Abstract
BRAF immunohistochemistry (IHC) serves as a surrogate for BRAF p.V600E but shows variable performance across tumor types and institutions. This study evaluated BRAF IHC staining quality and interpretation in general pathology laboratories through a nationwide proficiency test (PT) in Taiwan, focusing on the most commonly encountered thyroid neoplasm and colorectal cancer. This PT was organized by the Taiwan Society of Pathology using a tissue microarray, containing six tumor cores with confirmed BRAF mutation status and one positive control. Participating laboratories performed BRAF IHC staining and interpretation independently, with results centrally reviewed for concordance, accuracy, and staining quality. Twenty-six pathology laboratories participated. Two laboratories failed the initial control check. Among the remaining 24, 17 (70.83%) demonstrated optimal staining, while 5 (20.83%) showed over-staining and 2 (8.33%) under-staining. No significant associations were found between staining quality and antibody clones, platforms, dilution folds, or assay types. Interpretation was highly concordant (100% agreement and accuracy) for tissues with 3 + or negative staining. However, discrepancies arose in tissues with 2 + intensity (50% positive, 41.67% negative, 8.33% equivocal) and 1 + intensity (83.33% disagreement with test results). The overall accuracy was 79.2%, with sensitivity at 58.3% and specificity at 100%. Under-calling was frequent in cases with 1 + staining (33 cores across 23 laboratories) and 2 + staining (3 cores across 3 laboratories). Our study highlights the importance of optimizing staining quality and reinforcing education on interpretation criteria. To minimize false-negative results, we recommend molecular confirmation for all cases exhibiting diffusely weak staining.
Keywords: BRAF, p.V600E, VE1, Immunohistochemistry (IHC), Proficiency testing
Introduction
The BRAF gene encodes a serine/threonine kinase in the MAPK signaling pathway and activating mutations promote oncogenic proliferation in various cancers. Among solid tumors, BRAF mutations are most frequently observed in thyroid cancer (43.3%), melanoma (29.4%), and colorectal cancer (11.4%). Class 1 mutations, including p.V600E, p.V600K, and p.V600R, account for the majority of BRAF mutations, with p.V600E being the most common [1]. The BRAF p.V600E mutation has important prognostic and therapeutic implications. In 2022, the U.S. Food and Drug Administration approved combined dabrafenib and trametinib as tumor-agnostic treatment for all solid tumors harboring this mutation, except colorectal cancer [2]. In colorectal cancer (CRC), this mutation is linked to poor prognosis, resistance to anti-EGFR therapy [3] and help rule out Lynch syndrome in mismatch repair-deficient cases [4].
Detection methods for BRAF p.V600E include Sanger sequencing, qPCR, next-generation sequencing (NGS), and immunohistochemistry (IHC). While NGS and qPCR are highly sensitive, they can be costly or less accessible. IHC is widely adopted in routine pathology due to its cost-effectiveness, rapid turnaround, and ability to provide spatial information, especially in low-tumor-content samples [5–7]. Since Capper et al. developed the mutation-specific VE1 antibody in 2011[8], IHC has been evaluated as a surrogate for molecular testing, though results vary by tumor type and technical factors, with inter-study inconsistencies and occasional discordance with sequencing [9–11].
Melanoma, CRC and papillary thyroid carcinoma (PTC) are among the most frequently studied cancer types for BRAF IHC [5]. Studies have shown that BRAF IHC generally performs reliably in melanoma and PTC, while findings in CRC have been inconsistent, with significant variability across studies [12–18]. Previous studies have linked staining quality to technical factors [16, 17, 19, 20] and evaluated different interpretive criteria [16, 21]. However, most of these investigations were conducted at single institutions, and the available meta-analyses are limited in their ability to standardize staining performance or quantify inter-laboratory concordance due to variability in specimen types and staining protocols.
In Taiwan, thyroid cancer and CRC are among the top ten malignancies [22] and are most commonly encountered in BRAF IHC interpretation, while cutaneous melanoma is a rare disease. We therefore conducted a nationwide proficiency test (PT) in Taiwan, focusing on BRAF IHC for these two tumor types. Our goals were to evaluate staining quality, interpretation consistency, and inter-laboratory concordance across multiple pathology laboratories.
