Citations

Neuroendocrine neoplasms (NENs) represent a heterogeneous group of malignancies ranging from relatively indolent well-differentiated neuroendocrine tumors (NETs) to more aggressive poorly differentiated neuroendocrine carcinomas (NECs). The advent of somatostatin receptor (SSTR)–targeting therapies, particularly radioligand therapy (RLT), has transformed the therapeutic landscape of NETs. Ongoing efforts are aimed at maximizing the therapeutic benefit of RLT and include retreatment and combination strategies as well as novel α-emitter–based radiopharmaceuticals. The increasing use of molecular profiling has led to the identification of recurrent canonical alterations in pancreatic NETs, including in MEN1 , ATRX / DAXX , PI3K/Akt/mTOR, and angiogenic signaling pathways, facilitating the development of effective targeted therapies. However, despite the addition of newer targeted therapies to the therapeutic armamentarium, resistance remains inevitable and highlights the need for improved predictive markers to inform therapy sequencing and novel biomarker-selected therapies. In addition, the development of novel therapeutic strategies including SSTR antagonists, nonpeptide drug conjugates, and novel radiopharmaceutical constructs highlights the potential of biomarker-informed therapies in this space. By contrast, treatment options for NECs remain limited, with modest therapeutic benefit of platinum-based chemotherapy. The identification of delta-like ligand 3 (DLL3) as a therapeutic target in high-grade NENs has led to the development of novel targeted therapies such as T-cell engagers, which have demonstrated promising activity in early phase clinical trials. In addition, other DLL3-targeting agents such as antibody-drug conjugates, trispecific engagers, and cellular therapies remain under investigation. Collectively, these advances underscore the potential of biomarker-informed treatment approaches to personalize treatment decisions and improve long-term outcomes across the NEN spectrum.

Background: Anaplasmosis is an emerging tick-borne infection that typically presents as a non-specific febrile illness, with variable degrees of cytopenias and liver tests abnormalities. Severe complications remain atypical and uncommon. Case Report: We report a case of acute pulmonary embolism (PE) occurring during confirmed anaplasmosis in a 73-year-old male with no traditional thromboembolic risk factors. The patient presented with fever, constitutional symptoms, thrombocytopenia, leukopenia, and abnormal liver tests, raising suspicion for a tick-borne illness. Despite early clinical improvement on doxycycline, persistent tachycardia triggered further evaluation and uncovered an acute PE. Comprehensive workup at admission and repeated 14 months later excluded inherited and acquired thrombophilias, malignancies, autoimmune diseases, and alternative infectious etiologies. The patient was treated with doxycycline 100 mg orally twice daily for 10 days and anticoagulation with unfractionated heparin followed by 6 months of apixaban for a first episode of provoked PE. He attained complete clinical recovery without recurrence of thrombosis at the two-year follow-up. Discussion: Infectious diseases are increasingly recognized as contributors to thrombosis through inflammation-mediated hypercoagulability and endothelial dysfunction. Pulmonary involvement in anaplasmosis typically manifests as pneumonitis, pneumonia or acute respiratory distress syndrome, but thrombotic complications such as PE are exceedingly rare. This case highlights a rare but clinically significant vascular complication of anaplasmosis and underscores the importance of considering thromboembolic events in patients with persistent or unexplained tachycardia. Conclusions: As the incidence of anaplasmosis continues to rise, greater awareness of its potential cardiovascular manifestations is essential. Early recognition and prompt treatment with doxycycline remain critical, while further studies are needed to better define the thrombotic risk associated with this infection.

