Old Wax Blocks, New Signals: Phosphoproteomics Adds a Functional Layer to Brain Tumor Diagnostics

For more than a decade, the diagnosis of brain tumors has been transformed by reading DNA. Sequencing, copy number analysis and genome-wide DNA methylation profiling now sit at the heart of how pathologists classify central nervous system tumors, distinguishing entities that look identical under the microscope but behave in radically different ways. Yet these powerful tools share an important blind spot: they describe what a tumor is, not what it is actively doing. A new proof-of-concept study published in Acta Neuropathologica shows that even routine, formalin-fixed paraffin-embedded tissue — the humble wax blocks filling pathology archives worldwide — retains enough molecular detail to reveal the functional state of a tumor’s signaling networks, adding a dynamic layer of information that genomics alone cannot provide.

The study, led by Dennis Friedel, Rhaissa Ribeiro da Silva, Felix Sahm and Philipp Sievers of University Hospital Heidelberg together with collaborators across the German Cancer Research Center, set out to answer a deceptively simple question: can proteomic and phosphoproteomic profiling of ordinary archived tissue recover biologically meaningful signaling information that complements established molecular diagnostics? The researchers focused on ten cases of IDH-wildtype glioblastoma, the most aggressive adult brain tumor, split evenly between five tumors carrying EGFR amplification — one of the most frequent and well-characterized genomic alterations in this disease — and five without it. Every tumor had already undergone complete diagnostic workup, including DNA methylation profiling on the Infinium EPIC array with classification by the Heidelberg Brain Tumor Classifier and targeted sequencing of 220 CNS tumor genes, providing a rigorous genomic and epigenomic reference against which the new protein-level data could be judged.

The technical achievement underlying the study lies in how the tissue was prepared. Formalin fixation and paraffin embedding have long been the nemesis of proteomics, because cross-linking and wax infiltration make proteins difficult to extract. The Heidelberg team applied an optimized plate-based workflow that dispensed with conventional xylene deparaffinization altogether. Tiny tissue punches were placed in a 96-well plate with sodium dodecyl sulfate and magnetic beads, then processed in a BeatBox tissue homogenizer, where an alternating magnetic field drives the beads to mechanically shatter tissue and surrounding paraffin. Four cycles of ten minutes of bead-based disruption alternated with twenty minutes of heating at 95 degrees Celsius liberated the proteins, which were then cleaned up and digested using an automated single-pot solid-phase-enhanced sample preparation, or SP3, workflow on a liquid-handling robot, with 55 micrograms of protein input per sample.

Phosphopeptide enrichment was performed with iron-NTA cartridges on an automated platform before analysis on an Orbitrap Exploris 480 mass spectrometer. Global proteomes were measured using a 90-minute data-independent acquisition method, while phosphoproteomes used data-dependent acquisition, with rigorous quality controls including an MCF7 reference sample processed alongside the tumors and regular injections of a HeLa peptide standard to monitor instrument stability. The results were striking: global profiling identified a median of 7,647 proteins per tumor, with 5,417 proteins detected in all ten samples. The phosphoproteomic analysis reached a total of 13,467 phosphosites, with a cohort median of 5,457 confidently localized sites per sample, and 1,233 phosphosites reproducibly found in every single tumor. Comparable intensity distributions across samples confirmed that the quantification was robust and consistent.

To interpret phosphorylation correctly, the researchers made a crucial methodological choice: phosphosite intensities were adjusted by subtracting the measured abundance of the corresponding protein from the matched global proteome. This protein-abundance adjustment helps ensure that differences in phosphosite levels reflect genuine changes in phosphorylation state rather than simply more or less of the underlying protein being present. With this adjustment in place, the team asked whether EGFR amplification left a detectable signature on the phosphoproteome — effectively using a known genomic alteration as a biological benchmark for the new technology.

The answer was yes, but with an important nuance. Principal component analysis of the adjusted phosphoproteomic data showed only partial separation between the two groups, with EGFR amplification status significantly associated with the first principal component, which accounted for 29.9 percent of total variance. Differential analysis identified 443 phosphosites meeting predefined exploratory criteria, and among the sites enriched in EGFR-amplified tumors were two phosphorylation sites on the EGFR receptor itself, Y1110 and Y1197, which remained enriched even after adjustment for protein abundance — a biologically coherent finding given the known signaling role of the amplified receptor. Kinase-substrate enrichment analysis, which infers kinase activity from the coordinated behavior of annotated substrate sites, revealed higher activity of EGFR together with SRC-family kinases including YES1, FYN, SRC, LCK and LYN in the amplified tumors, while kinases such as PRKACA, PRKG1, MAPKAPK2 and PDPK1 showed lower inferred activity in that group.

