Cancer is shaped partly by changes in DNA.

Some of these changes are inherited. Others are acquired as cancer develops, grows, responds to treatment, or becomes resistant. Over the past five decades, the way we read DNA has changed dramatically, from examining one short region at a time to scanning selected cancer genes, whole exomes, whole genomes, and increasingly, longer and more complex DNA structures.

That evolution has changed cancer care.

Sequencing is now used across multiple clinical questions. It can help identify inherited cancer risk, classify tumors, guide therapy selection, monitor for recurrence, and track resistance. In some settings, it may also support early detection or screening approaches when combined with appropriate biomarkers and clinical validation. 

Each generation of sequencing has expanded what scientists and clinicians can see.

But more sequencing does not automatically mean clearer answers. The value of a sequencing technology depends on the clinical question, the sample being tested, the genomic region being examined, and whether the result can be interpreted and acted on.

Sanger Sequencing: Reading One Region Carefully

Sanger sequencing was first described in 1977 and became the foundational DNA sequencing method for decades.[1] It works by using chain-terminating nucleotides to determine the order of DNA bases in a sequence.[1]

In practical terms, Sanger sequencing reads a defined stretch of DNA, usually hundreds of bases long. Modern automated Sanger sequencing can generally generate sequences up to about 800 to 1000 base pairs under suitable conditions.[2]

Its strength is focus.

If a laboratory needs to confirm a specific variant in a known region, Sanger sequencing can be appropriate. It reads a small region carefully and gives a clear answer for that region.

Sanger sequencing also played an important role in the Human Genome Project, one of the major milestones in modern genomics. The first draft human genome sequence, published in 2001, provided a reference framework that later technologies would build on.[3]

The trade-off is scale. 

Sanger sequencing is not designed to screen many genes efficiently. If the clinical question involves dozens, hundreds, or thousands of possible regions, reading one stretch at a time becomes slow and inefficient.

That trade-off helped drive the shift to next-generation sequencing.

Next-Generation Sequencing: Reading Many Regions At Once

Next-generation sequencing, or NGS, can be seen as second-generation sequencing. The major change it brought was scale.

Instead of reading one DNA fragment at a time, NGS reads millions of DNA fragments in parallel. Many short pieces of DNA are sequenced at the same time, then computationally aligned back to a reference genome.[4]

In cancer care, this changed the kinds of questions clinicians and researchers could ask. Instead of testing one region for one variant, NGS made it possible to look across many cancer-relevant regions at once. Depending on the assay, this could support tumor profiling, diagnosis or classification, resistance tracking, blood-based monitoring, or inherited-risk assessment.

NGS gave oncology a wider molecular lens. The question then became how wide that lens needed to be.

Panels, Exomes, and Genomes: Choosing the Width of the Search

Not every clinical question needs the same amount of sequencing.

A targeted gene panel looks at a selected set of genes or genomic regions related to a specific clinical question. In diagnosed cancer, a panel may focus on genes with known therapeutic relevance. In diagnosis, it may help identify characteristic alterations that support tumor classification. In monitoring, highly focused panels may be used to track known variants over time. In inherited-risk assessment, panels may include genes associated with hereditary cancer syndromes.

The advantage of a targeted panel is focus. It directs sequencing toward regions most relevant to the clinical question. This can simplify interpretation, reduce unnecessary data, and increase sensitivity for selected variants, depending on assay design. 

The trade-off is scope: if the relevant alteration lies outside the selected regions, it may be missed.

Whole exome sequencing, or WES, widens the search to the exome: the protein-coding regions of the genome. These regions make up about 1% of the genome, but they contain many variants known to cause disease.[5] WES can be useful when a focused panel does not explain a strong clinical pattern, or when research questions require broader discovery without sequencing the entire genome.

Whole genome sequencing, or WGS, goes wider still. It sequences most of the genome, including coding and non-coding regions.[5] In principle, WGS can detect a wider range of variation than exome sequencing, including variants outside protein-coding regions and some structural changes.

The differences across sequencing technologies involve breadth, depth, cost, turnaround time, interpretability, and clinical actionability. WGS gives the broadest DNA-level view, but much of the genome remains difficult to classify in a healthcare setting. A targeted panel gives a narrower view, but can focus sequencing power on regions that are more likely to guide a clinical decision.

