Abstract Background Tumor budding (TB) is a histopathological feature associated with poor prognosis across multiple cancer types, including head and neck squamous cell carcinoma (HNSCC). Tumor buds represent the earliest traceable local invasion and are considered the before origin of minimal residual disease, local recurrence, and metastasis. However, the molecular processes underlying this phenomenon in HNSCC remain incompletely characterized, particularly with regard to intratumoral gene expression heterogeneity. Methods We performed whole-transcriptome spatial transcriptomics on tissue sections from Human Papillomavirus (HPV) negative HNSCCs, sampling distinct regions of interest encompassing tumor buds, tumor bulk from budding and non-budding tumors, and adjacent stroma. Differential gene expression analyses led to the development of a 28-gene tumor budding signature (TBS) that separated tumor buds from all other tissue types. The TBS was validated using bulk RNA-seq (TCGA-HNSC), single-cell RNA-seq, and independent spatial transcriptomics datasets. Associations of the TBS with responses to drugs were evaluated in pharmacogenomic datasets and findings were further investigated in a 3D invasion model including MEK inhibition. Results Tumor buds exhibited distinct transcriptional programs with upregulation of epithelial-mesenchymal transition markers and extracellular matrix remodeling genes. The TBS effectively identified tumor buds in the spatial transcriptomics dataset (AUC = 0.97), separated budding and non-budding tumors in the bulk RNA-seq TCGA-HNSC dataset (AUC = 0.8), and predicted overall survival in the latter dataset (HR = 1.54, p = 0.02). Analyses of single-cell and spatial transcriptomics datasets confirmed TBS expression primarily in malignant cells, its association with a hybrid epithelial-mesenchymal state, its expression predominantly at the leading edges of tumors, and its induction via subtypes of epidermal growth factor receptor activities. Pharmacogenomic analysis revealed that TBS-high squamous cell carcinoma cell lines were sensitive to MEK inhibitors, a finding validated in a 3D model of early local invasion. Conclusions Integrated spatial-molecular profiling established a molecular bud biomarker facilitating the quantification of TB in both tumor tissues and cultured cells. Insights from the analysis of diverse datasets contribute to a better understanding of the molecular mechanisms underlying tumor invasion, improved risk stratification, and the development of new therapeutic approaches in HNSCC.

Immune checkpoint inhibitors (ICIs) have markedly improved outcomes in malignant melanoma, yet accessible, tissue-based predictive biomarkers of response remain limited. PD-L1 expression, which remains widely used, offers some prognostic value but performs poorly at low expression levels. We performed liquid chromatography-mass spectrometry proteomic profiling on 185 melanoma samples, including 52 pretreatment samples from ICI responders and nonresponders. Differential expression and pathway analyses identified a 73-protein immune activation signature correlating with ICI response. Within this immune context, SH2D1A (SAP), a regulator of T- and natural killer-cell cytotoxicity, emerged as a top candidate biomarker. Internal immunohistochemical validation confirmed its strong predictive accuracy (area under the receiver operating characteristic curve: 0.93; sensitivity: 88%; specificity: 91%) in distinguishing responders from nonresponders, outperforming PD-L1, CD3, and CD8. Notably, SH2D1A retained its predictive power in PD-L1-low tumors (combined positive score < 10), suggesting clinical use in which the current markers fall short. Independent validation in an external tissue microarray cohort revealed attenuated predictive performance, likely reflecting the impact of intratumoral heterogeneity, as further suggested by whole-slide validation. Nevertheless, SH2D1A remained significantly enriched in tumors that responded to ICIs and was associated with improved survival outcomes, outperforming CD3, CD8, and PD-L1. In conclusion, these results suggest that SH2D1A provides information beyond established immune infiltration- and exhaustion-related markers, supporting further investigation of its potential role in biomarker-guided prediction of ICI response in melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense, desmoplastic microenvironment that drives disease progression, yet conventional models fail to capture this complex tumor-stroma coevolution. Here, we utilize the chick chorioallantoic membrane (CAM) platform to investigate tumor-stroma interactions using murine PDAC cell lines and patient-derived organoids (PDOs). Integrating single-cell RNA sequencing and spatial transcriptomics, we show that the CAM microenvironment supports the emergence of complex tumor ecosystems while preserving patient-specific characteristics. Within five days, in ovo tumors faithfully recapitulated the structural and molecular features of parental tumors. Histological analysis revealed the rapid recruitment and spatial organization of heterogeneous host cancer-associated fibroblast (CAF) populations, showcasing distinct myofibroblastic and inflammatory stromal states. Crucially, the model preserved intrinsic tumor heterogeneity and permitted functional interrogation of subtype-specific extracellular matrix remodeling and metastatic dissemination. Together, our findings demonstrate that the CAM provides a highly permissive niche for tumor-stroma coevolution. As a rapid, scalable, and biologically relevant platform, this in ovo model offers a powerful approach for studying stromal composition, metastatic progression, and patient-specific tumor biology in pancreatic cancer.

