Citations

Abstract Background: Endocrine therapy (ET) with aromatase inhibitors (AIs) plus ovarian function suppression (OFS) is a standard endocrine strategy for premenopausal women with ER+/HER2- breast cancer. However, poor tolerability to AI+OFS limits its use, leaving tamoxifen as the only alternative. Prospective studies demonstrated that premenopausal women treated with neoadjuvant ET whose tumors exhibit Ki-67 ≤ 10% following 4 weeks of therapy achieve 5-year distant disease-free survival > 96%. Problematically, only 41% of patients reach this threshold with tamoxifen compared to 78% with AI+OFS (Nitz JCO 2022). (Z)-endoxifen (ENDX) is a potent selective estrogen receptor modulator that dually targets ERα and PKCβ1. At plasma concentrations of 3-5 ng/mL, it inhibits ERα; at ≥ 500 ng/mL, it targets PKCβ1, leading to AKT suppression. The EVANGELINE trial aims to examine endocrine sensitivity in terms of Week 4 Ki-67 in premenopausal women whose baseline Ki-67 > 10%, and objective response rate after 24 weeks of ENDX + goserelin in premenopausal women with baseline Ki-67≤ 10%. Methods: EVANGELINE (NCT05607004) is a multicenter, open-label, Phase 2 study comprised of three parts. Eligible patients are premenopausal women with Stage IIA/IIB ER+/HER2- breast cancer. • Part 1 (PK Run-in): assessed 40mg vs 80mg ENDX (+/- OFS) in 22 patients. • Part 2: patients with baseline Ki-67 >10% were randomized to 40 mg ENDX + goserelin or exemestane + goserelin for 6 months with the primary objective being 4-week ESD rate. Patients with a baseline Ki-67 ≤10% were assigned to a single-arm cohort of 40 mg ENDX monotherapy (no OFS) to evaluate the 24-week endocrine sensitivity disease rate. • Part 3 (replaces Part 2): all patients are treated with ENDX 40mg daily + goserelin every 28 days. A two stage Phase II design was chosen to assess outcomes as follows: Part 3a: Up to 45 patients with baseline Ki-67> 10% to assess Week 4 Ki-67≤ 10% rate is at least 65%. If 9 or more of these patients have a Week 4 Ki-67>10%, enrollment will be stopped due to futility. Otherwise, enrollment will continue. Part 3b: Up to 20 patients enrolled with baseline Ki-67≤ 10% to assess Week 24 objective response rate. Ki-67 levels are determined by central laboratory and images are centrally reviewed. Secondary objectives include safety, tolerability, surgical outcomes, and biomarker analysis using paired biopsies (baseline, week 4) and surgical specimens. Results: The PK run-in (completed Fall 2024) enrolled 22 patients and assessed ENDX doses (40 mg daily vs 80 mg daily (+/-OFS)). The Week 4 Ki-67 ≤ 10% rate with ENDX was 86% and did not differ according to dose. Early safety, PK, efficacy and compliance data supported the selection of 40 mg ENDX daily as the optimal dose. Enrollment in Part 2 began in May 2025. Part 3 will replace Part 2 with simplification of the trial design. Conclusions: EVANGELINE is the first trial to evaluate (Z)-endoxifen + OFS as neoadjuvant therapy in premenopausal ER+/HER2- breast cancer. By targeting both ER and PKC pathways, ENDX may offer a well-tolerated alternative to AI-based regimens and expand endocrine therapy options for this population. Clinical Trial Registration: NCT05607004 Citation Format: M. P. Goetz, V. J. Suman, C. Lopez, H. Erickson, L. Beaulieu, S. S. Hammer, L. Mina, R. Leon-Ferre, K. N. Hunt, M. Piltin, A. Degnim, J. N. Ingle, J. C. Boughey, B. A. Sarah, J. M. Reid, M. Schellenberg, J. R. Hawse, P. Advani, K. Giridhar, F. Batalini, D. Flora, J. M. Jones, N. A. Bagegni, J. Jakub, V. Abramson, V. Dabak, W. J. Irvin, E. Sima, K. Seema, S. C. Quay. A Phase 2 Trial of (Z)-endoxifen + Goserelin as Neoadjuvant Treatment for Premenopausal Women with ER+, HER2-, Breast Cancer (EVANGELINE) [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS5-12-16.

