bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract B014: ONECUT2 activates diverse drug-resistant phenotypes in prostate cancer
Authors: Qian Chen , Yang Qian , Kim HyoYoung , Yan Yiwu , Mostaghel Elahe , Ellis Leigh , Knudsen Beatrice , Kaochar Salma , Ye Huihui , Garraway Isla , You Sungyong , Freeman Michael 
Published: June 2023

Abstract
BACKGROUND. Prostate cancer (PC) cells can escape from lineage confinement and be reprogrammed to a drug-resistant, high-plasticity state, however the mechanism underlying this process is not understood. Our group identified the HOX/CUT transcription factor ONECUT2 (OC2) as a mediator of metastatic castration-resistant PC (mCRPC) that can be inhibited with a novel family of small molecules. OC2 was shown to be a lineage plasticity driver that promotes neuroendocrine prostate cancer (NEPC). In this study, we sought to uncover the mechanism whereby OC2 exerts effects on lineage plasticity. METHODS. RNAseq, CUT&RUNseq, scRNAseq, forced expression, shRNA, CRISPR-Cas9, co-precipitation/western blot, PCR, mutagenesis, human PC, PC models, computational modeling. RESULTS. We found that OC2 is capable of activating multiple androgen receptor- (AR)-indifferent, drug-resistant lineages, including programs not associated with NEPC, such as upregulation of the glucocorticoid receptor (GR). Consistent with the GR findings, OC2 regulated genes on the AR cistrome previously shown to be regulated by GR in CRPC, including KLK3/PSA. OC2 activated bivalent promoters of master regulator genes via epigenetic modification, and reprogramed multiple super-enhancers, including those associated with TMPRSS2 and SRRM4. OC2-expressing cells in human CRPC included populations that express AR, NE+/stem-like+, NE-/stem-like+, and “double negative” (NE-/AR-) phenotypes. OC2 also transcriptionally upregulated UDP-glucuronosyltransferase enzymes UGT2B15 and UGT2B17, which inactivate DHT, suggesting that the emergence of phenotypic plasticity also arises from AR suppression by ligand depletion. Consistent with this, low levels of androgen correlated with OC2 activation in human CRPC tumors. Enforced OC2 promoted both enzalutamide and docetaxel resistance in PC models. CONCLUSIONS. These findings identify OC2 as an upstream mediator of many lineage-defining factors that govern drug resistance, including those associated with adenocarcinoma. Because OC2 can be inhibited pharmacologically, these results suggest that suppressing this target may inhibit the emergence of a wide range of drug resistance mechanisms arising from loss of lineage confinement.
Citation Format: Chen Qian, Qian Yang, HyoYoung Kim, Yiwu Yan, Elahe Mostaghel, Leigh Ellis, Beatrice Knudsen, Salma Kaochar, Huihui Ye, Isla Garraway, Sungyong You, Michael Freeman. ONECUT2 activates diverse drug-resistant phenotypes in prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr B014.
Abstract B022: Dopamine receptor antagonists sensitize prostate cancer cells to androgen targeted therapy
Authors: Zhang Le , Billet Sandrine , Gonzales Gabrielle , Rohena-Rivera Krizia , Muranaka Hayato , Lee Yeonjoo , You Sungyong , Posadas Edwin M. , Bhowmick Neil A. 
Published: June 2023

