Citations

Abstract Background: Epithelial ovarian cancer (EOC), commonly known as ovarian cancer (OvCa), is the deadliest gynecological malignancy. High tumor expression of either NR3C1 mRNA (encoding the glucocorticoid receptor or GR) or GR protein (IHC) are associated with poor overall survival (OS) in patients (pts) with advanced stage OvCa. We hypothesized that high GR expression and associated GR transcriptional activity favor OvCa cell survival and chemotherapy resistance, thereby reducing OS. Here we investigated whether a GR transcriptome-based gene signature (GR-sig) would be a better prognosticator than tumor NR3C1 mRNA expression alone. Methods: mRNAs up- or downregulated >1.5 fold after glucocorticoid treatment (Dex) in one or both cultured OvCa cell lines (OVSAHO and HEYA8) were defined as differentially expressed genes (DEGs). DEGs were then identified in n=1247 unique OvCa microarrays from 15 publicly available Gene Expression Omnibus (GEO) datasets with matched pt OS (training set). We then used the OS data to train a Cox proportional hazards model. The “best subset selection” (BeSS) algorithm and bootstrap sampling identified those GR-regulated DEGs whose tumor mRNA expression correlated most significantly with pt OS, creating a GR-sig “risk score.” Subsequently, all n=522 microarray and n=374 RNA-seq publicly available samples from the OvCa TCGA were used as two independent validation sets. Microarray and RNA-seq data were normalized using the MAS5 and FPKM-UQ algorithms respectively. The two validation sets were independently stratified relative to the median training set risk score into low- and high-risk score groups. To examine the prognostic ability of NR3C1 mRNA expression alone, the median training set NR3C1 expression value was used to stratify validation set pts into low- and high-expression groups. In all cases, OS was estimated by the Kaplan-Meier method. Results: We identified n=2288 protein-coding DEGs in one or both cell lines. Of these genes, n=1251 were expressed in each GEO microarray sample (training set). A 10-gene GR-signature (GR-Sig) was then identified using the BeSS algorithm and bootstrap sampling, yielding a median training set risk score of 1.02. In both the microarray and RNA-seq validation datasets, the 10-gene GR-sig risk score was associated with significant OS differences between low- and high-risk score groups (microarray p = 0.018; RNA-seq p = 0.00049). In contrast, the OS difference between low- and high- NR3C1 mRNA expression groups did not reach significance (microarray p = 0.12; RNA-seq p = 0.28). Conclusion: In this retrospective analysis, a 10-gene GR-sig derived from OvCa GR-regulated DEGs performed better as a prognosticator than NR3C1 mRNA expression alone. Prospective application of the GR-sig may be useful in stratifying patients for treatment response with novel agents in OvCa clinical trials. Citation Format: Ananth V. Panchamukhi, Lei Huang, Eleanore P. Gray, Yuanhang Liu, Manisha Taya, Jennifer T. Veneris, Xiaonan Hou, S John Weroha, Balázs Győrffy, Gini F. Fleming, Chen Wang, Suzanne D. Conzen. Development of a prognostic ovarian cancer gene signature based on glucocorticoid receptor transcriptional activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4739.

Breast and ovarian cancer represent the most common and lethal cancers in women. Despite chemotherapy and targeted agents, recurrence is frequent and outcomes for patients with advanced disease are dismal, underscoring the need for novel therapeutic strategies. Using an unbiased approach with DepMap CRISPR screens across more than 1000 cancer cell lines, we identified six genes (CTPS1, RHOA, PRKRA, RAD9A, HUS1, and RAD1) that were essential for triple negative breast cancer (TNBC) cells, but not ERα+ breast cancer cells, that were also associated with poor outcomes. Validation of these effects by siRNA knockdown studies revealed that suppression of CTPS1 elicited the most potent inhibitory effects, characterized by S phase cell cycle arrest and apoptosis. Similar effects were also found in ovarian cancer cells which share many molecular features. CTPS1, along with CTPS2, is responsible for enzymatic conversion of UTP to CTP, an essential nucleoside triphosphate required for multiple cellular processes including DNA/RNA synthesis, phospholipid synthesis and glycosylation. CTPS1 was found to be highly expressed in tumor tissues, for both breast and ovarian cancer. RT-PCR assessment of CTPS1 expression in a panel of over 40 breast and ovarian cancer lines confirmed variable, but elevated expression relative to normal models. Notably, chemotherapy-resistant and PARP inhibitor (PARPi)-resistant models exhibited the highest levels of CTPS1 expression among all cells analyzed. In partnership with Step Pharma, which has developed a first-in-class highly selective CTPS1 inhibitor (STP938), we have demonstrated that STP938 elicits potent anti-proliferative effects at nM concentrations across many cell line and patient derived models, both in 2D and 3D culture systems. Furthermore, STP938 exhibited strong anti-cancer activity in chemotherapy- and PARPi-resistant ovarian cancer models, both as a monotherapy and in combination with standard-of-care treatments. RNA-seq analysis in cell models following STP938 treatment or CTPS1 knockdown/knockout showed significant dysregulation of DNA replication and cell cycle related genes, suggesting potential synergy with drugs targeting replication stress or DNA damage response pathways. Single-cell sequencing further revealed specific cell-cell interactions/cross talk/pathways that are disrupted by STP938 in vivo using ovarian cancer patient-derived xenograft. The first-in-human clinical trial for STP938 began in 2022 for relapsed/refractory B- and T-cell lymphomas (NCT05463263). In August 2024, a second phase I trial opened for advanced solid tumors, including an expansion cohort for CTPS2-null ovarian cancer (NCT06297525) at Mayo Clinic. These laboratory discoveries, and ongoing clinical studies, are expected to pave the way for a broader uptake of this novel therapeutic approach aimed at improving outcomes in patients with highly aggressive forms of these diseases. Citation Format: Xiyin Wang, Michael Emch, Lauren Voll, Rebecca Epp, Esther Rodman, Noa Odell, Nicole Pearson, Xiaonan Hou, Matthew Goetz, Scott Kaufmann, John Weroha, Philip Beer, John Hawse. Exploiting CTPS1 dependency for the treatment of breast and ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6388.

