Cancer Chemistry最新文献

{"title":"Abstract 328: Selective fluorogenic probe for rapid detection of cathepsin L activity","authors":"Kelton A. Schleyer, Ben Fetrow, P. Z. Fatland, Jun Liu, Maya Chaaban, Biwu Ma, Lina Cui","doi":"10.1158/1538-7445.AM2021-328","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-328","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81516118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract SY07-02: Gaining biologic insights into glioblastoma using proteomics","authors":"J. Barnholtz-Sloan","doi":"10.1158/1538-7445.AM2021-SY07-02","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-SY07-02","url":null,"abstract":"Glioblastoma (GBM) is the most common type of primary malignant tumor in adults and contributes disproportionately to cancer morbidity and mortality. Understanding its molecular pathogenesis is crucial for improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomics data on 99-treatment naive GBMs provided insights to GBM biology. Multiple key findings emerged that were not known from traditional genomic analyses: (1) Analysis of protein phosphorylation identified key signaling intermediates in the RTK/RAS path-way common to multiple RTK genomic alterations (PTPN11 and PLCG1), potentially offering common therapeutic targets for different oncogenic drivers in GBM. (2) Phosphoproteomics also identified potential druggable targets based on kinase-substrate pathway analysis, as well as novel phosphoprotein targets associated with the regulation of telomere length by ATRX in IDH mutants. (3) TP53 protein abundance in GBM is regulated by protein/phosphoprotein effectors (4) Four immune GBM subtypes exist, characterized by distinct immune cell population differences – Immune High and Immune Low phenotypes in GBM were driven by tumor-associated macrophage markers, and associated with distinct epigenetic modifications and histone acetylation patterns. (5) The mesenchymal subtype displays EMT signatures specific in tumor cells, distinct from infiltrating immune cells. (6) Histone H2B acetylation and immune-low GBM was driven largely by BRDs, CREBBP, and EP300. (7) Identification of key metabolic changes in IDH mutants facilitating the accumulation of onco-metabolite 2-HG were also associated with lipidomic changes. This work identifies additional therapeutic channels for GBM and novel information useful for more accurate stratification patients for effective treatment. Citation Format: Jill S. Barnholtz-Sloan. Gaining biologic insights into glioblastoma using proteomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr SY07-02.","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86624797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 294:In vitroefficacy studies to support engineered T cell therapies","authors":"Sanne Holt, Sophie C Vermond, M. Hazenoot, Rene J. McLaughlin, Marco Guadagnoli, M. Vlaming","doi":"10.1158/1538-7445.AM2021-294","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-294","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81215723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 273: A mass spectrometry survey of frequent HLA alleles successfully presenting common tumor specific mutations for immune recognition","authors":"Catherine M. Ade, Y. Qi, Sudipto Das, K. Hanada, Tapan Maity, Xu Zhang, T. Andresson, U. Guha, J. Yang","doi":"10.1158/1538-7445.AM2021-273","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-273","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78974774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 284: Design, synthesis and biological evaluation of novel water-soluble salts of the antimitotic prodrugs 4-(3-alkyl-2-oxoimidazolidin-1-yl)-N-phenylbenzenesulfonamides selectively bioactivated by cytochrome p450 1A1 in breast cancer cells","authors":"V. Ouellette, Atziri Corin Chavez Alvarez, S. Fortin","doi":"10.1158/1538-7445.AM2021-284","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-284","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82969909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 325: Nascent proteome analysis of tumor cells and their microenvironment in cultured human tumor tissues","authors":"M. Dong, Karim Aljakouch, K. Böpple, Bernd Winkler, J. Schüler, F. Essmann, H. Kopp, J. Krijgsveld, W. Aulitzky","doi":"10.1158/1538-7445.AM2021-325","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-325","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88006121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 329: Targeting an emerging oncogenic biomarker, heparanase","authors":"Lina Cui","doi":"10.1158/1538-7445.AM2021-329","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-329","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90935273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 279: Transient opening of the blood brain barrier by Tumor Treating Fields (TTFields)","authors":"C. Brami, Ellaine Salvador, A. Kessler, M. Burek, T. Voloshin, M. Giladi, R. Ernestus, M. Löhr, C. Förster, C. Hagemann","doi":"10.1158/1538-7445.AM2021-279","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-279","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"28 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91499976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 19: Proteome-wide biomarker discovery using digital MosaicNeedles","authors":"Qimin Quan, J. Ritchey, J. Wilkinson, John Geanacopoulos, Alaina Kaiser, J. Boyce","doi":"10.1158/1538-7445.AM2021-19","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-19","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"12369 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79470443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Abstract 278: Artificial intelligence accelerate drug discovery","authors":"Weidong Xie, Xiaoyan Cheng, Zhengfang Ding, R. Deng, D. Gu","doi":"10.1158/1538-7445.AM2021-278","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-278","url":null,"abstract":"Drug discovery is resource intensive, and involves typical timelines of 10-20 years and costs that range from US$0.5 billion to US$2.6 billion. Artificial intelligence (AI) has recently started to gear-up its application in various sectors of the society and the pharmaceutical industry as a frontrunner beneficiary.Artificial intelligence can accelerate drug discovery and reduce costs by facilitating the rapid screening and identification of compounds. We have developed DM-AI drug discovery platform, including convolutional neural networks, decision treealgorithm, reinforcement learning, generative adversarial networks, big data, and knowledge graphs, along with structure and ligand-based high-throughput virtual screening , for new drug discovery and development. DM-AI optimizes biological activity,toxicity,physicochemical property. We used DM-AI to discover potent inhibitors of SHP2, PIM1, DNA-PK, kinases target implicated in solid tumor and other diseases.We started to train a biological activity prediction model on a database of the given target kinase inhibitors (positive set) and non-kinase targets molecules (negative set), and then predicted the activity of existing million data sets, obtained an initial output of thousands structures. We then evaluated these structures using a pharmacophore reward model on the basis of virtual chemical spaces of kinase inhibitors in complex with target protein. To narrow our focus to a smaller set of molecules for analysis, compounds with higher score were filtered to remove patents and applications molecules, also remove molecules bearing structural alerts and reactive groups.By day 7 after target selection, We had selected dozens structures with structural diversity for experimental validation. and by day 28, they were tested for in vitro inhibitory activity in an enzymatic kinase assay, active compounds accounted for up to 65% in some target models. This illustrates the utility of our DM-AI drug discovery platform for the successful, rapid discovery of drug candidates. Citation Format: Weidong Xie, Xing Cheng, Zhengfang Ding, Riqiang Deng, Dawei Gu. Artificial intelligence accelerate drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 278.","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85813141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}