Conclusiones

Many studies investigated alternative sample types that can be used to obtain tumour DNA for EGFR mutation detection. This is a logical approach to improving mutation detection as there are many detection assays available that can achieve high accuracy, and finding a new sample type without having to develop a new assay could prove to be a very cost-efficient and labour-efficient means of improving EGFR mutant detection.

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The best established sample type for EGFR mutation analysis is FFPE tumour material collected by biopsy. As a result, many studies focused on FFPE samples, or used FFPE as a comparator specimen to compare other sample types to. A total of seven studies (Allegrini et al., 2012; Betz et al., 2011; Hu et al., 2012; Liu et al., 2013a; Malapelle et al., 2012; Schmid- Bindert et al., 2013; Smouse et al., 2009; Sriram et al., 2011) included FFPE tumour samples in their investigations. Four studies focused on other sample types resulting in cytological preparations, including Fine-Needle Aspirates (FNA), Bronchoalveolar Lavage (BAL) and Malignant Pleural Effusion (MPE) (Billah et al., 2011; Buttitta et al., 2013; Kimura et al., 2006; Liu et al., 2013a). Studies focusing primarily on FFPE samples will be examined first.

Allegrini et al. (Allegrini et al., 2012) used Qiagen Therascreen to test a range of cytological samples including fine needle aspirates (FNA), pleural effusion (PE) or ascitic fluid, and samples from bronchial washing and brushing. This range of samples provided an interesting comparison as the samples are fixed by a number of different methods (ethanol 73.1%, Duboscq-Brasil 16.7%, formalin 9.3%). They analysed the sample types for the entire Qiagen Therascreen panel of EGFR mutations. 85.2% of samples were successfully amplified, detecting EGFR mutations in 23.9%. Amongst the samples detected positive for EGFR mutations, 41% contained less than 200 cancer cells and 18.2% contained less than 50% neoplastic cells. They concluded that cytological samples were a suitable source of genetic material for EGFR mutation analysis.

Betz et al. (Betz et al., 2011) compared cytological smears against FFPE tumour samples using direct sequencing and PCR-based fragment analysis to analyse the mutation status. Their assays examine KRAS codons 12, 13 and 61, and EGFR exon 19 deletions and L858R. Interestingly their data showed that cytological smears actually improved mutation

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detection over FFPE samples. In dilution experiments EGFR mutations were detectable at 10% (proportion of tumour to wild-type), and KRAS mutations were detectable at 5%.

Hu et al. (Hu et al., 2012) used both multiple sample types and detection methods. They examined three sample types: FFPE tumour samples, frozen tumour samples and serum; and used High Resolution Melting analysis and direct sequencing (as a comparator) for mutation detection. Using these two techniques they analysed EGFR exons 18-21. FFPE tumour samples proved to be the best sample type for mutation detection, as this sample type gave the most positive results (55.67%), followed by frozen tumour samples (51.06%) and serum (46.81%). Compared to direct sequencing, the sensitivity and specificity of the HRM assay was 91.97% and 100% respectively.

The study by Smouse et al. (Smouse et al., 2009) aimed to compare the use of FFPE surgical tumour samples against cytology cell blocks for mutation detection. They used only direct sequencing as their analysis method, examining EGFR exons 18-21. The study found that 90.9% of the 263 sample analysed were suitable for sequencing. EGFR mutations were detected in 28% of FFPE samples and 58% of cytology samples; however cytology samples made up only 5% of the total samples examined in the study. The group concluded that cytological samples were a suitable substitute for tumour samples, giving comparable sensitivity.

