Loading
Life sciences · Journal article
Clinical Proteomics · September 20, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Journal article.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
Abstract Background Precision oncology has largely relied on genomic and transcriptomic sequencing to guide therapy selection in patients with advanced cancer. However, these molecular layers do not fully capture the functional state of tumors, as proteins largely represent the active effectors of cellular processes and signaling pathways. Integrating proteomic and phosphoproteomic measurements with genomic data has therefore emerged as an important objective in translational oncology. In routine clinical workflows, tumor biopsies are frequently processed using DNA/RNA extraction kits such as the Qiagen AllPrep system, which generates a protein-rich flowthrough that is typically discarded. Methods Here we systematically evaluated whether the residual protein fraction generated during Qiagen AllPrep DNA/RNA extraction can serve as a reliable source for mass spectrometry–based proteomics in clinical tumor biopsies. Within the Copenhagen Prospective Personalized Oncology (CoPPO) precision oncology trial, residual protein fractions from metastatic cancer biopsies were recovered, precipitated, and processed using optimized workflows for liquid chromatography–mass spectrometry. We established procedures for protein recovery, digestion, and peptide cleanup, and evaluated multiple acquisition strategies including data-dependent acquisition (DDA) and data-independent acquisition (DIA). We further assessed sample stability during long-term storage, analytical reproducibility, scalability, and compatibility with phosphoproteomics. Results Optimized single-shot workflows consistently generated deep proteomes from AllPrep-derived biopsy material, quantifying more than 10,000 protein groups in DIA analyses. Protein integrity was preserved in samples stored at − 80 °C for up to five years. The resulting proteomes retained tissue-associated biological signatures and quantified protein products corresponding to approximately 71% of genes represented on the FoundationOne ® CDx panel. Phosphoproteomic analyses identified more than 10,000 phosphorylation sites associated with key oncogenic signaling pathways including AKT1, BRAF, and EGFR. Implementation of short liquid chromatography gradients enabled high-throughput analysis of up to 60 proteomes per day without compromising data quality. Conclusions Residual protein fractions from Qiagen AllPrep DNA/RNA extraction provide a scalable resource for deep proteomic and phosphoproteomic profiling from the same biopsy used for genomic and transcriptomic analyses. This workflow enables integrated proteogenomic characterization from a single clinical sample and provides a framework for integrated proteogenomic studies in precision oncology.