bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 3816: Functional atlas of prostate mesenchyme
Authors: Pakula Hubert , Carelli Ryan , Fanelli Nicolo , Jere Madhavi , Unkenholz Caitlin , Omar Mohamed , Fidalgo Caroline Ribeiro- , Pederzoli Filippo , Abate-Shen Cory , Rickman David S. , Robinson Brian , Marchionni Luigi , Loda Massimo 
Published: June 2022

Abstract
Prostate cancer has a heterogeneous prognosis, and genetic alterations alone do not fully explain clinical behavior. We previously characterized the stroma of localized human prostates by Laser Capture Microdissection, and found that stroma was substantially different in prostates with and without tumor. Furthermore, a stromal gene signature reflecting bone remodeling was upregulated in high compared to low Gleason grade cases. To determine how stromal cells contribute to carcinogenesis and progression we study whether specific genetic alterations in the epithelium induce unique stromal changes. To do this, we utilized Genetically Engineered Mouse Models (GEMMs) representing common prostate cancer mutations and compared these to their wild-type conterparts: the Tmprss2-ERG fusion knock-in murine model induces histological alterations in the stroma in the absence of an epithelial phenotype; the Pten deletion mouse model (PtenKO) results in prostate intraepithelial neoplasia (PIN) but not invasive cancer; the Hi-Myc GEMM, leads to PIN and subsequently invasion; and the Pb4-Cre +/-;Pten f/f; LSL-MYCN +/+; Rb1 f/f (MNRPDKO) mouse model that leads to neuroendocrine prostate cancer (NEPC). We generated a comprehensive single-cell transcriptomic atlas of the mouse prostate cancer mesenchyme in these models. Using deep generative modeling followed by graph-based clustering and gene regulatory network inference, six (6) distinct subsets of fibroblasts and two (2) subsets of smooth muscle cells (myofibroblasts and pericytes) were identified. Notably, some subsets were common across all GEMMs and WT mice, while others aligned with specific genotypes. Moreover, we found a variable pattern of positive and negative Ar expressing cells between genotypes. Analysis by CellphoneDB of mesenchymal-epithelial communications revealed the complex cross-talk between mutated epithelial cells and the tumor microenvironment. Multiplex immunofluorescence phenotyping of mesenchymal cell confirmed the cluster subtypes by both expression and spatial location. Finally, stromal transcripts defining mesenchymal cluster subtypes associated with Tmprss2-ERG were conserved between mouse and human genotypes.This study lays the groundwork for understanding and ultimately targeting stromal-epithelial interactions in prostate cancer.
Citation Format: Hubert Pakula, Ryan Carelli, Nicolo Fanelli, Madhavi Jere, Caitlin Unkenholz, Mohamed Omar, Caroline Ribeiro- Fidalgo, Filippo Pederzoli, Cory Abate-Shen, David S. Rickman, Brian Robinson, Luigi Marchionni, Massimo Loda. Functional atlas of prostate mesenchyme [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3816.
Abstract 384: Lipid nanoparticle aided delivery of a STING agonist to treat pancreatic cancer
Authors: Shaji Sherin George , Patel Pratikkumar , Cheng Kun 
Published: June 2022

Abstract
The tumor microenvironment (TME) of pancreatic cancer is highly immunosuppressive and characterized by a huge population of cancer-associated fibroblasts, myeloid-derived suppressor cells, regulatory T cells, and a scarce number of effector immune cells. Stimulator of interferon genes (STING) is an endoplasmic reticulum receptor that plays a critical role in immunity. Agonists of STING have been shown to inflame the TME, reduce tumor burden and confer anti-tumor activity in mouse models. 2’, 3’ cyclic guanosine monophosphate adenosine monophosphate (cGAMP) is a high-affinity endogenous ligand of STING. However, the cytosolic delivery of exogenous cGAMP to antigen-presenting cells and tumor cells remains a challenge due to poor cellular permeability, poor stability, and rapid clearance. We address these limitations by encapsulating cGAMP in a lipid nanoparticle (cGAMP-LNP) engineered for efficient cytosolic delivery. The size and morphology of the cGAMP-LNP were characterized using dynamic light scattering and TEM, respectively. The in-vitro activity of the cGAMP-LNP was determined in the THP-1 Blue࣪ ISG reporter cell line, whereas the endosomolytic activity of the LNP was evaluated by red blood cell hemolysis assay. The cGAMP-LNP activates the IRF3 pathway in-vitro and shows concentration- and pH-dependent endosomolytic activity. Moreover, the cGAMP-LNP was evaluated for cytotoxicity in-vitro and were found non-toxic to human pancreatic duct epithelial cell line at bioactive concentrations. Collectively, the cGAMP-LNP represents a promising strategy to convert immunosuppressive pancreatic cancer to immune-inflamed pancreatic cancer.
