Grant D. Stewart

Extract O’Dowd et al. [1] published the ERS/ESTS/ESTRO/ESR/ESTI/EFOMP (European Respiratory Society, European Society of Thoracic Surgeons, European Society for Radiation Oncology, European Society of Radiology, European Society of Thoracic Imaging, and European Federation of Organisations for Medical Physics) statement on the management of incidental findings on non-contrast thoracic low dose computed tomography (LDCT) for lung cancer screening. The kidney is partially imaged in 92% of people undergoing thoracic LDCT (median length of kidney visible 26% [2]). Shareable abstract Suggested updates to the ERS/ESTS/ESTRO/ESR/ESTI/EFOMP statement on management of incidental findings from low dose CT screening for lung cancer https://bit.ly/4bavVIH

Objectives: To assess to what extent hospitals meet the uniform English National Health Service ‘timely’ treatment standard, what happens after a breach, and determinants of delay for patients with high‐risk renal cell carcinoma (RCC). Patient and Methods: Population‐based study using linked data for 7030 patients with high‐risk and 10 708 patients with low‐risk RCC, 2019–2023. The probabilities of ‘timely’ treatment and prolonged delay (≤31 days or >62 days from decision‐to‐treat, respectively) were estimated using multilevel logistic regression. Daily treatment probabilities beyond 31 days were represented using smoothed hazard rates. Results: For a typical patient with high‐risk RCC, timely treatment declined from 83.7% (2019) to 64.8% (2023), with a corresponding decline in the low‐risk group from 71.3% to 47.6%, while prolonged delays more than doubled, from 3.9% to 9.4%. Patients with high‐risk RCC were prioritised over those with low‐risk disease (73.6% vs 58.2%; adjusted risk ratio 1.26, 95% confidence interval 1.22–1.31). Older and more socioeconomically deprived patients experienced longer delays. Once the standard was breached, the daily probability of surgery declined sharply. Adjusted percentages of patients with high‐ and low‐risk RCC treated within the standard were strongly correlated ( r = 0.78). Conclusion: Prioritisation of patients with high‐risk RCC was maintained throughout the study period but did not prevent a system‐wide decline in timely treatment. Patients who breach the timely treatment standard face diminishing daily probabilities of surgery. Risk‐stratified standards, ring‐fenced surgical capacity, and monitoring beyond defined timely treatment standards are needed to safeguard patients against delays that have significant prognostic implications.

Spatial transcriptomics maps gene expression at cellular resolution, revealing how cells organize into multicellular niches. Yet computational analyses remain dataset-specific, without a transferable representation of tissue organization that generalizes across datasets, tasks and tissues or predicts how tissues behave under perturbation. We present TERRA, a foundation model pretrained on 112 million human cells profiled by spatial transcriptomics. From a single pretrained backbone, TERRA yields embeddings at the scale of cells, the genes they express and the neighborhoods in which they reside, and supports spatial in silico perturbation, all applied zero-shot to unseen tissues. At the cell level, in newly generated spatial data for developing pancreas, TERRA identified an islet-associated capillary state which we posit represents a developmental precursor of the mature islet microvasculature. At the gene level, in untreated kidney sections, in silico knockout of immune-checkpoint targets predicted a gene program of immune-checkpoint-blockade-associated nephrotoxicity, which we validated in treatment-exposed tissue and recovered in blood. At the neighborhood level, TERRA mapped macrophages across tissues to identify recurring cross-organ niches, which we term archetypes, including a tumor-boundary niche associated with poor prognosis in kidney cancer. Together, TERRA captures the spatial and multicellular logic of human tissue and predicts, in silico, its response to perturbation, providing a multi-scale framework for tissue biology, therapeutic development and clinical application.

