bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 4148: Immunophenotyping of responses to immunotherapy in syngeneic tumor models using multiplex immunofluorescence compared to multiparametric flow cytometry
Authors: Metzger Philipp , Castro Carla , Obodozie Cynthia , Weber Holger 
Published: April 2023

Abstract
In the last decades, several major breakthroughs in cancer treatment were achieved through a better understanding and therapeutic targeting of the immune system. Multiparametric flow cytometry is a robust and powerful tool to evaluate the frequency and activation status of a large variety of immune cells. However, for flow cytometric analysis tumor, tissue must be digested into a single cell suspension, and thereby the information on the tumor architecture as well as the spatial distribution of immune cells is lost. The distribution of immune cells in the tumor microenvironment is often heterogeneous and a favorable immune cell distribution is crucial for an efficacious anti-tumor immunotherapy. The recent advances in multiplex immunofluorescence (mIF) allows the analysis of multiple parameters simultaneously so that the frequency as well as the spatial distribution of multiple immune cells can be analyzed.
In this study, immunotherapy-responsive tumor cell lines (colon carcinoma cell lines MC38-CEA and CT26wt as well as melanoma cell line Clone M3) were implanted in the mammary fat pad (subQperiorTM), which leads to reduce ulceration rate and homogenous tumor growth compared to subcutaneous implantation. Anti-PD-1 immunotherapy reduced the tumor growth in all three tumor models significantly. Formalin-fixed paraffin-embedded tumor samples were collected from control and anti-PD-1 treated animals. Murine specific InSituPlex® (ISP) technology (Ultivue) was used to perform multiplex immune profiling of the markers CD3, CD4, CD8 and FOXP3 on mouse whole slide FFPE tumor serial sections. Slides were then imaged for high quality images of the four targets and downstream analysis performed. The evaluated T cell frequency and spatial distribution was compared to flow cytometric data of anti-PD-1 treatment in these models.
In summary, flow cytometry and multiplex immunofluorescence (mIF) are valuable tools in the evaluation of immune responses in pre-clinical tumor models. Both technologies enable an improved understanding of treatment responses and facilitate the development of novel treatment modalities as well as the identification of potential predictive biomarkers.
Citation Format: Philipp Metzger, Carla Castro, Cynthia Obodozie, Holger Weber. Immunophenotyping of responses to immunotherapy in syngeneic tumor models using multiplex immunofluorescence compared to multiparametric flow cytometry. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4148.
Abstract 4150: Novel preclinical model for the evaluation of cytokine release syndrome in response to CD19xCD3 bispecific antibody in humanized mice
Authors: Shah Deep S. , Simion Catalina , hu Sang , Chronis Rhonda , McClellan Tre , Hwang Jae , Yang Ryan , Baker Heather , Cai Danying , Keck James , Shopland Lindsay 
Published: April 2023

Abstract
Cytokine Release Syndrome (CRS) is a systemic inflammatory response that is caused by the large, rapid release of cytokines in the blood by immune cells affected by infection or immunotherapy and remains a prominent challenge for T cell-based therapeutics. Bispecific T cell engagers (BiTEs) are fusion proteins that are generated by linking the targeting region of two antibodies: one arm binds to the tumor-associated antigen, and the other arm binds to T cells to promote T cell-mediated cytotoxicity in an MHC-independent manner. A CD19xCD3 BiTE has been approved by the FDA for the treatment of CD19-positive B-cell lymphoma. Despite having great clinical efficacy, CRS remains a major concern for BiTE therapy. This necessitates the development of a translational model that could predict CRS toxicity more accurately. Various in-vitro models proposed to assess BiTE-related CRS have several shortcomings as they do not provide details about the systemic immune response, off-target effects, neurotoxicity, tissue damage, and organ failure. Here we propose an in-vivo approach to concomitantly assess the efficacy and CRS toxicity of CD19xCD3 BiTE either alone or in combination with Rituximab (monoclonal antibody targeting CD20) in the Raji luciferase xenograft model of Burkitt’s lymphoma in PBMC humanized NSG-MHC Class I/II knockout mice. Five days post human PBMC engraftment (Study Day- SD 5), the mice were injected with Raji-luciferase cells. On SD 6, the mice were treated with BiTE, Rituximab, or the combination of BiTE and Rituximab. Additional control groups included OKT3 and Anti-CD28, the anti-T cell antibodies that failed clinically due to severe CRS. Efficacy was assessed through in-vivo imaging on SD5, SD8, and SD11. We observed tumor growth inhibition with BiTE, Rituximab, and the combination treatment. Clinical observations were recorded daily post treatment. Following cytokines were measured 6 hours after dosing and at study termination - IL-2, IL-4, IL-6, IL-10, TNF-α, and IFN-γ. Elevated cytokine levels were observed in the BiTE/combination group 6 hours post dosing but not in the Rituximab alone group. Together, the data suggest that the model could be used to assess the preclinical efficacy and CRS toxicity of BiTE.
Citation Format: Deep S. Shah, Catalina Simion, Sang hu, Rhonda Chronis, Tre McClellan, Jae Hwang, Ryan Yang, Heather Baker, Danying Cai, James Keck, Lindsay Shopland. Novel preclinical model for the evaluation of cytokine release syndrome in response to CD19xCD3 bispecific antibody in humanized mice. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4150.
Abstract 4154: mRNA-based immunotherapies to treat women's cancers
Authors: Tse Dan 
Published: April 2023

