bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 2182: 15-lipoxygenase-1 modulation of colonic resolvin production to suppress colorectal carcinogenesis
Authors: Zuo Xiangsheng , Kiyasu Yoshiyuki , Liu Yi , Moussalli Micheline , Wei Bo , Yang Peiying , Shureiqi Imad 
Published: March 2024

Abstract
Docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) are widely used dietary supplements and FDA-approved treatments. The reported impacts of fish oil, DHA, and EPA on colorectal carcinogenesis (CRC) have spurred debates, as certain studies suggest promotional effects while numerous others emphasize suppressive effects. Nevertheless, resolvins, oxidative metabolites of EPA and DHA, exhibit the ability to inhibit crucial pathways (such as TNF-α and IL-1β) that contribute to CRC. 15-lipoxygenase-1 (ALOX15) plays a crucial role in the oxidative metabolism of DHA and EPA, ultimately leading to the formation of resolvins. However, ALOX15 expression is commonly lost during human CRC. Whether loss of ALOX15 expression modulates the effects of DHA and EPA on CRC remains to be elucidated. We therefore conducted the experiments in preclinical CRC mouse models induced by Azoxymethane or Apc gene mutation to explore the hypothesis that ALOX15 expression in colonic epithelial cells regulates DHA and EPA metabolism to generate resolvins, subsequently influencing CRC outcomes. We found that 1) DHA and EPA exert differential effects on CRC, which can be further modified by factors such as their formulation (e.g., ethyl ester versus triglyceride); 2) targeted transgenic expression of ALOX15 in the intestines of mice (referred to as ALOX15-Gut mice) markedly augmented the production of resolvins and concurrently suppressed CRC; 3) the predominant products from the expressed ALOX15 enzymatic activity were identified as 17-HDHA and resolvin D5; and 4) the effects ALOX15 on increasing resolvin generation and suppressing CRC were consistent across various promoters used to drive ALOX15 transgenic expression in mice. These findings collectively underscore the profound importance of ALOX15 intestinal expression as a host-related factor in resolvin generation from EPA and DHA, which subsequently contributes to the suppression of CRC.
Citation Format: Xiangsheng Zuo, Yoshiyuki Kiyasu, Yi Liu, Micheline Moussalli, Bo Wei, Peiying Yang, Imad Shureiqi. 15-lipoxygenase-1 modulation of colonic resolvin production to suppress colorectal carcinogenesis [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 2182.
Abstract 2194: Association of metabolic syndrome conditions with risk of second primary cancer of any organ in breast cancer survivors
Authors: Mukherjee Amrita , Gu Zheng , Chen Lie Hong , Potosky Arnold L. , Haque Reina 
Published: March 2024

Abstract
Purpose: Breast cancer survivors are at increased risk of developing second primary cancers; however, factors attributing to increased risk of second primary cancer in breast cancer survivors are under-studied. We evaluated the association of metabolic syndrome conditions with second primary cancer of any organ in breast cancer survivors.
Methods: In this retrospective cohort study, we included 37,222 patients diagnosed with breast cancer between 2008-2020 at Kaiser Permanente Southern California (KPSC), an integrated healthcare system. We extracted data on cancer-related variables, sociodemographic and clinical variables from KPSC’s cancer registry and electronic health records. Among the metabolic conditions, we identified diabetes, hypertension, and dyslipidemia using ICD-10 diagnosis codes at or 1-year prior to breast cancer diagnosis; obesity was based on body mass index (BMI≥30kg/m2). We included metabolic syndrome as a categorical variable: 0, 1-2, and 3+ metabolic conditions. We followed patients electronically from breast cancer diagnosis until patients developed second primary cancer of any organ, died, disenrolled from the health plan, or reached study’s end (12/31/2021), whichever occurred first. Proportional hazards regression was used to report association [HR (95%CI)] between metabolic conditions and any second primary cancer.
