Technical Validation of a Next-Generation Sequencing Assay for Detecting Actionable Mutations in Patients with Gastrointestinal Cancer

A Validation Framework for Somatic Copy Number Detection in Targeted Sequencing Panels

Somatic copy number alterations (SCNAs) in tumors are clinically significant diagnostic, prognostic, and predictive biomarkers. SCNA detection from targeted next-generation sequencing panels is increasingly common in clinical practice; however, detailed descriptions of optimization and validation of SCNA pipelines for small targeted panels are limited. This study describes the validation and implementation of a tumor-only SCNA pipeline using CNVkit, augmented with custom modules and optimized for clinical implementation by testing reference materials and clinical tumor samples with different classes of copy number variation (CNV; amplification, single copy loss, and biallelic loss). Using wet-bench and in silico methods, various parameters impacting CNV calling, including assay-intrinsic variables (establishment of normal reference and sequencing coverage), sample-intrinsic variables (tumor purity and sample quality), and CNV algorithm-intrinsic variables (bin size), were optimized. The pipeline was trained and tested on an optimization cohort and validated using an independent cohort with a sensitivity and specificity of 100% and 93%, respectively. Using custom modules, intragenic CNVs with breakpoints within tumor suppressor genes were uncovered. Using the validated pipeline, re-analysis of 28 pediatric solid tumors that had been previously profiled for mutations identified SCNAs in 86% (24/28) samples, with 46% (13/28) samples harboring findings of potential clinical relevance. Our report highlights the importance of rigorous establishment of performance characteristics of SCNA pipelines and presents a detailed validation framework for optimal SCNA detection in targeted sequencing panels.

Development and Analytical Validation of a Targeted Next-Generation Sequencing Panel to Detect Actionable Mutations for Targeted Therapy

Background

The ability to rapidly, inexpensively, and accurately identify cancer patients based on actionable genomic mutations in tumour specimens is becoming critically important in routine clinical diagnostics. Targeted panel sequencing is becoming popular because it enables comprehensive and cost-effective diagnosis. However, the implementation of a next-generation sequencing (NGS) assay in clinical settings requires careful analytical validation to demonstrate its ability to detect multiple genomic variants.

Materials and Methods

Here, we developed a custom-targeted NGS panel to identify actionable variants, including single nucleotide variants, insertions, and deletions; copy number variants; and gene fusions, across 73 genes for targeted cancer therapy. We implemented a practical validation strategy with diluted samples and reference standard samples that modelled key determinants of accuracy, including mutant allele frequency, insertion/deletion length, amplitude of copy number, and hotspot gene fusions.

Results

The analytical validation results demonstrated that our panel can identify different types of genomic alterations in these test samples with high levels of accuracy, sensitivity, and reproducibility.

Conclusion

Our panel could be deployed as a routine clinical test to comprehensively detect actionable variants in cancer patients to guide targeted therapy decisions.

Quantitative and Qualitative QC of Next-Generation Sequencing for Detecting Somatic Variants: An Example of Detecting Clonal Hematopoiesis of Indeterminate Potential

BACKGROUND

Because next-generation sequencing (NGS) for detecting somatic mutations has been adopted in clinical fields, both qualitative and quantitative QC of the somatic variants through whole coding regions detected by NGS is crucial. However, specific applications or guidelines, especially for quantitative QC, are currently insufficient. Our goal was to devise a practical approach for both quantitative and qualitative QC using an example of detecting clonal hematopoiesis of indeterminate potential (CHIP).

METHODS

We applied the QC scheme using commercial reference materials and in-house QC materials (IQCM) composed of haplotype map and cancer cell lines for monitoring CHIP.

RESULTS

This approach efficiently validated a customized CHIP NGS assay. Accuracy, analytical sensitivity, analytical specificity, qualitative precision (concordance), and limit of detection achieved were 99.87%, 98.53%, 100.00%, 100.00%, and 1.00%, respectively. The quantitative precision analysis also had a higher CV percentage at a lower alternative read depth (R2 = 0.749∼0.858). Use of IQCM ensured more than 100-fold reduction in the cost per run compared with that achieved using commercial reference materials.

CONCLUSION

Our approach determined the general analytical performance of NGS for detecting CHIP and recognized limitations such as lower precision at a lower level of variant burden. This approach could also be theoretically expanded to a general NGS assay for detecting somatic variants. Considering the reliable NGS results and cost-effectiveness, we propose the use of IQCM for QC of NGS assays at clinical laboratories.

Versatile ion S5XL sequencer for targeted next generation sequencing of solid tumors in a clinical laboratory

BACKGROUND

Next generation sequencing based tumor tissue genotyping involves complex workflow and a relatively longer turnaround time. Semiconductor based next generation platforms varied from low throughput Ion PGM to high throughput Ion Proton and Ion S5XL sequencer. In this study, we compared Ion PGM and Ion Proton, with a new Ion S5XL NGS system for workflow scalability, analytical sensitivity and specificity, turnaround time and sequencing performance in a clinical laboratory.