Abstract
Prostate cancer (PC) incidence is predicted to reach around 2 million new cases by 2040. High fat diet and obesity are associated with the progression and mortality of PC. Palmitate is a common saturated fatty acid, it induces endoplasmic reticulum (ER) stress that activates the unfolded protein response (UPR). Failure to adapt to ER stress results in apoptosis to eliminate irreversibly damaged cells. Master regulator analysis found that Arid5a was a master regulator of saturated fat-induced cellular responses. We confirmed that exogenous palmitate activated ARID5a/UPR signaling, while further activation could induce apoptosis. In trying to determine the mechanism of ARID5a activation, we found that palmitate promoted the expression of dopamine receptors 2 and 3 (DRD2, DRD3) in prostate cancer cell lines. Since high diets have other deleterious effects, we tested the role of dopamine receptor antagonists (e.g. ONC201, prochlorperazine) and found them to serve as UPR activators, inducing apoptosis in ARCaPM and 22Rv1 cells. As our data showed that ARID5a expression could inhibit prostate-specific membrane antigen (PSMA), we next tested the role of dopamine receptor antagonists in sensitizing castrate resistant cells to androgen targeted therapy. Both castrate resistant cell lines (22Rv1 and ARCaPM) were found to be made sensitive to enzalutamide by dopamine inhibition, inhibiting cell proliferation and promoting apoptosis. These findings are especially compelling since dopamine receptor antagonist, prochlorperazine, is a commonly prescribed anti-nausea drug and ONC201 is currently in clinical trials meeting safety endpoints. Preclinical studies in mouse models of castrate resistant PC support the administration of such dopamine receptor antagonists with androgen targeted therapy to sensitize otherwise refractile tumors by the promotion of ER stress pathway, addressing a common adaptation mechanism employed by cancer cells.
Citation Format: Le Zhang, Sandrine Billet, Gabrielle Gonzales, Krizia Rohena-Rivera, Hayato Muranaka, Yeonjoo Lee, Sungyong You, Edwin M. Posadas, Neil A. Bhowmick. Dopamine receptor antagonists sensitize prostate cancer cells to androgen targeted therapy [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr B022.
Abstract B029: Foxf2 activates antitumor immunity to repress the progression of prostate cancer by repressing Fgl1
Authors: Jia Deyong , Zhou Zhicheng , Kwon OhJoon , Xin Li 
Published: June 2023

Abstract
Targeting immune suppressive mechanisms in the tumor microenvironment has revolutionized cancer treatment. Although immune checkpoint inhibition (ICI) has yielded meaningful responses across many cancer types, the ICI efficacy is still limited for prostate cancer. We generated a mouse model with prostate epithelial specific expression of Foxf2, a Forkhead box transcription factor. Foxf2 overexpression suppressed tumor growth in two mouse models for prostate cancer with prostate specific Pten deletion or TRAMP. Foxf2 expression strongly induced tumor cell-intrinsic immune responses by recruiting and activating CD8+ T cells and switching the polarization of macrophages from an immunosuppressive M2-like phenotype to a more inflammatory M1-like state in both syngeneic and autochthonous mouse prostate cancer models in an immunocompetent context. Furthermore, we showed that overexpression of Foxf2 in mouse and human prostate cells repressed the expression of FGL1, a major ligand of LAG-3 that mediates T cell suppression. In this study, we take a combination of bioinformatic, molecular, cellular, and genetic approaches and reveal that Foxf2 overexpression in prostate cancer suppresses tumor progression by activating antitumor immunity.
Citation Format: Deyong Jia, Zhicheng Zhou, OhJoon Kwon, Li Xin. Foxf2 activates antitumor immunity to repress the progression of prostate cancer by repressing Fgl1 [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr B029.
Abstract B033: Probing the role of hypoxia and the tumor microenvironment at spatially resolved single cell resolution in prostate cancer disease trajectories
Authors: Mikutenaite Migle , Karadoulama Evdoxia , Simon Ronald , Minner Sarah , Bristow Robert , Sauter Guido , Schlomm Thorsten , Weischenfeldt Joachim L. 
Published: June 2023

