52.1
0.429-0.612
94.777
421.176
22
0.001
Well
23
31.0
0.214-0.425
96.266
589.219
22
0.001
1Implies stages 1 and 2; 2implies stages 3 and 4.The country of Indonesia had the highest prevalence rates projection at 71.8% (95% CI: 55.9–83.6), while Pakistan had the lowest estimate of 13% (95% CI: 8.8-19.8) (Table3; Supplementary Figure SF3). Greater heterogeneity was found in studies from Saudi Arabia, China, South Korea, and India (I2=91.95%, 91.21%, 87.18%, and 83.77%), respectively (P value < 0.001), which may have added to the overall heterogeneity found in the outcome.On the period of study, studies done “after 2010” had the highest number of studies (28) during the study period (Table3; Supplementary Figure SF4) with the highest KRAS prevalence at 39.9% (95% CI: 37.3–42.5), while those done “2010 and below” had KRAS prevalence at 32.3% (95% CI: 28.8–36.0), respectively (P value < 0.001).On the tumour stage, KRAS mutation was reported highest in the late stage at 67.9% (95% CI: 59.3–75.5), while on location, the colon recorded the highest KRAS mutation of 61.2% (95% CI: 55.1–67.0). On the grading of KRAS mutation in CRC, “Moderate grading” recorded the highest KRAS mutation of 51.8% (95% CI: 42.9–61.2) (Table3; Supplementary Figure SF6, 8, and 10, respectively).


### 3.5. Prevalence of BRAF Gene Mutation of Patients with Colorectal Cancer Stratified by Forest Plot for BRAF

The prevalence of BRAF gene mutations in colorectal patients was investigated using the random-effect model. In the 29 (607 patients) out of 88 studies that reported BRAF prevalence, the highest prevalence was reported by Jauhri et al. [39] at 7.1% (95% CI: 3.6–13.6) and Yari et al. [67] at 7.0% (95% CI: 3.4–14.0), respectively. The least BRAF gene mutation was reported by Hsieh et al. [37] at 1.1% (95% CI: 0.3–4.3). In 2 out of the 29 studies, Kaji et al. [41] and Niya et al. [42] reported no BRAF mutation: 0% (95% CI: 0.0–7.6) and 0% (95% CI: 0.0–0.8), respectively. The overall prevalence of BRAF gene mutations was 5.6% (95% CI: 3.9-8.0) with I2=94.00% and (P value < 0.001) (Figure 3). In all the studies (29 out of 88), the screening of BRAF gene mutations was based on the detection of BRAF-V600E mutation.Figure 3
Forest plot for BRAF.


### 3.6. Subgroup Analysis of the Prevalence of BRAF Gene Mutation in Patients with Colorectal Cancer Stratified by Study Location and Period of Study Conduct

To determine the prevalence of BRAF in colorectal cancer CRC patients from various regions in Asia, a subgroup meta-analysis was undertaken. Data were available for fourteen locations from the listed studies, with the largest number of studies coming from China (n: 7) (Table 4; Supplementary Figure SF12).Table 4
Subgroup analysis. Prevalence of BRAF gene mutation of patients with colorectal cancer stratified by study location.
Subgroup
No. of Studies
Prevalence (%)
95% CI
I
2 (%)
Q
Heterogeneity test
DF
P
India
4
11.7
0.062-0.210
73.69
11.401
3
0.010
China
7
4.0
0.025-0.063
93.42
91.205
6
0.001
Iran
3
4.7
0.004-0.403
96.16
52.129
2
0.001
Taiwan
1
1.1
0.003-0.043
NA
NA
NA
NA
Japan
5
6.9
0.044-0.107
55.86
9.062
4
0.060
Thailand
1
1.9
0.005-0.071
NA
NA
NA
NA
South Korea
1
3.3
0.011-0.096
NA
NA
NA
NA
Singapore
1
11.4
0.048-0.245
NA
NA
NA
NA
Vietnam
1
2.6
0.010-0.068
NA
NA
NA
NA
Israel
2
9.8
0.025-0.316
96.90
32.271
1
0.001
Saudi Arabia
1
2.2
0.014-0.035
NA
NA
NA
NA
Indonesia
1
14.0
0.064-0.278
NA
NA
NA
NA
Malaysia
1
2.3
0.003-0.144
NA
NA
NA
NA
Overall
29
5.6
0.039-0.080
94.00
466.942
28
0.001
BRAF subgroup by period of study conduct
2010 and below
8
5.6
0.020-0.146
96.45
196.928
7
0.001
After 2010
17
5.4
0.037-0.077
91.27
183.302
16
0.001
BRAF subgroup by tumour stage
Early tumour stage1
10
40.1
0.293-0.518
62.297
62.297
9
0.005
Late tumour stage2
10
59.9
0.482-0.707
95.59
62.297
9
0.005
BRAF subgroup by tumour location
Colon
10
67.9
0.577-0.766
54.421
19.746
9
0.020
Rectum
10
32.1
0.234-0.423
54.421
19.746
9
0.020
BRAF subgroup by tumour grade
Poor
11
30.4
0.189-0.450
88.066
83.794
10
0.001
Moderate
11
56.3
0.432-0.686
86.413
73.599
10
0.001
Well
11
10.2
0.056–0.179
69.996
33.329
10
0.001
1Implies stages 1 and 2; 2implies stages 3 and 4.India had the highest prevalence rate projection at 11.7% (95% CI: 6.2 – 21.0), while Taiwan had the lowest estimate of 1.1% (95% CI: 0.3-4.3) (Table4; Supplementary Figure SF12). Greater heterogeneity was found in studies from China and Iran (I2=91.21% and 96.16%), respectively (P value < 0.001), which may have added to the overall heterogeneity found.On the period of study, studies done “after 2010” had the highest number of studies (17) during the study period (Table4; Supplementary Figure SF13) with the highest BRAF gene mutation prevalence at 5.4% (95% CI: 3.7–7.7), while those done “2010 and below” had BRAF mutation prevalence at 5.6% (95% CI: 2.0–14.6), respectively (P value < 0.001).On the tumour stage, BRAF mutation was reported highest in the “late stage” at 59.9% (95% CI: 48.2–70.7), while on location, “colon” recorded the highest BRAF mutation of 67.9% (95% CI: 37.3–42.5). On the grading of BRAF mutation in CRC, “moderate grading” recorded the highest BRAF mutation of 56.3% (95% CI: 43.3–68.6) (Table4; Supplementary Figures SF15, 17, and 19).


