The University of Kansas Cancer Center

Emerging evidence shows that Proton FLASH radiotherapy can spare normal tissues while maintaining anti-tumor efficacy. However, its impact on intestinal stem cells (ISCs) and the gut microbiome remains unclear. Gut microbiome influences ISC's radiosensitivity.In a mouse model of abdominal irradiation, Proton FLASH exposure exhibited improved survival and less crypt-villus damage compared to Proton Conventional dose rate. Using scRNA-sequencing, we demonstrated that Proton FLASH exposure using pulsed pencil beam scanning spares two distinct ISC populations, Lgr5+ Crypt-based columnar cells (CBCs) and a Ly6a+, Clu+, Areg+, Anxa2+ revival stem cell (revSC) population-by modulating oxidative stress and cell cycle progression. Analysis of α and β-diversity demonstrated that Proton FLASH modulates gut microbiota composition without compromising overall species richness. Notably, Proton FLASH-irradiated mice had higher abundances ofAlistipessp. andAkkermensiasp., both known for protective effects on ISCs and the intestinal mucosa. The role of microbiome in Proton FLASH-mediated sparing effect was further confirmed by fecal microbiota transplantation, where Proton FLASH-donor microbiota demonstrated reduced lethality with protection of crypt villus morphology in recipient mice exposed to Proton Conventional dose rate. Our findings highlight the crucial role of the microbiome in the Proton FLASH-mediated sparing of the mucosal epithelium.

Avelumab, pembrolizumab, and enfortumab vedotin (EV) demonstrated efficacy in mUC following platinum-based chemotherapy. However, real-world data in patients with urothelial carcinoma with squamous differentiation (UCSD) are limited. The aim of this study is to assess the real-world clinical outcomes of avelumab, pembrolizumab, or EV in mUCSD patients. The ARON-2EV study is a retrospective, international, multicenter analysis in patients with mUC treated with avelumab, pembrolizumab, or EV across 79 centers in 21 countries. Patients were divided into three cohorts: 1 (avelumab), 2 (pembrolizumab), and 3 (EV). Primary endpoints were overall survival (OS) and time on treatment (ToT). Secondary objectives included evaluating clinical factors associated with outcomes and exploring the impact of UCSD histology on response to therapy. Statistical methods included Kaplan-Meier estimates, log-rank tests, Fisher's exact and chi-square tests, and Pearson's correlation coefficients. A total of 1918 patients, 1696 with advanced pure UC (pUC) and 222 with mUCSD (36 in cohort 1, 111 in cohort 2, and 75 in cohort 3), were included. Median OS was shorter in patients with UCSD compared to patients with pUC histology in the three cohorts (1: 13.0 vs 26.8months, HR 2.66,p = 0.003; 2: 10.2 vs 18.5months, HR 1.52,p = 0.008; and 3: 7.6 vs 13.1months, HR 1.68,p = 0.011). Median ToT was shorter in patients with UCSD compared to patients with pUC histology in cohort 1 (3.5 vs 5.6months, HR 1.57,p = 0.044) and 3 (7.6 vs 13.6months, HR 1.83,p = 0.005) but not in cohort 2 (3.7 vs 4.7months, HR 1.19,p = 0.177). Response to therapy was negatively correlated with UCSD histology in cohorts 2 (correlation coefficient 0.094,p = 0.008) and 3 (correlation coefficient 0.107,p = 0.021), while response to avelumab was not correlated with UCSD (correlation coefficient 0.072,p = 0.263). UCSD is a histology with a poor prognosis and response to treatments compared to pUC. Treatments activity and effectiveness in divergent differentiations should be addressed in dedicated prospective studies. NCT05290038.

Cancer continues to be a major cause of death, with an anticipated 2,114,850 new cases and almost 626,140 deaths from the disease in 2026 [...].

821 Background: Nectin-4 targeting antibody drug conjugate (ADC) enfortumab vedotin (EV), in combination with pembrolizumab, is the first-line treatment for patients with metastatic or locally advanced urothelial cancer (UC). However, optimal treatment strategies for non-responders remain an unmet clinical need. We analyzed tumor transcriptomes to identify ADC target expression profiles which may inform treatment selection for these patients. Methods: We conducted a literature search to identify ADC targets approved or under investigation for UC. Molecular targets of interest included Nectin-4 ( NECTIN4 ), Her2 ( ERBB2 ), Trop-2 ( TACSTD2 ), DLL3, B7-H3 ( CD276 ), FGFR3, and PDL1 ( CD274 ). We interrogated The Cancer Genome Atlas (TCGA) dataset, comprising tumors from 434 patients with UC and 19 normal bladder tissue samples. Hierarchical clustering was used to identify recurrent ADC target expression profiles. To validate our findings, we repeated the analysis on an independent cohort of 478 patients with UC from the Oncology Research Information Exchange Network (ORIEN) using R version 4.5.1. Results: Two mutually exclusive patterns of ADC target expression were identified in the TCGA dataset. Cluster 1 (70.2%, n = 318) was characterized by overexpression of ERBB2 , FGFR3 , NECTIN4 and TACSTD2 . Cluster 2 (29.8%, n = 135) was characterized by overexpression of DLL3 , CD276 , and CD274 . The two clusters of ADC targets demonstrated a significant negative correlation (Spearman rho = -0.40, p < 0.0001). Normal bladder tissue did not cluster according to ADC gene expression profiles. In the ORIEN dataset, a similar pattern was observed: where the seven target genes were separated into two clusters. One cluster showed overexpression of FGFR3 , NECTIN4 , and TACSTD2 , while the other showed overexpression of DLL3 , CD276 , CD274 and ERBB2 . The enrichment scores of the two clusters were also negatively correlated (Spearman rho = -0.79, p < 0.0001) in the ORIEN dataset. Notably, ERBB2 clustered with the second group in ORIEN, suggesting biological variability. Conclusions: Through interrogation of TCGA data and validation in an independent ORIEN cohort, we identified two mutually exclusive ADC target expression profiles in UC. Tumors lacking overexpression of NECTIN4 , TACSTD2 , or FGFR3 were enriched for DLL3 , CD276 and CD274 expression, suggesting alternative ADC targets for non-responders to current therapies. The differential ERBB2 clustering highlights potential biological variability of this target. These findings warrant prospective proteomic validation and may inform rational treatment selection beyond EV.

