ADAM17, short for a disintegrin and metalloprotease 17, is also known as tumor necrosis factor-converting enzyme, or TACE. Its defining feature is its ability to shed membrane-bound proteins: it cleaves the extracellular portions of molecules anchored in the cell membrane, releasing them as soluble signaling factors. Among its best-known substrates are the precursors of epidermal growth factor receptor ligands, such as heparin-binding EGF-like growth factor, whose release activates EGFR signaling, a pathway central to cell proliferation and survival. ADAM17 also processes the interleukin-6 receptor, enabling IL-6 trans-signaling, a mechanism that amplifies inflammatory communication between cells. Through these activities, ADAM17 sits at the junction of inflammation and cancer biology, which is why it has been extensively studied in human breast cancer and other malignancies.

What has been missing, the researchers note, is any systematic characterization of ADAM17 signaling in veterinary pathophysiology. Canine mammary tumors share striking biological similarities with human breast cancer, including hormone dependence, histopathological diversity, and a propensity for metastatic spread, yet treatment options for affected dogs remain limited, often revolving around surgery and chemotherapy. The team, led by André Luz and Marina Badenes, with collaborators at NOVA University Lisbon and Lusófona University, set out to determine whether ADAM17 plays a functional role in these tumors and whether modulating the pathway could alter cancer-relevant behaviors.

The first question was clinical: is ADAM17 expressed differently in tumors compared with healthy tissue? The researchers compared ADAM17 mRNA levels in canine mammary carcinoma tissues against normal mammary gland samples. The result was clear. ADAM17 expression was significantly elevated in carcinomas of histopathological grade II or higher relative to normal controls. Because higher histopathological grade reflects greater cellular atypia and more aggressive biological behavior, the finding suggests that ADAM17 upregulation accompanies tumor progression. The authors further suggest that its expression may be associated with tumor progression and dissemination, although supplementary analyses across individual clinical and histopathological parameters, including breed, tumor multiplicity, nodal involvement, distant metastasis, tumor size, necrosis, ulceration, and mitotic activity, did not reveal statistically significant differences for those individual variables.

To probe function rather than mere correlation, the team turned to two established canine mammary tumor cell lines, FR37-CMT and FR10-CMT. Their strategy was pharmacological: stimulate the ADAM17 pathway, inhibit it, and observe what happens to key cancer-related processes. Stimulation was achieved with lipopolysaccharide, a bacterial endotoxin that provokes inflammatory signaling, and with phorbol-12-myristate-13-acetate, or PMA, a potent activator of protein kinase C that is known to trigger ADAM17 activation. Inhibition was pursued with several complementary agents, including batimastat (BB-94), a broad-spectrum metalloprotease inhibitor; GI254023X, which preferentially targets the related protease ADAM10; KP457 and MEDI3622, more selective ADAM17 inhibitors, the latter being an antibody-based inhibitor; and appropriate solvent controls.

The first biological outputs examined were cell viability, apoptosis, and the response to doxorubicin, a mainstay chemotherapeutic drug. Here the results were largely negative, and that in itself is informative. ADAM17 did not appear to play a major role in FR37-CMT cell viability or apoptosis under basal conditions, nor did modulating the pathway change the cytotoxic effectiveness of doxorubicin. In other words, ADAM17 does not seem to be a general survival factor for these tumor cells, and blocking it would not be expected to sensitize them to this particular chemotherapy agent. The team also examined epithelial-to-mesenchymal transition, the developmental program by which epithelial cancer cells acquire invasive, mesenchymal characteristics, and again found no major role for ADAM17 in the FR37-CMT model.

The decisive result came from a different assay: cell motility. Using scratch wound migration assays, in which a confluent cell monolayer is wounded and the rate at which cells close the gap is measured over time points of 4, 8, and 24 hours, the researchers found that activating the ADAM17 pathway enhanced the migration of both FR37-CMT and FR10-CMT cells. PMA stimulation accelerated the recovery of the scratch, and this effect could be blunted by ADAM17-targeted inhibitors. Conversely, inhibiting ADAM17 activity with BB-94, KP457, or MEDI3622 reduced the rate at which cells repopulated the wound, with the selective inhibitors providing mechanistic confirmation that the effect was attributable to ADAM17 rather than to off-target actions of the broader metalloprotease blockade. GI254023X, the ADAM10-preferring inhibitor, contributed additional context by implicating the closely related ADAM10 pathway in motility as well, suggesting a family-level contribution to cell movement in these tumors.

Why does motility matter? Metastasis, the process that makes cancer lethal, begins with local invasion: tumor cells must detach, migrate through surrounding tissue, enter blood or lymphatic vessels, and seed distant organs. A cell’s migratory capacity is therefore a direct functional readout of its metastatic potential. The finding that ADAM17 promotes migration, without appreciably affecting viability or chemotherapy response, refines the picture of what this enzyme does in canine mammary tumors. It is not a driver of tumor cell survival but a facilitator of movement, consistent with its known biology as a sheddase that releases factors enabling cells to remodel their surroundings and respond to motility cues. The supplementary data also showed that amphiregulin secretion by FR37-CMT cells was not increased by pathway activation, hinting that the motility effect may be mediated by other ADAM17 substrates or downstream pathways yet to be pinned down.

The translational implication is straightforward and, for veterinary oncology, potentially significant. If ADAM17 activity drives the migratory behavior of mammary tumor cells, then pharmacological inhibition of ADAM17 could represent a promising strategy to limit the metastatic spread of mammary cancer in dogs, as the authors conclude. This would position an ADAM17 inhibitor not as a cytotoxic drug that kills tumor cells, but as an anti-metastatic agent that restrains their ability to move and invade, an approach that could complement surgery and existing chemotherapy. The availability of selective inhibitors, including the antibody-based MEDI3622 tested in this study, provides a starting point for such a strategy, although the leap from cell culture dishes to canine patients will require further validation, including studies in primary tumor models and ultimately clinical trials.

The study also carries broader resonance beyond veterinary medicine. Because canine mammary tumors are widely regarded as a comparative model for human breast cancer, defining the role of ADAM17 in dogs may illuminate aspects of the enzyme’s behavior that are difficult to dissect in human clinical material. The work, conducted with samples collected in a clinical diagnostic context and approved by the local animal ethics committee, was supported by institutional and Portuguese national science funding, including the Foundation for Science and Technology. For now, the message is a measured one: a well-known human cancer protease has been shown to be upregulated in aggressive canine mammary carcinomas and to promote tumor cell motility, opening a concrete, testable avenue for keeping metastasis at bay in man’s best friend.

Subject of Research: The role of the ADAM17 protease pathway in canine mammary tumor cell migration and metastasis

Article Title: ADAM17 pathway promotes canine mammary tumor cell migration

Article References: Luz, A., Santos, J., Catarino, J., Sousa, C., Fonseca, J., Campos, S., Alves, M., Baptista, P. V., Faísca, P., Fernandes, A. R., & Badenes, M. (2026). ADAM17 pathway promotes canine mammary tumor cell migration. BMC Cancer. https://doi.org/10.1186/s12885-026-16984-2

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16984-2

Keywords: ADAM17, canine mammary tumor, cell migration, metastasis, veterinary oncology, EGFR, IL-6 trans-signaling, metalloprotease inhibitors, EMT, doxorubicin, breast cancer, cell motility

The technical foundations of this shift are worth unpacking. Modern veterinary AI draws on the same deep learning architectures that revolutionized human healthcare: convolutional neural networks that parse medical images pixel by pixel, natural language processing models that mine unstructured clinical records, and machine learning classifiers that integrate multi-omics data for personalized treatment planning. What has changed is not the underlying mathematics but the surrounding ecosystem. Digital pathology scanners have made whole slide images routine, picture archiving systems have accumulated years of computed tomography and magnetic resonance studies, and cloud computing has placed training-grade hardware within reach of university labs. The editorial argues that these conditions have finally aligned, allowing veterinary researchers to move from proof-of-concept demonstrations toward validated, deployable systems that can assist clinicians in real time.