Abstract Recent advances in long-read transcriptome sequencing enable high-throughput profiling of full-length RNA isoforms in bulk, single-cell, and single-nucleus samples. However, long-read datasets typically contain a mixture of complete and partial transcripts, leading to pervasive ambiguity in read-to-isoform assignment and complicating accurate isoform identification and quantification, particularly in the absence of reliable reference annotations. These challenges are further amplified in single-cell and single-nucleus samples, where coverage is sparse and transcriptional heterogeneity is high. Here, we present the Long Read Alignment Assembler (LRAA), a unified and versatile computational framework for isoform identification and quantification from long-read RNA sequencing data across bulk, single-cell, and single-nucleus transcriptomic samples. LRAA combines splice-graph based structural modeling with expectation maximization based optimization to probabilistically resolve ambiguous read assignments and improve isoform abundance estimation. The framework supports quantification-only, reference-guided, and fully reference-free (de novo) modes of analysis within a single methodological paradigm. We benchmarked LRAA using both simulated and genuine long-read datasets spanning sequencing standards and whole transcriptomes. Central to this evaluation is a novel benchmarking strategy based on Multiplexed Overexpression of Regulatory Factors (MORFs), which provides biologically expressed, barcoded isoforms with unambiguous read-level ground truth. Across all benchmarks, including MORFs, synthetic spike-ins, and whole-transcriptome datasets, LRAA consistently outperformed state-of-the-art methods in isoform identification accuracy, sensitivity, and expression quantification. Finally, we demonstrate the biological utility of LRAA by resolving cell-type-specific isoform usage across peripheral blood immune cell populations and by detecting a pathogenic cryptic isoform of STMN2 with associated transcriptional changes in single-nucleus RNA-seq data from frontal cortex tissue of an individual with frontotemporal dementia (FTD). Together, these results establish LRAA as a robust and general solution for resolving transcript diversity in complex biological systems, from development to disease.

ABSTRACT Background Immune checkpoint inhibitor-associated acute interstitial nephritis (ICI-AIN) requires a kidney biopsy for a definitive diagnosis. A recent study suggested that 2-deoxy-2-[18F] fluoro-D-glucose positron emission tomography-computed tomography (F18-FDG PET–CT) may offer a noninvasive alternative, but lack of kidney biopsies in all patients and a proper control group receiving ICI therapy remained important limitations. We conducted the first study addressing these limitations and examined whether PET–CT could differentiate biopsy-proven ICI-AIN from other causes of acute kidney injury (AKI) in patients on ICI therapy. Methods This retrospective cohort study comprises 105 patients on ICI therapy who underwent F18-FDG PET–CT and had a kidney biopsy, along with data from a control group receiving ICIs without AKI. PET–CT scans were performed within 14 days before or 10 days after biopsy, and baseline PET-CTs obtained during ICI therapy before AKI, were reviewed by a blinded nuclear radiologist. Renal cortical standardized uptake values (SUV) were measured in five regions of interest, liver and blood-pool SUVs served as internal references. Results Thirty-two patients were included (5 ICI-AIN, 7 AKI from other causes, 20 controls). Renal SUVs did not differ significantly among groups. In patients with serial PET-CTs, kidney SUVs tended to increase from baseline to AKI in ICI-AIN, but these changes were not statistically significant. Conclusions In this biopsy-validated cohort, PET-CTs did not reliably distinguish ICI-AIN from other causes of AKI in patients receiving ICI therapy. Larger prospective studies are needed to validate these findings.

Acute kidney injury (AKI) affects thousands of hospitalized patients annually, yet early detection remains challenging as serum creatinine elevation lags behind clinical deterioration. Decreased urine output (UO) represents a key diagnostic criterion of AKI, sometimes manifesting hours before biochemical changes; however, current manual monitoring methods are labor-intensive and prone to error. Here, we developed and validated a simple, cost-effective automated urine flow meter using non-contact optical sensors, a peristaltic pump, and microcontroller-based automation for precise, real-time monitoring of urine output in clinical settings, named P-meter. Three successive prototypes (V1, V2, V3) were validated against gold-standard gravimetric measurements over 285 h of testing during animal experiments that required bladder catheterization. Iterative refinement addressed miniaturization challenges, fluid dynamics optimization, and sensor positioning to achieve progressively improved accuracy. The optimized V3 prototype demonstrated further enhanced volumetric precision, stability, and flow accuracy with near-unity linearity vs. reference method (R2 = 0.9889), minimal bias (mean error −0.1 mL), and 94.18% agreement within confidence limits (n = 86), outperforming the initial V1 prototype (R2 = 0.9971, mean error −1.69 mL, n = 207) and intermediate V2 design (R2 = 0.9941, mean error 3.63 mL, n = 390), primarily in terms of reduced bias and improved agreement. The P-meter offers accurate urine output monitoring at a lower cost than commercial systems, facilitating its use in early AKI detection and thereby improving patient outcomes.

