25 Jun 2026
Integrating tumor genomics and disease dynamics in oncology development
Introduction
The limitations of traditional oncology trial design are well understood. Histology-based enrollment strategies, while operationally straightforward, frequently obscure the underlying molecular heterogeneity that governs therapeutic response. As a result, many late-stage failures may not reflect an absence of drug activity, but rather, an inability to resolve biologically distinct patient subsets within a single trial population.
Over the past decade, the role of genomics in clinical development has shifted from retrospective correlation to prospective design input. Increasingly, genomic data is being incorporated at early stages to inform target selection, define inclusion criteria, and guide stratification strategies. This evolution reflects a broader recognition that treatment response is determined less by tumor origin and more by the molecular and functional state of the disease at the time of intervention.
For clinical programs intended to demonstrate mechanistic efficacy, the challenge is no longer access to genomic data but the appropriate integration of that data into a cohesive trial design framework.
Comprehensive genomic profiling and the limits of single-marker selection
Early precision oncology strategies relied heavily on single-gene or limited-panel assays to identify patients with targetable mutations. While effective in specific contexts, these approaches rely on a single genomic event to sufficiently define therapeutic sensitivity. For example, KRAS mutations, (long considered “undruggable”), are now tractable targets, and patient selection based on specific KRAS variants has become routine. Yet even in genomically defined populations, sponsors have observed variable depth and durability of response, along with the emergence of resistance through pathway reactivation, co-mutations, and adaptive signaling changes.
This variability highlights a central reality of targeted oncology development: A shared driver mutation does not equate to shared tumor biology. Mechanistic understanding increasingly depends on tumor-level biology.
To address this, clinical development programs have increasingly adopted broader genomic profiling strategies, including comprehensive genomic profiling (CGP) panels and whole exome sequencing (WES). CGP assays, such as the Labcorp Tissue Complete service powered by PGDx elio™ tissue complete, enable simultaneous interrogation of multiple classes of genomic alteration, including single nucleotide variants, insertions/deletions, copy number changes, and gene fusions. These assays also report out relevant biomarkers such as tumor mutational burden and microsatellite instability, which reflect overall mutational complexity and underlying DNA repair dysfunction and can provide critical insight to differential sensitivity in immune-oncology programs.
WES further extends this capability by enabling characterization of the entire coding genome. While less commonly deployed in registrational settings due to operational considerations, WES remains highly relevant in exploratory and translational contexts, particularly for biomarker discovery and understanding emergent resistance mechanisms.
The adoption of CGP and WES assays represents a shift from binary biomarker selection toward multivariate genomic characterization. However, both CGP and WES remain inherently static measurements. They define the genomic architecture of a tumor at a single point in time but do not directly capture how disease burden evolves under therapeutic pressure.
Extending CGP in plasma and molecular residual disease
Circulating tumor DNA (ctDNA)–based assays create the ability to extend genomic profiling into the longitudinal setting. Plasma-based approaches enable repeated sampling of tumor-derived DNA where tissue is unavailable or insufficient, offering a dynamic view of disease burden that is not accessible through tissue-based assays.
Two conceptual frameworks dominate current implementation. The first involves plasma-based CGP, such as Labcorp Plasma Complete, that mirrors tissue profiling, but in a non-invasive format, and allows for serial assessment. The second, and increasingly relevant in trial design, is the tumor-informed approach and application to molecular residual disease (MRD).
In tumor-informed workflows, baseline sequencing using broad genomic assays like CGP or whole genome sequencing (WGS) is used to define a patient-specific variant signature. These variants are then tracked in plasma with high analytical sensitivity using targeted or genome-wide methods, as with Labcorp Plasma Detect®. This dynamic monitoring enables direct assessment of molecular disease kinetics and provides the utility for MRD by ctDNA as a frontier biomarker and emerging endpoint in oncology trial design.
A persistent limitation in adjuvant and neoadjuvant trial design is the inclusion of patients who have already achieved molecular remission following surgery or induction therapy. In these patients, the probability of recurrence is low, and additional therapeutic benefit is difficult to resolve. Their inclusion effectively dilutes treatment effect, increasing sample size requirements and extending development timelines. ctDNA-based MRD assessment provides a mechanism to address this problem.
Patients who are MRD-negative following definitive therapy consistently demonstrate low recurrence risk across multiple tumor types. Conversely, MRD-positive patients represent a population with measurable residual disease and substantially elevated risk of progression. This distinction is not accessible through conventional imaging or clinical assessment alone.
From a trial design standpoint, MRD enables the enrichment of high-risk populations most likely to derive benefit, reduction in cohort size and follow-up duration through improved event rates, and clearer mechanistic readouts, particularly in early-stage disease settings. The result is not only operational efficiency, but biological clarity.
Beyond DNA: Functional interpretation through transcriptomics
While DNA-based approaches define the mutational landscape and disease burden, they do not fully resolve a tumor’s functional state. Increasingly, there is recognition that transcriptional programs, rather than genomic alterations alone, mediate therapeutic response, particularly in the context of immune modulation and adaptive resistance.
Whole transcriptome sequencing (WTS) provides a measurement of relative gene expression, enabling characterization of pathway activation, immune activation states, alternative splicing events, gene fusions, and tumor microenvironment interactions that may not be apparent from DNA data alone and may vary independently of mutational status.
As a complement to genomic profiling, WTS provides a more functionally relevant view of tumor biology, linking genomic variation to downstream molecular activity. When incorporated into clinical development strategies, transcriptomic data can support more refined patient stratification, improved understanding of treatment response, and more precise hypothesis generation for combination strategies.
Conclusion
The role of genomics in oncology clinical development has expanded from marker identification to comprehensive characterization of tumor biology and disease dynamics. CGP and WES define the mutational landscape; ctDNA extends that insight into the circulating compartment; MRD provides a clinically actionable measure of residual disease; and transcriptomics offers a functional layer for interpreting response.
These modalities are not independent. Rather, they represent interdependent components of a unified framework in which tumor state is defined across structural, temporal, and functional dimensions. Clinical trial designs that incorporate this framework are better positioned to resolve therapeutic signal, define biologically relevant populations, and generate interpretable endpoints.
The increasing complexity of genomic assays also introduces corresponding challenges in clinical trial execution. For genomics to function as a true development enabler, analytical consistency is non-negotiable, particularly in global registrational trials. Variability in pre-analytical handling, assay performance, or bioinformatics pipelines undermines data interpretability and regulatory confidence.
Labcorp helps to mitigate these risks through globally harmonized laboratory execution, spanning sites in the United States, Geneva, Singapore, Shanghai, and Tokyo. Labcorp’s offerings for WES, WGS, WTS, CGP panels, and MRD are conducted under harmonized standardized operating procedures, quality systems, and version-controlled bioinformatics pipelines to support consistent data generation across regions. Our infrastructure enables data combinability and instills confidence that differences in aggregate global trial data reflect biology, not geography.
Labcorp’s unified approach and capabilities help reduce late-stage risk, accelerate development timelines, and help ensure that therapies are evaluated and delivered to the patients with the greatest biological likelihood of benefit. This is genomic data in action, and it is redefining how successful oncology trials are built.