### 3.7. Analyses of Sensitivity and Publication Bias

A funnel plot of random effects was generated to observe evidence of publication bias among the studies reporting KRAS gene mutation (Figure4) and BRAF gene mutation (Figure 5) among Asian CRC patients. There was no clear evidence of publication bias in both KRAS and BRAF mutation studies.Figure 4
KRAS funnel plot.P value: 2-tailed=0.503.Figure 5
BRAF funnel plot.P value: 1-tailed=0.16850; 2-tailed=0.33700.


## 3.1. Search Results and Study Selection

A total of 646 records were obtained by searching three electronic databases. After eliminating duplications and studies that do not favour the inclusion criteria, the remaining 498 were screened via titles and abstracts and by further excluding 261 records that satisfied the exclusion criteria and another 115 records that were done outside Asia; then, 122 records were left. Upon further scrutiny, another 34 records that did not merit the inclusion criteria as depicted in Figure1 above were excluded. Finally, a total of 88 unique records were confirmed eligible to be included in the meta-analysis. Among these later 88 eligible studies, 59 reported on KRAS gene mutation, and 29 reported on BRAF gene mutation. Thus, a total of 88 studies were selected for this meta-analysis.


## 3.2. Characteristics of the Eligible Studies

The characteristics of studies on KRAS and BRAF mutations are illustrated in Tables1 and 2, respectively. The meta-analysis study comprises of 25,525 sample sizes; all studies were from the Asian region with the male patient being most of the total participants, 15,743 out of 25525 (61.7%). The comprehensive characteristics of the included studies are illustrated in Table 1.Table 1
Major characteristics of the prevalence of KRAS screening studies that were included in the meta-analysis.
S/N
Author
Year
Location
Male,n (%)
Age
Sample size
Tumour stage (early stage)∗
Tumour stage (late stage)∗
Tumour location (colon)∗
Tumour location (rectum)∗
Tumour grade (poorly differentiated)∗
Tumour grade (moderately differentiated)∗
Tumour grade (well-differentiated)∗
Method
Total KRAS mutation (%)
KRAS (codon 12) %
KRAS (codon 13) %
1
Al-Allawi et al., 2012 [21]
2012
Iraq
54
55.4
±
15.25
50
50
50
44
56
18
62
20
Sequencing
48
91.7
8.3
2
Amirifard et al., 2016 [22]
2016
Iran
79
51.5
±
12.6
33
0
100
55
45
9
21.2
69.8
Sequencing
36.4
91.7
8.3
3
Awidi et al., 2019 [23]
2019
Jordan
60
58 (19-83)
190
NR
NR
97.4
2.63
NR
NR
NR
Sequencing
48.4
81.5
17.4
4
Bader and Ismail, 2014 [24]
2014
Saudi Arabia
58
55 (26-90)
83
13.3
86.7
76
24
9.6
82
8.4
Sequencing
42.2
88.6
11.4
5
Bakarman and AlGarni, 2019a [2]
2019
Saudi Arabia
56
57
±
13
279
34
56.6
59.5
40.5
6.5
73.8
5.7
Sequencing
12.5
NR
NR
6
Bando et al., 2012 [25]
2012
Japan
60
NR
109
NR
NR
69.7
30.2
NR
NR
NR
Sequencing
30.3
78.8
21.2
7
Bishehsari et al., 2006 [26]
2006
Iran
57
NR
182
NR
NR
71
29
NR
NR
NR
Sequencing
37.4
66.2
32.4
8
Bagadi et al., 2012 [27]
2012
India
74
56 (23-93)
100
22.5
77.5
78
22
NR
NR
NR
Sequencing
23
87
13
9
Chen et al., 2009 [28]
2009
Taiwan
54
25-90
90
NR
NR
68.9
31.1
NR
NR
NR
Sequencing
35.6
75
25
10
Dallol et al., 2016 [29]
2016
Saudi Arabia
59
NR
99
NR
NR
72.7
27.3
10.1
61.6
16.2
HTT-sequencing
35.4
NR
NR
11
Deng et al., 2015 [30]
2015
China
59
NR
433
50.3
49.7
73.9
26.1
21.2
49.2
21.9
Sequencing
38.3
74.1
25.9
12
Dolatkhah et al., 2015 [31]
2015
Iran
77
77.6 (27–90)
30
36.7
46.7
NR
NR
6.7
26.7
50
Sequencing
20
NR
NR
13
Dolatkhah et al., 2016 [32]
2016
Iran
65
61.9
±
15.34
100
37
29
72
28
3
22
49
Sequencing
26
61.5
34.6
14
Elbjeirami and Sughayer, 2012 [33]
2012
Jordan
55
55 (22-74)
100
5
95
78
22
NR
NR
NR
Sequencing
44
88.6
11.4
15
Elsamany et al., 2014 [34]
2014
Saudi Arabia
54
NR
116
23.3
76.7
67.8
32.2
29.3
58.7
12
Sequencing
37.1
NR
NR
16
Fu et al., 2019 [35]
2019
China
60
60 (14-96)
5495
NR
NR
50.1
49.9
6.5
71.3
24.4
HRMS
37.7
75.1
22.2
17
He et al., 2020 [36]
2020
China
62
59 (26-83)
194
4.1
83
72.6
27.3
45.9
NR
NR
Sequencing
42.3
63.4
17.1
18
Hsieh et al., 2012 [37]
2012
Taiwan
NR
NR
182
NR
NR
NR
NR
NR
NR
NR
Sequencing
33.5
NR
NR
19
Hamzehzadeh et al., 2018 [38]
2018
