bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2073: Human breast patient derived organoids: Development and characterization of a new tissue mimetic model
Authors: Bhowmick Rudra , Malla Sudarshan , Wani Sameena , Chatterjee Anirban 
Published: March 2024

Abstract
Worldwide, breast cancer (BC), is the most frequently diagnosed cancer among women. In the US, 1 out of 8 women may expect to be diagnosed with BC In their lifetime. Current models for studying BC tumor biology and BC drug discovery include 2D cultured cell lines and patient derived xenografts (PDX). As 2D cultured cells do not represent the 3D complexity of human tissue, and PDX models are time consuming and cost prohibitive, better tissue mimetic models are needed. Organoids are self-assembled 3D cultured cellular units that may mimic the corresponding human tissue structurally and functionally (1). Patient derived organoids (PDO) are developed from tissue of specific patients and may resemble the source tissue in molecular features, including recapitulation of patient specific responses to therapies (2). Here, we report development and characterization of novel breast PDO lines from fresh (≤24h post-surgery) and cryopreserved (≤7 days post-surgery) tissue. Breast tumor and normal, tumor adjacent (NTA) tissue were sourced from consented patients. Breast PDO were generated following modifications to a published protocol (3). Briefly, tissue samples were minced, digested with collagenase, and filtered. The filtrate was resuspended in Matrigel (Corning) and small drops were added on cell culture plates. Both tumor and NTA PDO were cultured using the same media and organoids were monitored using brightfield microscopy (Olympus CK40) and live cell imaging (Muvicyte, Perkin Elmer). PDO lines were analyzed for expression and distribution of important breast-specific biomarkers using confocal microscopy (ImagExpress, Molecular Devices). PDO lines displayed hormone receptors (ER, PR), cell surface (EpCAM, CD49f), cytoskeletal (cytokeratin 14, 19, E-cadherin, vimentin) and cell proliferation (Ki67) markers. Transcriptome profiles were analyzed using vendor services (Azenta). PDO were also tested for their susceptibility to breast cancer drugs, e.g., Tamoxifen, chlorambucil and Docetaxel. We have successfully generated one NTA ER+/PR+/HER2− PDO line and one tumor ER+/PR+/HER2− PDO line from different donors. Our breast PDO lines would be highly useful in understanding tumor biology, BC progression, signal transduction, and drug discovery/testing. Future efforts would include process scaling up and development of BC specific assays. References:1.Zhao et al., 2022. STAR Protocols 2.Bleijs, M. et al., 2019. EMBO J3.Dekkers et al., 2021. Nature Protocols
Citation Format: Rudra Bhowmick, Sudarshan Malla, Sameena Wani, Anirban Chatterjee. Human breast patient derived organoids: Development and characterization of a new tissue mimetic model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2073.
Abstract 2177: Postbiotic metabolites secreted by L. acidophilus reduce DNA damage in an experimental model of Barrett’s tumorigenesis
Authors: Joshi Divya , Andl Claudia 
Published: March 2024

Abstract
The origins of esophageal adenocarcinoma (EAC) are commonly attributed to the progression from gastroesophageal reflux disease (GERD) to Barrett’s Esophagus (BE) and finally to esophageal adenocarcinoma. During GERD, various types of bile induce oxidative stress and generate reactive oxygen species (ROS), resulting in DNA damage and inflammation in cells. Although there has been much research documenting the shift in the esophageal microbiome from gram-positive to gram-negative bacteria during this progression, there has also been an observed increase in the presence of Lactobacillus, a gram-positive commensal bacterium with probiotic qualities, in the esophagus during the progression from GERD to BE and eventually to EAC. Our previous research has demonstrated the ability of Lactobacillus spp. to not only colonize the esophagus under in vitro conditions of GERD, but also their anti-inflammatory and anti-genotoxic properties on esophageal cells exposed to bile. To assess the extent of reflux-induced DNA damage and oxidative stress during the progression of BE, we exposed two BE cell lines, CP-B and BAR-T, and the EAC cell line FLO-1 to ox bile or deoxycholic acid. Both bile types demonstrated significant increases in phosphorylated H2AX, as a marker for pronounced DNA damage repair. Next, we supplemented both live L. acidophilus and its postbiotic metabolites to cells exposed to ox bile and deoxycholic acid. We show a significant reduction in DNA damage as measured by pH2AX with both the live treatment and the treatment with postbiotic metabolites when compared to untreated, bile-exposed cells at various stages of BE and EAC. Ongoing experiments include assessing anti-genotoxic effects of postbiotic metabolites through DNA repair protein RAD51, reductions in oxidative stress though ROS marker 8-oxo-guanine, and anti-inflammatory effects through NFkB-associated inflammation. BE and EAC cell viability and proliferation upon bile exposure and postbiotic metabolite administration will also be assessed. This study aims to determine the supplementation with Lactobacillus postbiotic metabolites in the prevention and intervention of esophageal adenocarcinoma development.
Citation Format: Divya Joshi, Claudia Andl. Postbiotic metabolites secreted by L. acidophilus reduce DNA damage in an experimental model of Barrett’s tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2177.
Abstract 2270: UALCAN Mobile, An app for cancer gene expression data analysis
Authors: Varambally Sooryanarayana , Chandrashekar Darshan Shimoga , Puli Gopi Chand , Karthikeyan Santhosh Kumar , Manne Upender , Creighton Chad J. , Kumar Sidarth 
Published: March 2024

