bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2134: Disaggregating breast cancer mortality trends in Asian American women from 2005-2020
Authors: Marcotte Mia , Chauhan Yashi , Penmetcha Vedha , Thompson Caroline , Thompson Candice , Srinivasan Malathi , Kim Gloria , Qi Xinran , Huang Robert , Bacong Adrian 
Published: March 2024

Abstract
Background: Breast cancer (BC) is the second leading cause of death among women and has disproportionately higher rates of mortality in certain racial groups, including Asian Americans (AA). While differences in BC mortality between AA and other racial groups have been identified, few studies have disaggregated nationwide AA mortality data.
Methods: Using National Vital Statistics System mortality data, BC-related deaths were analyzed among AA groups (Asian Indian, Chinese, Filipina, Japanese, Korean, Vietnamese), Native Hawiian and Pacific Islanders (NHPIs), and non-Hispanic Whites (NHWs) from 2005-2020. We calculated cancer proportional mortality ratios (PMRs), age-adjusted mortality rates (AAMRs), standard mortality ratios, and used JoinPoint regression for average annual percentage change (AAPC).
Results: Among 13677 AA, 522 NHPI, 501282 NHW descendants, 14.3% cancer deaths were due to BC. PMRs increased for all racial groups except Filipina. AAMRs significantly decreased in NHWs (AAPC -1.61; CI -1.70 to -1.48) while significantly increasing for aggregate AAs (AAPC 0.45; CI 0.08 to 0.94). Among AAs, Filipinas had the highest AAMR. AAMRs significantly increased for Asian Indians (AAPC 2.05; CI 1.20 to 3.46), Filipinas (AAPC 0.61; CI 0.15 to 1.46), Koreans (AAPC 2.72; CI 1.57 to 4.65) and Vietnamese women (AAPC 3.63; CI 2.26 to 6.20), but significantly decreased for Japanese (AAPC -1.41; CI -2.22 to -0.53).
Conclusions: We observed heterogenous and converging BC mortality trends across AA groups. These trends elucidate which populations within the broader AA group have disproportionately higher death rates and therefore should be targeted for BC prevention protocols (e.g., Asian Indian and Filipina). Identifying such trends can also help elucidate disparities in cancer care and the overall social determinants that affect women with BC. Understanding disaggregated trends can inform more inclusive screening practices and culturally tailored interventions and treatments to reduce BC deaths in vulnerable populations.
Citation Format: Mia Marcotte, Yashi Chauhan, Vedha Penmetcha, Caroline Thompson, Candice Thompson, Malathi Srinivasan, Gloria Kim, Xinran Qi, Robert Huang, Adrian Bacong. Disaggregating breast cancer mortality trends in Asian American women from 2005-2020 [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 2134.
Abstract 2156: Exploring barriers to colorectal cancer screening among adult male immigrants in Salt Lake City
Authors: Onigbogi Olanrewaju Olusola , Kah Kebba , Okuyemi Kolawole 
Published: March 2024

Abstract
Background: The United States (U.S) foreign-born population aged 65+ increased substantially between 1990 and 2010 with migrants from Africa and the Middle East being a part of these new refugee admissions. According to 2010 data, socioeconomic disparities and reduced access to health care is common in this population with 16 percent of foreign-born elderly living below the poverty threshold in comparison with 8 percent of U.S.-born elderly. Colorectal Cancer (CRC) is the second leading cause of cancer related deaths in the U.S despite being easily preventable and treatable. Studies among male African Americans reveal a CRC incidence &gt;20% higher than what obtains among whites. Since, genetic factors are believed to contribute as much as 35% to the overall risk of CRC, male adult immigrants aged 45 years and above from Africa and the Middle East may be at increased risk of developing the disease. Determining CRC screening uptake in this population will be critical in planning interventions which may ultimately reduce disparities in CRC-related morbidity and mortality in the future.
Methods: We conducted a mixed methods study comprising administration of questionnaires and organizing four Focus Group Discussion (FGD) sessions among adult males in Salt Lake City who identified as refugees from Africa or the Middle East. The sessions were audio-taped, transcribed and coded using the Dedoose software.