ABSTRACT Background Although kidney biopsy remains the gold standard for diagnosing immune checkpoint inhibitors–associated acute interstitial nephritis (ICI-AIN), several promising urinary biomarkers have emerged as potential non-invasive diagnostics. Notably, recent studies have highlighted tumor necrosis factor alpha (TNF-α), CXC motif chemokine ligand 9 (CXCL-9) and others as potential biomarkers to help distinguish ICI-AIN from other causes of acute kidney injury (AKI). However, a direct systematic comparison between these two biomarkers in a cohort of patients undergoing immunotherapy has not been performed. Methods We prospectively enrolled a cohort of ICI-treated cancer patients who developed AKI (including both ICI-AIN and ICI-Non-AIN AKI), as well as those without AKI, referred to as the internal validation cohort. Urinary CXCL-9 and TNF-α were measured across all groups using the human Quantikine ELISA Kit. We externally validated our findings in a cohort of biopsy proven ICI-AIN patients from Spain, referred to as the external validation cohort. Results Urinary CXCL-9 levels were significantly higher in ICI-AIN patients from Mayo (n = 40) compared with those with ICI-Non-AIN AKI (n = 36) and ICI-treated patients without AKI (n = 16) (both P ≤ .0001); these findings were confirmed in the validation cohort from Spain (n = 19) with P-values of .0008 and <.0001, respectively. The area under the curve (AUC) for urinary CXCL-9 distinguishing ICI-AIN biopsy proven (combined from both cohorts, n = 45) from ICI-Non-AIN AKI was 0.83 (95% confidence interval 0.74–0.92), while for urinary TNF-α the AUC was 0.63 (0.51–0.75). Conclusions Increased urinary CXCL-9 was superior to TNF-α as a biomarker for the non-invasive diagnosis of ICI-AIN, even after prior corticosteroid exposure, highlighting its promise as clinical diagnostic tool.

Abstract Cancer occurs in ∼1 per 1000 pregnancies; thousands of patients may require radiation procedures for diagnosis and treatment each year in the United States alone. This rare but high-risk scenario, coupled with fear of radiation, has created ambiguity in the ideal management of pregnant patients. Without a comprehensive guide for the use of radiation in imaging and treatment for pregnant cancer patients, it is difficult for providers to offer optimal patient-centered care without introducing disparities. The goal of this paper is to provide guidance on the use of radiation for screening, diagnosis, staging, and treatment of cancer, while highlighting gaps in existing knowledge and guidelines. The intention is that physicians, medical physicists, and patients could use this document as a resource for shared decision-making, ensuring safe and effective practice. A team of physicians and medical physicists with expertise in imaging, radiotherapy, and maternal fetal medicine was assembled, along with a patient advocate and lawyer. Existing guidelines and recent literature were reviewed. Authors also drew from their experience where published guidance was lacking. The resulting document discusses best practice to guide use of radiation for cancer, as well as patient-centered care management and legal considerations. Overall, it is possible to safely and effectively deliver radiation to pregnant patients in numerous circumstances. Use of radiation or other modalities should be discussed through shared decision-making with the physician and patient, contextualizing the maternal and fetal risk from treatments. Healthcare providers should support wide access to reproductive healthcare to allow equitable, evidence-based, patient-centered healthcare.