Materials and methods
The study complied with local ethical regulations, and Institutional Review Board approval was exempted. A tissue microarray (TMA) was constructed with tissue cores of 2.0-mm diameter formalin-fixed paraffin-embedded tumor tissue. The TMA consisted of six cores of tumor tissues with molecularly confirmed BRAF mutation status, and one core of respiratory mucosa was included as a positive control [23]. The overall TMA design was adapted from the framework used in Nordic Immunohistochemical Quality Control (NordiQC) with similar core number [24]. However, in light of prior studies indicating inconsistent BRAF IHC performance in CRC, four of the six cores were selected from CRC cases with a range of staining intensities (1 + to 2 +) to better reflect diagnostic challenges in this tumor type. The original assessment of the immunohistochemical staining at the reference lab was performed using the VE1 in vitro diagnostic (IVD) monoclonal antibody (Ventana Medical Systems, Tucson, AZ, USA) at a ready-to-use concentration, on the Ventana BenchMark ULTRA automated staining platform. The details of each test sample are listed in Table 1.
Table 1.
Summary of the testing cores
| Tissue | Diagnosis | Sequencing Result | Consensus Staining Result | |
|---|---|---|---|---|
| Core 1 | Thyroid | NIFTP | BRAF WT (NRAS p.Q61R) | Negative (0) |
| Core 2 | Thyroid | Papillary carcinoma | BRAF p.V600E | Positive (3 +) |
| Core 3 | Colon | Adenocarcinoma | BRAF WT (NRAS p.G13R) | Negative (0) |
| Core 4 | Colon | Adenocarcinoma | BRAF p.V600E | Positive (2 +) |
| Core 5 | Colon | Adenocarcinoma | BRAF p.V600E | Positive (1 +) |
| Core 6 | Colon | Adenocarcinoma | BRAF WT (KRAS p.G12D) | Negative (0) |
NIFTP noninvasive follicular thyroid neoplasm with papillary-like nuclear features; WT wild type
The 2024 BRAF IHC stain PT activity was organized by the Proficiency Testing Committee of the Taiwan Society of Pathology and distributed to registered institutions. Each participating laboratory received one unstained, 3 μm-thick slides of the TMA. Participants performed BRAF IHC staining and interpreted the results independently, categorizing their responses as positive, negative, or others (with descriptive details). Staining technique details, including antibody clone, dilution, platform (if using an auto-stainer), and IHC assay protocol (In vitro diagnostics (IVD) antibody with IVD protocol, research-use only (RUO) antibody with laboratory-developed test (LDT) protocol, or IVD antibody with LDT protocol), were also submitted. The staining slides were sent back to the Proficiency Testing Committee for a central review by two expert pathologists (Y.-A.C. and J.-F.H.).
For the initial control check, any slides showing strong staining on the cilia of the respiratory mucosa was considered passed (Fig. 1a). The concordance and inter-laboratory variability of participant responses were evaluated. The accuracy of participant responses was assessed using molecular testing results as the standard reference (Table 1). Equivocal staining results typically trigger subsequent molecular testing and were therefore considered concordant to the molecular testing result for analysis.
Fig. 1.
VE1 antibody immunohistochemistry in tissue microarray for proficiency testing. Respiratory cilia should be stained in a strong intensity and served as an external positive control (800x) (a), while two participants failed from initial control check because of false negative staining (800x) (b). Representative images for 0, 1 +, 2 + and 3 + were demonstrated, respectively (c-f)
For staining quality assessment,"optimal,""under-staining,"or"over-staining"were categorized based on the following criteria: slides with a false-negative result in core 5 were classified as"under-staining,"while slides with a false-positive result, defined as granular cytoplasmic staining clearly distinguishable from the background, in core 6 were categorized as"over-staining". These results were reviewed and discussed by the two expert reviewers to reach a consensus.
For interpretation quality assessment, two expert pathologists (Y.-A.C. and J.-F.H.) independently reviewed each slide using criteria adapted from Capper et al. [8]. Slides showing unequivocal cytoplasmic staining were graded 1 +, 2 +, or 3 + according to intensity; complete absence of staining was considered 0 (Fig. 1c–f). The 1 + staining was extended to include diffuse faint expression clearly visible under high-power magnification (more than × 40) [13]. Any discrepancies in the intensities were resolved through consensus review of virtual slides. The concordance rate between the reviewers and participant responses were subsequently evaluated.
