Cancer Chemistry最新文献

{"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}

{"title":"Abstract 286: Conception and preparation of new potent antimicrotubule agents","authors":"Mathieu Gagné-Boulet, Chahrazed Bouzriba, Atziri Corin Chavez Alvarez, S. Fortin","doi":"10.1158/1538-7445.AM2021-286","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-286","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85170290","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 305: ELU001, a targeted C'Dot drug conjugate (CDC) for the treatment of folate receptor alpha (FRα) overexpressing cancers","authors":"G. Adams, Kai Ma, A. Venkatesan, F. Chen, Feixuan Wu, Melik Z. Turker, Thomas C. Gardinier, Pei-Ming Chen, Vaibhav Patel, E. Bayever, Paul Rudick, Geno Germano","doi":"10.1158/1538-7445.AM2021-305","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-305","url":null,"abstract":"CDCs are novel ultra-small (6-7 nm) nanoparticle drug conjugates that have been demonstrated to be capable of faster tumor targeting and deeper tumor penetration than antibody drug conjugates in animal models. CDCs are capable of targeting tumors in the brain and pancreas that are difficult to access, while exhibiting limited exposure to normal tissues due their efficient renal elimination. CDCs are composed of a silica core, in which Cy5, a far red dye is covalently encapsulated. The silica core is covalently coated with a layer of polyethylene glycol which is then functionalized with targeting moieties and payloads. ELU001 is a CDC functionalized with ~20 molecules of the topoisomerase-1 inhibitor exatecan linked via a proteolytic cleavable linker as a payload and ~15 folic acids to provide targeting to FRα overexpressing cancers. ELU001 is rapidly internalized into FRα expressing cells and is trafficked to the lysosome where the payload is released from the CDC. ELU001 exhibits potency in the low single digit nanomolar to sub-nanomolar range against cancer cells that express 3+ (KB, IGROV-1) and 2+ (SK-OV-3, HCC827 and OVCAR-3) levels of FRα after a 6-hr exposure in a 7-day viability study. In contrast, an anti-FRα ADC based ADC mirvetuximab soravtansine exhibits lower potency (>100 nM IC50) against SK-OV-3 and HCC827 cells and 40 nM IC50 against OVCAR-3 cells. ELU001 exhibits potent efficacy against established s.c. KB human cervical tumor xenografts in immunodeficient mice with significantly better efficacy and safety than free exatecan payload. It is also effective in treating established SK-OV-3 tumors with lower (2+) FRα expression, a setting where the ADC is again less effective. IND-enabling nonclinical studies are currently underway to prepare for initiation of a first-in-human phase 1 clinical trial in subjects with FRα overexpressing cancers in the second half of 2021. Citation Format: Gregory Paul Adams, Kai Ma, Aranapakam Venkatesan, Feng Chen, Fei Wu, Melik Turker, Thomas Gardinier, Peiming Chen, Vaibhav Patel, Eliel Bayever, Paul Rudick, Geno Germano. ELU001, a targeted C9Dot drug conjugate (CDC) for the treatment of folate receptor alpha (FRα) overexpressing cancers [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 305.","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"571 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77786844","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 324: Unbiased proteomic and phosphoproteomic analysis identifies response signatures and novel susceptibilities after combined MEK and mTOR inhibition in BRAFV600Emutant glioma","authors":"Micah J. Maxwell, A. Arnold, Heather Sweeney, Ljun Chen, T. Lih, M. Schnaubelt, C. Eberhart, Jeffrey A. Rubens, Hui Zhang, D. Clark, E. Raabe","doi":"10.1158/1538-7445.AM2021-324","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-324","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79849264","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 267: Light-activated molecular nanomachines kill bladder cancer cells","authors":"S. Nagaraju, Alexis van Venrooy, P. Hensley, K. Bree, C. Ayala-Orozco, N. Brooks, D. Izhaky, J. Tour, A. Kamat","doi":"10.1158/1538-7445.AM2021-267","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-267","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79946325","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 17: Proteogenomic characterization of pancreatic ductal adenocarcinoma","authors":"Liwei Cao, Chen Huang, D. Zhou, O. Bathe, Daniel W. Chan, R. Hruban, Lisha Ding, Bing Zhang, Hui Zhang","doi":"10.1158/1538-7445.AM2021-17","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-17","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77891862","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 283: Target cell-derived, G401-CLENs for selective delivery of model therapeutics to rhabdoid tumors","authors":"Lindsay Bourdeau, Carlos Cruz, Taylor Williams","doi":"10.1158/1538-7445.AM2021-283","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-283","url":null,"abstract":"One of the rarest and most aggressive pediatric cancers to date is the malignant rhabdoid tumor (MRT), maintaining a survival rate of 16%. Considered a renal cancer, approximately 20-25 new cases are diagnosed in the USA each year, with the average age of diagnosis being about 11 months old. Conventional strategies for treating MRT are limited due to several factors including off-target associated toxicities, patient population, age, metastasis to brain tissue, and diminished survival rates. CLENs (cell membrane lipid-extracted