ABSTRACT Rationale Before evidence‐based practice (EBP) was formally adopted, healthcare decisions relied on critical thinking and clinical judgment informed by disciplinary knowledge, theory, and research, but lacked full integration of patient values with clinical expertise. Sackett et al. redefined EBP as the integration of the best available evidence, clinical expertise, and patient values. This framework has been embraced by nursing and other healthcare disciplines, embedding EBP into education, clinical protocols, and quality improvement efforts. Despite widespread adoption, traditional conceptualizations prioritize empirical evidence above patient values, potentially undermining individualized care. Aims and Objectives This paper proposes a reconceptualization that places patient and client values—their why —at the center of EBP, inspired by Simon Sinek's Golden Circle model which emphasizes starting with purpose to influence behavior effectively. Prioritizing the patient's values before incorporating empirical evidence into a care plan ensures that care aligns with their personal goals and definitions of health, fostering therapeutic relationships and supporting meaningful behavior change. Methods A conceptual analysis was conducted using Simon Sinek's Golden Circle model as a guiding framework. This model emphasizes starting with purpose to influence behavior effectively. The analysis explores how integrating patient values first, followed by empirical evidence and clinical expertise, can operationalize person‐centered EBP. Results The reconceptualized framework positions patient values as the foundation of care planning. By aligning interventions with patients' personal goals and values first, clinicians can strengthen therapeutic relationships and support individualized care. Conclusion Effective nursing clinicians and leaders must embrace this patient‐first approach to truly operationalize person‐centered, evidence‐based care that respects the diverse needs and motivations of patients.

ABSTRACT Amidst the opioid crisis, understanding the genetic basis of opioid use disorder (OUD) is crucial for identifying biological mechanisms and intervention points. However, genome‐wide association studies (GWASs) have been hampered by inadequate sample sizes and often the use of control populations not assessed for prior opioid exposure. Because opioid exposure is a prerequisite for the development of OUD, consideration of exposure history in controls is important. Electronic health record data (EHR) paired with genomic information allow a broader sampling of patients with OUD and exposed controls. We leveraged data across two healthcare systems to evaluate the impact of using controls not screened for opioid exposure (‘generic’) versus minimally opioid‐exposed control (‘exposed’). First, at the phenotypic level, we conducted phenome‐wide association studies (PheWAS) to compare the medical comorbidity profiles of OUD cases when using generic versus exposed controls. While PheWAS results for OUD‐related comorbidities were more pronounced when using the generic group, 83% of the disease associations were overlapping and of similar effect sizes. Second, at the genetic level, we conducted GWAS (cases vs. generic; cases vs. exposed) and assessed differences in genetic correlations and degrees of phenotypic misclassification. Genetic results were concordant across control groups based on heritability (generic: 0.16 ± 0.07 vs. 0.10 ± 0.07), associations with the coding OPRM1 variant rs1799971 ( p generic = 8.83E‐03 vs. p exposed = 1.83E‐02) and genetic correlations with prior OUD GWAS ( r g‐generic = 0.83 ± 0.26 vs. r g‐exposed = 0.78 ± 0.27). Although GWASs were limited by sample size ( N generic = 6269, N exposed = 6365), compared to an independent OUD GWAS ( N = 425 944), the dilution value for the two GWAS was not different from 1, suggesting no major impact of phenotypic misclassification. This study represents the first effort to enhance OUD genetic research through optimization of control definitions using EHR data. Generic controls ascertained within the US health systems, where exposure to prescription opioids is high, offer a practical alternative for genetic studies of OUD.

198 Background: The Hedgehog (Hh) signaling pathway regulates tissue patterning, growth and differentiation, including within gastrointestinal tract. Mammalian homologs include Sonic (SHH), Indian (IHH) and Desert (DHH) Hedgehog, which signal through PTCH and SMO and the GLI transcription factors. In the digestive tract, both SHH and IHH are expressed, but the functional role of Hh signaling in mCRC remains incompletely defined. Methods: We analyzed 433 mCRC patients treated with either bevacizumab (bev = 226) or cetuximab (cet = 207) plus first line chemotherapy in CALGB/SWOG 80405 (NCT00265850). RNA expression (Illumina HiSeq 2500) of 9 Hh pathway genes (SHH, IHH, DHH, PTCH1, PTCH2, SMO, GLI1, GLI2, GLI3) was evaluated. Median overall survival (mOS) and progression free survival (mPFS) in months (mo) were compared across expression tertiles (low [L], medium [M], high [H]). Likelihood ratio tests, hazard ratios and 95% confidence intervals were computed from multivariable Cox proportional hazards models, adjusting for age, sex, ethnicity, ECOG PS, tumor location, number of metastatic sites, KRAS , microsatellites instability status and treatment. Prognostic effects were modeled as marginal terms; predictive effects were modeled as multiplicative interactions. Results: Overall, IHH and GLI2 demonstrated prognostic value for OS after adjusting for multiple testing (Benjamini-Hochberg False Discovery Rate (FDR) < 0.05). High IHH expression (H group, n = 143) correlated with improved mOS (H: 36.0 mo vs M: 32.8 mo vs L: 23.5 mo; p= 0.031), whereas low GLI2 expression (L group, n = 145) was associated with longer mOS (H: 25.6 mo vs M: 33.9 mo vs L: 33.7 mo; p= 0.0016). Moreover, IHH showed predictive value for cet benefit in both OS (mOS H: 38.1 mo vs M: 34.0 mo vs L: 18.4 mo; p= 0.0032) and PFS (mPFS H: 12.6 mo vs M: 12.9 mo vs L: 8.8 mo; p= 0.0025) with significant treatment interaction for OS and PFS (p= 0.0046 and p= 0.0049, respectively; FDR< 0.05). No significant associations were found in bev treated pts. No other Hh genes showed significant prognostic or predictive effects after FDR correction. Conclusions: These results highlight a dual role of Hh pathway in mCRC. Consistent with prior preclinical evidence, reduced IHH expression appears to mark poor prognosis, likely reflecting the loss of IHH-mediated restraint on Wnt signaling, which drives proliferation and dedifferentiation. Conversely, low GLI2, a downstream transcription factor, was linked with favorable outcomes, underscoring context-specific effects of Hh signaling. The strong predictive association of IHH with cet efficacy supports its potential as a biomarker in RAS wild type mCRC. These results suggest that Hh pathway modulation, particularly IHH signaling, may influence disease biology and treatment response. Validation in independent cohorts and mechanistic studies is warranted to clarify implications.

