Next-Generation Sequencing (NGS) Basics for Cancer Research

Next-generation sequencing (NGS) has significantly expanded our understanding of cancer biology and revolutionized the study and treatment of cancer.  Genomics research has revealed remarkable genetic heterogeneity even among cancers that were previously thought to be identical.  The discovery of these unique molecular ‘signatures’ has added a new level of complexity to developing potential cancer treatments and is driving the growth of precision medicine.  These findings may lead to a future reclassification of tumor types based on molecular profiles and aid in selecting treatments based on genomic biomarkers using pan-cancer assays (1).  They have led to the creation of The Cancer Genome Atlas (TCGA) (2), a database of molecular changes in multiple diverse cancer types, and the Pan Cancer Atlas, a reference library of key publications on cancer cell-of-origin patterns, oncogenic processes, and cancer signaling pathways (3).  

A major advantage of NGS over traditional single-gene molecular testing is the ability to assay multiple genomic variants at the same time from limited amounts of clinical samples.   From a single sample, NGS analysis can reveal a rich molecular profile of DNA and RNA genetic alterations: single nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs), gene fusions, and transcriptome changes driving tumor growth. Applications for NGS in cancer research range from basic discovery and translational research, to clinical trials and patient testing, including prognostic and diagnostic studies, biomarker testing, tumor classification, therapy selection, and tracking resistance to drug treatment.  

The following sections review sample considerations for NGS in cancer research and which methods are compatible with different sample types. For an introduction to how NGS works and to learn the basics of DNA and RNA sequencing methods please see the article Next-Generation Sequencing (NGS) Basics.

With NGS, it is possible to assay many genomic variants in a single sample, which reduces the need for using multiple tests or additional biopsies.  NGS libraries can be made from a variety of samples: fresh-frozen tissue biopsy, blood, formalin-fixed paraffin-embedded (FFPE) tissue, fine-needle aspirate (FNA) and core-needle biopsies (CNBs), liquid biopsy, and even single cells.   However, not all NGS methods are appropriate for all sample types because some require significantly higher tissue amounts and may not be compatible with compromised nucleic acid isolated from clinical samples.  Table 1 below summarizes the compatibility of typical NGS methods with clinical sample types. 

The amount and quality of the sample, how it was processed and stored, as well as the percent tumor content, all directly impact the quality of the NGS library that can be made from it and the accuracy and precision of the resulting sequencing data. As a general guideline, high-molecular weight genomic DNA and RNA purified from blood or fresh-frozen biopsy samples is the best quality and is compatible with most methods. However, DNA and RNA from samples such as FFPE tissue, FNAs, and liquid biopsies are typically short and may be damaged or degraded. These samples are best analyzed using targeted sequencing approaches, which have lower sample input requirements and are more tolerant of compromised nucleic acid material. 

Table 1. Sample compatibility with various NGS methods.

Each sample type has unique features that affect its suitability for NGS analysis. Here we review attributes of common sample types that can impact the accuracy and precision of NGS results.

The process of preparing a sample for NGS analysis involves DNA and/or RNA extraction, purification, and quantitation.  Key sample metrics include percent tumor content, nucleic acid concentration, the total amount (yield), and nucleic acid purity. Additional quality control (QC) assessment, such as DNA fragment length, may also be required to ensure samples meet sequencing laboratory acceptance criteria.  

Nucleic acid concentration and total amount should be determined using fluorescence-based methods. Determining concentration by ultra-violet (UV) absorbance is not recommended because these methods may overestimate concentration due to contaminants that absorb at the same wavelength. The integrity and fragmentation level of DNA can be estimated using agarose gel electrophoresis.  Finally, sample type-specific nucleic acid extraction kits should be used, and the nucleic acids stored in recommended buffers and at correct temperatures (-20[Symbol]C for DNA and -80[Symbol]C for RNA).

FFPE is the most common sample type used for NGS analysis.  Tissue is sectioned into thin slices and dipped into formaldehyde to preserve the internal molecular structures. This fixation process negatively impacts the quality and amount of usable nucleic acid available for NGS library preparation.  Formaldehyde chemically cross-links proteins and nucleic acids, leading to strand breaks and undesirable modifications such as deamination (cytosine to thymine or guanine to adenine mutations). DNA extracted from FFPE is typically low molecular weight and highly fragmented, with lengths typically less than 300 bp. FFPE sample quality varies widely based on processing method, percent tumor fraction, and sample age. Compared to nucleic acids isolated from fresh/frozen tissues or blood, FFPE samples tends to produce lower and more variable NGS library yields and may result in lower data accuracy, sensitivity and specificity without the right method applied for sequencing. Targeted amplicon sequencing is the most reliable method for producing high-quality NGS data from FFPE samples because the size of the amplicons is compatible with the short fragments of DNA and RNA.

Important considerations for FFPE samples include using a sufficient number of slides or sections to meet NGS library input requirements, evaluating percent tumor content, and accurate determination of nucleic acid concentration and quality.  Percent tumor content is an important metric because the presence of too many non-tumor cells in a sample can lead to false-negative results. Typical minimum tumor content for NGS analysis is 10–20%.  To enrich for the tumor fraction, samples can be macrodissected, or the pathologist can circle the area of the slide enriched for cancer cells to indicate which part to extract. Areas of necrosis should be avoided as well. If possible, sample fixation conditions such as time and temperature should be optimized to reduce nucleic acid damage, although this may not be an option for labs with established protocols or when analyzing archived samples. 

