The scale of the undertaking is considerable. The researchers assembled a panel of cell lines representing the major organs, tissues and cancers of the body: epithelial, mesenchymal, endothelial and fibroblast morphologies; cancerous and noncancerous phenotypes; primary and immortalized cells; suspension and adherent cultures; and even embryonal cells and induced pluripotent stem cells to capture early developmental signaling. Each line was profiled under two conditions, serum-starved and serum-stimulated, to sweep in both basal and dynamically regulated phosphorylation events. To boost coverage of the notoriously elusive phosphotyrosine sites, the team also treated colorectal cancer DLD-1 cells with pervanadate, a broad-spectrum inhibitor of tyrosine phosphatases that traps tyrosine phosphorylation at detectable levels. The result is a deliberately broad sampling of the signaling states a human cell can occupy.

Technically, the atlas was built on state-of-the-art mass spectrometry. Both unenriched peptide mixtures, representing each cell’s proteome, and phosphopeptide-enriched samples were analyzed on an Evosep One liquid chromatography system coupled to an Orbitrap Astral mass spectrometer operated in narrow-window data-independent acquisition, or nDIA, mode. Using a 30-samples-per-day gradient with a 200-hertz acquisition method, the team quantified an average of 9,681 protein groups per file. Collectively, the proteome library comprises 543,301 peptide precursors mapping to 16,454 protein groups, roughly 80 percent of the canonical human proteome, with a median protein sequence coverage of 50 percent. Crucially, more than 90 percent of protein kinases, phosphatases, transcription factors, oncogenes and tumor suppressors were identified, and nearly the entire human kinome, around 500 kinases, was covered without detectable bias across kinase families.

The phosphoproteome side of the atlas is even more striking. From the enriched samples, the researchers identified a mean of 30,446 class I phosphosites per file, and the combined phosphopeptide spectral library contains over 500,000 phosphopeptide precursors spanning 225,832 distinct phosphorylation sites. Almost two-thirds of these sites were assigned a localization probability of 0.99 or higher, meaning the exact position of the phosphate on the protein sequence could be pinned down with high confidence. The detected sites comprised 66 percent phosphoserine, 25 percent phosphothreonine and 9 percent phosphotyrosine, the latter proportion inflated by the pervanadate-treated cells; within individual cell lines, tyrosine phosphorylation settled back to the expected few percent. Benchmarking against public databases showed that over 60 percent of the detected sites overlapped with mass-spectrometry-derived resources such as PhosphoSitePlus, and that many sites previously catalogued without direct MS evidence could now be reproduced in a single unified experiment.

One of the most consequential outputs is the empirical spectral library itself, and the team put it through a rigorous stress test. They profiled a heterogeneous pool of differentiating stem cells, deliberately absent from the atlas, across four chromatographic gradients, and searched the data both with the empirical library and with library-free approaches in two widely used software packages, Spectronaut and DIA-NN. The library-based searches increased phosphoproteome depth under every condition tested, delivering a 60 percent gain in quantified phosphosites under high-flow conditions and 40 percent under low-flow conditions in Spectronaut when completeness filtering was applied. The gains came primarily through better-localized sites: library-based searches at a stringent localization cutoff of 0.98 matched the site counts of library-free searches at a much looser 0.75, indicating that high-quality reference spectra resolve the single biggest weakness of library-free phosphoproteomics, confident site localization.

The computational savings were equally dramatic. In DIA-NN, replacing a theoretical in silico phosphopeptide library of nearly 47 million precursors with the empirical library of roughly 540,000 slashed processing time for six files from 9 hours and 55 minutes to just 22 minutes, an average 30-fold speedup across gradients. For a field increasingly drowning in data from automated sample preparation and ultrafast instruments, that difference could reshape how large phosphoproteomics studies are designed. The library also proved its worth in low-input experiments: when the team analyzed EGF-stimulated HeLa cells with peptide inputs ranging from 1 to 20 micrograms, library-based searches yielded an average 18 percent increase in quantified phosphosites and, tellingly, more consistent detection of canonical EGFR activation sites such as the autophosphorylation site Y1110, which appeared in all stimulated replicates and none of the controls when the library was used.

