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Epidermal growth factor receptor mutations in adenocarcinoma lung: Comparison of techniques for mutation detection Shukla S, Pandey RK, Mishra S, Tripathi S, Garg R, Gupta G, Husain N



   Abstract  

Background: Targeted therapy using tyrosine kinase inhibitors in cases of non-small-cell lung carcinoma (NSCLC) that harbor epidermal growth factor receptor (EGFR) mutations has drastically improved the overall survival rate. The current study estimated the frequency of EGFR mutations in the Indian population by analyzing the diagnostic parameters of various techniques available for the detection of these mutations. Materials and Methods: A case series of 100 histologically diagnosed and immunohistochemically confirmed NSCLC with the adenocarcinoma phenotype comprises the study sample. EGFR mutations were detected using clone-specific immunohistochemistry (IHC), real-time polymerase chain reaction (PCR), and Sanger sequencing. Results: EGFR mutations were identified in 48% cases with 72.78% mutations involving exon 19. Clone-specific IHC had a low sensitivity of 46.43%, and the specificity was 79.17%. Sanger sequencing yielded interpretable results in 16% cases only, which were in concordance with the results of real-time PCR. Conclusion: EGFR mutations are increasingly being explored for targeted therapy and personalized medicine. Real-time PCR was found to be the best and the most accurate method for the detection of somatic EGFR mutations in adenocarcinoma primarily in the lungs.

Keywords: Clone-specific immunohistochemistry, EGFR mutations, lung adenocarcinoma, real-time PCR, sequencing

How to cite this article:
Shukla S, Pandey RK, Mishra S, Tripathi S, Garg R, Gupta G, Husain N. Epidermal growth factor receptor mutations in adenocarcinoma lung: Comparison of techniques for mutation detection. Indian J Pathol Microbiol 2022;65:296-304



How to cite this URL:
Shukla S, Pandey RK, Mishra S, Tripathi S, Garg R, Gupta G, Husain N. Epidermal growth factor receptor mutations in adenocarcinoma lung: Comparison of techniques for mutation detection. Indian J Pathol Microbiol [serial online] 2022 [cited 2022 May 4];65:296-304. Available from: https://www.ijpmonline.org/text.asp?2022/65/2/296/343159

   Introduction   Top

The discovery of mutations that have predictive and prognostic implications has largely altered treatment protocols for non-small-cell lung carcinoma (NSCLC), particularly the adenocarcinoma phenotype.[1] Most patients present with advanced disease, where testing for predictive and prognostic markers with targeted therapy is the mainstay of treatment.[2] The use of personalized medicine has drastically improved overall survival in NSCLC. Somatic mutations within the tyrosine kinase domain of epidermal growth factor receptor (EGFR) ranges from ~15% in Caucasians to ~50% in east Asians; 95% of such mutations have been found in adenocarcinomas.[3],[4] The EGFR protein is present on the cell membrane and in NSCLC mutations in the tyrosine kinase domain of the EGFR result in the requirement of very little growth factor to flip on the switch, which once turned on results in the cancer cell being driven to grow and divide essentially through this one signal.[4] The US Food and Development Association has approved the use of tyrosine kinase inhibitors (TKIs) for the treatment of EGFR mutated lung cancers that harbor somatic mutations as first-line therapy.[1] There are various methods available for the detection of EGFR mutations in NSCLC. Sensitive molecular techniques for the detection of EGFR mutations include quantitative real-time polymerase chain reaction (PCR) using specific probes or the amplified refractory mutation system (ARMS) technology. Direct Sanger sequencing is also employed; however, it has a lower sensitivity.[5] The use of mutant-specific immunohistochemistry (IHC) antibodies has also gained popularity due to their low cost and easy technical interpretation. Next-generation sequencing (NGS) is also being recommended for somatic mutation detection.[6],[7] The current study was undertaken with the objectives to detect the frequency of EGFR mutations in the Indian population to compare the clone-specific EGFR IHC antibodies, direct Sanger sequencing used for the detection of EGFR mutations with real-time PCR as the gold standard, and to analyze the clinicopathological and histomorphological features of cases that harbor EGFR mutations with mutation-negative cases.

