Purpose: The antibody–drug conjugate enfortumab vedotin (EV) releases a cytotoxic agent into tumor cells via binding to the membrane receptor NECTIN-4. EV was recently approved for patients with metastatic urothelial carcinoma (mUC) without prior assessment of the tumor receptor status as ubiquitous NECTIN-4 expression is assumed. Our objective was to determine the prevalence of membranous NECTIN-4 protein expression in primary tumors (PRIM) and patient-matched distant metastases (MET). Experimental Design: Membranous NECTIN-4 protein expression was measured (H-score) by IHC in PRIM and corresponding MET (N = 137) and in a multicenter EV-treated cohort (N = 47). Progression-free survival (PFS) after initiation of EV treatment was assessed for the NECTIN-4–negative/weak (H-score 0–99) versus moderate/strong (H-score 100–300) subgroup. The specificity of the NECTIN-4 IHC staining protocol was validated by establishing CRISPR-Cas9–induced polyclonal NECTIN-4 knockouts. Results: In our cohort, membranous NECTIN-4 expression significantly decreased during metastatic spread (Wilcoxon matched pairs P < 0.001; median H-score = 40; interquartile range, 0–140), with 39.4% of MET lacking membranous NECTIN-4 expression. In our multicenter EV cohort, absence or weak membranous NECTIN-4 expression (34.0% of the cohort) was associated with a significantly shortened PFS on EV (log-rank P < 0.001). Conclusions: Membranous NECTIN-4 expression is frequently decreased or absent in mUC tissue. Of note, the clinical benefit of EV strongly depends on membranous NECTIN-4 expression. Thus, our results are of highest clinical relevance and argue for a critical reconsideration of the current practice and suggest that the NECTIN-4 receptor status should be determined (ideally in a metastatic/progressive lesion) before initiation of EV. See related commentary by Aggen et al., p. 1377

Diabetes mellitus is a metabolic disease largely due to lifestyle and nutritional imbalance, resulting in insulin resistance, hyperglycemia and vascular complications. Diabetic kidney disease (DKD) is a major cause of end-stage renal failure contributing to morbidity and mortality worldwide. Therapeutic options to prevent or reverse DKD progression are limited. Endothelial and glomerular filtration barrier (GFB) dysfunction and sterile inflammation are associated with DKD. Neutrophil extracellular traps (NETs), originally identified as an innate immune mechanism to combat infection, have been implicated in sterile inflammatory responses in non-communicable diseases. However, the contribution of NETs in DKD remains unknown. Here, we show that biomarkers of NETs are increased in diabetic mice and diabetic patients and that these changes correlate with DKD severity. Mechanistically, NETs promote NLRP3 inflammasome activation and glomerular endothelial dysfunction under high glucose stress in vitro and in vivo. Inhibition of NETs (PAD4 inhibitor) ameliorate endothelial dysfunction and renal injury in DKD. Taken together, NET-induced sterile inflammation promotes diabetes-associated endothelial dysfunction, identifying a new pathomechanism contributing to DKD. Inhibition of NETs may be a promising therapeutic strategy in DKD.

PURPOSE: The anti-NECTIN4 antibody-drug conjugate enfortumab vedotin (EV) is approved for patients with metastatic urothelial cancer (mUC). However, durable benefit is only achieved in a small, yet uncharacterized patient subset. NECTIN4 is located on chromosome 1q23.3, and 1q23.3 gains represent frequent copy number variations (CNVs) in urothelial cancer. Here, we aimed to evaluate NECTIN4 amplifications as a genomic biomarker to predict EV response in patients with mUC. MATERIALS AND METHODS: We established a NECTIN4-specific fluorescence in situ hybridization (FISH) assay to assess the predictive value of NECTIN4 CNVs in a multicenter EV-treated mUC patient cohort (mUC-EV, n = 108). CNVs were correlated with membranous NECTIN4 protein expression, EV treatment responses, and outcomes. We also assessed the prognostic value of NECTIN4 CNVs measured in metastatic biopsies of non–EV-treated mUC (mUC-non-EV, n = 103). Furthermore, we queried The Cancer Genome Atlas (TCGA) data sets (10,712 patients across 32 cancer types) for NECTIN4 CNVs. RESULTS: NECTIN4 amplifications are frequent genomic events in muscle-invasive bladder cancer (TCGA bladder cancer data set: approximately 17%) and mUC (approximately 26% in our mUC cohorts). In mUC-EV, NECTIN4 amplification represents a stable genomic alteration during metastatic progression and associates with enhanced membranous NECTIN4 protein expression. Ninety-six percent (27 of 28) of patients with NECTIN4 amplifications demonstrated objective responses to EV compared with 32% (24 of 74) in the nonamplified subgroup ( P < .001). In multivariable Cox analysis adjusted for age, sex, and Bellmunt risk factors, NECTIN4 amplifications led to a 92% risk reduction for death (hazard ratio, 0.08 [95% CI, 0.02 to 0.34]; P < .001). In the mUC-non-EV, NECTIN4 amplifications were not associated with outcomes. TCGA Pan-Cancer analysis demonstrated that NECTIN4 amplifications occur frequently in other cancers, for example, in 5%-10% of breast and lung cancers. CONCLUSION: NECTIN4 amplifications are genomic predictors of EV responses and long-term survival in patients with mUC.