Abstract Background Treatment of head and neck squamous cell carcinoma (HNSCC) remains challenging and the survival rates of affected patients remain poor. A three-dimensional organotypic co-culture (3D-OTC) model where patient derived tumor tissue is cultured on human-derived fibroblasts (dermal equivalent, DE) was evaluated regarding its comparability to primary tumor tissue and its applicability in drug resistance testing. Methods 3D-OTC models were cultured from n = 10 HNSCC patients for up to 21 days. The growth pattern at the DE was compared to tumor budding of corresponding resection specimens. Furthermore, we immunohistochemically determined the immune cell infiltrate of primary tumor tissue and corresponding 3D-OTC models. Spatially resolved gene expression analysis (“Xenium in situ”) was performed for separate regions of interest within the 3D-OTC specimens and within primary tumor tissue. Up-regulated and down-regulated genes of the 3D-OTC samples were included in gene set enrichment analysis and up-regulated genes between invasive (invading the DE) and non-invasive tumor cells within the 3D-OTC samples were included in drug resistance testing using publicly available databases. Results The growth pattern observed at the DE was associated with tumor budding in primary tumor tissue. The density of CD3-/CD20-/CD56-positive cells was lower in 3D-OTC samples compared to primary tumor tissue. No such changes were observed for CD68-positive cells and no significant changes in the density of the immune cell infiltrate were detected during the cultivation period. The centroids and dispersion of the gene expression of the 3D-OTC samples did not differ from the corresponding primary tumor tissue. The regions of interest within the 3D-OTC samples showed distinct functional states in gene set enrichment analysis. The comparison of genes up-regulated in invasive tumor parts of the 3D-OTC samples could explain resistance of tumor subclones to certain chemotherapeutics. Conclusions The 3D-OTC model morphologically and transcriptomically resembles primary tumor tissue and its biology while preserving the tumor microenvironment. Furthermore, the 3D-OTC model allows the standardized evaluation of tumor tissue by the definition of transcriptomically separate regions of interest and thus, could help to evaluate the impact of personalized therapeutic interventions on the tumor and its microenvironment in vitro.