Statistical analyses were performed using R (version 4.4.2; R Foundation, Vienna, Austria). Fisher’s exact test with Monte Carlo simulation (10,000 replicates) assessed staining quality associations with antibody clone, platform, and assay, while the Kruskal–Wallis test evaluated dilution effects. Inter-laboratory variability was measured by Fleiss'kappa (0–1, with higher values indicating greater agreement). Data visualization was done using"ggplot2"[25].
Results
A total of 26 pathology laboratories registered for the 2024 BRAF IHC PT, with 15 located in northern Taiwan, five in central Taiwan, and six in southern Taiwan. The most commonly used clone of BRAF antibody was VE1 from Ventana (n = 12, 46.2%) and from Abcam (n = 11, 42.3%), followed by IHC 600 from GenomeMe (n = 3, 11.5%). The dilution folds utilized were as follows: 1:1 (n = 10, 38.5%), 1:2 (n = 2, 7.7%), 1:30 (n = 1, 3.8%), 1:50 (n = 3, 11.5%), 1:100 (n = 7, 26.9%), 1:150 (n = 2, 7.7%), and 1:400 (n = 1, 3.8%). For chromogenic detection, peroxidase with diaminobenzidine (DAB) was used in 24 laboratories (92.3%), and fast red was used in 2 laboratories (7.7%). All tests were performed on autostainers, including Ventana (n = 16, 61.5%), Leica (n = 9, 34.6%), and Dako (n = 1, 3.8%). The IHC assays varied significantly among the institutions, with seven using IVD antibodies with IVD protocols (n = 7, 26.9%), others using IVD antibodies with LDT protocols (n = 5, 19.2%), or RUO antibodies with LDT protocols (n = 14, 53.9%). The details of the methodologies from all institutes are summarized in Table 2.
Table 2.
Summary of staining methods
| Methods | N | % |
|---|---|---|
| Antibody clone | ||
| Clone VE1 | ||
| Ventana, predilute (IVD), cat no.:760–5095 | 12 | 46.2 |
| Abcam, cat no.: ab228461 | 11 | 42.3 |
| Clone IHC 600 | ||
| GenomeMe, cat. no.: IHC 600–100 | 3 | 11.5 |
| Dilution fold | ||
| 1:1 | 10 | 38.5% |
| 1:2 | 2 | 7.7% |
| 1:30 | 1 | 3.8% |
| 1:50 | 3 | 11.5% |
| 1:100 | 7 | 26.9% |
| 1:150 | 2 | 7.7% |
| 1:400 | 1 | 3.8% |
| Autostainer platform | ||
| Ventana | 16 | 61.5 |
| BenchMark ULTRA | 12 | 46.2 |
| Benchmark XT | 3 | 11.5 |
| Benchmark GX | 1 | 3.8 |
| Leica | 9 | 34.6 |
| BOND-III | 8 | 30.8 |
| BOND max | 1 | 3.8 |
| Dako Autostainer Link Omnis | 1 | 3.8 |
| IHC assay | ||
| RUO Ab LDT protocol | 14 | 53.8 |
| IVD Ab IVD protocol | 7 | 26.9 |
| IVD Ab LDT protocol | 5 | 19.2 |
| Detecting system | ||
| Fast red | 2 | 7.7% |
| DAB | 24 | 92.3% |
DAB diaminobenzidine; IHC immunohistochemistry; IVD in vitro diagnostics; LDT laboratory developed test; RUO research use only
All 26 participating laboratories returned their test slides for central expert review. Among them, two laboratories failed from the initial control check due to exhibiting false-negative results in the positive control (Fig. 1b). Notably, both laboratories utilized IVD antibody with LDT protocol on a different manufacturer's platform (Ventana VE1 predilute Ab + Leica BOND-III auto-stainer). The two laboratories were excluded for the substantial analysis.
Among the remaining 24 institutions, there was 100% concordance in the responses of cores 1, 2, 3, and 6, which exhibited staining intensities of either 0 or 3 +. In contrast, participant responses of core 4 failed to reach consensus, with a nearly equal distribution of positive (n = 12, 50%) and negative (n = 10, 41.67%) results, along with two laboratories reporting equivocal findings (8.33%). In core 5, the consensus of most participants (n = 20, 83.33%) was negative, with only 4 (16.67%) participants reported as positive. Overall, the 24 participants demonstrated fair agreement in their responses across all cores, with a Fleiss’ Kappa value of 0.66 (95% CI, 0.6–0.7; p < 0.001). The accuracy of participant responses for core 1, 2, 3 and 6 reached 100%. However, the accuracy in core 4 was 58.33%. In core 5, the participant consensus was contrary to the test result, with an accuracy of only 16.7%. The overall accuracy of participant responses was 79.2% (114/144 cores). The sensitivity was 58.3%, while specificity reached 100%. Table 3 demonstrated the summary of participant responses.
