More and more frequently we're seeing Tempus, Caris, and others bringing together RNA transcriptomes with large-panel or genomic tumor DNA sequencing.
Here's a new review at Nature Review Clinical Oncology that brings you up-to-date. And, we'll add a section, "Takeaways for Payors."
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AI CORNER
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Below, Chat GPT 5.2 reads amd discusses what's new in Johnson et al. 2026, with in put from articles by Siddaway 2025, a news article on Siddaway, and Li 2025.
The second section, below, discusses "Takeaways for Payors."
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RNA Sequencing Enters Clinical Genomics: From Conceptual Promise to Routine Practice
Introduction: from “adjunct” to clinical substrate
For more than a decade, RNA sequencing (RNA-seq) has been discussed as a powerful complement to DNA-based cancer genomics. Yet until recently, its role remained largely ancillary—most commonly for fusion detection, research applications, or select tumor types. The four papers considered here collectively argue that this phase has ended. Together, Johnson et al., 2026 and the three 2025 studies demonstrate that RNA-seq is no longer experimental or aspirational; rather, it is becoming a practical, scalable, and clinically consequential layer of molecular diagnostics for real-world cancer patients.
What distinguishes this literature from earlier RNA-seq enthusiasm is not technical novelty, but operational maturity: robust performance in FFPE tissue, acceptable failure rates, clinically interpretable outputs, and demonstrated effects on diagnosis and therapy selection.
Johnson et al., 2026: Defining the “Actionable Transcriptome”
Johnson et al. provide the most synthetic and forward-looking contribution of the four studies. Rather than focusing on assay performance alone, they articulate a conceptual framework—the “actionable transcriptome”—that reframes RNA-seq as a unifying diagnostic modality rather than a niche add-on
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Their central argument is that RNA-seq captures classes of actionability that DNA, immunohistochemistry (IHC), and low-plex assays assess only partially or serially. These include:
expressed gene fusions (including unknown partners),
RNA-level confirmation of DNA variants,
oncogene overexpression and tumor-suppressor underexpression independent of copy number,
multigene prognostic and predictive signatures,
immune-related expression states, and
expressed neoantigens and splice variants.
Importantly, Johnson et al. are not proposing RNA-seq as a wholesale replacement for DNA testing. Instead, they position RNA-seq as the first truly multiplexed assay that spans mutation, expression, structure, and functional consequence within a single analyte. This framing explains why RNA-seq is now attractive not only scientifically, but economically and operationally for clinical laboratories.
Siddaway et al., 2025: Real-World Clinical Proof at Scale
If Johnson et al. define the theory, Siddaway et al. provide the proof. In their Nature Medicine study of over 2,300 consecutively tested patients, targeted RNA-seq demonstrated clinical utility in 87% of cases, with actionable or diagnostically relevant findings in nearly two-thirds of tumors
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Several features of this study are pivotal for clinical adoption:
Specimen realism: ~75% of samples were FFPE, addressing a long-standing concern about RNA stability.
Operational reliability: a failure rate below 5%, comparable to many DNA assays.
Breadth of detection: RNA-seq detected SNVs, indels, fusions, splice alterations, and diagnostically informative negatives.
Clinical consequence: results led to revised diagnoses and altered treatment decisions, including initiation of targeted therapy.
The accompanying Nature Medicine editorial by Siddaway and Hawkins reinforces the central message: RNA-seq can function as a front-line diagnostic assay, reducing tissue consumption, cost, and turnaround time while expanding interpretive depth
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Li et al., 2025: Bridging DNA to Protein Through Expressed Mutation Detection
Where Siddaway et al. emphasize clinical workflow, Li et al. focus on molecular signal fidelity. Their npj Precision Oncology study evaluates targeted RNA-seq specifically as a tool for detecting expressed somatic mutations, using reference standards and controlled false-positive benchmarking
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Their findings sharpen an increasingly important clinical distinction:
DNA sequencing identifies potential variants.
RNA sequencing identifies expressed and therefore biologically plausible variants.
Li et al. demonstrate that a substantial fraction of DNA-detected mutations are not transcribed at meaningful levels, while RNA-seq can uncover expressed variants missed by DNA assays due to coverage, tumor purity, or technical limitations. This supports a pragmatic reframing: RNA-seq does not merely add sensitivity; it filters relevance.
Converging Themes Across the Four Studies
Across these papers, several shared conclusions emerge:
1. RNA-seq is clinically viable, not aspirational
All four studies reject the notion that RNA-seq is too fragile, noisy, or slow for routine diagnostics. FFPE compatibility, low failure rates, and standardized pipelines are now established realities.
2. Expression matters as much as mutation
RNA-seq resolves a core limitation of DNA-only profiling: the inability to determine whether a variant is biologically active. Expression-aware interpretation strengthens confidence in therapeutic relevance and deprioritizes silent alterations.
