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Performance comparison of NextSeq and Ion Proton platforms for molecular diagnosis of clinical oncology

Abstract

Purpose

Next-generation sequencing is a powerful approach to detect genetic mutations with which cancer diagnosis and treatment can be tailored to the individual patient in the era of personalized and precision medicine. Ion Torrent Systems Ion Proton and Illumina NextSeq are 2 major targeted sequencing platforms; however, not much work has been done to compare these platforms’ performance for mutation detection in formalin-fixed paraffin-embedded (FFPE) materials.

Methods

We benchmarked the performance by using a collection of FFPE samples from 23 patients with different cancers for NextSeq and Ion Proton platforms. We report analysis of sequencing in terms of average coverage depth, read length, and variant detection.

Results

Sequencing results by NextSeq and Ion Proton displayed near perfect coverage behavior (>99%) on target region. We analyzed the ability to call variants from each platform and found that Ion Proton sequencing can identify 89% of single nucleotide variants (SNVs) whose mutant allele frequency (MAF) is greater than or equal to 5% detected by the NextSeq pipeline in common analytical regions. The correlation coefficient of MAF for those common SNVs was 1.0046 (R2 = 0.973) between the 2 platforms. To call lower mutant frequency (5%-10%) mutations for NextSeq sequencing, coverage depth should be improved. The concordance of small insertions and deletions between these 2 pipelines was up to 100%.

Conclusions

The 2 sequencing pipelines evaluated were able to generate usable sequence and had high concordance. They are proper for mutation detection in clinical application.

Tumori 2017; 103(3): 223 - 230

Article Type: ORIGINAL RESEARCH ARTICLE

DOI:10.5301/tj.5000600

Authors

Fei Cao, Lianju Gao, Longgang Wei, Zhanni Chen, Yan Wang, Xia Ran, Xuehong Meng, Ji Tao

Article History

Disclosures

Financial support: No financial support was received for this submission.
Conflict of interest: None of the authors has conflict of interest with this submission.

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Authors

Affiliations

  • Department of Gastrointestinal Medical Oncology, The Affiliated Tumor Hospital of Harbin Medical University, Harbin - China
  • Novogene Bioinformatics Institute, Beijing - China
  • Fei Cao, Lianju Gao and Longgang Wei contributed equally to the work and should be considered co-first authors.

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