Abstract
Cancer is a complex disease effecting different organs and a major cause of death and a burden on the society. Multiple molecular alteration occur during cancer initiation and disease progression and metastasis. Recent advances in technology led to generation of large amount of molecular data including transcriptome. These large datasets can be used to analyze and identify sub-class specific cancer biomarkers and targets. However, there is a need for the development user friendly tools for its analysis and dissemination of the large scale cancer molecular data. Earlier, we had developed and upgraded web based comprehensive proteogenomic platform UALCAN (ualcan.path.uab.edu), which allows users to analyze and integrate the disparate data to better understand the gene, proteins, and pathways perturbed in cancer and make discoveries. UALCAN web platform enables intuitive analysis and discovery by cancer research community. In the current study, we describe the development of UALCAN Mobile application (App) that will provide cancer transcriptomic data obtained from The Cancer Genome Atlas (TCGA) project, to evaluate protein-coding gene expression based on various stratification including stage, grade, race, gender and molecular-subtypes across over 30 types of cancers. The UALCAN Mobile app aims at providing large cancer dataset on the go. In order to find causative gene expression changes, identify biomarkers and therapeutic targets, UALCAN Mobile will assist as the data will be easily mobile and transportable with this App. Here, we describe the development of UALCAN Mobile and its utility to the cancer research community. UALCAN Mobile App can be found at both iOS/Apple and Android play store and is free to download and use.
Citation Format: Sooryanarayana Varambally, Darshan Shimoga Chandrashekar, Gopi Chand Puli, Santhosh Kumar Karthikeyan, Upender Manne, Chad J. Creighton, Sidarth Kumar. UALCAN Mobile, An app for cancer gene expression data analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2270.
Abstract 2274: Genomic and transcriptomic analyses of chemical hepatocarcinogenesis aggravated by loss of oncoproteins in hepatocytes
Authors: Wang Xinyi , Zhang Jiemeng , Liu Yingluo , Zhang Shuo , Liang Yan , Zong Min , Lin Xiaoxue , Karin Michael , Feng Gensheng 
Published: March 2024

Abstract
Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death without effective treatment. Oncogenic drivers, including PTPN11/Shp2, Ikkβ kinase (IKK), c-Met and β-catenin, as well as tumor microenvironment as illustrated by a carcinogen or diethylnitrosamine (DEN)-treated models, have combined contribution to cancer progression that have distinct prevalence in human HCC progression. We previously found that disruption of Ras/Erk by Shp2 deletion combined with deletion of NF-κB unexpectedly dysregulated circadian clock genes which leads to further cancer progression. Except for this, limited reports investigated how various other oncogenic genes aberration would incorporate with DEN to induce HCC. Further, no reports investigated the dynamic evolution of transcriptomic aberration incorporating genetic changes and the differential functional pathways involved in DEN plus oncogene triggered-HCC progression. Thus, we here sought to investigate the context-dependent contribution of PTPN11/Shp2, IKK, c-Met and β-catenin to HCC using hepatocyte-specific deletion models (SKO, IKO, MKO, BKO) combined with DEN treatment. Exome sequencing and RNAseq were used to identify dynamic changes of the genomic and transcriptomic variations of HCC development under the influence of both genetic deletion and DEN-treatment. We found that upregulated epithelial-mesenchymal transition (EMT), cancer metastasis/migration and downregulated fatty-acid and cholesterol metabolism were highly involved across models. Macrophages together with genes including Spi1, Clec7a, and microRNA networks including miR-122 and miR-155 etc. were also deregulated. Specifically, upregulated IL2-STAT5 signaling in DEN-SKO liver tissues, upregulated myogenesis, KRAS signaling and EMT as well as apoptosis in DEN-MKO, downregulated xenobiotic metabolism and bile acid metabolism in DEN-IKO and -BKO were identified to be distinct to oncogenic deletion in relation with HCC development.
Citation Format: Xinyi Wang, Jiemeng Zhang, Yingluo Liu, Shuo Zhang, Yan Liang, Min Zong, Xiaoxue Lin, Michael Karin, Gensheng Feng. Genomic and transcriptomic analyses of chemical hepatocarcinogenesis aggravated by loss of oncoproteins in hepatocytes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2274.
Abstract 2291: Bravo automation of Agilent Avida targeted enrichment for high-throughput detection of genomic alteration and DNA methylation
Authors: Wahba Ashraf , Ho Tony , Johns Sarah , Aravind Aswati , Wang Heng , Mehendale Neelima V. , Amparo Gilbert P. , Win Khine , Gomez Manuel , Zhao Grace , Roberts Douglas N. 
Published: March 2024