One of the most striking themes in the collection is the two-way traffic between veterinary and human oncology. In human breast cancer care, radiomics-based deep learning approaches have already proven effective at predicting outcomes and have been implemented across multiple health systems, including an internationally evaluated AI system for breast cancer screening published in Nature. Veterinary researchers are now adapting those methodologies to animal patients, and, remarkably, sending innovations back across the species barrier. Bertram and colleagues demonstrated a comparative approach to mitotic count detection in which a model trained on a canine breast cancer dataset showed excellent cross-collaborative performance, supported by a completely annotated whole slide image dataset of canine mammary tumors built specifically to aid human breast cancer research.

The traffic flows in the other direction too. Osteosarcoma, an aggressive bone cancer, is far more common in dogs than in people, which means canine histopathology archives hold a wealth of data that human medicine simply cannot match. Patkar and colleagues exploited this asymmetry by training a model through deep domain adversarial learning on canine histopathology slides to detect histologic subsets of osteosarcoma in human patients. Domain adversarial learning is a technique that deliberately teaches a network to ignore species-specific features, forcing it to focus on the morphological signatures of malignancy that are shared across species. The result is a species-agnostic classifier, and the editorial points to it as evidence that comparative artificial intelligence, executed with validation and a collective domain approach, has major implications for advancing human healthcare alongside veterinary care.

Within veterinary oncology itself, the collection documents rapid progress across nearly every diagnostic modality. In digital pathology, machine learning models have achieved automated diagnosis of seven canine skin tumor types directly from H&E-stained whole slide images, while computer vision systems originally developed to detect inflammatory pododermatitis of the paw are being repurposed for neoplastic skin conditions. On the imaging side, machine learning classifiers have been trained to categorize focal splenic lesions from their CT features and to predict the histologic type and grade of canine gliomas from MRI texture analysis, offering clinicians a non-invasive preview of what a pathologist would otherwise only see under the microscope. These are not speculative demos; they are published studies with quantified performance, and they sketch a future in which pre-predicting histology before surgery becomes routine.

Perhaps the most technically consequential work concerns reproducibility, a chronic weakness in diagnostic pathology. Mitotic count, the number of dividing cells counted per high-power field, is a cornerstone of tumor grading, yet it suffers from notorious interobserver variability. Deep learning algorithms have now been shown to outperform veterinary pathologists in identifying the mitotically most active tumor region, and computer-assisted mitotic counting using a deep learning-based algorithm has been shown to improve both interobserver reproducibility and accuracy. Automated nuclear morphometry, another deep learning approach, has been applied to prognostication in canine pulmonary carcinoma. By standardizing measurements that were previously subjective, these tools attack the reproducibility problem at its root, and the editorial suggests that such techniques may become the template for AI-assisted grading across tumor types.

Data itself is the other half of the equation, and the collection highlights both progress and friction. On the progress side, the release of curated datasets such as the pan-tumor CAnine cuTaneous Cancer Histology, or CATCH, dataset is helping to standardize research and accelerate development, giving labs everywhere a common benchmark. On the friction side, an evaluation of an open-source Named Entity Recognizer applied to veterinary oncology records, conducted by Pinard and colleagues, demonstrated the potential of natural language processing to streamline data curation while exposing real limitations. General-purpose NLP systems, trained mostly on human medical text, struggled with veterinary terminology without rigorous oversight, underscoring the need for domain-specific tools. Companion reviews on quality assurance in AI model development and external validation reinforce the message that a clever algorithm is worthless, or worse, without disciplined testing.

Then comes the uncomfortable question: who is watching the deployment? The editorial is candid that veterinary medicine currently has limited to no formal guidelines for the safe and adequate deployment of AI in hospital systems. In human healthcare, concerns about data privacy, algorithmic transparency, and inherent bias have already spurred rigorous regulatory frameworks, and the risks are not hypothetical. A widely cited modelling study found that AI systems can recognize a patient’s race from medical imaging itself, a capability with troubling implications for bias. In the veterinary sphere, Duggirala and colleagues have offered a regulatory perspective outlining current initiatives and future prospects for AI and machine learning deployment, while reviews of veterinary diagnostic imaging emphasize the need for clear guidelines and safe-deployment toolboxes. The editorial argues that these initiatives will form the foundation of tailored regulatory frameworks that safeguard patient welfare and promote responsible innovation.

What makes this moment genuinely viral, in the sense of an idea spreading fast, is the realization that veterinary oncology is not merely a consumer of human AI advances but a full partner in producing them. Dogs share our environments, develop spontaneously occurring cancers with striking molecular parallels to human disease, and age fast enough to generate longitudinal data at a pace clinical trials in people cannot match. A validated model trained on canine data can seed human applications, and vice versa, creating a translational loop that benefits patients on both ends of the leash. The editorial’s closing invitation is for clinicians, researchers, and regulatory bodies to engage with the collection and to keep collaborating, because the technology is arriving whether the guidelines are ready or not.

The collection, then, captures a pivotal moment. Computer-aided diagnostics, integrated multi-omics, specialized natural language processing tools, and cross-disciplinary comparative studies are converging on a field that has historically been data-poor and resource-constrained. The editorial’s message is measured rather than utopian: AI holds real promise for diagnostic precision and therapeutic outcomes, but only if the community invests simultaneously in curated datasets, rigorous validation, domain-specific language tools, and the ethical and regulatory scaffolding that human medicine has already begun to build. If it does, the future promised in the collection’s title may arrive in veterinary clinics first, and human oncology will be better for it.

Subject of Research: Artificial intelligence and informatics applications in veterinary oncology

Article Title: The future is here: an introduction to the Veterinary Oncology collection on Artificial Intelligence and Informatics

Article References: Pinard, C. J. (2025). The future is here: an introduction to the Veterinary Oncology collection on Artificial Intelligence and Informatics. Veterinary Oncology, 2(1), Article 10. https://doi.org/10.1186/s44356-025-00027-2

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00027-2

Keywords: artificial intelligence, veterinary oncology, deep learning, digital pathology, comparative oncology, mitotic count, natural language processing, radiomics, osteosarcoma, CATCH dataset, regulation, machine learning

The Golden Retriever Lifetime Study, launched in 2012 by the Morris Animal Foundation, was designed to untangle the dietary, genetic, and environmental risk factors behind four major canine cancers: lymphoma, hemangiosarcoma, high-grade mast cell tumors, and osteosarcoma. Golden Retrievers were chosen deliberately. Roughly half of all deaths in the breed are attributed to cancer, according to data from the Veterinary Medical Database, and the breed shows a markedly elevated incidence of hemangiosarcoma and lymphoma. Because privately owned dogs were enrolled young, between six months and two years of age, and followed with annual questionnaires, veterinary examinations, and biological sampling, the study captures lifestyle exposures years before any diagnosis is made.

In the new analysis, Dennis Ronzani of Ross University School of Veterinary Medicine and Sarah E. Hooper of Arkansas State University examined the activity and lifestyle questionnaire responses of 3,044 purebred Golden Retrievers across the first seven years of the study. During that window, 277 dogs were diagnosed with cancer, with a median age at diagnosis of 6.1 years. The researchers asked a deceptively simple question: could the exercise habits reported by owners, on their own, distinguish dogs that would develop cancer from those that would not?

Answering that question required overcoming a statistical obstacle that has long discouraged researchers from mining longitudinal cohort data. Standard machine learning algorithms assume that every data point is independently sampled, an assumption shattered by repeated annual measurements of the same dog. Classical models, meanwhile, struggle when the number of observations is smaller than the number of predictors. The team turned to a hybrid method called the BiMM forest, developed by Speiser and colleagues, which combines a generalized linear mixed model with a random forest algorithm. This architecture is specifically built to handle clustered, high-dimensional data with nonlinear relationships and interactions between predictors, making it well suited to serial owner reports spanning multiple years.

The researchers built two models. The first used only questions asked consistently from year zero through year seven; the second incorporated additional questions about the pace and duration of exercise that the Morris Animal Foundation added to the questionnaire starting in year three. The difference in performance was dramatic. The years zero through seven model achieved an overall accuracy of just 68.2 percent, while the years three through seven model reached 80.7 percent accuracy, an F1 score of 74.9 percent, and a fair area under the receiver operating characteristic curve of 0.763. The lesson was clear: knowing how briskly and how long a dog exercises carries far more predictive signal than knowing only which activities it performs.