Introduction Targeted immunomodulators (eg, advanced therapies) effectively achieve symptomatic remission in patients with inflammatory bowel disease (IBD). However, ~25%–50% of patients with IBD achieving symptomatic remission with an advanced therapy may have continued endoscopically/radiologically active bowel inflammation, and it is uncertain whether changing alternative advanced therapies in asymptomatic patients with IBD will reduce bowel inflammation and achieve durable deep remission. Methods and analysis The QUality Outcomes Treating IBD to Target (QUOTIENT) study is an open-label, multicentre, pragmatic, randomised, controlled trial that aims to compare the efficacy and safety of switching to an alternative advanced therapy targeting endoscopic/radiological remission (treat-to-target) versus continuing the initial, or index, advanced therapy, in asymptomatic patients with IBD with moderate-to-severe endoscopic/radiological bowel inflammation. Enrolment is planned for ~250 participants in Canada/USA, randomised 1:1 to switching to alternative advanced therapy or continuing index advanced therapy, and then followed 104 weeks within routine clinical practice. Patient-reported outcomes measure efficacy and quality of life/treatment burden/safety. Primary endpoint is the time from randomisation to treatment failure. Ethics and dissemination The study is conducted in compliance with the protocol, ICH Good Clinical Practice, applicable regulatory requirements and appropriate review boards/independent ethics committees (approval numbers: Pro00077486; Pro00061437; STUDY00002062; 22-004171; i22-01269; IRB22-0890; IRB_00154397; 2000032384; SHIRB#2022.095-2; STUDY00007146; MMC#2024-18; REB#125290; 17784; Pro00142214; 20240660-01H), with documented written informed consent. Findings will be disseminated through peer-reviewed journals, scientific presentations, and publicly available Patient-Centered Outcomes Research Institute (PCORI) websites, including lay summaries. The Crohn’s & Colitis Foundation Education, Support, and Advocacy Department, and our patient advocacy stakeholder, will develop educational and marketing resources to communicate findings to a broad audience (>250 000 patients/caregivers/healthcare professionals). Trial registration number NCT05230173 .

Using 32 immune cell surface markers, we identified 23 monocyte clusters in murine blood. Diabetic gastroparesis was associated with a significant decrease in two circulating classical monocyte-like clusters and an upregulation of the Ccr2-Ccl2 axis in the gastric muscularis propria, suggesting increased tissue monocyte migration. This study offers new targets by pointing to a possible role for two classical monocyte subsets connected to the Ccr2- Ccl2 axis.

Abstract The prevalence of steatotic liver disease (SLD) is rising globally, presenting a significant public health challenge. While non-contrast computed tomography (CT) scans hold promise for the opportunistic detection of SLD, their full potential has not been systematically explored. Clinical indicators, such as serum data, are crucial for monitoring the progression of SLD. We introduce a novel Multimodal AI for Opportunistic Steatotic Liver Disease Screening (MAOSS), which integrates demographic data, serum tests, conventional CT biomarkers, and deep learning-derived CT image features to enhance model performance and explainability. MAOSS employs an innovative learning strategy, trained on a large-scale dataset (n = 1,783) encompassing both histopathologically-confirmed SLD and radiologically-reported steatosis cases. The model underwent extensive retrospective validation using steatosis grades derived from both histology and MRI-PDFF across internal and external datasets (n = 913), as well as real-world patient data (n = 18,504). It accurately detected mild to severe steatosis (≥ S1) with AUCs ranging from 0.903 to 0.929. Notably, MAOSS significantly improved the overall AUC for radiologists (n = 11) from 0.709 to 0.798 (p < 0.001). Furthermore, MAOSS was applied to optimize the standard clinical pathway for a simulated primary risk screening of SLD patients (n = 1,192), resulting in the identification of 31% more patients at risk of steatohepatitis and liver fibrosis progression, highlighting its potential to enhance SLD detection and management.