   Materials and Methods   Top

This was a tertiary care hospital-based case series that included 100 cases of NSCLC. The study was conducted for three years after approval from the Institutional ethical committee. A detailed clinical and radiological assessment was done. Biopsies from both primary and metastatic sites of NSCLC adenocarcinoma, adenosquamous carcinoma, or unspecified carcinoma excluding the squamous cell carcinoma subtype were included in the study. The cases were classified based on histopathology as per the recommendations of the 2015 World Health Organization classification criteria for lung tumors. A basic panel of IHC that included thyroid transcription factor-1 (TTF-1) and napsinfor confirmation of adenocarcinoma as well as p40 to exclude squamous NSCLC was performed as applicable.

Real-time PCR for EGFR mutation detection

Real-time PCR was performed in 100 cases. The FFPE tissue blocks were sectioned at 3–4 μm using an automated microtome (Leica, Germany). The specimen was lysed and incubated with protease and binding buffer, following which isopropanol was added and centrifugation was done. The amount of genomic DNA was spectrophotometrically determined and adjusted to a fixed concentration to be added to the amplification/detection mixture. The real-time PCR kit used was EGFR RGQ PCR kit (Qiagen technologies, Manchester UK) that detects 28 somatic mutations that span over exons 18 to 21.

Clone-specific IHC for detection of EGFR mutations

IHC was used for the detection of EGFR mutations using clone-specific IHC antibodies E746-A750 del-Specific Rabbit mAb (Cell Signaling, Danvers, MA) and L858R Mutant-Specific Rabbit mAb (Cell Signaling, Danvers, MA) was performed in 100 cases. The standard protocol for IHC was followed; the antigen retrieval was performed in Pascal (DAKO Cytomation, California) using the EDTA buffer (pH 9.0). Sections were incubated for an hour with E746-A750 del-specific Rabbit mAb and L858R Mutant-Specific Rabbit mAb, which were diluted at 1:100 using tris-HCl buffer antibody diluents (Dakopatts, Denmark). This was followed by treatment with a polymer-based secondary antibody kit (Dakopatts, Envision kit, Denmark). Bound antibody was visualized using diaminobenzidine, according to the manufacturer’s instructions. Sections were counter-stained with hematoxylin and mounted. Positive (cell lines) and negative (by omitting primary antibody) controls were run with all batches. Cytoplasmic and/or membranous staining was evaluated and a semi-quantitative assessment was done estimating the staining intensity and percentage of tumor cells that were positive. The following grades were given: Grade 0-No staining, Grade 1-Faint staining +/++ in <10% cells, Grade 2: Staining of intensity ++ in >10% cells OR +++ <10% cells, Grade 3: Strong granular staining/+++ in >10% cells. Samples with grade 0 are considered negative; grades 1 and 2 are designated as equivocal while grade 3 was considered as positive.

Sequencing for EGFR mutation detection

Direct Sanger sequencing was attempted in 100 cases. The following protocol was used: -DNA Isolation: Genomic DNA was isolated from tumor tissue by using QIAamp DNA FFPE Tissue Kit (Cat 56404, Qiagen, USA) as per the manufacturer’s instruction. The quality of DNA was checked on Nanodrop (Denovix, USA) by taking optical absorbance at 260/280. EGFR Mutation Screening: EGFR exons 19 and 21 were amplified by using the primer set as described in [Table 1]. Conventional Nested PCR was carried out in a 25-μl reaction mixture containing 4 μl of DNA, 12.5 μl of PCR Master Mix (Invitrogen, USA), and 0.5 μM of each forward and reverse primer, and the volume was adjusted with nuclease-free water. The PCR condition was as follows: 1 cycle at 94°C for 9 min, followed by 40 cycles each consisting of 94°C for 1 min, 60°C for 1 min, and 72°C for 2 min, and a final cycle at 72°C for 5 min. Presence-specific bands were checked by agarose gel electrophoresis of the original PCR product. One microliter of the original PCR product was sequenced using BigDye Terminator v3.1 cycle sequencing kit and an ABI PRISM 3500 genetic analyzer (Applied Biosystem, Foster City, CA, USA).