Ranking the predictors by their mean decrease in Gini importance, the team found that the top variables were year in study, exercise frequency, exercise pace, exercise duration, and the frequency of swimming in both warm and cold weather, followed by the owner-reported overall activity level. Four of the ten most important predictors related directly to the frequency and duration of aerobic activity. Perhaps most surprising, the specific type of exercise and the surface on which it took place ranked low in importance. It was the rhythm and intensity of movement, not the movement itself, that carried the strongest association with cancer status.

The data also revealed a poignant behavioral shift after diagnosis. Owners of dogs diagnosed with cancer reported an 8 to 10 percent increase in exercise frequency in the years following the diagnosis, and a 15.6 to 68.88 percent increase in cold weather swimming, while warm weather swimming declined by 2.0 to 13.9 percent. At the same time, exercise pace and duration fell, with dogs diagnosed in year four showing a 7.8 percent reduction in duration and overall activity levels declining by as much as 15.5 percent. The authors suggest this pattern may reflect veterinary recommendations or owner research into the benefits of exercise for canine cancer patients, mirroring the well-documented phenomenon in which roughly three out of four human cancer survivors meet physical activity guidelines after diagnosis.

The findings resonate strongly with human oncology research. Moderate-to-vigorous physical activity is firmly associated with reduced risk of colon, kidney, liver, and mammary cancers in people, and has been shown to delay cancer onset even in women genetically predisposed to breast cancer. Laboratory studies add mechanistic weight: moderate-intensity exercise inhibits cancer cell proliferation and induces apoptosis in animal models, whereas strenuous activity can, in some contexts, promote tumor growth. Notably, most Golden Retrievers in the study exercised at a brisk walking pace for 10 to 60 minutes per session, which qualifies as moderate intensity under the Physical Activity Guidelines for Americans, yet the total weekly volume often fell short of the 150 to 300 minutes recommended for humans, echoing the finding that three quarters of the US population also fails to meet those guidelines.

The swimming data carry their own intriguing, and cautionary, dimension. Dogs diagnosed with cancer swam slightly more often in cold weather before diagnosis, and cold weather swimming rose sharply afterward, possibly reflecting the growing popularity of aquatic therapy and underwater treadmills for canine rehabilitation. But water quality introduces a potential confound. The US Environmental Protection Agency reports that more than 13 million acres of lakes and ponds are impaired by pollution, and epidemiological studies in humans have linked disinfection by-products such as trihalomethanes in chlorinated pools to increased cancer risk. One prior study even found that dogs with urothelial cell carcinoma were more likely to have swum in pools than cancer-free dogs, a connection the authors say warrants closer investigation.

The study has limitations that its authors acknowledge candidly. Because a data embargo restricted the analysis to the first seven years, many dogs had not yet reached the typical age of cancer diagnosis, and fewer than 10 percent of the cohort had a neoplastic diagnosis, too few to build models for individual cancer types. All cancers were therefore grouped together, and missing body condition score data, available for only some dogs and years, prevented the team from accounting for obesity, itself a known risk factor for certain canine cancers. Still, the authors argue that the results point toward a future in which veterinarians can offer evidence-based exercise guidance for dogs, focused on frequency, duration, and pace rather than activity type, and in which cumulative lifestyle exposures, shaped by owner behavior and environment, take their rightful place in canine cancer risk assessment. As more years of Golden Retriever Lifetime Study data become available, the same machine learning approach may reveal whether these patterns hold for specific tumors, and whether adjusting a dog’s exercise routine could genuinely shift its cancer risk.

Subject of Research: Physical activity patterns as predictors of cancer development in Golden Retrievers

Article Title: Physical activity predictors of cancer in Golden Retrievers: it's about frequency and intensity, not type

Article References: Ronzani, D., & Hooper, S. E. (2025). Physical activity predictors of cancer in Golden Retrievers: it's about frequency and intensity, not type. Veterinary Oncology, 2(1), Article 11. https://doi.org/10.1186/s44356-025-00024-5

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00024-5

Keywords: Golden Retriever, canine cancer, machine learning, physical activity, Golden Retriever Lifetime Study, veterinary oncology, BiMM forest, exercise frequency, exercise intensity, swimming, cancer risk factors, longitudinal study

Canine malignant insulinoma is a functional neuroendocrine tumour of pancreatic beta cells: a cancer that not only grows and spreads but keeps manufacturing insulin as though it were still serving the body. Middle-aged and older dogs are typically affected, with Boxers, German shepherds, Labrador retrievers and West Highland white terriers among the predisposed breeds. Affected animals may show increased appetite and weight gain, weakness between meals or after exercise, and, as the disease advances, collapse and hypoglycaemic seizures. Diagnosis rests on documenting clinical signs alongside inappropriately high serum insulin concentrations in the face of low blood glucose, often supported by imaging of a pancreatic nodule. Surgical excision is the mainstay of treatment but is rarely curative, because functional metastases frequently seed new insulin-producing lesions and bring the clinical signs roaring back.

The prognosis is sobering. The largest study of canine insulinoma to date, covering 93 dogs, reported a median survival of eight months with medical management and twenty months with surgery. Adjunctive drugs such as prednisolone, octreotide and diazoxide aim to blunt insulin’s effects rather than attack the tumour itself, while small studies of beta-cell-toxic streptozotocin and the tyrosine kinase inhibitor toceranib have hinted at benefit without establishing clear efficacy. This therapeutic vacuum is precisely what makes a high-resolution map of the tumour’s cellular landscape so valuable: it offers both candidate drug targets and potential biomarkers to identify which patients are at risk of metastasis before it happens.

Single-cell RNA sequencing overcomes the fundamental limitation of bulk RNA-sequencing, which averages gene expression across thousands of heterogeneous cells and thereby blurs the very distinctions that matter most. By profiling individual cells, researchers can identify malignant sub-populations, reconstruct the tumour microenvironment, and infer the communication channels between cancer and immune cells. Until now, only human and mouse pancreatic neuroendocrine tumours had been examined this way, and the mouse work relied on an experimentally induced model rather than spontaneous disease. The new study is the first to apply the technique to naturally occurring insulinoma in any species, using tissue surplus to diagnostic requirements after planned therapeutic surgery, with owner consent and no influence on clinical management.

The technical execution was meticulous. Fresh tumour tissue was transported in cold buffer within two hours of excision, minced, enzymatically digested with Liberase TL, and processed into single-cell suspensions before library preparation on the 10X Chromium system and sequencing on an Illumina HiSeq4000. Reads were aligned to the canine reference genome CanFam3.1, and clustering and differential expression analyses were performed in Seurat, with cell types assigned through canonical marker genes and automatic classifiers. Quality control demanded more than fifty detected genes per cell and less than ten percent mitochondrial read content, yielding an average of 123,536 reads per cell and transcripts from a median of 1,010 genes per cell.

The headline discovery is that all three tumour samples contained two transcriptionally distinct populations of insulin-expressing cancer cells, separated by roughly 8,000 differentially expressed genes. One population, dubbed INS+ FOS+ EGR1+ TP53+ and abbreviated INS+, maintains expression of the tumour suppressor TP53, the transcription factor EGR1, and the AP-1 component FOS. The second, INS+ FOSlow, shows strong downregulation of these genes and of around sixty other tumour suppressors, including NF1, ARID1A and CDKN1A, together with a 23.5-fold reduction in DUSP1, a regulator of MAPK signalling. Pathway analysis of the genes separating the two populations flagged the MAPK, mTOR, PI3K-AKT, Notch, Wnt and p53 signalling pathways, along with cellular senescence and apoptosis, all of them famous for their deregulation in cancer.

Despite their deep differences, both malignant populations retained the molecular identity of their beta-cell origin, expressing insulin-related genes such as IAPP, PCSK2, NKX2-2 and SLC30A8, and the chromogranin and secretogranin family markers CHGA, CHGB, SCG2, SCG3, SCG5 and SCGN that define neuroendocrine tumours. Strikingly, one of the very few genes ubiquitously expressed and significantly upregulated in both insulin-expressing populations was COX7A2L, elevated more than twenty-fold, with a mean of twenty-seven-fold, over other captured cells. The gene encodes a subunit of cytochrome c oxidase involved in mitochondrial respiration, has been linked to poor prognosis in pancreatic, ovarian and breast cancers, and its knockdown reduces tumour growth in mice, making it an obvious candidate for further investigation in insulinoma.

