Dataset Information

Comparison of direct sequencing and amplification refractory mutation system for detecting epidermal growth factor receptor mutation in non-small-cell lung cancer patients: a systematic review and meta-analysis.

ABSTRACT:

Background

Direct sequencing and amplification refractory mutation system (ARMS) are commonly used to detect epidermal growth factor receptor (EGFR) mutation status in patients with non-small-cell lung cancer to inform the decision-making on tyrosine kinase inhibitors treatment. This study aimed to systematically compare the two methods in terms of the rate of detected mutations and the association of detected mutations with clinical outcomes.

Material and methods

PubMed, EMBASE, China National Knowledge Infrastructure (in Chinese) and Wanfang database (in Chinese) were searched to identify relevant studies. Meta-analyses of EGFR mutation rates, rate differences, and the associations of EGFR mutations with clinical outcomes of tyrosine kinase inhibitors treatment were conducted.

Results

Eight hundred and sixty-six records were retrieved and 26 studies with 3282 patients were included. The pooled rate of mutations detected by ARMS (41%, 95% confidence interval (CI) 35% to 47%) was significantly higher than that by direct sequencing (28%, 95%CI 22% to 34%), with a weighted rate difference of 11% (95%CI 8% to 13%). There was a consistent trend that the associations between ARMS-detected mutations and clinical outcomes were stronger than those between direct-sequencing-detected mutations and clinical outcomes (pooled risk ratio for objective response: 5.18 vs. 2.25; hazard ratio for progression-free survival: 0.30 vs. 0.42; hazard ratio for overall survival: 0.46 vs. 0.54).

Conclusions

More patients with EGFR mutations can be identified by ARMS than by direct sequencing, and those identified by ARMS seems to be able to benefit more from tyrosine kinase inhibitors than those identified by direct sequencing.

SUBMITTER: Feng Q

PROVIDER: S-EPMC5601754 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Publications

Comparison of direct sequencing and amplification refractory mutation system for detecting epidermal growth factor receptor mutation in non-small-cell lung cancer patients: a systematic review and meta-analysis.

Feng Qi Q Yang Zu-Yao ZY Zhang Jia-Tong JT Tang Jin-Ling JL

Oncotarget 20170708 35

<h4>Background</h4>Direct sequencing and amplification refractory mutation system (ARMS) are commonly used to detect epidermal growth factor receptor (<i>EGFR</i>) mutation status in patients with non-small-cell lung cancer to inform the decision-making on tyrosine kinase inhibitors treatment. This study aimed to systematically compare the two methods in terms of the rate of detected mutations and the association of detected mutations with clinical outcomes.<h4>Material and methods</h4>PubMed, E ...[more]

PMID: 28938658

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Project description:BackgroundDriven by high throughput next generation sequencing technologies and the pressing need to decipher cancer genomes, computational approaches for detecting somatic single nucleotide variants (sSNVs) have undergone dramatic improvements during the past 2 years. The recently developed tools typically compare a tumor sample directly with a matched normal sample at each variant locus in order to increase the accuracy of sSNV calling. These programs also address the detection of sSNVs at low allele frequencies, allowing for the study of tumor heterogeneity, cancer subclones, and mutation evolution in cancer development.MethodsWe used whole genome sequencing (Illumina Genome Analyzer IIx platform) of a melanoma sample and matched blood, whole exome sequencing (Illumina HiSeq 2000 platform) of 18 lung tumor-normal pairs and seven lung cancer cell lines to evaluate six tools for sSNV detection: EBCall, JointSNVMix, MuTect, SomaticSniper, Strelka, and VarScan 2, with a focus on MuTect and VarScan 2, two widely used publicly available software tools. Default/suggested parameters were used to run these tools. The missense sSNVs detected in these samples were validated through PCR and direct sequencing of genomic DNA from the samples. We also simulated 10 tumor-normal pairs to explore the ability of these programs to detect low allelic-frequency sSNVs.ResultsOut of the 237 sSNVs successfully validated in our cancer samples, VarScan 2 and MuTect detected the most of any tools (that is, 204 and 192, respectively). MuTect identified 11 more low-coverage validated sSNVs than VarScan 2, but missed 11 more sSNVs with alternate alleles in normal samples than VarScan 2. When examining the false calls of each tool using 169 invalidated sSNVs, we observed >63% false calls detected in the lung cancer cell lines had alternate alleles in normal samples. Additionally, from our simulation data, VarScan 2 identified more sSNVs than other tools, while MuTect characterized most low allelic-fraction sSNVs.ConclusionsOur study explored the typical false-positive and false-negative detections that arise from the use of sSNV-calling tools. Our results suggest that despite recent progress, these tools have significant room for improvement, especially in the discrimination of low coverage/allelic-frequency sSNVs and sSNVs with alternate alleles in normal samples.

Dataset Information

Comparison of direct sequencing and amplification refractory mutation system for detecting epidermal growth factor receptor mutation in non-small-cell lung cancer patients: a systematic review and meta-analysis.

Background

Material and methods

Results

Conclusions

Publications

Comparison of direct sequencing and amplification refractory mutation system for detecting epidermal growth factor receptor mutation in non-small-cell lung cancer patients: a systematic review and meta-analysis.

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