Beyond cataloguing sites, the atlas ventures into one of the hardest quantitative questions in signaling biology: what fraction of a given protein is actually phosphorylated at a given moment, the so-called site stoichiometry. By pairing phosphoproteome measurements with matched proteome data under serum-stimulated and control conditions, the team calculated absolute occupancy for 19,378 phosphosites across 31 cell lines. Occupancies were generally low, below 20 percent, and rose upon serum stimulation. Motif analysis of the sites that gained phosphate revealed basophilic sequences characteristic of AGC-family kinases such as PKA, PKB and S6K, while dephosphorylated sites were enriched for proline-directed motifs targeted by MAPKs and CDKs, indicating phosphatase-mediated shutdown of those pathways. Three independent kinase inference algorithms agreed on the most serum-activated kinases, including ribosomal protein kinases, AKT and MAPK family members, while MARK kinases and cell-cycle CDKs emerged as the most strongly deactivated.

The stoichiometry data also delivered a sobering insight about tyrosine signaling: regulatory phosphotyrosine sites showed the lowest baseline occupancy despite displaying the largest fold changes upon stimulation. Only a small fraction of a tyrosine site needs to be phosphorylated to drive crucial downstream signaling, which explains why global profiling of tyrosine phosphorylation has historically required antibody-based enrichment. The atlas now provides baseline occupancy values for 182 known activation sites and 1,202 regulatory sites, a resource the authors say can help define the occupancy thresholds at which signaling events actually fire.

The culmination of the study is a new metric called the combined kinase activity score, or Cscore, designed to fix a persistent problem in the field: closely related kinases, especially tyrosine kinases, share so many substrates that existing inference tools frequently produce false positives. The team showed that three popular tools assigned EGFR activity to blood cancer cell lines that express no EGFR at all, and failed to flag the constitutively active FLT3 mutant in specific leukemia lines. The Cscore instead integrates five independent lines of evidence: kinase abundance at the proteome and phosphoproteome levels, substrate phosphorylation based on in vitro kinase-reaction relationships, sequence motif enrichment, and quantification of activation-loop sites on the kinase itself, with weights correcting for redundancy among components. Applied across the panel, it produced activity scores for 385 kinases in 31 cell lines and correctly scored directionality, assigning zero activity to EGFR and ERBB2 in suspension cells and high activity to ERBB2 in the BT-474 breast cancer line.

The translational payoff came when the researchers cross-referenced Cscore-predicted vulnerabilities with drug-sensitivity data from the Genomics of Drug Sensitivity in Cancer project. Of 210 kinase-cell line associations identified, several matched known dependencies: the neuroblastoma line NB1 with high ALK activity was sensitive to ALK inhibitors, FLT3-active MOLM-13 and MV-4-11 cells responded to FLT3 inhibitors, and BT-474 cells were sensitive to the ERBB-family inhibitors afatinib and CI-1033. Some predictions, such as NTRK1 activity in OCI-M1 cells, did not validate, a reminder that drug off-target effects and incomplete inhibitor specificity profiles complicate such comparisons. Yet DepMap genetic dependency data independently confirmed vulnerabilities including ALK in NB1, FLT3 in the leukemia lines, ERBB2 in BT-474 and SYK in SU-DHL-4. The authors also flag unvalidated but tantalizing targets, such as the ephrin kinases EPHA3 and EPHA4 in pancreatic cancer cells and ERN1 in HepG2 liver cancer cells. With the full dataset, spectral libraries, stoichiometry tables and Cscore scores deposited in public repositories and browsable through a web interface, the atlas is positioned to become a community standard, one that could turn the noisy landscape of cellular phosphorylation into a navigable map for drug discovery.