Abstract Aims Transcatheter mitral valve replacement (TMVR) has become a feasible alternative to surgical mitral valve replacement (SMVR) in selected patients at high surgical risk. The risk of valve thrombosis following SMVR and TMVR, and the optimal antithrombotic therapy following these procedures, remains uncertain. We aimed to compare the incidence of bioprosthetic mitral valve thrombosis (bMVT) after SMVR and TMVR, and the incidence of bMVT between patients on different antithrombotic regimens. Methods and results A literature search of Medline, Embase, and Cochrane Library was performed between January 2000 and August 2024. Random-effects models were used to derive pooled estimates of the incidence of bMVT in the absence of prior or active endocarditis and valve thrombosis. A total of 47 studies (6170 patients, total follow-up 9541.8 patient-years) were eligible for inclusion. The overall incidence of bMVT was 5.05 [95% confidence interval (CI) 3.18–8.01, I2 = 82%] per 100-patient-years. Subclinical bMVT was more common than clinically significant bMVT: incidence 19.11 vs. 7.91 per 100-patient-years, adjusted incidence rate ratio (aIRR) 4.62 (95% CI 1.39–15.36), P = 0.012. bMVT was numerically more common after TMVR than SMVR, but the comparison was not statistically significant: incidence 7.03 vs. 0.58 per 100-patient-years, aIRR 2.19 (95% CI 0.72–6.72), P = 0.170. Patients on vitamin-K antagonists (VKA) had a lower incidence of bMVT than patients on direct oral anticoagulants (DOAC; incidence 5.72 vs. 17.08, aIRR 0.31, 95% CI 0.13–0.73, P = 0.007). Conclusions bMVT is not uncommon, with numerically higher incidence in transcatheter compared to surgical valves, but the comparison was not statistically significant. VKAs are associated with a lower incidence of bMVT compared to DOACs.

ABSTRACT Understanding clinical trajectories of sepsis patients is crucial for prognostication, resource planning, and to inform digital twin models of critical illness. This study aims to identify common clinical trajectories based on dynamic assessment of cardiorespiratory support using a validated electronic health record data that covers retrospective cohort of 19,177 patients with sepsis admitted to intensive care units (ICUs) of Mayo Clinic Hospitals over 8-year period. Patient trajectories were modeled from ICU admission up to 14 days using an unsupervised machine learning two-stage clustering method based on cardiorespiratory support in ICU and hospital discharge status. Of 19,177 patients, 42% were female with a median age of 65 (interquartile range [IQR], 55–76) years, The Acute Physiology, Age, and Chronic Health Evaluation III score of 70 (IQR, 56–87), hospital length of stay (LOS) of 7 (IQR, 4–12) days, and ICU LOS of 2 (IQR, 1–4) days. Four distinct trajectories were identified: fast recovery (27% with a mortality rate of 3.5% and median hospital LOS of 3 (IQR, 2–15) days), slow recovery (62% with a mortality rate of 3.6% and hospital LOS of 8 (IQR, 6–13) days), fast decline (4% with a mortality rate of 99.7% and hospital LOS of 1 (IQR, 0–1) day), and delayed decline (7% with a mortality rate of 97.9% and hospital LOS of 5 (IQR, 3–8) days). Distinct trajectories remained robust and were distinguished by Charlson Comorbidity Index, The Acute Physiology, Age, and Chronic Health Evaluation III scores, as well as day 1 and day 3 SOFA ( P < 0.001 ANOVA). These findings provide a foundation for developing prediction models and digital twin decision support tools, improving both shared decision making and resource planning.

Purpose: Trabecular micro-bypass devices (TBDs) such as the iStent series (Glaukos Corporation), are effective in reducing intraocular pressure (IOP). However, precise placement of TBDs is crucial in achieving surgical efficacy, as device malpositioning may lead to suboptimal IOP reduction. We demonstrate 2 novel intraoperative signs to aid confirmation of accurate iStent placement, without reliance on imaging technologies. Methods: Surgical technique report with video accompaniment. Surgical Technique: Two intraoperative clinical signs that confirm optimal iStent placement are described: (1) Luminal Blood Reflux—achieved by gently decompressing the anterior chamber, with or without flushing of the stent lumen with balanced salt solution (BSS), thereby confirming stent positioning in the Schlemm canal (SC). (2) Schlemm’s Bidirectional Fluid Wave (SBFW)—observable when flushing with BSS, suggesting fluid movement in the canal segments adjacent to the iStent device, thereby confirming stent patency and positioning in the SC. Conclusion: The identified signs are useful, feasible, and reproducible indicators of accurate iStent placement. Future studies may evaluate the application of these confirmatory maneuvers in diverse clinical contexts and further establish a correlation with clinical outcomes.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Lung Cancer Screening provide criteria for selecting individuals for screening and offer recommendations for evaluating and managing lung nodules detected during initial and subsequent annual screening. These NCCN Guidelines Insights focus on recent updates to the NCCN Guidelines for Lung Cancer Screening.