Results: We had thirty-one participants who were between 45 and 64 years of age. Twenty-five of them (83%) reported awareness of the existence of CRC screening tests. Ten participants (33%) had undergone a CRC test in the past. However, only nine participants (30%) indicated that they will be willing to participate (WTP) in CRC screening if offered for free. Increased WTP was associated with younger age (OR=1.45, 95% CI: 1.23-1.81), length of stay in the United States (OR=1.41, 95% CI: 1.13-1.78) and higher education (OR= 1.26, 95% CI 1.13-1.37). Three major themes identified in the FGDs include: (1) Mistrust - distrust of the US health system (2) Fear - fear of cancer and nature of test and (3) Fatalism - the belief that screening cannot lead to cancer cure.
Conclusion: The low level of WTP in CRC screening tests among the respondents may be associated with past experiences. There may be a need to consider the correlates of increased WTP and explore culture-specific CRC prevention measures in planning interventions designed to improve screening uptake in this population.
Citation Format: Olanrewaju Olusola Onigbogi, Kebba Kah, Kolawole Okuyemi. Exploring barriers to colorectal cancer screening among adult male immigrants in Salt Lake City [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 2156.
Abstract 224: Combining functional precision medicine and radiotherapy with bio-printed organoids in head and neck squamous cell carcinoma
Authors: Lin Luda , Bommakanti Krishna K. , Sannajust Andreanne V. , Alhiyari Yazeed , Mo Brandon , Evans Lauran , Tebon Peyton , St. John Maie , Soragni Alice 
Published: March 2024

Abstract
The study aims to establish a high throughput ex vivo organoid-based drug screening platform for head and neck squamous cell carcinoma (HNSCC) to investigate interactions between radiotherapy and different chemotherapies or targeted therapy agents and ultimately provide functional precision medicine therapeutic suggestions. HNSCC is the sixth most common cancer worldwide. Both HPV+ and HPV- cancers can be treated with surgery, radiotherapy, chemotherapy, or a combination of these. Cetuximab is currently the only FDA-approved targeted agent for HNSCC. Few clinical trials to date have shown an improved clinical outcome when combining targeted agents with radiotherapy, thus there is a need to identify new therapeutic combinations to improve outcomes.
In order to characterize HNSCC tumor behavior and sensitivity to therapy, we have leveraged our high throughput 3D tumor organoid screening platform. Our approach entails seeding tumor cells in extracellular matrix around the perimeter of tissue culture wells in ring-like structures, which we have successfully deployed in other cancer types (Phan et al, 2019; Al Shihabi et al, 2022; Nguyen et al, 2022; Al Shihabi et al 2023). To optimize a chemoradiation platform, we used the HN30, HN31, and SCC154 cell lines representing HPV- primary, HPV- metastatic, and HPV+ head and neck tumors. The cell-line-derived 3D models are exposed to both radiotherapy and various chemotherapy or targeted therapy drugs. We measured cell responses by ATP-release assays and by applying our machine learning-based brightfield image analysis pipeline (Al Shihabi et al, 2022).
Our results showed that the HPV+ SCC154 was the most sensitive line to radiotherapy while HPV- metastatic HN31 was the most resistant. HN31 was resistant to most drug treatments except for gemcitabine, docetaxel, and mitomycin c, while HN30 and SCC154 were sensitive to a broader set of agents. We have investigated combinatorial efficacy of radiation and chemotherapy as well as targeted agents and extended this platform to HNSCC patient-derived tumor organoids. Our proof-of-concept study highlights how our organoid-based drug screening platform can be used to test chemoradiation approaches that are more effective and personalized.
Citation Format: Luda Lin, Krishna K. Bommakanti, Andreanne V. Sannajust, Yazeed Alhiyari, Brandon Mo, Lauran Evans, Peyton Tebon, Maie St. John, Alice Soragni. Combining functional precision medicine and radiotherapy with bio-printed organoids in head and neck squamous cell carcinoma [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 224.