Subject of Research: A mass spectrometry-based phosphoproteome atlas of human cell lines mapping kinase activity and signaling vulnerabilities

Article Title: A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity

Article References: Koenig, C., Cho, H., Emdal, K. B., Piga, I., Sabatier, P., Lozano-Juárez, S., Martinez-Val, A., & Olsen, J. V. (2026). A phosphoproteome atlas of human cell lines reveals the landscape of kinase activity. Nature Structural & Molecular Biology. https://doi.org/10.1038/s41594-026-01877-6

Image Credits: AI Generated

DOI: 10.1038/s41594-026-01877-6

Keywords: phosphoproteomics, kinase activity, mass spectrometry, cell signaling, cancer, spectral library, DIA, phosphorylation, precision oncology, proteomics, drug sensitivity, cell lines

A research team led by Floryne O. Buishand, Phoebe Y. K. Chan, Dong Xia and Lucy J. Davison at the Royal Veterinary College turned to single-cell RNA sequencing, a technique that reads the gene expression of individual cells rather than averaging signals across a bulk tumour sample. This matters because tumours are not uniform populations; they contain rare subpopulations that may underlie treatment resistance or drive metastasis. Bulk RNA sequencing of canine insulinomas had previously shown that early-stage primary tumours resemble normal pancreas, while late-stage tumours resemble metastatic lymph nodes, but such bulk approaches cannot resolve the internal diversity of a tumour. By profiling cells one by one, the team could detect distinct clusters within each sample and identify marker genes that would be diluted into invisibility in a bulk measurement.

The researchers applied this technology to four insulinoma cell lines spanning three species: canINS, a canine line established from a spontaneously occurring insulinoma; CM, a human insulinoma line; INS-1, a rat line derived from a radiation-induced tumour; and MIN6, a murine line from a transgenic mouse expressing the large T antigen under the rat insulin promoter. Each line carries its own history and its own limitations. CM has large chromosomal rearrangements involving the insulin gene that abolished insulin secretion from early passages. MIN6 and INS-1 both secrete insulin, but their artificial genetic backgrounds do not resemble spontaneous insulinoma. Canine insulinoma, sharing clinical and molecular features with the human malignant disease, has been proposed as a translational model, and earlier work showed that Notch pathway inhibition could target chemoresistant cancer stem cells in both canINS and CM cells.

Between 5,427 and 9,423 cells were analysed per cell line, with a median of 3,606 to 5,964 genes detected per cell and 43,042 to 68,959 mean reads per cell. Computational clustering in R and Seurat revealed five or six distinct cell clusters in each line. All four lines expressed neuroendocrine markers, including ENO2, MAP2 and NCAM1, confirming their neuroendocrine identity, but a striking split emerged in their differentiation status. INS-1 and MIN6 expressed the full panel of islet hormones and mature beta-cell markers tested, including insulin genes Ins1 and Ins2, glucagon, Mafa and Pdx1. In contrast, canINS and CM expressed only ACVR1C, and in the case of CM also MAFA, among the mature beta-cell markers, and neither expressed insulin. Instead, canINS and CM expressed genes normally activated during pancreatic development or in early endocrine progenitors, such as GATA4 and ISL1, which were the only lineage-specific pancreatic progenitor markers detected in canINS.

This differentiation landscape has direct practical value. Dedifferentiation of pancreatic beta cells in adherent monolayer culture, with loss of insulin-secretory capacity, is one of the main obstacles to building representative preclinical insulinoma models. Notably, canINS cells have previously regained insulin expression and secretion when grown in non-adherent conditions, suggesting that their epigenetic memory remains intact and that the absence of insulin expression in monolayer culture does not disqualify a cell line as an insulinoma model. The study’s single-cell maps now allow researchers to make informed choices: INS-1 and MIN6 for questions requiring mature, insulin-producing beta-cell features, and canINS and CM, with their spontaneous-tumour origins, for studies closer to the clinical disease.

The team also examined epithelial-mesenchymal status, a critical axis in cancer metastasis. When cultured in monolayers, pancreatic beta cells undergo epithelial-mesenchymal transition, becoming highly proliferative cells that can re-differentiate into insulin producers. All four lines expressed the epithelial or ductal markers ANXA4, CDH1 and SLC4A4, but vimentin, a mesenchymal marker, was detected in all lines except MIN6 and was significantly higher in canINS and CM than in INS-1. This means canINS and CM contain substantial populations of hybrid epithelial/mesenchymal cells, a state previously observed in prostate, lung and colorectal cancer lines. Hybrid E/M cells are thought to migrate collectively as clusters of circulating tumour cells, enhancing metastatic potential compared with individually migrating cells, making canINS and CM the preferred models for studying how insulinoma cells acquire metastatic behaviour.