Copy number analysis added an evolutionary dimension. The INS+ FOSlow population carried more chromosomal alterations than the INS+ population, and in the patient with more advanced disease, these cells showed frequent deletion of chromosomes 13, 20 and 29 and amplification of 11, 14 and 15, alterations that were rare in the other population and largely absent in the less-affected patient. This pattern suggests that whole-chromosome copy number changes are not the initiating event in these tumours but accumulate as the disease progresses, potentially serving as a marker of advanced disease state. Meanwhile, comparisons between the two primary tumours revealed far fewer differences, roughly 600 differentially expressed genes, than existed between the two cancer cell populations within each patient, including genes such as TMSB4X, proposed as a cancer prognostic marker and reportedly overexpressed in toceranib-resistant liver cancer cells, and CLTRN, a stimulator of beta cell replication that was upregulated in the patient with more advanced disease.

Two findings from the metastatic lesion were genuinely unexpected. First, the metastasis contained all the cell types represented in the primary tumour, including immune populations, rather than presenting as a pure mass of neoplastic endocrine cells, a pattern consistent with locally invasive spread rather than lymph node metastasis. Second, and more startling, both insulin-expressing populations in the metastasis showed more than twenty- to seventy-fold upregulation of exocrine pancreatic genes, including CLPS, PRSS2, PRSS and CTRC, markers normally associated with digestive enzyme production and pancreatitis. For a tumour of endocrine origin, this is deeply atypical, and the authors suggest these genes may mark metastatic transformation, invasion or de-differentiation, though their significance remains to be determined.

The immune analysis completed the picture. The tumours harboured effector and memory T cells, naive CD4-positive T cells, B lymphocytes, and two macrophage populations distinguished by MS4A7 and S100A12 expression, with the greatest inter-patient differences appearing in the macrophage cluster. Cell communication analysis using CellChat identified significant interactions between cancer and immune cells, most notably CD40LG expressed by both insulin-expressing tumour populations engaging CD40 on infiltrating B cells, an axis implicated in angiogenesis and described as a prognostic indicator in breast cancer, and an APP interaction with the TREM2-TYROBP complex on macrophages. Insulin-expressing cells also showed upregulation of inflammatory response genes including C15orf48 and TRAF3IP2, while insulin-expressing tumour cells had the highest proportion of cells in S phase of any cell type examined, with the peak in the metastasis, underscoring why DNA replication remains a therapeutic target. The authors are candid about the study’s limits: two dogs, one breed, and no matched blood or healthy beta-cell reference data. Yet the demonstration that single-cell data can be recovered from veterinary surgical material surplus to diagnostic needs opens a translational window, since canine insulinoma shares histopathological features with human pancreatic neuroendocrine tumours, and any future therapy would need to hit both malignant sub-populations simultaneously, in dogs and potentially in people.

Subject of Research: Single-cell transcriptomic profiling of canine insulinoma and its tumour microenvironment

Article Title: Single-cell transcriptomic analysis of canine insulinoma reveals distinct sub-populations of insulin-expressing cancer cells

Article References: Wallace, M. D., Herrtage, M. E., Gostelow, R., Owen, L., Rutherford, L., Hughes, K., Denyer, A., Catchpole, B., O’Callaghan, C. A., & Davison, L. J. (2025). Single-cell transcriptomic analysis of canine insulinoma reveals distinct sub-populations of insulin-expressing cancer cells. Veterinary Oncology, 2(1), Article 13. https://doi.org/10.1186/s44356-025-00026-3

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00026-3

Keywords: single-cell RNA sequencing, canine insulinoma, pancreatic neuroendocrine tumour, beta cells, tumour microenvironment, TP53, EGR1, COX7A2L, metastasis, copy number alteration, tumour immunology, veterinary oncology

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

The stakes are high because AGASACA behaves in a paradoxical way. Although the primary tumor at the anal sac can be small at diagnosis, metastatic lymph nodes in the sublumbar region can grow large enough to partially obstruct the rectum, creating life-threatening consequences from disease that started in a gland the size of a pea. The disease also tends to progress relatively slowly compared with many other malignancies, which means that long-term locoregional control, rather than a rapid strike against distant spread, is the single most important goal for a successful outcome. Late in the disease course, metastases can also appear in distant organs such as the lungs, but it is the pelvic battlefield where most treatment decisions are won or lost.

Surgery has long been considered the first line of defense. Yet the review makes clear that the surgical landscape is more complicated than many clients realize. Local recurrence of the primary tumor after resection has been reported in anywhere from 4 to 44 percent of cases, with a median time to recurrence ranging from 140 to 374 days. When surgeons attempt to remove metastatic iliosacral lymph nodes, recurrence within the lymphocentrum has been documented in between roughly 12 and 59 percent of cases, sometimes within just six months of the operation. Perioperative complications occur in 12 to 39 percent of patients, and the most feared complication, hemorrhage during lymph node extirpation, affects up to 18 percent of dogs, with mortality reaching 2.2 percent. Critically, the risk of complications climbs sharply when lymph nodes exceed 4.5 centimeters in size, a threshold that should prompt especially careful conversations between veterinarians and owners.

Patterns of treatment failure tell a coherent story across studies. In one investigation of 34 dogs with early-stage disease treated with surgery alone, 21 percent developed local recurrence of the primary tumor at a median of 354 days, and 26 percent developed locoregional metastases at a median of 589 days. A larger study of 161 dogs stratified patients by surgical margins, using the familiar R0, R1, and R2 classification system, and found that only the presence of lymphovascular invasion and an R1 resection, in which tumor cells extend to the cut edge of the specimen, were statistically associated with recurrence. In dogs with massive primary tumors greater than 5 centimeters, none of the stage 2 patients developed lymph node metastasis, while more than half of those presenting with stage 3 disease progressed further. The unifying message is that disease stage at initial treatment mediates the risk of relapse, which implies that adjuvant therapies should be deployed on a risk-based basis rather than universally.

This is where radiation therapy enters the picture, and where the review offers its most nuanced analysis. Conventionally fractionated definitive radiotherapy, or CFDRT, aims to deliver the highest possible dose to residual tumor cells while respecting the tolerance of surrounding normal tissues, typically in 16 to 20 fractions of 2.5 to 3 Gy for total doses of 48 to 50 Gy. The problem is that its clinical role in microscopic AGASACA after surgery remains poorly defined. In a study of 113 variably treated dogs, adjuvant radiation did not produce a significant improvement in survival time, though the small number of irradiated patients and the slow natural history of the tumor may have masked a real effect. Meanwhile, dogs undergoing CFDRT develop moderate to severe acute side effects in organs at risk including the rectum, colon, urinary bladder, skin, and spinal cord, with recovery from acute toxicity taking 23 to 36 days after onset. The therapeutic index, the ratio of benefit to harm, may simply not be favorable enough for this approach in every patient.

The most striking finding in the review concerns hypofractionated radiotherapy for advanced disease. In a study comparing hypofractionated radiation against surgical extirpation of iliosacral lymph nodes in dogs with stage 3b AGASACA, radiation produced significantly longer outcomes: a median progression-free interval of 347 days versus 159 days for surgery, and a median survival time of 447 days versus 182 days. The authors offer a compelling technical explanation rooted in the geometry of radiation planning. When radiation oncologists contour a CT scan, they delineate all visible gross disease as the gross tumor volume, then add margins for subclinical microscopic extension to create the clinical target volume, and finally add further margin for setup uncertainty to create the planning target volume. This means radiation can treat the entire iliosacral lymphocentrum, including microscopic disease threading through the lymphatic network, in a way that no surgeon’s hands can match. Surgery removes individual enlarged nodes; radiation can sterilize the whole nodal basin.

Even the terminology of palliative care may need revision for this disease. Protocols delivering 20 Gy in five daily 4 Gy fractions, often labeled palliative because of their low total dose, have produced median progression-free survival of 289 to 347 days and median survival times of 329 to 447 days in AGASACA patients. For comparison, across a broad range of other tumor types treated with the same 4 Gy by 5 protocol, median progression-free survival was only 4.4 months. AGASACA appears roughly twice as responsive as expected, suggesting the tumor may harbor a low alpha-beta ratio, the radiobiological parameter that determines sensitivity to large fraction sizes, consistent with its slowly proliferating nature. The authors argue that defining treatment intent purely by fraction size and number may be inappropriate when a so-called palliative regimen delivers a year of disease control with mostly mild, grade 1 to 2 gastrointestinal side effects.