Table 3.
Summary of the participants’ responses
| Core 1 | Core 2 | Core 3 | Core 4 | Core 5 | Core 6 | |
|---|---|---|---|---|---|---|
| Positive | 0 | 24 | 0 | 12 | 4 | 0 |
| Negative | 24 | 0 | 24 | 10 | 20 | 24 |
| Equivocal | 0 | 0 | 0 | 2 | 0 | 0 |
| Total | 24 | 24 | 24 | 24 | 24 | 24 |
| Molecular results | Negative | Positive | Negative | Positive | Positive | Negative |
| Accuracy | 100% | 100% | 100% | 58.33%* | 16.67% | 100% |
*Two labs reported equivocal results and were consider concordant
Review of staining quality
Among the 24 laboratories, 17 (70.83%) achieved optimal results, five (20.83%) exhibited over-staining, and two (8.33%) displayed under-staining. No significant association was found between staining quality and antibody clones (p = 0.42), platforms (p = 0.08), or IHC assays (p = 0.28) (Table 4). Additionally, no significant relationship was observed between antibody dilution and staining quality among 14 laboratories using RUO antibodies with further dilution (Fig. 2, p = 0.95). Notably, within the overstaining group, eight cores showed non-specific cytoplasmic staining, including seven with BRAF wild-type colorectal tissue. These involved both fast red (2/2) and DAB (3/22) detection systems (Fig. 3a–d). Additional examples of over- and under-staining are shown in Fig. 3e–f.
Table 4.
Relationships between staining quality and methods
| Optimal | Over-staining | Under-staining | P-value | |
|---|---|---|---|---|
| Antibody Clone | 0.42 | |||
| VE1 (Ventana) | 9 | 1 | 0 | |
| VE1 (Abcam) | 6 | 3 | 2 | |
| IHC 600 (GenomeMe) | 2 | 1 | 0 | |
| Platform | 0.08 | |||
| Ventana | 13 | 3 | 0 | |
| Leica | 4 | 1 | 2 | |
| Dako | 0 | 1 | 0 | |
| IHC assay | 0.28 | |||
| RUO Ab LDT protocol | 7 | 4 | 2 | |
| IVD Ab IVD protocol | 7 | 0 | 0 | |
| IVD Ab LDT protocol | 3 | 1 | 0 |
IHC immunohistochemistry; IVD in vitro diagnostics; LDT laboratory developed test; RUO research use only
Fig. 2.
Boxplot demonstrated the relationships between dilution folds and staining quality
Fig. 3.
Representative images from over-staining and under-staining samples. (a) False positive staining in core 6, colorectal cancer (laboratory 23, 400x). (b) False positive staining in core 3, colorectal cancer (laboratory 23, 400x). (c) False positive staining using fast-red chromogen, colorectal cancer (laboratory 3, 400x). (d) False positive staining in core 1, NIFT-P (laboratory 23, 400x). (e–f) False negative staining in core 5, colorectal cancer (laboratory 15 and laboratory 16, 400x)
Review of interpretation
The concordance rate between reviewers and participants varied across institutions, with 100% agreement (6/6 cores) observed in one laboratory (4.17%), 83% agreement (5/6 cores) in twelve laboratories (50%), 67% agreement (4/6 cores) in nine laboratories (37.5%), and 50% agreement (3/6 cores) in two laboratories (8.33%). Overall, the agreement between reviewers and participants was 75% (108 out of 144 cores). All 36 cores with discrepancies between reviewers and participants exhibited issues of under-interpretation of 1 + or 2 + intensity as negative by participants. Specifically, in five laboratories with over-staining issues, eight cores from core 1, 3, and 6 showed false positives (1 + intensity) but were reported as “negative” by their institutions. In core 4, staining ranged from 1 + (n = 7) to 2 + (n = 17) across all slides. Despite this, ten laboratories initially reported them as negative (Fig. 4a-b), while two with 2 + staining reported them as equivocal (Fig. 4c-d). For core 5, 22 slides showed staining intensities of 1 + (n = 18) or 2 + (n = 4). Notably, all slides with a staining intensity of 1 + were reported as negative by the original institutions (Fig. 4e-f). Overall, the most frequent issue was the misinterpretation of 1 + staining as negative in 33 cores across 23 laboratories, and three laboratories under-called 2 + staining as negative.