Perhaps the most tantalising discovery came from the cross-species comparison. Because single-cell analysis exposes genes robustly expressed in subpopulations that bulk methods would miss, the researchers catalogued the top ten marker genes for each of the 23 clusters identified across the four lines. Nineteen of these clusters were characterised by genes consistently expressed across all cell lines. Filtering for unique cluster markers with plausible cancer-related functions that were conserved across species and expressed in all four lines yielded eight candidate genes: DEPTOR, BICC1, GHR, CCNB2, CENPA, LMO4, VANGL1 and L1CAM. Several of these have documented pro-tumour roles in other cancers. BICC1 drives pancreatic cancer stemness and chemoresistance, L1CAM promotes perineural invasion in pancreatic cancer, CENPA has been implicated in chromosomal instability of pancreatic neuroendocrine tumours, and LMO4 is overexpressed in late-stage pancreatic cancer.

Among these candidates, the growth hormone receptor gene GHR stands out for its translational potential. GHR expression has previously been demonstrated by immunohistochemistry in canine primary insulinomas and their metastases, and growth hormone and insulin-like growth factor 1 expression were increased in metastases compared with primary tumours. This has led to the hypothesis that targeting the GH/IGF-1 axis might inhibit insulinoma proliferation and prevent micrometastatic outgrowth after surgery. Pegvisomant, currently the only clinically available GHR antagonist, is FDA approved for acromegaly, and promising preclinical results have been obtained with pegvisomant and a variant called compound G against pancreatic cancer xenografts, particularly in combination with gemcitabine. Because GHR emerged as a cross-species conserved cluster marker in all four insulinoma lines, the study provides a direct rationale for testing GHR inhibition in these models.

The second major achievement of the study addresses a logistical bottleneck that has long hampered single-cell research on rare tumours. Ideally, fresh patient samples are dissociated into single-cell suspensions immediately upon retrieval to prevent ischaemia-related gene expression changes and RNA degradation, then loaded onto droplet-based platforms within minutes. For rare diseases, where samples arrive sporadically and often far from sequencing facilities, this workflow is difficult to sustain. Cryopreservation offers an obvious solution, but only if freezing does not distort the transcriptomic picture. To test this, the team froze canINS and CM cells in 90 percent fetal calf serum with 10 percent dimethyl sulfoxide, stored them at minus 80 degrees Celsius for four weeks, thawed them, and sequenced them alongside fresh counterparts.

The verdict was emphatically reassuring. Cryopreserved samples yielded five canINS clusters and seven CM clusters, and most clusters matched their fresh counterparts closely, sharing five to nine of the top ten marker genes. Merged datasets showed near-equal distribution of fresh and frozen cells across all clusters, and expression of neuroendocrine, epithelial-mesenchymal, islet hormone and progenitor markers was fully maintained. Differential expression analysis identified 1,395 genes changed in cryopreserved canINS, but only six exceeded a log2 fold change of one, with BTF3, MEI4, NUPR1, FOS and SLC25A6 upregulated; in CM, 1,484 genes were differentially expressed and 29 exceeded the threshold, with TNFRSF12A, CKS1B and PTTG1 upregulated. Only FOS upregulation had previously been linked to DMSO cryopreservation in other cell types. These modest perturbations, the authors note, will need consideration but do not compromise data quality. The message for the field is twofold: insulinoma researchers now have a validated, species-spanning toolkit of cell lines matched to specific experimental questions, and banks of cryopreserved patient samples can finally enter single-cell studies without sacrificing fidelity, reducing assay-based variability and opening the door to larger, multi-centre studies of one of veterinary and human medicine’s most stubborn tumours.

Subject of Research: Single-cell transcriptomic analysis of fresh and cryopreserved multispecies insulinoma cell lines

Article Title: Single-cell transcriptome conservation in a multispecies comparative analysis of fresh and cryopreserved insulinoma cell lines

Article References: Buishand, F. O., Chan, P. Y. K., Xia, D., & Davison, L. J. (2025). Single-cell transcriptome conservation in a multispecies comparative analysis of fresh and cryopreserved insulinoma cell lines. Veterinary Oncology, 2(1), Article 14. https://doi.org/10.1186/s44356-025-00025-4

