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March 29, 2022 | Genomics

Hitting the right targets: Maximizing the potential of targeted NGS in cancer research

The varied landscape of cancer biology

Characterizing the diversity in the genetic abnormalities found within cancers can be daunting. Identifying the genetic changes that initiate cancer development and discovering rare genetic alterations require optimized tools that provide a high level of sensitivity and precision. Next-generation sequencing (NGS) plays a pivotal role in unraveling the complexity of cancer, allowing high-resolution detection of the multiple genetic variations implicated in cancer – from somatic mutations, single nucleotide polymorphisms, copy number variations and small insertions/deletions to gene fusions.

It’s all in the small details

Have I missed a variant? Am I looking at a true variant or just an artifact? Is it a PCR error or a low-frequency mutation? Cancer researchers often grapple with these perplexing questions. Only a handful of DNA variants are likely to be relevant for a specific disease or a targeted treatment. Identifying these variants can be complicated, depending on the DNA sample, the specific gene or region and the methodology used to detect them.

While whole genome sequencing and whole exome sequencing provide the ability to profile a large portion of a DNA sample, they aren’t always suitable due to costs and time constraints, among other factors. If you’re looking for novel or known variants associated with cancer, targeted next-generation sequencing is a super-efficient alternative. By focusing on specific genomic regions of interest vs. the entire genome, you can increase sequencing depth and sample throughput while minimizing costs. However, coverage and bias are critical challenges to look out for. Coverage gaps can mean that you can easily miss a key variant, while PCR bias means that certain regions can be overrepresented. The choice of NGS panel can make all the difference when it comes to detecting low-frequency variants.

From coverage gaps to errors and bias: Avoiding the pitfalls of targeted next-generation sequencing

Traditional targeted next-generation sequencing using the two-primer amplicon approach can be riddled with challenges. PCR and sequencing errors can limit the sensitivity and accuracy of calling rare mutations, and inefficient enrichment of GC-rich regions can limit coverage of clinically-relevant genes. Some regions may be over-sequenced while others are under-sequenced, affecting uniformity and making it difficult to call variants in low-depth regions. These problems can be linked back to ineffective PCR amplification approaches. The PCR amplification process for the two-primer approach can result in primer dropouts, in which the forward and reverse primer interact, bind and the target is not enriched, causing coverage gaps.

A solution to this problem is a single primer extension approach or SPE. This eliminates the need for two region-specific primers. Instead, only one region-specific primer is needed, along with a universal primer. This results in higher uniformity, a complex library and improved coverage.

How can you be sure you’ve stumbled upon a true variant? All DNA fragments look exactly the same, making it almost impossible to distinguish between sequencing errors and unique DNA molecules. This limits your ability to detect low-frequency DNA variants confidently. A solution is to use Unique Molecular Indices (UMIs). These ‘molecular barcodes’ tag the original DNA molecules and eliminate false reads due to PCR, polymerase and machine-read errors.

Collectively, SPE and UMI technologies can improve the sensitivity of targeted DNA sequencing, making it a whole lot easier to detect rare variants.

Detecting actionable mutations from liquid biopsy samples using targeted next-generation sequencing

Liquid biopsy approaches, such as circulating tumor DNA (ctDNA) from plasma samples can provide valuable insights into relevant mutations. Liquid biopsy is also a more attractive and less invasive alternative to tissue biopsies. A recent study conducted by Kastrisiou et al. was aimed at developing a fast and cost-effective NGS panel for the management of metastatic colorectal cancer (mCRC) (1). Using a custom QIAseq Targeted DNA Panel, the researchers successfully detected hotspots in six clinically-relevant genes (KRAS, NRAS, MET, BRAF, ERBB2 and EGFR) implicated in mCRC from tumor tissue. The NGS panel was also able to detect novel variants, providing valuable information on the evolution of mCRC and the course of the disease as well as treatment response. The study underscored the importance of robust panel design to ensure high detection sensitivity and comprehensive coverage.

Developing biomarkers for evaluating the efficacy of treatments

Lymphoid malignancies display varied biological and clinical behavior, which guides treatment decisions. This study by Atli et al. highlighted the utility of targeted next-generation sequencing panels in characterizing highly selected instances of lymphoid malignancies and lymphoproliferative disorders where histopathology and more conventional molecular analyses remained inconclusive (2). Using the QIAseq Targeted DNA Panel, the researchers evaluated the molecular alterations in lymphoid malignancies, identifying actionable mutations for use as biomarkers.

In another example, Zhang et al. used a targeted next-generation sequencing approach to identify the most frequently mutated genes in ctDNA associated with lung cancer (3). Using the QIAseq Human Lung Cancer Panel to construct UMI-tagged libraries, the researchers performed targeted deep sequencing of 72 genes (15 000x). dVAF was used to evaluate the change level and trend of variant allele frequency (VAF). The team identified MUC16, KMT2D, AMER1 and NTRK1 as the most frequently mutated genes in ctDNA associated with lung cancer. The study also demonstrated that the change trend of dVAF in patients with lung cancer undergoing chemotherapy was closely related to the changes in both tumor volume and tumor biomarkers, including CEA, CA125, NSE and CK (Cytokeratin).

Hitting the right targets with the right panel

Whether your goal is to profile DNA variants in solid tumors or hematologic malignancies, examine variants in mitochondrial DNA or detect hotspots in solid tumors, the choice of panel dictates the level of success you achieve. Highly specific enrichment is key. Our platform-agnostic, expertly curated QIAseq Targeted DNA Panels incorporate SPE and UMI technologies, allowing you to access the most difficult regions of the genome. This means greater coverage uniformity and higher confidence in calling low-frequency DNA variants. From GC-rich genomic regions and exonic regions of genes to hotspots, SNPs or intronic and promoter regions, our custom designs let you effectively target your region of choice.

Advances in targeted sequencing to accelerate high-fidelity variant detection

If you’re facing issues with coverage or being slowed down by a complex, resource-intensive workflow for NGS-based biomarker research, we can help. We’ve further enhanced our QIAseq chemistry and optimized the workflow to improve NGS target enrichment and library prep, so you can combat the challenges you face. With just two hours of hands-on time and less than 40 pipetting steps, our new QIAseq Targeted DNA Pro Panels provide an ultra-efficient workflow for high-confidence variant detection. Enhanced chemistry incorporates Unique Molecular Indices and Single Primer Extension to minimize bias and ensure superior coverage, while Unique Dual Indices reduce index hopping. Compatible with diverse sample types, including cells, tissue and biofluids, the panels target the entire coding region of relevant oncogenes and tumor suppressor genes, as well as actionable and interpretable cancer-related somatic and germline variants. Flexible custom panel design options mean that you can easily target regions of interest or even boost the content of existing catalog panels.

QIAseq Targeted DNA Panels and QIAseq Targeted DNA Pro Panels are intended for molecular biology applications. These products are not intended for the diagnosis, prevention, or treatment of a disease.

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