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The landscape of prostate cancer care has rapidly evolved. We have transitioned from the use of conventional imaging, radical surgeries, and single-agent androgen deprivation therapy to an era of advanced imaging, precision diagnostics, genomics, and targeted treatment options. Concurrently, the emergence of large language models (LLMs) has dramatically transformed the paradigm for artificial intelligence (AI). This convergence of advancements in prostate cancer management and AI provides a compelling rationale to comprehensively review the current state of AI applications in prostate cancer care. Here, we review the advancements in AI-driven applications across the continuum of the journey of a patient with prostate cancer from early interception to survivorship care. We subsequently discuss the role of AI in prostate cancer drug discovery, clinical trials, and clinical practice guidelines. In the localized disease setting, deep learning models demonstrated impressive performance in detecting and grading prostate cancer using imaging and pathology data. For biochemically recurrent diseases, machine learning approaches are being tested for improved risk stratification and treatment decisions. In advanced prostate cancer, deep learning can potentially improve prognostication and assist in clinical decision making. Furthermore, LLMs are poised to revolutionize information summarization and extraction, clinical trial design and operations, drug development, evidence synthesis, and clinical practice guidelines. Synergistic integration of multimodal data integration and human-AI integration are emerging as a key strategy to unlock the full potential of AI in prostate cancer care.

Background. Chronic systemic inflammation is associated with mortality in patients with chronic kidney disease, cardiovascular disease, and diabetes. The goal of this study was to examine the relationship between pretransplant inflammatory biomarkers (growth differentiation factor-15 [GDF-15], interleukin-6 [IL-6], soluble tumor necrosis factor receptor-1, monokine induced by gamma interferon/chemokine [C-X-C motif] ligand 9 [MIG/CXCL9], monocyte chemoattractant protein-1, soluble FAS, tumor necrosis factor-α, interleukin-15, and interleukin-1β) and death with function (DWF) after kidney transplantation (KT). Methods. We retrospectively measured inflammatory biomarker levels in serum collected up to 1 y before KT (time from blood draw to KT was 130 ± 110 d) in recipients transplanted between January 2006 and December 2018. Kaplan-Meier estimation, Cox regression, and Gradient Boosting Machine modeling were used to examine the relationship between inflammatory biomarkers and DWF. Results. Our cohort consisted of 1595 KT recipients, of whom 62.9% were male and 83.2% were non-Hispanic White. Over a mean follow-up of 7.4 ± 3.9 y, 21.2% of patients (n = 338) experienced DWF. Patients with the highest quartile levels of GDF-15 (>4766 pg/mL), IL-6 (>6.11 pg/mL), and MIG/CXCL9 (> 5835 pg/mL) had increased rates of DWF, and each predicted mortality independently of the others. When adjusted for clinical factors (age, diabetes, etc), the highest quartile levels of GDF-15 and IL-6 remained independently associated with DWF. Adding inflammatory markers to a clinical Cox model improved the C-statistic for DWF from 0.727 to 0.762 using a Gradient Boosting Machine modeling approach. Conclusions. These findings suggest that pre-KT serum concentrations of GDF-15, IL-6, and MIG/CXCL9 may help to risk stratify and manage patients undergoing KT and suggests that chronic inflammation may play a role in mortality in KT recipients.

AbstractBackgroundIntensity Modulated Proton Therapy (IMPT) is a sophisticated radiation treatment allowing for precise dose distributions. However, conventional spot selection strategies in IMPT face challenges, particularly with minimum monitor unit (MU) constraints, affecting planning quality and efficiency.PurposeThis study introduces an innovative Two‐Stage Mixed Integer Linear Programming (MILP) method to optimize spot intensity in IMPT with Lower Bound (LB) constraints. This method seeks to improve treatment planning efficiency and precision, overcoming limitations of existing strategies.MethodsOur approach evaluates prevalent IMPT spot selection strategies, identifying their limitations, especially concerning MU constraints. We integrated LB constraints into a MILP framework, using a novel three‐phase strategy for spot pool selection, to enhance performance over traditional heuristic methods and L1 + L∞ strategies. The method's efficacy was tested in eight study cases, using Dose‐Volume Histograms (DVHs), spot selection efficiency, and computation time analysis for benchmarking against established methods.ResultsThe proposed method showed superior performance in DVH quality, adhering to LB constraints while maintaining high‐quality treatment plans. It outperformed existing techniques in spot selection, reducing unnecessary spots and balancing precision with efficiency. Cases studies confirmed the method's effectiveness in producing clinically feasible plans with enhanced dose distributions and reduced hotspots, especially in cases with elevated LB constraints.ConclusionsOur Two‐Stage MILP strategy signifies a significant advancement in IMPT treatment planning. By incorporating LB constraints directly into the optimization process, it achieves superior plan quality and deliverability compared to current methods. This approach is particularly advantageous in clinical settings requiring minimum spot number and high MU LB constraints, offering the potential for improved patient outcomes through more precise and efficient radiation therapy plans.