179 Background: Neuroligins are a family of postsynaptic cell adhesion molecules that play a crucial role in synapse formation and function. Recent studies suggest Neuroligin family genes (NLGN1,2,3,4X) may promote cancer cell growth and metastasis in various cancers, including colorectal cancer. Here, we investigated the association between neuroligin family gene expression and first-line treatment outcomes in mCRC. Methods: We evaluated the expression of 4 genes in the neuroligin family (NLGN1, NLGN2, NLGN3 and NLGN4X) on treatment outcomes of 433 pts with mCRC treated with either bevacizumab (Bev, n = 226) or cetuximab (Cet, n = 207) in combination with first-line chemotherapy within the CALGB/SWOG 80405 trial. mRNA was isolated from FFPE tumor samples and sequenced on the HiSeq 2500 (Illumina). Overall survival (OS) and progression-free survival (PFS) were compared between groups of pts categorized by low expression (Q1) (≤25 percentile), medium expression (Q2-3) (25th-75th percentile) and high expression (Q4)(>75th percentile) of NLGN family genes. The associations between gene expression and clinical outcomes were assessed via the multivariable Cox model and plotted with Kaplan-Meier curve. Treatment-gene interactions were evaluated using the likelihood ratio test. False discovery rate (FDR) was controlled through the Benjamini-Hochberg procedure. Results: High NLGN2 expression was associated with shorter PFS (median 10.0 mos, 95% CI (8.3, 11.3)) and OS (median 25.2mos, 95%CI (20.9, 30.0)) compared to low NLGN2 expression (PFS: median 11.2mos, 95% CI (9.8,14.3))(HR 1.41, 95% CI (1.06, 1.89)), P = 0.029). (OS: (median 31.8mos, 95%CI (26.8, 37.5)( HR 1.49, 95% CI (1.10, 2.01) P =0.0095) in multivariate analysis. Patients treated in the cetuximab arm(n=207), high HLGN2 expression significantly associated with shorter PFS (median 8.0 vs 13.4, HR 2.02, 95% CI (1.35, 3.03), P = 0.0021) and OS (median19.6 vs 36.3, HR 2.30, 95% CI (1.50, 3.53), P =8.3e-05). High NLGN3 expression was associated with shorter OS (23.9 vs 36.0 mos, P =0.0083) in cetuximab treatment arms, no significance found in PFS. We found significant treatment interaction for OS with NLGN2 and NLGN3 favoring cetuximab. In pts treated with cetuximab, High NLGN2 expression was significantly associated with shorter OS (median 29.1vs 36.3) (p=0.024) compared to pts treated with bevacizumab. For NLGN3, pts treated with cetuximab, high NLGN3 expression was significantly associated with shorter OS (median 25.0 vs 36.0) (p=0.018) compared to pts treated with bevacizumab. No significant association was found in NLGN1 and NLGN4X. Conclusions: Our results suggest NLGN2/3 gene expression may predict mCRC treatment outcomes. Potential therapeutic drug target NLGN in combination with anti-EGFR treatment in mCRC is warranted.