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00025-4

Keywords: insulinoma, single-cell RNA sequencing, cryopreservation, canine cancer, pancreatic neuroendocrine tumour, beta cells, transcriptomics, comparative oncology, GHR, oncogenes, cell lines, veterinary oncology

In an effort to improve on those dismal numbers, veterinary oncologists have tested a series of combination chemotherapy protocols incorporating agents such as vincristine, cyclophosphamide, and dacarbazine alongside doxorubicin. None has proven clearly superior to single-agent doxorubicin, and most carry greater toxicity. One combination, however, generated genuine excitement: doxorubicin paired with dacarbazine, administered as a true concurrent combination for dogs with advanced-stage hemangiosarcoma, produced an objective response rate of 47.4 percent in a prospective study, although its impact on overall survival remains undefined. The catch is logistical and toxic. Dacarbazine must be given as an eight-hour intravenous infusion every three weeks, and beyond the usual myelosuppressive risks of neutropenia and thrombocytopenia, it is notorious for causing acute gastrointestinal upset that requires prophylactic antiemetic therapy.

That is where temozolomide enters the story. Temozolomide is an oral chemotherapeutic closely related to dacarbazine, but far easier to administer and generally well tolerated in dogs, with favorable safety data already available when it is combined with doxorubicin in canine lymphoma patients. In human medicine, temozolomide is the first-line chemotherapy for glioblastoma multiforme, a deadly brain cancer, and its mechanism of action is well characterized. Once in the bloodstream, the drug spontaneously hydrolyzes into its active metabolite, 5-(3-methyl-1-triazeno) imidazole-4-carboxamide, or MTIC. MTIC methylates nucleotide bases in DNA, with guanine as the most important target. The cell’s mismatch repair pathway then detects these methylated bases and attempts to repair them in a futile cycle that ultimately triggers apoptosis, the programmed death of the cancer cell.

That mechanism also explains why some tumors resist the drug. In cells with an intact mismatch repair system, sensitivity to temozolomide is governed largely by a DNA repair protein called O-6-methylguanine-DNA methyltransferase, or MGMT. MGMT works by directly removing the methyl groups that temozolomide installs, effectively erasing the damage before it can become lethal. When MGMT is overexpressed, the drug’s fingerprints are wiped away almost as fast as they are written, and the tumor survives. In human glioblastoma, this relationship is so reliable that testing MGMT status, particularly epigenetic silencing of the MGMT promoter, is routinely used to decide whether temozolomide is a viable option for a patient. The question for veterinary researchers was whether the same logic could be imported into canine hemangiosarcoma: if MGMT expression varied among tumors, it might serve as a biomarker to identify which dogs would benefit from adding temozolomide to doxorubicin.

A new study led by Brianna Moore, Julie Nguyen-Edquilang, and Matthew R. Berry at the University of Illinois set out to test exactly that hypothesis in the laboratory. The team worked with five canine hemangiosarcoma cell lines, named DHSA-1426, Emma Brain, Emma Spleen, FITZ, and SBHSA, along with a canine aortic endothelial cell line as a comparison. The cell lines had been shared by collaborators at the University of Minnesota, Colorado State University, and the University of Wisconsin-Madison. To anchor their measurements, the researchers used a human cervical cancer cell line, HeLa, and a pair of mouse glioma cell lines, one wild type and one engineered to carry a human MGMT knock-in, as controls. All cells were cultured under standard conditions at 37 degrees Celsius in a humidified incubator with five percent carbon dioxide.

The researchers measured MGMT at two levels. Quantitative PCR, using canine-specific TaqMan primers with GAPDH as the reference gene, quantified MGMT transcript abundance across three biological replicates with five technical replicates each. Western blotting, performed with a rabbit monoclonal antibody and normalized to the loading control beta-actin, assessed protein expression. The two approaches told a generally concordant story. Four of the five hemangiosarcoma cell lines, DHSA-1426, Emma Brain, Emma Spleen, and SBHSA, showed low or absent MGMT transcript and protein. FITZ was the striking exception, displaying the highest MGMT expression of the panel, roughly twenty-fold greater protein expression than the canine endothelial cell line based on normalized densitometry. The protein bands appeared at the expected sizes, approximately 37 kilodaltons in human controls and approximately 40 kilodaltons in canine cells, a slight species difference confirmed against UniProt database entries.