Abstract Background Human papillomavirus (HPV) is a major etiological factor in a subset of head and neck squamous cell carcinomas (HNSCC), particularly in the oropharynx, and reliable detection is critical for prognosis and treatment decisions. Methods We applied droplet digital PCR (ddPCR) assays targeting HPV16 oncogenes (E6, E7) and the non-oncogenic gene E2 to tumor tissue, blood plasma, and oral rinse samples from 58 HNSCC patients. Results were compared with p16INK4a immunohistochemistry (IHC). A cohort of 44 non-cancer controls was included. Longitudinal monitoring was performed in 33 patients with serial liquid biopsies. Results ddPCR identified 41% of patients as HPV16-positive in tumor tissue, with higher specificity than p16INK4a IHC, which yielded 10 likely false positives. Baseline liquid biopsy results were highly concordant with tissue findings, and all 44 controls tested negative. Both blood plasma and oral rinse performed reliably, though oral rinse may be particularly well suited for HPV-related HNSCC due to direct mucosal shedding. In longitudinal analyses, all initially HPV-positive patients showed HPV clearance after surgery. In two cases, loss of clearance (i.e. re-detection of HPV DNA in plasma and oral rinse) preceded clinically confirmed progression, with lead times of 87 and 122 days. Conclusion ddPCR-based HPV testing provides high diagnostic specificity compared with p16INK4a IHC and allows minimally invasive monitoring. Plasma and oral rinse represent complementary liquid biopsy sources, with oral rinse offering particular advantages for mucosal tumors. Longitudinal testing revealed early molecular recurrence, supporting its potential as a prognostic tool. While promising, the use of liquid biopsy–based HPV detection for screening at-risk but undiagnosed populations remains exploratory and requires further evaluation in larger cohorts.

Tumor budding (TB) is a prognostic biomarker in HPV-negative and HPV-positive head and neck squamous cell carcinoma (HNSCC). Analyzing TCGA and CPTAC mutation, RNA, and RPPA data and performing proteomics and IHC in two independent in-house cohorts, we uncovered molecular correlates of TB in an unprecedentedly comprehensive manner. NSD1 mutations were associated with lower TB in HPV-negative HNSCC. Comparing budding and nonbudding tumors, 66 miRNAs, including the miRNA-200 family, were differentially expressed in HPV-negative HNSCC. 3,052 (HPV-negative HNSCC) and 360 (HPV-positive HNSCC) RNAs were differentially expressed. EMT, myogenesis, and other cancer hallmarks were enriched in the overexpressed RNAs. In HPV-negative HNSCC, 88 proteins were differentially expressed, significantly overlapping with the differentially expressed RNAs. CAV1 and MMP14 protein expression investigated by IHC increased gradually from nonbudding tumors to the bulk of budding tumors and tumor buds. The molecular insights gained support new approaches to therapy development and guidance for HNSCC.

Background Immune checkpoint inhibitors (ICIs) of programmed cell death protein-1 (PD-1) or cytotoxic T-lymphocytes-associated protein 4 (CTLA-4) reinvigorate strong polyclonal T-cell immune responses against tumor cells. For many patients, these therapies fail because the development of spontaneous immune responses is often compromised, as the tumor microenvironment (TME) lacks proinflammatory signals resulting in suboptimal activation of antigen-presenting cells (APCs). Necroptosis is a special form of programmed cell death associated with leakage of inflammatory factors that can lead to APC maturation. However, it is unclear to which extent functional necroptosis in tumor cells contributes to ICI immunotherapy.Methods With genetically engineered tumor cell lines that lack specific components of the necroptosis machinery (mixed lineage kinase domain-like pseudokinase (MLKL), receptor interacting protein kinase 3 (RIPK3)), we addressed the importance of necroptotic tumor cell death for the efficacy of ICI immunotherapy in murine models. Preclinical data were aligned with genome-wide transcriptional programs in patient tumor samples at diagnosis and during ICI treatment for the activity of these pathways and association with treatment outcome.Results Mice bearing MLKL-deficient or RIPK3-deficient tumors failed to control tumor growth in response to anti-PD-1/anti-CTLA-4 immunotherapy. Mechanistically, defects in the necroptosis pathway resulted in reduced tumor antigen cross-presentation by type 1 conventional dendritic cells (DCs) in tumor-draining lymph nodes, and subsequently impaired immunotherapy-induced expansion of circulating tumor antigen-specific CD8+ T cells and their accumulation and activation in the TME. In vitro, co-culture of tumor cells undergoing necroptotic but not apoptotic programmed cell death resulted in increased uptake by phagocytic cells, associated with maturation and activation of DCs. Treatment of tumors with the epigenetic modulator azacytidine enhanced intrinsic transcriptional activity of the necroptosis machinery, and hence their susceptibility to ICI immunotherapy. In humans, transcriptome analysis of melanoma samples revealed a strong association between high expression of MLKL and prolonged overall survival and durable clinical response to immunotherapy with anti-PD-1 and/or anti-CTLA-4 checkpoint inhibitors.Conclusions Defective necroptosis signaling in tumor cells is a cancer resistance mechanism to ICI immunotherapy. Reversion of epigenetic silencing of the necroptosis pathway can render tumors susceptible to checkpoint inhibition.