Results: During a median (IQR) follow-up of 5.17 (2.75-8.58) years, 1701 (4.6%) patients developed any second primary cancer. More than half (53.1%) of the breast cancer survivors had 1-2 metabolic conditions at baseline; 19.4% had 3+ metabolic conditions, and the rest 27.5% did not have any metabolic condition. Hypertension was the most common metabolic condition (45.5%), followed by obesity (38.9%), dyslipidemia (36.5%), and diabetes (19.0%). Survivors with 0 and 1-2 metabolic conditions were 35% and 19% less likely to develop any second primary cancer than survivors with 3+ metabolic conditions, respectively [crude HR (95%CI): 0.65 (0.57-0.75) and 0.81 (0.72-0.91), respectively]. Reduced risk in survivors with 1-2 metabolic conditions persisted adjusting for age, race and ethnicity, breast cancer diagnosis year, breast tumor SEER summary stage, breast tumor estrogen-progesterone status, smoking status, and breast tumor treatment [adjusted HR (95%CI): 0.87 (0.77-0.99)].
Conclusion: Risk of second primary cancer of any organ was elevated in breast cancer survivors with three or more metabolic conditions.
Citation Format: Amrita Mukherjee, Zheng Gu, Lie Hong Chen, Arnold L. Potosky, Reina Haque. Association of metabolic syndrome conditions with risk of second primary cancer of any organ in breast cancer survivors [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 2194.
Abstract 2214: Impacts of habitual and recent alcohol intake on gut microbiome diversity and composition among Black Americans
Authors: Liu Lili , Nguyen Sang , Cai Qiuyin , Shrubsole Martha , Zheng Wei , Yu Danxia 
Published: March 2024

Abstract
Background: Alcohol intake can alter the gut microbiome, which may play a role in the development of cancer and other chronic diseases. However, there have been limited population-based studies investigating the associations of habitual and recent alcohol intake with the gut microbiome, particularly among Black Americans.
Methods: We investigated the association of alcohol intake with the gut microbiome among 538 Black American participants of the Southern Community Cohort Study (150 men and 388 women). Habitual and recent alcohol intake was assessed at cohort baseline (2002-2009) and stool collection (2018-2021), respectively. DNA was extracted from fecal samples for gut microbiome profiling using shotgun metagenomic sequencing. Generalized linear models were employed to evaluate the associations between alcohol intake and gut microbiome diversity and composition, with adjustments for sociodemographic characteristics, other lifestyle factors, and comorbidities. False discovery rate (FDR)&lt;0.1 was considered statistically significant.
Results: The mean age at enrollment was 53.2 ± 7.7 years, with a mean interval of 13.8 years (range: 9.0-18.1 years) between baseline and stool collection. Neither habitual nor recent alcohol intake was associated with microbiome diversity indices, and recent alcohol intake was not associated with microbial taxa abundance either. However, habitual alcohol intake, both total amount and subtypes, showed significant associations with microbial taxa abundance primarily in men, including Actinobacteria, Proteobacteria, Firmicutes, and classes Bacilli and Clostridia within these phyla (all FDR&lt;0.1). Specifically, total alcohol and red wine intakes were inversely associated with genus MGYG-HGUT-02719 in class Clostridia; beer consumption was inversely associated with genus Anaerostipes; white wine intake showed negative associations with order RF32 and genus Eubacterium and a positive association with genus Paenibacillus. Most of these associations remained significant after adjusting for BMI and history of cardiometabolic diseases or cancer.
Conclusion: We identified gut microbiome taxa associated with habitual alcohol intake among Black American men, including several with anti- or pro-gastrointestinal-cancer properties. However, the magnitudes of these associations were generally small. Further research is needed to determine if these bacteria play a mediating or modifying role in alcohol-disease relationships.
Citation Format: Lili Liu, Sang Nguyen, Qiuyin Cai, Martha Shrubsole, Wei Zheng, Danxia Yu. Impacts of habitual and recent alcohol intake on gut microbiome diversity and composition among Black Americans [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 2214.