Iran
59
57 (27-86)
87
NR
NR
87.3
12.6
4.6
77
18.3
Sequencing
28.7
72
28
20
Jauhri et al., 2017a [39]
2017
India
61
NR
112
23.2
76.8
82.1
17.9
NR
NR
NR
Sequencing
35.7
67.5
17.5
21
Jazi et al., 2017 [40]
2017
Iran
56
61.2
±
9.13
52
55.8
28.8
28.8
71.2
15.4
42.3
23.1
Sequencing
15.4
75
25
22
Kaji et al., 2011 [41]
2011
Japan
35
68.9
±
9.8
98
NR
NR
NR
NR
NR
NR
NR
NR
60.2
71.2
23.7
23
Karbalaie Niya et al., 2016 [42]
2016
Iran
57
NR
1000
NR
NR
NR
NR
16.4
38.4
43.9
HRMS
33.6
85.1
14.9
24
Korphaisarn et al., 2019 [14]
2019
Thailand
57
64 (30-89)
108
24.1
75.9
82.4
17.6
6.5
86.1
4.6
PNAM-PCR
47.2
NR
NR
25
Kwon et al., 2011 [43]
2011
South Korea
60
54
±
12.33
92
0
100
56.5
43.5
15.2
67.4
12
PNAM/PCR/S
20.7
NR
NR
26
Kaidarova et al., 2020 [44]
2020
Kazakhstan
45
56.4
+
10.5
332
NR
NR
NR
NR
NR
NR
NR
PCR
44.9
80.5
19.5
27
Koochak et al., 2016 [16]
2016
Iran
57
NR
1000
0
100
NR
NR
16.4
38.4
43.9
HRMA/P
33.6
85.1
14.9
28
Kumar et al., 2015 [45]
2015
Oman
59
56 (18–80)
162
22.8
75.3
29.6
70.4
16.7
77.2
5.6
IHC
23.5
NR
NR
29
Kuo et al., 2014 [46]
2014
Taiwan
54
63.2 (30-88)
52
9.6
90.4
67.3
30.8
5.8
84.6
3.8
PNA-M/PCR
28.8
66.7
33.3
30
Lee et al., 2020 [47]
2020
South Korea
43
62 (27-88)
310
23.6
74.9
NR
NR
NR
NR
NR
Sequencing
37.1
76.5
23.5
31
Mohamed Suhaimi et al., 2015 [48]
2015
Singapore
54
58.5 (26-74)
44
50
40.9
54.5
45.5
NR
NR
NR
HRM-S
31.8
NR
NR
32
Mohsen et al., 2016 [49]
2016
Iran
70
62.17
±
14.18
50
NR
NR
74
26
NR
36
30
Sequencing
28
71.4
28.6
33
Mulla et al., 2020 [50]
2020
Saudi Arabia
51
60 (28-91)
51
35.3
64.7
NR
NR
3.9
84.3
11.8
Histopathology
39.2
75
20
34
Murtaza et al., 2014 [51]
2014
Pakistan
64
NR
150
12
88
48
52
38.7
26.7
34.7
Sequencing
13.3
60
35
35
Nagakubo et al., 2019 [52]
2019
Japan
NR
NR
50
NR
NR
NR
NR
NR
NR
NR
Sanger sequencing
50
68
20
36
Nguyen et al., 2021 [53]
2021
Vietnam
56
59.94
±
12.36
151
76.2
19.2
68.9
31.1
10.2
36.2
53.2
Sanger sequencing
37.1
55.4
44.6
37
Omidifar et al., 2015 [54]
2015
Iran
55
59.08
±
15.55
100
NR
NR
NR
NR
NR
NR
NR
Sequencing
32
71.9
25
38
Park et al., 2021 [55]
2021
South Korea
61
23–93
298
55.4
44.6
72.8
25.2
6
72.5
21.5
Sequencing
44
NR
NR
39
Payandeh et al., 2016 [56]
2016
Iran
61
57.7
±
13.0
83
0
100
61.4
38.6
7.3
32.5
60.2
HRM/AS/PCR/P
44.6
81.1
18.9
40
Rahadiani et al., 2018 [57]
2018
Indonesia
55
NR
39
NR
NR
NR
NR
2.6
NR
69.2
RT-PCR
71.8
75
17.9
41
Siraj et al., 2014 [58]
2014
Saudi Arabia
51
NR
770
44.5
49.2
NR
NR
12.1
76.6
9.6
PCR/sequencing
28.1
70.4
29.6
42
Song et al., 2020 [59]
2020
China
61
NR
2356
44.8
45.2
NR
NR
18.7
NR
81.3
Sequencing
32.3
NR
NR
43
Saito et al., 2014 [60]
2014
Japan
58
63.5 (20-82)
109
NR
NR
NR
NR
NR
NR
NR
ARMS/S-assay/DS
37.6
68.3
31.7
44
Sirisena et al., 2017 [61]
2017
Sri Lanka
63
61 (29-85)
108
NR
NR
NR
NR
NR
NR
NR
PCR/sequencing
23.1
60
40
45
Segal et al., 2011 [62]
2011
Israel
46
NR
419
NR
NR
NR
NR
NR
NR
NR
Sequencing
44.9
82.4
17.6
46
Taniguchi, H., et al. 2018 [63]
2018
Japan
59
64 (26-89)
302
26.8
73.2
53
47
9.6
NR
NR
Sequencing
42.7
69.8
15.5
47
Veldore et al., 2014 [64]
2014
India
65
55.9
±
12.8
299
NR
NR
70.2
29.8
7.02
13
79.9
RT/PCR/S
42.8
92.2
7.8
48
Watanabe et al., 2011 [65]
2011
Japan
67
66 (26-87)
113
21.2
78.8
73.5
26.5
12.4
34.5
53.1
PNA/RT-PCR
31
NR
NR
49
Watanabe et al., 2013 [66]
2013
Japan
61
NR
5732
17.1
79.7
68.3
31.7
NR
NR
NR
Sequencing
37.6
79.5
20.5
50
Yari et al., 2020 [67]
2020
Iran
NR
NR
100
NR
NR
NR
NR
NR
NR
NR
Sequencing
29
72.4
20.7
51
Yip et al., 2013 [68]
2013
Malaysia
65
NR
44
51.2
48.8
68.3
31.7
7.3
82.9
9.8
Sequencing
25
72.7
18.2
52
Yoshino et al., 2015 [69]
2015
Japan
NR
NR
307
NR
NR
NR
NR
NR
NR
NR
Sequencing
37.8
80.2
18.1
53
Zahrani et al., 2014 [70]
2014
Saudi Arabia
63
56.7 (21-88)
150
16
84
78.7
21.3
NR
NR
NR
Sequencing
56
86.9
13
54
Zekri et al., 2019 [71]
2019
Saudi Arabia
NR
NR
45
NR
NR
NR
NR
NR
NR
NR
Sanger sequencing
51.1
NR
NR
55
Zekri et al., 2012 [72]
2012
Saudi Arabia
65
61 (21-80)
46
30
70
83
17
15
83
2
Sanger sequencing
32.6
86.7
13
56
Zhang et al., 2015 [73]
2015
China
59
62.1 (18-96)
1110
19.1
80.9
50.7
49.3
7.5
73.5
19
PCR-SS
45.4
79
21
57
Zhu et al., 2020 [74]
2020
China
70
NR
53
37.7
62.3
NR
NR
NR
NR
NR