Schmid-Bindert et al. (Schmid-Bindert et al., 2013) performed a slightly different study to the articles reviewed so far, as they focused on RNA yield for a number of applications, but also included EGFR mutational analysis and thus the study was included in this review. They used the TaqMan MGB Real Time PCR assay to detect EGFR mutations (exons 19- 21) in three sample types including: endobronchial biopsy, endobronchial ultrasound-guided

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transbronchial needle aspirate (EBUS TBNA) and Computed Tomography-guided core biopsy. All three of these sample types were additionally split into two: one aliquot was FFPE preserved, whilst the other was stored in RNAlater until extraction. EGFR mutations were detected in 24.8% of samples tested, with EBUS TBNA giving the highest proportion of positive samples (31.3%). All samples came from patients with confirmed NSCLC, however the EGFR status had not been previously investigated, so interpretation of these EGFR results are unclear.

Malapelle et al. (Malapelle et al., 2012) performed another slightly different study. Their investigation examined the use Liquid Based Cytology (LBC) samples like some other studies, but they also analysed effect of a specialist sample processing technique: Laser Capture Microdissection (LCM) of Papanicolaou-stained cells. Direct sequencing was used to analyse the mutation status of EGFR (exon 19 deletions) and KRAS (codon 12), and the results were compared in samples with and without the use of LCM during sample preparation. The results showed that the use of LCM increased EGFR and KRAS mutation detection from 21% to 40% by concentrating the neoplastic cell DNA, suggesting insufficient sensitivity of their mutation analysis in standard cytological preparations.

Other studies focusing on sample type for optimising mutations detection used non-FFPE tumour material for their investigations. Billah et al. (Billah et al., 2011) used direct sequencing as their analysis method and analysed a range of cytological samples including: endobronchial ultrasound-guided fine-needle aspirates (EBUS FNA), computed-tomography guided fine-needle aspirates (CT FNA), body fluid, ultrasound guided superficial FNA and other cytological specimens. Using direct sequencing they analysed EGFR exons 18- 21 and KRAS codons 12, 13 and 61. Sample insufficiency was generally low (6.2% overall) ranging

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from 3.6% to 33% across the sample types. EBUS samples gave the lowest insufficiency rates. EGFR and KRAS mutations were detected in 19.4% and 23.6% of samples respectively.

Bronchoalveolar Lavage and Pleural Effusion were the focus of a study by Buttita et al. (Buttitta et al., 2013). Samples were previously characterised and grouped as mutant or wild- type. This was the only study to use Next Generation Sequencing (Roche 454) for analysis of EGFR (exons 19-21). Direct sequencing was used a comparator. This early NGS method proved to be extremely sensitive, achieving high coverage of the sequencing targets, and very high sensitivity detecting mutant DNA in a 1:10000 dilution with wild-type. In the mutant positive group of samples, NGS detected mutations in 81% of samples, against only 16% detected by Sanger sequencing. In the wild-type group, 42% of samples were identified as positive by NGS. This study showed NGS to be vastly superior to direct sequencing in terms of sensitivity.

Kimura et al. (Kimura et al., 2006) also focused on pleural effusion as the primary sample type, as this is a common complication in lung cancer. They extracted the cell free fraction of pleural effusion for analysis, using direct sequencing for mutation detection. EGFR mutants were detected in 25.6% of samples. No comparator method was used, as the main focus of the paper was examining the response to gefitinib in EGFR mutant positive patients. However, the principle of EGFR mutant detection from cell free pleural effusion was demonstrated.

Liu et al. 2013 (Liu et al., 2013b) performed a comparison of three EGFR mutant detection methodologies: the ADx ARMS kit, Sanger sequencing and mutant-specific Immunohistochemistry; using four different sample types: tumour tissue, malignant pleural effusion (MPE) cell block, MPE supernatant and plasma. The three techniques analysed EGFR

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exon19 deletions and L858R mutants. Compared to direct sequencing ARMS had a sensitivity and specificity of 81.8% and 100% respectively. Comparing plasma against tissue, ARMS had a sensitivity and specificity of 67.5% and 100%. This investigation showed that tumour tissue was the best source of tumour DNA for mutational analysis, but that that other sample types were also suitable for performing EGFR mutations detection.