Abstract Purpose: Germline mutations were evaluated in 530 Chinese breast cancer (BC)patients with different HER2 expression status plus 98 patients with atypical ductalhyperplasia or a breast cancer family history. Methods: DNA extracted from blood samples was analyzed with a next generationsequencing based multigene panel, with reporting of likely pathogenic and pathogenicvariants (PV) of 102 cancer associated genes, and correlation betweenclinicopathologic characteristics and known BC-associated genes. Results: The 71 identified PVs were categorized into five distinct pathway clusters:BRCA/FANC, DDR, HRR, FANC, and Other. The distribution of PVs enriched withinthese clusters differed significantly between BC patients and unaffected individuals(p=0.031). This difference was primarily driven by the BRCA/FANC, FANC, and DDRclusters, with enrichment percentages of 57.7% vs. 16.7% (BRCA/FANC), 7.0% vs.25.0% (FANC), and 15.5% vs. 41.7% (DDR) in BC vs. unaffected groups, respectively.Notably, the three BC groups stratified by HER2 expression level exhibited distinct PVdistributions. Both the HER2-low and HER2-zero BC groups showed significantlydifferent distributions compared to unaffected individuals (p=0.0132 and p=0.0081,respectively). The BRCA/FANC cluster was the predominant pathway enriched in bothHER2-low (59.6%) and HER2-zero (81.8%) groups. Furthermore, the PV distributionin the HER2-zero group was significantly different from that in the HER2-high group(p=0.0028). In contrast, the distribution in the HER2-high group resembled thatobserved in non-BC individuals. These findings indicate that BC patients with differentHER2 expression statuses harbor distinct germline PV signatures, which correlate withdifferential clinical outcomes following neoadjuvant systemic therapy. Discussion: Chinese breast cancer patients with different HER2 expression statusdemonstrated different pathogenic germline variant, which correlated with differentclinical outcome after neoadjuvant therapy. Multi-gene genetic test for pathogenicgermline variant should be offered to breast cancer patients as well as high-riskindividuals at risk for future breast cancer who would benefit from prevention and earlydetection programs. Citation Format: N. Liao, J. Wu, G. Zhang, J. Weitzel, C. Balch. Pathogenic germline variants associated with different HER2 expression among breast cancer patients [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 PS3-05-21.

Glioblastoma (GBM) is a highly prevalent and aggressive type of brain tumor characterized by profound molecular complexity and poor prognosis. While conventional biomarker studies focus on highly significant genes or proteins associated with cancer outcomes, the contribution of gene-gene co-regulation to GBM progression remains unclear. This study employs an application of integrative machine learning approach, utilizing a high-dimensional transcriptomic profile that considers gene-gene co-regulations to identify predictive gene networks involved in GBM occurrence and 1-year survival prediction. We further integrate these network models with both empirical protein-protein interaction (PPI) data and random walk-based information flow analysis across the PPI landscape. This dual-layered approach uncovers gene modules that bridge transcriptional co-regulation with functional connectivity at the protein level. This integration highlighted several hub genes, including both strong and weak (e.g. BSN, RHOC, ANXA1, CSF1R, and ITGAM), that emerged as key molecular connectors involved in critical GBM processes such as immune response and neuronal signaling. Notably, these hub genes also exhibited cross-disease associations with traits including gut microbiome composition, type 2 diabetes, coronary artery disease, and other cancers, underscoring their systemic biological relevance. Overall, our findings through the computational approach underscore the significance of co-regulatory gene networks in GBM biology. It also demonstrates how integrating transcriptomic and protein-level interactions can refine prognostic modeling, advance biomarker discovery, and inform future therapeutic development.

The importance of theranostic nanomedicine as a therapeutic paradigm is steadily increasing. The continuing progress in the synthesis of advanced materials facilitates the design of tailored nanoplatforms that can perform both imaging and therapeutic functions. Theranostic nanosystems diagnose diseases, such as the exact location of solid tumors and metastases or the sites of infection, with high precision when combined with the correct imaging modality. They then deliver drugs and monitor the therapeutic response of the host. Ideally, these systems can be adapted to administer personalized medicine to optimize the outcome of (theranostic) therapy. Here, we will focus on theranostic systems that are designed for using MRI as imaging modality. The accelerating evolution in the chemistry of synthesizing core materials and surface modifications, as well as in the field of supramolecular design has led to an abundance of theranostic systems, such as nanomicelles, nanoemulsions, nanovesicles, microcapsules, magnetoliposomes, polymer-based theranostic agents, dendrimers, multifunctional magnetic nanoparticles, and mesoporous silica nanoparticles that are covered in this chapter. Preclinical and clinical studies will show which approaches will be successful in the clinic.