Sequencing
47.2
NR
NR
58
Zhang et al., 2018 [75]
2018
China
62
64
813
52.4
47.5
45.5
54.5
4.1
73.7
17
Sequencing
42.6
NR
NR
59
Zihui Yong et al., 2020 [76]
2020
Singapore
53
62 (12-91)
363
0
100
77
23
NR
NR
NR
Sequencing
34.7
NR
NR
N: number; NR: not reported.∗Percentage of all samples, age is presented in years (mean+SD/median (range/IQR)/range). HRMS: high resolution melting- (HRM-) sequencing; HRMA/P: high resolution melting assay/pyrosequencing; PNAM/PCR and PNAM/PCR/S: peptide nucleic acid-mediated polymerase chain reaction/sequencing; IHC: immunohistochemistry; SS: Sanger sequencing.Table 2
Major characteristics of the prevalence of BRAF screening studies that were included in the meta-analysis.
S/N
Author
Year
Location
Male,n (%)
Age
Sample size
Tumour stage (early stage)∗
Tumour stage (late-stage)∗
Tumour location (colon)∗
Tumour location (rectum)∗
Tumour grade (poorly differentiated)∗
Tumour grade (moderately differentiated)∗
Tumour grade (well-differentiated)∗
Method
Total BRAF mutation (%)
1
Bagadi et al., 2012 [27]
2012
India
74
56 (23-93)
100
22.5
77.5
78
22
NR
NR
NR
Sequencing
17
2
Eachkoti et al., 2018 [77]
2018
India
49
51.2
±
14.3
57
36.8
63.2
52.6
47.4
8.8
54.4
36.8
Sequencing
21.1
3
Fu et al., 2019 [78]
2019
China
60
60 (14-96)
5495
NR
NR
50.1
0.499
6.5
0.713
24.4
HRMS
2.8
4
Mohammadi Asl et al., 2014 [79]
2014
Iran
55
44.ynn (40-50)
80
NR
NR
NR
NR
NR
NR
NR
PCR-FFLP/S
46.3
5
He et al., 2020 [36]
2020
China
62
59 (26-83)
194
4.1
83
72.6
27.3
45.9
NR
NR
Sequencing
11.9
6
Hsieh et al., 2012 [37]
2012
Taiwan
NR
NR
182
NR
NR
NR
NR
NR
NR
NR
Sequencing
1.1
7
Jauhri et al., 2017a [39]
2017
India
61
NR
112
23.2
76.8
82.1
17.9
NR
NR
NR
Sequencing
7.1
8
Kaji et al., 2011 [41]
2011
Japan
35
68.9
+
9.8
98
NR
NR
NR
NR
NR
NR
NR
NR
0
9
Karbalaie Niya et al., 2016 [42]
2016
Iran
57
NR
1000
NR
NR
NR
NR
16.4
38.4
43.9
HRMS
0
10
Korphaisarn et al., 2019 [14]
2019
Thailand
57
64 (30-89)
108
24.1
75.9
82.4
17.6
6.5
86.1
4.6
PNAMPCR
1.9
11
Kwon et al., 2011 [43]
2011
South Korea
60
54
±
12.33
92
0
100
56.5
43.5
15.2
67.4
12
PNAMPCR/S
3.3
12
Mohamed Suhaimi et al., 2015 [48]
2015
Singapore
55
58.5 (26-74)
44
50
40.9
54.5
45.5
NR
NR
NR
HRM-S
11.4
13
Nagakubo et al., 2019 [52]
2019
Japan
NR
NR
50
NR
NR
NR
NR
NR
NR
NR
SS
6
14
Nguyen et al., 2021 [53]
2021
Vietnam
56
59.94
±
12.36
151
76.2
19.2
68.9
31.1
10.2
36.2
53.2
SS
2.6
15
Rozek et al., 2010 [80]
2010
Israel
5
NR
1297
NR
NR
NR
NR
NR
NR
NR
Sequencing
5
16
Saxena et al., 2018 [81]
2018
India
68
64 (26-90)
65
60
40
NR
NR
23.1
50.8
26.2
Immunohistochemistry
4.6
17
Shimada et al., 2018 [82]
2018
Japan
59
NR
111
NR
NR
NR
NR
NR
NR
NR
NGS
6.3
18
Siraj et al., 2014 [58]
2014
Saudi Arabia
51
NR
770
44.5
49.2
NR
NR
12.1
76.6
9.6
PCR/sequencing
2.2
19
Song et al., 2020 [59]
2020
China
61
NR
2356
44.8
45.2
NR
NR
18.7
NR
81.3
Sequencing
1
20
Taniguchi et al., 2020 [83]
2020
Japan
NR
66
325
NR
NR
NR
NR
NR
NR
NR
Sequencing
10.5
21
Taniguchi et al., 2018 [63]
2018
Japan
59
64 (26-89)
302
26.8
73.2
53
47
9.6
NR
NR
Sequencing
6
22
Vilkin et al., 2009 [84]
2009
Israel
47
67.6
±
12.3
128
54.9
45.1
NR
NR
25.1
54.6
20.3
Sequencing
18.8
23
Wang et al., 2017 [85]
2017
China
NR
NR
1694
NR
NR
NR
NR
NR
NR
NR
Sequencing
4.2
24
Warsinggih et al., 2020 [86]
2020
Indonesia
46
56
±
11.2
43
NR
NR
67.4
32.6
44.2
34.9
20.9
Sequencing
14
25
Yari et al., 2020 [67]
2020
Iran
NR
NR
100
NR
NR
NR
NR
NR
NR
NR
Sequencing
7
26
Yip et al., 2013 [68]
2013
Malaysia
65
NR
44
51.2
48.8
68.3
31.7
7.3
82.9
9.8
Sequencing
2.3
27
Zhang et al., 2020 [87]
2020
China
60
NR
480
18.8
81.3
44
56
21.5
NR
NR
Sequencing
4
28
Zhang et al., 2015 [73]
2015
China
59
62.1 (18-96)
1110
19.1
80.9
50.7
49.3
7.5
73.5
19
PCR-SS
3.1
29
Zhu et al., 2020 [74]
2020
China
70
NR
53
37.7
62.3
NR
NR
NR
NR
NR
Sequencing
11.3
N: number; NR: not reported.∗Percentage of all samples, age is presented in years ((mean+SD/median (range/IQR)/range). HRMS: high resolution melting- (HRM-) sequencing; HRMA/P: high resolution melting assay/pyrosequencing; PNAM/PCR and PNAM/PCR/S: peptide nucleic acid-mediated polymerase chain reaction/sequencing; IHC: immunohistochemistry; SS: Sanger sequencing.