Abstract
Prostate cancer (PCa) is the second most common cancer in men. Most patients will not develop aggressive disease, and a main challenge is to distinguish those patients that can be put on surveillance strategies from those that require definite treatment. Identifying robust prognostic and predictive biomarkers from tumor biopsies have been challenging due to the intra-tumor heterogeneity (ITH) and long life-history of the disease. Several components of the tumor micro-environment (TME) have been associated with shorter time to biochemical relapse and time to metastasis, but these analyses have mostly been based on single sample analysis, thus neglecting the high degree of ITH in PCa. Here, we performed pathology-guided 3D spatial sampling of PCa, followed by multi-layered genomic and transcriptomic profiling. Using single-cell sequencing from multiple distinct areas from each patient, we find both genomic, transcriptional and cellular ITH. We identify “pockets” of the tumor associated with markers of hypoxia and oxidative phosphorylation, and that these are associated with specific tumor and stromal cell-types. Using copy-number based analysis, our data reveal clonal evolution patterns at the single-cell level, pointing towards the earliest clonal populations, and our data supports an interplay between clonal evolution and tumor-promoting TMEs.
Citation Format: Migle Mikutenaite, Evdoxia Karadoulama, Ronald Simon, Sarah Minner, Robert Bristow, Guido Sauter, Thorsten Schlomm, Joachim L. Weischenfeldt. Probing the role of hypoxia and the tumor microenvironment at spatially resolved single cell resolution in prostate cancer disease trajectories [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr B033.
Abstract IA002: Genomic and epigenomic regulation during prostate cancer progression
Authors: Yu Jindan 
Published: June 2023

Abstract
Prostate cancer (PCa) development and progression are controlled by aberrant expression, mutation, and function of essential transcriptional factors and epigenetic modifiers. Over the years, our work has delineated the molecular mechanisms by which androgen receptor (AR) and Polycomb Repressive Complex 2 (PRC2) protein EZH2 regulate PCa progression in concert with other key transcriptional factors such as TMPRSS2-ERG and FOXA1. We recently found that HOXB13, a homeodomain transcription factor primarily known as a pioneering factor of AR, plays an AR-independent role in inhibiting cancer metabolism and tumor metastasis. An important function that is mediated by its interaction with the HDAC3-NCoR corepressor complex, which is disrupted by the PCa risk-associated HOXB13 G84E mutation. On the other hand, we characterize the unique roles of PALI1, a newly identified PRC2-accessory protein, in mediating molecular crosstalk between PRC2 and G9A proteins to catalyze dual H3K27 and H3K9 methylation at target loci. Thus, PALI1 enforces strong repression of differentiation genes, rendering cell stemness and cancer progression. Our findings laid the foundations for the development of several new therapeutic strategies for the treatment of advanced PCa.
Citation Format: Jindan Yu. Genomic and epigenomic regulation during prostate cancer progression [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr IA002.
Abstract IA007: Science of prostate cancer care and survivorship in black men: Structural, social and biological determinants
Authors: Odedina Folakemi , Dronca Roxana , Ashing Kimlin , Kaninjing Ernest , Rotimi Solomon , Ngufor Che ,   Arnold Merriweather, iCCaRE Consortium
Published: June 2023

Abstract
Black men are disproportionately affected by prostate cancer (CaP), with limited progress in closing the CaP care and survivorship gaps experienced by Black men compared to other racial/ethnic groups. Unfortunately, there is an uptick in CaP incidence rate in the United States (US) since 2014. As reported by the American Cancer Society, the rising CaP incidence rate indicates a shift towards higher grade and stage during diagnosis. The prostate cancer (CaP) disparities experienced by Black men in the US is a microcosm of the global burden of CaP seen in men of African ancestry. For example, the top ten countries leading CaP mortality in the world are all Black nations in Africa and the Caribbean. The complexity of CaP disparities and the need for a unique approach to better understand and address a complex chronic disease, such as CaP, underscores the need for consortium research that is multilevel, collaborative, translational, and global. Through the Department of Defense funding, we formed an inclusive Cancer Care Research Equity (iCCaRE) for Black Men Consortium to advance health equity and reduce disparities in CaP.
Comprising CaP survivors, advocates, scientists, and clinicians, the iCCaRE for Black Men Consortium addresses structural, social and biological determinants of CaP among ethnically diverse Black men globally, including US Black men, West African immigrant men in the US and indigenous West African men. The overall goal of the iCCaRE consortium is to optimize CaP diagnosis experiences, treatment and survivorship based on the Science of Survivorship (SOS). Our central hypothesis is that improving social-determinants of health (SDOH) factors, CaP care and survivorship (CaPCaS)-related factors and mediating biological factors will lead to an improvement in patient-reported outcomes (PROs). This presentation will highlight the structural inequities, societal injustices and biological determinants found to be associated with CaP care and survivorship among Black men. Additionally, we will present the use of Community Living Lab (CoLLab) Health System approach to address inequity in minoritized and marginalized communities.
Citation Format: Folakemi Odedina, Roxana Dronca, Kimlin Ashing, Ernest Kaninjing, Solomon Rotimi, Che Ngufor, Arnold Merriweather, iCCaRE Consortium. Science of prostate cancer care and survivorship in black men: Structural, social and biological determinants [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr IA007.
Abstract IA012: Modeling prostate cancer metastasis in genetically engineered mouse models
Authors: Abate-Shen Cory , Giacobbe Arianna , Obradovic Aleksandar , Vasciaveo Alessandro , Picech Florencia , Ronaldson-Bouchard Kacey , Vunjak-Novakovic Gordana , Shen Michael M. , Califano Andrea , Sims Peter 
Published: June 2023

