What's the value of going upscale to whole genome sequencing (WGS) in solid cancers? Van Putten et al. assemble date from their experience with 888 solid cancers. The work is from Hartwig Medical Foundation / Netherlands Cancer Institute.
Find the paper here and a Linked In essay here by Joseph Steward.
Chat GPT Discusses the Paper:
Whole-genome sequencing (WGS) in routine cancer care is feasible, fast, and clinically impactful, identifying actionable biomarkers in most patients and improving treatment selection, diagnosis, and survival in real-world practice.
This Nature Medicine study evaluates real-world use of tumor whole-genome sequencing (WGS) in 888 patients with solid cancers at a major cancer center, showing it can function as a practical, high-impact clinical tool rather than a research-only technology .
WGS proved operationally feasible, succeeding in 89% of cases with a median turnaround of 6 working days—comparable to panel-based testing. It identified actionable biomarkers in 73% of patients, including markers linked to both reimbursed therapies (27%) and experimental options (63%) .
Importantly, simulation analyses showed that even large NGS panels would miss clinically relevant findings in ~10% of patients, highlighting WGS’s broader detection capability.
Clinically, WGS influenced care in 41% of patients overall, either by guiding treatment, refining diagnosis, or identifying germline variants. In cancers of unknown primary (CUP), its impact was particularly strong—67% received meaningful diagnostic or therapeutic insights, often ending prolonged diagnostic uncertainty.
Treatment outcomes suggest real benefit: patients receiving biomarker-informed therapy had ~31% longer median survival (+96 days). This benefit was most pronounced when WGS was used earlier in the treatment pathway, before multiple prior therapies.
WGS also added diagnostic value beyond treatment selection—occasionally revising tumor classification, improving subtyping, and detecting clinically relevant germline variants (6.5%), about half previously missed.
The authors argue that WGS supports a “learning healthcare system,” where comprehensive genomic data continuously improves care, but emphasize remaining barriers: cost, infrastructure, and data integration.
Five surprising points
About 1 in 10 patients would miss actionable findings with even large gene panels.
CUP diagnosis was solved or clarified in ~2/3 of cases, a major clinical pain point.
WGS turnaround (~6 days) is now comparable to standard NGS panels.
Half of germline findings were previously undetected, despite prior testing.
Survival benefit appears front-loaded—strongest before prior therapy, not after multiple lines.
Fun Fact
Here's the title of this Dutch paper, in Dutch:
“Klinisch nut van volledige genoomsequencing van tumoren in de praktijk bij solide kankers”
What do the authors see as next steps?
The authors’ main next step is not “more sequencing” per se. It is building the system around WGS so it can be used earlier, more consistently, and in a way that keeps generating reusable evidence. They explicitly call for timely integration of WGS into care pathways, rather than using it mainly as a late-stage or last-resort test. They also emphasize centralized data infrastructure, harmonized reimbursement and guideline recommendations, and routine use of molecular-tumor-board-guided decision-making.
A second big next step is better prospective data capture. They want structured collection of treatment and outcome data so WGS results can be linked to what actually happened to patients. That is central to their vision of a “learning healthcare system,” where genomic data, treatments, outcomes, and quality of life are continuously connected and reused to improve future care.
Third, they say broader implementation will require national and international data platforms that aggregate WGS results together with clinical metadata and make those data usable not just for record-keeping, but for clinical and fundamental research.
And lurking behind all this is the practical barrier of cost and infrastructure. The authors note that WGS still faces adoption barriers despite falling sequencing costs, so policy alignment and implementation capacity are essential if it is to become a routine cornerstone of precision oncology.
In plainer English: their next step is from successful pilot to durable ecosystem.