## 3.3. Prevalence of KRAS Mutations in CRC Patients

The prevalence of KRAS gene mutation illustrated in the 59 studies included in the meta-analysis involves a total of 25525 patients. Among the studies, the highest frequency of KRAS mutations reported by Rahadiani et al. [57] was 71.8% (95% CI: 55.9-83.6) (38), and the lowest frequency of KRAS mutations was reported by Bakarman and AlGarni [2] was at a rate of 12.5% (95% CI: 9.1-17.0) (37). Using the random-effect model, the overall prevalence of KRAS mutations among Asians was 36.3% (95% CI: 34.5-38.2) with I2=85.54% and (P value < 0.001) (Figure 2). Furthermore, in 43 out of 59 studies, the frequency of KRAS gene mutations was reported in codon 12 and codon 13. The prevalence of mutated codons across all KRAS mutations could be seen in supplementary figures SF1 and SF2. Codon 12 and codon 13 mutations were discovered in the populations to be 76.6% (95% CI: 74.2-78.8) and 21.0% (95% CI: 19.1-23.0), respectively (Supplementary figures SF1 and SF2).Figure 2
A forest plot for the prevalence of KRAS mutation in Asian CRC patients.


## 3.4. Prevalence of KRAS Gene Mutation in Colorectal Cancer Stratified by Study Location and Period of Study

To determine the prevalence of KRAS mutation in CRC patients from various regions in Asia, a subgroup meta-analysis was undertaken. Data were available for nineteen locations from the listed studies, with the largest number of studies coming from Iran (n: 12) (Table 3; Supplementary Figure SF3).Table 3
Subgroup analysis. Prevalence of KRAS of patients with colorectal cancer stratified by study location of study.
No. of Studies
Prevalence (%)
95% CI
I
2 (%)
Q
Heterogeneity test
DF
P
Location
Iraq
1
48.0
0.346-0.617
NA
NA
NA
NA
Iran
12
32.2
0.293-0.353
45.35
20.129
11
0.044
Jordan
2
46.9
0.412-0.527
0
0.514
1
0.474
Saudi Arabia
9
35.7
0.265-0.460
91.95
99.408
8
0.001
Japan
8
40.1
0.355-0.448
77.04
30.494
7
0.001
India
3
34.0
0.237-0.461
83.77
12.320
2
0.002
Taiwan
3
33.4
0.284-0.387
0
0.672
2
0.715
China
7
39.9
0.361-0.439
91.21
68.226
6
0.001
Thailand
1
47.2
0.380-0.566
NA
NA
NA
NA
South Korea
3
34.3
0.246–0.456
87.18
15.600
2
0.001
Kazakhstan
1
44.9
0.396-0.503
NA
NA
NA
NA
Oman
1
23.5
0.176-0.306
NA
NA
NA
NA
Singapore
2
34.4
0.299-0.392
0
0.145
1
0.703
Pakistan
1
13.3
0.088-0.198
NA
NA
NA
NA
Vietnam
1
37.1
0.298-0.451
NA
NA
NA
NA
Indonesia
1
71.8
0.559-0.836
NA
NA
NA
NA
Sri Lanka
1
23.1
0.161-0.320
NA
NA
NA
NA
Israel
1
44.9
0.402-0.497
NA
NA
NA
NA
Malaysia
1
25.0
0.144-0.397
NA
NA
NA
NA
Overall
59
36.3
0.345-0.382
85.54
401.015
58
0.001
KRAS subgroup by period of study conduct
2010 and below
19
32.3
0.288-0.360
90.78
187.902
18
0.001
After 2010
28
39.9
0.373-0.425
82.25
152.081
27
0.001
Early tumour stage1
27
30.3
0.224-0.395
96.11
768.164
26
0.001
Late tumour stage2
27
67.9
0.593-0.755
82.25
668.459
26
0.001
KRAS subgroup by tumour location
Colon
26
61.2
0.551-0.670
92.78
346.249
25
0.001
Rectum
26
39.3
0.336-0.453
92.34
326.498
25
0.001
KRAS subgroup by tumour grading
Poor
23
9.6
0.063-0.145
90.420
229.651
22
0.001
Moderate
23
52.1
0.429-0.612
94.777
421.176
22
0.001
Well
23
31.0
0.214-0.425
96.266
589.219
22
0.001
1Implies stages 1 and 2; 2implies stages 3 and 4.The country of Indonesia had the highest prevalence rates projection at 71.8% (95% CI: 55.9–83.6), while Pakistan had the lowest estimate of 13% (95% CI: 8.8-19.8) (Table3; Supplementary Figure SF3). Greater heterogeneity was found in studies from Saudi Arabia, China, South Korea, and India (I2=91.95%, 91.21%, 87.18%, and 83.77%), respectively (P value < 0.001), which may have added to the overall heterogeneity found in the outcome.On the period of study, studies done “after 2010” had the highest number of studies (28) during the study period (Table3; Supplementary Figure SF4) with the highest KRAS prevalence at 39.9% (95% CI: 37.3–42.5), while those done “2010 and below” had KRAS prevalence at 32.3% (95% CI: 28.8–36.0), respectively (P value < 0.001).On the tumour stage, KRAS mutation was reported highest in the late stage at 67.9% (95% CI: 59.3–75.5), while on location, the colon recorded the highest KRAS mutation of 61.2% (95% CI: 55.1–67.0). On the grading of KRAS mutation in CRC, “Moderate grading” recorded the highest KRAS mutation of 51.8% (95% CI: 42.9–61.2) (Table3; Supplementary Figure SF6, 8, and 10, respectively).