Fig. 4.
Representative images from cores under-called by participants. (a) Core 4, 1 + intensity with participant response as negative (400x). (b) Core 4, 2 + intensity with participant response as negative (400x). (c) Core 4, 2 + intensity participant response as equivocal (400x). (d) Core 4, 2 + intensity with participant response as equivocal (400x). (e) Core 5, 1 + intensity with participant response as negative (400x). (f) Core 5, 1 + intensity with participant response as negative (400x)
Discussion
This proficiency test assessed the quality of BRAF immunohistochemistry (IHC) staining and interpretation in thyroid and colorectal cancers across clinical laboratories in Taiwan. Our findings highlight two key challenges: staining variability and interpretation discrepancies. While 100% consensus was achieved for cores with 0 or 3 + staining, significant inconsistencies arose in cores with 1 + or 2 + staining. Compared to molecular testing, overall accuracy was 79.2%, with 100% specificity but only 58.3% sensitivity. Over-staining (20.83%) was more prevalent in colorectal cancer specimens, while under-staining (8.33%) remained a concern. A 1 + staining control is therefore recommended to help detect under-staining. Interpretation concordance between reviewers and participants was 75%, with all discrepancies due to under-calling of 1 + and rarely 2 + cases. Overall, our results emphasize the need for continuing education focused on technical standardization, the use of appropriate controls, and interpretation criteria to improve diagnostic quality and reduce inter-laboratory variability.
In our study, we assessed staining quality among participants and evaluated the relationship with key analytical parameters, including antibody clone, platform, dilution fold, and IHC assay. Statistical analysis revealed no significant associations between these parameters and staining quality, aligning with most prior reports. Among the examined parameters, antibody clone performance is of particular interest. In our proficiency test, the widely adopted VE1 clone (n = 23) demonstrated robust performance. Notably, three laboratories that using the previously unreported clone IHC600 also achieved acceptable quality, with no statistically significant difference observed between the two clones. These findings suggests that IHC600 may represent a potential alternative to VE1 for clinical application. However, further validation in a larger cohort is warranted to confirm its reliability and diagnostic utility.
While previous studies have found limited correlation between antibody dilution and staining quality, Kuan et al. reported that dilutions above 200-fold may reduce nonspecific nuclear staining [16, 20, 21]. In contrast, the only laboratory in our cohort using a 400-fold dilution, applying the VE1 clone from Abcam on the Dako platform with an LDT protocol, exhibited mild cytoplasmic over-staining. As other detailed information, such as antigen retrieval and detection systems, was not collected, the basis for this finding remains unclear. Regarding staining platforms, earlier studies have generally concluded that platform choice alone does not significantly affect staining outcomes [16, 17], which is consistent with our findings.
In addition, two laboratories in our cohort demonstrated false-negative staining on positive controls and failed the initial quality control; both employed the VE1 antibody from Ventana using the Leica Bond-III platform with an LDT staining protocol. However, a large retrospective study on colorectal cancer reported comparable performance with this combination [16]. Similarly, Estrella et al. found that VE1 staining quality was not affected by the choice of automated stainer (Ventana vs. Leica) [17]. In thyroid cancer studies, only two reports have utilized this combination: one reported 100% sensitivity and 90.63% accuracy [26], while the other reported 88.89% sensitivity and 79.12% accuracy [27]. These discrepancies in reported performance metrics with the same antibody-platform combination indicate that current evidence is insufficient to consider this combination inherently problematic. The observed staining issues may instead reflect laboratory-specific variables not captured in our dataset.
Our study also found that overstaining was more frequently observed in colorectal cancer samples, particularly in the mucin-rich core (core 6), consistent with previous reports [4, 12, 16, 17, 20, 28]. This observation highlights that intrinsic tissue characteristics may contribute to staining variability. Taken together, our findings suggest that the evaluated analytical parameters do not significantly influence staining quality. To improve assay reliability, we recommend that validation protocols incorporate samples from diverse tissue types and that routine practice utilize positive control materials with weak to moderate staining intensity.