Abstract
With its ability to potentially code for any given protein, peptide and fragments, synthetic mRNA has landed itself a broad range of cancer immunotherapy applications, including costimulatory receptors, therapeutic antibodies, vaccines, and cytokines able to change the tumor microenvironment.We have been able to leverage our mRNA platform to generate a vaccine for HPV-associated cervical cancer (CC), as well as an immune-stimulatory cytokine for triple negative breast cancer (TNBC), both diseases that disproportionately affects minorities who do not participate in routine medical screenings and contribute to disparity in mortality beyond individual risk factors.IL-12 is a potent pro-inflammatory type 1 cytokine with potential to enter the clinical practice as immunotherapy for cancer. Its use in the form of recombinant protein and/or DNA plasmid has been hampered by issues with systemic toxicity or protein bioavailability within the tumor. To overcome these roadblocks, we developed a novel secreted single chain IL-12p70 mRNA. Intra-tumoral dosing of this mRNA induced tumor regression in a syngeneic and orthotopic mouse model of TNBC. Almost all cervical cancers are HPV (human papilloma virus) associated. We have developed a therapeutic vaccine, based on a single mRNA coding for two de-risked antigens, that is able to induce a T cell response against the oncogenic proteins E6 and E7 of the most common serotype (HPV16). When injected intramuscularly in mice bearing C3.43 masses, this vaccine suppressed tumor growth and generated immunological memory.Currently, these women’s cancers do not have a cure or an effective standard of care. With an efficacy that relies on a few injections and non-invasive routes of administration, we believe our innovative RNA-based pharmaceuticals might close some treatment gaps.
Citation Format: Dan Tse. mRNA-based immunotherapies to treat women's cancers. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4154.
Abstract 4202: Kidney function and risk of renal cell carcinoma
Authors: Alcala Karine , Alcala Nicolas , Martin Richard , Brennan Paul , Muller David , Robbins Hilary A. , Johansson Mattias 
Published: April 2023

Abstract
Background: The relationship between kidney function and risk of renal cell carcinoma (RCC) is not well understood. In this study, we evaluated the association between estimated glomerular filtration rate (eGFR) and risk of incident RCC, and assessed whether this association depends on time between eGFR measurement and RCC diagnosis. We also sought to evaluate if eGFR may be useful to predict RCC risk.
Methods: We conducted this study in the UK Biobank cohort based on 440,983 participants of whom 984 were diagnosed with RCC during 4,552,747 person-years of follow-up. The temporal relation between kidney function and RCC was evaluated with flexible parametric survival models for eGFR calculated from creatinine, cystatin C and both, adjusted for C-reactive protein (CRP) and common RCC risk factors. We also assessed the benefit of combining CRP and eGFR with a published RCC risk prediction model by estimating calibration and discrimination using a resampling algorithm as internal validation.
Results: We found that a lower eGFR - an indication of poor kidney function - was associated with higher RCC risk when measured up to five years prior to diagnosis. We estimated the RCC hazard ratio per standard deviation decrease in eGFR when measured one year before diagnosis at 1.22 (95% confidence interval [95% CI]: 1.11-1.34), and at 1.14 (95% CI: 1.05-1.19) when measured five years before diagnosis. The corresponding RCC HR for eGFR measured ten years before diagnosis was 1.03 (95% CI: 0.95-1.12). Adding eGFR to the RCC risk model provided a small improvement in risk discrimination 2 years before diagnosis with a C-index of 0.76 (95% CI: 0.71-0.81) compared to the published model (0.73, 95% CI: 0.68-0.79).
Conclusion: This study demonstrated that markers of kidney function are robustly associated with RCC risk when measured within the last five years leading up to diagnosis. However, kidney function markers do not seem to provide important improvements in RCC risk discrimination beyond established risk factors.
Citation Format: Karine Alcala, Nicolas Alcala, Richard Martin, Paul Brennan, David Muller, Hilary A. Robbins, Mattias Johansson. Kidney function and risk of renal cell carcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4202.
Abstract 424: RTK inhibitor resistance in NSCLC harboring MED12 mutation is overcome by only blocking MEK signaling, not AKT due to mutated MED12-induced YAP-PTEN dysregulation
Authors: Ryu Hyun-Min , Kim Deokhoon , Yoon Shinkyo , Lee Ho-Su , Lee Eunjin , Lee Chang Hoon , Kim Wanlim , Seo Seyoung , Jung Kyung Hae , Park Sook Ryun , Kim Sang-We , Park Kang-Seo , Lee Dae Ho 
Published: April 2023