Abstract 2262: Genomic profiling of leukemic cell lines, responders vs. non-responders to Narazaciclib (HX301 or ON123300), a novel kinase inhibitor with activity against CSF1R and FLT3
Authors: Xue Jia , Yang Tao , Ke Hang , Guos Sheng , Li Henry Qixiang 
Published: March 2024

Abstract
Acute myeloid leukemia (AML) is an aggressive myeloid leukemia with global annual mortality ~150,000. While standard of care (SOC) of the 1st -line treatment being mainly induction chemotherapy, available targeted therapies cover rather limited patients carrying specific driver mutations (IDH mutations and FLT3-ITR). We previously reported a novel kinase inhibitor, Narazaciclib with strong anti-CSF1R activity (IC50 0.7nM) as well as anti-FLT3 (IC50 7nM), and also thus anti-AML activity for certain AML experimental models, as shown in vitro and in vivo (AACR Annual Meeeting, 2023). In the present study, we assessed the impact of HX301 on the in vitro proliferations of a panel of leukemic cell lines (n = 54), including a panel of AML cell lines (n = 33), that have been parallelly genomic-profiled by whole-exome sequencing and whole-transcriptome sequencing. We then set out to analyze the proliferation data and the genomic data, in attempt to elucidate genes and pathways that may be associated with the treatment responses. The biomarker analysis has been performed on gene expression, mutation and copy number variation levels, and the data been presented using common methodologies, including principal component analysis, differential expression analysis, correlation analysis, Gene Ontology enrichment analysis, gene set variation analysis, somatic gene mutation analysis, and copy number variation analysis, etc. Some of the observations have been made: 1) differential expression analysis on all leukemic cell lines shows that 254 genes have been positively associated with the responders; while expression of 191 genes are negatively correlated with AUC, i.e. positively associated with response, as revealed by Spearman correlation analysis; 2) Gene Ontology enrichment analysis revealed these response related genes are mostly involved in myeloid leukocyte activation and defense response; 3) all FLT3-ITD AML lines are responders, presumably due to the FLT3i activity of HX301; 4) CSF1R expression levels seem not correlated to drug responses; 5) pathway analysis on non FLT3-ITD AML lines reveals that STAT5 activation downstream of FLT3 signaling, IL7 pathway and NFKB pathway are significantly associated with better response. Finally, we are also attempted to use statistics learning to reveal genes, as a potential predictive biomarker, that may be correlated to drug response.
Citation Format: Jia Xue, Tao Yang, Hang Ke, Sheng Guos, Henry Qixiang Li. Genomic profiling of leukemic cell lines, responders vs. non-responders to Narazaciclib (HX301 or ON123300), a novel kinase inhibitor with activity against CSF1R and FLT3 [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 2262.
Abstract 2272: Unlocking the potential of miRNA sequencing for early detection and monitoring of pancreatic cancer progression and recurrence
Authors: Fuller Ryan N. , Morcos Ann , Escalera Desirae , Wall Nathan R. 
Published: March 2024

Abstract
Pancreatic cancer (PC) is an elusive and deadly disease. Many patients with PC are diagnosed with metastatic or locally advanced tumors, limiting surgical resection, and increasing the risk of relapse after treatment. Relapse is recorded to be as high as 75% in the first 2 years after clinical intervention, resulting in a mean 5-year survival of 12% in the US, and as low as 2% worldwide. It is vital to develop diagnostic and monitoring techniques for PC. MicroRNAs (miRNAs) are robustly expressed in patient tumors and provide a rich source of biomarkers for disease detection and status. miRNA are short nucleic acid strands that bind to catalytic proteins to guide the regulation of large RNAs within the cellular space. This system is altered in tumors, leading to abhorrent expression of miRNA. Due to significant advancements in sequencing technology, miRNA-seq has become more accurate and affordable in detecting profile changes. To identify biomarkers for PC progression, we developed from the Gemcitabine-sensitive MIA-PaCa-2 (MP2) cell line the Gemcitabine and FOLFIRINOX resistant MP2-GR cell line. MiRNA-seq was conducted on the parental MP2 and resistant MP2-GR cells to identify those miRNAs that were differentially expressed between the cell lines. These miRNAs were analyzed via pathway analysis and gene ontology to find predicted functions followed by annotations from the miRNA Enrichment Analysis and Annotation tool (miEAA) to identify differentially expressed miRNAs associated with PC progression. This comparison indicated several miRNAs related to PC resistance. This dataset was then compared to The Cancer Genome Atlas (TCGA), which contains data from over 300 PC patients. The miRNA set was used to predict both PC progression after treatment, and recurrence. We are currently refining this data set to increase its predictive sensitivity and widen our patient data set comparison to further elucidate this approach in a clinical setting.