Abstract
Background: Current genomic and epigenomic profiling of cancer tissue DNA or cfDNA (cell-free DNA) in liquid biopsy relies upon separate, time- and sample-consuming technologies for somatic variant detection or methylation analysis. Here we describe workflow and performance of the Agilent Bravo automated liquid handling platform with the Agilent Avida targeted enrichment solution for next generation sequencing of somatic variants and methylation profiling. This solution can effectively analyze low-input tumor DNA or cfDNA samples. The Avida Duo workflow enables highly sensitive detection of single nucleotide variant (SNV), insertions and deletions (INDEL), copy number variation (CNV) and DNA methylation profiles from a single sample, without any sample splitting. Methods and Results: Panels, reagents, and automated workflows for Avida DNA, Avida Methyl, and Avida Duo Methyl (combined DNA & methylation) kits were developed to accommodate up to 96 samples on the Bravo NGS workstation. The automated solution supports independent single-day workflows for somatic variants or methylation sample preparation. The Avida Duo analysis combines both workflows without sample splitting, streamlining the process and reducing sample consumption. Leveraging a focused cancer hotspot panel, we demonstrate excellent reproducibility and low allele frequency (SNV at sub 1%) variant detection in cfDNA samples and reference standards with as little as 10ng DNA input. We exhibit similar performance with a larger ~300 kb target region tumor profiling panel. Finally, we demonstrate DNA methylation detection in the standalone or combined (“Duo”) workflows across differentially methylated regions (DMRs) with a panel of ~3400 targets. Conclusions: Automation of the Avida targeted enrichment solution with the Bravo NGS workstation enables a sensitive, high-throughput, end-to-end analysis for detection of genomic alterations and DNA methylation changes from a single low-input cfDNA or tumor DNA sample.
Citation Format: Ashraf Wahba, Tony Ho, Sarah Johns, Aswati Aravind, Heng Wang, Neelima V. Mehendale, Gilbert P. Amparo, Khine Win, Manuel Gomez, Grace Zhao, Douglas N. Roberts. Bravo automation of Agilent Avida targeted enrichment for high-throughput detection of genomic alteration and DNA methylation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2291.
Abstract 2340: STRUMP-I: Structure-based binding prediction of MHC class I
Authors: Voshall Adam , Park Woongyang , Lee Eunjung Alice , Choi Yoonjoo 
Published: March 2024

Abstract
The presentation of short peptides derived from endogenously expressed proteins within the Major Histocompatability Complex-I (MHC-I), together known as the pMHC, allows the adaptive immune system to monitor the internal functioning of a cell and surveil for foreign or mutated self-proteins. With the rising importance of immunotherapies targeting neoantigens in cancers, the ability to accurately predict which peptides will bind to the diverse population of MHC alleles is critically important. Computational methods for predicting MHC/peptide interactions fall into two broad categories: sequence-based methods that utilize machine learning or deep learning to predict binding from information about the MHC and peptide sequence alone, and structure-based methods that leverage the computed structure and energetics of the pMHC to predict binding. While sequence-based methods have outperformed structure-based methods, their performance varies with the quantity and quality of training data for each MHC allele. The pMHC structure also provides additional insights into downstream analyses, such as predicting the immunogenicity of cancer neoantigens, that cannot be determined from the sequence alone. We developed a STRUMP-I (STRUcture-based pMHC Prediction (for class I)), a novel pMHC binding prediction tool that combines structural modelling with a machine learning-based classifier to discriminate binders from non-binders. STRUMP-I has comparable performance to the state-of-the-art sequence-based methods on data taken from IEDB, the HLAthena training set, TESLA, PRIME, and an in-house cancer neoantigen dataset. However, it generalizes better to alleles with low representation or a lower proportion of positive examples in the training data than the sequence-based methods. Additionally, we demonstrate how STRUMP-I can be used in conjunction with PRIME, a sequence-based immunogenicity prediction method, to use structural information about the peptide to filter out false positive predictions and increase the precision of immunogenicity predictions, increasing the precision by up to 2-fold. Further, on a set of 10 experimentally validated peptides from the in-house cancer neoantigen dataset containing only a single immunogenic peptide, STRUMP-I filtered all false positive predictions and retained only the true positive prediction. By leveraging structural information about the pMHC, STRUMP-I provides robust binding predicting performance across MHC alleles and increases the precision of immunogenicity prediction for neoantigen screening.
Citation Format: Adam Voshall, Woongyang Park, Eunjung Alice Lee, Yoonjoo Choi. STRUMP-I: Structure-based binding prediction of MHC class I [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2340.
Abstract 2356: NAV-006: A next-generation rituximab targeting CD20 for the treatment of B-cell lymphomas immunosuppressed by MUC16/CA125
Authors: Grasso Luigi , Kline J. Bradford , Nicolaides Nicholas C. 
Published: March 2024

