Genomic variants provide a useful starting point into this discussion because they can be detected in multiple biospecimen types. The same variant may be best identified in tumor tissue or blood- or marrow-derived samples. It just depends on the answers you’re looking for.
The Genomic Landscape of Precision Oncology
Genomic variants are central to precision medicine approaches. Advances in next-generation sequencing (NGS) have enabled comprehensive profiling of patient tumors, allowing researchers to identify biomarkers that inform disease biology, support clinical trial enrollment, and guide the development of targeted therapies and companion diagnostics.
Genomic variants serve as a broad umbrella term for any alteration in the DNA sequence and encompass a wide variety of classes, ranging from single-base substitutions to chromosomal rearrangements.
- Single nucleotide variants (SNVs) and insertions/deletions (indels): The most common alterations in solid tumors, with key research interest in genes including KRAS, EGFR, BRAF, ERBB2 and PTEN. Variant allele frequency (VAF) provides a quantitative measure of how prevalent a given variant is within the tumor population, offering additional insight into tumor heterogeneity.
- Gene fusions: Structural rearrangements that create oncogenic drivers. Clinically relevant fusions (ALK, RET, ROS1, NTRK) occur at low incidence. For example, ALK fusions appear in only 3–7% of non-small cell lung cancer (NSCLC) patients, for example, making them easy to miss without sufficient structural coverage and large-scale sequencing initiatives.
- Copy number variants (CNVs): Larger-scale changes in the number of copies of the full gene. Gains or losses become pathogenic when they activate oncogenes or delete tumor suppressors. These require broader profiling approaches than those offered by small, targeted panels.
- Splice variants: Altered RNA processing events like MET exon 14 skipping that can dramatically impact therapeutic response. These variants highlight the importance of integrating RNA-based assays into genomic workflows.
- Multi-gene signatures: Aggregate patterns like tumor mutational burden (TMB) and microsatellite instability (MSI) that reflect broader genomic states rather than single-gene events, which help guide immunotherapy selection and broader precision-oncology strategies.
These variants exist across multiple sample types, which means researchers are not simply searching for a genomic variant, but for a variant within the appropriate biospecimen context. For example, FFPE tissue is typically used to characterize ALK-positive tumors in their native tissue context, while double-spun plasma (DSP) would be used to detect the same ALK fusion in circulating tumor DNA (ctDNA) for liquid biopsy applications while viable ALK-positive DTCs in culture could model the response to an ALK-fusion targeting drug. Studies assessing concordance between tissue- and blood-based testing require matched biospecimens derived from the same donor.
While personalized medicine is making strong headway in oncology, the reality is that many patients are still not tested for these genetic variants as part of standard of care. Even for advanced NSCLC, which has one of the highest levels of clinical adoption, 49.7% of patients do not receive diagnostic genetic testing1.
This creates a fundamental bottleneck: the lack of genomic data linked to available patient biospecimens. Therefore, before a study can begin, researchers must not only identify the genomic alteration of interest but also locate a biospecimen where that alteration is present, measurable, and suited for the research question at hand. In practice, this often means screening large numbers of samples to identify a smaller subset that satisfies both criteria.
A Faster Path to the Variants You Need
SpecimenSeq™ addresses this challenge by providing access to biospecimens from Discovery’s biobank that have been genomically characterized upfront, eliminating the need for extensive de novo screening to identify samples with specific variants of interest. By linking molecular profiles to available biospecimens upfront, researchers can identify and receive relevant biospecimens within days, significantly reducing turnaround time and cost.
Targeted NGS profiling captures clinically relevant SNVs, indels, gene fusions, and copy number variants (CNVs), as well as larger patterns such as TMB and MSI across tumor types and biospecimen sources (Figure 2).