Citation Format: Ryan N. Fuller, Ann Morcos, Desirae Escalera, Nathan R. Wall. Unlocking the potential of miRNA sequencing for early detection and monitoring of pancreatic cancer progression and recurrence [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 2272.
Abstract 2339: GPNotebook: A toolkit for identifying cancer-related glycosylation alterations in glycoproteomic analysis
Authors: Zhang Hui , Hoang Trung , Hu Yingwei 
Published: March 2024

Abstract
This study is dedicated to the development and application of 'GPNotebook', an innovative Python-based data analysis tool, specifically designed to enhance glycopeptide research in cancer studies by enabling the detailed investigation of glycosylation patterns and their correlation with various clinical cancer phenotypes. In our study, we recognize the critical role of protein glycosylation in biological processes and its relevance in cancer. To address the lack of specialized tools for glycoproteomic analysis, we developed GPNotebook, a comprehensive Python package designed for detailed investigation of intact glycopeptides (IGPs). This tool integrates multiple functionalities, including statistical profiling, differential expression analysis, categorization of glycosylation subtypes, and exploration of the interactions between glycosylation and phosphorylation. It also encompasses survival analysis and assessments of glycosylation enzymes. We applied GPNotebook in a research project focused on 10 cancer types collected from Clinical Proteomic Tumor Analysis Consortium (CPTAC) projects to validate its efficacy and demonstrate its wide-ranging capabilities. Through this application, we were able to analyze and interpret complex glycoproteomic data, revealing potential IGPs as biomarkers for cancer detection and differentiation of cancer subtypes. We identified hundreds of cancer-specific IGPs, with several showing promise as early-stage cancer biomarkers. In addition, our analysis revealed unique glycosylation patterns linked to specific molecular subtypes and immune cell distributions in tumor microenvironments. We also clarified the roles of certain glycosylation enzymes across different cancer types, highlighting their potential significance in cancer progression. GPNotebook has proven to be a critical tool in glycopeptide research. Our findings not only enhance the understanding of glycosylation in cancer but also demonstrate GPNotebook's potential in identifying novel biomarkers and providing insights into cancer subtype differentiation. This study positions GPNotebook as a valuable resource for exploring the complex relationships between protein glycosylation and cancer phenotypes.
Citation Format: Hui Zhang, Trung Hoang, Yingwei Hu. GPNotebook: A toolkit for identifying cancer-related glycosylation alterations in glycoproteomic 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 2339.
