bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 1830: Bergenin inhibits growth of human cervical cancer cells by decreasing galectin-3 and MMP-9 expression
Authors: Singh Mayank , Chauhan Ravi , Malhotra Lakshay , Gupta Ashna , Dagar Gunjan , Das Dayasagar , Uddin Shahab , Samath Ethayathulla Abdul , Macha Muzafar A. , Akil Ammira Al shabeeb , Bhat Ajaz A. 
Published: March 2024

Abstract
Cervical cancer is still the leading of cancer mortality worldwide, even after introducing a vaccine against Human papillomavirus (HPV), due to low vaccine coverage, especially in the developing world. Cervical cancer is primarily treated by Chemo/Radiotherapy, depending on the disease stage, with Carboplatin/Cisplatin-based drug regime. These drugs being non-specific, target rapidly dividing cells, including normal cells, so safer options are needed for more targeted therapy and lower off-target toxicity. Natural products offer an attractive option compared to synthetic drugs due to their well-established safety profile and capacity to target multiple oncogenic hallmarks of cancer like inflammation, angiogenesis, etc. In the current study, we investigated the effect of Bergenin (C-glycoside of 4-O-methylgallic acid), a natural polyphenol compound that is isolated from medicinal plants such as Bergenia crassifolia, Caesalpinia digyna, and Flueggea leucopyrus. Bergenin has been shown to have anti-inflammatory, anti-ulcerogenic, and wound healing properties. Still, its anticancer potential has been realized only recently. We performed a proteomic analysis of cervical carcinoma cells treated with bergenin and found it to influence multiple hallmarks of cancers, including apoptosis, angiogenesis, and tumor suppressor proteins. It was also involved in many different cellular processes unrelated to cancer, as shown by our proteomic analysis. Further analysis showed bergenin to be a potent -angiogenic agent by reducing key angiogenic proteins like Galectin 3 and MMP-9 (Matrix Metalloprotease 9) in cervical carcinoma cells at cellular level as shown by western blotting assay. Further understanding of this interaction was carried out using molecular docking analysis, which indicated MMP-9 has more affinity for Bergenin as compared to Galectin-3. Cumulatively, our data provide novel insight into the anti-angiogenic mechanism of Bergenin in cervical carcinoma cells by modulation of multiple angiogenic proteins like Galectin-3 and MMP-9 which warrant its further development as an anticancer agent in cervical cancer.
Citation Format: Mayank Singh, Ravi Chauhan, Lakshay Malhotra, Ashna Gupta, Gunjan Dagar, Dayasagar Das, Shahab Uddin, Ethayathulla Abdul Samath, Muzafar A. Macha, Ammira Al shabeeb Akil, Ajaz A. Bhat. Bergenin inhibits growth of human cervical cancer cells by decreasing galectin-3 and MMP-9 expression [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 1830.
Abstract 1835: Discovery of HSN003839, a highly potent inhibitor of ubiquitin-specific protease USP21 for cancer therapy
Authors: Liu Xiaohui , Wang Ying , Xia Dongliang , Zhang Wei , He Yan , Tian Shijie , Feng Xuerong , Yang Xia , Zhang Qi , Liu Fei , Jiang Shiyi , Hu Ran , Tang Ming , Tang Xuelin , Liu Yuqing , Yuan Weijiao , You Xuedan 
Published: March 2024