Not every advanced technique earns endorsement. Stereotactic body radiotherapy, which delivers ablative doses of 6 to 10 Gy per fraction over 3 to 5 fractions, showed promising survival numbers in small studies, with one report of a 991-day median survival in five dogs. But the largest SBRT study to date, involving 25 dogs treated for metastatic sublumbar lymph nodes, revealed a sobering safety signal: 48 percent of dogs developed late-onset changes in gait and hind limb lameness, including ataxia, paraparesis, weakness, and pain. The authors recommend reserving SBRT for macroscopic disease rather than microscopic tumor beds, and focusing treatment on the nodal region while addressing the primary site surgically. Chemoradiotherapy fares even worse in the evidence hierarchy. The largest dataset, 15 dogs treated with concurrent mitoxantrone, produced a 93 percent rate of severe moist desquamation and a 53 percent rate of clinically relevant late effects, including two dogs euthanized for chronic colorectal toxicity. The review concludes there is insufficient evidence to recommend routine chemoradiotherapy in this disease.

One further clinical pearl concerns hypercalcemia of malignancy, a paraneoplastic syndrome affecting 27 to 34 percent of AGASACA patients that can become an emergency when total calcium exceeds 16 mg/dL. Hypofractionated radiation resolved hypercalcemia in about 31 percent of cases alone, rising to 77 percent when combined with steroids or bisphosphonates, offering a non-surgical route to controlling this dangerous metabolic derangement. Looking forward, the authors call for prospective trials comparing fractionation schemes, systematic imaging-based assessment of response rates, and rigorous studies of patterns of failure. Modern technology, including intensity-modulated radiation therapy and cone beam CT image guidance, should theoretically reduce both acute and late toxicities compared with the older two-dimensional planning used in much of the published literature, though no study has yet confirmed this. For now, the review’s practical bottom line is clear: surgery remains the cornerstone for the primary tumor, radiation deserves serious consideration, and may even be preferred, for advanced nodal disease, and the humble five-fraction protocol may deserve a better name than palliative.

Subject of Research: The role of radiotherapy in treating canine apocrine gland anal sac adenocarcinoma

Article Title: Role of radiotherapy in canine apocrine gland anal sac adenocarcinoma: a review

Article References: Murakami, K., & Rancilio, N. (2025). Role of radiotherapy in canine apocrine gland anal sac adenocarcinoma: a review. Veterinary Oncology, 2(1), Article 12. https://doi.org/10.1186/s44356-025-00028-1

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00028-1

Keywords: canine cancer, AGASACA, radiotherapy, veterinary oncology, hypofractionated radiation, SBRT, iliosacral lymph nodes, hypercalcemia, chemoradiotherapy, surgical oncology, dogs, radiation side effects

The pharmacological rationale for studying epirubicin in cats stems from decades of human clinical data. In metastatic breast cancer trials comparing the two drugs at equimolar doses of 50 milligrams per square metre, doxorubicin produced ten cases of congestive heart failure, an incidence of 2.6 percent, while epirubicin produced just one case, or 0.3 percent. Epirubicin achieved similar anti-tumour efficacy with a more favourable haematological and non-haematological toxicity profile, particularly with respect to cardiac harm. In veterinary practice, interest in epirubicin as an alternative to doxorubicin was initially driven by this potential for reduced cardiotoxicity, and studies in dogs confirmed its activity in lymphoma as part of multi-agent protocols and as adjunctive therapy for splenic haemangiosarcoma. In the cats of this study, epirubicin had become the standard anthracycline because doxorubicin had become cost-prohibitive at the start of the study period, creating an unplanned but valuable natural experiment in feline tolerance of the drug.

The dosing regimen followed conventions extrapolated from feline doxorubicin practice. Every cat began treatment at 1 milligram per kilogram of body weight, administered intravenously, with five patients later escalated to 25 milligrams per square metre of body surface area at the treating clinician’s discretion, accounting for 19 of the 186 treatments, or roughly 10 percent. Cats received a median of two treatments each, with a range of one to seven doses; twenty-eight cats received a single dose while twenty-seven received four or more. No dose reductions were recorded for any patient. Prophylactic anti-emetic support was common: 55 of the 186 treatments included injectable maropitant given before the epirubicin infusion, and oral maropitant was prescribed for home use in 30 treatments. Other supportive medications, most frequently corticosteroids, the acid blocker famotidine and antibiotics, accompanied 54 percent of treatments. Infusion protocols differed slightly between the two institutions, with one diluting the drug in saline and delivering it over twenty minutes and the other administering it over ten minutes through a side port of a giving set.

The headline finding is that 56 percent of cats, thirty-seven of the sixty-six, exhibited some form of possible toxicity during or after treatment, but the overwhelming majority of these events were mild. Adverse events were graded using the Veterinary Comparative Oncology Group common terminology criteria, a standardised system borrowed conceptually from human oncology that ranks side effects from grade 1, mild, to grade 5, fatal. Anorexia and neutropenia, a fall in the white blood cells that fight infection, were the most common toxicities, and nearly all were grade 1 or grade 2. Only two events in the entire study resulted in temporary hospitalisation, and just four cats, 6 percent of the cohort, had treatment withdrawn because of adverse effects. No cat died as a consequence of epirubicin treatment. The authors caution, however, that distinguishing genuine drug toxicity from clinical signs of the underlying cancer was not always possible, particularly since many patients had lymphoma or metastatic disease that itself causes lethargy and poor appetite.

The haematological data offer reassurance about one of the most feared complications of anthracycline chemotherapy. Twenty-seven percent of cats developed at least one episode of neutropenia at some stage, but the highest grades recorded were only grade 1 in thirteen cats and grade 2 in five. Across all 186 treatments there were 37 episodes of neutropenia, a rate of 20 percent, and not a single case of grade 3 or grade 4 neutropenia, febrile neutropenia, or a neutrophil count below 1 times 10 to the ninth per litre was observed. Blood counts taken seven days after treatment, the presumed nadir or lowest point of the white cell curve, were available for 43 cats, and eleven of these showed mild neutropenia. No dose delays occurred in the 38 cats that received more than one treatment. The researchers note an important caveat: because the true timing of the neutrophil nadir after epirubicin has never been established in cats, sampling at day seven may have missed the actual low point, meaning some suppression could have gone undetected.

Gastrointestinal effects were less frequent than with doxorubicin. Twenty-nine gastrointestinal events occurred across the 186 treatments, affecting 24 cats, with sixteen treatments producing hyporexia, reduced appetite, and seven producing vomiting. Constitutional signs of lethargy appeared in ten cats, accounting for fourteen events. Where timing was documented, these episodes emerged between one and twelve days after treatment and typically resolved within 24 to 48 hours. Notably, a previous study of single-agent doxorubicin in feline lymphoma reported that 47 percent of cats lost their appetite and 26 percent were severely affected, whereas only about 9 percent of treatments in this cohort produced hyporexia and just five cats vomited. The authors cannot determine whether the widespread use of the anti-emetic maropitant suppressed these signs or whether epirubicin genuinely causes less gastrointestinal harm than doxorubicin in cats. They also raise the possibility that the doses used, extrapolated from doxorubicin rather than derived from feline pharmacokinetic studies, may have been subtherapeutic.

Renal and hepatic laboratory changes were scrutinised closely because nephrotoxicity is a known hazard of doxorubicin in cats. Among 52 cats with before-and-after measurements, eleven, or 21 percent, showed elevated or worsening blood urea nitrogen, though ten of these were grade 1 and seven cats with pre-existing elevation actually had stable or improved values afterwards. Only three cats, 6 percent, had increases in creatinine, all grade 1 and all less than 10 percent above baseline in animals that already had mild pre-treatment elevations. Urine specific gravity was not recorded, so pre-renal dehydration cannot be excluded as a contributor. On the liver side, seven of 42 cats, 17 percent, developed raised alanine aminotransferase, including two grade 3 and three grade 4 elevations, but the authors considered most of these unlikely to be caused by epirubicin. One grade 4 case resolved with antibiotics for a urinary tract infection, another occurred in a cat with chronic pancreatitis, cholangiohepatitis and hyperthyroidism, and a third involved a myeloma patient whose liver was infiltrated by plasma cells. No cat stopped treatment because of liver enzyme changes.

