Citations

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.

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Background The current classification of pulmonary hypertension (PH), based largely on expert opinion, has limitations in prognostication and guiding therapies. We hypothesize that novel PH clusters that predict survival will reveal mechanistic phenotypes associated with biomarkers of vascular health across all PH groups. Methods We first identify novel PH clinical clusters by performing unsupervised clustering analysis on the CC‐PH (Cleveland Clinic PH) registry (N=1529). We develop classification models to predict the new PH clusters and then apply them to the multicenter PVDOMICS (Pulmonary Vascular Diseases Phenomics) cohort (N=853) for validation. We compare transplantation‐free survival across the new PH clusters. We quantify metabolites of the arginine‐nitric oxide pathway and D‐dimer levels and calculate global arginine bioavailability (arginine/[ornithine+citrulline]) to assess endothelial function and activation in the new clusters and link these biomarkers to clinical outcomes. Results Clustering analysis identify 3 clear clusters in CC ‐ PH that are validated in PVDOMICS and outperform conventional classifications in predicting transplantation‐free survival. The phenotype associated with the worst survival is characterized by reduced lung diffusion capacity, decreased arginine bioavailability and nitrate levels, and elevated D‐dimer levels, consistent with loss of pulmonary microcirculation and endothelial dysfunction. Conclusions We identify new informative PH phenotypes associated with mortality and defined by biomarkers of endothelial function and activation. Loss of endothelial health and pronounced pulmonary vascular rarefication contribute more substantially to mortality across the spectrum of PH than right heart function. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02980887.

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) frequently recurs after neoadjuvant therapy (NT) and curative-intent resection. Although major pathologic response predicts favorable outcomes, most patients achieve only minor response with a heterogeneous recurrence risk. We asked whether the spatial organization of residual PDAC encodes clinically relevant biology beyond residual tumor burden. Experimental Design: In a retrospective cohort of 203 patients with resected PDAC treated with NT and restricted to minor pathologic response, routine hematoxylin and eosin (H&E) whole-slide images were segmented into cancer and stroma using an artificial intelligence–enabled pipeline. Spatial composition (patch density, edge density) and configuration (compactness/complexity, intermixing) were quantified and tested for associations with disease-free survival (DFS) using multivariable models adjusted for standard clinicopathologic factors. Results: Shorter DFS was associated with a fragmented, interface-rich tumor–stroma ecology featuring higher edge density and diversity and reduced homotypic aggregation, independent of clinicopathologic variables. Two spatial risk models were independently prognostic: (i) cancer mean shape index plus stromal shape index variability [adjusted hazard ratio (HR), 1.71; P = 0.003] and (ii) mean stromal patch area plus edge density (adjusted HR, 2.19; P = 0.002). Both models stratified outcomes in which pathologic response grading and residual cancer area did not. High-risk configurations were further associated with reduced intratumoral tumor-infiltrating lymphocyte (TIL) density and infiltration ratio, with relative TIL accumulation at the cancer periphery and within the stroma, consistent with an immune-excluded phenotype. Conclusions: Residual cancer–stroma topology quantified from standard H&E slides yields independent prognostic signals after NT in PDAC, provides a cellular immune correlate for spatial risk, and motivates prospective validation and spatially informed adjuvant strategies.

Abstract Context Biochemical test results are central to clinical decision-making for the diagnosis and management of Cushing syndrome (CS). With emerging research and increasing availability of different tests, updated consensus on the utility of these biomarkers is warranted. Objective To establish an updated consensus on the role of biomarkers in the diagnosis and monitoring of adrenocorticotropic hormone-dependent CS, address novel therapeutic approaches, and identify areas for future research. Design A modified 2-round Delphi panel was conducted. Consensus was defined as ≥70% agreement/disagreement for Likert-scale statements or ≥70% selection of the same option for single-choice questions. Setting Participants represented a range of international expertise. Participants Forty-one participants took part in the Delphi panel, with no attrition between rounds (one nonclinician was not required to complete the second round). An 8-member Steering Committee guided statement development. Results Of statements designed to reach consensus, 45% (14/31) and 44% (11/25) statements reached consensus in Rounds 1 and 2, respectively. Notably, most panelists reported the use of late-night salivary cortisol for diagnosis of mild CS and for monitoring following pituitary surgery or medical or radiation therapy. Most panelists responded that block-and-replace therapies can be considered in patients with cyclical or severe CS, and consensus was reached that restoration of circadian rhythm is a treatment goal for patients with CS. Conclusion Areas of alignment among experts on the diagnosis and monitoring of CS are presented. The findings from this study are intended to support clinicians in their clinical decision-making and highlight priority areas for future research.