Citation Format: Sherin George Shaji, Pratikkumar Patel, Kun Cheng. Lipid nanoparticle aided delivery of a STING agonist to treat pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 384.
Abstract 3862: Microbial immunomodulation for enhancing immunotherapeutic efficacy in a patient-specific colorectal cancer chip
Authors: Shin Yong Cheol , Wu Alexander , Min Soyoun , Kim Daesung , Shin Woojung , Eckhardt S. Gail , Fleming R. Y. Declan , Kim Hyun Jung 
Published: June 2022

Abstract
Immune checkpoint inhibitors (ICI) targeting PD-1, PD-L1, or CTLA-4 have shown remarkable therapeutic outcomes in various cancers. However, the therapeutic efficacy of ICI-based immunotherapy in microsatellite stable (MSS) colorectal cancer (CRC) has been extremely limited. Recent studies strikingly revealed that the human gut microbiome controls the efficacy of immune checkpoint blockades. Yet, the effect of the gut microbiome on reinforcing the ICI efficacy in MSS tumors in CRC is unknown. Here, we suggest a microengineered CRC Chip that recapitulates the tumor microenvironment of individual CRC patients by introducing biopsy-derived colonic organoid epithelium. We have built a three-dimensional (3D) lumen-capillary interface under peristalsis-like motions and flow in an oxygen-controlled microenvironment. We leverage this pathomimetic CRC Chip to recapitulate the patient-specific tumor-microbiome-immune axis to demonstrate microbial immunomodulation on the tumor cells and cytotoxic tumor immunity. We co-cultured various human intestinal bacteria in a CRC Chip to assess the immunomodulatory contribution to the tumor epithelium. We found that living Bifidobacterium sp. significantly reduces the PD-L1 on the tumor surface, followed by elevated anti-tumor activity after CD8 T cell-mediated cytotoxic interactions. We envision that our CRC Chip model can potentially reduce the knowledge gap between the bench and bedside. Furthermore, our innovative CRC Chip model may potentially offer a platform to validate the “Druggable microbiome” and the utility of the patient’s avatar model for Precision Medicine.
Citation Format: Yong Cheol Shin, Alexander Wu, Soyoun Min, Daesung Kim, Woojung Shin, S. Gail Eckhardt, R. Y. Declan Fleming, Hyun Jung Kim. Microbial immunomodulation for enhancing immunotherapeutic efficacy in a patient-specific colorectal cancer chip [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3862.
Abstract 3876: The importance of spatial analysis and multispectral imaging when evaluating tumor-immune interactions in glioblastoma
Authors: Haggerty Agnes E. , Mammadova Najiba , Barish Michael E. , Brown Christine E. 
