What Is Precision Oncology? Understanding What Genomic Testing Can — and Cannot — Tell Us About Cancer

Precision oncology is the discipline that tries to answer that question responsibly. It integrates molecular information about a cancer with pathology, tumour type, disease stage, clinical history, imaging and the available evidence, so that molecular findings can be interpreted in context rather than in isolation.

This article explains what precision oncology is, what genomic testing can genuinely tell us about a cancer, and — equally importantly — what it cannot. It is written for healthcare professionals, and for informed patients and family members who want to understand what genomic testing means after a diagnosis. It is not a substitute for individual clinical advice; treatment decisions always belong with the treating clinical team.

When someone asks “What else can I do?”, genomic testing may sometimes help answer a different question first: “What else can we learn about this cancer?”

Precision oncology is sometimes described as “matching mutations to targeted drugs.” That shorthand is too narrow, and it can mislead.

More accurately, precision oncology is an integrated approach to cancer care in which molecular information about a tumour is interpreted together with the established pillars of cancer diagnosis: pathology, tumour type and grade, stage, clinical history, imaging, and the patient’s treatment context. The molecular layer adds information; it does not replace the clinical and pathological foundation on which cancer care is built.

Depending on the cancer and the clinical situation, precision oncology may contribute to:

• molecular characterisation of the tumour;
• diagnostic clarification in selected settings;
• biomarker assessment;
• treatment-selection discussions;
• consideration of clinical trials;
• molecular monitoring in appropriate settings.

Not all of these apply to every patient. In some clinical situations, additional genomic testing may not provide information that changes diagnosis, management or treatment selection. Knowing when molecular testing is likely to add value — and when it is unlikely to — is itself part of precision oncology.

Cancer develops when cells acquire genomic alterations — changes in DNA — that affect how cells grow, divide, repair damage or die. Most cancer-related alterations are acquired during a person’s life (somatic); a smaller proportion are inherited (germline) and can be assessed separately when clinically indicated. Tumour genomic testing examines the molecular characteristics of the cancer itself.

Different tests look for different classes of molecular change:

• single nucleotide variants (SNVs) — changes at single positions in the DNA sequence;
• small insertions and deletions (indels) — short stretches of DNA added or lost;
• copy-number alterations (CNAs) — genes or chromosome regions present in excess or reduced numbers;
• gene fusions and rearrangements — structural changes that join or reorder DNA, sometimes creating cancer-driving fusion genes;
• genomic signatures and composite biomarkers — genome-wide patterns, such as mutational signatures or instability measures, rather than single-gene findings.

Assay design matters. A test designed to detect sequence variants will not necessarily detect copy-number changes; a panel of selected genes will not report alterations in genes it does not cover. Two equally valid tests can therefore return different results, simply because they were designed to answer different questions. Understanding what a given assay does and does not detect is part of interpreting its report.

Oncology testing may examine DNA, RNA, or both. These are not competing options; they carry different kinds of information.

DNA testing can identify sequence variants, insertions and deletions, copy-number changes, and selected rearrangements depending on assay design. It examines the tumour’s genomic blueprint — what changes are present.

RNA testing examines what the tumour’s cells are actually expressing. This can provide complementary information, particularly for:

• expressed gene fusions — demonstrating that a fusion gene is actively transcribed;
• transcript-level events;
• selected rearrangements that may be more directly demonstrated at the RNA level.

Two clarifications matter. RNA is not always required — many clinical questions are fully answered by DNA-based assays. And DNA sequencing can detect fusions; RNA is not the only route to fusion information, though for some fusion types it provides the most direct evidence.

The practical takeaway is simple: DNA and RNA can provide complementary molecular information, and the right combination depends on the cancer, the alteration classes in question, and the clinical context.

Genomic profiling exists on a spectrum, and both ends are legitimate clinical tools.

The choice is not “basic versus advanced.” A focused panel that answers the clinical question is good testing; a comprehensive profile that answers a broader question is also good testing. What matters is fit.