3. Multiplexing drives value
RNA-seq consolidates what would otherwise require multiple assays—fusion testing, expression profiling, splice analysis, and confirmatory variant assessment—into a single workflow.
4. Clinical negatives are informative
Both Johnson et al. and Siddaway et al. emphasize that RNA-seq can generate pertinent negatives—ruling out specific entities or therapeutic targets with confidence, which is itself clinically actionable.
What to Expect Next (2026–2027)
Based on these studies, several near-term developments are likely:
RNA-first testing strategies
Clinical laboratories will increasingly deploy RNA-seq as an initial assay, with reflex DNA testing reserved for copy-number changes, mutational burden, or germline assessment.Expansion beyond oncology panels
RNA-based diagnostics will broaden from oncology into immune profiling, resistance monitoring, and therapy-response prediction, particularly for ADCs, bispecifics, and cell therapies.Regulatory and reimbursement alignment
As RNA-seq demonstrates consistent clinical utility, payers and regulators will be forced to engage with expression-based biomarkers as legitimate medical decision tools, not exploratory analytics.Interpretive standardization
Frameworks such as the “actionable transcriptome” will drive standardized reporting vocabularies and decision-support systems, analogous to earlier DNA variant classification schemes.
Conclusion
Taken together, these four papers mark a transition point. RNA sequencing has moved from conceptual bridge to clinical substrate—a technology capable of supporting real-world cancer care at scale. Johnson et al., 2026 provide the intellectual architecture; Siddaway et al. demonstrate feasibility and impact; Li et al. clarify biological relevance; and the accompanying editorial underscores urgency. By 2026–2027, RNA-seq is poised not merely to complement DNA genomics, but to reshape the definition of actionable molecular oncology.
What are the takeaways for payors? (Version 01)
For a reimbursement and payor audience, the central takeaway from this body of work is that RNA sequencing is no longer an exploratory “add-on” technology but a consolidating diagnostic service that can replace multiple sequential or parallel tests while improving clinical decision quality. The studies collectively show that RNA-seq reduces diagnostic uncertainty by determining which genomic alterations are actually expressed and therefore biologically relevant. For payors, this directly addresses a common concern with large DNA panels: that they detect numerous variants of unclear or low clinical consequence, increasing downstream utilization without proportional patient benefit.
A second key takeaway is that RNA-seq supports earlier and more confident treatment selection, which is closely aligned with payor goals of avoiding trial-and-error therapy. Across real-world cohorts, RNA-seq identifies actionable alterations—particularly gene fusions, splice variants, and expression-defined targets—that are either missed or ambiguous with DNA-only testing. Importantly, these findings are not academic: they demonstrably change diagnoses, confirm or refute eligibility for targeted therapies, and guide enrollment into appropriate treatment pathways. From a utilization perspective, this means fewer ineffective therapies, fewer reversals, and better alignment between molecular testing and approved or guideline-supported treatments.
Third, RNA-seq creates value by generating clinically meaningful negative results, which payors often undervalue but rely on implicitly. When RNA-seq shows that a putative DNA alteration is not expressed—or that no actionable transcriptomic drivers are present—it helps rule out costly targeted therapies or immunotherapies that are unlikely to benefit the patient. This ability to produce “pertinent negatives” strengthens medical necessity arguments and supports more defensible coverage decisions, particularly in advanced cancer settings where treatment costs are high and evidence thresholds are scrutinized.
Another important reimbursement-relevant insight is that RNA-seq enables test consolidation and tissue stewardship, both of which have cost implications. By capturing fusion detection, expressed mutation confirmation, splice effects, and multigene signatures in a single assay, RNA-seq can reduce the need for multiple sequential tests such as separate DNA panels, FISH, IHC, and standalone expression assays. This consolidation lowers cumulative testing costs, shortens time to treatment, and reduces the likelihood of repeat biopsies—outcomes that align with payor objectives even when the per-test price of RNA-seq is higher than that of an individual legacy assay.
Finally, these studies signal that RNA-seq is moving toward predictable, standardizable clinical performance, which is critical for coverage policy. Low failure rates in FFPE tissue, consistent turnaround times, and reproducible clinical utility across thousands of patients address historical payor skepticism about RNA-based assays. As the concept of the “actionable transcriptome” matures, RNA-seq results can be framed not as exploratory omics data, but as structured, interpretable medical information that directly informs treatment eligibility, prognosis, and care pathways. For payors, this shifts RNA-seq from a discretionary molecular test to a decision-enabling diagnostic service with a clearer value proposition tied to outcomes, utilization control, and care efficiency.
What are the takeaways for payors? (Version 02)
That's a fairly happy way to present these papers to payers. What about payers that are more skeptical that this is a lot of expensive sequencing and few outcome and benefit studies? Assume payors are more skeptical - which they are - and taking more of a third-party viewpoint, with the "RNA companies" on the left, the payers on the right, and what is likely to be important, what is likely to happen.