The technique for Sanger sequencing was standardized and sequencing was performed in all 100 cases as per the protocol with a positive and negative control in every batch.

Histomorphological analysis

The histomorphological analysis was done in terms of the pattern of arrangement of the cells that included solid, micropapillary, acinar, lepidic, loose clusters, or dispersed cells along with the presence of mucin. The presence or absence of necrosis was assessed and tumors were histologically graded into well, moderately, or poorly differentiated lesions. The morphology of the cases that harbored driver mutations was compared with cases that had wild phenotypes.

Statistical analysis

Statistical analysis was performed using IBM-Statistical Package for Social Sciences (International Business Machines Corporation, New York, USA) analysis software, version 16. The Chi-square test was used for the categorical variables. All P values were calculated with two-sided tests, and P ≤ 0.05 was considered significant.

   Results   Top

Clinicopathological features

This prospective cases series included 100 cases of NSCLC adenocarcinoma, adenosquamous carcinoma, or unspecified carcinoma subtype. The age range varied from 26 to 88 years with a mean of 56.85 years. The maximum number of cases was within the age range of 51–60 years (39%). The M:F ratio was 1.6:1. The biopsy was performed from lung/pleura in 87% of cases, while metastatic sites were biopsied in 13% of cases. The most common metastatic site was the liver (n = 6) followed by lymph nodes (n = 4). The primary site was confirmed to lung with the aid of IHC in all metastatic cases. The most common clinical finding was cough, followed by breathlessness and hemoptysis. The history of smoking was obtained in 81/100 cases; 64.19% (n = 52/81) were non-smokers. 22.22% (n = 18/81) were smokers, while 13.58% (n = 11/81) were ex-smokers. Immunohistochemistry for TTF-1 was performed in 77/100 cases; 74.03% (n = 57/77) were positive for TTF-1 while 25.97% (n = 20/77) were negative for TTF-1. Squamous differentiation was identified with the aid of IHC (p-40) in 2% of cases. The histopathological diagnosis was NSCLC- adenocarcinoma in 80%, NSCLC adenocarcinoma with squamous differentiation in 2%, NSCLC-undifferentiated carcinoma in 5% cases, and metastatic NSCLC adenocarcinoma in 13% cases.

Real-time PCR for EGFR mutation detection

Real-time PCR for EGFR mutations was performed using the kit from Qiagen technologies (EGFR RGQ PCR kit) for the detection of EGFR exon 18, 19, 20, and 21 somatic mutations. EGFR mutations were identified in 48% cases (n = 48/100). A single mutation was identified in 91.67% (n = 44/48) cases, while 8.33% (n = 4/48) cases harbored multiple mutations. In the single mutation group, the EGFR mutations were distributed over exons 18 (4.55%), 19 (72.73%), 20 (4.55%), and 21 (18.18%). In the multiple mutation group, three cases had mutations in exon 19 and exon 21 while one case had mutations in exon 19 and exon 20.

Characteristics of cases with EGFR mutations

The age range of the patients varied from 40 years to 88 years with a mean of 57.11 years. EGFR mutations were more common in females, which was statistically significant (P = 0.0053) when compared with the EGFR negative group [Table 2].

