Citations

Abstract Purpose: Selinexor is a first-in-class, central nervous system (CNS)–penetrant, oral inhibitor of exportin 1 (XPO1), the main nuclear exporter of many key tumor suppressors. We report a phase I trial of selinexor in children and adolescents with recurrent CNS and solid tumors (NCT02323880). Patients and Methods: A rolling six design was used to evaluate the maximum tolerated dose (MTD) and first dose pharmacokinetics of selinexor administered once (35–45 mg/m2) or twice (20–35 mg/m2) weekly during a 28-day cycle (part A). Ten additional patients with high-grade glioma (HGG) were treated at the MTD administered once weekly (part B). Results: In part A, 49 patients were enrolled. Continuous twice weekly dosing was limited by extended hematologic toxicity. The MTD on a twice weekly schedule for 3 weeks on/1 week off (twice weekly 3/1) was 20 mg/m2/dose. Dose-limiting toxicities (DLTs) on this schedule included fatigue, acute reversible neurologic changes, neutropenia, thrombocytopenia, and aspartate aminotransferase/alanine aminotransferase increase. On a continuous once weekly schedule, the MTD was 35 mg/m2/dose; DLTs included seizure and thrombocytopenia. In part B (HGG expansion), there were no additional DLTs observed. Non-DLTs included lymphopenia, leukopenia, neutropenia, thrombocytopenia, anorexia, fatigue, hypophosphatemia, nausea, and vomiting. There were no objective responses. The median number of cycles received was 1 (range, 1–9); eight of 59 patients (13.5%) received 5 to 9 cycles, five of whom had HGG. Conclusions: Selinexor-related toxicities were primarily hematologic and neurologic, requiring dose or dose-frequency reduction. The MTD and recommended initial phase II dose of selinexor in children and adolescents with recurrent solid and CNS tumors is 35 mg/m2/dose once weekly.

Abstract Background Despite advances in clinical microbiology, the diagnosis of invasive fungal infections remains challenging. Giant magnetoresistance (GMR) is a novel technology that enables the detection of trace amounts of cell-free DNA (cfDNA). We evaluated a high-multiplex molecular diagnostic assay coupled with GMR-enabled lab-on-a-chip technology that can detect 18 different fungal species. Methods Analytical performance was evaluated in spiked plasma samples. After amplification, cfDNA was digested. Residual single-stranded DNA was flowed over a GMR sensor that was surface-coated with probes specific to different fungal species. After hybridization, magnetic beads bound to the probe complexes produced a GMR signal that was detected by the sensors. Clinical performance was determined using residual serum samples collected before the initiation of antifungal treatment from 20 patients with infection. Results The limit of detection of the assay ranged from 5 to 50 copies per polymerase chain reaction (PCR) reaction. Nonspecific signals were not observed in the spiked samples. Fungal cfDNA was detected in 80% of patients with invasive candidiasis (3/4 with candidemia, 5/6 with invasive candidiasis without candidemia), all 3 cases of invasive pulmonary aspergillosis, and all 3 cases of disseminated histoplasmosis. cfDNA was not detected in 2 patients with cryptococcosis (both had negative blood cultures) and 2 patients with Pneumocystis pneumonia. Conclusions We developed a novel GMR-enabled multiplex PCR assay detecting fungal pathogens that have been prioritized for public health action. Clinical sensitivity was highest in cases of presumed angioinvasion and dissemination. This technology has the potential for use in the clinical microbiology laboratory setting.

Abstract Purpose: Digital proteomic profiling was performed to identify spatial context in relationship to patient response and survival after anti–PD-1 therapy in metastatic colorectal cancer. Experimental Design: Primary colorectal cancers with deficient mismatch repair from patients treated with anti–PD-1 antibodies were analyzed (N = 30) using digital spatial profiling (GeoMx nCounter). At the invasive margin, 71 proteins were profiled in 10 regions of interest/slide that were segmented into 3 compartments labeled with pan-cytokeratin (epithelia), CD45 (stromal cells), and SYTO13 (nuclei). In an independent cohort (n = 13), digital spatial profiling data and single-cell transcriptomic data were analyzed. Differential protein abundance, after Benjamini–Hochberg correction, was examined by clinical response and progression-free survival (PFS) using multivariable Cox regression. Results: Protein abundance varied significantly between epithelial and stromal compartments. Nonresponders to anti–PD-1 showed higher fibronectin and smooth muscle actin abundance in the epithelial compartment that was associated with significantly shorter PFS (adjusted HR: 6.49 and 4.52, respectively; P < 0.05). In CD45+ stroma, increased expression of proteins related to T cells (CD3 and CD4), NK cells (CD56), antigen presentation (CD40), immune activation (CD27, ICOS), and apoptosis (GZMA) were found in responders (vs nonresponders) to anti–PD-1; each marker was significantly associated with longer patient PFS (0.02 < adjusted HR < 0.17; P < 0.05). In a separate cohort, consistent results by compartment were found for fibronectin and CD56. Gene expression data revealed that fibronectin and smooth muscle actin were primarily derived from cancer-associated fibroblasts. Conclusions: Spatially resolved protein profiles within microenvironments of deficient mismatch repair colorectal cancers can influence patient response and survival after anti–PD-1, highlighting their potential clinical significance.