Diagnosis of adenocarcinoma in the liver is a frequent scenario in routine pathology and has a critical impact on clinical decision-making. However, rendering a correct diagnosis can be challenging and often requires the integration of clinical, radiological, and immunohistochemical information. We present a deep learning model (HEPNET) to distinguish intrahepatic cholangiocarcinoma (iCCA) from colorectal liver metastasis (CRM) as the most frequent primary and secondary forms of liver adenocarcinoma with clinical-grade accuracy using hematoxylin and eosin-stained whole-slide images. HEPNET was trained on 714 589 image tiles from 456 patients who were randomly selected in a stratified manner from a pool of 571 patients who underwent surgical resection or biopsy at Heidelberg University Hospital. Model performance was evaluated on a hold-out internal test set comprising 115 patients and externally validated on 159 patients recruited at Mainz University Hospital. On the hold-out internal test set, HEPNET achieved an area under the receiver operating characteristic curve (AUROC) of 0.994 (95% CI 0.989-1.000) and an accuracy of 96.522% (95% CI 94.521-98.694%) at the patient level. Validation on the external test set yielded an AUROC of 0.997 (95% CI 0.995-1.000), corresponding to an accuracy of 98.113% (95% CI 96.907-100.000%). HEPNET surpassed the performance of six pathology experts with different levels of experience in a reader study of 50 patients (P=.0005), boosted the performance of resident pathologists to the level of senior pathologists, and reduced potential downstream analyses. Here, we provide a ready-to-use tool with a clinical-grade performance that may facilitate routine pathology by rendering a definitive diagnosis and guiding ancillary testing. The incorporation of HEPNET into pathology laboratories may optimize the diagnostic workflow, complemented by test-related labor and cost savings.

Clear cell renal cell carcinoma (ccRCC) is characterized by a high degree of intratumoral heterogeneity (ITH). Besides genomic ITH, there is considerable functional ITH, which encompasses spatial niches with distinct proliferative and signaling activities. The full extent of functional spatial heterogeneity in ccRCC is incompletely understood. In the present study, a total of 17 ccRCC tissue specimens from different sites (primary tumor, n = 11; local recurrence, n = 1; distant metastasis, n = 5) were analyzed using digital spatial profiling (DSP) of protein expression. A total of 128 regions of interest from the tumor periphery and tumor center were analyzed for the expression of 46 proteins, comprising three major signaling pathways as well as immune cell markers. Results were correlated to clinico-pathological variables. The differential expression of granzyme B was validated using conventional immunohistochemistry and was correlated to the cancer-specific patient survival. We found that a total of 37 proteins were differentially expressed between the tumor periphery and tumor center. Thirty-five of the proteins were upregulated in the tumor periphery compared to the center. These included proteins involved in cell proliferation, MAPK and PI3K/AKT signaling, apoptosis regulation, epithelial-to-mesenchymal transition, as well as immune cell markers. Among the most significantly upregulated proteins in the tumor periphery was granzyme B. Granzyme B upregulation in the tumor periphery correlated with a significantly reduced cancer-specific patient survival. In conclusion, this study highlights the unique cellular contexture of the tumor periphery in ccRCC. The correlation between granzyme B upregulation in the tumor periphery and patient survival suggests local selection pressure for aggressive tumor growth and disease progression. Our results underscore the potential of spatial biology for biomarker discovery in ccRCC and cancer in general.

Aims: Different SARS‐CoV‐2 variants are driving various waves of infection of the corona pandemic. Official statistics provide no information on who died due to coronavirus disease 2019 (COVID‐19) or an alternative disease during which SARS‐CoV‐2 infection was detected. The current study aims at addressing the effect of the different variants evolving during the pandemic on fatal outcomes.Methods and results: Standardised autopsies were performed on 117 people who died of a SARS‐CoV‐2 infection and the findings were interpreted in clinical and pathophysiological contexts. The typical histological sequence of COVID‐19‐related lung injury was detected independently of the disease‐causing virus variant, but was significantly less common (50 versus 80–100%) and less severe in cases infected by omicron variants compared to precedent variants (P < 0.05). COVID‐19 was less often the leading cause of death following omicron infection. Extrapulmonary manifestations of COVID‐19 did not contribute to death in this cohort. Lethal COVID‐19 may occur after complete SARS‐CoV‐2 vaccination. Reinfection was not the cause of death in any of the autopsies of this cohort.Conclusion: Autopsies represent the gold standard in determining the cause of death after SARS‐CoV‐2 infection and autopsy registers are currently the only available data source allowing for evaluation of which patients died of COVID‐19 or with SARS‐CoV‐2 infection. Compared to previous variants, infection with an omicron variant affected the lungs less frequently and resulted in less severe lung disease.