Table 2: Demographic features and correlation of Clinicopathological characteristics with the presence of EGFR mutations in NSCLC

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IHC for EGFR mutation detection

IHC testing using clone-specific IHC antibodies [EGFR monoclonal antibodies E746-A750 del-specific (CST) and the L858R mutant-specific (CST)] for the detection of EGFR mutations was performed in 100 cases. IHC was negative in 72 cases, positive in 13 cases, and equivocal in 15 cases. Among the positive cases, 9/13 (69.23%) were positive for the E740-A750 mutation while 4/13 (30.77%) were positive for the L858R deletion. Among the equivocal cases, 12/15 (80%) were equivocal for the E740-A750 mutation while 3/15 (20%) were equivocal for the L858R deletion.

When compared with real-time PCR, the sensitivity of clone-specific IHC was 46.43% (CI = 27.51% to 66.13%), and the specificity was 79.17% (CI = 67.98% to 87.84%), with a positive predictive value of 46.43% and a negative predictive value of 79.17% [Figure 1].

Figure 1: (a-d) EGFR mutational analysis using monoclonal antibodies: (a and b) Positive for E746-A750 del-specific and negative for L858R mutant-specific [DAB ×100}, (c and d) Positive for L858R mutant-specific and negative for E746-A750 del-specific [DAB ×50], (e) Real-time PCR performed on the FFPE tissue with mutation-positive for L858R

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Sequencing for detection of EGFR mutations

Sanger sequencing was attempted in 100 cases. Nested PCR was performed for amplification of exon 19 and exon 21 [Figure 2]a and [Figure 2]b. The amplified PCR products were sequenced using specific primers [Table 1], and internal sequencing control (PGEM) was run with each batch to check the performance of the Sanger sequencer (3500 Genetic analyzer). Sequencing batches were run using the isolated DNA in all 100 cases. In 40 cases, the quantity of DNA was very low and hence was not detected in sequencing. In the remaining 60 cases, the sequencing cycle was completed and results were obtained in 16 cases (11 cases were negative and five cases were positive). The results were in concordance with the real-time PCR results. In 44 cases, there was a background signal and clear peaks were not obtained in Sanger sequencing. The reason for inconclusive results in Sanger sequencing can be attributed to poor quality DNA (DNA fragmentation) and low quantity of the DNA [Figure 3] and [Figure 4].

Figure 2: (a) Agarose gel electrophoresis L1-L6-350 bp PCR product for Exon 19 amplification, L-7 100 bp DNA ladder. (b) Agarose gel electrophoresis L-1 100 bp DNA ladder. L2-L5-390 bp PCR product for Exon 21 amplification

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Figure 3: Sequencing of internal sequencing control (PGEM) to check the instrument performance

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Figure 4: (a) Analysis of multiple cases on SeqScape Software (version 3) with reference gene. Cases negative in real-time PCR; no mutation was detected using Sanger Sequencing. (b) EGFR Exon 21 (L858R) point mutation as detected by direct sequencing (as indicated by arrow). (c) Sanger sequencing results in cases with low quality DNA with excessive background

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The histomorphological features of the EGFR real-time PCR positive (n = 48) and the EGFR real-time PCR negative (n = 52) were analyzed. Most of the cases had a mixed pattern. In the EGFR positive group, the most common pattern was singly dispersed cells or cells in loosely cohesive clusters (81.81%), followed by the acinar pattern (77.27%), which was statistically significant (P = 0.003) when compared with the EGFR negative group. Necrosis was present in 27.27% of cases in the EGFR positive group, and 68.18% of cases were moderately differentiated with a nuclear grade of 2 (68.18%), which was statistically significant (P = 0.01) when compared with the EGFR negative group [Figure 5].