## 3.5. Prevalence of BRAF Gene Mutation of Patients with Colorectal Cancer Stratified by Forest Plot for BRAF

The prevalence of BRAF gene mutations in colorectal patients was investigated using the random-effect model. In the 29 (607 patients) out of 88 studies that reported BRAF prevalence, the highest prevalence was reported by Jauhri et al. [39] at 7.1% (95% CI: 3.6–13.6) and Yari et al. [67] at 7.0% (95% CI: 3.4–14.0), respectively. The least BRAF gene mutation was reported by Hsieh et al. [37] at 1.1% (95% CI: 0.3–4.3). In 2 out of the 29 studies, Kaji et al. [41] and Niya et al. [42] reported no BRAF mutation: 0% (95% CI: 0.0–7.6) and 0% (95% CI: 0.0–0.8), respectively. The overall prevalence of BRAF gene mutations was 5.6% (95% CI: 3.9-8.0) with I2=94.00% and (P value < 0.001) (Figure 3). In all the studies (29 out of 88), the screening of BRAF gene mutations was based on the detection of BRAF-V600E mutation.Figure 3
Forest plot for BRAF.


## 3.6. Subgroup Analysis of the Prevalence of BRAF Gene Mutation in Patients with Colorectal Cancer Stratified by Study Location and Period of Study Conduct

To determine the prevalence of BRAF in colorectal cancer CRC patients from various regions in Asia, a subgroup meta-analysis was undertaken. Data were available for fourteen locations from the listed studies, with the largest number of studies coming from China (n: 7) (Table 4; Supplementary Figure SF12).Table 4
Subgroup analysis. Prevalence of BRAF gene mutation of patients with colorectal cancer stratified by study location.
Subgroup
No. of Studies
Prevalence (%)
95% CI
I
2 (%)
Q
Heterogeneity test
DF
P
India
4
11.7
0.062-0.210
73.69
11.401
3
0.010
China
7
4.0
0.025-0.063
93.42
91.205
6
0.001
Iran
3
4.7
0.004-0.403
96.16
52.129
2
0.001
Taiwan
1
1.1
0.003-0.043
NA
NA
NA
NA
Japan
5
6.9
0.044-0.107
55.86
9.062
4
0.060
Thailand
1
1.9
0.005-0.071
NA
NA
NA
NA
South Korea
1
3.3
0.011-0.096
NA
NA
NA
NA
Singapore
1
11.4
0.048-0.245
NA
NA
NA
NA
Vietnam
1
2.6
0.010-0.068
NA
NA
NA
NA
Israel
2
9.8
0.025-0.316
96.90
32.271
1
0.001
Saudi Arabia
1
2.2
0.014-0.035
NA
NA
NA
NA
Indonesia
1
14.0
0.064-0.278
NA
NA
NA
NA
Malaysia
1
2.3
0.003-0.144
NA
NA
NA
NA
Overall
29
5.6
0.039-0.080
94.00
466.942
28
0.001
BRAF subgroup by period of study conduct
2010 and below
8
5.6
0.020-0.146
96.45
196.928
7
0.001
After 2010
17
5.4
0.037-0.077
91.27
183.302
16
0.001
BRAF subgroup by tumour stage
Early tumour stage1
10
40.1
0.293-0.518
62.297
62.297
9
0.005
Late tumour stage2
10
59.9
0.482-0.707
95.59
62.297
9
0.005
BRAF subgroup by tumour location
Colon
10
67.9
0.577-0.766
54.421
19.746
9
0.020
Rectum
10
32.1
0.234-0.423
54.421
19.746
9
0.020
BRAF subgroup by tumour grade
Poor
11
30.4
0.189-0.450
88.066
83.794
10
0.001
Moderate
11
56.3
0.432-0.686
86.413
73.599
10
0.001
Well
11
10.2
0.056–0.179
69.996
33.329
10
0.001
1Implies stages 1 and 2; 2implies stages 3 and 4.India had the highest prevalence rate projection at 11.7% (95% CI: 6.2 – 21.0), while Taiwan had the lowest estimate of 1.1% (95% CI: 0.3-4.3) (Table4; Supplementary Figure SF12). Greater heterogeneity was found in studies from China and Iran (I2=91.21% and 96.16%), respectively (P value < 0.001), which may have added to the overall heterogeneity found.On the period of study, studies done “after 2010” had the highest number of studies (17) during the study period (Table4; Supplementary Figure SF13) with the highest BRAF gene mutation prevalence at 5.4% (95% CI: 3.7–7.7), while those done “2010 and below” had BRAF mutation prevalence at 5.6% (95% CI: 2.0–14.6), respectively (P value < 0.001).On the tumour stage, BRAF mutation was reported highest in the “late stage” at 59.9% (95% CI: 48.2–70.7), while on location, “colon” recorded the highest BRAF mutation of 67.9% (95% CI: 37.3–42.5). On the grading of BRAF mutation in CRC, “moderate grading” recorded the highest BRAF mutation of 56.3% (95% CI: 43.3–68.6) (Table4; Supplementary Figures SF15, 17, and 19).