Abstract Background Cholangiocarcinoma (CCA) is an aggressive hepatobiliary malignancy with marked molecular heterogeneity, limited systemic treatment options, and poor prognosis. Chemoresistance and KRAS mutations remain major therapeutic challenges. Dysregulation of the Hippo pathway, particularly YAP/TAZ hyperactivation, drives CCA progression and resistance. TEAD, the essential transcriptional partner of YAP/TAZ, represents a promising target. IAG933 is a novel oral pan-TEAD inhibitor designed to disrupt YAP/TAZ–TEAD interactions. RMC-6236, a pan-KRAS inhibitor, has also gained attention. Combining TEAD and KRAS inhibition may overcome resistance and improve efficacy in CCA. Methods We evaluated IAG933 in human (HuCCT1, RBE) and murine (SB1, FAC) CCA cell lines. Cells were treated with IAG933 alone or in combination with GemCis or RMC-6236. Cell viability assays were used to determine IC50 values and calculate combination index (CI). TEAD activity was assessed by luciferase reporter and qRT-PCR of YAP/TAZ target genes (CTGF, CYR61, NUAK2). In vivo efficacy was evaluated in syngeneic orthotopic and patient-derived xenograft (PDX) models. Results IAG933 suppressed TEAD-dependent transcription (IC50≈500 nM) and downregulated YAP/TAZ target genes. Combination with GemCis or RMC-6236 produced synergistic effects (CI < 1) in all CCA lines. In vivo, IAG933 monotherapy suppressed tumor growth similarly to GemCis. Dual TEAD and KRAS inhibition achieved marked tumor regression and significantly delayed tumor regrowth after treatment cessation in KRAS-mutant PDX models. Conclusion IAG933 effectively suppresses YAP/TAZ–TEAD signaling and inhibits CCA growth. While the combination with GemCis showed limited additional benefit due to strong single-agent efficacy, synergy with RMC-6236 produced durable antitumor effects, particularly in run-out studies, delaying regrowth in KRAS-mutant models. These findings highlight IAG933 as a promising therapeutic candidate targeting the Hippo–TEAD pathway, with potential benefit in KRAS-mutant CCA.

Importance TMEM106B is a frontotemporal lobar degeneration (FTLD) genetic susceptibility factor, and TMEM106B protein aggregates are a feature of aging and neurodegeneration. Whether TMEM106B protein levels are associated with clinical features is unknown. Objective To investigate the clinical associations of cerebrospinal fluid (CSF) TMEM106B in FTLD. Design, Setting, and Participants This cross-sectional study was conducted in 2 independent frontotemporal dementia (FTD) cohorts (recruitment from April 2009 through July 2023, with analyses from January 2025 through April 2026), with a 2-year follow up. This multicenter clinical study integrated clinical, genetic, biomarker, and neuroimaging data. Individuals were recruited through the University of California, San Francisco (n = 3733), or ALLFTD (n = 2343). Participants with available CSF were included. A discovery cohort (n = 271) included participants with sporadic neuropathology-confirmed FTLD; presymptomatic or symptomatic carriers of pathogenic variants in C9orf72 , GRN , or MAPT ; or controls. An independent validation cohort (n = 383) included participants with clinically diagnosed sporadic FTD, Alzheimer disease (AD), and controls. Exposures CSF samples for TMEM106B quantification with aptamer proteomics (SomaScan version 3.0 [discovery cohort] and SomaScan version 4.1 [validation cohort]). Main Outcomes and Measures Parametric tests compared the primary outcome, CSF TMEM106B, by disease severity, TMEM106B rs1990622 genotype, sex, clinical syndrome, pathological diagnosis, and pathogenic variant and determined associations with brain volume. Results In the discovery (n = 271; 136 women [51%]; median [IQR] age, 59 [38-80] years) and validation (n = 383; 183 women [48%]; median [IQR] age, 64 [50-78] years) cohorts, lower CSF TMEM106B was associated with more severe disease (β, −0.15; 95% CI, −0.24 to −0.04; P = .003), lower frontotemporal brain volumes (β, 0.42; 95% CI, 0.24-0.61; P < .001), and faster clinical progression (β, −2.21; 95% CI, −3.70 to −0.72; P = .001). Associations of TMEM106B with clinical disease severity were independent of those with neurofilament light chain. TMEM106B levels were influenced by TMEM106B rs1990622 genotype, where individuals with the protective G/G genotype had lower levels than the risk A/A genotype. CSF TMEM106B levels did not differentiate between FTLD subtypes or between FTLD and AD. Conclusions and Relevance Per the results of this cross-sectional study, TMEM106B is detectable in CSF and levels reflect disease severity in sporadic and genetic FTLD and AD, but levels are also influenced by the TMEM106B rs1990622 genotype. CSF TMEM106B could support further studies to understand the mechanisms of disease and develop clinical tools in FTLD and other neurodegenerative diseases.