Abstract
USP21 belongs to the ubiquitin-specific protease (USP) subfamily of deubiquitinating enzymes (DUBs), which catalyze the removal of ubiquitin chain from targeted proteins. Numerous efforts over the last decade have identified a wide range of USP21 substrates and revealed the momentous and multifaceted role of USP21 in physiological and pathological states, especially in tumorigenesis, indicating that USP21 is an appealing target for the therapy of many correlative diseases. Nevertheless, progress in the development of potent USP21 inhibitors remains limited. Herein, we present the discovery of HSN003839, a highly potent and selective USP21 inhibitor with excellent anticancer activity and drug-like properties. Following screening tool compounds to identify hits and subsequent optimization, we discovered a series of compounds with strong enzymatic inhibition for USP21 with IC50 &lt; 100 nM. Among them, HSN003839 displayed low nanomolar cancer cells proliferation inhibitions and excellent ADMET properties. The mouse oral bioavailability (F) is 76.5% at 10 mg/kg. In a preliminary mouse CDX model, monotherapy of HSN003839 showed 105% tumor growth inhibition (TGI) at 30 mg/kg with no obvious body weight reduction. Further biological characterization, efficacy and toxicity studies are ongoing.
The structure of HSN003839 was not presented and will not be disclosed at the time of presentation at AACR meeting.
Citation Format: Xiaohui Liu, Ying Wang, Dongliang Xia, Wei Zhang, Yan He, Shijie Tian, Xuerong Feng, Xia Yang, Qi Zhang, Fei Liu, Shiyi Jiang, Ran Hu, Ming Tang, Xuelin Tang, Yuqing Liu, Weijiao Yuan, Xuedan You. Discovery of HSN003839, a highly potent inhibitor of ubiquitin-specific protease USP21 for cancer therapy [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 1835.
Abstract 1851: Comprehensive multi-level proteomics characterization of gastric cancer
Authors: Wang Yuefan ,   Clinical Proteomic Tumor Analysis Consortium (CPTAC)
Published: March 2024

Abstract
Gastric cancer is the leading cause of cancer related deaths worldwide, accounts for over 700,000 deaths each year. There is an urgent need for advancing therapeutic strategies for patients with gastric cancer. Addressing this need, the Clinical Proteomics Tumor Analysis Consortium (CPTAC) has conducted a comprehensive characterization of gastric cancer, aiming to elucidate the complex molecular mechanisms driving this cancer type, and to discover underlying cancer biology that will form the basis for developing new approaches for precision medicine. This comprehensive study includes an integrated multi-level proteomics analysis of 165 surgically resected gastric cancer and 41 normal adjacent tissues. We employed a multi-faceted approach, analyzing the proteome, phosphoproteome and glycoproteome, along with other protein modifications including ubiquitination, acetylation, and tyrosine phosphorylation. Furthermore, we extended our research to include 74 pairs of early-onset gastric cancer and normal adjacent tissues, analyzed using a proteomic approach. We can totally identify more than 12,000 protein groups with median identification of 9750 protein groups per sample. This expansive dataset helps constructing a comprehensive multi-omics atlas of gastric cancer, offering a deep understanding into the disease's molecular landscape. The depth of this study was enhanced by incorporating multi-level proteomics data across 6 tiers, facilitating an unprecedented multi-level proteomics analysis. Our integrated approach allows us to illustrate the changes in protein expression, protein modifications, signaling pathways, and protein networks during tumorigeneis. This analysis uncovers potential therapeutic targets for personalized treatments. Overall, our study provides a multi-omics atlas for gastric cancer, a profound insight into gastric cancer biology, contributing significantly to the understanding of its pathogenesis. It could pave the way for precise treatments for gastric cancer, underscoring the potential of multi-level proteomics analyses in advancing personalized medicine.
Citation Format: Yuefan Wang, Clinical Proteomic Tumor Analysis Consortium (CPTAC). Comprehensive multi-level proteomics characterization of gastric cancer [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 1851.
Abstract 1868: Target-dependent considerations for the design of bispecific T-cell engagers
Authors: Mai Matt , Tonikian Raffi , Bergqvist Peter , Amash Alaa , Blamey Nathalie , Conaghan Gabrielle , de Puyraimond Valentine , Farber Patrick , Goodman Allison , Lee Ahn , Scortecci Jessica Fernandes , Crichlow Cindy-Lee , Khodabandehloo Akram , Pinsky Tova , Caldwell Kate , Patterson Jessica , Pouliot Philippe , Tortora Davide , Urtatiz Oscar , Xiang Ping , Yu Irene , Brown Kirstin , Bullock Kelly , Chee Andrea , Masterman Stephanie K. , Aubuchon Neil , Devorkin Lindsay , Barnhart Bryan C. , Jacobs Tim 
Published: March 2024

