Citations

ABSTRACT Glioblastoma (GBM) is universally lethal despite decades of research to find effective treatments. This highlights the need to identify druggable targets essential for sustaining the malignant phenotype but dispensable for normal tissue. We propose that the enzyme α-tubulin acetyl transferase ( ATAT1 ) meets these criteria. ATAT1 acetylates α-tubulin at lysine 40, which increases microtubule stability and promotes microtubule-based transport. While ATAT1 knockout mice have only a very mild phenotype, ATAT1 suppression in GBM has multiple therapeutic effects by reducing tumor invasion, proliferation, and therapeutic resistance. These translate not only into improved survival with ATAT1 targeting by itself, but also into synergy when ATAT1 deletion is combined with FDA approved therapies. This study strongly supports our conclusion that ATAT1 is a promising therapeutic target in GBM.

Abstract Multiple myeloma (MM) is a heterogenous cancer that remains mostly incurable. A unifying feature of MM cells is a highly interconnected network of transcription factors and co-factors that coordinate the activity of super-enhancers to enforce myeloma cell identity. Targeting this network offers a promising avenue for therapeutic intervention across genetically diverse myeloma sub-types. Using integrated molecular and functional genomic approaches we identified Menin as a key driver of oncogenic gene expression in MM cells. Menin and its co-factor KMT2A bind at super-enhancers and maintain expression of essential myeloma genes, including IRF4. We demonstrate that Menin inhibitors, which have recently been approved for treatment of acute myeloid leukaemia, are highly active in myeloma cell lines and in vivo models. Combining Menin inhibitors with other super-enhancer targeting therapies such EP300/CREBBP inhibitors or immunomodulatory drugs (IMiDs) overcomes epigenetic plasticity in cells resistant to single agent treatment.

Artificial intelligence (AI) is now applied across oncology, including imaging, pathology, therapy selection, toxicity assessment, and survival modeling, and large language models (LLMs) have been adopted particularly quickly. Reported physician use of AI roughly doubled between 2023 and 2026. The frameworks used to evaluate these tools have not advanced at the same rate. Many are available, but each was designed for a single stage of the AI lifecycle, and none directly answers the question most relevant to a treating clinician: whether a given tool is appropriate for the individual patient under care. We reviewed the frameworks in current use, including TRIPOD+AI, PROBAST+AI, CLAIM, SPIRIT-AI, CONSORT-AI, DECIDE-AI, MINIMAR, and CREMLS, together with the oncology-specific ESMO EBAI and the newer LLM-specific guidance (TRIPOD-LLM, MI-CLEAR-LLM, CHART, and ESMO ELCAP). Each addresses part of the evaluation problem, but none is sufficient on its own for oncology, where the standard of care changes rapidly, assays drift, biomarker-defined subgroups are small, and a model validated in one period may perform poorly in the next. LLMs introduce additional challenges, including sensitivity to prompting, undisclosed vendor updates, behavioral drift, and hallucination rates approaching 50% on clinical quality-assurance tasks. The predictive-model frameworks were not designed to capture these failure modes. The central argument of this review is that the frameworks the field requires already exist; what is missing is their mandatory adoption. We propose that journals and regulators move from recommending these frameworks to requiring their use, and we outline a cancer-aware evaluation pathway together with the specific responsibilities of authors, reviewers, journals, and regulators in implementing it.

Abstract Spatial transcriptomics has been widely applied to study the spatial distribution of cell types, cell states, and specific gene expression in tissue samples. However, we show that there is a prevalent transcript leakage problem in spatial transcriptomics data, where transcripts expressed by a cell diffuse to its neighborhood and are recurrently detected in the nearby cells. By analyzing published data sets, we show that this problem is general across data produced from different tissues and different species using different imaging-based and sequencing-based spatial transcriptomics platforms. It affects both upstream tasks such as expression quantification as well as downstream tasks such as cell-type annotation and detection of spatially-dependent gene expression. To tackle the transcript leakage problem, we propose a reference-free Bayesian model-based method, DeLeakage, which cleans up the data much more effectively than existing denoising methods. DeLeakage also improves cell-type annotation and avoids false detection of spatially dependent expression.