Abstract
Rituximab is a CD20-targeting antibody that is the standard-of-care for patients with Non-Hodgkin Lymphoma (NHL) cases. Rituximab’s mechanism of action includes complement-dependent cytotoxicity (CDC) and antibody-dependent cellular cytotoxicity (ADCC), herein referred to as Humoral Immuno-Oncology (HIO) mechanisms. Recent clinical evidence suggest that high serum levels of the MUC16 (CA125) protein inversely correlate with the effectiveness of rituximab clinical activity in 40-50% of follicular lymphoma (FL) as well as diffuse large B-cell lymphoma patients with newly diagnosed or relapsed/refractory (R/R) disease. In this study we demonstrated that CA125 binds to and suppresses the activity of rituximab, tafasitamab as well as the bispecific mosunetuzumab and glofitamab antibodies, which are approved for treating cases with indolent disease. These therapies have an overall response rate around 50-60%, suggesting the presence of a mechanism that allows lymphoma cells to escape these agents’ immune-mediated killing effects. CA125 may facilitate this immunosuppressive mechanism, and in fact, upon binding rituximab, CA125 reduces its affinity for the Fc receptor, CD16a, thus suppressing ADCC. Using a proprietary technology called Block-Removed Immunoglobulin Technology (BRITE) that employs randomized amino acid substitution and HIO effector function screening, we have identified a rituximab variant named NAV-006. NAV-006 is refractory to the immunosuppressive effects mediated by CA125 via its reduced CA125 interaction and increased HIO activity as compared to parent rituximab as well as the other antibodies used to treat R/R FL. In an in vivo model of human B-cell lymphoma, NAV-006 showed superior efficacy compared to parent rituximab. These data warrant further investigation of NAV-006 as a next generation anti-CD20 antibody that could improve upon the efficacy of antibody-mediated therapies used to treat NHL patients with high levels of CA125.
Citation Format: Luigi Grasso, J. Bradford Kline, Nicholas C. Nicolaides. NAV-006: A next-generation rituximab targeting CD20 for the treatment of B-cell lymphomas immunosuppressed by MUC16/CA125 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2356.
Abstract 2431: Identification of highly expressed exosomal RNAs derived from pancreatic cancer cell lines and exploration of their potential as biomarkers
Authors: Rong Yuhan , Okubo Naoki , Kobayashi Noritoshi , Katsuta Eriko , Ichikawa Yasushi 
Published: March 2024

Abstract
Background: Not all exosomes in the blood of cancer patients originate from cancer cells. This study evaluated the relationships between mRNAs and miRNAs in pancreatic cancer (PC) cell lines and those in exosomes secreted into the supernatant. We aimed to identify candidates for PC biomarkers from cancer-specific exosomal mRNAs and miRNAs.
Materials and Methods: Three PC cell lines were utilized. Exosomes were isolated from the supernatant, and cellular and exosomal mRNAs and miRNAs were extracted. Subsequently, RNA sequencing (RNA-seq) was performed, and the data were analyzed using R software.
Results: In the MIAPaCa-2 cell line, the expression of cellular mRNAs and corresponding exosomal mRNAs showed a strong correlation. In the other two cell lines, a moderate correlation was observed. Across all three cell lines, cellular miRNAs and corresponding exosomal miRNAs exhibited moderate correlation. We focused on RNAs that were lowly expressed in cells but highly expressed in exosomes and conducted differential expression analysis using R. Compared with healthy volunteers in the GEO database, some RNAs showed high expression in the supernatant and low expression in the plasma of healthy volunteers.
Conclusion: We identified three mRNAs and three miRNAs that may serve as promising biomarker candidates for PC.
Citation Format: Yuhan Rong, Naoki Okubo, Noritoshi Kobayashi, Eriko Katsuta, Yasushi Ichikawa. Identification of highly expressed exosomal RNAs derived from pancreatic cancer cell lines and exploration of their potential as biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2431.