Citations

Abstract Motor speech disorders (MSDs) are early markers of neurological disease, but expert perceptual analysis is rarely available outside specialized centers. Automated speech analysis offers a scalable alternative, yet prior studies have not systematically compared modeling approaches or assessed clinically relevant metrics in independent datasets. This study compared static acoustic features, articulatory informed Phonet features, and self-supervised pretrained models for binary and multi label MSD classification. We trained and evaluated models on 583 speech samples using speaker level splits. Baseline models included logistic regression and Gated Recurrent Units (GRUs) trained on eGeMAPS and MFCCs. We extracted three types of Phonet derived features and evaluated pretrained HuBERT and SSAST models in frozen, partially fine-tuned, and fully fine-tuned configurations. Binary classification distinguished MSDs from controls, while multi label classification identified six MSD subtypes. Models were assessed using validation AUC, and cut points were tested on two independent datasets. Pretrained and Phonet based models substantially outperformed static acoustic features. In binary classification, HuBERT achieved the highest AUC (0.95), while compact Phonet derived GRUs achieved comparable performance (up to 0.94). These models generalized well to independent datasets, maintaining high sensitivity (0.94) and specificity (0.97). In multi label classification, Phonet models achieved the highest macro average AUC (0.86), but threshold-based subtype performance declined on unseen data. Automated MSD detection is feasible and clinically promising. Binary classification generalized well, whereas multi label classification showed limited threshold stability across datasets.

Purpose of review Hepatorenal syndrome (HRS) is the extreme manifestation of acute renal dysfunction in patients with cirrhosis, resulting from systemic vasodilation and renal vasoconstriction, leading to a reduction in the glomerular filtration rate. Recent findings The diagnostic criteria redefined diagnostic criteria for HRS-AKI (Hepatorenal syndrome -Acute kidney injury) as our understanding of disease progression has improved. This understanding of the HRS disease process guides current management, with the combination of intravascular volume expansion and vasoconstrictor therapy being the cornerstone of treatment. In addition to treatment selection, timing of treatment initiation, duration, dosage, and monitoring during treatment are decisive factors in HRS outcomes. Pathogenesis of HRS-AKI may be different in patients with acute-on-chronic liver failure (ACLF) in comparison to decompensated cirrhosis. Unfortunately, outcomes remain poor with medical therapies alone and a high risk of disease recurrence exists for HRS-AKI with persistence of the cirrhotic milieu. Liver transplantation remains the only definitive treatment of HRS-AKI. Given the critical nature of HRS-AKI, a multidisciplinary approach involving hepatologists, nephrologists, and intensive care physicians is essential for optimal clinical management. Summary Patients with HRS-AKI should be managed ideally in tertiary care centers and referred for liver transplantation promptly when eligible.

Abstract Background: Early-onset pancreatic cancer (EOPC; age <50 y at diagnosis) is rare (≈1.3/100,000), biologically distinct, and germline-enriched (BRCA1/2, PALB2, ATM, CDKN2A, Lynch). Despite NCCN and CAPS Consortium recognition, its pre-diagnostic electronic health record (EHR) trajectory is uncharacterized. We sought reproducible signatures to guide subtype-aware surveillance for this under-screened young-adult population, where conventional guidelines do not apply. Methods: We assembled an EOPC cohort from Mayo Clinic (3 sites, 2001–2023; n=169 EOPC, n=3,162 older-onset PDAC), identified by ICD-10 C25.0–C25.3, C25.7, C25.9 or ICD-9 157.x with age <50 at first diagnosis. For each patient, 3-year pre-diagnostic trajectories of 10 routine laboratory analytes (bilirubin, CA 19-9, CEA, lipase, amylase, glucose, HbA1c, ALT, AST, alkaline phosphatase) were summarized over 30/90/180/365-day windows (mean, slope, delta; 1,706 features total; 131 retained at ≥10% non-zero). Features were winsorized (1–99 pct), standardized, and projected onto 15 PCA components capturing 81.7% variance. K-means clustering (k=2–6, min cluster fraction ≥10%) was assessed by silhouette and 100-resample bootstrap Adjusted Rand Index (ARI). Cluster signatures were compared against the older-onset PDAC cohort projected into the same component space. Results: Two reproducible pre-diagnostic clusters emerged (k=2; silhouette 0.469; bootstrap ARI 0.440). Cluster A: "occult prodrome" (87.0%; n=147; mean age 44.9 y) showed no clear signal across the 10 monitored analytes, with all analyte z-scores near zero through the 3-year window. Cluster B: "metabolic-biliary active" (13.0%; n=22; mean age 44.4 y) was characterized by elevated mean HbA1c (z=+1.08), rising bilirubin slope (z=+0.54), and rising ALT/alkaline phosphatase slopes (z=+0.51 each), consistent with combined diabetic-onset and biliary-obstructive prodrome. The two-cluster structure reproduced in older-onset Mayo PDAC at 87.3% / 12.7%, nearly identical to the EOPC distribution, indicating a fundamental pre-diagnostic dichotomy of pancreatic cancer rather than an age-specific phenomenon. The dominant occult phenotype across age strata indicates that lab-trajectory–anchored surveillance can only address the active minority and motivates complementary genetic-, demographic-, or imaging-anchored pathways for the occult majority. Conclusions: EOPC pre-diagnostic trajectories partition into a dominant occult prodrome (∼87%) without detectable signal in the 10 routine labs evaluated and a minority metabolic-biliary active prodrome (∼13%) with combined diabetic and obstructive features. The high occult prevalence motivates germline-guided active surveillance for genetically at-risk young adults rather than symptom-driven workup, anchoring next-generation surveillance trial designs in rare and hereditary pancreatic malignancies. External validation in independent institutional cohorts (Mayo Clinic Platform / MERCI, or comparable EHR networks) is the planned next step. Citation Format: Jianfu Li Li, Yingyun Yang, Wallace MIchael, Yan Bi. Pre-diagnostic clinical-trajectory signatures of early-onset pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Breaking Barriers in the Fight against Rare Cancers; 2026 Jul 18-20; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(14_Suppl):Abstract nr A046.