One clinically instructive case involved a hypersensitivity reaction during a cat’s second epirubicin infusion, with retching, vomiting, dullness, stridor and pharyngeal oedema appearing acutely. Treatment with oxygen, the antihistamine chlorphenamine, dexamethasone and maropitant resolved all signs within ten minutes, and the cat went on to receive two further uneventful treatments after prophylactic pre-medication. The timing after the second dose suggests a possible antibody-mediated mechanism, and the faster infusion rate used at one institution may have been a contributing factor, although two of three acute ptyalism events occurred during slower infusions at the other site. The authors also acknowledge a blind spot regarding the heart: no cat in the study developed signs of cardiotoxicity, but patients did not routinely undergo cardiac auscultation by a cardiologist, biomarker testing, electrocardiography or echocardiography, so cardiac harm may have been underestimated, particularly given that few cats received high cumulative doses or survived long enough for late effects to emerge.

The study’s limitations are those inherent to retrospective design: medical records vary in how faithfully adverse events are captured, clinician interpretation introduces observer bias, concurrent chemotherapy drugs and radiotherapy may have contributed to perceived toxicity, and owner reporting depends on their ability to recognise side effects at home. Severe events are considered unlikely to have been missed, since owners typically contacted the referral hospitals directly when problems arose. Nevertheless, the authors conclude that epirubicin at the doses used appears generally well tolerated in cats, with mainly mild and self-limiting adverse effects, and they argue that the low rates of gastrointestinal toxicity and neutropenia suggest dose escalation could be worth exploring. Before that happens, however, they strongly recommend a phase 1 clinical trial to establish the maximum tolerated dose, characterise feline pharmacokinetics, standardise infusion rates, which are known to influence doxorubicin pharmacology in cats, and define the drug’s optimal spectrum of activity. Proper evaluation of systemic toxicity, they emphasise, remains essential before epirubicin can be adopted as a routine substitute for doxorubicin in feline cancer patients.

Subject of Research: Toxicity of epirubicin chemotherapy in cats with cancer

Article Title: Retrospective assessment of toxicity associated with epirubicin chemotherapy in 66 tumour-bearing cats

Article References: Retrospective assessment of toxicity associated with epirubicin chemotherapy in 66 tumour-bearing cats. (n.d.). https://doi.org/10.1186/s44356-025-00029-0

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00029-0

Keywords: epirubicin, doxorubicin, chemotherapy, feline oncology, veterinary oncology, toxicity, neutropenia, cardiotoxicity, lymphoma, cats, anthracyclines, adverse events

The research team, led by Hedda Fjell Scheel of the Norwegian University of Life Sciences together with colleagues at Oslo University Hospital and the University of Oslo, took advantage of a publicly available dataset of whole transcriptome sequencing data from canine mammary tumors. After quality control and the removal of animals with incomplete survival records, the final cohort comprised 146 dogs aged between two and nineteen years, representing twenty different breeds. Thirty-eight of these dogs had a recorded time of death after surgery, ranging from one day to 709 days with a median of 205.5 days, while the remaining 108 were right censored, meaning they were still alive at their last follow-up. This substantial censoring proportion, roughly 74 percent of the cohort, posed a genuine statistical challenge that shaped every subsequent analytical decision.

The investigators built three competing Cox proportional hazards survival models. The first, a clinical model, used only variables measurable through standard veterinary workup. The second, a gene expression model, relied exclusively on standardized, pre-filtered transcriptomic features. The third combined both data types. Because the gene expression matrix contained 18,579 genes, vastly more predictors than the 38 survival events available, the team applied careful feature pre-filtering: they retained the 1,000 most variable genes by mean absolute deviation, removed highly correlated pairs above a threshold of 0.95, and selected genes significant in univariate Cox models at a false discovery rate below 0.1. This left forty candidate genes, none of which belonged to the PAM50 subtyping panel used in human breast cancer. Regularized elastic net regression with cross-validated tuning of the alpha and lambda parameters then selected the most informative features for the gene-based models.

Model performance was evaluated with Uno’s C-index, a censoring-robust concordance measure in which 0.5 represents random prediction and 1.0 perfect discrimination, and with time-dependent ROC-AUC at six months, one year, and two years after surgery. Across 100 iterations of Monte Carlo cross-validation with stratified train-test splits of 4:1, the results were strikingly clear. The clinical model achieved a median C-index of 0.646, marginally ahead of the gene expression model at 0.635 and the combined model at 0.621, though none of these differences reached statistical significance. More tellingly, at the clinically critical timepoints of six months and one year after surgery, the clinical model significantly outperformed both transcriptomic models, with a median ROC-AUC of 0.811 at six months compared with 0.727 for the gene expression model and 0.768 for the combined model.

What emerged as decisive were three humble, readily obtainable clinical variables. Stepwise regression favored a multivariate model containing age, lymphatic invasion assessed by tumor histology, and estrogen receptor status evaluated by immunohistochemistry. Lymphatic invasion exerted the largest effect on the hazard of death, confirming its previously reported prognostic power, while estrogen receptor positivity was associated with improved survival, mirroring the pattern well established in human breast cancer. Notably, histopathological grade and molecular subtype, both significant in univariate analyses, dropped out of the multivariate model, likely because they were strongly correlated with lymphatic invasion and estrogen receptor negativity and therefore added no independent information. The final clinical model explained 17.8 percent of the overall variation in survival.

The molecular subtyping analysis itself yielded biologically meaningful results. Using the single-sample MPAM50 classifier, every tumor in the cohort was assigned to either the luminal A or the basal-like subtype, with luminal A accounting for 58.2 percent of samples. Subtype was significantly associated with age, breed, lymphatic invasion, grade, and estrogen receptor status. Basal-like tumors were more frequently grade 2 or 3, more often showed lymphatic vessel invasion, and were overrepresented among estrogen receptor negative tumors, with 69.6 percent of the 23 receptor-negative tumors classified as basal-like. Dogs with luminal A tumors were on average one year younger, and Maltese dogs were more likely to harbor luminal A tumors. These findings indicate that the canine PAM50 subtypes capture tumor biology beyond what estrogen receptor status alone reveals, echoing their prognostic significance in human patients.

Perhaps the most intriguing result came when the researchers used the best-performing clinical model to assign each dog a risk score and split the cohort at the median into high-risk and low-risk groups of 73 dogs each. Survival differed significantly between the groups, with a log-rank p-value of 0.0036. Differential gene expression analysis then uncovered 433 genes significantly differentially expressed between the groups, 279 upregulated in high-risk tumors and 154 in low-risk tumors. Gene set enrichment analysis using the Hallmark collection from the Molecular Signatures Database revealed twenty-four significantly enriched pathways. High-risk tumors were enriched for signatures of proliferation, including E2F targets and the G2M checkpoint, and for metabolic programs such as oxidative phosphorylation and glycolysis, while low-risk tumors showed enrichment of immune-related pathways, including TNF alpha signaling, IL6-JAK-STAT signaling, inflammatory response, and interferon alpha response.

That immune activity marks the low-risk group is a finding with real translational resonance. In human breast cancer, both innate and adaptive immune components are associated with recurrence-free survival, and immune gene expression carries prognostic weight particularly in hormone receptor negative tumors. The canine data suggest that the immune system plays an equally central role in anti-tumor response across species, reinforcing the value of dogs as a comparative model for human breast cancer research. The two diseases share spontaneous onset, histological subtypes, underlying genetic alterations, and gene expression changes, yet molecular markers that transformed human breast cancer management, from PAM50 subtyping to gene expression signatures like MammaPrint, have never been incorporated into routine canine staging. This study represents one of the most systematic attempts to close that gap.

Why, then, did gene expression fail to improve prediction? The authors offer several candid explanations. Adding thousands of transcriptomic features to a small, heavily censored dataset may introduce more noise than signal, a phenomenon documented in large-scale benchmark studies showing that multi-omics survival models are widely sensitive to noise. Linear Cox models may also miss non-linear interactions between genomic and clinical features. Moreover, with only 38 events, statistical power is inherently limited, and a larger number of events might reveal differences that this cohort cannot detect. None of the models exceeded a time-independent C-index of 0.65, which, while comfortably above random, falls short of what would be needed for clinical implementation, though comparable multi-omics studies in humans rarely exceed 0.7 either.