This is worth stating plainly, because a common misconception runs in the opposite direction:

More genes ≠ automatically better testing.

Larger panels detect more alterations — including more variants of uncertain significance and more findings with weak or no established clinical actionability. A larger report can therefore be harder to interpret, not easier, and can generate findings that create questions without answering any. Larger panels also detect more incidental or uncertain findings that must be communicated and managed carefully. The appropriate test follows the clinical question — not the other way around.

This is where genomic testing most often gets misunderstood. Sequencing does not output a treatment. It outputs a list of molecular observations. Between those observations and any clinical decision sit several layers of interpretation.

A detected alteration must be assessed for:

• biological significance — is this alteration plausibly involved in the cancer’s behaviour?
• cancer type — the same alteration can have very different significance in different tumour types;
• evidence linking the alteration to a therapy — is there clinical evidence that targeting it benefits patients, and in which cancer?
• the strength of that evidence — from guideline-supported, standard-of-care associations down to isolated case reports;
• regulatory and guideline context — is the associated treatment approved and recommended in this setting, and available locally?
• available treatment options and clinical trials — what could actually be offered, here and now?
• patient-specific factors — fitness, comorbidities, prior treatments, and patient goals.

International frameworks help make these judgments systematic and comparable. The ESMO Scale for Clinical Actionability of molecular Targets (ESCAT) organises molecular alterations by the strength of evidence linking them to clinical benefit from specific treatments. Complementary joint consensus guidelines from the AMP, ASCO and CAP classify reported somatic variants into tiers by level of clinical significance — from variants with strong clinical significance, through those with potential significance, to variants whose significance is uncertain. Real genomic reports use structures of this kind: findings grouped by evidence tier, with sources, and with clear language about what is — and is not — established.

And its most important corollary:

Detected alteration ≠ actionable alteration ≠ guaranteed treatment benefit.

An alteration detected is not automatically an actionable one. An actionable alteration does not automatically mean a targeted treatment is available for that patient. And a targeted treatment being available does not automatically mean it will work. Every link in that chain is decided by evidence and clinical context — not by the detection itself.

Genomic testing can identify alterations whose clinical significance is not yet established. A variant of uncertain significance (VUS) is a detected molecular alteration for which the available evidence is insufficient to establish its clinical significance. It should not be treated as an established pathogenic driver or actionable biomarker, and it is not a treatment target. In broad comprehensive profiles, VUS findings are common — they are a normal part of genomic testing, not usually a cause for alarm — and their classification may change as additional evidence becomes available.

The VUS concept supports the article’s wider point:

More detected information ≠ more clinically useful information.

Precision oncology is not only about mutations in individual genes. Some of the most informative biomarkers are genome-wide or pathway-level measures.

MSI — microsatellite instability. Microsatellites are short, repetitive DNA sequences. When a cell’s DNA mismatch repair system stops working properly, errors accumulate in these regions — a pattern called microsatellite instability. MSI can indicate underlying mismatch-repair deficiency and has established predictive relevance for immune-checkpoint therapy in defined clinical settings. MSI is not a general cancer marker; its meaning depends on the cancer type and clinical context.

TMB — tumour mutational burden. TMB is a measure of how many mutations a tumour carries. Higher mutational burden can be associated with the generation of more tumour neoantigens, which is one reason TMB has been investigated as a biomarker of response to immune-checkpoint therapy. Its predictive value varies by tumour type, assay and clinical context. TMB values also depend on how they are measured: the panel used, the counting method and the platform all affect the number, and TMB results are interpreted against method-specific thresholds — never in isolation.

HRD — homologous recombination deficiency. Homologous recombination is one of the cell’s main pathways for repairing certain kinds of DNA damage. Homologous recombination deficiency can arise through different biological mechanisms, including alterations affecting genes in the homologous-recombination repair pathway such as BRCA1 and BRCA2. HRD assays may evaluate relevant gene alterations, genomic-instability patterns, or combinations of these approaches depending on assay design.