Abstract Objective . Phase gating is a critical technique to mitigate tumor motion during radiotherapy, particularly in spot-scanned particle therapy where internal motion can interfere with dynamic spot scanning patterns and, simultaneously, introducing substantial range uncertainties. However, the current commercial state of the art in real-time phase prediction is challenged by patient-specific breathing variability as well as detection and delivery system latencies. This leads to suboptimal efficiency, mis-timed radiation delivery and requires frequent manual intervention. This study aims to improve phase prediction accuracy using deep learning (DL)-based time series forecasting to enable more accurate dose delivery. Approach . Retrospective breathing waveforms from 69 proton therapy patients, sampled at 30 Hz, were labeled with inspiratory peaks and assigned subjective regularity scores (four levels). DL models with various architectures were trained using waveform amplitude to predict current or future breathing phases. Model performance was evaluated using mean squared error, phase binning accuracy, and timing deviation for radiation on/off events. Bayesian optimization was used for hyperparameter tuning. Results were compared between models and against a commercial algorithm currently in clinical use. Main Results . The curated waveform dataset included 165 242 s for training, 24 057 s for validation, and 30 322 s for testing, with an additional 40 604 s from separate patients for extended validation. The long short-term memory and temporal fusion transformer models significantly outperformed the commercial algorithm, improving phase prediction accuracy by nearly 20% and reducing timing deviations across all regularity levels. Significance . DL-based time series forecasting may substantially improve breathing phase prediction accuracy over current clinically available methods, offering a more precise and reliable approach to phase-gated radiation delivery.

Abstract Background Glioblastoma (GBM) remains a devastating cancer with limited treatment options, largely due to its heterogeneity. While supramaximal resection has recently provided survival benefits, therapeutic profiling of different tumor compartments, particularly its infiltrative edge remains largely unexplored. Methods Here, we leveraged magnetic resonance imaging (MRI)-guided multi-sampling, collecting 2 cores and 2 margins per case, to query GBM heterogeneity. Whole-exome and RNA-seq with drug testing in two patient-derived 3D models were used to reveal similarities and differences in genomic and transcriptomic makeups, cellular compositions, and drug responses across cores and margins. Bioinformatics interrogations further identified response biomarkers. Results Mutation analysis showed that oncogenes exhibited a higher degree of spatial heterogeneity than tumor suppressor genes, regardless of MRI status. While the mesenchymal transcriptional subtype with extracellular matrix remodeling, stress response, and immune programs were preferentially enriched in enhancing cores, proneural tumors with neurological processes favored non-enhancing margins. Using a 15-drug GBM-targeted panel, ERK (ulixertinib) and PI3K pathway (paxalisib, CC-115) inhibitors showed preferential efficacy in enhancing cores and non-enhancing margins, respectively. The anti-apoptosis, pan-Bcl2 agent navitoclax and the epigenetic drug trotabresib represented the most effective, tumor-wide monotherapies. Importantly, drug combinations generally outperformed single agents across all regions. Conclusions This work demonstrates the regional heterogeneity of therapeutic vulnerabilities in GBM ex vivo, showing various drugs with tumor-wide or MRI-enhancement informed activity. These findings offer preclinical bases of numerous monotherapies and drug combinations for future clinical trial design.