Catherine B Whitney, Nicole C Beller, Brian D Fries, Arbil Lopez, Amanda B Hummon
{"title":"Longitudinal Proteomic Changes in HCT 116 Colon Cancer Spheroids During Growth.","authors":"Catherine B Whitney, Nicole C Beller, Brian D Fries, Arbil Lopez, Amanda B Hummon","doi":"10.1021/acs.jproteome.5c00207","DOIUrl":null,"url":null,"abstract":"<p><p>The FDA Modernization Act 2.0 permits data from advanced microphysiological systems, such as spheroids, to be used as a testbed for drug candidates entering phase 1 clinical trials. Despite their increasing adoption, spheroids of varying growth durations are often used interchangeably as disease models. While transcriptomic studies have been employed to monitor spheroids over time, proteomics has primarily been used to validate their utility as model systems and assess drug responses rather than for longitudinal studies. Here, we apply data independent acquisition with gas phase fractionation (DIA-GPF) proteomics to investigate temporal changes in HCT 116 spheroids every 2 days throughout 18 days of growth, identifying 6,835 proteins across all samples. Differential expression analysis reveals that day 2 spheroids more closely resemble monolayer cells than spheroids cultured for extended periods. Gene ontology (GO) term analysis of differentially expressed proteins indicates that relative to monolayer cells DNA replication is downregulated, while glycolysis is upregulated during spheroid maturation. Parallel reaction monitoring (PRM) experiments targeting thymidylate synthase and fructose-bisphosphate aldolase C validate the initial proteomic findings and corroborate the trends observed in the GO term analysis. These results highlight the importance of growth duration when spheroids are used as a model for avascular tumors.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":"4181-4190"},"PeriodicalIF":3.6000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Proteome Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jproteome.5c00207","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/7 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
The FDA Modernization Act 2.0 permits data from advanced microphysiological systems, such as spheroids, to be used as a testbed for drug candidates entering phase 1 clinical trials. Despite their increasing adoption, spheroids of varying growth durations are often used interchangeably as disease models. While transcriptomic studies have been employed to monitor spheroids over time, proteomics has primarily been used to validate their utility as model systems and assess drug responses rather than for longitudinal studies. Here, we apply data independent acquisition with gas phase fractionation (DIA-GPF) proteomics to investigate temporal changes in HCT 116 spheroids every 2 days throughout 18 days of growth, identifying 6,835 proteins across all samples. Differential expression analysis reveals that day 2 spheroids more closely resemble monolayer cells than spheroids cultured for extended periods. Gene ontology (GO) term analysis of differentially expressed proteins indicates that relative to monolayer cells DNA replication is downregulated, while glycolysis is upregulated during spheroid maturation. Parallel reaction monitoring (PRM) experiments targeting thymidylate synthase and fructose-bisphosphate aldolase C validate the initial proteomic findings and corroborate the trends observed in the GO term analysis. These results highlight the importance of growth duration when spheroids are used as a model for avascular tumors.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".