140 Background: In the phase II EXTEND iADT omPC basket, MDT+iADT improved progression-free survival (PFS) vs iADT. Here we present the primary results of the EXTEND cADT omPC basket. We further report a pre-specified combined analysis with updated results from the iADT basket and examine the effects of MDT on immunity. Methods: Patients with 1 to 5 omPC metastases were randomized 1:1 to MDT+cADT vs cADT (NCT03599765). MDT consisted of definitive local therapy. cADT consisted of ADT +/- second-generation anti-androgens. The primary endpoint was per-protocol PFS, defined by biochemical criteria (Prostate Cancer Working Group 3), radiologic measures (RECIST v1.1), clinical progression, or death. 87 patients were needed to show superiority at a one-sided P of 0.10 by log-rank test. CDR3 regions in rearranged T cell receptor (TCR) β-chains from pre- and post-enrollment peripheral blood were sequenced with immunoSEQ (Adaptive Biotech). TCR repertoire modulation was defined as having TCR expansion plus contraction using a false-discovery-corrected betabinomial model. TCR sequencing from the ORIOLE trial (NCT02680587) was assessed for external validation. Results: From 2018 to 2022, 87 randomized patients were treated per protocol (MDT+cADT: 45; cADT: 42). 39% had castrate resistant omPC. MDT was definitive radiotherapy in all cases. With median follow-up of 31 mo, median PFS was 47 mo after MDT+cADT vs 22 mo after cADT (HR 0.50; 95% CI 0.23 to 1.08; one-sided P = 0.036). In the combined analysis (N=174) with median follow-up of 42 mo, MDT+ADT improved PFS (HR 0.45; 95% CI 0.30 to 0.69; P < 0.001), radiologic PFS (HR 0.63; 95% CI 0.40 to 0.97; P = 0.038), and castration-resistance free-survival (HR 0.40; 95% CI 0.19 to 0.82; P = 0.013). MDT+ADT had higher odds of TCR repertoire modulation vs ADT (55% vs 15%, P < 0.001). This finding was validated in the ORIOLE trial (MDT: 57% vs observation: 19%, P = 0.03). Among the subset of patients with extreme responses, random forest modeling of 37 clinical/immune variables identified TCR repertoire modulation as the variable with highest importance; further, MDT+ADT induced TCR repertoire modulation in all patients with favorable responses (i.e. PFS > 4 years) and none with unfavorable responses (i.e. PFS < 1 year). Among all patients randomized to MDT+ADT, TCR repertoire modulation was associated with longer PFS (HR 0.21; 95% CI 0.06 to 0.76; P = 0.02). Conclusions: MDT+cADT met the PFS primary endpoint of the phase II EXTEND trial, warranting phase III testing. From the combined analysis, MDT+ADT may also improve longer term outcomes including radiologic PFS and castration-resistance-free survival. Improved outcomes may result from MDT-induced immunomodulation, with implications for future trial design. Clinical trial information: NCT03599765 .