Abstract 2248: Diminished survival in patients with pancreatic ductal adenocarcinoma is linked with residence in redlined neighborhoods
Authors: Vudatha Vignesh , Freudenberger Devon , Liu Christopher , Fernandez Leopoldo , Trevino Jose 
Published: March 2024

Abstract
Redlining refers to the practice of classifying neighborhoods with racial minorities and low-income residents as “hazardous” for investors. This discriminatory practice by the Home Owners’ Loan Corporation (HOLC) has been shown to impact patient cancer incidence and outcomes in breast, lung, cervical, and colorectal cancers. In this study, we evaluate the impact of HOLC status on pancreatic ductal adenocarcinoma (PDAC) outcomes in Virginia. The Virginia Department of Health Cancer Registry was queried for adult patients diagnosed with pancreatic ductal adenocarcinoma from 2009-2018. The HOLC grade (A: best, B: still desirable, C: definitely declining, D: hazardous) of each patient’s address was determined using the University of Richmond Inequality map. Patient demographics, treatment, and survival data were compared by HOLC Grade via descriptive statistics, bivariate and multivariate analysis. 394 patients were identified (A: 24 (6.1%), B: 54 (13.7%), C: 198 (50.3%), D: 118 (29.9%)). There was no association between patient age, sex, insurance status, receipt of therapy, or smoking history and HOLC status. Patient race was significantly associated with HOLC status with more Black patients living in areas with worse HOLC grades compared to White patients (p&lt;0.001). Survival analysis demonstrated that lack of surgery and chemotherapy (p&lt;0.0001), metastatic disease (p&lt;0.0001), and residential status in areas of HOLC grade D (p=0.012) were associated with worse survival. Based on Cox regression analysis, patients who lived in areas with HOLC grade B (adjusted HR 0.70; CI 0.49-0.98) and C (adjusted HR 0.74; CI 0.58-0.95) had improved survival compared to those living in areas with HOLC grade D. Additionally, age greater than 65, metastatic disease, and lack of treatment were associated with worse survival. Residence in a redlined neighborhoods can play a significant role in pancreatic ductal adenocarcinoma outcomes. Location in a “hazardous” area in Virginia is associated with worse survival in PDAC patients. Disparities in socioeconomics, housing, education, and food accessibility in these areas likely play a role in shaping these outcomes. Future studies are warranted to further investigate this disparity in care.
Citation Format: Vignesh Vudatha, Devon Freudenberger, Christopher Liu, Leopoldo Fernandez, Jose Trevino. Diminished survival in patients with pancreatic ductal adenocarcinoma is linked with residence in redlined neighborhoods [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 2248.
Abstract 2298: Optimization of high-volume cell free DNA extraction and end-to-end automation for TSO 500 ctDNA library prep
Authors: Prasad Nripesh , Rock Rachel , Beatty Rebecca , Robinson Melanie , Wildman Dineen , Sykes Michael , Umylny Boris , Halsey Thomas 
Published: March 2024

Abstract
Liquid biopsy such as plasma, has emerged as one of the most valuable sample types for profiling circulating tumor DNA (ctDNA) for screening, response to treatment, and monitoring relapse in oncology patients. Due to the diffuse nature of ctDNA however, both extraction and library preparation must be optimized for the efficient downstream next-generation sequencing (NGS) application. We initially addressed the optimization of quality and quantity of cfDNA recovery from healthy and various oncology patients by evaluating QIAsymphony DSP Circulating DNA Kit and Apostle MiniMax cfDNA isolation kits. Overall, the cfDNA yields from Apostle MiniMax kit were approximately 12X higher. We then optimized high-volume automated cfDNA extraction from 1ml, 3ml and 6ml plasma samples using the Biomek i7 for Apostle MiniMax kit. Colorectal, Gastric and Ovarian cancer gave the highest yield of cfDNA whereas, Esophageal, Lung and Kidney cancers were the lowest cfDNA yielding samples. We then analyzed ctDNA from plasma from healthy donors, colorectal, kidney, Breast, and endometrial cancer patients along with Oncospan and Seraseq ctDNA mutation mix (5-0.5% AF) to evaluate the mutation detection efficacy, repeatability, and reproducibility by targeted NGS using TSO 500ctDNA assay ay 10ng, 20ng, and 30ng inputs. For library preparation batches of 48 samples were prepared using a fully automated processes for the library prep, Hybridization capture and post capture enrichment on the Beckman i5 robot. Libraries were sequenced on NovaSeq 6000 at 600M Paired-end depth. This method demonstrates an overall concordance of inter-run and intra-run accuracy of variant detection to be 90% demonstrating that this method run as described produces highly repeatable and reproducible variant detection to sub-1% allele frequencies. The inter-run, lot-to-lot, and operator-to-operator variability was ≥99%. Down-sample analysis demonstrated high levels of assay performance with sample inputs of 30 ng with ≥96% sample passing Illumina cut-off metrics at 150M PE read depth as compared to Illumina recommended 420M PE reads. Taken together, we provide a high-volume automated solution for cfDNA extraction from plasma samples, additionally these data demonstrate a robust, reproducible, and highly accurate targeted DNA sequencing method that can be used for low allele frequency variant detection in cfDNA.