For routine cancer care, this is why targeted NGS panels remain widely used. They can be designed to zoom in on clinically relevant cancer genes, including those used for tumor profiling, treatment selection, resistance tracking, and blood-based monitoring. WES and WGS remain important, but their value depends on whether the broader search changes diagnosis, treatment, monitoring, trial eligibility, or inherited-risk assessment.

Short Reads and Long Reads: Different Levels of Resolution

Most clinical NGS today use short-read sequencing. DNA is broken into many small fragments, each fragment is sequenced, and software maps those short sequences back to a reference genome. This approach is scalable, efficient, and well suited for targeted panels, WES, and WGS.

The trade-off is genomic context. Short reads can be harder to place accurately in repetitive, highly similar, or structurally complex regions of the genome. This can make it more difficult to resolve larger insertions, deletions, inversions, repeat expansions, or complex rearrangements.

Long-read sequencing, often described as third-generation sequencing, was developed to address some of these challenges. Platforms such as Pacific Biosciences and Oxford Nanopore can read much longer stretches of DNA, allowing a single read to span larger or more complex genomic regions.[6,7]

This gives long-read sequencing a potential advantage for structural variants, phasing, and difficult-to-map regions. Phasing means determining whether two variants are on the same copy of a chromosome or on opposite copies. This can matter when assessing whether one functional copy of a gene may remain intact.[6-8]

However, long-read sequencing remains a work in progress for routine cancer care. Earlier platforms were limited by higher error rates, and while newer approaches have improved substantially, clinical adoption still depends on accuracy, cost, throughput, sample requirements, workflow integration, and whether the additional information changes patient management.[6-8]

The comparison between short-read NGS and long-read sequencing is therefore not about which is universally better. It is about the level of resolution needed for the question being asked. Short-read NGS remains the current workhorse of precision oncology because it is scalable, widely implemented, and already supports many clinical applications. Long-read sequencing may be most useful when larger genomic context is needed, but its broader role in routine cancer care is still evolving. 

What This Means for Cancer Care

The evolution of sequencing has moved oncology from single-region analysis to broad genomic interrogation. Sanger sequencing gave clinicians precision at a defined site. NGS made multi-gene testing practical. Targeted panels brought focus to routine cancer testing. WES and WGS widened the search space. Long-read sequencing added another layer of resolution for complex genomic regions.

Together, these technologies have changed what cancer teams can ask of DNA.

But sequencing only matters when the result leads somewhere. A finding may support screening, diagnostic clarification, therapy selection, recurrence monitoring, resistance tracking, risk-reducing options, or genetic counselling for relatives.

The goal is not to sequence everything, but to choose the sequencing approach that best matches the clinical decision. 

References

1. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci U S A. 1977;74(12):5463-5467. doi:10.1073/pnas.74.12.5463.

2. Al-Shuhaib MBS. Mastering DNA chromatogram analysis in Sanger sequencing for reliable clinical analysis. J Genet Eng Biotechnol. 2023;21:115. doi: 10.1186/s43141-023-00587-6.

3. International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature. 2001;409:860-921.

4. Behjati S, Tarpey PS. What is next generation sequencing? Arch Dis Child Educ Pract Ed. 2013;98(6):236-238. doi:10.1136/archdischild-2013-304340.

5. MedlinePlus Genetics. What are whole exome sequencing and whole genome sequencing? National Library of Medicine. Updated July 28, 2021. Accessed July 13, 2026.

6. Logsdon GA, Vollger MR, Eichler EE. Long-read human genome sequencing and its applications. Nat Rev Genet. 2020;21(10):597-614. doi: 10.1038/s41576-020-0236-x.

7. Ermini L, Driguez P. The application of long-read sequencing to cancer. Cancers (Basel). 2024;16(7):1275. doi:10.3390/cancers16071275. 

8. Sen S, Handler HP, Victorsen A, et al. Validation of a comprehensive long-read sequencing platform for broad clinical genetic diagnosis. Front Genet. 2025;16:1499456. doi:10.3389/fgene.2025.1499456.