Figure 5: Histomorphological features of EGFR positive cases: (a) Acinar pattern, (b) Singly dispersed cells with severe nuclear pleomorphism, and (c) Solid clusters with central necrosis (Arrow) [a-c=H and Ex200]

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   Discussion   Top

The EGFR gene spans over exons 18 to 21 that code for the tyrosine kinase part of the receptor. About 45% of sensitizing mutations are in-frame deletions in exon 19, making them the most common EGFR mutations. About 40%–45% of the sensitizing mutations are point mutations in exon 21, the most common being L858R (at the “point” in the 858th position, the normal amino acid leucine (L) is switched out for an arginine (R), which changes the protein function). Most of the remaining mutations are not sensitive to EGFR TKIs; however, they drive the cancer cells to grow. The most important of these is the T790M, a point mutation in exon 20 resulting in the substitution of methionine (M) for threonine (T). Mutations in exon 20 have also been associated with resistance to TKI therapy.[3],[4],[5],[6] EGFR mutations were detected in 48% of cases in this study. The frequency of EGFR mutations among the various studies conducted in the Indian subcontinent varied from 16.6% to 40.3% [Table 3]. In the study conducted by Shi et al.[5], the frequency of EGFR mutations in India was reported as 22.2%. The mutation frequency in the other Asian countries as reported by Shi et al.[5] was 50.2% in China, 47.2% in Hong Kong, 52.3% in the Philippines, 62.1% in Taiwan, 53.8% in Thailand and 64.2% in Vietnam. EGFR mutations were more common in females with a mean age of 57.11 years, which is in concordance with the results of Kota et al.,[11] Veldore et al.[14], and Shi et al.[5], and contradictory to the results of the study conducted by Bhatt et al.[15]

In this study, 91.67% of cases had a single mutation while 8.33% of cases had compound mutations. Veldore et al.[14] reported compound mutations in 1.1% of cases. In the study conducted by Kobayashi et al.[21] compound mutations were identified in 14% of cases and most of the cases responded well to TKI therapy. In this study, exon 19 and exon 21 mutations together constitute 90.91% of all mutations. This finding is in concordance with the reports published by various Indian studies [Table 3]. The frequency of exon 20 mutations in the various Indian studies varied from 2.8% to 25.39%. Exon 20 mutations confer resistance to the classical TKI therapy that is given in cases with harbor EGFR mutations; thus, the detection of exon 20 mutations is therapeutically significant.[18],[19],[20]

EGFR mutation detection is now recommended by molecular techniques. Yu et al.[22] developed specific monoclonal primary antibodies that are E746-A750 del-specific on exon 19 and the L858R mutant-specific on exon 21. The detection rate of EGFR protein over-expression using these specific antibodies as previously published in the literature was comparable to the molecular methods. Kawahara et al.[3] reported a sensitivity of 81.4% and a specificity of 97.5% using clone-specific IHC for the detection of EGFR mutations. However, the overall sensitivity of these clone-specific antibodies varied from 47% to 92% in different studies using the same antibodies.[22],[23] In this study, the sensitivity of clone-specific IHC was 46.43% and the specificity was 79.17%. This can partly be explained by the presence of rarer mutations or detections of mutations that are not detected by clone-specific IHC. Jain et al.[10] reported a sensitivity of 81.8% and a specificity of 100% using clone-specific IHC when compared with the high-resolution melting analysis. Based on this study, it can be implied that detection of EGFR mutations using clone-specific IHC antibodies has fair specificity but the sensitivity is low. These findings are in concordance with the reports published by Ragazzi et al.,[24] Seo et al.[25], and Bondgaard et al.[26] Additionally, mutations of exon 20 (T790M) are not detected using IHC as the IHC clones detect mutations of exon 19 and exon 21 only. Detection of exon 20 mutations is essential as these mutations are responsible for resistance to tyrosine kinase inhibitor therapy. Therefore, IHC is not recommended as an alternative to real-time PCR for the detection of EGFR mutations.