Abstract
In this study, we present data from four T-cell engager (TCE) programs in which we leveraged our highly diverse CD3-binding antibodies to generate functional bispecifics for each tumor target. By aggregating tumor-cell killing and cytokine data across four tumor targets with different properties and target expression levels, we have gained novel insights into target-specific considerations for the development of CD3 TCEs. TCEs recapitulate a synapse between T cells and target cells. T cell function downstream of this synapse is determined by the complex interplay between multiple independent factors. These include properties of the CD3- and tumor-binding arms, such as binding kinetics and epitope, as well as target-dependent factors such as cell type and target density. We used our diverse CD3 antibodies to engineer bispecific TCEs against four solid tumor targets: PSMA, B7-H4, 5T4, and the peptide-MHC target MAGE-A4. For each target, we engineered and characterized hundreds of bispecific molecules using high-throughput assays, including T-cell dependent tumor-cell killing, cytokine release, developability assessments, and structural studies. Here, we compare data from across these programs to elucidate the impact of target-dependent parameters on TCE function. These data provide important insights for the selection of appropriate TCE targets and efficient design of bispecific antibodies with high therapeutic potential.
Citation Format: Matt Mai, Raffi Tonikian, Peter Bergqvist, Alaa Amash, Nathalie Blamey, Gabrielle Conaghan, Valentine de Puyraimond, Patrick Farber, Allison Goodman, Ahn Lee, Jessica Fernandes Scortecci, Cindy-Lee Crichlow, Akram Khodabandehloo, Tova Pinsky, Kate Caldwell, Jessica Patterson, Philippe Pouliot, Davide Tortora, Oscar Urtatiz, Ping Xiang, Irene Yu, Kirstin Brown, Kelly Bullock, Andrea Chee, Stephanie K. Masterman, Neil Aubuchon, Lindsay Devorkin, Bryan C. Barnhart, Tim Jacobs. Target-dependent considerations for the design of bispecific T-cell engagers [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 1868.
Abstract 2111: Impact of HER2 Expression on trastuzumab deruxtecan(T-DXd) efficacy
Authors: Chen Wanyi , Drago Joshua , Gupta Avantika , Liu Bo , Chandarlapaty Sarat 
Published: March 2024

Abstract
Background: T-DXd is an FDA-approved anti-HER2 Antibody Drug Conjugate (ADC), which has shown clinical efficacy in breast cancers with either overexpression or low-level expression of HER2. The benefit of T-DXd across the spectrum of HER2 expression has called into question the relevance of HER2 expression level as relevant parameter for T-DXd sensitivity. We sought to experimentally address the relevance of HER2 expression level upon the degree of T-DXd response.
Methods: A series of isogenic models was generated that expressed different levels of surface HER2 using a doxycycline-inducible promoter. These were analyzed for impact of differential expression level upon T-DXd internalization and drug response. Human breast cancer samples were analyzed for HER2 expression levels and association with clinical response to T-DXd under an IRB approved protocol.
Results: Induction of different levels of HER2 at specified doxycycline concentrations was verified in multiple models using immunoblotting and FACS. These different levels appeared to correspond to clinical breast cancer immunohistochemistry (IHC) scoring levels to 0, 1+, 2+, and 3+. The models were analyzed for T-DXd response and showed increasing levels of HER2 led to increase lysosomal uptake of T-DXd (p&lt;0.0001). Moreover, elevation of HER2 levels led to lower concentrations of T-DXd needed to suppress tumor growth. Analyses of the effects of increasing levels of HER2 upon xenograft response to T-DXd are ongoing. Finally, retrospective analyses of a cohort of 50 breast cancer patients treated with T-DXd revealed that higher levels of HER2 corresponded to longer time on treatment (time to progression).
Conclusion: We observe a consistent relationship between elevated expression of HER2 and breast cancer response to T-DXd. The findings highlight the relevance of HER2 expression level as a biomarker of T-DXd response and support the potential value of therapeutic strategies that can induce HER2 surface expression levels to enhance response.
Citation Format: Wanyi Chen, Joshua Drago, Avantika Gupta, Bo Liu, Sarat Chandarlapaty. Impact of HER2 Expression on trastuzumab deruxtecan(T-DXd) efficacy [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 2111.
Abstract 2232: Association between sleep characteristics and cancer survival: Findings from the UK Biobank study
Authors: Che Jiajing , Lv Jiali , Pan Keyu , Sun Tiantian , Cao Chao , Li Shengxu , Zhang Tao , Xue Fuzhong , Yang Lin 
Published: March 2024