Currently, there is no universally accepted standard for IHC interpretation, with most studies utilizing criteria based on the percentage of stained tumor cells and staining intensity, tailored to their specific needs [16, 21]. The most widely adopted standard, described by Capper et al., defines positive cases as those with unambiguous cytoplasmic staining in a substantial portion of viable tumor cells, and faint diffuse staining, isolated nuclear staining, weak staining of scattered cells, or staining in monocytes or macrophages is considered negative [8, 29]. However, weak staining remains a major challenge, affecting diagnostic consistency. For instance, in colorectal cancer, non-specific staining complicates interpretation, with weak staining presenting challenges in approximately 10% of cases [30]. Similarly, in both thyroid and colorectal cancers, 1 + staining is variably classified as negative [16, 21, 31–33] or equivocal, warranting molecular testing [13, 20]. Our findings indicate that most general pathologists interpret weak staining as negative, with varied interpretations for weak-to-moderate staining. Even experienced pathologists struggle with weak staining evaluation. Furthermore, our previous study revealed that 1 + staining can be occasionally observed in BRAF wild-type colorectal cancers [13]. Therefore, we recommend generally adhering to the criteria proposed by Capper et al., with an expanded definition of 1 + staining to include diffuse faint cytoplasmic expression, and considered 1 + as equivocal. As supported by several previous studies [13, 20, 30, 34] and illustrated in Fig. 5, molecular testing is recommended for all cases interpreted as 1 + to ensure diagnostic accuracy. Standardizing the interpretation of weak staining may help reduce interobserver variability and improve clinical reliability.
Fig. 5.
Algorithmic approach integrating BRAF immunohistochemistry with molecular confirmation
The main limitation of this pilot PT study is its representativeness, involving only 26 participants and six tissue cores. Additionally, focusing solely on thyroid and colorectal neoplasms may limit applicability to other cancers, as BRAF IHC performance varies by tumor origin. Despite these limitations, this PT provides a valuable overview of BRAF IHC performance in Taiwan, identifying key staining and interpretation issues to guide improvements. Future rounds of PT should expand case diversity and include comprehensive documentation of technical parameters, such as incubation times, antigen retrieval methods, and amplification systems, to enable more standardized comparisons and foster inter-laboratory harmonization.
In conclusion, our PT survey evaluated BRAF IHC staining and interpretation in Taiwanese pathology laboratories. We recommend using control samples from diverse tissue sources, including those with staining intensities ranging from 1 + to 2 +, to better calibrate interpretation thresholds. Given the tendency for conservative interpretation of weak staining, targeted educational initiatives and the application of confirmatory molecular testing for equivocal (1 +) cases are essential to minimize the risk of false-negative results.
Acknowledgements
This study was presented in part as a poster at the annual meeting of the United States and Canadian Academy of Pathology on March 26th, 2025, Boston, MA, USA.
Author contribution
Yun-An Chen and Jen-Fan Hang conducted the central review, performed statistical analysis, and interpreted the data. Yun-An Chen drafted the manuscript. Jyie-Yu Lai managed administrative tasks and sample distribution. Chih-Yi Hsu, Huang-Chun Lien, and Jen-Fan Hang contributed to specimen acquisition and critically reviewed and revised the manuscript. Jen-Fan Hang oversaw the study design and supervision. All authors read and approved the final manuscript.
Funding
Open Access funding enabled and organized by National Yang Ming Chiao Tung University. The study has no specific funding. Open access for this article is supported by the transformative agreement between National Yang Ming Chiao Tung University and Springer Nature.
Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval
The study complied with local ethical regulations.