Objective: To evaluate the institutional learning curve of robotic liver resection (RLR), its association with surgical complexity and outcomes in an international multicenter cohort. Summary of Background Data: RLR is increasingly adopted worldwide, but the dynamics of the learning process and its impact on surgical outcomes remain poorly defined. Methods: This international, multicenter, retrospective cohort study included consecutive patients who underwent RLR between 06/2013 and 12/2024 across 22 expert centers. Based on the first 150 cases at each center, three phases were used to define the learning curve: operative time for competency, major complications for proficiency, and textbook outcome for mastery. Risk-adjusted generalized additive models were used to assess the learning process. Benchmark performance was compared to international reference values. Results: Among 2,331 patients, the most common indications were hepatocellular carcinoma (36%), benign lesions (23%) and colorectal liver metastases (21%). Operative time decreased after achieving competency (case #62), from 240 to 220 minutes ( P <0.001). Major morbidity reached a plateau during the proficiency phase (cases #63–138; 9% vs. 11%, P =0.144), while progression to mastery (cases #139–150) was associated with a higher rate of textbook outcome (76% vs. 87%, P =0.021). In contrast, conversion (5.1% vs. 4.9% vs. 2%), bile leak (4.0% vs. 5.3% vs. 3.8%), and 90-day mortality (0.7% vs. 0.9% vs. 0.9%) remained low and stable across all learning phases. Importantly, benchmark criteria for operative time, hospital stay, and textbook outcome were met across all complexity groups, including during the early learning phase. Conclusions: Robotic liver surgery shows progressive outcome improvement with early achievement of benchmark-level results and stable performance across increasing complexity. These findings indicate that, in experienced centers, RLR can be safely implemented and integrated into clinical practice, supporting its key role in modern hepatobiliary surgery.

Renal water reabsorption is classically regulated by vasopressin V2 receptor (V2R) signaling through cyclic AMP and protein kinase A, driving apical accumulation of aquaporin-2 (AQP2). However, collecting duct water handling is also modulated by vasopressin-independent mechanisms. Here, we examined intracellular soluble urate as a vasopressin-independent regulator of AQP2 trafficking. Intracellular urate accumulation in collecting duct cells was mediated by enhanced apical urate uptake via GLUT9b and reduced apical urate efflux through ABCG2, triggering phosphodiesterase-4 activation, reduced cAMP, and downstream AMP-activated protein kinase (AMPK) activation. The resulting AQP2 accumulation at the apical membrane was independent of V2R signaling, required ongoing endocytosis, and was associated with features of postendocytic apical trafficking of internalized AQP2. In vivo ABCG2 inhibition with probenecid increased apical AQP2 abundance and markedly attenuated tolvaptan-induced polyuria in both wild-type and Pkd1 RC/RC autosomal dominant polycystic kidney disease (ADPKD) mice in a uricase-independent manner while preserving tolvaptan’s ADPKD-modifying efficacy. In a phase II trial with tolvaptan-treated patients with ADPKD, probenecid reduced urine volume and nocturia frequency. Together, these findings support a vasopressin-independent urate/AMPK/AQP2 pathway that regulates renal water handling and, in a preclinical ADPKD model, can uncouple cyst growth attenuation from the dose-limiting aquaretic effects of V2R antagonism.