Abstract
My laboratory has a longstanding interest in developing mouse models of prostate cancer that recapitulate the broad spectrum of prostate cancer phenotypes. We have been employing state-of-the-art systems biology approaches to integrate molecular data from our mouse models with comparable data from human prostate cancer, with the ultimate goal of informing patient care. This is exemplified by our recent description of OncoLoop, a transcriptomic framework that can support rapid-turnaround co-clinical studies to identify and validate drugs for individual patients. Our current studies have largely focused on modeling metastatic prostate cancer, particularly metastasis to bone. We have generated genetically engineered mouse models, as well as syngeneic allograft models, that model bone metastasis with high penetrance. In addition, we are employing an “organ-on-a-chip” platform that simulates bone tropism. We are using these models to decipher the molecular mechanisms that drive metastatic dissemination and bone metastasis. My presentation at this AACR conference will focus on how we have been using these various models to study circulating tumor cells (CTCs). In particular, I will describe our recent studies in which we have been using single-cell sequencing of CTCs and have generated CTC-derived organoids to interrogate mechanisms that drive dissemination and metastasis.
Citation Format: Cory Abate-Shen, Arianna Giacobbe, Aleksandar Obradovic, Alessandro Vasciaveo, Florencia Picech, Kacey Ronaldson-Bouchard, Gordana Vunjak-Novakovic, Michael M. Shen, Andrea Califano, Peter Sims. Modeling prostate cancer metastasis in genetically engineered mouse models [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr IA012.
Abstract IA020: Senescence in cancer and myeloid cells control prostate cancer progression
Authors: Alimonti Andrea 
Published: June 2023

Abstract
Recent evidence demonstrates that senescence can act as a tumor-suppressive or tumor-promoting mechanism in cancer. Here, I will discuss recent findings demonstrating that cellular senescence can promote metastases formation in prostate cancer and that therapies that eliminate senescent tumor cells (senolytics) or reprogram the SASP (senostatics) can efficiently prevent metastases in different mouse models. Moreover, I will present recent data demonstrating that senescence can occur in tumor-infiltrating myeloid cells (PMN-MDSCs). As previously reported, this population of immune cells can support prostate tumor proliferation through different mechanisms. Senescent-like myeloid cells express TREM2, are more immunosuppressive and tumor-promoting, and have an increased lifespan than canonical PMN-MDSCs. Genetic and pharmacological elimination of senescent-like myeloid cells decreases tumor progression in different mouse models of prostate cancer. These results support the development of senolytics targeting cancer and senescent-like myeloid cells for cancer therapy.
Citation Format: Andrea Alimonti. Senescence in cancer and myeloid cells control prostate cancer progression [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr IA020.
Prediction of Shock-Refractory Ventricular Fibrillation During Resuscitation of Out-of-Hospital Cardiac Arrest
Authors: Coult Jason , Yang Betty Y. , Kwok Heemun , Kutz J. Nathan , Boyle Patrick M. , Blackwood Jennifer , Rea Thomas D. , Kudenchuk Peter J. 
Published: June 2023

BACKGROUND:
Out-of-hospital cardiac arrest due to shock-refractory ventricular fibrillation (VF) is associated with relatively poor survival. The ability to predict refractory VF (requiring ≥3 shocks) in advance of repeated shock failure could enable preemptive targeted interventions aimed at improving outcome, such as earlier administration of antiarrhythmics, reconsideration of epinephrine use or dosage, changes in shock delivery strategy, or expedited invasive treatments.