The practical message for veterinary oncology is nonetheless concrete. Estrogen receptor status measured by immunohistochemistry and lymphatic invasion assessed by routine histology could be valuable additions to current TNM staging, potentially refining survival predictions and informing decisions such as whether ovariohysterectomy at the time of tumor removal might benefit a particular patient, since dogs with high serum estradiol and receptor-positive tumors appear more likely to benefit from that intervention. The authors also emphasize the limitations of using overall survival rather than cancer-specific survival in an elderly cohort, and they call for future studies to record cause of death, complete TNM parameters, and richer genomic data. Alternative modeling approaches such as boosting methods and random survival forests may yet extract more from transcriptomic data. For now, the study stands as a sobering and instructive reminder that in the era of big data, the humble microscope slide and the immunohistochemistry stain still hold their ground.

Subject of Research: Machine learning-based identification of prognostic factors for survival in canine mammary gland tumors

Article Title: Unraveling prognostic factors in canine mammary gland tumors using machine learning

Article References: Scheel, H. F., Zobolas, J., Lien, T. G., Lingaas, F., & Bergholtz, H. (2025). Unraveling prognostic factors in canine mammary gland tumors using machine learning. Veterinary Oncology, 2(1), Article 16. https://doi.org/10.1186/s44356-025-00030-7

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00030-7

Keywords: canine mammary tumors, machine learning, Cox regression, gene expression, estrogen receptor, lymphatic invasion, survival prediction, TNM staging, PAM50 subtyping, gene set enrichment analysis, veterinary oncology, precision medicine

Soft tissue sarcomas are malignant, locally invasive tumors arising from mesenchymal cells, and they are among the most common cancers in dogs. Sarcomas account for roughly 10 to 15 percent of malignant tumors in dogs, and about 80 percent of those are soft tissue sarcomas rather than bone tumors. The primary treatment is surgical removal, and the success of local control hinges on whether histological assessment of the margins confirms complete excision. Positive margins leave cancerous cells behind, increasing the risk of local recurrence and the morbidity that comes with it. The stakes are therefore high for getting margin information quickly, ideally while the patient is still on the table.

Optical coherence tomography, or OCT, is the imaging technology at the heart of this effort. It uses near-infrared light to generate real-time, high-resolution images of tissue microstructure, in much the same way ultrasound uses sound waves but with micrometer-scale resolution. Traditional spectral-domain OCT builds images from the intensity of reflected light, revealing depth-resolved structural detail. The technology has been tested for margin assessment in human breast cancer, where it achieved sensitivities of 92 to 100 percent for detecting positive margins, and human clinical trials are underway. The Ohio State team, led by Yuanlong Wang, Laura E. Selmic, and Ping Zhang, has now extended this approach to companion animals with an important upgrade: polarization sensitivity.

Polarization-sensitive OCT, or PS-OCT, is a set of hardware and software extensions that track the polarization state of the light reflected from tissue. This adds contrast mechanisms that ordinary OCT cannot provide. The key property is birefringence, an optical signature that arises from the arrangement of subcellular collagen within tissue and reflects how organized that tissue is. When tissue is damaged, degenerated, or necrotic, its structure breaks down and its birefringence drops. Cancerous tissue, with its disrupted architecture, therefore looks measurably different from healthy fat or muscle under polarization contrast. In prior studies of human breast tissue, PS-OCT demonstrated both qualitative and quantitative differences between cancerous and normal tissue. The system used in the study, a Thorlabs Telesto PS-OCT with a 1300 nanometer central wavelength, 3.5 millimeter imaging depth, and 5.5 micrometer axial resolution in air, synchronously captures traditional OCT images and three polarization metrics: retardation, optic axis, and degree of polarization uniformity, known as DOPU.

The physics behind these metrics is elegant. Two cameras record the reflected light as complex numbers, from which total intensity is computed pixel-wise for the standard OCT image. Retardation measures the difference in optical path experienced by two orthogonal linearly polarized states, calculated as an angle that reflects the ratio of irradiances in each polarization channel. The optic axis describes the orientation of the tissue’s birefringent axis within the plane transverse to the beam, derived from the Stokes parameters that fully characterize the polarization of light. DOPU quantifies the uniformity of polarization within a pixel neighborhood, ranging from 0 to 1, and serves as a regularized measure of how orderly the tissue’s polarization response is. Together with the intensity image, these four channels provide a far richer description of tissue than intensity alone, and the study set out to prove that a neural network could exploit that richness.

The researchers enrolled 48 canine soft tissue sarcoma specimens under an Institutional Animal Care and Use Committee approved protocol, ultimately analyzing 40 after excluding eight tumors that turned out not to be sarcomas. Board-certified veterinary surgeons excised the tumors with margins chosen purely on clinical grounds, and each specimen was wrapped in saline-soaked gauze to prevent drying before imaging. The team scanned the entire surgical margin in B-mode, continuously sweeping the tissue, and captured paired OCT and PS-OCT frames. An expert reviewed image quality, and a pathologist’s evaluation of corresponding histopathology sections provided the gold standard tissue labels. From 140 image pairs, the team cropped 1,553 patches using a sliding window with a 50-pixel stride, resizing each to 224 by 224 pixels to fit the ResNet50 backbone, a convolutional neural network architecture widely used in medical imaging.

The heart of the technical contribution lies in how the four image channels are combined. The team tested two fusion strategies. Early fusion simply concatenates all four images along the channel dimension and feeds them into a single ResNet50 backbone. Joint fusion instead runs four separate backbones, one per metric, and merges their learned feature vectors through a learnable weighted sum before a linear classifier makes the final cancer-versus-normal call. The joint fusion model won decisively, though at the cost of four times the parameters, longer training, and greater vulnerability to overfitting, a trade-off the authors describe explicitly between performance and computational complexity. Training used a 70-15-15 split of train, validation, and test data, with dogs kept whole within a single split to prevent patient overlap, five-fold cross-validation for hyperparameter tuning, random horizontal flips for augmentation, and early stopping against the validation set. Performance was assessed with AUROC, area under the precision-recall curve, F1 score, precision, recall, and accuracy, with uncertainty estimated by bootstrapping the test set 1,000 times.

The results were unambiguous. Both fusion strategies substantially outperformed a baseline model trained solely on traditional OCT images, which the authors attribute to the complementary polarization information. Adding PS-OCT metrics improved AUROC by up to 0.15 for cancerous image classification, and the more polarization metrics included, the greater the gain. The final joint fusion model reached 0.989 AUROC and 91 percent accuracy in detecting positive margins. Notably, the OCT-only baseline achieved the highest recall but at a punishing cost to precision, illustrating why intensity alone is insufficient for reliable intraoperative decisions. Ablation experiments with partial inputs, pairing OCT with just one PS-OCT metric at a time, confirmed that each polarization channel contributes, and that the full multimodal model is the strongest performer on the threshold-agnostic metrics that best reflect underlying discriminative power.

Perhaps the most clinically compelling feature is the diagnostic curve. Rather than simply reporting whether an image contains cancer, the model slides a fine window with a 5-pixel stride across the original image, computes the cancer probability for each patch, and aggregates overlapping predictions into a one-dimensional curve showing the probability of cancer at every horizontal position. In case studies, the curve stayed flat for pure cancerous and pure normal images, and for a mixed image containing tumor in roughly one third of the frame, it rose sharply over the cancerous region and tapered gradually across the margin into fat. This effectively performs a one-dimensional segmentation of the tumor, giving surgeons a map of where cancerous tissue lies rather than a bare yes-or-no verdict, and the window size and aggregation method remain adjustable to clinical preference.

The authors are candid about limitations. The training set is relatively small, and convolutional networks depend heavily on the comprehensiveness of their data, so broader validation is needed before generalizability can be trusted. Raw OCT images carry optical artifacts, motion blur, and noise whose effects on the model remain unquantified, and the fusion strategies explored were deliberately simple, leaving higher-order interactions between polarization metrics unexploited. The model is also far from clinical deployment; explainability, integration into surgical workflows, and careful validation of its effect on surgical outcomes all remain ahead. Still, the trajectory is clear. By teaching a neural network to read the polarization fingerprints that cancer leaves in collagen, this work moves real-time, AI-assisted margin assessment from a promising concept toward a practical tool, one that could spare dogs a second surgery and, if the companion-animal findings translate, may one day help human surgeons answer that oldest of operating room questions with far greater confidence.