## 3.7. Analyses of Sensitivity and Publication Bias

A funnel plot of random effects was generated to observe evidence of publication bias among the studies reporting KRAS gene mutation (Figure4) and BRAF gene mutation (Figure 5) among Asian CRC patients. There was no clear evidence of publication bias in both KRAS and BRAF mutation studies.Figure 4
KRAS funnel plot.P value: 2-tailed=0.503.Figure 5
BRAF funnel plot.P value: 1-tailed=0.16850; 2-tailed=0.33700.


## 4. Discussion

Several research today showed that mutations in the RAS family of genes especially the KRAS are linked to around a third of all malignancies; however, the incidence of the gene mutations varies greatly depending on the kind of cancer: often seen to be 40% in colorectal cancer, 15-20% in non-small-cell lung cancer, and 95% in pancreas carcinoma [44]. Only a few individuals diagnosed with colorectal cancer would be opportune to receive curative surgery if detected early because, at the time of consult with the surgeon, it is already in the late stage wherein the prognosis is poor. More so, the illness involves no specific early presenting features, and the long-term disease period is usually associated with probable organ metastases [86, 88]. Also, because colorectal cancer is thought to grow progressively over time due to the buildup of genetic abnormalities, the threat of reoccurrence and mortality from colorectal cancer is significantly linked to the stage of the disease at diagnosis [86]. Although there is a tremendous advance in the CRC treatment via the use of cytotoxic agents, i.e., monoclonal antibodies to targeted therapy such as on EGF receptor [78], CRC still poses a significant threat to life as KRAS gene mutation is reported as a major cause of treatment failure in cancer therapy [89].Colorectal cancer (CRC) is the third most frequent cancer in the world, with 2.0 million new cases in 2020, accounting for 11% of all new cancer cases [90]. It was estimated as 1.9 million of all new cases and 880,000 deaths in 2018 [91]. The incidence and mortality rates of colorectal cancer (CRC) differ significantly around the globe, i.e., differs in various regions. From a total of 646 eligible papers that were filtered in this study, 88 studies were finally selected to investigate the prevalence of KRAS and BRAF gene mutations in this analysis. During this analysis, approximately 115 articles reporting KRAS and BRAF gene mutations in CRC outside Asia were identified, but they were, however, excluded because they did not fulfill the study’s inclusion criteria. This plethora of articles discovered spanned almost every corner of the world. Balschun et al. [92] documented the prevalence case of KRAS and BRAF in German patients in Europe. Di Fiore et al. [93] reported the first instance of KRAS and BRAF mutations in CRC in the United Kingdom. Raskin et al. [94] and Osasan [95] studies were done in Africa. Altogether, these illustrated the different prevalence of KRAS mutation existence in CRC around the globe.In this study, the prevalence of KRAS and BRAF mutations was investigated in 88 studies involving 25,527 CRC patients from various countries in Asia; the overall prevalence of KRAS gene mutations was found to be 36.3% (95% CI: 34.5-38.2). KRAS gene mutations are a well-investigated mutation in several carcinomas such as melanoma [96], non-small-cell lung carcinoma [97], colorectal carcinoma [98, 99], and papillary thyroid cancer [100]. KRAS gene mutations, which function as an active oncogene, are found in 35 to 45 percent of CRC cases globally [50, 101–103]. The findings of these investigations corroborate our study’s outcome that approximately thirty-six percent of the patients have KRAS gene mutation. This prevalence rate was similar to data reported from the US (35.7% [104] and 31% [105]), China (32%) [106], Japan (33.5%) [107], Taiwan (33.5%) [37], Russia (35.9%) [108], France (33.8) [109], the United Kingdom (36.9%) [110], and Brazil (36%) [111], although KRAS prevalence was reported to slightly differ from some published data from Germany (41%) [112], Italy (62.2%, 43%, and 43%) [113–115], Turkey (44%) [116], Morocco (24%) [117], and Egypt (11% and18.4%) [118, 119]. These latter differences could be associated with various factors such as race, lifestyle, period, and means of sample collection and geographical locations.The dynamic of gene expression patterns on gender and age was investigated by some studies as a possible risk for developing CRC [120, 121]. In this study, the age of the participants was also taken into consideration, the bulk of the recruited participants were adults, with most of them being over 50 years old, implying that KRAS gene mutation predominates in adult CRC. It was indeed as anticipated, given that older age has hitherto been identified as a health risk for CRC in numerous investigations [122]. Although data on gender were not reported for some studies in the included studies for this analysis, CRC was found to be more common in male patients (60.7%) than female patients (39.3%). This information points to the importance of gender predilection in the occurrence of CRC which is consistent with findings from other studies around the world [123, 124]. On the location of the tumour, the cancer was mostly found in the colon (82.1%) which is a similar finding in several studies [39], probably because the patient would present at the latter stage of cancer [125].Although human scientific knowledge has greatly advanced compared to decades ago, however, our study found that the prevalence of KRAS gene mutation was higher among patients screened “after 2010,” 36.7% (95% CI: 34.6-38.8), than when compared to those screened “before 2010,” 32.3% (95% CI: 28.8-36.0), probably due