Recent studies have shown that pulmonary neuroendocrine tumor (NET) subgroups, defined by the transcription factors OTP and ASCL1, correlate with age, sex, and tumor location. Their relationships with histology and hormone production, however, remain unclear. We analyzed 170 pulmonary NETs classified by OTP (O) and ASCL1 (A) expression into four groups: O + /A + , O + /A-, O-/A + , and O-/A-. Subgroups were assessed for histology, hormone expression, therapy-related markers, outcomes, and matched metastases. Among 152 resected primaries, O + /A + tumors (38%) were most frequent, occurring mainly in females (median age 72 years), and typically showed central or peripheral location, solid/spindle morphology with diffuse gastrin-releasing peptide (GRP), and focal ACTH/calcitonin. They also showed strong DLL3 expression and pronounced neuroendocrine cell hyperplasia. O + /A- tumors (23%) occurred predominantly in females (median age 56 years) with solid/trabecular patterns, occasional/ACTH, and strong SSTR2A/5 expression. O-/A- tumors (25%) were more common in males (median age 70 years), often central with solid/trabecular or oncocytic histology, serotonin expression (24%), and frequently SSTR2A-positivity. O-/A + tumors (14%) occurred across both sexes (median age 58 years), were centrally located, and solid, sometimes oncocytic features with moderate DLL3/SSTR2A expression. Metastases mirrored their primaries in transcription factor and hormone profiles. In the univariate analysis, OTP-negative tumors were associated with poorer disease-free survival (DFS). However, the multivariate analysis identified Ki67-based WHO grades (G1-G3) as the only independent prognostic factors. In conclusion, integrating OTP and ASCL1 refines pulmonary NET classification into four histologically and biologically distinct subgroups, providing additional insight into tumor heterogeneity. O + /A + tumors showed solid-spindle features and diffuse GRP and frequent ACTH expression, trabecular patterns characterized ASCL1-negative tumors, while oncocytic histology predominated in OTP-negative tumors, highlighting their role in defining tumor heterogeneity.

T-cell recruiting chemokines are required for a successful immune intervention in ovarian cancer, and also for the efficacy of modern anticancer agents such as PARP inhibitors. The chemokine CX3CL1 recruits tumoursuppressive T-cells into solid tumours, but also mediates cell-cell adhesions, e.g. of tumour cells, through its membrane-bound form. So far, its role in ovarian cancer has only been rudimentarily addressed. We show that high CX3CL1 expression significantly correlates with worsened survival in human high-grade serous ovarian cancer (n=219). In preclinical ovarian cancer, CX3CL1 plays a dual role, as it enhances the adaptive anti-tumour response, but overall still promotes tumour growth, the latter as a feature of the intraperitoneal environment. Moreover, PARP inhibitors are able to increase CX3CL1 release from human ovarian cancer cells. Collectively, our study shows that CX3CL1 is a driver of intraperitoneal tumour growth in ovarian cancer, a feature that may compromise the anticancer effect of CX3CL1-inducing PARP inhibitors.