METHODS

Eighteen solid tumor samples positive for various mutations as detected previously by Ion PGM and Ion Proton were selected for study. Libraries were prepared using DNA (range10-40ng) from micro-dissected formalin-fixed, paraffin-embedded (FFPE) specimens using the Ion Ampliseq Library Kit 2.0 for comprehensive cancer (CCP), oncomine comprehensive cancer (OCP) and cancer hotspot panel v2 (CHPv2) panel as per manufacturer's instructions. The CHPv2 were sequenced using Ion PGM whereas CCP and OCP were sequenced using Ion Proton respectively. All the three libraries were further sequenced individually (S540) or multiplexed (S530) using Ion S5XL. For S5XL, Ion chef was used to automate template preparation, enrichment of ion spheres and chip loading. Data analysis was performed using Torrent Suite 4.6 software on board S5XL and Ion Reporter. A limit of detection and reproducibility studies was performed using serially diluted DLD1 cell line.

RESULTS

A total of 241 variant calls (235 single nucleotide variants and 6 indels) expected in the studied cohort were successfully detected by S5XL with 100% and 97% concordance with Ion PGM and Proton, respectively. Sequencing run time was reduced from 4.5 to 2.5 hours with output range of 3-5 GB (S530) and 8-9.3Gb (S540). Data analysis time for the Ion S5XL is faster 1 h (S520), 2.5 h (S530) and 5 h (S540) chip, respectively as compared to the Ion PGM (3.5-5 h) and Ion Proton (8h). A limit detection of 5% allelic frequency was established along with high inter-run reproducibility.

CONCLUSION

Ion S5XL system simplified workflow in a clinical laboratory, was feasible for running smaller and larger panels on the same instrument, had a shorter turnaround time, and showed good concordance for variant calls with similar sensitivity and reproducibility as the Ion PGM and Proton.

Quality control materials for pharmacogenomic testing in the clinic

Pharmacogenomics has significantly added to our understanding of drug responses in clinical pharmacology, changing the paradigm of treatment decisions. Interrogations of both inherited and somatic variations for therapeutic purposes are increasingly being adopted in clinics, where quality control (QC) materials are required. However, for many pharmacogenomic tests, the acquisition of well-characterized QC materials is often difficult or impossible. In this review, several sources of appropriate QC materials for therapy-associated genetic testing are discussed. Among them, the novel methods for producing renewable controls that resemble patient samples are highlighted. Owing to technological complexity, more efforts are needed to develop proper controls for next-generation sequencing-based assay.

Tissue-based next generation sequencing: application in a universal healthcare system

In the context of solid tumours, the evolution of cancer therapies to more targeted and nuanced approaches has led to the impetus for personalised medicine. The targets for these therapies are largely based on the driving genetic mutations of the tumours. To track these multiple driving mutations the use of next generation sequencing (NGS) coupled with a morphomolecular approach to tumours, has the potential to deliver on the promises of personalised medicine. A review of NGS and its application in a universal healthcare (UHC) setting is undertaken as the technology has a wide appeal and utility in diagnostic, clinical trial and research paradigms. Furthermore, we suggest that these can be accommodated with a unified integromic approach. Challenges remain in bringing NGS to routine clinical use and these include validation, handling of the large amounts of information flow and production of a clinically useful report. These challenges are particularly acute in the setting of UHC where tests are not reimbursed and there are finite resources available. It is our opinion that the challenges faced in applying NGS in a UHC setting are surmountable and we outline our approach for its routine application in diagnostic, clinical trial and research paradigms.

Next-generation sequencing: advances and applications in cancer diagnosis

Technological advances have led to the introduction of next-generation sequencing (NGS) platforms in cancer investigation. NGS allows massive parallel sequencing that affords maximal tumor genomic assessment. NGS approaches are different, and concern DNA and RNA analysis. DNA sequencing includes whole-genome, whole-exome, and targeted sequencing, which focuses on a selection of genes of interest for a specific disease. RNA sequencing facilitates the detection of alternative gene-spliced transcripts, posttranscriptional modifications, gene fusion, mutations/single-nucleotide polymorphisms, small and long noncoding RNAs, and changes in gene expression. Most applications are in the cancer research field, but lately NGS technology has been revolutionizing cancer molecular diagnostics, due to the many advantages it offers compared to traditional methods. There is greater knowledge on solid cancer diagnostics, and recent interest has been shown also in the field of hematologic cancer. In this review, we report the latest data on NGS diagnostic/predictive clinical applications in solid and hematologic cancers. Moreover, since the amount of NGS data produced is very large and their interpretation is very complex, we briefly discuss two bioinformatic aspects, variant-calling accuracy and copy-number variation detection, which are gaining a lot of importance in cancer-diagnostic assessment.