The cellular response to hypoxia is driven by hypoxia-inducible factors (HIF), which regulate genes involved in glycolysis, angiogenesis, and cell proliferation, as well as inflammation and tumor progression. HIF activation is well characterized and is primarily regulated by oxygen-dependent prolyl hydroxylation and subsequent degradation. SET1B, a histone H3 lysine 4 methyltransferase, has recently emerged as a key modulator of HIF target gene transcription, but evidence suggests that it plays a broader role in modulating HIF transcriptional activity beyond histone methylation. In this study, we revealed that SET1B interacts with RNA polymerase II to coordinate sustained HIF-mediated transcriptional activity through multiple functional domains. In clear-cell renal cell carcinoma (ccRCC), SET1B is critical for sustained HIF activity, and SET1B expression correlated with disease progression and metastasis in patient samples. Moreover, SET1B depletion enhanced the efficacy of HIF2 inhibitors. These findings establish SET1B as a driver of tumor progression and potential therapeutic target in ccRCC. Significance:SET1B functions as a key regulator of HIF-dependent transcription and cancer growth under low-oxygen conditions, revealing a therapeutic target to enhance treatment efficacy and potentially slow disease progression in kidney cancer.

SET1B depletion overcomes resistance to HIF2 inhibition in ccRCC. A, Immunoblots of WT, HIF2α KO, and HIF2α KO 786-0 cells reconstituted with WT HIF2α or the HIF2α G323E mutation. B, HIF2α KO cells reconstituted with WT and HIF2 G323E mutation were treated with 1 µmol/L PT2385 for 24 hours. Endogenous HIF1β was immunoprecipitated, and the interaction with HIF2α was assessed by immunoblotting. Immunoblot is representative of 3 independent experiments. C, HIF2α KO cells reconstituted with WT and HIF2 G323E mutation were treated with 1 μmol/L PT2385 for 24 hours. HIF2α target gene and SET1B mRNA expression was assessed by qPCR (n = 3 biological replicates). Graphs show mean ± SD. Two-way ANOVA. D, HIF2α KO cells reconstituted with WT and HIF2α G323E mutation were transfected with an SET1B siRNA for 48 hours. Twenty-four hours before harvesting, cells were treated with and without 1 μmol/L PT2385. qPCR analysis was performed using primers targeting the VEGFA and ANGPTL4 mRNAs (n = 3 biological replicates). Graphs show mean ± SD. Two-way ANOVA. E, ChIP of H3K4me3 and RNA Pol II (F) in HIF2α KO cells reconstituted with WT and HIF2α G323E mutation following CRISPR-mediated SET1B depletion 24 hours before harvesting cells were treated with 1 μmol/L PT2385. ChIP-PCR was performed using primers targeting the VEGFA promoter (n = 3 biological replicates). Graphs show mean ± SD. Two-way ANOVA. G, ChIP of HIF2α in HIF2α KO cells reconstituted with WT and HIF2α G323E mutation following CRISPR-mediated SET1B depletion 24 hours before harvesting cells were treated with 1 μmol/L PT2385. ChIP-PCR was performed using primers targeting the VEGFA promoter and exon 3 (n = 3 biological replicates). Two-way ANOVA. H, ccRCC mouse xenograft model. WT and SET1B-depleted 786-0 cells expressing luciferase were injected into the tail vein of nude mice. Bioluminescence was measured and quantified from the lungs on day 18, and luminescence was normalized to the vehicle from the specific genotype (control = 6; control + PT2385 = 6; SET1B KO = 6; and SET1B KO + PT2385 = 7). Mean ± SEM. Kruskal–Wallis test). siSET1B, SET1B siRNA.