With the expression map in hand, the team turned to cytotoxicity testing using the sulforhodamine B assay. Cells were seeded in 96-well plates, pretreated for two hours with O6-benzylguanine, an inhibitor that depletes the functional pool of MGMT, and then exposed to temozolomide at concentrations ranging from 0.033 micromolar to 1000 micromolar for seven days. Because temozolomide is unstable in solution, it was dissolved fresh immediately before each experiment. Cytotoxicity values were normalized against a DMSO live-cell control and a raptinal control that induces complete cell death, allowing relative responses to be compared across conditions. The control cell lines behaved exactly as biology predicts. GL261 wild-type cells, which lack MGMT, were sensitive to temozolomide even without the inhibitor, while GL261 MGMT knock-in cells were strongly resistant, with IC50 values comparable to the hemangiosarcoma lines, until O6-benzylguanine pretreatment sensitized them, producing the largest drop in IC50 of any line tested.

The hemangiosarcoma results defied expectations. Every canine cell line proved resistant to temozolomide across the entire tested concentration range, regardless of MGMT status. FITZ, the only line expected to be sensitized by MGMT inhibition based on its high expression, remained stubbornly resistant, showing an undulating dose-response curve with no concentration-dependent effect in any of three biological replicates, and no reliable IC50 could be determined. DHSA-1426 likewise showed minimal cytotoxic response across the range, precluding curve fitting. In other words, MGMT expression status could not predict temozolomide sensitivity in canine hemangiosarcoma cells, and blocking MGMT did not rescue drug sensitivity even where the protein was abundant. The data point instead to an MGMT-independent resistance mechanism, and the authors hypothesize that mismatch repair deficiency is the culprit.

That hypothesis has independent support. A comprehensive analysis of microsatellite instability in canine cancers, a hallmark of mismatch repair defects marked by mutations accumulating in repetitive DNA sequences, found a surprisingly high incidence of 63 percent across canine tumors, with hemangiosarcoma among the tumor types showing elevated instability. If canine hemangiosarcoma is indeed frequently mismatch repair deficient, the implications extend well beyond temozolomide. Mismatch repair deficiency also means deficient methylated DNA goes unnoticed by the cell, undermining the drug’s lethal futile-repair cycle. More intriguingly, tumors with high microsatellite instability carry increased mutational burden and therefore heightened immunogenicity, making them particularly susceptible to immune checkpoint blockade. The authors suggest this provides biological rationale for moving beyond chemotherapy combinations entirely and exploring chemo-immunotherapy, pairing doxorubicin with agents such as PD-1 or PD-L1 inhibitors.

The study’s conclusions are a sober but valuable course correction. MGMT remains a highly promising predictive biomarker for temozolomide selection in human glioblastoma, but this in vitro investigation demonstrates that canine hemangiosarcoma cell lines resist the drug through a mechanism that MGMT testing cannot capture. On that basis, the authors conclude the data do not support clinical exploration of temozolomide, alone or combined with doxorubicin, for treating dogs with hemangiosarcoma. Instead, the findings redirect attention toward characterizing mismatch repair deficiency in canine hemangiosarcoma and toward immunotherapy-based strategies that exploit the high mutational burden such deficiency creates. For a disease that claims most of its canine victims within a year of diagnosis, a result that rules out one dead-end combination while pointing toward a biologically grounded alternative is a meaningful step forward for comparative oncology.

Subject of Research: MGMT expression and temozolomide resistance mechanisms in canine hemangiosarcoma cell lines

Article Title: Investigating MGMT expression as a resistance mechanism to temozolomide in canine hemangiosarcoma cell lines

Article References: Moore, B., Nguyen-Edquilang, J., & Berry, M. R. (2026). Investigating MGMT expression as a resistance mechanism to temozolomide in canine hemangiosarcoma cell lines. Veterinary Oncology, 3(1), Article 24. https://doi.org/10.1186/s44356-026-00076-1

Image Credits: AI Generated

DOI: 10.1186/s44356-026-00076-1

Keywords: canine hemangiosarcoma, temozolomide, MGMT, doxorubicin, chemotherapy resistance, mismatch repair deficiency, microsatellite instability, veterinary oncology, DNA repair, immunotherapy, cell lines, dog cancer