That’s a fair pushback—and it’s exactly the stance many payers will take. If we step out of the “author voice” and adopt a third-party, skeptical payer perspective, the same papers read quite differently. What follows reframes the evidence without advocacy, focusing on what payers are likely to accept, question, and eventually demand.
From a skeptical payer viewpoint, these papers do not yet establish RNA sequencing as an outcomes-proven technology; rather, they establish RNA-seq as a technically mature diagnostic platform whose clinical claims are still upstream of hard evidence. The studies convincingly show feasibility, signal detection, and interpretive richness—but they stop short of demonstrating that RNA-guided decisions consistently improve survival, quality of life, or total cost of care relative to existing DNA-based pathways. For payers, that gap matters, because coverage decisions hinge less on molecular elegance than on downstream impact.
A core payer concern is that RNA-seq risks becoming “more information without clearer decisions.” While RNA-seq identifies additional alterations—expressed variants, fusions, splice events—these papers largely report diagnostic yield rather than clinical resolution. From a payer lens, the question is not “did RNA-seq find something?” but “did it replace something, avoid something, or change something in a way that measurably improved outcomes or reduced waste?” The current evidence base is heavy on plausibility and light on comparative effectiveness.
Payers are also likely to challenge the implicit assumption that expression equals actionability. While expressed alterations are biologically appealing, payers will note that regulatory approvals, NCCN categories, and compendia listings remain overwhelmingly DNA-anchored. RNA-defined targets—especially overexpression or underexpression without a corresponding genomic alteration—often lack FDA-labeled companion diagnostics and may lead to off-label therapy use. From a utilization-management standpoint, RNA-seq could therefore increase—not decrease—therapy costs unless carefully constrained by policy.
Another skeptical interpretation is that RNA-seq currently bundles multiple analytical functions that payers prefer to adjudicate separately. DNA sequencing, IHC, FISH, and expression assays each have established coverage precedents and policy guardrails. RNA-seq collapses these into a single test, which is efficient for laboratories but problematic for payers who rely on indication-specific coverage logic. The payer concern is not duplication of information, but loss of control over indication-based reimbursement.
Importantly, payers will also notice that most outcome claims in these papers are proximal, not distal. Changes in diagnosis, identification of targetable alterations, or initiation of targeted therapy are intermediate endpoints. Payers are increasingly wary of these surrogate claims, especially after prior experiences with broad NGS panels where early enthusiasm did not translate into clear population-level benefit. The absence of randomized or quasi-experimental comparisons between RNA-first and DNA-first strategies will be a recurring objection.
That said, skeptical payers are unlikely to reject RNA-seq outright. Instead, the likely near-term outcome is selective containment rather than broad adoption. RNA-seq will be tolerated—and sometimes welcomed—in niches where its value proposition is clearest and risk is lowest: fusion-heavy tumors, cancers of unknown primary, pediatric malignancies, and cases where standard DNA testing has failed. In these contexts, RNA-seq looks less like an added cost and more like a salvage or clarification tool.
What is most likely to matter going forward is how RNA companies reposition their evidence strategy. Payers will increasingly expect studies that show RNA-seq can replace existing tests, not merely augment them; that it shortens diagnostic pathways; or that it reduces ineffective therapy exposure. Budget-impact models, not just diagnostic yield, will become central. Comparative studies against “DNA-only plus standard reflex testing” pathways will carry far more weight than additional catalogs of actionable findings.
In practical terms, the equilibrium between RNA companies and payers will probably settle into a conditional acceptance model. RNA-seq will be covered under defined clinical scenarios, often after prior testing or within institutional programs, while broader first-line use will remain restricted pending stronger outcomes and economic data. Over time, if RNA-seq can demonstrate test substitution, therapy avoidance, or durable response enrichment, payers may begin to view it less as expensive sequencing and more as care pathway optimization.
In short, from a third-party payer perspective, these papers mark RNA-seq as credible but unproven. They lower the technical and operational objections but leave the economic and outcomes questions largely unanswered. What is likely to happen next is not rapid payer enthusiasm, but measured, conditional uptake, with increasing pressure on RNA-based diagnostics to prove that more molecular insight leads to fewer wasted dollars—not just better biology.
Li D. et al. Augmenting precision medicine via targeted RNA-Seq detection of expressed mutations. npj Precision Oncology. 2025.
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Siddaway R. et al. Clinical utility of targeted RNA sequencing in cancer molecular diagnostics. Nature Medicine. 2025.
Siddaway R., Hawkins C. The power of RNA sequencing in molecular oncology. Nature Medicine (Research Briefing). 2025.
Johnson F. et al. The actionable transcriptome: a framework for incorporating RNA sequencing into precision oncology. Nature Reviews Clinical Oncology. 2026.