Abstract 2341: Morph: A feature extraction toolset for spatial transcriptomics
Authors: da Costa André Luiz N. Targino , Liu Jingxian , Mo Chia-Kuei , Storrs Erik , Southard-Smith Austin N. , Jayasinghe Reyka G. , Wang Julia T. , Iglesia Michael D. , Wendl Michael , Chen Siqi , Houston Andrew , Karpova Alla , Li Yize , Ding Li 
Published: March 2024

Abstract
Accurately defining spatial characteristics of tumors has been a challenge in cancer research. Specifically, there is still a lack of spatial transcriptomic (ST) bioinformatic methods that infer tumor boundaries, a necessity for tumor microenvironment (TME) analyses, that are fully automated and handle non-rectangular grids (like the one found in Visium). Here we introduce Morph, a toolset that not only addresses these limitations, but also accurately extracts tumor regions, layers surrounding them, and distances related to such regions. Morph was tested on a dataset composed of 117 ST slides across 6 different cancer types, including primary and metastatic tumors. More broadly, Morph is a computationally efficient tool based on mathematical morphology that is designed to work without any approximations on ST slides (that can be composed of spots in a hexagonal lattice) of any resolution. The toolset accepts a variety of input types, such as tumor purity and manual annotation, and can perform a diverse set of morphological operations, such as erosion, dilation, opening and closing, using a number of structuring elements with different shapes and sizes, such as a hexagon of side 1. Moreover, Morph runs quickly (seconds per sample). Its main focus is to unveil the aforementioned features of any spatially distinct tumor region (here defined as microregion) for various downstream analyses, such as spatially-varying copy number variations, cell-type distribution, and tumor-microenvironment interaction. Overall, we developed a spatial transcriptomics toolset that is not limited to any specific technology platform, and that can accurately extract ST features facilitating the discovery of spatial transcriptomic and interaction patterns.
Citation Format: André Luiz N. Targino da Costa, Jingxian Liu, Chia-Kuei Mo, Erik Storrs, Austin N. Southard-Smith, Reyka G. Jayasinghe, Julia T. Wang, Michael D. Iglesia, Michael Wendl, Siqi Chen, Andrew Houston, Alla Karpova, Yize Li, Li Ding. Morph: A feature extraction toolset for spatial transcriptomics [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 2341.
Abstract 2348: A global multiscale map of protein assemblies from integration of protein interactions and images
Authors: Schaffer Leah V. , Hu Mengzhou , Huttlin Edward L. , Qian Gege , Pal Abantika , Soni Neelesh , Latham Andrew , Vaites Laura Pontano , Le Trang , Qin Yue , Churas Christopher , Pratt Dexter , Echeverria Ignacia , Sali Andrej , Harper J Wade , Gygi Steven P. , Lundberg Emma , Ideker Trey 
Published: March 2024

Abstract
Cells regulate growth and function through a hierarchical structure of subcellular protein assemblies, in which alterations can result in cellular dysfunction leading to disease such as cancer. Much of this structure remains uncharted, resulting in recent efforts to map subcellular organization at different physical scales. Here, we report a global architectural map of human cancer cell protein assemblies spanning 10−9 to 10−5 nm, based on integration of near-proteome-wide affinity purification mass spectrometry-based protein interactions and immunofluorescent imaging in U-2 OS osteosarcoma cancer cells. The U-2 OS multi-scale integrated cell map places &gt;5000 proteins into 270 distinct subcellular protein assemblies across biological scales, representing approximately half of expressed proteins. There are known organelles and protein complexes recovered in the map, as well as 152 putative assemblies, such as a putative interferon signaling complex consisting of a serine protease and STAT transcription factors. The map also incorporates 128 previously uncharacterized proteins into protein assemblies, such as C18orf21 association with a canonical RNAse complex. Protein subsystems in the U-2 OS map were evaluated for the potential for downstream integrative structural modeling, where available structural data (e.g. crosslinking, Protein Data Bank structures, AlphaFold predictions) are combined in a Bayesian framework to model the physical structures of protein complexes. Using this framework, we created an integrated structural model of new proteins interacting with the Rag-Ragulator complex, which regulates MAPK and mTOR signaling. In summary, the global proteome architecture map provides a resource for cellular biology discovery and the systematic determination of protein functions and structures.
Citation Format: Leah V. Schaffer, Mengzhou Hu, Edward L. Huttlin, Gege Qian, Abantika Pal, Neelesh Soni, Andrew Latham, Laura Pontano Vaites, Trang Le, Yue Qin, Christopher Churas, Dexter Pratt, Ignacia Echeverria, Andrej Sali, J Wade Harper, Steven P. Gygi, Emma Lundberg, Trey Ideker. A global multiscale map of protein assemblies from integration of protein interactions and images [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 2348.