nanoliposomes), a novel drug delivery system, was previously developed and evaluated for selective delivery of cytotoxic drug agents to breast cancer cells and compared to more conventional liposomes. The purpose of this investigation was to optimize and characterize G401-CLENs for selective targeting and delivery of model payloads to a cellular model of rhabdoid tumors. The MRT cell line (G-401 [G401] (ATCC® CRL-1441™) was cultured in McCoy9s 5A Medium (ATCC® 30-2007™), supplemented by 10% FBS. The G401 cellular lipid materials (otherwise known as lipid extracts (LE)) were derived from G401 cells. Follow up studies include the incorporation of G401-LE in liposomes to form G401-CLENs. For development, special consideration was given to distinct determinants of targeting (i.e., particle size and zeta potential) and cellular uptake by G401-CLENs. Other analyses include a comparison of delivery of model and functional siRNA (BRD9 Silencer Select Pre-designed, siRNA ID s35295, Ambion) to G401 target cells using G401-CLENs, and conventional nano-preparations in vitro. G401-LE cell membrane components were extracted from rhabdoid G401 cells. On-going physiochemical characterization studies of G401-CLENs and functional in vitro and fluorescence microscopic analyses are currently underway. Citation Format: Lindsay Bourdeau, Carlos Cruz, Taylor Williams. Target cell-derived, G401-CLENs for selective delivery of model therapeutics to rhabdoid tumors [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 283.","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"93 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78065903","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 21: LiP-MS, a machine learning-based chemoproteomic approach to identify drug targets in complex proteomes","authors":"N. Beaton, Yuehan Feng, R. Bruderer, Adam Hendricks, Ghaith M. Hamza, Eric Miele, Rick Davies, K. Beeler, Ilaria Piazza, P. Picotti, P. Castaldi, L. Reiter","doi":"10.1158/1538-7445.AM2021-21","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-21","url":null,"abstract":"","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73927834","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 299: Self-assembling peptide hydrogel for delivery and conversion of temozolomide in glioblastoma treatment","authors":"M. Pitz, Alexandra Nukovic, M. Elpers, Sarah Wilde, Angela A Alexander-Bryant","doi":"10.1158/1538-7445.AM2021-299","DOIUrl":"https://doi.org/10.1158/1538-7445.AM2021-299","url":null,"abstract":"Traditional treatment methods for glioblastoma multiforme (GBM) including resection, radiation, and chemotherapy have been largely unsuccessful, with a current 5-year survival rate of 5.6%. In this project we examine the potential of nanosized self-assembling peptide hydrogels to locally deliver and convert temozolomide (TMZ), an FDA-approved pH-sensitive prodrug, for GBM treatment. The peptide hydrogel is designed to load TMZ into the hydrophobic regions of the hydrogels, and during hydrogel degradation in vivo, convert TMZ into its active form. Hydrogel characterization, drug loading and conversion, and cellular uptake and viability are examined to determine the in vitro efficacy of this delivery method. A combination of dynamic light scattering (DLS), scanning electron microscopy (SEM), and circular dichroism (CD) are used to characterize size and structure of the hydrogels. Loading and conversion of TMZ are quantified using UV-Vis spectroscopy. Fluorescent imaging and cell viability assays are used to determine uptake and anti-cancer effects of the drug-loaded hydrogels on glioblastoma cells. Our results show high uptake in drug-resistant T98G and non-resistant LN-18 glioblastoma cell lines using several of our tunable peptide formulations. CD has shown that all peptide formulations form mostly beta-sheet and random structures during self-assembly. SEM and DLS show that peptide hydrogels formed in a water solvent are more polydisperse than hydrogels in a PBS solvent. Using a pH-meter, we have shown that as the peptides in PBS degrade, there is an increase in local pH. Additionally, TMZ conversion is observed to occur more quickly in drug-loaded hydrogels than TMZ alone. Preliminary cell viability studies have shown that unassembled peptides are not cytotoxic; some of the assembled peptide hydrogels are cytotoxic while others maintain greater than 80% viability when compared to untreated cells. Future studies for the project will include cell viability assays with the most promising peptide formulations loaded with TMZ to determine efficacy of the delivery and conversion system. Finally, this project will culminate in an in vivo study to confirm the overall anti-cancer effect of the drug-loaded peptide hydrogels in a tumor model of GBM. Acknowledgements: This research was supported in part by the National Science Foundation EPSCoR Program under NSF Award # OIA-1655740, the National Institute of Health Award # P30GM131959, and National Science Foundation9s Graduate Research Fellowship Program. Citation Format: Megan Pitz, Alexandra Nukovic, Margaret Elpers, Sarah Wilde, Angela Alexander-Bryant. Self-assembling peptide hydrogel for delivery and conversion of temozolomide in glioblastoma treatment [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 299.","PeriodicalId":9563,"journal":{"name":"Cancer Chemistry","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85243730","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}