Published: June 2022

Abstract
Glioblastoma (GBM) is an aggressive and almost universally fatal brain cancer. Glioblastoma tumor masses are highly vascularized and infiltrated with cells mediating both innate and adaptive immunity. The presence and organization of various immune cells within the tumor microenvironment varies between patients and within individual tumors. This variability in the immune landscape influences responses to different treatment modalities, including immunotherapies. Understanding reciprocal immune-tumor cell interactions will enhance design and implementation of novel therapies. Currently, review of GBM patient tissues by neuropathologists is done visually using single or low-plex biomarker panels whose complexity is constrained by limitations of traditional immunohistochemistry, including the lack of well characterized primary antibody clones, limited antibody selection due to species-dependent workflows, and inaccuracies such as false signal intensities introduced by autofluorescence (AF) and spectral overlap from traditional immunofluorescence imaging methods. Multiplex immunofluorescence (mIF) and multispectral imaging (MSI) allows for fast, accurate imaging on a single tissue section of up to eight fluorophores (using Phenoptics technology), cell type-specific AF spectra, and DAPI/Hoechst. It has been shown in other cancer types (i.e. lung cancer, breast cancer, melanoma) that spatial biology techniques including multiplex immunofluorescence is necessary to determine cellular densities and interactions in tissue context to better predict outcomes and stratify patient populations. Here, we have used pre-validated mIF kits that use Opal fluorophores together with the Vectra Polaris Automated Quantitative MSI system on human formalin-fixed, paraffin embedded GBM tissue samples to further characterize immune-tumor microenvironments, with consideration for spatial distributions of interacting cells. Pre-optimized immunofluorescent kits targeting immune cell subsets, checkpoint inhibitors, and other biomarkers have been shown to provide clinically relevant information in other cancer types (such as lung cancer and melanoma). Our study indicates that widespread use of these reagents, coupled with spatial analysis and complex phenotyping, would better characterize the complex immune landscape of tumors and enhance design and implementation of therapeutics for GBM.
Citation Format: Agnes E. Haggerty, Najiba Mammadova, Michael E. Barish, Christine E. Brown. The importance of spatial analysis and multispectral imaging when evaluating tumor-immune interactions in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3876.
Abstract 388: AI/ML-driven discovery of a novel proteoglycan for precision targeting of ADCs for disruption of stromal barriers and direct anti-tumor activity
Authors: Koch Elizabeth , London Max , Berkley Amy , Nixon Allison , Phippen Sean , White Kerry , Hanson Amanda , Cooper Samuel , Harvey Christopher , Briskin Michael 
Published: June 2022

Abstract
Background: While checkpoint inhibitors (CPIs) such as anti-CTLA-4 and anti-PD-1/L1 have demonstrated efficacy in a number of solid tumor indications, those with high stromal presence have been difficult to treat with minimal response observed. We aimed to use a proprietary machine learning/artificial intelligence platform to identify novel stromal targets to relieve this immunosuppressive barrier and increase CPI responsiveness in difficult to treat indications.
Methods: Based on bioinformatic analysis using our single cell RNA atlas, we assessed cancer-associated fibroblasts (CAFs)/fibroblastic cells in cancer tissue for identification of novel targets, including proteoglycans. Antibodies were generated by immunization of humanized mice, and lead antibodies were tested for activity in inhibiting cell adhesion and were further characterized for staining of both CAFs as well as tumor cells. ADCs were developed and tested in vitro for selective tumor cell killing.
Results: Bioinformatic analysis identified a unique subset of cancer-associated fibroblasts, termed ecmCAFs, which demonstrated selective expression of Collagen Triple Helix Repeat Containing 1 (CTHRC1). This highly-selective expression pattern suggests it may be ideal as a target for alternative modalities, including ADC targeting or specific T cell activation. In addition, we identified that in certain tumor types, such a triple negative breast cancer and pancreatic ductal adenocarcinoma (PDAC), CTHRC1 is also highly expressed by cancer cells within the tumor and shows a more favorable expression profile for ADC targeting when compared to other stromal proteins such as FAP and LRRC15. We have confirmed surface expression and binding of CTHRC1 by our lead antibodies and have observed robust internalization on both human and mouse cancer cell lines. In vitro killing of tumor cells by ADCs and in vivo PD and efficacy will be presented on both ADCs and naked antibodies.
Conclusions: We have identified CTHRC1 as a novel proteoglycan expressed by both ecmCAFs and tumor cells that appears to be an ideal target for both direct inhibition of stromal barrier function as well as targeting of cytotoxic payloads as an ADC. CTHRC1 expression is more selective than the classical markers FAP and LRRC15, both of which have been previously developed as ADCs.