425 Background: Prostate cancer (PC) ranks among the most prevalent cancers in men, with incidence rising due to factors like aging populations and enhanced screening techniques. Effective data extraction from clinical records is crucial for advancing research and improving patient care; however, traditional manual methods can be time-consuming and susceptible to mistakes. This study seeks to evaluate RadOnc-GPT against human annotation for extracting essential clinical information from prostate cancer clinical records. Methods: RadOnc-GPT is a retrieval augmented generation (RAG)-based chatbot with access to a variety of patient data including treatment details, radiology reports, and clinical notes. RadOnc-GPT uses Open AI’s gpt-4o model. Patients who received curative intent radiotherapy as initial treatment for PC in our institution between 2014 and 2023 were randomly selected for evaluation. Relevant Clinical factors were extracted by a human expert annotator on our on-site RedCap database. The extraction of the same variables was performed using RadOnc-GPT. A comparison between the ground truth (human annotation) and RadOnc-GPT, to evaluate the performance of the AI system, was carried out including accuracy, recall and F1 score. Results: A total of 382 PC patients were included in the cohort for data extraction. The clinical variables extracted were the treatment intent, NCCN risk category, T and N stage, Gleason score, radiation volume, and Androgen Deprivation therapy (ADT) use. The overall performance of RadOnc-GPT was excellent, with the highest accuracy achieved for treatment intent (99.7%), Gleason score (98.4%), and Treatment Volume (90.1-99.5%). Conclusions: RadOnc-GPT performed excellent at extracting relevant clinical details from the electronic medical record and radiation oncology information systems with dramatic reduction in time and cost compared with manual review. LLMs could be highly useful for large-scale data extraction in PC research, offering a promising solution for automating the accurate data extraction process. Correct (n) Total (n) Accuracy Recall F1 score RT with curative intent 381 382 99.7 99.9 99.9 Prostate Cancer Risk Category 345 382 90.3 90.4 95.1 Primary tumor staging (T) at diagnosis 368 382 96.3 96.3 97.9 Regional nodal status (N) at diagnosis 352 382 92.1 92.2 95.9 Gleason Score Primary Secondary Total 376372376 382382382 98.497.498.4 98.597.498.5 99.298.799.2 Treated Areas Prostate Pelvic Nodes Para-Aortic Nodes Distant Site 380344378372 382382382382 99.590.19997.4 99.490.199.197.4 99.79599.598.7 ADT Use with RT 365 382 95.5 95.7 97.8

ABSTRACTBackgroundContrast‐enhanced magnetic resonance neurography (ceMRN) can enhance brachial plexus visualization and quality of imaging. However, the interval between contrast injection and scanning that provides the highest‐quality images is not known.MethodsFifteen patients underwent brachial plexus imaging using the 3D T2‐NerveView sequence with a scanning duration of 5 min. A consecutive six‐phase scan was initiated immediately at the start of contrast agent injection. Subsequently, all patients' images were classified into six groups according to the phases: group A (phase 1, delay 0 min), group B (phase 2, delay 5 min), group C (phase 3, delay 10 min), group D (phase 4, delay 15 min), group E (phase 5, delay 20 min), and group F (phase 6, delay 25 min). The image quality in each group was assessed based on nerve signal (signalnerve), muscle signal (signalmuscle), lymph node signal (signallymph node), background noise (BN), signal‐to‐noise ratio (SNR), contrast‐to‐noise ratio (CNR), and subjective score.ResultsSignalnerve, signalmuscle, BN, and SNR did not significantly differ among the six groups (p > 0.05). However, significant differences (p < 0.05) were observed in signallymph node (F = 16.067), CNR (F = 9.495), and subjective score (χ2 = 23.586). As the scanning delay increased, signallymph node intensity gradually increased whereas the CNR gradually decreased. The subjective score was significantly higher in groups B (4.83 ± 0.24), C (4.90 ± 0.21), D (4.87 ± 0.30), E (4.83 ± 0.31), and F (4.83 ± 0.31) than in group A (4.47 ± 0.30).ConclusionWe recommend performing brachial plexus ceMRN 5 min after contrast injection. With this delay, the brachial plexus can be visualized optimally with minimal interference from background signals.

Abstract The prevalence of steatotic liver disease (SLD) is rising globally, presenting a significant public health challenge. While non-contrast computed tomography (CT) scans hold promise for the opportunistic detection of SLD, their full potential has not been systematically explored. Clinical indicators, such as serum data, are crucial for monitoring the progression of SLD. We introduce a novel Multimodal AI for Opportunistic Steatotic Liver Disease Screening (MAOSS), which integrates demographic data, serum tests, conventional CT biomarkers, and deep learning-derived CT image features to enhance model performance and explainability. MAOSS employs an innovative learning strategy, trained on a large-scale dataset (n = 1,783) encompassing both histopathologically-confirmed SLD and radiologically-reported steatosis cases. The model underwent extensive retrospective validation using steatosis grades derived from both histology and MRI-PDFF across internal and external datasets (n = 913), as well as real-world patient data (n = 18,504). It accurately detected mild to severe steatosis (≥ S1) with AUCs ranging from 0.903 to 0.929. Notably, MAOSS significantly improved the overall AUC for radiologists (n = 11) from 0.709 to 0.798 (p < 0.001). Furthermore, MAOSS was applied to optimize the standard clinical pathway for a simulated primary risk screening of SLD patients (n = 1,192), resulting in the identification of 31% more patients at risk of steatohepatitis and liver fibrosis progression, highlighting its potential to enhance SLD detection and management.