That nuance — substantial overlap between the groups despite the clear genomic difference — may be the study’s most conceptually significant message. Two tumors can carry the same driver alteration yet differ markedly in how that alteration is expressed at the level of downstream signaling. Genomics establishes that a driver is present; phosphorylation patterns reveal whether and how its pathway is actually being used. The authors argue that this makes phosphoproteomics an orthogonal functional layer that complements, rather than duplicates, genomic and epigenomic classification. The global proteome told a parallel story: EGFR protein itself was more abundant in amplified tumors, E2F target programs were enriched in that group, while non-amplified tumors showed enrichment of stress-, immune- and microenvironment-associated programs including hypoxia, interferon-gamma response, complement and apoptosis signaling.

To show how this might work in practice, the team built a prototype research-use-only report for one representative EGFR-amplified tumor, generated entirely from that single sample without reference to the rest of the cohort. The report combined analytical quality-control metrics with pathway-level enrichment and representative phosphosites, grouped into therapeutically relevant signaling categories such as EGFR/ERBB, RAS–RAF–MEK–ERK/MAPK, PI3K–AKT–mTOR and VEGF-associated signaling, with sites including EGFR Y869 and Y1197 supporting the pathway-level findings. The authors stress that this report is a demonstration of a potential reporting framework, not a validated diagnostic or therapeutic readout, and implies nothing about drug sensitivity.

The broader context makes the approach timely. Large-scale proteogenomic studies of glioblastoma have already shown that signaling states undergo substantial post-translational remodeling during tumor evolution, meaning functional state cannot be inferred from genomic alterations alone. Elsewhere in oncology, phosphoproteomic profiling has identified patient-specific drug targets in cholangiocarcinoma and defined clinically distinct subtypes with actionable vulnerabilities in hepatocellular carcinoma. In neuro-oncology, the N2M2/NOA-20 umbrella trial has already demonstrated the clinical value of functional pathway assessment, selecting glioblastoma patients with activated mTOR signaling — judged by phospho-mTOR staining — for treatment with temsirolimus. Multiplexed phosphoproteomics could in principle extend such strategies by assessing many signaling pathways simultaneously, though the authors caution that prospective validation and clinically applicable thresholds will be required.

Significant hurdles remain before this technology reaches the clinic. The study cohort comprised only ten tumors, so individual phosphosites and inferred kinase activities must be treated as hypothesis-generating rather than candidate biomarkers. Bulk tissue analysis cannot resolve the spatial and subclonal heterogeneity that defines glioblastoma, and the protein-abundance adjustment, while informative, does not constitute a direct measurement of phosphorylation stoichiometry. Kinase-substrate enrichment infers activity from annotated substrate behavior rather than measuring enzymatic activity directly. Analytical complexity, infrastructure requirements and the cost of mass spectrometry will likely confine the approach to selected clinical and translational settings for now, and standardization of tissue processing, pipelines, thresholds and reporting will be essential for broader implementation. Nevertheless, the core demonstration stands: routine FFPE archive tissue, long valued primarily for morphology and DNA, also preserves a readable record of the tumor’s active signaling life. Integrating that functional layer with genomic and epigenomic diagnostics could eventually give neuro-oncologists a more complete picture — connecting who a tumor is with what it is actually doing.

Subject of Research: Proteomic and phosphoproteomic profiling of archived FFPE glioblastoma tissue to complement genomic and epigenomic CNS tumor diagnostics

Article Title: Functional proteomic and phosphoproteomic profiling of routine FFPE CNS tumor tissue complements genomic and epigenomic characterization

Article References: Friedel, D., da Silva, R. R., Ahmed, I. A., Wolff, B. M., Neuerburg, A., Irsevic, R., Ahmadi, S., Jayavelu, A. K., Kulozik, A. E., Witt, O., Pfister, S. M., Krieg, S. M., Wick, W., von Deimling, A., Reuss, D. E., Sahm, F., & Sievers, P. (2026). Functional proteomic and phosphoproteomic profiling of routine FFPE CNS tumor tissue complements genomic and epigenomic characterization. Acta Neuropathologica, 152(1), Article 42. https://doi.org/10.1007/s00401-026-03091-6

Image Credits: AI Generated

DOI: 10.1007/s00401-026-03091-6

Keywords: phosphoproteomics, proteomics, FFPE tissue, glioblastoma, EGFR amplification, mass spectrometry, molecular diagnostics, CNS tumors, DNA methylation profiling, kinase signaling, precision oncology, neuropathology