Citation Format: Nripesh Prasad, Rachel Rock, Rebecca Beatty, Melanie Robinson, Dineen Wildman, Michael Sykes, Boris Umylny, Thomas Halsey. Optimization of high-volume cell free DNA extraction and end-to-end automation for TSO 500 ctDNA library prep [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 2298.
Abstract 230: Deep learning embedding-based segmentation for morphological analysis in organoids
Authors: Sureshkumar Akash , Bisht Shilpa , Easwaran Hariharan 
Published: March 2024

Abstract
Background: The organoid model is a useful tool for modeling the cellular microenvironment of the organ from which they are derived. Organoids recapitulate the self-organization of heterogenous cell types and the microenvironment. Quantifying the morphological features of organoids can provide valuable insights into cellular organizational defects and growth characteristics, which can facilitate drug discovery. Measurement of these characteristics in live organoids can be performed quickly and easily directly in culture using widefield microscopy. The current state-of-the-art method to detect and identify the shape of individual organoids in brightfield images uses the U-Net Convolutional Neural Network (CNN) with a watershed transform to label pixels. However, this method yields jagged shape proposals and cannot detect overlapping regions. We propose the use of an embedding-based segmentation network based on the Branched ERF-Net to solve these issues.
Methods: Organoids were established from the proximal colon of BrafV600E heterozygous mice, and 50 phase-contrast images of the organoids were acquired at 2.5x and 4x magnification. Organoids present in acquired images were labeled manually. The network was trained on this collection of manually labeled images and validated on a separate validation dataset.
Results: The network accurately labels organoids. Overlapping organoids are segmented correctly and shape proposals are smoother. Detection of overlapping organoids with the Branched ERF-Net architecture yields an accurate organoid count, verified against manual counting. Smoother shape proposals also enable the use of convexity defects to measure organoid budding.
Conclusions: Deep-learning analysis of widefield images enables the rapid assessment of morphological characteristics, such as size, count, and budding, which are key to understanding proliferation and differentiation changes. The modified Branched ERF-Net architecture we propose for organoid segmentation is a robust and versatile method to quantify organoid morphology.
Citation Format: Akash Sureshkumar, Shilpa Bisht, Hariharan Easwaran. Deep learning embedding-based segmentation for morphological analysis in organoids [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 230.
Abstract 2351: Genomics annotation and interpretation in somatic oncology using structured data from a clinical knowledgebase
Authors: Li Jian , Niu Lili , krishna Shuba , Kinshuk Fnu , Jones Martin , Hernandez Carlos , Clark Michael , Balladares Sandra 
Published: March 2024

Abstract
Accurate and comprehensive interpretation of genomic variants has become a bottleneck in clinical sequencing applications due to the accelerating precision oncology and biomedical information explosion. This motivated us to build Ephesus, a framework enabling curation of predictive, prognostic and diagnostic evidence for clinical biomarkers in cancers. Currently Ephesus is the primary content source for Roche navify Mutation Profiler (nMP).
The Ephesus’ data model ensures adherence to best practices in clinical genomic content curation. Variant classification follows the AMP guidelines for somatic variant interpretation. Variant interpretations are derived from international regulatory approvals and clinical practice guidelines (FDA, EMA, TGA, eVIQ, etc.) and recommendations (NCCN, ESMO). The data model is mapped to a set of relational tables. To enforce data integrity and validity, strategies such as data normalization based on standard nomenclatural ontologies, a submit-review-approval workflow, and biological constraints are adopted. Ephesus is deployed as a web application used by curators inside and outside Roche. The UI allows users to conduct edits, filtering, sorting and bulk operations on entities by attributes. In order to minimize manual effort and maximize content coverage, inference rules are applied before ingesting into nMP.
