Discarded Protein Leftovers From Routine Cancer Biopsies Yield Deep Proteomes in Precision Oncology Breakthrough

Every day, in hospitals and genomic laboratories around the world, a remarkable resource is quietly thrown away. When tumor biopsies are processed for DNA and RNA sequencing, the extraction kits used to isolate genetic material leave behind a protein-rich residue that has, until now, been treated as waste. A new study from researchers at the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen, working with clinicians at Rigshospitalet, shows that this discarded fraction can be transformed into deep, clinically useful proteomic data, potentially changing how precision oncology is practiced. The work, published in the journal Clinical Proteomics, demonstrates that a single cancer biopsy can now yield integrated genomic, transcriptomic, and proteomic information without any additional tissue being taken from the patient.

The research emerged from the Copenhagen Prospective Personalized Oncology trial, known as CoPPO, an ongoing precision oncology study in which patients with advanced cancer undergo molecular profiling to guide therapy selection. In this setting, metastatic biopsies are routinely processed using the Qiagen AllPrep system, a commercial kit that simultaneously extracts DNA and RNA from a single sample. During that extraction, proteins are separated from the nucleic acids and end up in a flowthrough fraction that is normally discarded. The team, led by Filip Mundt and including renowned proteomics pioneer Matthias Mann, systematically asked whether this residual protein fraction could serve as a reliable starting material for mass spectrometry-based proteomics, and the answer turned out to be a resounding yes.

The technical challenge was considerable. Protein recovered from extraction flowthroughs is diluted in chemical buffers designed for nucleic acid work, and it must be recovered, concentrated, and cleaned up before it can be digested into peptides and analyzed by liquid chromatography coupled to mass spectrometry. The researchers developed and optimized procedures for each of these steps, including protein precipitation, enzymatic digestion, and peptide cleanup, and they evaluated multiple mass spectrometry acquisition strategies to determine which would deliver the best performance from this unconventional source material. Both data-dependent acquisition, which favors depth of identification, and data-independent acquisition, which favors quantitative consistency across samples, were tested in the context of real clinical biopsy specimens rather than idealized reference material.

The results were striking. Using optimized single-shot workflows, the team consistently generated deep proteomes from the AllPrep-derived material, quantifying more than 10,000 protein groups in data-independent acquisition analyses. That depth of coverage, from material that would otherwise have been discarded, places the quality of these measurements on par with dedicated proteomics workflows that consume precious additional tissue. Perhaps even more importantly for clinical applications, the proteomes retained tissue-associated biological signatures, meaning the protein profiles faithfully reflected the biology of the tumors from which the biopsies were taken rather than artifacts introduced by the extraction process.

One of the most clinically significant findings concerns compatibility with existing genomic diagnostics. The researchers found that the proteomes derived from the flowthrough material quantified protein products corresponding to approximately 71 percent of the genes represented on the FoundationOne CDx panel, a widely used clinical genomic profiling assay. This overlap means that the protein data can be directly interpreted alongside the genomic results that oncologists already rely on, providing a functional layer of information on top of the genetic alterations detected in the same specimen. Where genomics reveals which genes are mutated or amplified, proteomics reveals whether those changes are actually reflected in the abundance of the proteins they encode, and whether downstream signaling pathways are active.

Beyond total protein abundance, the team extended the workflow to phosphoproteomics, the analysis of phosphorylation marks that act as molecular switches on proteins and report on the activity of signaling pathways. Phosphoproteomic analyses of the recovered material identified more than 10,000 phosphorylation sites, including many associated with key oncogenic signaling pathways driven by AKT1, BRAF, and EGFR, proteins that sit at the heart of some of the most commonly targeted pathways in modern cancer therapy. This is particularly valuable in precision oncology, where a tumor may harbor a mutation in a druggable gene, yet the downstream pathway may or may not be activated. Phosphoproteomics offers a direct readout of that functional state, information that genomic sequencing alone cannot provide.

Practical considerations for clinical deployment were also addressed head-on. The researchers assessed sample stability during long-term storage and found that protein integrity was preserved in samples kept at minus 80 degrees Celsius for up to five years. This finding has immediate operational implications, because it means that flowthrough fractions recovered during routine DNA and RNA extraction can simply be archived in existing freezers, creating a retrospective proteomic resource from biopsies processed years earlier. Hospitals would not need to change their current extraction protocols or acquire new tissue; they would only need to stop discarding the protein fraction and store it instead.

Scalability, often the Achilles heel of clinical proteomics, was another focus of the study. Mass spectrometry throughput has historically been a bottleneck for large-scale clinical studies, but the team implemented short liquid chromatography gradients that enabled high-throughput analysis of up to 60 proteomes per day without compromising data quality. At that rate, a single instrument could theoretically process thousands of patient samples per year, bringing proteomic profiling within reach of the kind of scale that genomic sequencing pipelines already achieve routinely. The analytical reproducibility of the workflow was also evaluated, confirming that measurements were consistent enough to support the comparisons that clinical decision-making would require.

The implications for precision oncology are substantial. Current molecular tumor boards typically work from genomic and transcriptomic data, which describe the blueprint and the transcriptional activity of a tumor but say little about the actual effector molecules, the proteins, that carry out cellular processes and respond to drugs. Proteins are, as the authors note, the active effectors of cellular signaling, and integrating proteomic and phosphoproteomic measurements with genomic data has become an important objective in translational oncology. By demonstrating that this integration can be achieved from a single biopsy already being processed in routine clinical workflows, the study removes one of the biggest practical obstacles: the need for extra tissue that patients often cannot spare and that clinics often cannot obtain.

The Copenhagen team frames the work as a framework for integrated proteogenomic studies in precision oncology, and the phrase is apt. What they have built is not merely a new laboratory technique but a bridge between the molecular diagnostics that hospitals already perform and the deeper functional characterization that proteomics can add. As mass spectrometry instruments become faster and more sensitive, and as workflows like this one demonstrate that clinical material streams can feed them without added burden on patients, the vision of truly multi-layered molecular profiling, spanning genome, transcriptome, proteome, and phosphoproteome from a single needle biopsy, moves closer to routine reality. For patients with advanced cancer, whose treatment options often hinge on the quality and completeness of the molecular information available, that could mean better-matched therapies chosen from a far richer picture of what their tumor is actually doing.

Subject of Research: Recovery of protein from DNA/RNA extraction flowthroughs for scalable clinical proteomics and integrated proteogenomic profiling of cancer biopsies

Article Title: Scalable clinical proteomics from DNA/RNA extraction flowthroughs enables integrated proteogenomic profiling from a single cancer biopsy

Article References: Mundt, F., Bach Nielsen, A., Wang, J., Kerzel Duel, J., Westmose Yde, C., Amnitzbøll Eriksen, M., Lassen, U., Cilius Nielsen, F., Rohrberg, K., & Mann, M. (2026). Scalable clinical proteomics from DNA/RNA extraction flowthroughs enables integrated proteogenomic profiling from a single cancer biopsy. Clinical Proteomics. https://doi.org/10.1186/s12014-026-09632-1

Image Credits: AI Generated

DOI: 10.1186/s12014-026-09632-1

Keywords: proteomics, precision oncology, mass spectrometry, phosphoproteomics, cancer biopsy, proteogenomics, DNA/RNA extraction, clinical proteomics, CoPPO trial, FoundationOne CDx, data-independent acquisition, signaling pathways