Three HRD clarifications matter at this introductory level. First, HRD interpretation and its predictive relevance depend on the tumour context — an HRD score does not carry identical predictive meaning across all cancer types. Second, an HRD-positive result is information for clinical discussion; it does not automatically determine treatment. Third, the technical details of HRD scoring — the individual genomic-instability measures and the genes involved — are a subject for dedicated future education, not for this cornerstone article.

MSI, TMB and HRD share a common lesson: in modern oncology, useful biomarkers extend beyond single mutations, and every one of them is interpreted within its cancer type and evidence base — never as a universal signal.

Molecular information about a tumour can be obtained from two complementary sources.

Liquid biopsy also has real limitations. Tumours release DNA unevenly (“shedding” varies with tumour type, burden, and location), and analytical sensitivity varies between assays. The consequence is important:

A not-detected result in plasma ≠ the alteration is absent from the tumour.

Where plasma testing is non-informative and the clinical need remains, testing of tumour tissue may need to be considered, depending on the clinical situation.

Stated plainly: liquid biopsy is not a universal replacement for tissue. The two are used together, in sequence, or not at all, according to the clinical question.

A genomic test can return several kinds of outcome:

• an actionable finding — an alteration or biomarker with established, evidence-supported relevance in that cancer type;
• a finding with emerging or limited evidence;
• one or more variants of uncertain significance;
• no currently actionable finding;
• a non-informative result, depending on assay, specimen quality and context.

The last two outcomes matter most to address honestly. A result without an actionable alteration does not mean “nothing else can be done.” Standard oncology care — guided by tumour type, stage, pathology, established biomarkers, the patient’s condition, and current guidelines, assessed by the multidisciplinary team — continues regardless of the genomic result. Genomic testing adds one layer of information; it does not define the whole of cancer treatment.

This is also where a genomic report’s honest value becomes visible: a well-structured report tells the clinical team what was found, how confident the interpretation is, and what the evidence supports — which sometimes means confirming that the established path of care remains the right one.

No.

Genomic testing should be selected according to the cancer type, the stage and clinical setting, established biomarker requirements, specimen availability, the clinical question, guideline recommendations, and whether the result is reasonably likely to inform management.

Broad next-generation sequencing has established clinical roles in selected cancers and settings — for example, in certain advanced or metastatic tumours where guideline bodies recommend multigene testing. But presenting NGS as universally necessary for every patient would be neither scientifically supported nor clinically responsible. For many patients, established pathology, biomarker testing and standard care fully answer the clinical question, and genomic testing would add cost, complexity and uncertain findings without expected benefit.

The decision to test — and which test to use — is a clinical one, made by the treating team for the individual patient.

Precision oncology can extend beyond a single baseline profile. In selected settings, tumour-derived molecular information can be used to build longitudinal monitoring strategies.

After curative-intent treatment for some solid tumours, very low levels of circulating tumour DNA may, in appropriate settings, provide molecular evidence consistent with residual disease before recurrence becomes detectable by conventional clinical or radiological assessment. This is molecular residual disease (MRD) monitoring — and it is not an off-the-shelf test. It is a personalised, longitudinal workflow:

Two boundaries keep this concept honest. First, across multiple tumour types, post-treatment ctDNA detection has demonstrated prognostic significance and has been associated with increased risk of recurrence — that is clinical validity. Whether changing treatment based on an MRD result improves outcomes — clinical utility — is a separate question, and MRD-directed treatment decisions are not yet a universally established standard of care. Second, MRD monitoring complements, and does not replace, imaging, pathology and standard clinical surveillance.

Molecular monitoring, like every other application in this article, is a tool whose value depends on context — not a universal upgrade to cancer care.

The through-line of this article is that the clinical question comes first. A practical sequence for that principle:

The appropriate test follows the clinical and molecular question — never the reverse.