Abstract INTRODUCTION: Pleuropulmonary blastoma (PPB) and Sertoli-Leydig cell tumor (SLCT) are DICER1-related tumors for which novel therapies are urgently needed. A subset of Wilms tumors are also associated with germline or somatic variants in DICER1. Current therapies include cytotoxic chemotherapy, radiation, and surgery, but there are limited options for patients with recurrent disease. Antibody-Drug Conjugates (ADC) have emerged as promising therapies for several solid tumors. Aberrantly expressed cell surface proteins, including Preferentially Expressed Antigen in Melanoma (PRAME), represent potential targets for immunotherapeutic treatments like CAR-T cell and antibody-based therapies in malignant cancers, including DICER1-associated tumors. METHODS: Individuals diagnosed with PPB, SLCT, and Wilms tumor who enrolled in the International PPB/DICER1 Registry, International OTST Registry, and/or UT Southwestern Pediatric Hematology-Oncology Biorepository were selected for analysis. We analyzed ten PPB samples (four PDX, six primary tumor), four SLCT samples (all primary tumor), and 54 Wilms tumor samples (4 PDX, 50 primary tumor). DICER1 hotspot variants were verified in all 14 PPB and SLCT samples, while none of the Wilms tumor samples we analyzed exhibited DICER1 hotspot variants. Mapped and normalized whole-transcriptome sequencing reads were used to examine expression of 73 targets of antibody- or cell-based therapies that are clinically approved or under clinical investigation on clinicaltrials.gov. Genes with a median expression exceeding 2.5 transcripts per million (TPM) were considered expressed in a given tumor type; this threshold was selected to be permissive in identifying potential targets for further evaluation. RESULTS: Of the 73 genes of interest, 21 targetable cell-surface genes met a median expression threshold of 2.5 TPM in at least one tumor type: 11 genes in PPB, 16 in SLCT, and 14 in Wilms. Seven genes (FN1, PRAME, MCAM, CD248, IL11RA, CD276 (B7-H3), and MRC2) were expressed at this level in all three tumor types. Additional genes were expressed above this level in only two of the tumor types; PDGFRA in PPB and SLCT; GPC2 and TYRO3 in SLCT and Wilms tumor; and CSPG4, ERBB2, FZD10 in PPB and Wilms tumor. Six genes were exclusively expressed in SLCT (AXL, GPNMB, PROM1, KDR, ITGA6, FGFR4), and two were unique to Wilms tumor (GPC1, ULBP3). Of these, PRAME was previously reported as frequently expressed in DICER1-associated tumors; little has been reported about the remaining potential targets. CONCLUSION: PPB, SLCT, and Wilms tumor express several potential immunotherapy targets by RNA-seq. Expression of these potential targets should be investigated by immunostaining in a wider panel of tumors. Further study on the potential for ADCs or CAR-T cell therapies to treat DICER1-related conditions is needed. Citation Format: Brenya McNally, BS, Paige H.R. Mallinger, MS, David Huntsman, MD, FRCPC, FCCMG, Yemin Wang, PhD, Joyce Zhang, PhD, Claudette R. Fraire, PhD, Peter J. Schoettler, MD, Kris Ann P. Schultz, MD, Kenneth S. Chen, MD. Identifying potential cell-surface targets for therapeutic treatment of DICER1-related cancers [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Breaking Barriers in the Fight against Rare Cancers; 2026 Jul 18-20; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(14_Suppl):Abstract nr A018.