PURPOSE In large B-cell lymphoma (LBCL), use of high-dose methotrexate (HD-MTX) to prevent CNS relapse (so-called CNS prophylaxis) remains controversial. International guidelines continue to recommend HD-MTX in patients deemed ultra high risk (UHR) because of a lack of robust data specific to these subgroups. This study was designed to examine the impact of HD-MTX specifically in UHR patients. METHODS Data from two previous retrospective analyses were combined to produce a cohort of UHR patients (≥1 of the following criteria: CNS international prognostic index score 5-6; testicular, renal/adrenal, or breast involvement; ≥3 extranodal sites), treated with or without HD-MTX. The primary outcome was CNS relapse rate (isolated or concurrent with systemic relapse) measured from diagnosis with additional landmark analysis of all responding patients with no progression event at 6 months. RESULTS Analyses were performed on 1,923 patients meeting UHR criteria. No significant difference in 3-year CNS relapse rate was observed between no HD-MTX (n = 1,051) versus HD-MTX patients (n = 872), including in multivariable analyses adjusting for baseline characteristics (3-year rate, 9.3% v 8.1%; adjusted hazard ratio [HR], 1.13 [95% CI, 0.82 to 1.57]). Analyses restricted to isolated CNS relapse also confirmed no difference (5.9% v 5.7%; adjusted HR, 1.03 [95% CI, 0.69 to 1.53]). In the landmark analysis (no HD-MTX n = 782, HD-MTX n = 773), no difference in 3-year CNS relapse was observed (6.7% v 6.6%, adjusted HR, 0.95 [95% CI, 0.62 to 1.44]). CONCLUSION To our knowledge, this is the largest international comparative data set of patients with LBCL with UHR features showing no significant reduction in CNS relapse with HD-MTX in all UHR or in any individual subgroup. Despite inherent limitations of retrospective analyses, the data strongly support previous studies in suggesting HD-MTX prophylaxis has no meaningful benefit for most patients.

ABSTRACT Background and Objectives Converging evidence hints at neurodevelopmental effects in genetic frontotemporal degeneration (FTD). In cross-sectional studies, for some genes, young adult FTD variant carriers show differences in brain volumes and cognition compared to familial non-carriers. However, longitudinal trajectories may more sensitively capture FTD-related neurodevelopmental vs. neurodegenerative changes than cross-sectional approaches. This study examined longitudinal trajectories of brain volumes, executive function, and plasma biomarkers in young adult carriers compared to familial non-carriers, as measures of neurodevelopmental and neurodegenerative outcomes of FTD-causing variants. Methods This longitudinal cohort study comprised participants, aged 18-30 years, from the FTD Prevention Initiative across Europe, Canada, and the USA. Genetic groups included C9orf72 (47%), MAPT (30%), and GRN (23%). Linear mixed-effects models were computed to assess longitudinal outcomes across age between groups, controlling for sex, scanner (for brain volumes), and education (for executive function); random effects accounted for between-subject variability nested within family membership. Results Variant carriers ( n =147) and familial non-carriers ( n =113) did not differ in age (mean±SD, 25.9±3.2 years), sex (53% female), or number of visits (2.1±1.7). Young adult C9orf72 repeat expansion carriers exhibited smaller thalamic volumes than non-carriers at the reference age of 26 years ( b =-982.8mm 3 , SE=317.0, p= 0.0046, f 2 =0.32), with relatively stable trajectories across ages 18-30 (i.e., no change over time). Trajectories of rostral anterior cingulate volumes differed in C9orf72 carriers and non-carriers across age, where carriers showed relatively stable trajectories and non-carriers showed age-appropriate declines ( b =64.4mm 3 , SE=29.9, p= 0.035, f 2 =0.07). For MAPT and GRN , there were little to no differences in total brain, cortical, or subcortical volumes between groups and over time. No longitudinal differences were observed between carriers and non-carriers in executive function, or plasma NfL or GFAP for any genetic group. Discussion C9orf72 repeat expansions were linked to smaller average thalamic volumes and stable trajectories between ages 18 to 30, supporting potential neurodevelopmental origins. The modest evidence supporting an absence of difference in neurodegenerative biomarkers and executive function suggests minimal early neurodegeneration and functional preservation in young adulthood.