Currently Ephesus is developed for data collection, browsing and summarizing primary entities such as biomarkers, evidence items, genes, variants, variant groups, and drugs. The content from the 2023-Aug snapshot contains 11,596 directly curated biomarker profiles (including biomarker combinations), and 6M+ expanded profiles for 41 major cancer types. To evaluate the clinical reporting value of the curated knowledge, ~160k real cancer patient samples of the AACR GENIE project were queried on Ephesus. Compared with three other major knowledgebases, Ephesus/NMP is observed showing the highest performance.
Table 1. Percentage of patients or biomarkers with at least one interpretation from each knowledgebase CGI (2022-10-17) CIVIC(2023-09-01) ClinVar(2023-09-09) NMP(2023-08-11) AACR-Genie-v14.0 Total patient % with any interpretation 25% (40,545) 46% (73,835) 81% (130,882) 89% (142,905) 160,965 biomarker % (including combos) with any interpretation 0.03% (256) 0.06% (526) 13.26% (122,424) 73.79% (681,128) 923,093
Citation Format: Jian Li, Lili Niu, Shuba krishna, Fnu Kinshuk, Martin Jones, Carlos Hernandez, Michael Clark, Sandra Balladares. Genomics annotation and interpretation in somatic oncology using structured data from a clinical knowledgebase [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 2351.
Abstract 2361: A PD1-antibody-attenuated IL-2 fusion protein activates immune cells leading to the inhibition of tumor growth in ex vivo human 3D tumor models
Authors: Satchi-Fainaro Ronit , Avramoff Opal , Katyal Anshika , Yeini Eilam , Krinsky Anne , Liubomirski Yulia , Dulberg Shai , Tiram Galia , Kaminitz Ayelet , Gill Jason , Pedersen Jessica , Bar-On Dana , Tamir Ayala , Ayton Paul , Taura Tetsuya , Wilson David , Madi Asaf 
Published: March 2024

Abstract
IL-2 has been prescribed to effectively treat malignancies, mainly melanoma, for decades. Its use has waned in recent years due to significant toxicity and a narrow therapeutic index. To overcome the limitations of systemic administration of IL-2, we have generated a modified IL-2 (IL2Att) with specific substitutions to reduce the binding affinity with the IL-2R. The attenuated cytokine was fused to a high-affinity anti-PD1 antibody that does not block PD-1 binding with its ligands (PD-L1 and PD-L2). The resulting antibody-cytokine fusion, anti-PD1-IL2Att, allows selective delivery of IL-2 to tumor-reactive PD1+ T cells, with limited potential to activate PD1− cells. To evaluate the effect of anti-PD1-IL2Att in a human tumor microenvironment (TME), we established a unique human 3D multi-cellular cancer system. This model system includes neoplastic and somatic cells that make up the TME, further supplemented with peripheral blood mononuclear cells (PBMC). We found that the anti-PD1-IL2Att reduced tumor cell survival more effectively in several types of these 3D cancer models (melanoma, glioblastoma, ovarian and colon cancer) than standard immune checkpoint inhibitors pembrolizumab or nivolumab. Combination treatments of anti-PD1-IL2Att with either of these agents resulted in improved immune activation and tumor cell killing. Our findings suggest that tumor-targeted attenuated cytokines such as IL-2 can promote robust tumor killing while minimizing systemic toxicity.
Citation Format: Ronit Satchi-Fainaro, Opal Avramoff, Anshika Katyal, Eilam Yeini, Anne Krinsky, Yulia Liubomirski, Shai Dulberg, Galia Tiram, Ayelet Kaminitz, Jason Gill, Jessica Pedersen, Dana Bar-On, Ayala Tamir, Paul Ayton, Tetsuya Taura, David Wilson, Asaf Madi. A PD1-antibody-attenuated IL-2 fusion protein activates immune cells leading to the inhibition of tumor growth in ex vivo human 3D tumor models [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 2361.