In the present study, EGFR mutations detection using Sanger sequencing yielded reportable results in 16% of cases. This can be explained partly by the requirement of a high tumor load for Sanger sequencing. The load required is about 10 to 20%. In the present study, most of the biopsies were small trucut cores in which the DNA concentration and tumor load were below the required criteria of Sanger sequencing. Additionally, adequate fixation of tissues in 10% neutral buffered formalin is essential. The biopsy tissue should contain viable tumors and the presence of tumor necrosis further degrades tumor DNA quality that leads to inconclusive results in Sanger sequencing. Warth et al.[27] stated that an important reason for failure to obtain results using Sanger sequencing is due to the admixture of non-neoplastic cells with tumor cells. This admixture leads to dilution of tumor DNA, causing low-frequency signals. Hence, it is essential to visualize the tumor area before DNA isolation to avoid admixture of non-neoplastic cells with tumor cells. In the study conducted by Zhang et al.[6], it was concluded that the ARMS technique has a higher sensitivity when compared with Sanger sequencing for the detection of EGFR mutations. Gao et al.[7] stated that compared with Sanger sequencing, NGS and qualitative PCR assays have significantly higher sensitivity, as Sanger failed to detect variants with mutation rates lower than 15%. Sanger sequencing is not a good method for the detection of somatic EGFR mutations in adenocarcinoma lung in cases where small biopsies are sent for testing.

In the case of molecular testing in lung adenocarcinoma, tissue is always an issue. It is recommended that during grossing and processing of lung biopsies, adequate precautions are taken to preserve tissue for ancillary testing. If multiple core biopsies have been taken out, then an attempt should be made to embed each core separately so that sufficient tissue remains for further molecular diagnostics. During microtomy, when sections are cut for routine diagnostics, additional sections should be taken, which can be further used for testing of molecular markers. However, it is essential to accurately subtype the tumor; therefore, histological diagnosis should not be compromised. In cases of small biopsy/trucut biopsy, in certain instances, accurate tumor typing cannot be achieved. The pathologist should precisely categorize the tumor as either non-small-cell or small-cell subtype. It is essential to try and judiciously use IHC, namely for TTF-1, and a single squamous maker like p-40 to further sub-categorize the tumor as either adenocarcinoma or squamous cell carcinoma. If specific sub-classification of the tumor cannot be achieved, it is best to label such lesions as only NSCLC. In these cases, accurate categorization is performed in larger biopsies or resection specimens.[28]

In this study, the presence of an acinar pattern in the group that harbored EGFR mutations was statistically significant when compared with the EGFR negative group. In the study conducted by Marotti et al., most of the EGFR positive tumors had morphology like the bronchiole-alveolar carcinoma. Necrosis was absent in a majority of EGFR positive cases, which is concordant with the findings of Li et al.[29] and Marotti et al.[30] In this study, the cases that had EGFR mutations were moderately differentiated with moderate nuclear pleomorphism. However, in the studies conducted by Marotti et al. and Li et al., EGFR positive tumors lacked nuclear pleomorphism.[29],[30],[31],[32],[33]

This study has identified the frequency of EGFR mutations in the Indian context and defined the specific type of EGFR mutation. The findings of this study indicate that EGFR positive tumors are more common in females and harbor distinct features in histomorphology. The limitations of the study are the lack of follow-up and survival data.

   Conclusion   Top

This study has defined the specific type of EGFR mutation along with the assessment of the frequency of EGFR mutations. The comparison of various diagnostic techniques used for the detection of EGFR mutations was performed. Real-time PCR is the best method for the detection of somatic EGFR mutations in advanced cases of lung cancer where surgery is contraindicated and where small trucut biopsies are submitted for testing.

Acknowledgements

Financial assistance from Intramural research project, Dr. Ram Manohar Lohia Institute of Medical Sciences, Lucknow, India-IEC 32/15.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 

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Correspondence Address:
Nuzhat Husain
Department of Pathology, Dr. Ram Manohar Lohia Institute of Medical Sciences, Vibhooti Khand, Gomti Nagar, Lucknow – 226 010, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/IJPM.IJPM_1096_20

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[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
 
[Table 1], [Table 2], [Table 3]

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