Abstract
The advent of receptor tyrosine kinase inhibitors (RTKi) are important contributions to treat NSCLC patients harboring genetic aberration effectively. Nevertheless, the emergence of acquired or intrinsic RTKi resistance by other RTK activation bypass finally limits their efficacy. First of all, in this study, we identified MED12 mutation in TKI-resistant NSCLC cells based-on NGS analysis. Although MED12 was known to controls the response to multiple cancer drugs through regulation of TGF-beta receptor signaling reportedly, we additionally found that MED12 mutation activates not only TGF-beta receptor not also other ones, such as EGFR, meaning that blocking TGF-beta receptor or EGFR alone may not effective to overcome MED12 mutation-induced RTKi resistance. To overcome the RTKi resistance in NSCLC harboring MED12 mutation, we elaborated the two downstream signaling of RTK in MED12 knock-out NSCLC cells and observed that PI3K/AKT signaling is downregulated but MEK/ERK signaling is upregulated. We observed that only MEK inhibitor (MEKi), not PI3K/mTOR inhibitor, shows effective anti-cancer effect. Therefore, we explored why MEKi alone is effective in RTKi resistant NSCLC cells harboring MED12 mutation and presented that MED12 mutation directly suppressed activation of YAP via blocking a large mediator complex of MED12, MED13, CDK8 and CCNC, thereby increasing PTEN expression by inhibition of miR-29 expression. Increased PTEN inhibits reactivation of PI3K/AKT pathway. In conclusion, we first identified that MED12 mutation induces RTKi resistance though activating other RTKs, such as TGF-beta receptor or EGFR, and blocks PI3K/AKT pathway via dysregulation of YAP/PTEN/AKT interaction. Therefore, among two downstream signaling of RTK, activated MEK/ERK pathway can be a definitive target enough to overcome RTKi resistant NSCLC patients harboring MED12 mutation and MEKi could be a primary treatment option for resistant patients harboring MED12 mutation among NSCLC patients with repetitive recurrence of RTKi resistance by another RTK activation bypass.
Citation Format: Hyun-Min Ryu, Deokhoon Kim, Shinkyo Yoon, Ho-Su Lee, Eunjin Lee, Chang Hoon Lee, Wanlim Kim, Seyoung Seo, Kyung Hae Jung, Sook Ryun Park, Sang-We Kim, Kang-Seo Park, Dae Ho Lee. RTK inhibitor resistance in NSCLC harboring MED12 mutation is overcome by only blocking MEK signaling, not AKT due to mutated MED12-induced YAP-PTEN dysregulation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 424.
Abstract 4281: Data driven refinement of gene signatures for enrichment analysis and cell state characterization
Authors: Wenzel Alexander T. , Tamayo Pablo , Mesirov Jill P. 
Published: April 2023

Abstract
The use of gene expression data has been crucial to the functional characterization of changes in molecular pathway activity and for identifying targets for novel treatments. However, the interpretation of this data is complicated by its high dimensionality and the difficulty of identifying biological signals within a list of differentially expressed genes. Gene Set Enrichment Analysis (GSEA) is a standard method for identifying pathway enrichment in gene expression data by testing whether a set of genes whose expression would indicate the activity of a specific process or phenotype are coordinately up- or downregulated more than would be expected by chance. As GSEA relies on high quality gene sets with coordinately regulated member genes, we maintain the Molecular Signatures Database (MSigDB) which contains 9 collections of curated gene sets representing different biological pathways and processes. Over time, we have observed that some of the MSigDB gene sets, especially those that are manually curated or defined in a very specific biological context, may not provide a sensitive and specific enough co-regulation signature. In response, we have created a data-driven, matrix-factorization-based refinement method to build more sensitive and specific gene sets. This method incorporates large-scale datasets from multiple sources such as the Cancer Dependency Map as well as curated protein-protein interaction networks. We will present the initial results of this refinement method and our ongoing work which will yield a new collection of refined gene sets that will be made freely available in MSigDB for use with GSEA and many other applications.
Citation Format: Alexander T. Wenzel, Pablo Tamayo, Jill P. Mesirov. Data driven refinement of gene signatures for enrichment analysis and cell state characterization. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4281.
Abstract 4306: Identifying genetic dependencies of replication stress using interpretable artificial intelligence
Authors: Zhao Xiaoyu , Singhal Akshat , Ideker Trey 
Published: April 2023