to medical advances and more medical screening [126]. During the shedding of tumour cells or apoptosis, small DNA fragments flow into the blood system, leading to the detection of this ctDNA mutation in almost all cancer types and in the late stages of the tumour or the malignancy, hence, more frequency of the DNA mutation detection on screening. Another reason could range from lifestyle evolution to dietary choice, synergically working together to modify our body biocomposition and genetic make-up [127]. The late-stage (stages 3 and 4) recorded more KRAS gene mutation (68%) than the early stage (30%) but this could be associated with discrepancies in the time of consultation and stages of the tumour at the time of recruitment of the patients for the included studies, as the majority of the mean age reported by the studies was in 5th or 6th decade of life and because most of the patient would have distant metastases at the period of diagnosis.On the location of KRAS and BRAF gene mutations, the colon (61% and 68%), respectively, was the most recorded mutation site which on the contrary is the rectum [128]; however, this is as expected as the main physiological function of the intestinal lumen of the colon includes water absorption and stool storage. Therefore, the contents contained inside the colon are relatively desiccated which is the tumour-conducive condition for gene mutation detection [129, 130]. In this present research, the majority of KRAS mutations occurred in codon 12, 76.6% (95% CI: 74.2-78.8), than in codon 13, 21.0% (95% CI: 19.1-23.0). These findings are comparable to those of previous research [105, 116, 117]. For example, in a Belgian research, 36.3 percent of people had KRAS mutations, with 91 percent of mutations in codon 12 [131]. Another study published in Dobre et al. [132] found that KRAS mutations in codons 12 and 13 were found in 79.3 percent and 19.7 percent of people, respectively. A similar study in Brazil reported that 87% of KRAS mutations were in codon 12 and 13% in codon 13. However, research in the Greek population found that KRAS mutations at codon 12 are uncommon (29.3%) [133]. Only 3 studies of the colorectal cancer patients in our analysis had a KRAS codon 61 mutations [26, 67, 68] which is not surprising given that the majority of KRAS mutations reported in human tumours are in codon 12, with mutations in codons 13 and 61 accounting for only 1.7-9 percent [27].BRAF is also a member of the RAF gene subfamily that, like KRAS, performs its function in the EGFR downstream cascade, but their mutations are less frequent than the KRAS gene mutations. Among the BRAF gene, BRAFV600E mutation is the most prevailing [134], and in this present study, BRAFV600E mutation is used to examine the prevalence of BRAF gene mutation in CRC. The frequency of BRAF mutation varies globally, approximately 1.1–25% [16, 49, 135–139]. The prevalence of BRAF mutation obtained in this study was 5.6% (95% CI: 3.9-8.0), and this is conforming with the several existing findings, i.e., 1.1 to 5.8% in Asian studies and 5–21% in western studies [112, 131, 134, 140–142]. Another reason for these prevalence similarities could be associated with genetic homogeneity as the studies involve certain regions, and their lifestyles and diet are almost similar [143]. BRAF-activating mutations are frequently exclusive with KRAS mutations, accounting for 5–15% of mCRC cases, and are linked to a poor prognosis in stages II, III, and IV [144]. This mutation causes a constant stimulation of the mitogen-activating protein kinase MAPK pathway, which controls the transcriptase activity of regulatory genes in the cell cycle by modulating cell growth stimuli, a nonfunctioning condition that predisposes to cancerous growth [145].This study possesses several merits and strengths. First, to the best of the author’s knowledge, it has been the first systematic review and meta-analysis carried out on the prevalence of KRAS and BRAF mutations among Asians with CRC. Also, a well-detailed and comprehensive search strategy ensures that elaborate all-inclusive papers are included, thus leading to a very large population size of 25,525. This also ensures high confidence in the outcomes obtained since the included studies were of high methodology quality. However, this analysis was not without some limitations, with many linked to the data from the literature of the included studies such as small sample size, incomplete reports on sex, mean age, period of study conduction, differentiation, and location of the tumour, and lastly, mutation screening was done just for the BRAFV600E. All these parameters/characteristics that would be crucial in upholding the study appraisal were not reported in some of the studies analysed in this meta-analysis, thus accounting to some of the heterogeneity seen in the studies.


## 5. Conclusions

This systematic review and meta-analysis study, which to the best of our knowledge, is the first to report on the prevalence of KRAS (36.6%) and BRAF (5.6%) mutations in CRC patients in Asia. The result showed that the rate of KRAS and BRAF gene mutations in CRC among Asians is rising. The adult age was more associated with CRC prevalence, and the males have increase fold and poorer outcome than their female counterparts. Despite some limitations, the meta-analysis yielded impressive results. The total prevalence of KRAS and BRAF mutations, 36.6% and 5.6%, respectively, differs in various countries in Asia according to this meta-analysis. Furthermore, when the findings of this study were compared to those of other studies, it was discovered that the prevalence of these mutations obtained in our analysis conformed with them.



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