METHODS:
We conducted a cohort study of VF out-of-hospital cardiac arrest to develop an ECG-based algorithm to predict patients with refractory VF. Patients with available defibrillator recordings were randomized 80%/20% into training/test groups. A random forest classifier applied to 3-s ECG segments immediately before and 1 minute after the initial shock during cardiopulmonary resuscitation was used to predict the need for ≥3 shocks based on singular value decompositions of ECG wavelet transforms. Performance was quantified by area under the receiver operating characteristic curve.

RESULTS:

Of 1376 patients with VF out-of-hospital cardiac arrest, 311 (23%) were female, 864 (63%) experienced refractory VF, and 591 (43%) achieved functional neurological survival. Total shock count was associated with decreasing likelihood of functional neurological survival, with a relative risk of 0.95 (95% CI, 0.93–0.97) for each successive shock (
P
<0.001). In the 275 test patients, the area under the receiver operating characteristic curve for predicting refractory VF was 0.85 (95% CI, 0.79–0.89), with specificity of 91%, sensitivity of 63%, and a positive likelihood ratio of 6.7.

CONCLUSIONS:
A machine learning algorithm using ECGs surrounding the initial shock predicts patients likely to experience refractory VF, and could enable rescuers to preemptively target interventions to potentially improve resuscitation outcome.
Automatic Ischemic Core Estimation Based on Noncontrast-Enhanced Computed Tomography
Authors: Nishi Hidehisa , Ishii Akira , Tsuji Hirofumi , Fuchigami Takuya , Sasaki Natsuhi , Tachibana Atsushi , Ito Hirotaka , Miyamoto Susumu 
Published: June 2023

BACKGROUND:
Evaluating the extent of ischemic change is an important step in deciding whether to use thrombolysis or mechanical thrombectomy, but the current standard method, Alberta Stroke Program Early CT Score, is semiquantitative and has low consistency among raters. We aim to create and test a fully automated machine learning–based ischemic core segmentation model using only noncontrast-enhanced computed tomography images.

METHODS:
In this multicenter retrospective study, patients with anterior circulation acute ischemic stroke who received both computed tomography (CT) and magnetic resonance imaging before thrombolysis or recanalization treatment between 2013 and 2019 were included. On CT, the ischemic core was manually delineated using the diffusion-weighted image and apparent diffusion coefficient maps. A deep learning–based ischemic core segmentation model (DL model) was developed using data from 3 institutions (n=272), and the model performance was validated using data from 3 institutions (n=106

RESULTS:

The median time ).between CT and magnetic resonance imaging in the validation cohort was 18 min. The DL model calculated ischemic core volume was significantly correlated with the reference standard (intraclass correlation coefficient, 0.90,
P
<0.01). Both the early time window (≤4.5 hours from onset; intraclass correlation coefficient, 0.90,
P
<0.01) and the late time window (>4.5 hours from onset; intraclass correlation coefficient, 0.93,
P
<0.01) had significant correlations. The median difference in ivolume between the model and the reference standard was 4.7 mL (interquartile range, 0.8–12.4 mL). The DL model performed well in distinguishing large ischemic cores (>70 mL), with a sensitivity of 84.2%, specificity of 97.7%, and area under the curve of 0.91.

CONCLUSIONS:
The deep learning–based ischemic core segmentation model, which was based on noncontrast-enhanced CT, demonstrated high accuracy in assessing ischemic core volume in patients with anterior circulation acute ischemic stroke.