Competing interests
The authors declare that there are no conflicts of interest.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Hanrahan AJ, Chen Z, Rosen N, Solit DB (2024) BRAF - a tumour-agnostic drug target with lineage-specific dependencies. Nat Rev Clin Oncol 21(3):224–247 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Subbiah V, Kreitman RJ, Wainberg ZA, Gazzah A, Lassen U, Stein A et al (2023) Dabrafenib plus trametinib in BRAFV600E-mutated rare cancers: the phase 2 ROAR trial. Nat Med 29(5):1103–1112 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.De Roock W, Claes B, Bernasconi D, De Schutter J, Biesmans B, Fountzilas G et al (2010) Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis. Lancet Oncol 11(8):753–762 [DOI] [PubMed] [Google Scholar]
- 4.Toon CW, Walsh MD, Chou A, Capper D, Clarkson A, Sioson L et al (2013) BRAFV600E Immunohistochemistry Facilitates Universal Screening of Colorectal Cancers for Lynch Syndrome. Am J Surg Pathol 37(10):1592 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Wang W, Lian B, Xu C, Wang Q, Li Z, Zheng N et al (2024) Expert consensus on the diagnosis and treatment of solid tumors with BRAF mutations. Inno (Camb) 5(6):100661
- 6.Ritterhouse LL, Barletta JA (2015) BRAF V600E mutation-specific antibody: a review. Seminars Diag Pathol 32(5):400–408 [DOI] [PubMed]
- 7.Rivera JP, Yeh YC, Chen PC, Hang JF (2024) Multifocal papillary thyroid carcinomas with discordant molecular drivers: emphasizing the morphology and collision tumors. Am J Surg Pathol 48(11):1359–1371 [DOI] [PubMed]
- 8.Capper D, Preusser M, Habel A, Sahm F, Ackermann U, Schindler G et al (2011) Assessment of BRAF V600E mutation status by immunohistochemistry with a mutation-specific monoclonal antibody. Acta Neuropathol 122(1):11–19 [DOI] [PubMed] [Google Scholar]
- 9.Sperveslage J, Gierke M, Capper D, Honegger J, Sipos B, Beschorner R et al (2013) VE1 immunohistochemistry in pituitary adenomas is not associated with BRAF V600E mutation. Acta Neuropathol 125(6):911–912 [DOI] [PubMed] [Google Scholar]
- 10.Farzin M, Toon CW, Clarkson A, Sioson L, Gill AJ (2014) BRAF V600E mutation specific immunohistochemistry with clone VE1 is not reliable in pituitary adenomas. Pathology 46(1):79–80 [DOI] [PubMed] [Google Scholar]
- 11.Mordes DA, Lynch K, Campbell S, Dias-Santagata D, Nose V, Louis DN et al (2014) VE1 antibody immunoreactivity in normal anterior pituitary and adrenal cortex without detectable BRAF V600E mutations. Am J Clin Pathol 141(6):811–815 [DOI] [PubMed] [Google Scholar]
- 12.Lasota J, Kowalik A, Wasag B, Wang ZF, Felisiak-Golabek A, Coates T et al (2014) Detection of the BRAF V600E mutation in colon carcinoma: critical evaluation of the immunohistochemical approach. Am J Surg Pathol 38(9):1235–1241 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Hang JF, Li AFY, Chang SC, Liang WY (2016) Immunohistochemical detection of the BRAF V600E mutant protein in colorectal cancers in Taiwan is highly concordant with the molecular test. Histopathology 69(1):54–62 [DOI] [PubMed] [Google Scholar]
- 14.Huang WK, Kuo TT, Wu CE, Cheng HY, Hsieh CH, Hsieh JJ et al (2016) A comparison of immunohistochemical and molecular methods used for analyzing the BRAF V600E gene mutation in malignant melanoma in Taiwan. Asia Pac J Clin Oncol 12(4):403–408 [DOI] [PubMed] [Google Scholar]
- 15.Singarayer R, Mete O, Perrier L, Thabane L, Asa SL, Van Uum S et al (2019) A Systematic Review and Meta-Analysis of the Diagnostic Performance of BRAF V600E Immunohistochemistry in Thyroid Histopathology. Endocr Pathol 30(3):201–218 [DOI] [PubMed] [Google Scholar]
- 16.Dvorak K, Higgins A, Palting J, Cohen M, Brunhoeber P (2019) Immunohistochemistry with Anti-BRAF V600E (VE1) Mouse Monoclonal Antibody is a Sensitive Method for Detection of the BRAF V600E Mutation in Colon Cancer: Evaluation of 120 Cases with and without KRAS Mutation and Literature Review. Pathol Oncol Res 25(1):349–359 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Estrella JS, Tetzlaff MT, Bassett RL Jr, Patel KP, Williams MD, Curry JL et al (2015) Assessment of BRAF V600E Status in Colorectal Carcinoma: Tissue-Specific Discordances between Immunohistochemistry and Sequencing. Mol Cancer Ther 14(12):2887–2895 [DOI] [PubMed] [Google Scholar]