Citation Format: Elizabeth Koch, Max London, Amy Berkley, Allison Nixon, Sean Phippen, Kerry White, Amanda Hanson, Samuel Cooper, Christopher Harvey, Michael Briskin. AI/ML-driven discovery of a novel proteoglycan for precision targeting of ADCs for disruption of stromal barriers and direct anti-tumor activity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 388.
Abstract 3891: Efficacy of dinaciclib in hepatoblastoma through inhibition of cyclin dependent kinases
Authors: Srivastava Rohit K. , Patel Roma , Espinoza Andres F. , Yu Yang , Whitlock Richard S. , Larson Samuel , Badachhape Andrew , Yang Jianhua , Woodfield Sarah E. , Vasudevan Sanjeev A. 
Published: June 2022

Abstract
Introduction: Hepatoblastoma (HB) is the most frequent liver malignancy of childhood with an annual incidence of 1.5 per million and a survival rate less than 50%. Due to significant side effects and ineffectiveness of standard chemotherapy for relapse refractory disease, the treatment options are now shifting towards targeted therapies. Cyclin-dependent kinases (CDKs) are potential cancer therapeutic targets because of their critical role in promoting cell growth and regulating transcriptional processes. This study aims to assess the therapeutic efficacy of dinaciclib, cyclin-dependent kinase inhibitor, with HB in preclinical in vitroand in vivo models.
Method: Dinaciclib was tested in patient derived cell lines (PDCL) from different patient derived xenograft (PDX) models using CellTiter-Glo Luminescent Viability assays. Dinaciclib was also assayed in vitro for cytotoxicity (MTT assay) and proliferation (CCK-8 assay). Differential expression of CDKs was checked by microarray analysis between normal liver and HB patients. Results were confirmed by immunoblotting assays. Immunoblotting assays were also used to see the effect of dinaciclib on CDK 1/2/5/9 and to assess the induction of apoptosis (PARP cleavage) in vitro. Dinaciclib was also tested in our orthotopic PDX models of high-risk HB. MRI and alpha-fetoprotein (AFP) ELISA were done to evaluate tumor growth. Tumor weights and volumes, as well as, immunohistochemistry were also used to assess effects of dinaciclib in vivo.
Result: Dinaciclib suppressed cell proliferation and viability in a dose-dependent manner in all HB cell lines tested with IC50 in the low micromolar range (HepG2- 3.75; HepT1- 0.007; Huh6- 1.42; HB17- 0.72). Microarray analysis showed significant upregulation of CDK1 (p=0.0003), CDK2 (p=0.00023) and CDK9 (p=0.015) in HB patient samples, however, immunoblotting with dinaciclib-treated cells showed decreased expression of CDKs 1/2/5/9 as well as induction of apoptosis. Dinaciclib also showed in vivo inhibition of tumor growth compared to placebo in both PDX models (HB47: relative tumor volume p = 0.03, T/C ratio= 0.36, tumor weight p = 0.02; HB52: relative tumor volume p = 0.06, T/C ratio= 0.16, tumor weight p = 0.07).
Conclusion: Dinaciclib treatment showed promising effects with preclinical HB cell lines and PDX models.
Citation Format: Rohit K. Srivastava, Roma Patel, Andres F. Espinoza, Yang Yu, Richard S. Whitlock, Samuel Larson, Andrew Badachhape, Jianhua Yang, Sarah E. Woodfield, Sanjeev A. Vasudevan. Efficacy of dinaciclib in hepatoblastoma through inhibition of cyclin dependent kinases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3891.
Abstract 3892: High-throughput combination screen for identifying novel therapies against high-risk neuroblastoma
Authors: Radke Katarzyna , Hansson Karin , Saarela Jani , Ianevski Aleksandr , Ianevski Philipp , Baudet Aurélie , Magnusson Mattias , Bexell Daniel 
Published: June 2022

Abstract
Neuroblastoma is a childhood solid tumor commonly located in the adrenal gland. High-risk neuroblastoma patients undergo multidrug and multi-interventional treatment but despite these efforts many patients develop resistance to chemotherapy and eventually relapse. Neuroblastoma patients face an urgent need of novel therapeutic strategies that could effectively combat the disease.