Abstract
Rapid proliferation is a hallmark of tumor cells, associated with sensitivity to chemicals that cause DNA replication stress (RS). Due to sustained proliferative signaling and/or defective DNA repair, cancer cells undergo persistent RS making them strongly dependent on the replication stress response (RSR). A consequence of this dependency is that RS becomes an exploitable therapeutic vulnerability in cancer treatment. Classical RS drugs work predominantly by interfering with DNA replication in dividing cells. Recently, an increasing number of drugs have been designed to specifically target RSR proteins. However, molecular pathways responsible for drug response are incompletely understood. Here we build an interpretable deep-learning model aimed at understanding mechanisms of susceptibility and resistance to replicative stress. Instead of associating genetic alterations with drug responses directly, our approach is to project individual mutations on a map of protein complexes and larger molecular assemblies with prior evidence for involvement in cancer. This approach is prompted and supported by the concept that cancer is a network-based disease arising from the action of hallmark cancer pathways. Through systematic interpretation, the model identifies 37 complexes that integrate rare alterations in hundreds of genes for accurate response prediction. The complexes, which cover roles in transcription, DNA repair, cell-cycle checkpoint, and immunity, are further investigated by directed genetic perturbations, validating 24 for which RS effects are phenocopied by CRISPR guide RNAs. For complexes with poorly characterized functions, further insights are obtained via their profiles of in-silico activation across RS agents. This study creates a library of system-level genetic vulnerabilities governing replication stress, with implications for drug selection and combination.
Citation Format: Xiaoyu Zhao, Akshat Singhal, Trey Ideker. Identifying genetic dependencies of replication stress using interpretable artificial intelligence. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4306.
Abstract 4378: Risk factors for death in the emergency department for melanoma patients
Authors: Hsiung Jayla , Taneja Kamil , Patel Karan , Diaz Michael , Wolfe Jared , Toloza Eric M. 
Published: April 2023

Abstract
Introduction: Many cancer deaths are related to melanoma. While there have been many studies that have identified risk factors for death in these patients, very few of them have analyzed the risk factors for death in melanoma patients in the emergency department (ED).
Methods: We utilized the 2006-2012 Nationwide Emergency Department Sample to characterize melanoma patients who die in the ED. Multivariate logistic regression was used to identify patient and hospital characteristics that were significantly associated with a higher chance of death. A p-value ≤0.05 was considered significant.
Results: From 2006 to 2012, 239,956 melanoma patients presented to the ED, and 2.1% of these melanoma patients died. Most melanoma patients who died in the ED were over the age of 70 years (60.0%), male (63.8%), Medicare beneficiaries (65.6%), of the highest income quartile (31.0%), presenting to a hospital in the South (35.3%), presenting to non-trauma hospitals (48.3%), and presenting to metropolitan non-teaching hospitals (43.4%). The most common reasons for patients who died upon presentation to the ED were a secondary malignancy (20.7%), septicemia (10.8%), acute cerebrovascular disease (7.5%), pneumonia (5.2%), and congestive heart failure (2.6%). The top 3 factors associated with high risk of death were septicemia (odds ratio (OR)=7.39, 95% confidence interval (CI)=5.79-9.43; p&lt;0.001), acute cerebrovascular disease (OR=3.44, 95%CI=2.62-4.51; p&lt;0.001), and age &gt;70 years (OR=2.50, 95%CI=1.24-5.03; p=0.010). Table 1 lists all risk factors associated with a higher risk of death.
Conclusion: Melanoma patients over the age of 70, with septicemia, acute cerebrovascular disease, or pneumonia, and of male sex are at higher risk for death in the ED. Clinicians should be aware of these risk factors when melanoma patients present to the ED.
Risk Factors Associated with Death for Melanoma Patients in the Emergency Department Risk Factor Odds Ratio (95% Confidence Interval) p-value Septicemia 7.39 (5.79-9.43) &lt;0.001 Acute Cerebrovascular Disease 3.44 (2.62-4.51) &lt;0.001 Age &gt;70 2.50 (1.24-5.03) 0.010 Charlson Comorbidity Index of 3 or More 2.32 (1.89-2.84) &lt;0.001 Pneumonia 1.76 (1.27-2.45) 0.001 Charlson Comorbidity Index of 1 1.64 (1.40-1.93) &lt;0.001 Charlson Comorbidity Index of 2 1.63 (1.31-2.03) &lt;0.001 Medicaid 1.63 (1.19-2.23) 0.002 Metropolitan Teaching Hospital 1.33 (1.05-1.68) 0.017
Citation Format: Jayla Hsiung, Kamil Taneja, Karan Patel, Michael Diaz, Jared Wolfe, Eric M. Toloza. Risk factors for death in the emergency department for melanoma patients. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4378.