Depletion of SET1B potentiates HIF2 inhibition in ccRCC. A, WT 786-0 cells were treated with and without 1 µmol/L PT2385 for 24 hours. Endogenous SET1B and HIF2α were immunoprecipitated, and their interaction was evaluated by immunoblotting using the indicated antibodies. Immunoblots are representative of 3 biological replicates. B, 786-0 cells were treated with and without 1 µmol/L PT2385, fractionated into cytoplasmic (Cyto), nucleoplasm (Nuc), and chromatin (Chr) fractions, and SET1B and HIF2α were monitored using immunoblotting. The ratio of SET1B and HIF2α in the chromatin fraction was quantified using ImageJ (n = 3 biologically independent experiments, mean ± SD). C, WT 786-0 cells were transfected with a control and an SET1B siRNA (siSET1B) for 48 hours. Twenty-four hours prior to harvesting, cells were treated with indicated concentrations of PT2385. HIF2α activity was determined by performing qPCR for VEGFA and ANGPTL4 (n = 3 biologically independent experiments, mean ± SD). SET1B mRNA levels was analyzed to validate successful depletion. ChIP-PCR of H3K4me3 (D), RNA Pol II (E), and HIF2α (F) in WT and SET1B KO 786-0 cells treated in the presence and absence of 1 µmol/L PT2385. ChIP-PCR was performed using primers surrounding the VEGFA promoter (n = 3 biological replicates). Graphs show mean ± SD. Two-way ANOVA. G, VEGFA ELISA in control and SET1B-depleted 786-0 cells. Twenty-four hours before collecting supernatants, cells were treated with 1 µmol/L PT2385. Graph is representative of 3 biological replicates. Two-way ANOVA. H, Control and SET1B KO 786-0 cells treated with and without 1 μmol/L PT2385 were embedded in Matrigel, and cellular invasion was measured over indicated time using Incucyte. Graphs are representative for 3 biological replicates and depict the mean ± SD. Two-way ANOVA.

SET1B interacts with the RNA Pol II complex and requires multiple functional domains to coordinate HIF activity. A, Schematic representation of full-length (FL) SET1B and truncation mutants. Key functional domains are highlighted, including the SET domain (associated with methylation activity), RRM, and DPR motif (involved in RNA Pol II binding). B, HEK293T cells were transfected with 4 µg of the indicated expression constructs for 48 hours. Constructs were immunoprecipitated using FLAG-tagged magnetic beads, and their interaction with other members of the SET complex was evaluated by immunoblotting. C, A549 cells stably expressing full-length SET1B or SET1B truncation mutants were transfected with an SET1B siRNA (siSET1B) targeting the 3′-UTR and incubated under 21% or 1% O2 for 24 hours. mRNA expression of HIF target genes (CA9, VEGFA, and ANGPTL4) was assessed using qPCR. Graphs represent the mean ± SD from 3 biological replicates. Statistical analysis was performed using two-way ANOVA. EV; empty vector. D, Coimmunoprecipitation of SET1B and RNA Pol II. SET1B was immunoprecipitated from HeLa cells incubated under 21% or 1% O2 conditions for 6 hours. Samples were analyzed by immunoblotting with the indicated antibodies. Results are representative of 3 biological replicates. Graph depicts densitometric analysis of 3 independent experiments quantifying the interaction between SET1B and RNA Pol II under normoxic (21% O2) and hypoxic (1% O2) conditions. E, ChIP-PCR analysis of SET1B and RNA Pol II in A549 cells exposed to 21% or 1% O2 for 6 hours. Primers targeted the promoter and exon 3 regions of the CA9 and VEGFA genes. Data represent the mean ± SD from 3 biological replicates. Statistical significance was determined using two-way ANOVA. TSS; transcriptional start site. F, HEK293T cells were transfected with 4 µg of the indicated expression constructs for 48 hours. Constructs were immunoprecipitated using FLAG-tagged magnetic beads, and their interaction with other members of the SET complex and RNA Pol II was assessed by immunoblotting. G, ChIP-PCR analysis of FLAG-tagged SET1B and SET1B mutants in A549 cells exposed to 21% or 1% O2 for 6 hours. Primers targeted the promoters of the CA9 and VEGFA genes. Data represent the mean ± SD from 3 biological replicates. Statistical significance was determined using two-way ANOVA.