Small biopsy samples are best analyzed using targeted sequencing methods, which have the lowest sample input requirements and are more tolerant of degraded samples.  The quality of NGS results will depend on the cytopreparation method used. To obtain high quality nucleic acids, samples should fresh or frozen, because formalin-fixed samples will generate less usable material and more sample may be needed for extraction. Percent tumor content should also be evaluated if possible, to ensure the sample has sufficient cancer cells for analysis. Typical minimum tumor content requirements for NGS analysis is 10–20%.

A liquid biopsy sample consists of cell-free DNA (cfDNA) or cancer cells isolated from blood or other fluids. Only a small fraction of the total cfDNA may be from the tumor (circulating tumor DNA, ctDNA), so a specialized NGS method, called ultra-deep targeted sequencing, must be used to obtain sufficient coverage of the tumor DNA. cfDNA consists of very short fragments and can degrade rapidly. Thus, critical sample considerations for liquid biopsies include selecting appropriate blood collection tubes and optimizing sample processing time and conditions. Both serum and plasma may be used for cfDNA extraction. 

Liquid biopsy testing using NGS is a promising method for early cancer detection and screening, monitoring cancer progression, or evaluating treatment effectiveness. Learn more about using NGS for testing cfDNA.

[Top of page]

Selecting an appropriate NGS method for a research project can be overwhelming due to the rapidly growing variety of methods and the large amounts of complex information generated in NGS experiments.  To narrow the choice of NGS technique, start by considering 1) what research question you want to answer, 2) what kind of genomic information you would like to obtain from your experiments, and 3) what type of samples are available for testing. 

TThis section describes the common NGS methods used in oncology research: whole genome sequencing, exome sequencing, targeted sequencing panels, and RNA sequencing. For a background on these methods please see the Next-Generation Sequencing (NGS) Basics articles.

WGS is typically used in projects focused on discovery, particularly in basic and translational research. This technique enables the most comprehensive studies of entire genomes, which are valuable when seeking to discover novel genomic alterations associated with a particular cancer or to characterize a novel tumor type.  However, performing WGS is a lengthy process that requires high sample input and is generally not practical for testing limited amounts of samples such as FFPE tissue or fine-needle aspirates.  Additionally, this method generates highly complex information that may be difficult to interpret or not relevant. The majority of oncology researchers use more focused targeted sequencing assays to analyze a limited number of specific genes, structural features, or RNA targets implicated in cancer pathways.

The exome consists of all of the exons, which are the coding portions of our genes that get translated and expressed as proteins. Exome sequencing allows researchers to focus on the portion of the genome that is more likely to contain clinically actionable variants, such as mutations in tumor-suppressor genes. Compared to whole genome sequencing, exome sequencing generates data at higher coverage depth, which provides more confidence in detecting low allele frequency somatic variants typically found in tumor tissue samples. However, exome sequencing still produces large amounts of data that may not be relevant, and it is generally not recommended for use with FFPE samples due to high sample input and stringent quality requirements. 

Targeted sequencing panels are the most widely used NGS method in oncology research. Scientists can simultaneously analyze multiple pre-selected sets of genes, research-relevant variants, or biomarkers from a single sample.  Targets can include oncogenes and tumor suppressor genes, mutation hotspots, copy number variants, and RNA fusions, splice variants, and gene expression changes.  Ready-to-use NGS panels are available for applications such as deep sequencing of single oncogenes (BRCA or TP53) and biomarker analysis, as well as for emerging applications, such as monitoring tumor mutation burden, microsatellite instability, liquid biopsy assays, and immuno-oncology.

Targeted NGS panels are highly compatible with samples, such as FFPE or fine needle aspirates, with a capability of producing high-quality, reproducible data from as little as 1 ng of material. Due to their small focused content, they generate more clinically relevant data with a lower likelihood of unexpected results, such as variants of unknown significance.  Additionally, they enable faster time to result and at a lower cost compared to whole genome or exome methods. See the article Targeted Sequencing Approaches for NGS to learn how either hybridization capture or amplicon-based enrichment is used to target genomic regions of interest for sequencing.

RNA sequencing enables cancer researchers to investigate how alterations in RNA expression affect biological pathways that drive tumor growth, regulate cell fate, and impact disease progression.  It is also used to classify tumor subtypes and discover novel RNA biomarkers for disease research.

Oncology researchers and testing laboratories can select from a variety of RNA sequencing techniques, depending on research needs and sample type.  Current methods allow the flexibility to interrogate the whole transcriptome, target specific gene fusions or regulatory elements, or to study small and non-coding RNAs. Analysis of small amounts of samples, such as FFPE, is typically done with targeted RNA sequencing methods, which have low input requirements and can tolerate poor sample quality.  See the article RNA Sequencing (RNA-Seq) methods for NGS to learn more about the various workflows.

1. Hoadley KA, et al. Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer. Cell. 2018 Apr 5;173(2):291-304.e6.
2. https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga
3. https://www.cell.com/pb-assets/consortium/pancanceratlas/pancani3/index.html
4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6476432/ (a Canadian guideline on the use of next-generation sequencing in oncology)

[Top of page]