Mass spectrometry imaging (MSI) is a powerful tool for spatially resolved multiomics analysis of tissue samples in clinical research. However, its proteomics application is still limited due to challenges such as low ionization efficiency and signal interference from complex tissue environments. On-tissue mass-tag labeling (OTMT) addresses these limitations using affinity-based imaging agents that incorporate cleavable, highly ionizable reporter groups known as mass-tags (MTs). The majority of existing MTs rely on antibodies as targeting elements and organic moieties as reporter groups. Here, we introduce a new class of MTs featuring small-molecule inhibitors as binding motifs. Specifically, we present PARPi-MT, composed of a photocleavable and luminescent Ru-(II)-based reporter and the poly-(ADP-ribose) polymerase (PARP) inhibitor Olaparib for the targeted bimodal imaging of PARP1 in H446 xenograft tumor and mouse brain sections, via desorption electrospray ionization (DESI)-MSI and fluorescence microscopy. Using small-molecule inhibitors as binding motifs expands the design versatility and potential applications of OTMT, while overcoming some of the challenges of antibody-based mass-tags. The Ru-(II)-based reporter group offers further advantages, including distinct isotopic signatures derived from the metal center and inherent multimodal imaging capabilities.

Lebertumoren sind häufige und tödliche Erkrankungen beim Menschen mit einer oft schlechten Prognose. Um Mechanismen und potenzielle Therapien des hepatozellulären Karzinoms und des Cholangiokarzinoms besser zu verstehen, werden in der präklinischen Forschung meist experimentelle Tiermodelle eingesetzt. Spontan auftretende Tumoren in Haustieren könnten ebenfalls modellhaft untersucht werden. Häufig verwendete Tiermodelle in der Erforschung hepatischer Tumoren inklusive ihrer Verwendung und Vor- und Nachteile werden in Übersichtsform dargestellt. Daneben wird auch die Pathologie häufiger spontaner Lebertumoren bei Hund und Katze charakterisiert. Neben einer Auswertung von Fachliteratur und der Darstellung von Befunden in Tiermodellen wurde eine Fallstatistik eines veterinärpathologischen Einsendungslabors durchgeführt. Zur Erforschung hepatischer Tumoren werden am häufigsten Mausmodelle verwendet. Dabei kommen Xenografts, bei denen humane Tumorzellen injiziert werden, chemisch und diätetisch induzierte Modelle zur Untersuchung von Umweltfaktoren und metabolischen Faktoren sowie gentechnisch veränderte Mäuse zum Einsatz. Neben Mäusen werden auch andere Spezies wie Ratten, Kaninchen und Waldmurmeltiere herangezogen. Letztgenannte besitzen ein artspezifisches Hepatitis-Virus und eignen sich daher besonders gut für die Untersuchung viraler Pathogenesen. Darüber hinaus entwickeln Haussäugetiere wie Hunde und Katzen spontane Neoplasien der Leber, was sie zu wertvollen Modellen macht. Hunde entwickeln bevorzugt hepatozelluläre Adenome und Karzinome. Bei Katzen stehen hingegen benigne, zystische Gallengangveränderungen im Vordergrund. Es stehen zahlreiche Tiermodelle für diverse Fragestellungen zur Verfügung. Die Auswahl des richtigen Modells ist für den Erfolg jeder Studie entscheidend und von vielen Faktoren abhängig.

Pancreatic ductal adenocarcinoma (PDAC) subtyping typically relies on immunohistochemistry (IHC) staining for critical markers like HNF1A and KRT81, a labor-intensive manual staining process that introduces variability. Virtual staining methods offer promising alternatives by generating synthetic IHC images from routine hematoxylin and eosin (H&E) slides. However, most current approaches evaluate success by image quality measures rather than assessing diagnostically relevant features. Here, we introduce a novel cycleGAN framework utilizing a contrastive-inspired approach trained on semipaired datasets derived from consecutive tissue sections. Our method significantly enhances PDAC subtyping accuracy based on synthetic IHC images generated from standard H&E inputs, improving the classification F1-score from 0.66 to 0.77 for KRT81 and from 0.61 to 0.73 for HNF1A, compared with classification directly on H&E images. This approach also substantially outperforms baseline CycleGAN models. These results underscore the clinical potential of contrastive virtual staining to streamline PDAC diagnostics and improve their robustness. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.