- 18.Adackapara CA, Sholl LM, Barletta JA, Hornick JL (2013) Immunohistochemistry using the BRAF V600E mutation-specific monoclonal antibody VE1 is not a useful surrogate for genotyping in colorectal adenocarcinoma. Histopathology 63(2):187–193 [DOI] [PubMed] [Google Scholar]
- 19.Dvorak K, Aggeler B, Palting J, McKelvie P, Ruszkiewicz A, Waring P (2014) Immunohistochemistry with the anti-BRAF V600E (VE1) antibody: impact of pre-analytical conditions and concordance with DNA sequencing in colorectal and papillary thyroid carcinoma. Pathology 46(6):509–517 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kuan SF, Navina S, Cressman KL, Pai RK (2014) Immunohistochemical detection of BRAF V600E mutant protein using the VE1 antibody in colorectal carcinoma is highly concordant with molecular testing but requires rigorous antibody optimization. Hum Pathol 45(3):464–472 [DOI] [PubMed] [Google Scholar]
- 21.Parker KG, White MG, Cipriani NA (2020) Comparison of Molecular Methods and BRAF Immunohistochemistry (VE1 Clone) for the Detection of BRAF V600E Mutation in Papillary Thyroid Carcinoma: A Meta-Analysis. Head Neck Pathol 14(4):1067–1079 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Ministry of Health and Welfare, Health Promotion Administration (2024) Cancer registry annual report: Republic of China (2022 data). Ministry of Health and Welfare, Taipei. https://www.hpa.gov.tw/Pages/List.aspx?nodeid=269. Accessed 23 Apr 2025
- 23.Jones RT, Abedalthagafi MS, Brahmandam M, Greenfield EA, Hoang MP, Louis DN et al (2015) Cross-reactivity of the BRAF VE1 antibody with epitopes in axonemal dyneins leads to staining of cilia. Mod Pathol 28(4):596–606 [DOI] [PubMed] [Google Scholar]
- 24.Vyberg M, Nielsen S (2016) Proficiency testing in immunohistochemistry—experiences from Nordic Immunohistochemical Quality Control (NordiQC). Virchows Arch 468(1):19–29 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer-Verlag, New York
- 26.Bullock M, O’Neill C, Chou A, Clarkson A, Dodds T, Toon C et al (2012) Utilization of a MAB for BRAF(V600E) detection in papillary thyroid carcinoma. Endocr Relat Cancer 19(6):779–784 [DOI] [PubMed] [Google Scholar]
- 27.Kim YH, Choi Eun S, Yoon SO, Hong SW (2014) A testing algorithm for detection of the B-type Raf kinase V600E mutation in papillary thyroid carcinoma. Human Pathol 45(7):1483–8 [DOI] [PubMed] [Google Scholar]
- 28.Bledsoe JR, Kamionek M, Mino-Kenudson M et al (2014) BRAF V600E immunohistochemistry is reliable in primary and metastatic colorectal carcinoma regardless of treatment status and shows high intratumoral homogeneity. Am J Surg Pathol 38(10):1418–1428 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Capper D, Berghoff AS, Magerle M, Ilhan A, Wöhrer A, Hackl M et al (2012) Immunohistochemical testing of BRAF V600E status in 1,120 tumor tissue samples of patients with brain metastases. Acta Neuropathol 123(2):223–233 [DOI] [PubMed] [Google Scholar]
- 30.Schafroth C, Galván JA, Centeno I, Koelzer VH, Dawson HE, Sokol L et al (2015) VE1 immunohistochemistry predicts BRAF V600E mutation status and clinical outcome in colorectal cancer. Oncotarget 6(39):41453–41463 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Fisher KE, Neill SG, Ehsani L, Caltharp SA, Siddiqui MT, Cohen C (2014) Immunohistochemical Investigation of BRAF p.V600E Mutations in Thyroid Carcinoma Using 2 Separate BRAF Antibodies. Appl Immunohistochem Mol Morphol 22(8):562 [DOI] [PubMed] [Google Scholar]
- 32.Ghossein RA, Katabi N, Fagin JA (2013) Immunohistochemical Detection of Mutated BRAF V600E Supports the Clonal Origin of BRAF-Induced Thyroid Cancers Along the Spectrum of Disease Progression. J Clin Endocrinol Metab 98(8):E1414–E1421 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Løes IM, Immervoll H, Angelsen JH, Horn A, Geisler J, Busch C et al (2014) Performance comparison of three BRAF V600E detection methods in malignant melanoma and colorectal cancer specimens. Tumour Biol 36(2):1003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Pyo JS, Sohn JH, Kang G (2016) Diagnostic Accuracy of BRAF Immunohistochemistry in Colorectal Cancer: a Meta-Analysis and Diagnostic Test Accuracy Review. Pathol Oncol Res 22(4):831–837 [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.