Abstract
Background
Sleep characteristics have been associated with patient outcomes after cancer. We aimed to appraise the causal relationship of chronotype, sleep duration, insomnia, and snoring with cancer survival.
Methods
This large prospective cohort study enrolled 38350 cancer survivors aged ≥40 years from the UK Biobank between 2004 and 2022. Habitual sleep characteristics were obtained from the self-reported baseline questionnaire, including chronotype, sleep duration, insomnia, and snoring. Cox proportional hazards regression models were applied to evaluate the association between sleep characteristics and cancer survival, then one sample Mendelian randomization (MR) analyses were further used to validate these causal relationships. In particular, restricted cubic splines (RCS) and non-linear MR analyses were applied to assess the possible nonlinear association between sleep duration and cancer survival.
Results
Among 38350 study participants (mean [SD] age, 59.8 [7.3] years; 24150 [63.0%] males; 35534 [92.7%] White individuals), 12671 (33.1%) reported evening preference chronotype; 9050 (23.6%) reported short and 3773 (9.8%) reported long sleep duration;12274 (32.0%) reported snoring; and 30426 (79.4%) reported experiencing insomnia sometimes or usually. During up to 18 years of follow-up, 6274 deaths occurred. Multivariable regression models showed that evening preference (HR = 1.09, 95% CI: 1.03 to 1.15), short (HR = 1.14, 95% CI: 1.07 to 1.21) and long sleep duration (HR = 1.37, 95% CI: 1.28 to 1.48), insomnia (HR = 1.14, 95% CI: 1.09 to 1.21) and snoring (HR = 0.83, 95% CI: 0.78 to 0.87) were associated with death among pan to cancer survivors. Restricted cubic splines suggested nonlinear associations between sleep duration and death after cancer (nonlinear P &lt; 0.001). In the one-sample MR, genetically predicted sleep duration (HR = 0.71, 95% CI: 0.56 to 0.90) and snoring (HR = 1.18, 95% CI: 1.05 to 1.34) demonstrated a reversed cancer survival pattern compared to multivariable regressions. A nonlinear U-shape association between sleep duration and cancer survival was observed in restricted cubic spline analyses (P &lt; 0.001) but not evident when evaluating by nonlinear MR (P &gt; 0.05).
Conclusions
Evening preference chronotype, insomnia, snoring, and short sleep duration are likely to be causally associated with a higher risk of death among cancer survivors, whilst long sleep duration does not appear to be a causal factor.
Citation Format: Jiajing Che, Jiali Lv, Keyu Pan, Tiantian Sun, Chao Cao, Shengxu Li, Tao Zhang, Fuzhong Xue, Lin Yang. Association between sleep characteristics and cancer survival: Findings from the UK Biobank study [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 2232.
Abstract 2327: MADVAR: An algorithm that improves the relevance of computational biology output, while reducing compute time and space requirements
Authors: Silberberg Gilad , Ritchie Michael 
Published: March 2024

Abstract
High-throughput methods implemented in biology research produce a continuously growing array of data input that are used to produce data output with an increasing abundance of features. While growth in the volume and diversity of data input can be highly valuable for studying biological systems, it presents the challenge of managing enormous quantities of features, many of which are not relevant to the specific research question being asked. This excess data input burdens storage and computation of downstream clustering and machine learning tasks. A common approach used to manage this data input relies on filters applied to the features by their variance across the sample set, while applying random cutoffs. Our proprietary algorithm (“MADVAR”) enables the prioritization of variable features from high-throughput continuous data, by automatically finding an optimal cutoff for the distribution of the data. Based on the right-skew nature of biological data distribution, MADVAR finds and excludes the "0 variance peak" using the median of the distributions and the median absolute deviation (MAD). MADVAR enables a faster analysis with a reduced memory requirement, and dramatically improves clustering results with minimal loss of relevant features.
Citation Format: Gilad Silberberg, Michael Ritchie. MADVAR: An algorithm that improves the relevance of computational biology output, while reducing compute time and space requirements [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 2327.
Abstract 2333: Methylation based phylogeny and timing in cancer
Authors: Guteneva Nataliya , Lichter Eliezer , Leshchiner Ignaty 
Published: March 2024