AbstractBackgroundThe impact of atrial fibrillation (AF) among patients with amyloidosis on in‐hospital outcomes is not well‐established. We aimed to examine in‐hospital outcomes among patients admitted with a primary diagnosis of AF with and without amyloidosis.Methods and ResultsWe queried the Nationwide Readmissions Database to compare the in‐hospital outcomes among AF patients with and without amyloidosis. Our study demonstrated that in‐hospital all‐cause mortality, adverse events, and 30‐day readmission were comparable between the two groups.ConclusionsPatients with AF and concurrent amyloidosis did not have worse in‐hospital outcomes than those with AF alone.

IntroductionAlzheimer's disease (AD) is a neurodegenerative disease with neurogenic fiber tangles caused by amyloid-β protein plaques and tau protein hyperphosphorylation as the pathological manifestations. This study was based on multi-omics to investigate the mechanisms and immune characterization of AD.Material and methodsBased on bulk RNA-seq (GSE122063 and GSE97760), we screened potential biomarkers for AD by differential expression analysis and machine learning algorithms. Then, we elaborated the expression characteristics and immune functions of the above biomarkers by scRNA-seq (single-cell RNA sequencing) data analysis (GSM4996463 and GSM4996462) and immune infiltration analysis.ResultsFive biomarkers (RBM3, GOLGA8A, ALS2, FSD2, and LOC100287628) were identified using machine learning algorithms. Single-cell analysis revealed distinct expression patterns of these biomarkers in astrocytes from AD samples compared to normal samples. Additionally, three key biomarkers were selected based on interaction networks, and the diagnostic models indicated high diagnostic efficacy for these biomarkers. Based on immune infiltration and correlation analyses, RBM3, GOLGA8A, and ALS2 were all highly correlated with CD8 T cell content in the immune microenvironment of AD.ConclusionsThe biomarkers identified in this study demonstrate significant diagnostic potential for AD. Notably, the downregulation of RBM3 in astrocytes and the decreased presence of CD8 T cells infiltrating brain tissue are potential risk factors for AD.

11023 Background: Randomized clinical trials (RCTs) in cancer typically compare experimental to control arm regimens. The choice of an appropriate control (ctrl) arm can have a major impact on the expected success of an RCT. The frequency with which cancer RCTs use control arms based on established dosing and scheduling protocols has not been described. Methods: The HemOnc knowledgebase (KB) was used to identify systemic anti-cancer therapy (SACT) regimen variants, defined as regimens with identical components that differ in dosing, scheduling, and/or route. Non-cancer, nonrandomized, and non-SACT studies were excluded. Study publication year was used to define standard variants as those evaluated in the experimental arm of a positive phase 3 RCT >1 year prior to publication as a control arm, regardless of cancer type or context of treatment. Study-variant dyads were evaluated to determine whether the variant was standard. Success rates of RCTs with standard vs non-standard control arms were evaluated with Fisher’s exact test. Results: 5221 studies were associated with ≥1 named variant in the HemOnc KB, as of 2024-02-06. After exclusions, there were 3511 study-variant dyads (2386 studies; 1714 variants). The 9 most common regimens are shown in the Table. The median (IQR) number of variants per regimen was 2 (1-3); carboplatin & paclitaxel (CP) had the most variants (n=33). Across all control arm study-variant dyads, 2228/3492 (64%) utilized non-standard variants. For example, 60/97 studies (62%) of docetaxel as control used the 75 mg/m2 q3wk variant after it was established in 2000, whereas n=27 others used 19 non-standard variants. Trials that used a standard control arm had a numerically higher success rate, 45% vs 42% (OR 1.10, 95% CI 0.92-1.32). Conclusions: Non-standard regimen variants are frequently used in cancer RCTs. Reasons for this could include toxicity, patient convenience, or emerging data from smaller studies that establish comparable efficacy or improved toxicity to standard variants. However, the a priori efficacy of non-standard control arms is less rigorously established, and trials with standard control arms might be more successful. Future directions include quantifying the granular differences between standard and non-standard variants and investigating whether certain types of non-standard variation (e.g. fewer cycles, lower doses) associate with trial success rates. [Table: see text]

AbstractDNA damage plays a significant role in the tumorigenesis and progression of the disease. Abnormal DNA repair affects the therapy and prognosis of cancer. In this study, it is demonstrated that the deubiquitinase USP25 promotes non‐homologous end joining (NHEJ), which in turn contributes to chemoresistance in cancer. It is shown that USP25 deubiquitinates SHLD2 at the K64 site, which enhances its binding with REV7 and promotes NHEJ. Furthermore, USP25 deficiency impairs NHEJ‐mediated DNA repair and reduces class switch recombination (CSR) in USP25‐deficient mice. USP25 is overexpressed in a subset of colon cancers. Depletion of USP25 sensitizes colon cancer cells to IR, 5‐Fu, and cisplatin. TRIM25 is also identified, an E3 ligase, as the enzyme responsible for degrading USP25. Downregulation of TRIM25 leads to an increase in USP25 levels, which in turn induces chemoresistance in colon cancer cells. Finally, a peptide that disrupts the USP25‐SHLD2 interaction is successfully identified, impairing NHEJ and increasing sensitivity to chemotherapy in PDX model. Overall, these findings reveal USP25 as a critical effector of SHLD2 in regulating the NHEJ repair pathway and suggest its potential as a therapeutic target for cancer therapy.