Subject of Research: Deep learning-based intraoperative surgical margin assessment for canine soft tissue sarcoma using polarization-sensitive optical coherence tomography

Article Title: Deep learning-assisted surgical margin assessment for canine soft tissue sarcoma based on polarization-sensitive optical coherence tomography

Article References: Wang, Y., Selmic, L. E., & Zhang, P. (2025). Deep learning-assisted surgical margin assessment for canine soft tissue sarcoma based on polarization-sensitive optical coherence tomography. Veterinary Oncology, 2(1), Article 17. https://doi.org/10.1186/s44356-025-00032-5

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00032-5

Keywords: deep learning, polarization-sensitive OCT, optical coherence tomography, soft tissue sarcoma, surgical margins, veterinary oncology, canine cancer, convolutional neural networks, birefringence, cancer imaging, intraoperative diagnosis, ResNet50

The scale of the problem is considerable. Canine oral tumors account for up to 12 percent of all cancers seen in dogs, with melanoma, squamous cell carcinoma, acanthomatous ameloblastoma, and fibrosarcoma representing the most common diagnoses of the oral cavity and pharynx. When these tumors are caught early, wide surgical excision remains the most effective local treatment. But many oral cancers are diagnosed at a locally advanced stage, when complete surgical resection is no longer possible. Radiation and chemotherapy become the fallback options, and while radiation can produce high response rates in tumors such as oral melanoma and squamous cell carcinoma, one-year survival rates for some of the most common oral cancers fall below 50 percent. Novel adjuvant therapies are urgently needed to make those responses last.

The drug at the heart of the study, CB101, is a proprietary hydrogel-based injectable formulation of resiquimod, a molecule known as a toll-like receptor 7/8 agonist. Toll-like receptors sit on the surface or within certain immune cells and act as sentinels for danger signals. In humans, TLR8 is uniquely expressed on myeloid dendritic cells, monocytes, and natural killer cells, making it an attractive lever for pulling the immune system into a fight against cancer. Activating these receptors may disrupt the immunosuppressive microenvironment that tumors build around themselves. Resiquimod itself has never been approved by the FDA, but topical formulations have been tested in human clinical trials for skin diseases and as a vaccine adjuvant, generating an extensive body of toxicology and pharmacology data supporting its safety profile.

The rationale for pairing this immune agonist with radiation rests on a phenomenon called immunogenic cell death. High-dose radiation, such as the 8 Gy per fraction used in some hypofractionated protocols, can kill tumor cells in a way that makes them more visible to the immune system, releasing tumor antigens that dendritic cells can engulf and cross-present to CD8-positive cytotoxic T lymphocytes. Research suggests that doses around 8 Gy per fraction are particularly well suited to synergizing with immunotherapeutics. In principle, this cascade can generate an adaptive, tumor-specific immune response capable of affecting not just the irradiated tumor but also distant, non-irradiated lesions, the so-called abscopal effect. Preliminary mouse data showed that the combination of radiation and CB101 improved local tumor control compared with either treatment alone and elicited such abscopal responses. Injecting the drug directly into the tumor is designed to limit systemic exposure and minimize off-target immune side effects.

Three dogs with histologically confirmed head and neck cancers were prospectively enrolled in the pilot study. Each animal received a baseline CT scan for radiation planning, followed by palliative radiation therapy delivered as four weekly 8 Gy fractions over weeks one through four. CB101 was administered intratumorally at a fixed dose of 10 micrograms in 500 to 1,000 microliters of volume at one-week intervals during weeks two through five, with the first dose given immediately before the second radiation fraction. Treatment planning relied on CT-based software, and dogs were anesthetized and immobilized in vacuum cushions with bite blocks to ensure reproducible setup. A follow-up CT scan at week 12 assessed tumor response, and serial thoracic radiographs at week 24 monitored for distant metastasis. All owners provided informed consent under institutional animal care protocols.

Feasibility proved to be the study’s clearest success. Little to no difficulty occurred during the intratumoral injections, and leakage of the formulation was negligible. Tumors arising from or containing bone were more challenging to infuse; one dog with mandibular fibrosarcoma required both intratumoral and peritumoral administration because of the density of the tumor and its proximity to the normal mandible. Injections were generally performed under general anesthesia for patient comfort, and no pain was noted after the procedure. The volume of each injection was chosen based on the expected ability of the hydrogel to diffuse into the tumor and surrounding tissue, guided by physical examination, CT evidence of bone infiltration, and three-dimensional tumor measurements.

Safety outcomes were equally encouraging. Toxicity was graded using the Veterinary Cooperative Oncology Group criteria and a veterinary radiation morbidity scoring scheme. Only one adverse event was attributable to CB101 itself: a case of grade 1, mild pain during a fourth injection performed under light sedation rather than general anesthesia. Every other adverse event documented was an expected side effect of palliative radiation, and no dog experienced toxicity higher than grade II. One dog developed grade I skin and mucosal toxicity along with grade II ocular toxicity requiring eye drops and antibiotics, an outcome anticipated from the radiation dose distribution, which included a large portion of the left eye. Another dog experienced no toxicity at all.

Tumor responses varied, as expected in such a small and histologically diverse cohort. The dog with oronasal squamous cell carcinoma showed a partial response at week 12 but developed distant progressive disease, first in lymph nodes and then in the lungs, between weeks 12 and 24, and was euthanized 198 days after enrollment. The dog with oral melanoma experienced local progression at week 12 and pulmonary metastasis by week 24, surviving 254 days. The dog with oral fibrosarcoma had stable disease at the week 12 scan, with eventual progression outside the radiation field at week 26 and a survival time of 371 days. All three dogs were free of distant metastases when treatment began.

Intriguingly, serum cytokine analysis revealed negligible changes in the immune signaling molecules the team measured, including TNF-alpha, IL-6, IL-15, interferon-alpha, IL-1 beta, and IL-12p40. The researchers suspect the sampling schedule missed any transient cytokine peaks, which could be expected within hours to three days after dosing rather than a full week later. The absence of clinical signs of cytokine release suggests the weekly 10 microgram dose was well tolerated but may have fallen below a therapeutic threshold. The starting dose was chosen conservatively because a human trial using 12.5 micrograms intralesionally had reportedly triggered cytokine storm and hypotension in some patients. Other veterinary researchers have used far higher resiquimod doses, with a University of Kansas group treating dogs with cutaneous mast cell tumors using doses ranging from 0.07 to 1.36 milligrams and observing one complete response and three partial responses among six dogs.

The Penn team acknowledges several confounders, including the use of NSAIDs in two of the three dogs, which could have either blunted the innate immune response or improved outcomes through COX-2 inhibition, and antimicrobial treatment in one dog, which in human melanoma patients has been associated with worse survival on immunotherapy. Future studies, the authors say, should standardize these medications, sample blood at multiple early time points after injection, and consider analyzing tumor tissue to capture local immune effects within the microenvironment. A dose escalation study appears warranted, and the researchers envision eventually combining TLR agonists with checkpoint inhibitors, an approach that could shift immunologically cold tumors toward hot ones. As academic and industry groups work toward commercializing canine checkpoint inhibitors, this modest pilot study in three dogs may mark the first step of a translational path that runs from the veterinary clinic to human oncology and back again.

Subject of Research: Combining intratumoral resiquimod immunotherapy with hypofractionated radiation therapy in canine head and neck cancer

Article Title: Preliminary evaluation of the safety and feasibility of toll-like receptor ligand CB101 combined with hypofractionated radiation therapy in canine head and neck cancer: a pilot study

Article References: Ghanian, A., DiBona, J., Duda, L., Xu, X., Lukens, J. N., Pearce, T., Ehrhardt, M., Rook, A., Durham, A., Maity, A., & Flesner, B. (2025). Preliminary evaluation of the safety and feasibility of toll-like receptor ligand CB101 combined with hypofractionated radiation therapy in canine head and neck cancer: a pilot study. Veterinary Oncology, 2(1), Article 18. https://doi.org/10.1186/s44356-025-00031-6

Image Credits: AI Generated

DOI: 10.1186/s44356-025-00031-6

Keywords: canine cancer, head and neck cancer, radiation therapy, resiquimod, CB101, toll-like receptors, immunotherapy, intratumoral injection, veterinary oncology, dendritic cells, abscopal effect, pilot study