Abstract
Knowing the chronological sequence of genetic alterations during cancer development and progression is crucial for understanding the process of transformation of normal tissue into malignant tumors. This can offer insights into the etiology and intrinsic cellular mechanisms of the process, presenting opportunities for early detection and treatment of initial disease stages, as well as highlight key events as potential therapeutic. Current methods of establishing progression histories of cancers rely either on direct sequencing of premalignant lesions, which are seldom available for tumors or on computational inference timing methods capable of reconstructing the history from primary tumor data. These methods require genome or exome sequencing data from a relatively large cohort of tumors and provide limited resolution due to overall scarcity of somatic mutations. We utilize a different source of genetic information, genome methylation, that also “records” historic information about acquisition and development of mutations. Over 28 million methylated CpG sites exist in the genome with several percent of them differentially methylated (DMS) between tissue types and tumor vs adjacent normal tissue. The several orders of magnitude higher density of distinctly methylated sites provides unprecedented resolution, needs fewer tumors, can be merged with driver mutation data and co-analyzed with “methylation clock” information that allows to establish early development, phylogeny and progression at unprecedented resolution. We developed methods for whole genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS) and Oxford Nanopore Technologies native methylation sequencing data. Somatic DMS sites have distinct properties from somatic point mutations, can appear and disappear in the process of tumor evolution and development allowing for unique configuration of methylated islands. Our tools perform single sample and cohort level “timing”, multi-sample phylogeny reconstruction and cancer population reconstruction by integrating methylation and mutation information from the same sample. These new methods will significantly contribute to our understanding of cancer initiation and progression at a resolution not available previously.
Citation Format: Nataliya Guteneva, Eliezer Lichter, Ignaty Leshchiner. Methylation based phylogeny and timing in cancer [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 2333.
Abstract 2608: Hu2G10 antibody-drug conjugates selectively target cleaved-activated Trop-2 in cancer cells and show therapeutic efficacy against multiple human cancers
Authors: Alberti Saverio , Trerotola Marco , Moschella Antonino , Giavazzi Raffaella , Guerra Emanuela 
Published: March 2024

Abstract
Trop-2 is a transmembrane calcium signal transducer which activates growth-signaling networks that converge on Akt, ERK, Cyclin D1, NFkB (1). Trop-2 cleavage by ADAM10 was shown to be an activator switch for induction of cancer growth and metastatic diffusion (2). We devised a strategy to obtain monoclonal antibodies (mAb) capable of recognizing ADAM10-exposed sites in cancer cells. We succeeded at obtaining mAb that efficiently bound Trop-2 expressing cancer cells and were able to inhibit cell growth in vitro. We humanized the 2G10 mAb as the IgG1/k Hu2G10 antibody. Hu2G10 binds cancer-specific, cleaved/activated Trop-2 with Kd 10−12 M. On the other hand, it binds uncleaved/wtTrop-2 in normal cells with Kd 3.16 × 10−8 M, thus promising an unprecedented therapeutic index in patients. Antibody-drug conjugates (ADC) of Hu2G10 were obtained using stable linkers, multiple conjugation chemistries and different payloads, among them topoisomerase I inhibitors, bleomycin, RNA polymerase inhibitor, MMAE and calicheamicin. Hu2G10-ADC selectively killed Trop-2-expressing cells in vitro. Dose-response curves were obtained for the BxPC-3 pancreatic cancer, DU-145 prostate cancer, HT29 colon cancer cell lines and KM12SM/Trop2 colon cancer transfectants, reaching EC50 values as low as 5.05 × 10−10 M. Hu2G10-ADC drove high anticancer effectiveness on cell- and patient-derived xenografts from colon, pancreas, prostate and ovarian cancer. Effectiveness followed a gradient of payload potency, with correspondingly high therapeutic indexes. Consistently, neither detectable toxic effects nor weight loss were observed in any subgroup of treated xenotransplant-bearing mice. Taken together these findings candidate anti-Trop-2 Hu2G10-ADC for best-in-class anticancer therapy. (1) E. Guerra et al., The Trop-2 signaling network in cancer growth. Oncogene 32, 1594-1600 (2013).(2) M. Trerotola et al., Trop-2 cleavage by ADAM10 is an activator switch for cancer growth and metastasis. Neoplasia 23, 415-428 (2021).
Citation Format: Saverio Alberti, Marco Trerotola, Antonino Moschella, Raffaella Giavazzi, Emanuela Guerra. Hu2G10 antibody-drug conjugates selectively target cleaved-activated Trop-2 in cancer cells and show therapeutic efficacy against multiple human cancers [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 2608.