Abstract Background the electrophysiological substrate underpinning ventricular tachycardia (VT) in cardiac amyloidosis (CA) remains elusive, and outcomes of catheter ablation in this peculiar population are currently unknown. Purpose we sought to describe the electrophysiological substrate and clinical outcomes of VT ablation in a cohort of patients with CA. Methods we included 19 consecutive patients (mean age, 69±10 years; male sex, 89%) with CA (ATTR, n=13; AL, n=6) undergoing catheter ablation for VT/ventricular fibrillation (VF) between 2013 and 2023 in a retrospective, observational, international study, involving 7 referral European and North American electrophysiology units. The primary efficacy outcome was recurrent VT/VF during follow-up, while the primary safety outcome included major procedure-related adverse events. Results the indication for ablation was drug-refractory VT in 16 patients (84%), and PVC-initiated polymorphic VT/VF in 3 (16%). Catheter ablation was performed using endocardial (n=14, 74%) or endo-epicardial approaches (n=5, 26%). Complete endocardial electroanatomical voltage maps of the left and right ventricles were obtained in 14 (74%) and 6 (32%) patients, respectively. Each patient had evidence of low-voltage areas, most commonly involving the interventricular septum (n=12); late potentials were recorded in 13 patients (68%). A median of 1 (1-2) VTs were inducible per patient; in 10 subjects (43% of mappable VTs), activation mapping was consistent with septal VT origin. Complete procedural success was obtained in 13 patients (68%), at the expense of 4 (21%) major procedure-related adverse events. After a median follow-up of 36 (18-54) months, sustained VT/VF recurrence was observed in 9 patients (47%); survival free from VT/VF recurrence was 74% (95%CI, 56-96%) at 12 months, and 53% (95%CI, 34-94%) at 36-month follow-up; the majority of patients remained on antiarrhythmic drugs (Figure). Low-voltage QRS (HR,21.96; p=0.022) and complete procedural success (HR,0.08; p=0.029) were associated with recurrent VT/VF at multivariable analysis (Figure). Conclusions catheter ablation of VT/VF is associated with favorable acute and mid-term arrhythmia control, yet with substantial risk of procedure-related complications and long-term recurrences. Septal substrate and frailty challenge successful management of patients with CA and VT/VF.Multimodality evaluation of LV substrateMain Study Outcomes

Acute pancreatitis (AP) is among the most common hospital gastrointestinal diagnoses; understanding the mechanisms underlying the severity of AP is critical for development of new treatment options for this disease. Here, we evaluate the biological function of phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) in AP pathogenesis in 2 independent genetically engineered mouse models of AP. PFKFB3 was elevated in AP and severe AP (SAP), and KO of Pfkfb3 abrogated the severity of alcoholic SAP (FAEE-SAP). Using a combination of genetic, pharmacological, and molecular studies, we defined the interaction of PFKFB3 with inositol 1,4,5-trisphosphate receptor (IP3R) as a key event mediating this phenomenon. Further analysis demonstrated that the interaction between PFKFB3 and IP3R promotes FAEE-SAP severity by altering intracellular calcium homeostasis in acinar cells. Together, our results support a PFKFB3-driven mechanism controlling AP pathobiology and define this enzyme as a therapeutic target to ameliorate the severity of this condition.

Proton therapy has emerged as a crucial tool in the treatment of head and neck and skull-base cancers, offering advantages over photon therapy in terms of decreasing integral dose and reducing acute and late toxicities, such as dysgeusia, feeding tube dependence, xerostomia, secondary malignancies, and neurocognitive dysfunction. Despite its benefits in dose distribution and biological effectiveness, the application of proton therapy is challenged by uncertainties in its relative biological effectiveness (RBE). Overcoming the challenges related to RBE is key to fully realizing proton therapy’s potential, which extends beyond its physical dosimetric properties when compared with photon-based therapies. In this paper, we discuss the clinical significance of RBE within treatment volumes and adjacent serial organs at risk in the management of head and neck and skull-base tumors. We review proton RBE uncertainties and its modeling and explore clinical outcomes. Additionally, we highlight technological advancements and innovations in plan optimization and treatment delivery, including linear energy transfer/RBE optimizations and the development of spot-scanning proton arc therapy. These advancements show promise in harnessing the full capabilities of proton therapy from an academic standpoint, further technological innovations and clinical outcome studies, however, are needed for their integration into routine clinical practice.