In a recent study we identified kinesin spindle protein (KSP) as a highly effective target in high-risk neuroblastoma. Pharmacological inhibition of KSP resulted in complete regression of a subset of neuroblastoma subcutaneous PDX tumors and tumor growth delay in orthotopic PDXs (Hansson, Radke et al, Sci. Transl. Med 2020). The purpose of the present study is to identify novel synergistic drug combinations effective against neuroblastoma and investigate their translational potential. We designed, optimized, and performed a high-throughput combination screen using 3D tumor organoids that represent three MYCN-amplified neuroblastoma tumors. KSP inhibition was tested in combination with the FIMM drug set of 527 approved and investigational drugs.
Screening was performed stepwise:
• Step 1: High-throughput drug screening 527 drug combinations and machine learning prediction (DECREASE tool) of drug combination synergy based on minimal required input.
• Step 2: Screening of 6x6 dose-response matrices of top 26 predicted hits in high-risk neuroblastoma models.
• Step 3: Screening of 6x6 dose-response matrices of top 26 hits in CD34+ cord blood controls to identify compounds that have low toxicity towards proliferating fraction of hematopoietic cells.
Overall, we identified seven drug candidates (P1-P7). They classify as: kinase inhibitors, differentiating modifiers, and one hormone therapy. Screened combinations were chosen based on selective efficacy (difference between anti-neuroblastoma efficacy and efficacy towards CD34+ cord blood controls). Identified drug combinations are common among three high-risk neuroblastoma models and have most synergistic area score (MSA) over five. We further plan to validate seven hits in neuroblastoma models in vitro, investigate MOA of the most promising combination and test it in PDX models in vivo.
Citation Format: Katarzyna Radke, Karin Hansson, Jani Saarela, Aleksandr Ianevski, Philipp Ianevski, Aurélie Baudet, Mattias Magnusson, Daniel Bexell. High-throughput combination screen for identifying novel therapies against high-risk neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3892.
Abstract 3921: Precise spatial multiplexing for immune profiling in clinical FFPE tumor samples with ChipCytometry࣪
Authors: Gamber Kevin , Christians Arne , Brooks Jennifer , Kwarta Karen , Winkeler Crystal 
Published: June 2022

Abstract
Highly multiplexed spatial biomarker analysis has the potential to inform the discovery of novel biomarkers and treatments with the potential to improve clinical outcomes. Clinical diagnoses and treatment decisions have traditionally been made with spatially resolved techniques like immunohistochemistry, that offer a wealth of information about cellular morphology and the spatial context of cells but are limited to a single plex. Newer technologies, such as single-cell RNA sequencing, identify cell subpopulations within tissue but do not capture their spatial distribution or intercellular interactions in situ. Here we present the analysis of clinical FFPE tumor samples using ChipCytometry, a novel precise spatial multiplexing technology that offers high-plex biomarker analysis, without compromising spatial context. ChipCytometry combines iterative immuno-fluorescent staining with high-dynamic range imaging to facilitate quantitative phenotyping with single-cell resolution. Standard FCS files are generated from multichannel OME-TIFF images, enabling identification of cellular phenotypes via flow cytometry-like hierarchical gating. In this study, we identify and quantify immune and epithelial cell phenotypes and subtypes in melanoma and non-small cell lung cancer FFPE samples. The results show precise expression levels for each marker in the assay in each individual cell in the sample, while maintaining spatial information about each cell. Spatial analysis of the samples reveals quantifiable heterogeneity of immune cell infiltration within the tumor samples, demonstrating the utility of the ChipCytometry platform for the in-depth immune profiling in clinical FFPE samples.
-Bruker Confidential-
Citation Format: Kevin Gamber, Arne Christians, Jennifer Brooks, Karen Kwarta, Crystal Winkeler. Precise spatial multiplexing for immune profiling in clinical FFPE tumor samples with ChipCytometry࣪ [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3921.